hh.sePublications
Change search
Refine search result
123 1 - 50 of 147
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Akhtar, Naeem
    Halmstad University, School of Business, Engineering and Science.
    Analysis of Simris Hybrid Energy System Design and Working and Checking the Effects of Using High Capacity Factor Wind Turbine2019Independent thesis Advanced level (degree of Master (One Year)), 40 credits / 60 HE creditsStudent thesis
    Abstract [en]

    The world is entering the future where integration of renewable energy sources within the power grid will play an important role when facing the challenge of reducing global warming. The intermittent generation characteristics associate with renewable energy sources can be handled by the implementation of microgrids. A Microgrid is a group of energy source (e.g. wind, solar etc) that are located in the same local area that can operate independently in the event of electricity outage and can also be connected to the national grid in case of energy demand exceeds than the energy produced in the same local area. The implementation of microgrid in an electrical distribution system must be well planned to avoid problems. The EU has set high goals to reduce the non-renewable energy sources by 2030. EU has started some local energy systems (microgrids) and Simris is a part of it.

    This study is about a microgrid project at Simris in the south-east of Sweden. The village of Simris has 140 households supplied by a wind turbine of rated power 500kW and a solar power plant of 440 kW rated power. This project is run by E. ON within the framework and collaboration of Interflux, in which several network operators within the EU participate to investigate flexibility options in local energy systems. 

    The aim of this study is to find different scenarios in which the Simris microgrid can be run in islanded-mode. Four different scenarios were investigated, and simulation was done in MATLab. After simulation the results were discussed in the “Analysis and Results” section and the size of the wind turbine, the solar park (PV)and the battery were suggested for each of the scenarios. A short calculation was also included between the installation cost of the suggested wind turbine and the needed battery size. The cost of battery is much higher than the cost of wind turbine, so its beneficial for the economy of the microgrid to have a wind turbine of 1000 kW rated power and battery size 35 MWh rather than using the same old wind turbine of 469 kW rated power and upgrade the battery to 462 MWh. 

    Download full text (pdf)
    fulltext
  • 2.
    AL Darabseh, Mutaz
    et al.
    Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL).
    Nasar, Nazia Rumana
    Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL).
    An Exploratory Study on the Post-Acquisition Process of Technological Acquisition – a case study of HMS2020Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Although M&A’s have the greatest probability of failure in organizations, the major reasons for this outcome is the integration process. M&As have been a popular strategy for accessing new markets, introducing new products, expanding their knowledge base, and enhancing competitive advantage. In this study, we explore a case of technology acquisition, and we propose a theoretical framework based on literature that identifies phases in post-acquisition process. The process involves three stages: knowledge absorption, operational phase and commercial phase that is explored and evaluated with the empirical data of the case study. Then, thematic analysis was utilized in this study to identify common themes related to the role of acquisition. The related functions and benefits were grouped under acquisition roles. Since the case study was a successful acquisition, it was easy to figure out the roles and dimensions of integration from it. Both the methods contribute in addressing, the necessary phases that need to be organized with integration and deriving different functionalities to achieve common goals. Finally, we present a discussion and bring out the relationships that emerged from this study from different themes and have been mapped to stages in the post-acquisition process, resulting in outcomes from each role. Thus, this study puts an emphasis on the range of factors that create value from successful technological acquisition and conclude as post-acquisition process with integration elements is the initial pivotal position for the consequences.

    Download full text (pdf)
    fulltext
  • 3.
    Alabdallah, Abdallah
    Halmstad University, School of Information Technology.
    Machine Learning Survival Models: Performance and Explainability2023Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Survival analysis is an essential statistics and machine learning field in various critical applications like medical research and predictive maintenance. In these domains understanding models' predictions is paramount. While machine learning techniques are increasingly applied to enhance the predictive performance of survival models, they simultaneously sacrifice transparency and explainability. 

    Survival models, in contrast to regular machine learning models, predict functions rather than point estimates like regression and classification models. This creates a challenge regarding explaining such models using the known off-the-shelf machine learning explanation techniques, like Shapley Values, Counterfactual examples, and others.   

    Censoring is also a major issue in survival analysis where the target time variable is not fully observed for all subjects. Moreover, in predictive maintenance settings, recorded events do not always map to actual failures, where some components could be replaced because it is considered faulty or about to fail in the future based on an expert's opinion. Censoring and noisy labels create problems in terms of modeling and evaluation that require to be addressed during the development and evaluation of the survival models.

    Considering the challenges in survival modeling and the differences from regular machine learning models, this thesis aims to bridge this gap by facilitating the use of machine learning explanation methods to produce plausible and actionable explanations for survival models. It also aims to enhance survival modeling and evaluation revealing a better insight into the differences among the compared survival models.

    In this thesis, we propose two methods for explaining survival models which rely on discovering survival patterns in the model's predictions that group the studied subjects into significantly different survival groups. Each pattern reflects a specific survival behavior common to all the subjects in their respective group. We utilize these patterns to explain the predictions of the studied model in two ways. In the first, we employ a classification proxy model that can capture the relationship between the descriptive features of subjects and the learned survival patterns. Explaining such a proxy model using Shapley Values provides insights into the feature attribution of belonging to a specific survival pattern. In the second method, we addressed the "what if?" question by generating plausible and actionable counterfactual examples that would change the predicted pattern of the studied subject. Such counterfactual examples provide insights into actionable changes required to enhance the survivability of subjects.

    We also propose a variational-inference-based generative model for estimating the time-to-event distribution. The model relies on a regression-based loss function with the ability to handle censored cases. It also relies on sampling for estimating the conditional probability of event times. Moreover, we propose a decomposition of the C-index into a weighted harmonic average of two quantities, the concordance among the observed events and the concordance between observed and censored cases. These two quantities, weighted by a factor representing the balance between the two, can reveal differences between survival models previously unseen using only the total Concordance index. This can give insight into the performances of different models and their relation to the characteristics of the studied data.

    Finally, as part of enhancing survival modeling, we propose an algorithm that can correct erroneous event labels in predictive maintenance time-to-event data. we adopt an expectation-maximization-like approach utilizing a genetic algorithm to find better labels that would maximize the survival model's performance. Over iteration, the algorithm builds confidence about events' assignments which improves the search in the following iterations until convergence.

    We performed experiments on real and synthetic data showing that our proposed methods enhance the performance in survival modeling and can reveal the underlying factors contributing to the explainability of survival models' behavior and performance.

    Download full text (pdf)
    fulltext
  • 4.
    Ali Hamad, Rebeen
    Halmstad University, School of Information Technology.
    Towards Reliable, Stable and Fast Learning for Smart Home Activity Recognition2022Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    The current population age grows increasingly in industrialized societies and calls for more intelligent tools to monitor human activities.  The aims of these intelligent tools are often to support senior people in their homes, to keep track of their daily activities, and to early detect potential health problems to facilitate a long and independent life.  The recent advancements of smart environments using miniaturized sensors and wireless communications have facilitated unobtrusively human activity recognition.  

    Human activity recognition has been an active field of research due to its broad applications in different areas such as healthcare and smart home monitoring. This thesis project develops work on machine learning systems to improve the understanding of human activity patterns in smart home environments. One of the contributions of this research is to process and share information across multiple smart homes to reduce the learning time, reduce the need and effort to recollect the training data, as well as increase the accuracy for applications such as activity recognition. To achieve that, several contributions are presented to pave the way to transfer knowledge among smart homes that includes the following studies. Firstly, a method to align manifolds is proposed to facilitate transfer learning. Secondly, we propose a method to further improve the performance of activity recognition over the existing methods. Moreover, we explore imbalanced class problems in human activity recognition and propose a method to handle imbalanced human activities. The summary of these studies are provided below. 

    In our work, it is hypothesized that aligning learned low-dimensional  manifolds from disparate datasets could be used to transfer knowledge between different but related datasets. The t-distributed Stochastic Neighbor Embedding(t-SNE) is used to project the high-dimensional input dataset into low-dimensional manifolds. However, since t-SNE is a stochastic algorithm and  there is a large variance of t-SNE maps, a thorough analysis of the stability is required before applying  Transfer learning.  In response to this, an extension to Local Procrustes Analysis called Normalized Local Procrustes Analysis (NLPA) is proposed to non-linearly align manifolds by using locally linear mappings to test the stability of t-SNE low-dimensional manifolds. Experiments show that the disparity from using NLPA to align low-dimensional manifolds decreases by order of magnitude compared to the disparity obtained by Procrustes Analysis (PA). NLPA outperforms PA and provides much better alignments for the low-dimensional manifolds. This indicates that t-SNE low-dimensional manifolds are locally stable, which is the part of the contribution in this thesis.

    Human activity recognition in smart homes shows satisfying recognition results using existing methods. Often these methods process sensor readings that precede the evaluation time (where the decision is made) to evaluate and deliver real-time human activity recognition. However, there are several critical situations, such as diagnosing people with dementia where "preceding sensor activations" are not always sufficient to accurately recognize the resident's daily activities in each evaluated time. To improve performance, we propose a method that delays the recognition process to include some sensor activations that occur after the point in time where the decision needs to be made. For this, the proposed method uses multiple incremental fuzzy temporal windows to extract features from both preceding and some oncoming sensor activations. The proposed method is evaluated with two temporal deep learning models: one-dimensional convolutional neural network (1D CNN) and long short-term memory (LSTM) on a binary sensor dataset of real daily living activities.  The experimental evaluation shows that the proposed method achieves significantly better results than the previous state-of-the-art. 

    Further, one of the main problems of activity recognition in a smart home setting is that the frequency and duration of human activities are intrinsically imbalanced. The huge difference in the number of observations for the categories means that many machine learning algorithms focus on the classification of the majority examples due to their increased prior probability while ignoring or misclassifying minority examples. This thesis explores well-known class imbalance approaches (synthetic minority over-sampling technique, cost-sensitive learning and ensemble learning) applied to activity recognition data with two temporal data pre-processing for the deep learning models LSTM and 1D CNN. This thesis proposes a data level perspective combined with a temporal window technique to handle imbalanced human activities from smart homes in order to make the learning algorithms more sensitive to the minority class. The experimental results indicate that handling imbalanced human activities from the data-level outperforms algorithm level and improved the classification performance.

    Download full text (pdf)
    fulltext
  • 5.
    Almouayad Alazm, Zafer
    Halmstad University.
    Study on solar driven office cooling system2019Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Download full text (pdf)
    fulltext
  • 6.
    Altarabichi, Mohammed Ghaith
    Halmstad University, School of Information Technology.
    Evolving intelligence: Overcoming challenges for Evolutionary Deep Learning2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Deep Learning (DL) has achieved remarkable results in both academic and industrial fields over the last few years. However, DL models are often hard to design and require proper selection of features and tuning of hyper-parameters to achieve high performance. These selections are tedious for human experts and require substantial time and resources. A difficulty that encouraged a growing number of researchers to use Evolutionary Computation (EC) algorithms to optimize Deep Neural Networks (DNN); a research branch called Evolutionary Deep Learning (EDL).

    This thesis is a two-fold exploration within the domains of EDL, and more broadly Evolutionary Machine Learning (EML). The first goal is to makeEDL/EML algorithms more practical by reducing the high computational costassociated with EC methods. In particular, we have proposed methods to alleviate the computation burden using approximate models. We show that surrogate-models can speed up EC methods by three times without compromising the quality of the final solutions. Our surrogate-assisted approach allows EC methods to scale better for both, expensive learning algorithms and large datasets with over 100K instances. Our second objective is to leverage EC methods for advancing our understanding of Deep Neural Network (DNN) design. We identify a knowledge gap in DL algorithms and introduce an EC algorithm precisely designed to optimize this uncharted aspect of DL design. Our analytical focus revolves around revealing avant-garde concepts and acquiring novel insights. In our study of randomness techniques in DNN, we offer insights into the design and training of more robust and generalizable neural networks. We also propose, in another study, a novel survival regression loss function discovered based on evolutionary search.

    Download full text (pdf)
    fulltext
  • 7.
    Amos, Gideon Jojo
    Halmstad University, School of Business, Innovation and Sustainability, Centre for Innovation, Entrepreneurship and Learning Research (CIEL).
    (Investigating) MNCs' CSR-related behaviour and impacts in institutionally and culturally distant markets: African developing-countries in focus2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The overall purpose of this thesis is to explore why and how institutional distance and contextual differences influence MNCs’ CSR-related behavior in African developing-countries. In order to achieve the purpose stated above, the thesis seeks to answer the overarching research question: How do institutional distance and contextual differences influence MNCs’ CSR-related behavior in African developing countries? To answer the research question this thesis employed an interpretive methodological approach in order to increase my understanding of the CSR phenomenon in a specific contextual environment characterized by different institutional distance through different theoretical and empirical perspectives (Guba and Lincoln, 1994; Lincoln and Guba, 2000). The thesis consists of two qualitative case studies, a systematic literature review, a conceptual paper focused on analyzing distance and MNC foreign subsidiaries’ CSR-related behaviour, and a longitudinal content analysis of annual CSR reports.

    The thesis found that the most prevalent CSR themes addressed in journal articles focused on developing-countries have been social issues, followed by environmental issues as a distant second, with ethics-related issues receiving the least attention. The findings further indicate that CSR rhetoric plays a more positive and significant role than so far explored in CSR research, as it incentivises the host-communities to push for the fulfilment of their CSR expectations or CSR initiatives proposed by the mining companies. Soft’ regulations to which members of industry associations voluntarily adhere mitigate the absence of enforcement of more stringent hard regulations by the state for companies. In doing business in distant or different institutional contexts, institutional duality of MNC subsidiaries renders business activities complex and even conflicting when it comes to seeking internal and external legitimacy. This finding and the proposed model extend Hillman and Wan’s (2005) argument of the existence of ‘institutional duality’ of MNC subsidiaries. The 60-item disclosure index is in itself a contribution to research as it provides a measure of ‘disclosure quality’ in relation to the disclosures of CSR-related performance information and CSR-related governance information.

    The main theoretical contribution of the thesis is that CSR expectations in developing-countries are distinct and may be more important to know how these empirical realities are taken into account when firms with their origin in developed-countries internationalize and enter markets in developing-countries. Second, an extended model is proposed which illustrates the roles of organizational fields, institutional pressures, legitimating environments, and legitimating strategies for MNC subsidiaries’ voluntary disclosure of CSR performance information. The overall contribution of the thesis is that it deepens our understanding of the CSR phenomenon, and of the role of host-communities and MNC subsidiaries’ managers from the context of developing-countries.

    © Gideon Jojo Amos

  • 8.
    Annekanavar, Sankarshan
    Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL).
    Circular Business Model Innovation within the manufacturing industry in India: Integrated Barriers2019Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Manufacturing is found to be crucial for the globally industrialized countries whereas its impacts on environment is a concern. Competition worldwide has challenged manufacturing industries with severe economic and environmental pressures, out of which resource scarcity is the most severe. Therefore, since Circular Economy (CE) mitigates these sustainable development challenges, a need to move from the linear “take-make-use-dispose” process to a CE is generated by adopting innovative business models which are called circular business models (CBM). However, a wide gap can be seen between how CE is conceptualized in the literature and how the real life practitioners in India face barriers in realizing it. Hence, the purpose of this thesis is to explore and examine in detail, the various barriers to the adoption of CBMs and thus, creating a shift towards CE among manufacturing firms by exploring challenges faced by practioners in India from various perspectives of the company and the external actors influencing the company and triangulate the barriers found out in the findings with the barriers from the existing literature with an aim of shrinking the literature gap mentioned previously. To fulfil the aims and objectives in this thesis, an extensive literature review is conducted to accumulate information about what information already exists about Sustainable Development (SD) in developing context, Business Model Innovation (BMI) and CE with its barriers. Further, an in-depth case study is conducted on Shree Renuka Sugars Limited (SRSL), which is a sugar manufacturing company in India who practice circular economic principles by achieving resource efficiency through conversion of by-products and wastes into new forms of value. Interviews are conducted on the case company to explore the barriers from the perspectives of the company staff as well as from the perspectives of external actors who influence the company by thinking of the company as a system dependent on its surroundings. Apart from this, additional secondary data has been researched which is used to triangulate with the findings in the later part of the thesis. The findings uncover that the challenges faced by the company are complex, diverse and multidimensional. These identified challenges are clubbed under four dimensions, that is, the barriers from the government, barriers from the supply chain, barriers from financial perspective and barriers from the organizational structure and culture. It was seen that CE was practiced differently in this context than conceptualized in the literature and therefore, other conditions along with this created new barriers for the firm. Also, different opinions were found from different people who were interviewed. This thesis aimed to fill the literature gap on how CE is conceptualized in the literature and how practitioners in India face barriers. The identified barriers in Indian context although not significantly different from the ones in literature yet has tremendous impacts when applied to manufacturing scenario within India. This further leads to also conclude that while all the barriers are interconnected, meaning that they depend on each other extensively, some barriers are more crucial than the other barriers in the Indian context as compared to the literature.

  • 9.
    Aramrattana, Maytheewat
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES). The Swedish National Road and Transport Research Institute (VTI), Göteborg, Sweden.
    A Simulation-Based Safety Analysis of CACC-Enabled Highway Platooning2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Cooperative Intelligent Transport Systems (C-ITS) enable actors in the transport systems to interact and collaborate by exchanging information via wireless communication networks. There are several challenges to overcome before they can be implemented and deployed on public roads. Among the most important challenges are testing and evaluation in order to ensure the safety of C-ITS applications.

    This thesis focuses on testing and evaluation of C-ITS applications with regard to their safety using simulation. The main focus is on one C-ITS application, namely platooning, that is enabled by the Cooperative Adaptive Cruise Control (CACC) function. Therefore, this thesis considers two main topics: i) what should be modelled and simulated for testing and evaluation of C-ITS applications? and ii) how should CACC functions be evaluated in order to ensure safety?

    When C-ITS applications are deployed, we can expect traffic situations which consist of vehicles with different capabilities, in terms of automation and connectivity. We propose that involving human drivers in testing and evaluation is important in such mixed traffic situations. Considering important aspects of C-ITS including human drivers, we propose a simulation framework, which combines driving-, network-, and traffic simulators. The simulation framework has been validated by demonstrating several use cases in the scope of platooning. In particular, it is used to demonstrate and analyse the safety of platooning applications in cut-in situations, where a vehicle driven by a human driver cuts in between vehicles in platoon. To assess the situations, time-to-collision (TTC) and its extensions are used as safety indicators in the analyses.

    The simulation framework permits future C-ITS research in other fields such as human factors by involving human drivers in a C-ITS context. Results from the safety analyses show that cut-in situations are not always hazardous, and two factors that are the most highly correlated to the collisions are relative speed and distance between vehicles at the moment of cutting in. Moreover, we suggest that to solely rely on CACC functions is not sufficient to handle cut-in situations. Therefore, guidelines and standards are required to address these situations properly.

    Download full text (pdf)
    fulltext
  • 10.
    Aramrattana, Maytheewat
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES). The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    Modelling and Simulation for Evaluation of Cooperative Intelligent Transport System Functions2016Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Future vehicles are expected to be equipped with wireless communication tech- nology, that enables them to be “connected” to each others and road infras- tructures. Complementing current autonomous vehicles and automated driving systems, the wireless communication allows the vehicles to interact, cooperate, and be aware of its surroundings beyond their own sensors’ range. Such sys- tems are often referred to as Cooperative Intelligent Transport Systems (C-ITS), which aims to provide extra safety, efficiency, and sustainability to transporta- tion systems. Several C-ITS applications are under development and will require thorough testing and evaluation before their deployment in the real-world. C- ITS depend on several sub-systems, which increase their complexity, and makes them difficult to evaluate.

    Simulations are often used to evaluate many different automotive appli- cations, including C-ITS. Although they have been used extensively, simulation tools dedicated to determine all aspects of C-ITS are rare, especially human fac- tors aspects, which are often ignored. The majority of the simulation tools for C-ITS rely heavily on different combinations of network and traffic simulators. The human factors issues have been covered in only a few C-ITS simulation tools, that involve a driving simulator. Therefore, in this thesis, a C-ITS simu- lation framework that combines driving, network, and traffic simulators is pre- sented. The simulation framework is able to evaluate C-ITS applications from three perspectives; a) human driver; b) wireless communication; and c) traffic systems.

    Cooperative Adaptive Cruise Control (CACC) and its applications are cho- sen as the first set of C-ITS functions to be evaluated. Example scenarios from CACC and platoon merging applications are presented, and used as test cases for the simulation framework, as well as to elaborate potential usages of it. Moreover, approaches, results, and challenges from composing the simulation framework are presented and discussed. The results shows the usefulness of the proposed simulation framework.

    Download full text (pdf)
    fulltext
  • 11.
    Arvidsson, Jessica
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI), The Wigforss Group.
    Sysselsättning och social rättvisa: En nationell registerstudie om 12 269 unga vuxna med intellektuell funktionsnedsättning2016Doctoral thesis, comprehensive summary (Other academic)
    Abstract [sv]

    Kunskapen om övergången mellan gymnasiesärskola och arbetsliv för unga vuxna med intellektuell funktionsnedsättning är begränsad. Varken välfärds- eller forskarsamhället har kunskap om vilken typ av sysselsättning som före detta elever i den svenska gymnasieskolan har efter skoltiden.

    Huvudsyftet med denna sammanläggningsavhandling är tredelat: att (a) öka kunskapen om vilka typer av sysselsättning som personer med intellektuell funktionsnedsättning har efter avslutad gymnasiesärskola, att (b) åskådliggöra mönster och faktorer (kön, förfluten tid sedan examen, utbildningsprogram, boendekommun samt föräldrarnas födelseland och utbildningsnivå) som kan bidra till skillnader vad gäller typ av sysselsättning, samt att (c) skapa ett nationellt register som möjliggör kvantitativa analyser, longitudinella studier och utgör underlag för kvalitativa fördjupande studier av efter(sär)gymnasial sysselsättning. Avhandlingen innehåller fyra artiklar och en ramberättelse.

    Ett nationellt register, Halmstad University Register on Pupils with Intellectual Disability (HURPID) skapades utifrån information i slutbetygen från 12 269 tidigare elever i gymnasiesärskolan. Slutbetyg är allmänna handlingar som begärdes från kommunerna. HURPID samkördes med två nationella register: Longitudinell Integrationsdatabas för Sjukförsäkrings- och Arbetsmarknadsstudier (LISA) och LSS-registret som innehåller information om insatser som beviljats enligt lag (1993:387) om stöd och service till vissa funktionshindrade. Avhandlingen bygger på tvärsnittsstudier vilka ger en ögonblicksbild av den efter(sär)gymnasiala sysselsättningen under 2011 bland de personer som gått ut mellan 2001-2011. Frekvensanalyser användes för att beskriva studiepopulationens karaktäristika. Korstabeller och Pearson´s chi2-test användes för att analysera skillnader avseende typ av sysselsättning mellan olika grupper i studiepopulationen. Sambandet mellan avhandlingens beroende och oberoende variabler undersöktes med bivariata och multivariata logistiska regressionsanalyser.

    Analyserna visar att den största andelen (47%) av de unga har sin sysselsättning inom daglig verksamhet, 22,4% har ett förvärvsarbete, de flesta med någon form av lönesubvention; och 6,6% studerar. En betydande andel (24%) betecknas vara "någon annanstans" (inte i någon av de andra tre sysselsättningstyperna). Andelen unga vuxna i daglig verksamhet är lägre än förväntat och andelen som har ett förvärvsarbete är högre än förväntat. En oväntat stor andel tillhör kategorin "någon annanstans" och har inte daglig verksamhet, inte ett förvärvsarabete och studerar inte.

    Kön, typ av utbildningsprogram, hur lång tid som förflutit sedan examen, boendekommun och föräldrarnas utbildningsnivå samt geografiska härkomst är alla faktorer som påverkar vilken typ av sysselsättning som unga vuxna med intellektuell funktionsnedsättning har. Män som har gått ett nationellt program i gymnasiesärskolan och som tog examen mellan 2001-2006 är de som har störst sannolikhet för att ha ett förvärvsarbete. Personernas boendekommun har en viss oberoende effekt på typ av efter(sär)gymnasial sysselsättning och den totalt sett låga andelen flyttar i populationen antas förstärka betydelsen av vilken kommun de bor i. Unga vars föräldrar är lågutbildade har mer sannolikt ett förvärvsarbete eller tillhör kategorin "någon annanstans". De vars föräldrar är högutbildade har mer sannolikt en sysselsättning inom daglig verksamhet eller studerar (exempelvis på Komvux eller folkhögskola). De unga vars föräldrar är födda i ett utom-europeiskt land är med större sannolikhet studerande eller personer som tillhör kategorin "någon annanstans".

    Avhandlingens huvudresultat diskuteras i förhållande till ett teoretiskt ramverk om social rättvisa. Betydelsen av samhällets ansvar att främja alla medborgares möjlighet att vara och göra vad de har anledning att värdesätta betonas. Ett samhälle som främjar social rättvisa måste stödja människors möjligheter att oavsett funktionsförmåga kunna välja sysselsättning. Såväl den offentliga som den privata sektorn behöver tydligare betrakta personer med intellektuell funktionsnedsättning som en viktig resurs i samhället och på arbetsmarknaden; se dem som personer med förmågor som riskerar att döljas bakom kategorier, fördomar och föråldrade strukturer.

    Download full text (pdf)
    Sysselsättning och social rättvisa
  • 12.
    Ashfaq, Awais
    Halmstad University, School of Information Technology.
    Deep Evidential Doctor2022Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Recent years have witnessed an unparalleled surge in deep neural networks (DNNs) research, surpassing traditional machine learning (ML) and statistical methods on benchmark datasets in computer vision, audio processing and natural language processing (NLP). Much of this success can be attributed to the availability of numerous open-source datasets, advanced computational resources and algorithms. These algorithms learn multiple levels of simple to complex abstractions (or representations) of data resulting in superior performances on downstream applications. This has led to an increasing interest in reaping the potential of DNNs in real-life safety-critical domains such as autonomous driving, security systems and healthcare. Each of them comes with their own set of complexities and requirements, thereby necessitating the development of new approaches to address domain-specific problems, even if building on common foundations.

    In this thesis, we address data science related challenges involved in learning effective prediction models from structured electronic health records (EHRs). In particular, questions related to numerical representation of complex and heterogeneous clinical concepts, modelling the sequential structure of EHRs and quantifying prediction uncertainties are studied. From a clinical perspective, the question of predicting onset of adverse outcomes for individual patients is considered to enable early interventions, improve patient outcomes, curb unnecessary expenditures and expand clinical knowledge.

    This is a compilation thesis including five articles. It begins by describing a healthcare information platform that encapsulates clinical, operational and financial data of patients across all public care delivery units in Halland, Sweden. Thus, the platform overcomes the technical and legislative data-related challenges inherent to the modern era's complex and fragmented healthcare sector. The thesis presents evidence that expert clinical features are powerful predictors of adverse patient outcomes. However, they are well complemented by clinical concept embeddings; gleaned via NLP inspired language models. In particular, a novel representation learning framework (KAFE: Knowledge And Frequency adapted Embeddings) has been proposed that leverages medical knowledge schema and adversarial principles to learn high quality embeddings of both frequent and rare clinical concepts. In the context of sequential EHR modelling, benchmark experiments on cost-sensitive recurrent nets have shown significant improvements compared to non-sequential networks. In particular, an attention based hierarchical recurrent net is proposed that represents individual patients as weighted sums of ordered visits, where visits are, in turn, represented as weighted sums of unordered clinical concepts. In the context of uncertainty quantification and building trust in models, the field of deep evidential learning has been extended. In particular for multi-label tasks, simple extensions to current neural network architecture are proposed, coupled with a novel loss criterion to infer prediction uncertainties without compromising on accuracy. Moreover, a qualitative assessment of the model behaviour has also been an important part of the research articles, to analyse the correlations learned by the model in relation to established clinical science.

    Put together, we develop DEep Evidential Doctor (DEED). DEED is a generic predictive model that learns efficient representations of patients and clinical concepts from EHRs and quantifies its confidence in individual predictions. It is also equipped to infer unseen labels.

    Overall, this thesis presents a few small steps towards solving the bigger goal of artificial intelligence (AI) in healthcare. The research has consistently shown impressive prediction performance for multiple adverse outcomes. However, we believe that there are numerous emerging challenges to be addressed in order to reap the full benefits of data and AI in healthcare. For future works, we aim to extend the DEED framework to incorporate wider data modalities such as clinical notes, signals and daily lifestyle information. We will also work to equip DEED with explainability features.

    Download full text (pdf)
    fulltext
  • 13.
    Ashfaq, Awais
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Predicting clinical outcomes via machine learning on electronic health records2019Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    The rising complexity in healthcare, exacerbated by an ageing population, results in ineffective decision-making leading to detrimental effects on care quality and escalates care costs. Consequently, there is a need for smart decision support systems that can empower clinician's to make better informed care decisions. Decisions, which are not only based on general clinical knowledge and personal experience, but also rest on personalised and precise insights about future patient outcomes. A promising approach is to leverage the ongoing digitization of healthcare that generates unprecedented amounts of clinical data stored in Electronic Health Records (EHRs) and couple it with modern Machine Learning (ML) toolset for clinical decision support, and simultaneously, expand the evidence base of medicine. As promising as it sounds, assimilating complete clinical data that provides a rich perspective of the patient's health state comes with a multitude of data-science challenges that impede efficient learning of ML models. This thesis primarily focuses on learning comprehensive patient representations from EHRs. The key challenges of heterogeneity and temporality in EHR data are addressed using human-derived features appended to contextual embeddings of clinical concepts and Long-Short-Term-Memory networks, respectively. The developed models are empirically evaluated in the context of predicting adverse clinical outcomes such as mortality or hospital readmissions. We also present evidence that, surprisingly, different ML models primarily designed for non-EHR analysis (like language processing and time-series prediction) can be combined and adapted into a single framework to efficiently represent EHR data and predict patient outcomes.

    Download full text (pdf)
    Lic
  • 14.
    Augustine, Joyal
    et al.
    Halmstad University.
    Simons, Steven
    Halmstad University.
    Improving the surface finish of the rubber weight plate: Master thesis in mechanical engineering2021Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Flash is the unwanted or excessrubber material that presents on the outersurface of themolded rubber product. This will affect the surface finish; it is a cosmetic defect andit can be removed. It forms because of the leak or the excess molded rubber materialbetween the surface of the mold, typically on the parting line, (Jordan Anderson,2014). The presence of flash will reduce customer satisfaction. There are manymethods to remove the flash. The method is selected according to the degree of flashextension and the location where it occurs.The project aims to design a semi/full automated machine, which helps for having asmooth and fine surface finish of the weight plates. These plates are made up of rubberfor the ELEIKO group. The weight plates have different weights from 10 to 20 kg,but the diameter of each plate stays the same, but the thickness will be different foreach plate. The machine should be designed that removes all the excess rubber andshould smoothen the outer surface of the weight. The purpose of this work is to gainknowledge about different product development methods, respective tools, andtechniques that are used. The machine should be user- friendly, should not becomplicated, should not damage the workpiece (marks or trace of the blade), shouldnot put the employer in danger, and economically feasible.This report presents the progress of designing of the product, product development,methods, and literature study. The designed model can construct in the industry fortheir problem they are faced by the flash. The model is very simple and unique so thateveryone can perform the task without any previous experience. Material alternativeswere evaluated as well as manufacturing possibilities. The designed machine was theoffered for free as means for further research and development.

    Keywords: flashing, additive manufacturing, Ullman method, Pugh matrix, rubberweight plates, lever arm, smoothening tool.

    Download full text (pdf)
    fulltext
  • 15.
    Backman, Ellen
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI). Region Halland, Halmstad, Sverige.
    Ordinary mealtimes under extraordinary circumstances: Routines and rituals of nutrition, feeding and eating in children with a gastrostomy and their families2021Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The aim of this thesis is to explore routines and rituals related to feeding, eating, and mealtimes in families that have a child with a gastrostomy tube (G-tube), from the perspectives of healthcare professionals, the children, and their parents. The thesis is based on four empirical studies. Study I is a longitudinal, quantitative study with the aim to describe children with developmental or acquired disorders receiving a G-tube, and to compare characteristics, contacts with healthcare professionals, and longitudinal eating outcomes. Findings from Study I demonstrated that children with developmental disorders needed G-tube feeding for longer than children with acquired disorders. Children with developmental disorders were also younger at G-tube placement, and had more multidisciplinary healthcare. These findings led to the subsequent studies focused specifically on children with developmental disorders. 

    Study II applies mixed methods and explores everyday life, health care, and intervention goals during the first year following G-tube placement through the documentation in medical records. In Studies III and IV, the experiences of family mealtimes for children with a G-tube and their parents are collected through individual interviews that are analysed qualitatively. Triangulation of methods, participants, researchers, and data across the four studies is applied to search for confirmation between findings, as well as to identify areas of discrepancy. Ecocultural theory, the WHO framework ICF, and the concept of participation form the conceptual framework of the thesis. Taken together, findings from the studies describe how the main experiences of feeding, eating, and mealtime relate to specific impairments of the child, the collective value attached to family mealtimes, and the parental responsibility to harmonise competing interests and conflicts among family members and/or healthcare professionals. 

    This thesis extends previous research by focusing on the ecocultural context of the child in combination with a dimensional understanding of health. The findings shed light on measures taken by the families themselves to adjust to and handle their daily lives, as well as spell out areas where more support is needed. Furthermore, this thesis suggests that an expanded focus on children’s participation in everyday mealtimes, and in the healthcare follow-up of G-tube feeding, is important in enhancing intervention outcomes.

    Download full text (pdf)
    fulltext
    Download full text (pdf)
    Errata
  • 16.
    Badhan, Kaniz Fatema
    Halmstad University, School of Business, Engineering and Science. Halmstad University.
    A Study on ISO 14001:2015 Requirementsand How to Fulfill Them in an Organization: Life Cycle Perspective in Product Design and Development2020Independent thesis Advanced level (degree of Master (One Year)), 40 credits / 60 HE creditsStudent thesis
    Abstract [en]

    ISO 14001 is an International Standard based on the concept that better environmental performancecan be achieved when environmental aspects are systematically identified and managed. Nowadays,manufacturing organizations are emphasizing more on product sustainability and the prevention ofenvironmental problems. Environmental aspect consideration opens an opportunity to enjoy theeffects of better environmental performances in terms of competitive advantage. The revised standardISO 14001:2015 was created by market requirements to get better environmental performance,ensuring top management involvement, a more specific life cycle analysis, better risk-based thinking,and a better communication strategy. The standard applies to any organization, regardless of size,type, and nature but does not specify environmental performance criteria or explicit rules concerningpreventive actions (Haggar et al., 2019) (ISO 14001, 2015). ISO 14001 (2015) emphasis more on theevaluation of risks and opportunities, also in reference to significant environmental aspects andcompliance obligations (Tüv Nord, 2015). The new ISO 14001:2015 certified organizations shoulddetermine the negative and positive environmental aspects while designing a product considering lifecycle thinking. Life cycle thinking could be a better approach to figure out more suitable solutionsfor sustainable development (Milazzo P. et al., 2017).This study has presented the output of an extensive literature review, survey results, and informationfrom the interview session to understand how the ISO 14001:2015 certified organizations areconsidering the environmental aspects in their life cycle thinking. The organizations monitoringstrategies and the risks and opportunities results from the implementation of ISO 14001:2015 (EMS)during the design and development phase are also analyzed. The study also prevails whether themanufacturing organizations consider design for environment (DFE) as a way of getting betterenvironmental performance by their products or not and how they are approaching towardssustainable development and circular economy.

    Download full text (pdf)
    fulltext
  • 17.
    Berggren, Eva
    Halmstad University, School of Business, Innovation and Sustainability, Centre for Innovation, Entrepreneurship and Learning Research (CIEL), Knowledge Entrepreneurship and Enterprise Research (KEEN).
    Students in Academic Entrepreneurship: Entrepreneurship Education and Key Actors Facilitating Student Start-ups in the University Context2021Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The ongoing discussion about academic research not being sufficiently commercialized has overlooked the individual actors in the university context, not least students as potential entrepreneurs. The purpose of this thesis is to enhance our understanding of student entrepreneurs by exploring how entrepreneurship education and key actors in the university context facilitate the formation of student start-ups. Two overall research questions are in focus; i) How does entrepreneurship education at university facilitate start-up formation among students? ii) How and why do key actors in the university context facilitate the formation of student start-ups? These questions are answered by three sub-studies, presented in the five published and appended papers. The data were collected through postal questionnaires as well as interviews in the context of three universities, namely Halmstad University, Chalmers University of Technology and the University of Gothenburg.

    This thesis makes several contributions. Firstly, it shows that entrepreneurship education at university facilitates start-ups by enabling knowledge spillovers from research to students willing to take on the entrepreneurial role, the so-called missing link in academic entrepreneurship. Secondly, it also demonstrates that entrepreneurship education contributes to the development of long-term entrepreneurial capital, which facilitates future start-ups. Thirdly, entrepreneurship education facilitates start-ups by connecting key actors with different roles; students were found to be present, prepared and persistent entrepreneurs, alumni to be resource-providers and role models, while researchers became enablers with a need for utilization of their research. The revealed reasons for these interconnected key actors to enable student start-ups were; i) students are looking for a career, have start-ups skills from entrepreneurship education and access to role-models and business opportunities in the university context; ii) alumni are anxious to pass on their business experience and maintain the mutually beneficial ties to the university; iii) researchers are reluctant to change their established career but with a strong need for utilization of their research enables students to make commercial use of it.

    Download full text (pdf)
    fulltext
  • 18.
    Bergquist, Elin
    Halmstad University, School of Education, Humanities and Social Science.
    Hey girl, I just wanted to reach out with this amazing business opportunity.: A study on language used to attract people into a Multi-Level Marketing business.2021Independent thesis Advanced level (professional degree), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    This study examines the language used by independent distributors in Multi-Level Marketing companies (MLMs) when attempting to recruit new people into the business. Social media posts and messages were read and analysed to identify themes or categories within the data, which each detailed a means used by distributors to recruit new distributors or customers. The findings were then analysed in relation to Steven Hassan's BITE-model of authoritarian control; Robert Cialdini's principles of inlfuence; Roman Jakobson's pragmatic functions; and Roland Barthes thery of cultural. The findings showed that the most frequent tactic used by the distributors was different forms of emotional tactics. The distributors also used signifiers to evoke cultural myths regarding how one should live one's life and how their MLM could help people achieve that lifestyle. Lastly, questions were frequently used in order to prolong communication between distributor and prospective recruit or customer. 

    Download full text (pdf)
    fulltext
  • 19. Berkestam Drysén, Viktoria
    A Study of Child-led Learning: Learning a Second Language Through Natural Progression.2022Independent thesis Basic level (degree of Bachelor), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The theories on ways to learn a second language have varied throughout history and existing research is often dependent on school settings to discover the best methods to motivate students. Removing the aspect of school from the equation, why would someone choose to learn English as a second language when the choice is independent of structures such as curriculum? What methods would the student choose to rely on for their learning if it is up to them? Through semi-structured interviews with natural learning, home educated, Swedish speaking students, this qualitative study examines the process of learning English as a second language. The findings suggest that learning English as a second language occurs as a natural progression rather than the goal-oriented learning in a class setting. The conclusion of the study is that learning occurs as a side effect from focusing on natural interests rather than structured methods. 

    Download full text (pdf)
    fulltext
  • 20.
    Bhatti, Harrison John
    Halmstad University, School of Business, Innovation and Sustainability. VTI, Swedish National Road and Transport Research Institute, Gothenburg, Sweden.
    Sustainable Electromobility: A System Approach to Transformation of Transportation2023Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Electrification of transportation is generally analyzed from a technical aspect. Whereas the technical aspect is merely one of the main aspects of transforming the transportation system from fossil-based to electric. The other significant aspects, such as political, societal, and economic, are mostly neglected that can empower the transformation processes. This thesis aims to explore, analyze, and develop knowledge that leads to an understanding of identifying the key actors and their symbiotic relationships and dependencies in transforming the energy and transportation system from fossil-based to renewable and fossil fuel-powered vehicles to electric. 

    The research was explorative and categorized into two studies. The Study – I focuses on the technological development that leads toward transforming from the old fossil-based analog electricity generation and distribution system to the new digitalized renewable system.This study further explores the impact of these disruptive technologies on the market and society, and the challenges hindering the implementation and adoption of the new energysystem. Study – II focuses on developing new knowledge and understanding by integrating technological, political, societal, and economic aspects into one model and named it a 'multidimensional readiness index model.' This model can serve as an analytical tool and provide a broader perspective for exploring, analyzing, evaluating, and determining the countries' positions in transforming the transformation system. The model has been applied to eight countries, two from Asia (China and India) and Australia and five from Europe (Germany, Norway, Sweden, Slovenia, and the UK). The kappa synthesizes the exploration of the papers. Additionally, the system approach is applied to explore and understand the symbiotic relationship in the new ecosystem among the key actors and stakeholders and their significant role in transforming the transportation system from fossil-based to electric. 

    The main conclusion is that the countries with a higher symbiotic relationship among the key actors achieved a higher level of readiness in transforming the transportation system. In contrast, other countries with a low symbiotic relationship among the key actors are slowly catching up or even far behind in transforming the transportation system towards electrification. 

     The analysis shows that a higher level of readiness in transforming the transportation system is achieved by the countries where their government took firm decisions to integrate their associated manufacturing industries and society into their national agenda. China is one example of these countries leading globally in manufacturing and sales of electric vehicles. Norway does not manufacture electric vehicles. However, Norway is leading globally with the highest market share of electric vehicles. The Norwegian government uses its economic means to compensate for the price differentiation with its policies and provide subsidies and rebates to the buyers of electric vehicles. In countries that have adopted a fragmented approach toward transportation electrification and are waiting for the industries to take further initiatives, slow progress can be seen in those countries, such as Germany, Sweden, and the UK. Countries where the government showed less interest in electrification, even though they have introduced some policies, are still far behind in transforming the transportation system, such as India, Australia, and Slovenia. 

    The key message is that the political role is decisive in transforming the energy and transportation system. It is a revolutionary change requiring enormous investment and political support to stabilize the industry and the market to compensate as the new actors enter the manufacturing industry and threaten the old firms. The new products enter the market and threaten the old businesses. The new political policies and regulations are required to balance the price differences between electric and fossil fuel vehicles by providing subsidies or rebates to encourage society to adopt change. Thus, energy and transportation industries are intertwined and operate under the umbrella of government rules and regulations. Without firm political support, the entire transformation from a fossil-based to an electric system is difficult to achieve. 

    Download full text (pdf)
    Sustainable Electromobility
  • 21.
    Blomqvist, Marjut
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI), Health and Nursing.
    Health among people with psychotic disorders and effects of an individualized lifestyle intervention to promote health2020Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The overall aim of the thesis was to increase knowledge of health among people with psychotic disorders such as schizophrenia and other long-term psychotic conditions. The aim was also to investigate health effects, in terms of clinical health outcomes and self-reported questionnaires, of atwo-year individualized lifestyle intervention implemented in psychiatric outpatient services involving cooperation with the municipal social psychiatry services. The motivation for the study was to generate new knowledge in order to be able to promote health in people with psychotic disorders and to improve the care and support provided for this target group. The thesis consists of four studies. A quantitative study (Study I), was conducted using a cross-sectional design to investigate the prevalence of overweight, obesity, risk of cardiovascular disease (CVD) and the relationships between self-rated salutogenic health, sense of coherence, CVD risk, and body mass index among people with psychoticdisorders (n=57). The study was conducted in four psychiatric outpatient services; questionnaires were completed by the participants and clinical health measurements were collected by the participant’s contact nurse at the psychiatric outpatient services. The participants showed a moderate/high risk of CVD, the mean for BMI was 31.9 (59.6% were obese) and 31.6% were overweight. The results did not reveal any relationships between the subjective and objective measuresof health indicating the need for both subjective and objective assessments of health in psychiatric care. In a qualitative study (Study II), data were collected with semi-structured interviews (n=16) andanalyzed with qualitative content analysis. The interviews resulted in an overall theme “Being regarded as a whole human being by self and others”, which showed the multidimensional nature of health and the issues that enable healthy living among people with severe mental illness. Three categories emerged: (i) everyday structure (ii), motivating life events and (iii) support from significant others. The results indicate that a person with severe mental illness needs to be encountered as a wholeperson if healthy living is to be enabled. In a quasi-experimental study (Study III), the potential effects of participation in the two-year lifestyle intervention (intervention group n=54 and control group (n=13) were investigated. The data were collected at baseline, after 12 months and after 24 months using the self-reported questionnaire the Salutogenic Health Indicator Scale (SHIS), the Hopkins Symptom Checklist (HSCL-25) and the National Public Health Survey. Measures of clinical healthoutcomes were conducted by the participant’s contact nurse at the psychiatric outpatient services. Multilevel modeling was used to test differences in changes over time. Significant changes were foundin physical activity, HbA1c and waist circumference after participation in individualized lifestyle intervention. The relationship between changes in physical activity, levels of salutogenic health and glycated hemoglobin (Hb1Ac) were investigated (n=54) in Study IV. The data were collected atbaseline, after 12 months and after 24 months using the self-reported questionnaires Salutogenic Health Indicator Scale (SHIS) and National Public Health Survey. Within-person changes in physical activity between baseline and at the end of the twenty-four-month intervention were calculated. Selfreported increased physical activity was positively associated with self-rated salutogenic health and negatively associated with level of HbA1c after participation in the intervention. The thesis shows that a well-founded assessment of general health needs must consider both the individual's subjective experiences and objective measurements in order to form a solid foundation for dialogue and shareddecision-making about essential care services. The results also show that it is possible to stimulate healthy behavioral changes with a two-year individualized lifestyle intervention and bring both subjectively and objectively measured health benefits for people with psychotic disorders. The importance of nurses in psychiatric care applying a holistic approach and integrating lifestyle interventions into daily person-centered psychiatric care in collaboration with other healthcare providers to facilitate changes towards a healthy lifestyle in persons with psychotic illness is emphasized in the thesis.

    Download full text (pdf)
    fulltext
  • 22.
    Boualleg, Abdelmadjid
    Halmstad University, School of Business, Engineering and Science.
    Investigations on post-processing of 3D printed thermoplastic polyurethane (TPU) surface2019Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Abstract

    The reduction of product development cycle time is a major concern in industries to remain competitive in the marketplace. Among various manufacturing technologies, 3D printing technology or also known as additive manufacturing (AM), has shown excellent potential to reduce both the cycle time and cost of the product due to its lower consumption of energy and material usage compared to conventional manufacturing. Fused deposition modeling (FDM) is one of the most popular additive manufacturing technologies for various engineering applications which has the ability to build functional parts having complex geometrical shapes in reasonable build time and can use less expensive equipment and cheaper material. However, the quality of parts produced by FDM has some challenges such as poor surface quality.  

    The focus of this study is improving the surface quality produced by Fused Deposition Modeling. The investigations include 3D printing study samples with optimum parameter settings and post-processing the sample’s surfaces by laser ablation. Taguchi’s design of the experiment is employed to identify the optimum settings of laser ablation the FDM surfaces. Laser power, laser speed and pulse per inch (PPI) are the laser settings considered in the study. Characterization of the samples are done using Dino-lite USB camera images and GFM Mikro-CAD fringe projection microscope is used to measure the surface roughness of the samples.

    Areal surface parameters are used to characterize and compare the surfaces of as printed and laser ablated. It is observed that the effect of laser ablation varies with respect to surfaces printed at different angles and laser-ablated with different settings. The surface roughness of laser-ablated surfaces is found to be lower than as-printed FDM surfaces.

    Download full text (pdf)
    fulltext
  • 23.
    Bumroongkit, Suphalak
    Halmstad University, School of Health and Welfare.
    Gender Equality and Intergenerational Mobility: Cross-country Results2023Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Nowadays, intergenerational mobility and gender equality have captured widespread attention. This study aims to examine the relationship between the two to provide policy insights that benefit both polarized issues. This study reviewed the existing literature and formulated hypotheses that early childhood development has long-lasting impacts on adults' outcomes and is a decisive factor in determining social mobility in adulthood. Gender equality policies play huge roles in this period, mitigating adverse effects from childhood and providing opportunities for disadvantaged children in early childhood development. This study tests the hypotheses with multiple regression and performs sensitivity analysis with an alternative proxy. The result is that public spending on childcare, female labour market participation, and child poverty are statistically significant with social mobility, while weeks of maternity leave and poverty rates of single-earner families are not.

    Download full text (pdf)
    fulltext
  • 24.
    Böhm, Annette
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Delay-sensitive wireless communication for cooperative driving applications2013Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Cooperative driving holds the potential to considerably improve the level of safety and efficiency on our roads. Recent advances in in-vehicle sensing and wireless communication technology have paved the way for the development of cooperative traffic safety applications based on the exchange of data between vehicles (or between vehicles and road side units) over a wireless link. The access to up-to-date status information from surrounding vehicles is vital to most cooperative driving applications. Other applications rely on the fast dissemination of warning messages in case a hazardous event or certain situation is detected. Both message types put high requirements on timeliness and reliability of the underlying communication protocols.

    The recently adopted European profile of IEEE 802.11p defines two message types,periodic beacons for basic status exchange and event-triggered hazard warnings, both operating at pre-defined send rates and sharing a common control channel. The IEEE 802.11p Medium Access Control (MAC) scheme is a random access protocol that doesnot offer deterministic real-time support, i.e. no guarantee that a packet is granted access to the channel before its deadline can be given. It has been shown that a high number of channel access requests, either due to a high number of communicating vehicles or highdata volumes produced by these vehicles, cannot be supported by the IEEE 802.11p MAC protocol, as it may result in dropped packets and unbounded delays.

    The goal of the work presented in this thesis has therefore been to enhance IEEE 802.11p without altering the standard such that it better supports the timing and reliability requirements of traffic safety applications and provides context-aware andefficient use of the available communication resources in a vehicular network. The proposed solutions are mapped to the specific demands of a set of cooperative driving scenarios (featuring infrastructure-based and infrastructure-free use cases, densely and sparsely trafficked roads, very high and more relaxed timing requirements) and evaluated either analytically, by computer simulation or by measurements and compared to the results produced by the unaltered IEEE 802.11p standard.

    As an alternative to the random MAC method of IEEE 802.11p, a centralized solution isproposed for application scenarios where either a road side unit or a suitable dedicated vehicle is present long enough to take the coordinating role. A random access phase forevent-driven data traffic is interleaved with a collision-free phase where timely channel access of periodic delay-sensitive data is scheduled. The ratio of the two phases isdynamically adapted to the current data traffic load and specific application requirements. This centralized MAC solution is mapped on two cooperative driving applications: merge assistance at highway entrances and platooning of trucks. Further,the effect of a context-aware choice of parameters like send rate or priority settings based on a vehicle’s position or role in the safety application is studied with the goal to reduce the overall number of packets in the network or, alternatively, use the available resources more efficiently. Examples include position-based priorities for the merge assistance use case, context-aware send rate adaptation of status updates in anovertaking warning application targeting sparsely-trafficked rural roads and an efficient dissemination strategy for warning messages within a platoon.

    It can be concluded that IEEE 802.11p as is does not provide sufficient support for the specific timing and reliability requirements imposed by the exchange of safety-criticalreal-time data for cooperative driving applications. While the proper, context-awarechoice of parameters, concerning send rate or priority level, within the limits of the standard, can lead to improved packet inter-arrival rates and reduced end-to-end delays,the added benefits from integrating MAC solutions with real-time support into the standard are obvious and needs to be investigated further.

    Download full text (pdf)
    Delay-Sensitive Wireless Communication for Cooperative Driving Applications
  • 25.
    Calikus, Ece
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Self-Monitoring using Joint Human-Machine Learning: Algorithms and Applications2020Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    The ability to diagnose deviations and predict faults effectively is an important task in various industrial domains for minimizing costs and productivity loss and also conserving environmental resources. However, the majority of the efforts for diagnostics are still carried out by human experts in a time-consuming and expensive manner. Automated data-driven solutions are needed for continuous monitoring of complex systems over time. On the other hand, domain expertise plays a significant role in developing, evaluating, and improving diagnostics and monitoring functions. Therefore, automatically derived solutions must be able to interact with domain experts by taking advantage of available a priori knowledge and by incorporating their feedback into the learning process.

    This thesis and appended papers tackle the problem of generating a real-world self-monitoring system for continuous monitoring of machines and operations by developing algorithms that can learn data streams and their relations over time and detect anomalies using joint-human machine learning. Throughout this thesis, we have described a number of different approaches, each designed for the needs of a self-monitoring system, and have composed these methods into a coherent framework. More specifically, we presented a two-layer meta-framework, in which the first layer was concerned with learning appropriate data representations and detectinganomalies in an unsupervised fashion, and the second layer aimed at interactively exploiting available expert knowledge in a joint human-machine learning fashion.

    Furthermore, district heating has been the focus of this thesis as the application domain with the goal of automatically detecting faults and anomalies by comparing heat demands among different groups of customers. We applied and enriched different methods on this domain, which then contributed to the development and improvement of the meta-framework. The contributions that result from the studies included in this work can be summarized into four categories: (1) exploring different data representations that are suitable for the self-monitoring task based on data characteristics and domain knowledge, (2) discovering patterns and groups in data that describe normal behavior of the monitored system/systems, (3) implementing methods to successfully discriminate anomalies from the normal behavior, and (4) incorporating domain knowledge and expert feedback into self-monitoring.

    Download full text (pdf)
    fulltext
  • 26.
    Calikus, Ece
    Halmstad University, School of Information Technology.
    Together We Learn More: Algorithms and Applications for User-Centric Anomaly Detection2022Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Anomaly detection is the problem of identifying data points or patterns that do not conform to normal behavior. Anomalies in data often correspond to important and actionable information such as frauds in financial applications, faults in production units, intrusions in computer systems, and serious diseases in patient records. One of the fundamental challenges of anomaly detection is that the exact notion of anomaly is subjective and varies greatly in different applications and domains. This makes distinguishing anomalies that match with the end-user's expectations from other observations difficult. As a result, anomaly detectors produce many false alarms that do not correspond to semantically meaningful anomalies for the analyst. 

    Humans can help, in different ways, to bridge this gap between detected anomalies and ''anomalies-of-interest'': by giving clues on features more likely to reveal interesting anomalies or providing feedback to separate them from irrelevant ones. However, it is not realistic to assume a human to easily provide feedback without explaining why the algorithm classifies a certain sample as an anomaly. Interpretability of results is crucial for an analyst to be able to investigate the candidate anomaly and decide whether it is actually interesting or not. 

    In this thesis, we take a step forward to improve the practical use of anomaly detection in real-life by leveraging human-algorithm collaboration. This thesis and appended papers study the problem of formulating and implementing algorithms for user-centric anomaly detection-- a setting in which people analyze, interpret, and learn from the detector's results, as well as provide domain knowledge or feedback. Throughout this thesis, we have described a number of diverse approaches, each addressing different challenges and needs of user-centric anomaly detection in the real world, and combined these methods into a coherent framework. By conducting different studies, this thesis finds that a comprehensive approach incorporating human knowledge and providing interpretable results can lead to more effective and practical anomaly detection and more successful real-world applications. The major contributions that result from the studies included in this work and led the above conclusion can be summarized into five categories: (1) exploring different data representations that are suitable for anomaly detection based on data characteristics and domain knowledge, (2) discovering patterns and groups in data that describe normal behavior in the current application, (3) implementing a generic and extensible framework enabling use-case-specific detectors suitable for different scenarios, (4) incorporating domain knowledge and expert feedback into anomaly detection, and (5) producing interpretable detection results that support end-users in understanding and validating the anomalies. 

    Download full text (pdf)
    fulltext
  • 27.
    Carpatorea, Iulian
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Methods to quantify and qualify truck driver performance2017Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Fuel consumption is a major economical component of vehicles, particularly for heavy-duty vehicles. It is dependent on many factors, such as driver and environment, and control over some factors is present, e.g. route, and we can try to optimize others, e.g. driver. The driver is responsible for around 30% of the operational cost for the fleet operator and is therefore important to have efficient drivers as they also inuence fuel consumption which is another major cost, amounting to around 40% of vehicle operation. The difference between good and bad drivers can be substantial, depending on the environment, experience and other factors.

    In this thesis, two methods are proposed that aim at quantifying and qualifying driver performance of heavy duty vehicles with respect to fuel consumption. The first method, Fuel under Predefined Conditions (FPC), makes use of domain knowledge in order to incorporate effect of factors which are not measured. Due to the complexity of the vehicles, many factors cannot be quantified precisely or even measured, e.g. wind speed and direction, tire pressure. For FPC to be feasible, several assumptions need to be made regarding unmeasured variables. The effect of said unmeasured variables has to be quantified, which is done by defining specific conditions that enable their estimation. Having calculated the effect of unmeasured variables, the contribution of measured variables can be estimated. All the steps are required to be able to calculate the influence of the driver. The second method, Accelerator Pedal Position - Engine Speed (APPES) seeks to qualify driver performance irrespective of the external factors by analyzing driver intention. APPES is a 2D histogram build from the two mentioned signals. Driver performance is expressed, in this case, using features calculated from APPES.

    The focus of first method is to quantify fuel consumption, giving us the possibility to estimate driver performance. The second method is more skewed towards qualitative analysis allowing a better understanding of driver decisions and how they affect fuel consumption. Both methods have the ability to give transferable knowledge that can be used to improve driver's performance or automatic driving systems.

    Throughout the thesis and attached articles we show that both methods are able to operate within the specified conditions and achieve the set goal.

    Download full text (pdf)
    fulltext
  • 28.
    Cederholm Björklund, Jennie
    Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL). Hushållningssällskapet Halland, Halmstad, Sverige.
    Value creation for sustainable rural development – perspectives of entrepreneurship in agriculture2020Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Entrepreneurship and innovation are regarded as key factors in the development of society - not least in the development of sustainable rural areas, where they are emphasised by both authorities and research. This thesis is situated in this field of inquiry and studies entrepreneurship in agriculture. It explores how we can further develop both agriculture and sustainable rural areas. Farmers have traditionally played a significant role in rural areas and rural development, and still do. However in pace with societal development and the reduced number of farms and farm production, their role has changed. Today, they are considered as raw material producers, being the first link in a food chain, and active in landscape conservation in the countryside. However, agriculture plays a significant role in rural development and in Sweden, authorities strive for development of sustainable rural areas by encouraging economic growth and innovation within and between companies (business models, value chains etc.). They work with economic growth strategies, but both their management and results are criticised (OECD, 2019).This thesis states that greater contextualized knowledge is required to facilitate sustainable rural and agricultural development. Against this background, the purpose of this thesis is to explore entrepreneurship in agriculture from different perspectives, to find mechanisms affecting value creation for sustainable rural development.

    To meet the research purpose, Swedish agricultural entrepreneurship was studied from different perspectives and data was collected with different methods enabling significant triangulation of data. Studies of challenges in entrepreneurship and sustainable rural development were conducted from individual farmer and business perspectives as well as from the individual and organisational levels of actors within the support system, actors such as advisors, authorities, policy makers and officials. Thus, it was possible to explore perspectives on entrepreneurship in agriculture and identify mechanisms and structures affecting value creation for sustainable rural development. Mechanisms can be explained as underlying, invisible and sometimes unconscious and non-rational factors, feelings, norms, values or attitudes that affect behaviour in various ways.

    The key theories and literature covered included the concept of entrepreneurship with the intertwined sub-concepts of innovation and management at individual, business, organisational and societal levels.The thesis probed under the surface of rural development, exploring agricultural development at business level by using the concepts of Sustainable Entrepreneurship, Business Model Innovation and Barriers to Sustainable Business Model Innovation when exploring the challenges farmers face. The concepts of Self-leadership, Emotional Intelligence and Entrepreneurial Orientation helped to explore how challenges are approached, by for example understanding mechanisms concerned with feelings and mind-set. Further, the thesis also studied how entrepreneurship was encouraged and supported by the agricultural support system, and, with help from the Complexity Leadership Theory, established the urgent need of adaption to environmental changes and the creation of innovation within the system. The concepts of Agricultural and Rural Entrepreneurship and Embeddedness helped in understanding and shed light on the importance of considering the mutual influence and interplay between farmers, actors within the support system, embeddedness in context and rural entrepreneurship.

    This thesis makes several contributions. It extends knowledge about entrepreneurship in agriculture by highlighting the importance of understanding embeddedness and the concept of agricultural sustainability, and by this providing evidence of the importance of including agriculture in entrepreneurship research. Consequently, this thesis has another viewpoint than previous research which states that farmers are not entrepreneurial and has overlooked agriculture in entrepreneurship research.

    Firstly, it shows that farmers, to a very considerable degree, contribute to sustainable rural development and also play the role of enabler for rural entrepreneurship. Second, by exploring the support system, and thereby providing insights into the challenges within the system, in the organisations and betweenthe organisations, this thesis shows transparency and improved understanding of challenges in for example communication, trust, management and culture. Further, a model contributes suggestions for how to improve the system and create innovation to enable encouragement of entrepreneurship in agriculture. Third, this thesis contributes to business model research by illustrating the importance of including and reflecting on embeddedness in context and the understanding of agricultural sustainabilityin business model innovation. Hence, this thesis extends previous business model research which mainly considered agriculture as the first step in a food production chain, exposed to the same challenges as other non-agricultural companies further up the value chain. By providing insights about challenges to farmers’ entrepreneurship, and how these challenges can be approached as well as how entrepreneurship can be encouraged and supported in agriculture, this thesis can contribute to policies and strategies shifting focus from primarily trying to transform farmers into traditional entrepreneurs to taking advantage of the enabling role played by farmers. This thesis contributes to show the diversity in entrepreneurship, by providing understanding of entrepreneurship in agriculture, where value creation extends far beyond individual companies and competitive advantages, and hence impacts sustainable rural development.

    Download full text (pdf)
    Jennie Cederholm_inlaga_slutlig till tryck
    Download full text (pdf)
    Errata list
  • 29.
    Chen, Kunru
    Halmstad University, School of Information Technology.
    Learning Representations for Machine Activity Recognition2022Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Machine activity recognition (MAR) is an essential and effective approach for equipment productivity monitoring. Developing MAR methods for forklift trucks, a vital piece of the industry, can benefit productivity efficiency, maintenance service, product design, and potential savings. With the growth of the Internet of Things, a large amount of sensory data has become accessible. Conventional MAR methods that have been developed primarily focus on data collected from external sensors, such as inertial measurement units (IMUs) and cameras. However, they are not effective for forklift applications: the IMU data does not reflect kinematic patterns due to a lack of large articulated parts, while the vision-based data collection requires many cameras to create sufficient coverage of an indoor environment, which, in result, risks the privacy and is less economical. Moreover, typical objectives in the existing MAR works are heavy equipment in construction sites where the working environment and tasks differ from the logistics sector. Therefore, it is necessary to develop intelligent and innovative approaches that are more suitable for forklift trucks.

    This thesis demonstrates developing and utilizing representation learning methods to solve forklift MAR problems, based on the assumption that forklift activities are formed by a series of basic movements that can be detected from the onboard communication, i.e., signals in a Controller Area Network (CAN). Most of the methods proposed in this thesis incorporate semi-supervised techniques to deal with the limited amount of labeled data and to capitalize on a large amount of unlabeled data in our experiments. Deep neural networks are implemented to overcome different challenges of recognizing forklift activities and learn various representations of the data: i) learning invariant features to reconstruct input CAN signals by applying autoencoders, ii) learning discriminative features to recognize forklift activities by fine-tuning pre-training networks, and iii) learning temporal coherence to capture activity transitions by implementing gated recurrent units. Apart from achieving promising classification performance for forklift MAR problems, the representations obtained also support visualization and interpretability of the data as they are three-dimensional. Our ongoing works are new experiments about learning domain-invariant features, where domain adaptation methods are implemented to recognize activities performed by forklift trucks from different sites.

    Download full text (pdf)
    fulltext
  • 30.
    Chettiyamkudiyil Joy, Shincy Mol
    Halmstad University, School of Health and Welfare.
    Discrimination Of Unskilled Immigrants in Sweden: A Workplace Perspective2023Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    The study aims to explore discrimination against unskilled Swedish immigrants in the workplace and its psychological impact on immigrant workers. It focuses on identifying the main conditions affecting immigrant employees' working environments and their effects on their mental and physical health. The study uses a systematic literature review to summarize existing research findings, specifically on unskilled immigrants. The concepts of Chronic Ethnic Stress and dissociation theory are used to understand the study findings better. The keywords for this study include work discrimination, Sweden, unskilled immigrants, and psychological effects.

    Further, the Boolean framework has been used in the research to increase the effectiveness of information retrieval and literature search. The study obtained focused and pertinent results by generating sophisticated search queries utilising logical operators, guaranteeing a methodical investigation of the subject issue. To maintain sustainability, a systematic literature analysis has been covered with 10 articles and a peer-reviewed segment. The roles of each piece and its alliances with this research context have also manifested in this study. 

     

    Download full text (pdf)
    fulltext
  • 31.
    Correa da Cunha, Henrique
    Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL).
    Asymmetry and the moderating effects of formal institutional distance on the relationship between cultural distance and performance of foreign subsidiaries in Latin America2019Doctoral thesis, monograph (Other academic)
    Abstract [en]

    This study investigates how Cultural and Formal Institutional distances and their interaction affect the performance of multinational foreign subsidiaries in Latin America. It is shown that using Kogut and Singh (1988) index or attributing the positive and negative signals to distances in opposite directions fail to capture asymmetric effects as it assumes either symmetry or opposing symmetry. To overcome such limitations, I propose an alternative measurement, which allows capturing the asymmetric effects of distances on the performance of foreign subsidiary firms. To test the main research question, I run a panel data model including 1466 subsidiaries, being 1216 from developed and 250 from developing countries, totaling 168 combinations of different home and host countries for a period ranging from 2013 to 2015.Cultural Distance is measured using Hofstede (1980) dimensions and Formal Institutional distances are calculated using the six World Governance Indicator’s variables. Findings show that when the direction of cultural and formal institutional distances is included, the effects on performance are in fact asymmetric. Moreover, not all formal institutional distances affect in a negative manner the performance of developed country subsidiaries operating in less developed countries as these firms seem to know how to interpret and respond to different regulatory quality conditions in the host countries. Latin American firms are in advantage when dealing with formal institutional distances while being affected in the same manner by cultural distances if compared to other emerging market firms from outside Latin America. Emerging market firms are affected in a positive manner while operating in less developed countries and in a negative way when institutions in the host country are superior to its home country. Finally, results show that formal institutional distance positively moderates the relationship between cultural distance and performance particularly when formal institutional distance is towards less developed countries. It can be concluded that despite the fact that cultural values remain fairly stable over time, the contextual changes in terms of formal institutions (and formal institutional distances among countries) will modify the way cultural distance affects the performance and the competitiveness of firms around the world.

    Download full text (pdf)
    fulltext
    Download (pdf)
    omslag
  • 32.
    Das, Mousumi
    et al.
    Halmstad University, School of Business, Engineering and Science.
    Shafiquzzaman, Mohammad
    Halmstad University, School of Business, Engineering and Science.
    The Case Studies of Bangladesh Ready made Garments: Supplier Sustainable Practices for International Market: A Multiple Case Study2020Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The purpose of this paper was to investigate the overview of sustainability in apparel manufacturing industry and why environmentally and socially sustainable practices are being adopted by developing country suppliers and how the implementation process is both hindered and enabled. Currently the worldwide survival of the apparel industry is the main significant question. The most spoken about issue is for the sustainability of fashion in the world. Many organizations and fashion-conscious personalities have come forward to uphold the further extension of tomorrow 's good environment campaign, but the garments and textile industries in Bangladesh are far beyond this awareness, posing a risk of losing the world market. On the other hand, one of the key concepts for humanity and sustainability point of view is fashion for the moral or ethical issues. It is high time specific sustainability strategies and approaches were implemented. Improvements in social and environmental support migrant employees, help manufacturers establish longer-term partnerships with transnational companies and lead to production. The Bangladeshi garments industries are currently facing great challenges in terms of the working environment. Fire injuries are frequent in garments factories and the recent collapse of buildings poses a significant danger to their future.  In addition, the workers earn the world's lowest salaries which make them unsatisfied, sometimes causing clashes and violence during low-wage protests. This paper has looked at the work environment, fire and health problems facing Bangladesh's garments industry and proposes major steps to strengthen the environment and sustainability.

    Download full text (pdf)
    fulltext
  • 33.
    Del Moral Pastor, Pablo José
    Halmstad University, School of Information Technology.
    Hierarchical Methods for Self-Monitoring Systems: Theory and Application2022Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Self-monitoring solutions first appeared to avoid catastrophic breakdowns in safety-critical mechanisms. The design behind these solutions relied heavily on the physical knowledge of the mechanism and its fault. They usually involved installing specialized sensors to monitor the state of the mechanism and statistical modeling of the recorded data. Mainly, these solutions focused on specific components of a machine and rarely considered more than one type of fault.

    In our work, on the other hand, we focus on self-monitoring of complex machines, systems composed of multiple components performing heterogeneous tasks and interacting with each other: systems with many possible faults. Today, the data available to monitor these machines is vast but usually lacks the design and specificity to monitor each possible fault in the system accurately. Some faults will show distinctive symptoms in the data; some faults will not; more interestingly, there will be groups of faults with common symptoms in the recorded data.

    The thesis in this manuscript is that we can exploit the similarities between faults to train machine learning models that can significantly improve the performance of self-monitoring solutions for complex systems that overlook these similarities. We choose to encode these similarity relationships into hierarchies of faults, which we use to train hierarchical supervised models. We use both real-life problems and standard benchmarks to prove the adequacy of our approach on tasks like fault diagnosis and fault prediction.

    We also demonstrate that models trained on different hierarchies result in significantly different performances. We analyze what makes a good hierarchy and what are the best practices to develop methods to extract hierarchies of classes from the data. We advance the state-of-the-art by defining the concept of heterogeneity of decision boundaries and studying how it affects the performance of different class decompositions. 

    Download full text (pdf)
    fulltext
  • 34.
    Delooz, Quentin
    Halmstad University, School of Information Technology.
    Sensor Data Sharing in V2X Communications: Protocol Design and Performance Optimization of Collective Perception2023Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Sensor data sharing involves exchanging sensor data among multiple devices, systems, or platforms through various means, such as wired or wireless communication, cloud storage, and distributed computing. In Vehicle-to-Everything (V2X) communication, sensor data sharing is known as Collective Perception (CP). V2X Collective Perception is the principle of exchanging sensor data among V2X-capable stations, such as vehicles, vulnerable road users, or roadside units, by exchanging lists of perceived objects in the allocated 5.9 GHz frequency band for road safety and traffic efficiency. An object can be anything relevant to traffic safety and is described using its characteristics such as position, heading, and velocity. Objects are detected thanks to sensors such as cameras, LiDARs, and radars mounted on V2X stations. This thesis investigates the message generation rule for CP, specifically how often and with which objects a Collective Perception Message (CPM) should be generated for transmission. The contained studies focus on the challenges posed by the limited bandwidth available in the 5.9 GHz channel against the object selection for inclusion in CPMs. In the first part of the realized studies, the protocol design and the requirements of CP are comprehended from the network and application-related aspects, concluding that the process of filtering objects is necessary to control the channel usage of CP. Moreover, results show that object filtering is only beneficial in high-traffic density scenarios and should not be applied when channel resources are plenty available. In the second part, methods are developed and assessed to adapt the object filtering mechanism to the available channel resources and control information redundancy, i.e., controlling the number of vehicles transmitting updates about the same objects. Through a combination of theoretical analysis, large-scale simulations, and experimental evaluation, this thesis provides a better understanding of the requirements of CP for object filtering and shows the benefits of a developed novel algorithm to adapt object filtering to the available channel resources. Additionally, it elaborates on new metrics and provides a requirements analysis and performance assessment of selected information redundancy reduction techniques. Finally, the results show that combining both approaches enables efficient control of information redundancy while allowing efficient channel resource usage.

    Download full text (pdf)
    fulltext
  • 35.
    Deraz, Hossam
    Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL), Centre for International Marketing and Entrepreneurship Research (CIMER).
    Assessments of Advertisements on Social Networking Sites2016Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Advertisements (ads) in social networking sites (SNSAs) have been considered by many researchers as a crucial area of research. However, the scope of the existing studies on consumers’ assessments of SNSAs has been very limited. Most of the existing studies on assessing SNSAs have focused on Ducoffe’s (1996) model with its three variables, and they have ignored other related variables like the credibility value and interactivity value of the advertisement, which are more logically related to SNSAs than the traditional ads. Moreover, most of these studies have been skewed towards younger users and have ignored the social networking site (SNS) users from other age categories. Finally, previous studies about the assessment of SNSAs have depended on data collected from users of popular SNSs and ignored active users from the brand communities (fans of brands on SNSs). In this thesis, the present author has emphasized these three points as the major gaps in the literature about assessing SNSAs. Moreover, to deepen our understanding of how SNS users assess SNSAs this study presents the research findings of three published papers with three different purposes and with different levels of analysis.

    The first article aimed to extend Ducoffe’s (1996) model – which was used in the previous literature in assessing SNSAs – by considering the ads’ credibility and interactivity values in addition to Ducoffe’s (1996) three variables of information value, entertainment value, and irritation value. A multiple regression analysis was used to test the modified model, and based on the regression analysis of testing the five predictors, the model without the irritation value had the best coefficient of determination (R2). Moreover, coefficient analysis to test the given hypothesis and to determine the coefficients of the predictors was used. According to this survey study, the four primary variables that predicted the consumers’ assessment of the SNSAs were the information value, entertainment value, credibility value, and interactivity value. As perceived by the SNS users, the interactivity value was the strongest among the four predictors.

    Based on the unexpected result ofthe irritation value of the first paper, the second paper focused on testing the extended model of the assessments of SNSAs as perceived by a different research population, in this case, brand communities’ consumers (BCCs). Based on the regression analysis of testing the five predictors, the model with the five predictors had the best coefficient of determination (R2). The coefficient analysis was used to test the given hypothesis, to determine the coefficients of the five predictors, and to form a construct equation for assessing the SNSAs. Based on this survey study, the four variables with significant positive effects on the consumers’ assessment of SNSAs were informativeness, entertainment value, credibility value, and interactivity value, while the fifth dimension (irritation value) had a significant negative coefficient on the consumers’ assessment of SNSAs. Moreover, that study provided a deeper understanding of how the BCCs assess SNSAs, and it contributed to identifying the main characteristics ofthe BCCs on an SNS.

    The third paper focused on exploring the effect of national culture on the consumers’ assessment of SNSAs. The cultural features of the respondents in that study gave additional evidence about how a nation’s cultural characteristics can influence the consumers’ assessment of SNSAs. This study helped to identify how SNS users from Egypt, the Netherlands, and the United Kingdom assess SNSAs. In this study, one-way analysis of variance with post hoc tests was used to compare the assessments of the three nations. Based on the empirical findings of this survey study, the three groups had significant difference F-ratios for their perception of four of the five variables for assessing SNSAs. Their perceptions of the entertainment value did not significantly differ between the three groups while the interactivity value had the strongest F-ratio.

    The overall purpose of this study was to deepen our understanding of how SNS users are assessing SNSAs in different settings by considering SNS users, BCCs, and others from various nations. All of the studies presented here have focused on variables for assessing the ads that have been used by other researchers in different research contexts.

    Download full text (pdf)
    fulltext
  • 36.
    Deraz, Hossam
    Halmstad University, School of Business, Innovation and Sustainability, Centre for Innovation, Entrepreneurship and Learning Research (CIEL), Centre for International Marketing and Entrepreneurship Research (CIMER).
    Social Networking Sites – Consumers’ assessment of the value of advertisements (Extended Model)2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    In light of the identified shortcomings in the earlier studies of consumers’ assessment of advertisement value on social networking sites, and the relative importance of explaining advertisement value, the overall purpose of this dissertation is to develop and empirically test a conceptual framework that can advance knowledge and increase our understanding of how online consumers assess the value of advertisements on social networking sites. In reference to this purpose, this doctoral dissertation has sought to answer the following overarching research question: What are the relevant variables that predict online consumers’ assessment of advertisement value on social networking sites, and how do these variables affect their assessment?

    To achieve the purpose of this study and to answer its overarching research question, a mixed method approach was used, adapting both quantitative and qualitative methods. A sequential explanatory strategy using mixed methods was the primary approach used to explain and interpret the quantitative results, by collecting and analyzing follow-up qualitative data. Consequently, this study started by doing a systematic literature review to identify the related factors, followed by a conceptual study to provide an extended conceptual framework that connected consumer beliefs to their sources of gratifications from using SNSs. That conceptual framework was partially examined in three survey papers to test the effects of its five belief factors (information value, entertainment value, irritation value, interactivity value, and credibility value) on assesments of advertisement value on SNSs. The three survey papers found that these five belief factors have significant effects on assessments of advertisement value on social networking sites. However, those effects varied according to consumers’ cultural backgrounds. The three survey papers were then followed by a qualitative focus group study to give a deeper explanation, and to discover the underlying reasons behind consumers’ assessment of advertisement value. That focus group study confirmed the role of culture in assessing the value of advertisements, and it gave deeper explanations behind the reasons for that variance in assessments of advertisement value within the context of social networking sites from one research population to another. In general, this study contributes to the understanding of consumers’ assessments of advertisements on social networking sites. It offers a new approach by connecting consumers’ gratifications from using social networking sites to their assessment of advertisement value. In turn, it helps to reflect a number of valuable insights that can be utilized by both researchers and marketers in order to understand how the addressed factors enhance consumers’ assessments by testing the contribution of credibility, interactivity value, social influence, pre-purchase search motivation, and cultural backgrounds, in addition to previously tested variables: information value, entertainment value, and irritation value.

    Download full text (pdf)
    fulltext
  • 37.
    Duracz, Adam
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Rigorous Simulation: Its Theory and Applications2016Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Designing Cyber-Physical Systems is hard. Physical testing can be slow, expensive and dangerous. Furthermore computational components make testing all possible behavior unfeasible. Model-based design mitigates these issues by making it possible to iterate over a design much faster. Traditional simulation tools can produce useful results, but their results are traditionally approximations that make it impossible to distinguish a useful simulation from one dominated by numerical error. Verification tools require skills in formal specification and a priori understanding of the particular dynamical system being studied.

    This thesis presents rigorous simulation, an approach to simulation that uses validated numerics to produce results that quantify and bound all approximation errors accumulated during simulation. This makes it possible for the user to objectively and reliably distinguish accurate simulations from ones that do not provide enough information to be useful. Explicitly quantifying the error in the output has the side-effect of leading to a tool for dealing with inputs that come with quantified uncertainty.

    We formalize the approach as an operational semantics for a core subset of the domain-specific language Acumen. The operational semantics is extended to a larger subset through a translation. Preliminary results toward proving the soundness of the operational semantics with respect to a denotational semantics are presented. A modeling environment with a rigorous simulator based on the operational semantics is described. The implementation is portable, and its source code is freely available. The accuracy of the simulator on different kinds of systems is explored through a set of benchmark models that exercise different aspects of a rigorous simulator. A case study from the automotive domain is used to evaluate the applicability of the simulator and its modeling language. In the case study, the simulator is used to compute rigorous bounds on the output of a model.

    Download full text (pdf)
    thesis
    Download full text (pdf)
    errata
  • 38.
    Ebbesson, Esbjörn
    Halmstad University, School of Information Technology.
    Engaging in Urban Living Lab Co-design2023Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Urban Living Labs (ULL) have become a common way to address wicked design challenges within the future mobility, and smart city context. The move toward ULL is part of a paradigm shift away from focusing purely on the IT-artifact, innovation, and user-centeredness toward focusing on the urban context and the construction of a place as a social context rather than implementation of a product or service in isolation.

    This shift requires diverse sets of stakeholders with different backgrounds to come together to address wicked design challenges collaboratively tied to specific urban contexts. However, the change toward ULLs also brings unique qualities to collaborations. For example, it is often hard to generalize or transfer findings from one ULL to another. In addition, it requires new modes of thinking and acting concerning the value of bottomup approaches anchored in context.

    Therefore, a core challenge for impactful work in an ULL, is to find ways to retain stakeholders’ local engagements and ways of doing collaborative design beyond the ULL project to create ripple effects. This thesis tweaks this challenge into a question that aims at investigating what a locally contextualized ULL set-up means for the involved stakeholders from a participatory perspective by asking: How can we understand engagement in ULL co-design, and how can this engagement be retained beyond the Living Lab? The question was explored through a design ethnographic approach in a ULL, where citizens, city representatives, car manufacturers, and representatives from public transport worked together to explore future mobility services. The research question is addressed through a description of how stakeholder engagement played out in the ULL along with an analysis of the dynamics of co-design as a co-appropriation process within the ULL, which enabled stakeholders to engage in a social context across sectors and disciplines to co-learn ways of appropriating findings from the ULL as an explorative way of working. Co-appropriation is described as a process moving from acclimatization towards cogitation in co-design, with patching as an activity that supports the process. The thesis also elaborates on how findings from a ULL can be retained and scaled beyond the Living Lab through transformation games, as an example of a patching activity.

    Download full text (pdf)
    fulltext
  • 39.
    Ekengren, Johan
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI), Health and Sport.
    Careers of Swedish Professional Handball Players: From an Empirical Model to Career-Long Psychological Support Services2020Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This PhD Project with a specialization in sport psychology is inspired by the cultural praxis of athletes’ careers paradigm. This implies that the Project blends theory, research, and practice within the context of Swedish handball, by investigating career pathways of professional players providing empirically based, and context specific, implications. The overarching aim of the Project is twofold: (a) to examine the career experiences of Swedish professional handball players and consolidate them into the empirical career model of Swedish professional handball players (ECM-H), and (b) based on the ECM-H, to develop, validate, and test an applied framework promoting career-long psychological support services in Swedish handball (CPS-H). The first aim is covered by Study I and II, and the second aim is met in Study III and IV. The dissertation is designed as a collection of four articles with one article per study. Study I focused on a qualitative exploration of career experiences from 18 Swedish professional handball players including major career stages and transitions in their athletic and non-athletic development. The players’ accounts were consolidated into the ECM-H describing the context-specific features and pathways throughout the handball career. When developing the ECM-H, gender-specific issues appeared of interest for further investigation. Gender issues were addressed in Study II by re-analyzing the data from Study I. Two composite vignettes were created describing the career pathways of nine male and nine female players. Study III initiated a move from research to practice. Based on the ECM-H, applied sport psychology literature and experiences of the research team led by the first author, the applied framework CPS-H was heuristically developed and validated in three focus groups with end users; professional players, coaches, and sport psychology practitioners. The validated version of the CPS-H is presented with general and career stage-specific recommendations for its implementation among support providers (i.e., where, when, what, who, why, and how of psychological support service). Study IV was designed as an instrumental case study for testing a part of the CPS-H framework. More specifically, the mastery career stage. A career assistance program (CAP) named Life as a professional handball player was developed for, implemented with, and evaluated by Swedish League team. The program included eight workshops dealing with various aspects of the players’ athletic and non-athletic life (e.g., performance, training, lifestyle, recovery, future planning), together with crisis-related issues (e.g., coping with uncertainty). These workshops were delivered by the first author during 12 weeks of a competitive season. The mixed-methods evaluation revealed a perceived improvement in players’ personal coping resources (e.g., increased awareness) and a decrease in their fatigue and stress. This Project contributes to the athlete career sport psychology discourse and the emerging athlete mental health discourse by presenting the ECM-H and CPS-H frameworks, and the CAP Life as a professional handball player, grounded in the cultural context of Swedish handball. The frameworks and CAP can serve as inspiration for future research and practice, informed by a cultural praxis. The Project shows the usefulness of working as a scientist-practitioner and establishing theory-researchpractice-context links for the promotion of culturally informed implications, and supports the work of facilitating a holistic understanding of athletes’ striving for healthy, successful, and long-lasting careers in sport and life.

    Download full text (pdf)
    comprehensive summary/kappa
    Download full text (pdf)
    cover/omslag
  • 40.
    Fabricius, Victor
    Halmstad University, School of Information Technology. RISE Research Institutes of Sweden, Gothenburg, Sweden.
    Exploring Road Traffic Interactions Between Highly Automated Vehicles and Vulnerable Road Users2023Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Understandings of road traffic interactions are largely based on human-human interactions. However, the development of vehicles controlled by highly auto- mated driving systems (ADS) would introduce a radically novel type of road user. This compilation thesis explores encounters between these “autonomous vehicles” (AVs) and human vulnerable road users (VRUs) such as pedestrians and cyclists. The included publications are connected to three research questions. First, empirical studies are reviewed to highlight existing interactive be- haviors and communication cues. This is followed by a methodological question of how to investigate AV-VRU interactions. Finally, VRUs’ experiences from initial experiments on AV crossing encounters are presented.

    While road user trajectories and kinematic behaviors are viewed as primary mechanisms to facilitate traffic interactions, they might also be influenced by cues such as appearances, gestures, eye-gaze, and external human-machine interfaces (eHMI). Using the Wizard-of-Oz approach, we are able to explore VRU encounters with a seemingly highly automated vehicle. Compared to meeting an attentive driver, AV encounters resulted in a reported lower willingness to cross, lower perceived safety, and less calm emotional state, indicating that the absence of driver-centric cues could lead to interaction issues and impede acceptance of AVs. To further explore this, we included light-based eHMI to signal the driving mode and intent of the vehicle (e.g., intent to yield). Future research should continue to investigate how AVs may co-exist with human road users focusing on aspects such as behavioral adaptations, research methodologies, and the role of various eHMI.

    Download full text (pdf)
    Licentiate Thesis Summary
  • 41.
    Fan, Yuantao
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    A Self-Organized Fault Detection Method for Vehicle Fleets2016Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    A fleet of commercial heavy-duty vehicles is a very interesting application arena for fault detection and predictive maintenance. With a highly digitized electronic system and hundreds of sensors mounted on-board a modern bus, a huge amount of data is generated from daily operations.

    This thesis and appended papers present a study of an autonomous framework for fault detection, using the data gathered from the regular operation of vehicles. We employed an unsupervised deviation detection method, called Consensus Self-Organising Models (COSMO), which is based on the concept of ‘wisdom of the crowd’. It assumes that the majority of the group is ‘healthy’; by comparing individual units within the group, deviations from the majority can be considered as potentially ‘faulty’. Information regarding detected anomalies can be utilized to prevent unplanned stops.

    This thesis demonstrates how knowledge useful for detecting faults and predicting failures can be autonomously generated based on the COSMO method, using different generic data representations. The case study in this work focuses on vehicle air system problems of a commercial fleet of city buses. We propose an approach to evaluate the COSMO method and show that it is capable of detecting various faults and indicates upcoming air compressor failures. A comparison of the proposed method with an expert knowledge based system shows that both methods perform equally well. The thesis also analyses the usage and potential benefits of using the Echo State Network as a generic data representation for the COSMO method and demonstrates the capability of Echo State Network to capture interesting characteristics in detecting different types of faults.

    Download full text (pdf)
    fulltext
  • 42.
    Fan, Yuantao
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Wisdom of the Crowd for Fault Detection and Prognosis2020Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Monitoring and maintaining the equipment to ensure its reliability and availability is vital to industrial operations. With the rapid development and growth of interconnected devices, the Internet of Things promotes digitization of industrial assets, to be sensed and controlled across existing networks, enabling access to a vast amount of sensor data that can be used for condition monitoring. However, the traditional way of gaining knowledge and wisdom, by the expert, for designing condition monitoring methods is unfeasible for fully utilizing and digesting this enormous amount of information. It does not scale well to complex systems with a huge amount of components and subsystems. Therefore, a more automated approach that relies on human experts to a lesser degree, being capable of discovering interesting patterns, generating models for estimating the health status of the equipment, supporting maintenance scheduling, and can scale up to many equipment and its subsystems, will provide great benefits for the industry. 

    This thesis demonstrates how to utilize the concept of "Wisdom of the Crowd", i.e. a group of similar individuals, for fault detection and prognosis. The approach is built based on an unsupervised deviation detection method, Consensus Self-Organizing Models (COSMO). The method assumes that the majority of a crowd is healthy; individual deviates from the majority are considered as potentially faulty. The COSMO method encodes sensor data into models, and the distances between individual samples and the crowd are measured in the model space. This information, regarding how different an individual performs compared to its peers, is utilized as an indicator for estimating the health status of the equipment. The generality of the COSMO method is demonstrated with three condition monitoring case studies: i) fault detection and failure prediction for a commercial fleet of city buses, ii) prognosis for a fleet of turbofan engines and iii) finding cracks in metallic material. In addition, the flexibility of the COSMO method is demonstrated with: i) being capable of incorporating domain knowledge on specializing relevant expert features; ii) able to detect multiple types of faults with a generic data- representation, i.e. Echo State Network; iii) incorporating expert feedback on adapting reference group candidate under an active learning setting. Last but not least, this thesis demonstrated that the remaining useful life of the equipment can be estimated from the distance to a crowd of peers. 

    Download full text (pdf)
    fulltext
  • 43.
    Farouq, Shiraz
    Halmstad University, School of Information Technology.
    Towards conformal methods for large-scale monitoring of district heating substations2022Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Increasing technical complexity, design variations, and customization options of IoT units create difficulties for the construction of monitoring infrastructure. These units can be associated with different domains, such as a fleet of vehicles in the mobility domain and a fleet of heat-pumps in the heating domain. The lack of labeled datasets and well-understood prior unit and fleet behavior models exacerbates the problem. Moreover, the time-series nature of the data makes it difficult to strike a reasonable balance between precision and detection delay. The thesis aims to develop a framework for scalable and cost-efficient monitoring of industrial fleets. The investigations were conducted on real-world operational data obtained from District Heating (DH) substations to detect anomalous behavior and faults. A foundational hypothesis of the thesis is that fleet-level models can mitigate the lack of labeled datasets, improve anomaly detection performance, and achieve a scalable monitoring alternative.

    Our preliminary investigations found that operational heterogeneity among the substations in a DH network can cause fleet-level models to be inefficient in detecting anomalous behavior at the target units. An alternative is to rely on subfleet-level models to act as a proxy for the behavior of target units. However, the main difficulty in constructing a subfleet-level model is the selection of its members such that their behavior is stable over time and representative of the target unit. Therefore, we investigated various ways of constructing the subfleets and estimating their stability. To mitigate the lack of well-understood prior unit and fleet behavior models, we proposed constructing Unit-Level and Subfleet-Level Ensemble Models, i.e., ULEM and SLEM. Herein, each member of the respective ensemble consists of a Conformal Anomaly Detector (CAD). Each ensemble yields a nonconformity score matrix that provides information about the behavior of a target unit relative to its historical data and its subfleet, respectively. However, these ensemble models can give different information about the nature of an anomaly that may not always agree with each other. Therefore, we further synthesized this information by proposing a Combined Ensemble Model (CEM). We investigated the advantages and limitations of decisions that rely on the information obtained from ULEM, SLEM, and CEM using precision and detection delay. We observed the decisions that relied on the information obtained through CEM showed a reduction in overall false alarms compared to those obtained through ULEM or SLEM, albeit at the cost of some detection delay. Finally, we combined the components of ULEM, SLEM, and CEM into what we refer to as TRANTOR: a conformal anomaly detection based indusTRiAl fleet moNiTORing framework. The proposed framework is expected to enable fleet operators in various domains to improve their monitoring infrastructure by efficiently detecting anomalous behavior and controlling false alarms at the target units.

    Download full text (pdf)
    fulltext
  • 44.
    Farouq, Shiraz
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Towards large-scale monitoring of operationally diverse thermal energy systems with data-driven techniques2019Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    The core of many typical large-scale industrial infrastructures consists of hundreds or thousands of systems that are similar in their basic design and purpose. For instance, District Heating (DH) utilities rely on a large network of substations to deliver heat to their customers. Similarly, a factory may require a large fleet of specialized robots for manufacturing a certain product. Monitoring these systems is important for maintaining the overall efficiency of industrial operations by detecting various problems due to faults and misconfiguration. However, this can be challenging since a well-understood prior model for each system is rarely available.

    In most cases, each system in a fleet or network is fitted with a set of sensors to measure its state at different time intervals. Typically, a data-driven model for each system can be used for their monitoring. However, not all factors that can influence the operation of each system in a fleet have an associated sensor. Moreover, sufficient data instances of normal, atypical, and faulty behavior are rarely available to train such a model. These issues can impede the effectiveness of a system-level data-driven model. Alternatively, it can be assumed that since all the systems in a fleet are working on a similar task, they should all behave in a homogeneous manner. Any system that behaves differently from the majority is then considered an outlier. It is referred to as a global or fleet-level model. While the approach is simple, it is less effective in the presence of non-stationary working conditions. Hence, both system-level and fleet-level modeling approaches have their limitations.

    This thesis investigates system-level and fleet-level models for large-scale monitoring of systems. It proposes to rely on an alternative way, referred to as a reference-group based approach. Herein, the operational monitoring of a target system is delegated to a reference-group, which consists of systems experiencing a comparable operating regime along with the target system. Thus, the definition of a normal, atypical, or faulty operational behavior in a target system is described relative to its reference-group. This definition depends on the choice of the selected anomaly detection model. In this sense, if the target system is not behaving operationally in consort with the systems in its reference-group, then it can be inferred that this is either due to a fault or because of some atypical operation arising at the target system due to its local peculiarities. The application area for these investigations is the large-scale operational monitoring of thermal energy systems: network of DH substations and fleet of heat-pumps.

    The current findings indicate three advantages of a reference-group based approach. The first is that the reference operational behavior of a target system in the fleet does not need to be predefined. The second is that it provides a basis for what a target system’s operational behavior should have been and what it is. In this respect, each system in the reference-group provides evidence about a particular behavior during a particular period. It can be very useful when the description of a normal, atypical, and faulty operational behavior is not available. The third is that it can detect atypical and faulty operational behavior quickly compared to fleet-level models of anomaly detection.

    Download full text (pdf)
    fulltext
  • 45.
    From, Malcolm
    Halmstad University, School of Education, Humanities and Social Science.
    An Analysis of the way Grammar is Presented in two Coursebooks for English as a Second Language: A Qualitative Conceptual Analysis of Grammar in Swedish Coursebooks for Teaching English2021Independent thesis Advanced level (professional degree), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    This essay aims to investigate theoretically how two currently used coursebooks, What’s Up 9 and Solid Gold 1, in a local area of Southern Sweden, present (introduces and covers) grammar. The overall aim is to investigate how grammar is presented, using the present simple and the present continuous as examples. The findings are also mapped to teaching approaches, as well as SLA (Second Language Acquisition) research, to see what approaches are favoured for teaching grammar in the first decades of the 21st century. In order to investigate the course- books, a qualitative content analysis and conceptual analysis was chosen with the presentation of grammar mapped into different categories, by using concepts for teaching and approaches used in SLA. The results show that the two proposed coursebooks favoured a FoFs (Focus on Forms) approach for presenting grammar. Furthermore, the results show that grammar is pre- sented explicitly and, if the teachers use the structures proposed in the coursebook rigidly, they automatically follow a deductive teaching procedure. When using a FoFs, explicit instructions and taking a deductive teaching approach, it may be regarded as the coursebooks suggest a grammar-translation approach as well. However, when observing other exercises connected to the reading texts in the coursebooks, it was detected that both coursebooks favoured a text- based approach for teaching, where the learners are supposed to learn the structure of different texts. In doing so, the grammatical structures are learned subconsciously and implicitly, which indicates that grammar is, in general, taught implicitly in the coursebooks, but presented (intro- duced and covered) explicitly.

    Download full text (pdf)
    fulltext
  • 46.
    Galozy, Alexander
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Data-driven personalized healthcare: Towards personalized interventions via reinforcement learning for Mobile Health2021Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Medical and technological advancement in the last century has led to the unprecedented increase of the populace's quality of life and lifespan. As a result, an ever-increasing number of people live with chronic health conditions that require long-term treatment, resulting in increased healthcare costs and managerial burden to the healthcare provider. This increase in complexity can lead to ineffective decision-making and reduce care quality for the individual while increasing costs. One promising direction to tackle these issues is the active involvement of the patient in managing their care. Particularly for chronic diseases, where ongoing support is often required, patients must understand their illness and be empowered to manage their care. With the advent of smart devices such as smartphones, it is easier than ever to provide personalised digital interventions to patients, help them manage their treatment in their daily lives, and raise awareness about their illness. If such new approaches are to succeed, scalability is necessary, and solutions are needed that can act autonomously without costly human intervention. Furthermore, solutions should exhibit adaptability to the changing circumstances of an individual patient's health, needs and goals. Through the ongoing digitisation of healthcare, we are presented with the unique opportunity to develop cost-effective and scalable solutions through Artificial Intelligence (AI).

    This thesis presents work that we conducted as part of the project improving Medication Adherence through Person-Centered Care and Adaptive Interventions (iMedA) that aims to provide personalised adaptive interventions to hypertensive patients, supporting them in managing their medication regiment. The focus lies on inadequate medication adherence (MA), a pervasive issue where patients do not take their medication as instructed by their physician. The selection of individuals for intervention through secondary database analysis on Electronic Health Records (EHRs) was a key challenge and is addressed through in-depth analysis of common adherence measures, development of prediction models for MA and discussions on limitations of such approaches for analysing MA. Furthermore, providing personalised adaptive interventions is framed in the contextual bandit setting and addresses the challenge of delivering relevant interventions in environments where contextual information is significantly corrupted.       

    The contributions of the thesis can be summarised as follows: (1) Highlighting the issues encountered in measuring MA through secondary database analysis and providing recommendations to address these issues, (2) Investigating machine learning models developed using EHRs for MA prediction and extraction of common refilling patterns through EHRs and (3) formal problem definition for a novel contextual bandit setting with context uncertainty commonly encountered in Mobile Health and development of an algorithm designed for such environments.  

    Download full text (pdf)
    fulltext
  • 47.
    Galozy, Alexander
    Halmstad University, School of Information Technology.
    Mobile Health Interventions through Reinforcement Learning2023Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis presents work conducted in the domain of sequential decision-making in general and Bandit problems in particular, tackling challenges from a practical and theoretical perspective, framed in the contexts of mobile Health. The early stages of this work have been conducted in the context of the project ``improving Medication Adherence through Person-Centred Care and Adaptive Interventions'' (iMedA) which aims to provide personalized adaptive interventions to hypertensive patients, supporting them in managing their medication regimen. The focus lies on inadequate medication adherence (MA), a pervasive issue where patients do not take their medication as instructed by their physician. The selection of individuals for intervention through secondary database analysis on Electronic Health Records (EHRs) was a key challenge and is addressed through in-depth analysis of common adherence measures, development of prediction models for MA, and discussions on limitations of such approaches for analyzing MA. Providing personalized adaptive interventions is framed in several bandit settings and addresses the challenge of delivering relevant interventions in environments where contextual information is unreliable and full of noise. Furthermore, the need for good initial policies is explored and improved in the latent-bandits setting, utilizing prior collected data to optimal selection the best intervention at every decision point. As the final concluding work, this thesis elaborates on the need for privacy and explores different privatization techniques in the form of noise-additive strategies using a realistic recommendation scenario.         

    The contributions of the thesis can be summarised as follows: (1) Highlighting the issues encountered in measuring MA through secondary database analysis and providing recommendations to address these issues, (2) Investigating machine learning models developed using EHRs for MA prediction and extraction of common refilling patterns through EHRs, (3) formal problem definition for a novel contextual bandit setting with context uncertainty commonly encountered in Mobile Health and development of an algorithm designed for such environments. (4) Algorithmic improvements, equipping the agent with information-gathering capabilities for active action selection in the latent bandit setting, and (5) exploring important privacy aspects using a realistic recommender scenario.   

    Download full text (pdf)
    Thesis Fulltext
  • 48.
    Gashi, Arlinda
    et al.
    Halmstad University, School of Health and Welfare.
    Krasniqi, Lirijeta
    Halmstad University, School of Health and Welfare.
    Ett sjuksköterskeperspektiv på patientdelaktighet: En litteraturstudie2022Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Backgroud: Patient participation is an important aspect in healthcare. It is the nurses' responsibility to involve patients in their own care and treatment. Research raises the importance of involving the patient in care and how participation is prometed. At the same time, hindering factors are raised that mean that  patientparticipation does not always work in reality.Aim: The aim of the study was to describe the patient's participation; from the nurse's perspective. Method: A general qualitative literature review with structured information retrieval was performed. Results: The results present a compilation of ten qualitative articles and the analysis revealed four themes: mutual relationship and engament, shared power and competence, time and ability and other hindering and promoting factors. For patient participation to work, mutual respect and a good relationship between nurse and patient are required. Something that affect patient participation was the lack of time among the nurses but also the physical or cognitive ability of the patient. Conclusion: Patient participation advocates an equal relationship between nurses and patients. The nurses experienced that there were contributing factors that constituted obstacles to patient participation. Patients' lack of knowledge about health had a negative effect or hindered patient participation. Something that was unsatisfying was the limited time that the nurses had to devote to the patients as other tasks also required time.

    Download full text (pdf)
    fulltext
  • 49.
    Gasimova, Nurana
    Halmstad University, School of Business, Innovation and Sustainability.
    Developing tokenomics framework: Conceptual framework for self-sustaining tokenomics2023Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Tokenomics is the design and implementation of token economies in blockchain projects, which utilizes tokens as means of exchange, unit of account, and governance mechanism. Despite its significance, there is a lack of established frameworks for designing tokenomics from the start. Existing research often focuses on post-tokenomics or studying tokens as investment tools, leaving a gap in practical guidelines and best practices for creating sustainable token economies. This master thesis aims to address this gap by exploring the elements in designing self-sustainable tokenomics and proposing a potential framework. To accomplish this, an action research methodology was employed, collaborating with a leading blockchain company, and conducting interviews and workshops with the project participants. The results contribute to theory by establishing a three-phase and three-dimensional approach to design tokenomics and offer valuable insights for practitioners and researchers. By considering these findings and implementing best practices, blockchain projects can increase their chances of success and create sustainable token economies.

    Download full text (pdf)
    fulltext
  • 50.
    Gebrewahid, Essayas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Compiling Concurrent Programs for Manycores2015Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    The arrival of manycore systems enforces new approaches for developing applications in order to exploit the available hardware resources. Developing applications for manycores requires programmers to partition the application into subtasks, consider the dependence between the subtasks, understand the underlying hardware and select an appropriate programming model. This is complex, time-consuming and prone to error.

    In this thesis, we identify and implement abstraction layers in compilation tools to decrease the burden of the programmer, increase programming productivity and program portability for manycores and to analyze their impact on performance and efficiency. We present compilation frameworks for two concurrent programming languages, occam-pi and CAL Actor Language, and demonstrate the applicability of the approach with application case-studies targeting these different manycore architectures: STHorm, Epiphany and Ambric.

    For occam-pi, we have extended the Tock compiler and added a backend for STHorm. We evaluate the approach using a fault tolerance model for a four stage 1D-DCT algorithm implemented by using occam-pi’s constructs for dynamic reconfiguration, and the FAST corner detection algorithm which demonstrates the suitability of occam-pi and the compilation framework for data-intensive applications. We also present a new CAL compilation framework which has a front end, two intermediate representations and three backends: for a uniprocessor, Epiphany, and Ambric. We show the feasibility of our approach by compiling a CAL implementation of the 2D-IDCT for the three backends. We also present an evaluation and optimization of code generation for Epiphany by comparing the code generated from CAL with a hand-written C code implementation of 2D-IDCT.

    Download full text (pdf)
    LicEssa
123 1 - 50 of 147
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf