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  • 1.
    Savas, Süleyman
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES). Department of Computers Science, Lund University, Lund, Sweden.
    Ul-Abdin, Zain
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Nordström, Tomas
    Umeå University, Umeå, Sweden.
    A Framework to Generate Domain-Specific Manycore Architectures from Dataflow Programs2020Ingår i: Microprocessors and microsystems, ISSN 0141-9331, E-ISSN 1872-9436, Vol. 72, artikel-id 102908Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In the last 15 years we have seen, as a response to power and thermal limits for current chip technologies, an explosion in the use of multiple and even many computer cores on a single chip. But now, to further improve performance and energy efficiency, when there are potentially hundreds of computing cores on a chip, we see a need for a specialization of individual cores and the development of heterogeneous manycore computer architectures.

    However, developing such heterogeneous architectures is a significant challenge. Therefore, we propose a design method to generate domain specific manycore architectures based on RISC-V instruction set architecture and automate the main steps of this method with software tools. The design method allows generation of manycore architectures with different configurations including core augmentation through instruction extensions and custom accelerators. The method starts from developing applications in a high-level dataflow language and ends by generating synthesizable Verilog code and cycle accurate emulator for the generated architecture.

    We evaluate the design method and the software tools by generating several architectures specialized for two different applications and measure their performance and hardware resource usages. Our results show that the design method can be used to generate specialized manycore architectures targeting applications from different domains. The specialized architectures show at least 3 to 4 times better performance than the general purpose counterparts. In certain cases, replacing general purpose components with specialized components saves hardware resources. Automating the method increases the speed of architecture development and facilitates the design space exploration of manycore architectures. © 2019 The Authors. Published by Elsevier B.V.

  • 2.
    Rabbani, Mahdi
    et al.
    Nanjing University of Science and Technology, Nanjing, China.
    Wang, Young Li
    Nanjing University of Science and Technology, Nanjing, China.
    Khoshkangini, Reza
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Jelodar, Hamed
    Nanjing University of Science and Technology, Nanjing, China.
    A Hybrid Machine Learning Approach for Malicious Behaviour Detection and Recognition in Cloud Computing2020Ingår i: Journal of Network and Computer Applications, ISSN 1084-8045, E-ISSN 1095-8592, Vol. 151, artikel-id 102507Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The rapid growth of new emerging computing technologies has encouraged many organizations to outsource their data and computational requirements. Such services are expected to always provide security principles such as confidentiality, availability and integrity; therefore, a highly secure platform is one of the most important aspects of cloud-based computing environments. A considerable improvement over traditional security strategies is achieved by understanding how malware behaves over the entire behavioural space. In this paper, we propose a new approach to improve the capability of cloud service providers to model users’ behaviours. We applied a particle swarm optimization-based probabilistic neural network (PSO-PNN) for the detection and recognition process, in the first module of the recognition process, we meaningfully converted the users’ behaviours to an understandable format and then classified and recognized the malicious behaviours by using a multi-layer neural network. We took advantage of the UNSW-NB15 dataset to validate the proposed solution by characterizing different types of malicious behaviours exhibited by users. Evaluation of the experimental results shows that the proposed method is promising for use in security monitoring and recognition of malicious behaviours. © 2019 Elsevier Ltd

  • 3.
    Marcos, Mar
    et al.
    Universitat Jaume I, Castellón, Spain.
    Juarez, Jose M.University of Murcia, Murcia, Spain.Lenz, RichardFriedrich-Alexander-University of Erlangen-Nuremberg, Erlangen, Germany.Nalepa, Grzegorz J.Jagiellonian University and AGH University of Science and Technology, Kraków, Poland.Nowaczyk, SławomirHögskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).Peleg, MorUniversity of Haifa, Haifa, Israel.Stefanowski, JerzyPoznań University of Technology, Poznan, Poland.Stiglic, GregorUniversity of Maribor, Maribor, Slovenia.
    Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems2020Proceedings (redaktörskap) (Refereegranskat)
  • 4.
    Vedder, Benjamin
    et al.
    Department of Electronics, RISE Research Institutes of Sweden, Borås, Sweden.
    Svensson, Bo Joel
    Department of Electronics, RISE Research Institutes of Sweden, Borås, Sweden.
    Vinter, Jonny
    Department of Electronics, RISE Research Institutes of Sweden, Borås, Sweden.
    Jonsson, Magnus
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Automated Testing of Ultrawideband Positioning for Autonomous Driving2020Ingår i: Journal of Robotics, ISSN 1687-9600, E-ISSN 1687-9619, Vol. 2020, artikel-id 9345360Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Autonomous vehicles need accurate and dependable positioning, and these systems need to be tested extensively. We have evaluated positioning based on ultrawideband (UWB) ranging with our self-driving model car using a highly automated approach. Random drivable trajectories were generated, while the UWB position was compared against the Real-Time Kinematic Satellite Navigation (RTK-SN) positioning system which our model car also is equipped with. Fault injection was used to study the fault tolerance of the UWB positioning system. Addressed challenges are automatically generating test cases for real-time hardware, restoring the state between tests, and maintaining safety by preventing collisions. We were able to automatically generate and carry out hundreds of experiments on the model car in real time and rerun them consistently with and without fault injection enabled. Thereby, we demonstrate one novel approach to perform automated testing on complex real-time hardware. Copyright © 2020 Benjamin Vedder et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

  • 5.
    Pelliccione, Patrizio
    et al.
    Dipartimento di Ingegneria e Scienze dell'Informazione e Matematica, Università degli Studi dell'Aquila, L'Aquila, Italy & Chalmers, Gothenburg University, Gothenburg, Sweden.
    Knauss, Eric
    Chalmers, Gothenburg University, Gothenburg, Sweden.
    Ågren, S. Magnus
    Chalmers, Gothenburg University, Gothenburg, Sweden.
    Heldal, Rogardt
    Chalmers, Gothenburg University, Gothenburg, Sweden & Western Norway University of Applied Sciences, Bergen, Norway.
    Bergenhem, Carl
    Qamcom Research & Technology AB, Gothenburg, Sweden.
    Vinel, Alexey
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES). Western Norway University of Applied Sciences, Bergen, Norway.
    Brunnegård, Oliver
    Veoneer Sweden AB, Vårgårda, Sweden.
    Beyond connected cars: A systems of systems perspective2020Ingår i: Science of Computer Programming, ISSN 0167-6423, E-ISSN 1872-7964, Vol. 191, artikel-id 102414Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The automotive domain is rapidly changing in the last years. Among the different challenges OEMs (i.e. the vehicle manufacturers) are facing, vehicles are evolving into systems of systems. In fact, over the last years vehicles have evolved from disconnected and “blind" systems to systems that are (i) able to sense the surrounding environment and (ii) connected with other vehicles, the city, pedestrians, cyclists, etc. Future transportation systems can be seen as a System of Systems (SoS). In an SoS, constituent systems, i.e. the units that compose an SoS, can act as standalone systems, but their cooperation enables new emerging and promising scenarios. While this trend creates new opportunities, it also poses a risk to compromise key qualities such as safety, security, and privacy.

    In this paper we focus on the automotive domain and we investigate how to engineer and architect cars in order to build them as constituents of future transportation systems. Our contribution is an architectural viewpoint for System of Systems, which we demonstrate based on an automotive example. Moreover, we contribute a functional reference architecture for cars as constituents of an SoS. This reference architecture can be considered as an imprinting for the implementations that would be devised in specific projects and contexts. We also point out the necessity for a collaboration among different OEMs and with other relevant stakeholders, such as road authorities and smart cities, to properly engineer systems of systems composed of cars, trucks, roads, pedestrians, etc. This work is realized in the context of two Swedish projects coordinated by Volvo Cars and involving some universities and research centers in Sweden and many suppliers of the OEM, including Autoliv, Arccore, Combitech, Cybercom, Knowit, Prevas, ÅF-Technology, Semcom, and Qamcom. © 2020 Published by Elsevier.

  • 6.
    Ali Hamad, Rebeen
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Salguero Hidalgo, Alberto
    University of Cádiz, Cádiz, Spain.
    Bouguelia, Mohamed-Rafik
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Estevez, Macarena Espinilla
    University of Jaén, Jaén, Spain.
    Quero, Javier Medina
    University of Jaén, Jaén, Spain.
    Efficient Activity Recognition in Smart Homes Using Delayed Fuzzy Temporal Windows on Binary Sensors2020Ingår i: IEEE journal of biomedical and health informatics, ISSN 2168-2194, E-ISSN 2168-2208, Vol. 24, nr 2, s. 387-395Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Human activity recognition has become an activeresearch field over the past few years due to its wide applicationin various fields such as health-care, smart homemonitoring, and surveillance. Existing approaches for activityrecognition in smart homes have achieved promisingresults. Most of these approaches evaluate real-timerecognition of activities using only sensor activations thatprecede the evaluation time (where the decision is made).However, in several critical situations, such as diagnosingpeople with dementia, “preceding sensor activations”are not always sufficient to accurately recognize theinhabitant’s daily activities in each evaluated time. Toimprove performance, we propose a method that delaysthe recognition process in order to include some sensoractivations that occur after the point in time where thedecision needs to be made. For this, the proposed methoduses multiple incremental fuzzy temporal windows toextract features from both preceding and some oncomingsensor activations. The proposed method is evaluated withtwo temporal deep learning models (convolutional neuralnetwork and long short-term memory), on a binary sensordataset of real daily living activities. The experimentalevaluation shows that the proposed method achievessignificantly better results than the real-time approach,and that the representation with fuzzy temporal windowsenhances performance within deep learning models. © Copyright 2020 IEEE

  • 7.
    Viteckova, Slavka
    et al.
    Faculty of Biomedical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
    Khandelwal, Siddhartha
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Kutilek, Patrik
    Faculty of Biomedical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
    Krupicka, Radim
    Faculty of Biomedical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
    Szabo, Zoltan
    Faculty of Biomedical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
    Gait symmetry methods: Comparison of waveform-based Methods and recommendation for use2020Ingår i: Biomedical Signal Processing and Control, ISSN 1746-8094, E-ISSN 1746-8108, Vol. 55, artikel-id 101643Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Gait symmetry has been shown to be a relevant measure for differentiating between normal and pathological gait. Although a number of symmetry methods exist, it is not clear which of these methods should be used as they have been developed using data collected from varying experimental protocols. This paper presents a comparison of state-of-the-art waveform-based symmetry methods and tests them on walking data collected from different environments. Acceleration signals collected from the ankle are used to analyse symmetry methods under different signal circumstances, such as phase shift, waveform shape difference, signal length (i.e. number of gait cycles) and gait initiation phase. The cyclogram based method is invariant to signal phase shifts, signal length and the gait initiation phase. The trend symmetry method is not affected by signal scaling and the gait initiation phase but is affected by signal length depending on the environment. Similar to the trend method, the cross-correlation symmetry method is not responsive to signal scaling and the gait initiation phase. The results of the symbolic method are not influenced by signal scaling, gait initiation and depending on the environment by the signal phase shift. From the results of the performed analysis, we recommend the trend method to gait symmetry assessment. The comparison of waveform-based symmetry methods brings new knowledge that will help in selecting an appropriate method for gait symmetry assessment under different experimental protocols. © 2019 Elsevier Ltd. All rights reserved.

  • 8.
    Gidlund, M.
    et al.
    Mid Sweden Univ, S-85170 Sundsvall, Sweden..
    Hancke, G. P.
    City Univ Hong Kong, Hong Kong, Peoples R China..
    Eldefrawy, M. H.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Åkerberg, J.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Guest Editorial: Security, Privacy, and Trust for Industrial Internet of Things2020Ingår i: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050, Vol. 16, nr 1, s. 625-628Artikel i tidskrift (Övrigt vetenskapligt)
  • 9.
    Markdahl, J.
    et al.
    Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belval, Luxembourg.
    Thunberg, Johan
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Goncalves, J.
    Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belval, Luxembourg.
    High-dimensional Kuramoto models on Stiefel manifolds synchronize complex networks almost globally2020Ingår i: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 113, artikel-id 108736Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The Kuramoto model of coupled phase oscillators is often used to describe synchronization phenomena in nature. Some applications, e.g., quantum synchronization and rigid-body attitude synchronization, involve high-dimensional Kuramoto models where each oscillator lives on the n-sphere or SO(n). These manifolds are special cases of the compact, real Stiefel manifold St(p,n). Using tools from optimization and control theory, we prove that the generalized Kuramoto model on St(p,n) converges to a synchronized state for any connected graph and from almost all initial conditions provided (p,n) satisfies p≤2/3n−1 and all oscillator frequencies are equal. This result could not have been predicted based on knowledge of the Kuramoto model in complex networks over the circle. In that case, almost global synchronization is graph dependent; it applies if the network is acyclic or sufficiently dense. This paper hence identifies a property that distinguishes many high-dimensional generalizations of the Kuramoto models from the original model. © 2019 Elsevier Ltd

  • 10.
    Bae, Juhee
    et al.
    University of Skövde, Skövde, Sweden.
    Helldin, Tove
    University of Skövde, Skövde, Sweden.
    Riveiro, Maria
    Jönköping University, Jönköping, Sweden & University of Skövde, Skövde, Sweden.
    Nowaczyk, Sławomir
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Bouguelia, Mohamed-Rafik
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Falkman, Göran
    University of Skövde, Skövde, Sweden.
    Interactive Clustering: A Comprehensive Review2020Ingår i: ACM Computing Surveys, ISSN 0360-0300, E-ISSN 1557-7341, Vol. 53, nr 1, artikel-id 1Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In this survey, 105 papers related to interactive clustering were reviewed according to seven perspectives: (1) on what level is the interaction happening, (2) which interactive operations are involved, (3) how user feedback is incorporated, (4) how interactive clustering is evaluated, (5) which data and (6) which clustering methods have been used, and (7) what outlined challenges there are. This article serves as a comprehensive overview of the field and outlines the state of the art within the area as well as identifies challenges and future research needs. © 2020 Copyright held by the owner/author(s).

  • 11.
    Farouq, Shiraz
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Byttner, Stefan
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Bouguelia, Mohamed-Rafik
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Nord, Natasa
    Department of Energy and Process Engineering, Norwegian University of Science and Technology, Trondheim, Norway.
    Gadd, Henrik
    Öresundskraft, Helsingborg, Sweden.
    Large-scale monitoring of operationally diverse district heating substations: A reference-group based approach2020Ingår i: Engineering applications of artificial intelligence, ISSN 0952-1976, E-ISSN 1873-6769, Vol. 90, artikel-id 103492Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A well-understood prior model for a District Heating (DH) substation is rarely available. Alternatively, since DH substations in a network share a common task, one can assume that they are all operationally homogeneous. Any DH substation that does not conform with the majority is an outlier, and therefore ought to be investigated. However, a DH substation can be affected by varying social and technical factors. Such details are rarely available.  Therefore, large-scale monitoring of DH substations in a network is challenging. Hence, in order to address these issues, we proposed a reference-group based monitoring approach. Herein, the operational monitoring of a DH substation, referred to as a target, is delegated to a reference-group which consists of DH substations experiencing a comparable operating regime along with the target. The approach was demonstrated on the monitoring of the return temperature variable for atypical\footnote{Here, "atypical" means that while it does not fit the definition of a normal operation, it is not faulty either and may also have some context.}  and faulty operational behavior in $778$ DH substations associated with multi-dwelling buildings. No target substation specific information related to its normal, atypical or faulty operation was used. Instead, information from the target's reference-group was leveraged to track its operational behavior. In this manner, $44$ DH substations were found where a possible deviation in the return temperature was detected earlier compared to models assuming overall operational homogeneity among the DH substations. In addition, six frequent patterns of deviating behavior in the return temperature of DH substations were identified based on the proposed reference-group based approach, which were then further corroborated by the feedback from a DH domain expert. © 2020 Elsevier Ltd

  • 12.
    Calikus, Ece
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Nowaczyk, Sławomir
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Pinheiro Sant'Anna, Anita
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Dikmen, Onur
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    No Free Lunch But A Cheaper Supper: A General Framework for Streaming Anomaly Detection2020Ingår i: Expert systems with applications, ISSN 0957-4174, E-ISSN 1873-6793Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In recent years, there has been increased research interest in detecting anomalies in temporal streaming data. A variety of algorithms have been developed in the data mining community, which can be divided into two categories (i.e., general and ad hoc). In most cases, general approaches assume the one-size-fits-all solution model where a single anomaly detector can detect all anomalies in any domain.  To date, there exists no single general method that has been shown to outperform the others across different anomaly types, use cases and datasets. On the other hand, ad hoc approaches that are designed for a specific application lack flexibility. Adapting an existing algorithm is not straightforward if the specific constraints or requirements for the existing task change. In this paper, we propose SAFARI, a general framework formulated by abstracting and unifying the fundamental tasks in streaming anomaly detection, which provides a flexible and extensible anomaly detection procedure. SAFARI helps to facilitate more elaborate algorithm comparisons by allowing us to isolate the effects of shared and unique characteristics of different algorithms on detection performance. Using SAFARI, we have implemented various anomaly detectors and identified a research gap that motivates us to propose a novel learning strategy in this work. We conducted an extensive evaluation study of 20 detectors that are composed using SAFARI and compared their performances using real-world benchmark datasets with different properties. The results indicate that there is no single superior detector that works well for every case, proving our hypothesis that "there is no free lunch" in the streaming anomaly detection world. Finally, we discuss the benefits and drawbacks of each method in-depth and draw a set of conclusions to guide future users of SAFARI.

  • 13.
    Galozy, Alexander
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Nowaczyk, Sławomir
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Pinheiro Sant'Anna, Anita
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Ohlsson, Mattias
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Lingman, Markus
    Pitfalls of medication adherence approximation through EHR and pharmacy records: Definitions, data and computation.2020Ingår i: International Journal of Medical Informatics, ISSN 1386-5056, E-ISSN 1872-8243, Vol. 136Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Abstract

    Background and purpose

    Patients’ adherence to medication is a complex, multidimensional phenomenon. Dispensation data and electronic health records are used to approximate medication-taking through refill adherence. In-depth discussions on the adverse effects of data quality and computational differences are rare. The purpose of this article is to evaluate the impact of common pitfalls when computing medication adherence using electronic health records.

    Procedures

    We point out common pitfalls associated with the data and operationalization of adherence measures. We provide operational definitions of refill adherence and conduct experiments to determine the effect of the pitfalls on adherence estimations. We performed statistical significance testing on the impact of common pitfalls using a baseline scenario as reference.

    Findings

    Slight changes in definition can significantly skew refill adherence estimates. Pickup patterns cause significant disagreement between measures and the commonly used proportion of days covered. Common data related issues had a small but statistically significant (p < 0.05) impact on population-level and significant effect on individual cases.

    Conclusion

    Data-related issues encountered in real-world administrative databases, which affect various operational definitions of refill adherence differently, can significantly skew refill adherence values, leading to false conclusions about adherence, particularly when estimating adherence for individuals.

  • 14.
    Calikus, Ece
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Self-Monitoring using Joint Human-Machine Learning: Algorithms and Applications2020Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
    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.

  • 15.
    Sheikholharam Mashhadi, Peyman
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Nowaczyk, Sławomir
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Pashami, Sepideh
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Stacked Ensemble of Recurrent Neural Networks for Predicting Turbocharger Remaining Useful Life2020Ingår i: Applied Sciences, E-ISSN 2076-3417, Vol. 10, nr 1, artikel-id 69Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Predictive Maintenance (PM) is a proactive maintenance strategy that tries to minimize a system’s downtime by predicting failures before they happen. It uses data from sensors to measure the component’s state of health and make forecasts about its future degradation. However, existing PM methods typically focus on individual measurements. While it is natural to assume that a history of measurements carries more information than a single one. This paper aims at incorporating such information into PM models. In practice, especially in the automotive domain, diagnostic models have low performance, due to a large amount of noise in the data and limited sensing capability. To address this issue, this paper proposes to use a specific type of ensemble learning known as Stacked Ensemble. The idea is to aggregate predictions of multiple models—consisting of Long Short-Term Memory (LSTM) and Convolutional-LSTM—via a meta model, in order to boost performance. Stacked Ensemble model performs well when its base models are as diverse as possible. To this end, each such model is trained using a specific combination of the following three aspects: feature subsets, past dependency horizon, and model architectures. Experimental results demonstrate benefits of the proposed approach on a case study of heavy-duty truck turbochargers. © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). 

  • 16.
    Jam, Reza Jafari
    et al.
    Lund Univ, Div Solid State Phys & NanoLund, Box 118, SE-21100 Lund, Sweden..
    Persson, Axel R.
    Lund Univ, Centr & Anal & Synth & NanoLund, POB 124, SE-21100 Lund, Sweden..
    Barrigon, Enrique
    Lund Univ, Div Solid State Phys & NanoLund, Box 118, SE-21100 Lund, Sweden..
    Heurlin, Magnus
    Lund Univ, Div Solid State Phys & NanoLund, Box 118, SE-21100 Lund, Sweden..
    Geijselaers, Irene
    Lund Univ, Div Solid State Phys & NanoLund, Box 118, SE-21100 Lund, Sweden..
    Gomez, Victor J.
    Lund Univ, Div Solid State Phys & NanoLund, Box 118, SE-21100 Lund, Sweden..
    Hultin, Olof
    RISE Res Inst Sweden, Scheelevagen 17, S-22370 Lund, Sweden..
    Samuelson, Lars
    Lund Univ, Div Solid State Phys & NanoLund, Box 118, SE-21100 Lund, Sweden..
    Borgstrom, Magnus T.
    Lund Univ, Div Solid State Phys & NanoLund, Box 118, SE-21100 Lund, Sweden..
    Pettersson, Håkan
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Tillämpad matematik och fysik (MPE-lab). Lund Univ, Div Solid State Phys & NanoLund, Box 118, SE-21100 Lund, Sweden.;Halmstad Univ, Sch Informat Technol, Box 823, S-30118 Halmstad, Sweden..
    Template-assisted vapour-liquid-solid growth of InP nanowires on (001) InP and Si substrates2020Ingår i: Nanoscale, ISSN 2040-3364, E-ISSN 2040-3372, Vol. 12, nr 2, s. 888-894Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We report on the synthesis of vertical InP nanowire arrays on (001) InP and Si substrates using template-assisted vapour-liquid-solid growth. A thick silicon oxide layer was first deposited on the substrates. The samples were then patterned by electron beam lithography and deep dry etching through the oxide layer down to the substrate surface. Gold seed particles were subsequently deposited in the holes of the pattern by the use of pulse electrodeposition. The subsequent growth of nanowires by the vapour-liquid-solid method was guided towards the [001] direction by the patterned oxide template, and displayed a high growth yield with respect to the array of holes in the template. In order to confirm the versatility and robustness of the process, we have also demonstrated guided growth of InP nanowire p-n junctions and InP/InAs/InP nanowire heterostructures on (001) InP substrates. Our results show a promising route to monolithically integrate III-V nanowire heterostructure devices with commercially viable (001) silicon platforms.

  • 17.
    Miyasaka, Hiroyuki
    et al.
    Fujita Hlth Univ, Dept Rehabil, Nanakuri Mem Hosp, Tsu, Mie, Japan..
    Kondo, Izumi
    Fujita Hlth Univ, Fujita Mem Nanakuri Inst, Dept Rehabil, Tsu, Mie, Japan.;Natl Ctr Geriatr & Gerontol, Dept Rehabil Med, Obu, Aichi, Japan..
    Yamamura, Chihiro
    Fujita Hlth Univ, Dept Rehabil, Nanakuri Mem Hosp, Tsu, Mie, Japan..
    Fujita, Naoko
    Fujita Hlth Univ, Dept Rehabil, Nanakuri Mem Hosp, Tsu, Mie, Japan.;Kariya Toyota Gen Hosp, Takahama Branch Hosp, Kariya, Aichi, Japan..
    Orand, Abbas
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Sonoda, Shigeru
    Fujita Hlth Univ, Sch Med, Dept Rehabil Med 2, Tsu, Mie, Japan..
    The quantification of task-difficulty of upper limb motor function skill based on Rasch analysis2020Ingår i: Topics in Stroke Rehabilitation, ISSN 1074-9357, E-ISSN 1945-5119, Vol. 27, nr 1, s. 49-56Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: The degree of difficulty of skills of paretic upper limbs in daily life has not been investigated. Objective: To determine the internal validity and level of difficulty of items of the Functional Skills Measure After Paralysis (FSMAP), which can be used to evaluate the functional skills of daily living for stroke patients. Method: A total of 105 first-stroke patients were assessed using the FSMAP. The evaluation system consists of 65 items in 15 categories. We examined the internal validity and level of difficulty of these items using Rasch analysis. In this study, an item with either infit or outfit of >= 1.5 was defined as underfit. Results: Rasch analysis showed that 8 items were underfit. The highest infit and outfit logits were 2.47 for "Trouser donning/doffing" and 8.44 for "Paper manipulation". "Shirt donning/doffing" was the easiest item and "Coin manipulation" was the most difficult, with difficulty logits of -35.8 and 41.5, respectively. Conclusion: The therapist can confirm items that the patient can or cannot perform. By understanding the level of difficulty of each item, the most appropriate functional skill to focus on acquiring next can be identified.

  • 18.
    Ni, Yuanzhi
    et al.
    School of Internet of Things Engineering, Jiangnan University, Wuxi, China.
    Cai, Lin
    Department of Electrical and Computer Engineering, University of Victoria, Victoria, Canada.
    He, Jianping
    Department of Automation, Shanghai Jiao Tong University, Shanghai, China.
    Vinel, Alexey
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES). Department of Electrical Engineering, Western Norway University of Applied Sciences, Bergen, Norway.
    Li, Yue
    Department of Electrical and Computer Engineering, University of Victoria, Victoria, Canada.
    Mosavat-Jahromi, Hamed
    Department of Electrical and Computer Engineering, University of Victoria, Victoria, Canada.
    Pan, Jianping
    Department of Computer Science, University of Victoria, Victoria, Canada.
    Toward Reliable and Scalable Internet-of-Vehicles: Performance Analysis and Resource Management2020Ingår i: Proceedings of the IEEE, ISSN 0018-9219, E-ISSN 1558-2256, Vol. 108, nr 2, s. 325-340Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Reliable and scalable wireless transmissions for Internet-of-Vehicles (IoV) are technically challenging. Each vehicle, from driver-assisted to automated one, will generate a flood of information, up to thousands of times of that by a person. Vehicle density may change drastically over time and location. Emergency messages and real-time cooperative control messages have stringent delay constraints while infotainment applications may tolerate a certain degree of latency. On a congested road, thousands of vehicles need to exchange information badly, only to find that service is limited due to the scarcity of wireless spectrum. Considering the service requirements of heterogeneous IoV applications, service guarantee relies on an in-depth understanding of network performance and innovations in wireless resource management leveraging the mobility of vehicles, which are addressed in this article. For single-hop transmissions, we study and compare the performance of vehicle-to-vehicle (V2V) beacon broadcasting using random access-based (IEEE 802.11p) and resource allocation-based (cellular vehicle-to-everything) protocols, and the enhancement strategies using distributed congestion control. For messages propagated in IoV using multihop V2V relay transmissions, the fundamental network connectivity property of 1-D and 2-D roads is given. To have a message delivered farther away in a sparse, disconnected V2V network, vehicles can carry and forward the message, with the help of infrastructure if possible. The optimal locations to deploy different types of roadside infrastructures, including storage-only devices and roadside units with Internet connections, are analyzed. © 2019 IEEE

  • 19.
    Dahl, Oskar
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Johansson, Fredrik
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Khoshkangini, Reza
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Pashami, Sepideh
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Nowaczyk, Sławomir
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Pihl, Claes
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Understanding Association Between Logged Vehicle Data and Vehicle Marketing Parameters - Using Clustering and Rule-Based Machine Learning2020Konferensbidrag (Refereegranskat)
    Abstract [en]

    Trucks are designed, configured and marketed for various working environments. There lies a concern whether trucks are used as intended by the manufacturer, as usage may impact the longevity, efficiency and productivity of the trucks.

    In this paper we propose a framework that aims to extract costumers' vehicle behaviours from LVD in order to evaluate whether they align with vehicle configurations, so-called GTA parameters. GMMs are employed to cluster and classify various vehicle behaviors from the LVD. RBML was applied on the clusters to examine whether vehicle behaviors follow the GTA configuration. Particularly, we propose an approach based on studying associations that is able to extract insights on whether the trucks are used as intended. Experimental results shown that while for the vast majority of the trucks' behaviors seemingly follows their GTA configuration, there are also interesting outliers that warrant further analysis.

  • 20.
    Fan, Yuantao
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Wisdom of the Crowd for Fault Detection and Prognosis2020Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    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. 

  • 21.
    Gholami Shahbandi, Saeed
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Magnusson, Martin
    Örebro University, Örebro, Sweden.
    2D Map Alignment With Region Decomposition2019Ingår i: Autonomous Robots, ISSN 0929-5593, E-ISSN 1573-7527, Vol. 43, nr 5, s. 1117-1136Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In many applications of autonomous mobile robots the following problem is encountered. Two maps of the same environment are available, one a prior map and the other a sensor map built by the robot. To benefit from all available information in both maps, the robot must find the correct alignment between the two maps. There exist many approaches to address this challenge, however, most of the previous methods rely on assumptions such as similar modalities of the maps, same scale, or existence of an initial guess for the alignment. In this work we propose a decomposition-based method for 2D spatial map alignment which does not rely on those assumptions. Our proposed method is validated and compared with other approaches, including generic data association approaches and map alignment algorithms. Real world examples of four different environments with thirty six sensor maps and four layout maps are used for this analysis. The maps, along with an implementation of the method, are made publicly available online. © 2018, The Author(s).

  • 22.
    Friel, Ross
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Gerling-Gedin, Maria
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Nilsson, Emil
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Tillämpad matematik och fysik (MPE-lab). Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Inbyggda system (CERES).
    Andreasson, Björn Pererik
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    3D Printed Radar Lenses with Anti-Reflective Structures2019Ingår i: Designs, E-ISSN 2411-9660, Vol. 3, nr 2, artikel-id 28Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: The purpose of this study was to determine if 3D printed lenses with wavelength specific anti-reflective (AR) surface structures would improve beam intensity and thus radar efficiency for a Printed Circuit Board (PCB)-based 60 GHz radar. This would have potential for improved low-cost radar lenses for the consumer product market. Methods: A hyperbolic lens was designed in 3D Computer Aided Design (CAD) software and was then modified with a wavelength specified AR structure. Electromagnetic computer simulation was performed on both the ‘smooth’ and ‘AR structure’ lenses and compared to actual 60 GHz radar measurements of 3D printed polylactic acid (PLA) lenses. Results: The simulation results showed an increase of 10% in signal intensity of the AR structure lens over the smooth lens. Actual measurement showed an 8% increase in signal of the AR structure lens over the smooth lens. Conclusions: Low cost and readily available Fused Filament Fabrication (FFF) 3D printing has been shown to be capable of printing an AR structure coated hyperbolic lens for millimeter wavelength radar applications. These 3D Printed AR structure lenses are effective in improving radar measurements over non-AR structure lenses.

  • 23.
    Savas, Süleyman
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Ul-Abdin, Zain
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Nordström, Tomas
    RISE Research Institutes of Sweden, Gothenburg, Sweden.
    A Configurable Two Dimensional Mesh Network-on-Chip Implementation in Chisel2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    On-chip communication plays a significant role in the performance of manycore architectures. Therefore, they require a proper on-chip communication infrastructure that can scale with the number of the cores. As a solution, network-on-chip structures have emerged and are being used.

    This paper presents description of a two dimensional mesh network-on-chip router and a network interface, which are implemented in Chisel to be integrated to the rocket chip generator that generates RISC-V (rocket) cores. The router is implemented in VHDL as well and the two implementations are verified and compared.

    Hardware resource usage and performance of different sized networks are analyzed. The implementations are synthesized for a Xilinx Ultrascale FPGA via Xilinx tools for the hardware resource usage and clock frequency results. The performance results including latency and throughput measurements with different traffic patterns, are collected with cycle accurate emulations. 

    The implementations in Chisel and VHDL do not show a significant difference. Chisel requires around 10% fewer lines of code, however, the difference in the synthesis results is negligible. Our latency result are better than the majority of the other studies. The other results such as hardware usage, clock frequency, and throughput are competitive when compared to the related works.

  • 24.
    Calikus, Ece
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Nowaczyk, Sławomir
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Pinheiro Sant'Anna, Anita
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Gadd, Henrik
    Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap. Öresundskraft, Helsingborg, Sweden.
    Werner, Sven
    Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Rydberglaboratoriet för tillämpad naturvetenskap (RLAS).
    A data-driven approach for discovering heat load patterns in district heating2019Ingår i: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 252, artikel-id 113409Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Understanding the heat usage of customers is crucial for effective district heating operations and management. Unfortunately, existing knowledge about customers and their heat load behaviors is quite scarce. Most previous studies are limited to small-scale analyses that are not representative enough to understand the behavior of the overall network. In this work, we propose a data-driven approach that enables large-scale automatic analysis of heat load patterns in district heating networks without requiring prior knowledge. Our method clusters the customer profiles into different groups, extracts their representative patterns, and detects unusual customers whose profiles deviate significantly from the rest of their group. Using our approach, we present the first large-scale, comprehensive analysis of the heat load patterns by conducting a case study on many buildings in six different customer categories connected to two district heating networks in the south of Sweden. The 1222 buildings had a total floor space of 3.4 million square meters and used 1540 TJ heat during 2016. The results show that the proposed method has a high potential to be deployed and used in practice to analyze and understand customers’ heat-use habits. © 2019 Calikus et al. Published by Elsevier Ltd.

  • 25.
    Khan, Taha
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Lundgren, Lina
    Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Rydberglaboratoriet för tillämpad naturvetenskap (RLAS). Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Järpe, Eric
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Olsson, M. Charlotte
    Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Rydberglaboratoriet för tillämpad naturvetenskap (RLAS).
    Wiberg, Pelle
    Raytelligence AB, Halmstad, Sweden.
    A Novel Method for Classification of Running Fatigue Using Change-Point Segmentation2019Ingår i: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 19, nr 21, artikel-id 4729Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Blood lactate accumulation is a crucial fatigue indicator during sports training. Previous studies have predicted cycling fatigue using surface-electromyography (sEMG) to non-invasively estimate lactate concentration in blood. This study used sEMG to predict muscle fatigue while running and proposes a novel method for the automatic classification of running fatigue based on sEMG. Data were acquired from 12 runners during an incremental treadmill running-test using sEMG sensors placed on the vastus-lateralis, vastus-medialis, biceps-femoris, semitendinosus, and gastrocnemius muscles of the right and left legs. Blood lactate samples of each runner were collected every two minutes during the test. A change-point segmentation algorithm labeled each sample with a class of fatigue level as (1) aerobic, (2) anaerobic, or (3) recovery. Three separate random forest models were trained to classify fatigue using 36 frequency, 51 time-domain, and 36 time-event sEMG features. The models were optimized using a forward sequential feature elimination algorithm. Results showed that the random forest trained using distributive power frequency of the sEMG signal of the vastus-lateralis muscle alone could classify fatigue with high accuracy. Importantly for this feature, group-mean ranks were significantly different (p < 0.01) between fatigue classes. Findings support using this model for monitoring fatigue levels during running. © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

  • 26.
    Aramrattana, Maytheewat
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES). The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    Larsson, Tony
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Jansson, Jonas
    The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    Nåbo, Arne
    The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    A simulation framework for cooperative intelligent transport systems testing and evaluation2019Ingår i: Transportation Research Part F: Traffic Psychology and Behaviour, ISSN 1369-8478, E-ISSN 1873-5517, Vol. 61, s. 268-280Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Connected and automated driving in the context of cooperative intelligent transport systems (C-ITS) is an emerging area in transport systems research. Interaction and cooperation between actors in transport systems are now enabled by the connectivity by means of vehicle-to-vehicle and vehicle-to-infrastructure (V2X) communication. To ensure the goals of C-ITS, which are safer and more efficient transport systems, testing and evaluation are required before deployment of C-ITS applications. Therefore, this paper presents a simulation framework—consisting of driving-, traffic-, and network-simulators—for testing and evaluation of C-ITS applications. Examples of cooperative adaptive cruise control (CACC) applications are presented, and are used as test cases for the simulation framework as well as to elaborate on potential use cases of it. Challenges from combining the simulators into one framework, and limitations are reported and discussed. Finally, the paper concludes with future development directions, and applications of the simulation framework in testing and evaluation of C-ITS. © 2017 Elsevier Ltd. All rights reserved.

  • 27.
    Pejner, Norell Margaretha
    et al.
    Högskolan i Halmstad, Akademin för hälsa och välfärd, Centrum för forskning om välfärd, hälsa och idrott (CVHI).
    Ourique de Morais, Wagner
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Lundström, Jens
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Laurell, Hélène
    Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Centrum för innovations-, entreprenörskaps- och lärandeforskning (CIEL).
    Skärsäter, Ingela
    Högskolan i Halmstad, Akademin för hälsa och välfärd, Centrum för forskning om välfärd, hälsa och idrott (CVHI).
    A Smart Home System for Information Sharing, Health Assessments, and Medication Self-Management for Older People: Protocol for a Mixed-Methods Study2019Ingår i: JMIR Research Protocols, ISSN 1929-0748, E-ISSN 1929-0748, Vol. 8, nr 4, artikel-id e12447Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: Older adults often want to stay in a familiar place, such as their home, as they get older. This so-called aging in place, which may involve support from relatives or care professionals, can promote older people’s independence and well-being. The combination of aging and disease, however, can lead to complex medication regimes, and difficulties for care providers in correctly assessing the older person's health. In addition, the organization of the health care is fragmented, which makes it difficult for health professionals to encourage older people to participate in their care. It is also a challenge to perform adequate health assessment and appropriate communication between health care professionals.

    Objective: The purpose of this paper is to describe the design for an integrated home-based system that can acquire and compile health-related evidence for guidance and information sharing among care providers and care receivers in order to support and promote medication self-management among older people.

    Methods: The authors used a participatory design (PD) approach for this mixed-method project, which was divided into four phases: Phase I, Conceptualization, consisted of the conceptualization of a system to support medication self- management, objective health assessments, and communication between health care professionals. Phase II, Development of a System, consisted of building and bringing together the conceptualized systems from phase I. Phases III (pilot study) and IV (a full-scale study) are described briefly.

    Results: Our participants in phase I were people who were involved in some way in the care of older adults, and included older adults themselves, relatives of older adults, care professionals, and industrial partners. With input from phase I participants, we identified two relevant concepts for promoting medication self-management, both of which related to systems that participants believed could provide guidance for the older adults themselves, relatives of older adults, and care professionals. The system will also encourage information sharing between care providers and care receivers. The first is the concept of the Intelligent Friendly Home (IAFH), defined as an integrated residential system that evolves to sense, reason and act in response to individual needs, preferences and behaviors as these change over time. The second concept is the MedOP system, a system that would be supported by the IAFH, and which consists of three related components: one that assess health behaviors, another that communicates health data, and a third that promotes medication self-management.

    Conclusions: The participants in this project were older adults, relatives of older adults, care professionals, and our industrial partners. With input from the participants, we identified two main concepts that could comprise a system for health assessment, communication and medication self-management: the Intelligent Friendly Home (IAFH), and the MedOP system. These concepts will be tested in this study to determine whether they can facilitate and promote medication self-management in older people. © The authors. All rights reserved. 

  • 28.
    Alonso-Fernandez, Fernando
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Farrugia, Reuben A.
    University of Malta, Msida, Malta.
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Fierrez, Julian
    Universidad Autonoma de Madrid, Madrid, Spain.
    Gonzalez-Sosa, Ester
    Nokia Bell-Labs, Madrid, Spain.
    A Survey of Super-Resolution in Iris Biometrics with Evaluation of Dictionary-Learning2019Ingår i: IEEE Access, E-ISSN 2169-3536, Vol. 7, s. 6519-6544Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The lack of resolution has a negative impact on the performance of image-based biometrics. While many generic super-resolution methods have been proposed to restore low-resolution images, they usually aim to enhance their visual appearance. However, an overall visual enhancement of biometric images does not necessarily correlate with a better recognition performance. Reconstruction approaches need thus to incorporate specific information from the target biometric modality to effectively improve recognition performance. This paper presents a comprehensive survey of iris super-resolution approaches proposed in the literature. We have also adapted an Eigen-patches reconstruction method based on PCA Eigentransformation of local image patches. The structure of the iris is exploited by building a patch-position dependent dictionary. In addition, image patches are restored separately, having their own reconstruction weights. This allows the solution to be locally optimized, helping to preserve local information. To evaluate the algorithm, we degraded high-resolution images from the CASIA Interval V3 database. Different restorations were considered, with 15 × 15 pixels being the smallest resolution evaluated. To the best of our knowledge, this is among the smallest resolutions employed in the literature. The experimental framework is complemented with six publicly available iris comparators, which were used to carry out biometric verification and identification experiments. Experimental results show that the proposed method significantly outperforms both bilinear and bicubic interpolation at very low-resolution. The performance of a number of comparators attain an impressive Equal Error Rate as low as 5%, and a Top-1 accuracy of 77-84% when considering iris images of only 15 × 15 pixels. These results clearly demonstrate the benefit of using trained super-resolution techniques to improve the quality of iris images prior to matching. © 2018, Emerald Publishing Limited.

  • 29.
    Mendoza-Palechor, Fabio
    et al.
    Department of Electronic and Systems Engineering, Universidad de la Costa, CUC, Barranquilla, Colombia.
    Menezes, Maria Luiza Recena
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Pinheiro Sant'Anna, Anita
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Ortiz-Barrios, Miguel
    Department of Industrial Management, Agroindustry and Operations, Universidad de la Costa, CUC, Barranquilla, Colombia.
    Samara, Anas
    School of Computing, Computer Science Research Institute, Ulster University, Belfast, United Kingdom.
    Galway, Leo
    School of Computing, Computer Science Research Institute, Ulster University, Belfast, United Kingdom.
    Affective recognition from EEG signals: an integrated data-mining approach2019Ingår i: Journal of Ambient Intelligence and Humanized Computing, ISSN 1868-5137, E-ISSN 1868-5145, Vol. 10, nr 10, s. 3955-3974Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Emotions play an important role in human communication, interaction, and decision making processes. Therefore, considerable efforts have been made towards the automatic identification of human emotions, in particular electroencephalogram (EEG) signals and Data Mining (DM) techniques have been then used to create models recognizing the affective states of users. However, most previous works have used clinical grade EEG systems with at least 32 electrodes. These systems are expensive and cumbersome, and therefore unsuitable for usage during normal daily activities. Smaller EEG headsets such as the Emotiv are now available and can be used during daily activities. This paper investigates the accuracy and applicability of previous affective recognition methods on data collected with an Emotiv headset while participants used a personal computer to fulfill several tasks. Several features were extracted from four channels only (AF3, AF4, F3 and F4 in accordance with the 10–20 system). Both Support Vector Machine and Naïve Bayes were used for emotion classification. Results demonstrate that such methods can be used to accurately detect emotions using a small EEG headset during a normal daily activity. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.

  • 30.
    Lyamin, Nikita
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Bellalta, Boris
    Universitat Pompeu Fabra, Barcelona, Catalunya, Spain.
    Vinel, Alexey
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Age-of-Information-Aware Decentralized Congestion Control in VANETs2019Ingår i: IEEE Networking Letters, E-ISSN 2576-3156Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Decentralized Congestion Control (DCC) is one the central components of inter-vehicular communications protocol stack enabling Cooperative Intelligent Transportation System (C-ITS). In this letter we first present an analytical framework that allows to tune parameters of the DCC algorithm specified by ETSI. Then we suggest two approaches to optimize the DCC configuration using our framework. Finally, we evaluate the performance of the proposed approaches using detailed simulation experiments. We demonstrate that proposed approaches are able to control channel busy ratio stably, while proposed analytical model precisely estimates application level metrics. © 2019 IEEE

  • 31.
    Khan, Taha
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Lundgren, Lina
    Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Rydberglaboratoriet för tillämpad naturvetenskap (RLAS).
    Anderson, David G.
    Donald Gordon Brain and Mind Centre, Johannesburg, South Africa & School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa.
    Novak, Irena
    Aquatic Rehabilitation Center, University of Johannesburg, Johannesburg, South Africa.
    Dougherty, Mark
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Verikas, Antanas
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Pavel, Misha
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Jimison, Holly
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Nowaczyk, Sławomir
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Aharonson, Vered
    School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa.
    Assessing Parkinson's disease severity using speech analysis in non-native speakers2019Ingår i: Computer speech & language (Print), ISSN 0885-2308, E-ISSN 1095-8363, Vol. 61, artikel-id 101047Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: Speech disorder is a common manifestation of Parkinson's disease with two main symptoms, dysprosody and dysphonia. Previous research studying objective measures of speech symptoms involved patients and examiners who were native language speakers. Measures such as cepstral separation difference (CSD) features to quantify dysphonia and dysprosody accurately distinguish the severity of speech impairment. Importantly CSD, together with other speech features, including Mel-frequency coefficients, fundamental-frequency variation, and spectral dynamics, characterize speech intelligibility in PD. However, non-native language speakers transfer phonological rules of their mother language that tamper speech assessment.

    Objectives: This paper explores CSD's capability: first, to quantify dysprosody and dysphonia of non-native language speakers, Parkinson patients and controls, and secondly, to characterize the severity of speech impairment when Parkinson's dysprosody accompanies non-native linguistic dysprosody.

    Methods: CSD features were extracted from 168 speech samples recorded from 19 healthy controls, 15 rehabilitated and 23 not-rehabilitated Parkinson patients in three different clinical speech tests based on Unified Parkinson's disease rating scale motor-speech examination. Statistical analyses were performed to compare groups using analysis of variance, intraclass correlation, and Guttman correlation coefficient µ2. Random forests were trained to classify the severity of speech impairment using CSD and the other speech features. Feature importance in classification was determined using permutation importance score.

    Results: Results showed that the CSD feature describing dysphonia was uninfluenced by non-native accents, strongly correlated with the clinical examination (µ2>0.5), and significantly discriminated between the healthy, rehabilitated, and not-rehabilitated patient groups based on the severity of speech symptoms. However, the feature describing dysprosody did not correlate with the clinical examination but significantly distinguished the groups. The classification model based on random forests and selected features characterized the severity of speech impairment of non-native language speakers with high accuracy. Importantly, the permutation importance score of the CSD feature representing dysphonia was the highest compared to other features. Results showed a strong negative correlation (µ2<-0.5) between L-dopa administration and the CSD features.

    Conclusions: Although non-native accents reduce speech intelligibility, the CSD features can accurately characterize speech impairment, which is not always possible in the clinical examination. Findings support using CSD for monitoring Parkinson's disease.

    © 2019 Elsevier Ltd. All rights reserved.

  • 32.
    Pink, Sarah
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS). RMIT University, Melbourne, Australia.
    Fors, Vaike
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Glöss, Mareike
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Automated futures and the mobile present: In-car video ethnographies2019Ingår i: Ethnography, ISSN 1466-1381, E-ISSN 1741-2714, Vol. 20, nr 1, s. 88-107Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    New technological possibilities associated with autonomous driving (AD) cars are generating new questions and imaginaries about automated futures. In this article we advance a theoretical-methodological approach towards researching this context based in design anthropological theory and sensory ethnographic practice. In doing so we explain and discuss the findings of an in-car video ethnography study designed to investigate the usually unspoken and not necessarily visible elements of car-based mobility. Such an approach is needed, we argue, both in order to inform a research agenda that is capable of addressing the emergence of automated vehicles specifically, as well as in preparation for understanding the implications of automation more generally as human mobility is increasingly entangled with automated technologies and the future imaginaries associated with them. © The British Association of Hand Therapists Ltd 2017.

  • 33.
    Cooney, Martin
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Ong, Linda
    I+ srl, Florence, Italy.
    Pashami, Sepideh
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Järpe, Eric
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Ashfaq, Awais
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Avoiding Improper Treatment of Dementia Patients by Care Robots2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    The phrase “most cruel and revolting crimes” has been used to describe some poor historical treatment of vulnerable impaired persons by precisely those who should have had the responsibility of protecting and helping them. We believe we might be poised to see history repeat itself, as increasingly humanlike aware robots become capable of engaging in behavior which we would consider immoral in a human–either unknowingly or deliberately. In the current paper we focus in particular on exploring some potential dangers affecting persons with dementia (PWD), which could arise from insufficient software or external factors, and describe a proposed solution involving rich causal models and accountability measures: Specifically, the Consequences of Needs-driven Dementia-compromised Behaviour model (C-NDB) could be adapted to be used with conversation topic detection, causal networks and multi-criteria decision making, alongside reports, audits, and deterrents. Our aim is that the considerations raised could help inform the design of care robots intended to support well-being in PWD.

  • 34.
    Orand, Abbas
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Erdal Aksoy, Eren
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Miyasaka, Hiroyuki
    Department of Rehabilitation, Fujita Health University, Nanakuri Memorial Hospital, Tsu, Japan.
    Weeks Levy, Carolyn
    Schools of Mechatronics Systems Engineering and Engineering Science, Simon Fraser University, Surrey, Canada.
    Zhang, Xin
    Schools of Mechatronics Systems Engineering and Engineering Science, Simon Fraser University, Surrey, Canada.
    Menon, Carlo
    Schools of Mechatronics Systems Engineering and Engineering Science, Simon Fraser University, Surrey, Canada.
    Bilateral Tactile Feedback-Enabled Training for Stroke Survivors Using Microsoft KinectTM2019Ingår i: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 19, nr 16, artikel-id 3474Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Rehabilitation and mobility training of post-stroke patients is crucial for their functional recovery. While traditional methods can still help patients, new rehabilitation and mobility training methods are necessary to facilitate better recovery at lower costs. In this work, our objective was to design and develop a rehabilitation training system targeting the functional recovery ofpost-stroke users with high efficiency. To accomplish this goal, we applied a bilateral training method, which proved to be effective in enhancing motor recovery using tactile feedback for the training. One participant with hemiparesis underwent six weeks of training. Two protocols, “contralater alarm matching” and “both arms moving together”, were carried out by the participant. Each ofthe protocols consisted of “shoulder abduction” and “shoulder flexion” at angles close to 30 and 60 degrees. The participant carried out 15 repetitions at each angle for each task. For example, in the“contralateral arm matching” protocol, the unaffected arm of the participant was set to an angle close to 30 degrees. He was then requested to keep the unaffected arm at the specified angle while trying to match the position with the affected arm. Whenever the two arms matched, a vibration was given on both brachialis muscles. For the “both arms moving together” protocol, the two arms were first set approximately to an angle of either 30 or 60 degrees. The participant was asked to return both arms to a relaxed position before moving both arms back to the remembered specified angle.The arm that was slower in moving to the specified angle received a vibration. We performed clinical assessments before, midway through, and after the training period using a Fugl-Meyer assessment (FMA), a Wolf motor function test (WMFT), and a proprioceptive assessment. For the assessments, two ipsilateral and contralateral arm matching tasks, each consisting of three movements (shoulder abduction, shoulder flexion, and elbow flexion), were used. Movements were performed at two angles, 30 and 60 degrees. For both tasks, the same procedure was used. For example, in the case of the ipsilateral arm matching task, an experimenter positioned the affected arm of the participant at 30 degrees of shoulder abduction. The participant was requested to keep the arm in that positionfor ~5 s before returning to a relaxed initial position. Then, after another ~5-s delay, the participant moved the affected arm back to the remembered position. An experimenter measured this shoulder abduction angle manually using a goniometer. The same procedure was repeated for the 60 degree angle and for the other two movements. We applied a low-cost Kinect to extract the participant’s body joint position data. Tactile feedback was given based on the arm position detected by the Kinect sensor. By using a Kinect sensor, we demonstrated the feasibility of the system for the training ofa post-stroke user. The proposed system can further be employed for self-training of patients at home. The results of the FMA, WMFT, and goniometer angle measurements showed improvements in several tasks, suggesting a positive effect of the training system and its feasibility for further application for stroke survivors’ rehabilitation. © 2019 by the authors.

  • 35.
    Ghazawneh, Ahmad
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS). IT University of Copenhagen, Copenhagen, Denmark.
    Blockchain in the Middle East: Challenges and Opportunities2019Ingår i: MCIS 2019 Proceedings, Naples: Association for Information Systems, 2019, artikel-id 34Konferensbidrag (Refereegranskat)
    Abstract [en]

    The Blockchain technology has attracted a huge attention from both industry and academia. Despite the fact that there are great potentials of the blockchain, it is facing a number of technical challenges and social challenges. There is a substantial body of literature on the technical challenges and a limited number of researches that addressed the social challenges and opportunities of blockchain. Drawing on a multiple case study of twenty-one firms from six different Middle Eastern countries we synthesize the blockchain technology and IT in the Middle East literature to understand the challenges and opportunities of that technology in the Middle East. Our study identifies a classification of challenges and opportunities: Fine-tune challenges, estrangement challenges, sprint opportunities and act on opportunities and four associated factors: regulation, education, collaboration and culture. In doing this, our research extends and complements existing blockchain research and contributes to the IT literature in the Middle East.

  • 36.
    Bocharova, Irina
    et al.
    Department of Information Systems, St. Petersburg University of Information Technologies, Mechanics and Optics, St.-Petersburg, Russia & Institute of Computer Science, University of Tartu, Estonia.
    Kudryashov, Boris
    Department of Information Systems, St. Petersburg University of Information Technologies, Mechanics and Optics, St.-Petersburg, Russia & Institute of Computer Science, University of Tartu, Estonia.
    Rabi, Maben
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Lyamin, Nikita
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Dankers, Wouter
    Volvo GTT, Goteborg, Sweden.
    Frick, Erik
    AstaZero, Hällered, Sandhult, Sweden.
    Vinel, Alexey
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES). Department of Electrical Engineering, Western Norway University of Applied Sciences, Bergen, Norway.
    Characterizing Packet Losses in Vehicular Networks2019Ingår i: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 68, nr 9, s. 8347-8358Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    To enable testing and performance evaluation of new connected and autonomous driving functions, it is important to characterize packet losses caused by degradation in vehicular (V2X) communication channels. In this paper we suggest an approach to constructing packet loss models based on the socalled Pseudo-Markov chains (PMC). The PMC based model needs only short training sequences, has low computational complexity, and yet provides more precise approximations than known techniques. We show how to learn PMC models from either empirical records of packet receptions, or from analytical models of fluctuations in the received signal strength. In particular, we validate our approach by applying it on (i) V2X packet reception data collected from an active safety test run, which used the LTE network of the AstaZero automotive testing site in Sweden, and (ii) variants of the Rician fading channel models corresponding to two models of correlations of packet losses. We also show that initializing the Baum-Welch algorithm with a second order PMC model leads to a high accuracy model. © 2019 IEEE.

  • 37.
    Hilt, Benoît
    et al.
    University of Haute Alsace, Mulhouse, Colmar, France.
    Berbineau, MarionFrench Institute of Science and Technology, Spatial Planning, Development, and Networks, Villeneuve d'Ascq, France.Vinel, AlexeyHögskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).Jonsson, MagnusHögskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).Pirovano, AlainÉcole Nationale de l’Aviation Civile, Toulouse, France.
    Communication Technologies for Vehicles: 14th International Workshop, Nets4Cars/Nets4Trains/Nets4Aircraft 2019, Colmar, France, May 16–17, 2019, Proceedings2019Proceedings (redaktörskap) (Refereegranskat)
  • 38.
    Varshosaz, Mahsa
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Mousavi, Mohammad Reza
    Department of Informatics, University of Leicester, Leicester, United Kingdom.
    Comparative Expressiveness of Product Line Calculus of Communicating Systems and 1-Selecting Modal Transition Systems2019Ingår i: SOFSEM 2019: Theory and Practice of Computer Science / [ed] Barbara Catania, Rastislav Královič, Jerzy Nawrocki & Giovanni Pighizzini, Cham: Springer, 2019, s. 490-503Konferensbidrag (Refereegranskat)
    Abstract [en]

    Product line calculus of communicating systems (PL-CCSs) is a process calculus proposed to model the behavior of software product lines. Modal transition systems (MTSs) are also used to model variability in behavioral models. MTSs are known to be strictly less expressive than PL-CCS. In this paper, we show that the extension of MTSs with hyper transitions by Fecher and Schmidt, called 1-selecting modal transition systems (1MTSs), closes this expressiveness gap. To this end, we propose a novel notion of refinement for 1MTSs that makes them more suitable for specifying variability for software product lines and prove its various essential properties. © Springer Nature Switzerland AG 2019

  • 39.
    Khoshkangini, Reza
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Pini, M. S.
    Department of Information Engineering, University of Padova, Padua, Italy.
    Rossi, F.
    IBM T. J. Watson Research Center, Yorktown Heights, NY, United States.
    Constructing CP-Nets from Users Past Selection2019Ingår i: Lecture Notes in Computer Science: Volume 11919 LNAI, Springer , 2019, s. 130-142Konferensbidrag (Refereegranskat)
    Abstract [en]

    Although recommender systems have been significantly developed for providing customized services to users in various domains, they still have some limitations regarding the extraction of users’ conditional preferences from their past selections when they are in a dynamic context. We propose a framework to automatically extract and learn users’ conditional and qualitative preferences in a gamified system taking into consideration the players’ past behaviour, without asking any information from the players. To do that, we construct CP-nets modeling users preferences via a procedure that employs multiple Information Criterion score functions within an heuristic algorithm to learn a Bayesian network. The approach has been validated experimentally in the challenge recommendation domain in an urban mobility gamified system. © 2019, Springer Nature Switzerland AG.

  • 40.
    Zhang, Ke
    et al.
    University of Electronic Science and Technology of China, Chengdu, China.
    Mao, Yuming
    University of Electronic Science and Technology of China, Chengdu, China.
    Leng, Supeng
    University of Electronic Science and Technology of China, Chengdu, China.
    Maharjan, Sabita
    Simula Research Laboratory, Fornebu, Norway & University of Oslo, Oslo, Norway.
    Vinel, Alexey
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Zhang, Yan
    University of Oslo, Oslo, Norway.
    Contract-theoretic Approach for Delay Constrained Offloading in Vehicular Edge Computing Networks2019Ingår i: Mobile Networks and Applications , ISSN 1383-469X, E-ISSN 1572-8153, Vol. 24, nr 3, s. 1003-1014Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Mobile Edge Computing (MEC) is a promising solution to improve vehicular services through offloading computation to cloud servers in close proximity to mobile vehicles. However, the self-interested nature together with the high mobility characteristic of the vehicles make the design of the computation offloading scheme a significant challenge. In this paper, we propose a new Vehicular Edge Computing (VEC) framework to model the computation offloading process of the mobile vehicles running on a bidirectional road. Based on this framework, we adopt a contract theoretic approach to design optimal offloading strategies for the VEC service provider, which maximize the revenue of the provider while enhancing the utilities of the vehicles. To further improve the utilization of the computing resources of the VEC servers, we incorporate task priority distinction as well as additional resource providing into the design of the offloading scheme, and propose an efficient VEC server selection and computing resource allocation algorithm. Numerical results indicate that our proposed schemes greatly enhance the revenue of the VEC provider, and concurrently improve the utilization of cloud computing resources. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.

  • 41.
    Hernandez-Diaz, Kevin
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Cross Spectral Periocular Matching using ResNet Features2019Ingår i: 2019 International Conference on Biometrics (ICB), 2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    Periocular recognition has gained attention in the last years thanks to its high discrimination capabilities in less constraint scenarios than other ocular modalities. In this paper we propose a method for periocular verification under different light spectra using CNN features with the particularity that the network has not been trained for this purpose. We use a ResNet-101 pretrained model for the ImageNet Large Scale Visual Recognition Challenge to extract features from the IIITD Multispectral Periocular Database. At each layer the features are compared using χ 2 distance and cosine similitude to carry on verification between images, achieving an improvement in the EER and accuracy at 1% FAR of up to 63.13% and 24.79% in comparison to previous works that employ the same database. In addition to this, we train a neural network to match the best CNN feature layer vector from each spectrum. With this procedure, we achieve improvements of up to 65% (EER) and 87% (accuracy at 1% FAR) in cross-spectral verification with respect to previous studies.

  • 42.
    Hernandez-Diaz, Kevin
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Cross-Spectral Biometric Recognition with Pretrained CNNs as Generic Feature Extractors2019Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    Periocular recognition has gained attention in the last years thanks to its high discrimination capabilities in less constraint scenarios than face or iris. In this paper we propose a method for periocular verification under different light spectra using CNN features with the particularity that the network has not been trained for this purpose. We use a ResNet-101 pretrained model for the ImageNet Large Scale Visual Recognition Challenge to extract features from the IIITD Multispectral Periocular Database. At each layer the features are compared using χ 2 distance and cosine similitude to carry on verification between images, achieving an improvement in the EER and accuracy at 1% FAR of up to 63.13% and 24.79% in comparison to previous works that employ the same database. In addition to this, we train a neural network to match the best CNN feature layer vector from each spectrum. With this procedure, we achieve improvements of up to 65% (EER) and 87% (accuracy at 1% FAR) in cross-spectral verification with respect to previous studies.

  • 43.
    Chamberlain, Roger
    et al.
    Computer Science and Engineering, Washington University, Saint Louis, USA.
    Taha, WalidHögskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).Törngren, MartinDepartment of Machine Design, KTH Royal Institute of Technology, Stockholm, Sweden.
    Cyber Physical Systems. Model-Based Design: 8th International Workshop, CyPhy 2018, and 14th International Workshop, WESE 2018, Turin, Italy, October 4–5, 2018, Revised Selected Papers2019Proceedings (redaktörskap) (Refereegranskat)
    Abstract [en]

    This book constitutes the proceedings of the 8th International Workshop on Design, Modeling, and Evaluation of Cyber Physical Systems, CyPhy 2018 and 14th International Workshop on Embedded and Cyber-Physical Systems Education, WESE 2018, held in conjunction with ESWeek 2018, in Torino, Italy, in October 2018. The 13 full papers presented together  with 1 short paper in this volume were carefully reviewed and selected from 18 submissions. The conference presents a wide range of domains including Modeling, simulation, verification, design, cyber-physical systems, embedded systems, real-time systems, safety, and reliability. © 2019 Springer Nature Switzerland AG. Part of Springer Nature.

  • 44.
    Mashad Nemati, Hassan
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Data analytics for weak spot detection in power distribution grids2019Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    This research aims to develop data-driven methods that extract information from the available data in distribution grids for detecting weak spots, including the components with degraded reliability and areas with power quality problems. The results enable power distribution companies to change from reactive maintenance to predictive maintenance by deriving benefits from available data. In particular, the data is exploited for three purposes: (a) failure pattern discovery, (b) reliability evaluation of power cables, and (c) analyzing and modeling propagation of power quality disturbances (PQDs) in low-voltage grids.

    To analyze failure characteristics it is important to discover which failures share common features, e.g., if there are any types of failures that happen mostly in certain parts of the grid or at certain times. This analysis provides information about correlation between different features and identifying the most vulnerable components. In this case, we applied statistical analysis and association rules to discover failure patterns. Furthermore, we propose a visualization of the correlations between different factors representing failures by using an approximated Bayesian network. We show that the Bayesian Network constructed based on the interesting rules of two items is a good approximation of the real dataset.

    The main focus of reliability evaluation is on failure rate estimation and reliability ranking. In case of power cables, the limited amount of recorded events makes it difficult to perform failure rate modeling. Therefore, we propose a method for interpreting the results of goodness-of-fit measures with confidence intervals, estimated using synthetic data.

    To perform reliability ranking of power cables, in addition to the age of cables, we consider other factors. Then, we use the proportional hazard model (PHM) to assess the impact of the factors and calculate the failure rate of each individual cable. In reliability evaluation, it is important to consider the fact that power cables are repairable components. We discuss that the conclusions about different factors in PHM and cables ranking will be misleading if one considers the cables as non-repairable components.

    In low-voltage distribution grids, analyzing PQDs is important as we are moving towards smart grids with the next generation of producers and consumers. Installing Power Quality and Monitoring Systems (PQMS) at all the nodes in the network, for monitoring the impacts of the new consumer/producer, is prohibitively expensive. Instead, we demonstrate that power companies can utilize the available smart meters, which are widely deployed in the low-voltage grids, for monitoring power quality events and identifying areas with power quality problems. In particular, several models for propagation of PQDs, within neighbor customers in different levels of the grid topology, are investigated. The results show that meters data can be used to detect and describe propagation in low-voltage grids.

    The developed methods of (a) failure pattern discovery are applied on data from Halmstad Energi och Miljö (HEM Nät), Öresundskraft, Göteborg Energy, and Växjö Energy, four different distribution system operators in Sweden. The developed methods of (b) reliability evaluation of power cables and (c) analyzing and modeling propagation of PQDs are applied on data from HEM Nät.

  • 45.
    Ashfaq, Awais
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab). Halland Hospital, Region Halland, Halmstad, Sweden.
    Lönn, Stefan
    Research and Development, Region Halland, Halmstad, Sweden.
    Nilsson, Håkan
    Economic Department, Region Halland, Halmstad, Sweden.
    Eriksson, Jonny
    Halland Hospital, Region Halland, Halmstad, Sweden.
    Kwatra, Japneet
    Brigham and Women’s Hospital, Boston, MA, USA.
    Yasin, Zayed
    Economic Department, Region Halland, Sweden & Harvard Medical School, Boston, MA, USA.
    Slutzman, Jonathan E
    Harvard Medical School, Boston, MA, USA & Massachusetts General Hospital, Boston, MA, USA.
    Wallenfeldt, Thomas
    CGI Group Inc. Consultants to Government and Industries, Halmstad, Sweden.
    Obermeyer, Ziad
    School of Public Health, University of California at Berkeley, Berkeley, CA, USA.
    Anderson, Philip D
    Brigham and Women’s Hospital, Boston, MA, USA & Harvard Medical School, Boston, MA, USA.
    Lingman, Markus
    Halland Hospital, Region Halland, Halmstad, Sweden & Institute of Medicine, Dept. of Molecular and Clinical Medicine/Cardiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
    Data resource profile: Regional healthcare information platform in Halland, Sweden, a dedicated environment for healthcare research2019Ingår i: International Journal of Epidemiology, ISSN 0300-5771, E-ISSN 1464-3685Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Accurate and comprehensive healthcare data coupled with modern analytical tools can play a vital role in enabling care providers to make better-informed decisions, leading to effective and cost-efficient care delivery. This paper describes a novel strategic healthcare analysis and research platform that encapsulates 360-degree pseudo-anonymized data covering clinical, operational capacity and financial data on over 500,000 patients treated since 2009 across all care delivery units in the county of Halland, Sweden. The over-arching goal is to develop a comprehensive healthcare data infrastructure that captures complete care processes at individual, organizational and population levels. These longitudinal linked healthcare data are a valuable tool for research in a broad range of areas including health economy and process development using real world evidence.

    Key messages

    Structured and standardized variables have been linked from different regional healthcare sources into a research information platform including all healthcare visits in the county of Halland in Sweden, from 2009 to date.

    Since 2015, the regional information platform integrates a cost component to each healthcare visit: thus being able to quantify patient level value, safety and cost efficiency across the continuum of care.

  • 46.
    Polymeri, E.
    et al.
    Department of Radiology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
    Sadik, M.
    Department of Clinical Physiology, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden.
    Kaboteh, R.
    Department of Clinical Physiology, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden.
    Borrelli, P.
    Department of Clinical Physiology, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden.
    Enqvist, O.
    Department of Electrical Engineering, Region Västra Götaland, Chalmers University of Technology, Gothenburg, Sweden.
    Ulén, J.
    Eigenvision AB, Malmö, Sweden.
    Ohlsson, Mattias
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Trägårdh, E.
    Department of Translational Medicine, Institute of Clinical Sciences, Lund University, Malmö, Sweden.
    Poulsen, M. H.
    Department of Urology, Odense University Hospital, Odense, Denmark.
    Simonsen, J. A.
    Department of Nuclear Medicine, Odense University Hospital, Odense, Denmark.
    Hoilund-Carlsen, P. F.
    Department of Nuclear Medicine, Odense University Hospital, Odense, Denmark.
    Johnsson, ÅA.
    Department of Radiology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
    Edenbrandt, L.
    Department of Clinical Physiology, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden.
    Deep learning-based quantification of PET/CT prostate gland uptake: association with overall survival2019Ingår i: Clinical Physiology and Functional Imaging, ISSN 1475-0961, E-ISSN 1475-097XArtikel i tidskrift (Refereegranskat)
    Abstract [en]

    Aim: To validate a deep-learning (DL) algorithm for automated quantification of prostate cancer on positron emission tomography/computed tomography (PET/CT) and explore the potential of PET/CT measurements as prognostic biomarkers. Material and methods: Training of the DL-algorithm regarding prostate volume was performed on manually segmented CT images in 100 patients. Validation of the DL-algorithm was carried out in 45 patients with biopsy-proven hormone-naïve prostate cancer. The automated measurements of prostate volume were compared with manual measurements made independently by two observers. PET/CT measurements of tumour burden based on volume and SUV of abnormal voxels were calculated automatically. Voxels in the co-registered 18F-choline PET images above a standardized uptake value (SUV) of 2·65, and corresponding to the prostate as defined by the automated segmentation in the CT images, were defined as abnormal. Validation of abnormal voxels was performed by manual segmentation of radiotracer uptake. Agreement between algorithm and observers regarding prostate volume was analysed by Sørensen-Dice index (SDI). Associations between automatically based PET/CT biomarkers and age, prostate-specific antigen (PSA), Gleason score as well as overall survival were evaluated by a univariate Cox regression model. Results: The SDI between the automated and the manual volume segmentations was 0·78 and 0·79, respectively. Automated PET/CT measures reflecting total lesion uptake and the relation between volume of abnormal voxels and total prostate volume were significantly associated with overall survival (P = 0·02), whereas age, PSA, and Gleason score were not. Conclusion: Automated PET/CT biomarkers showed good agreement to manual measurements and were significantly associated with overall survival. © 2019 The Authors. Clinical Physiology and Functional Imaging published by John Wiley & Sons Ltd on behalf of Scandinavian Society of Clinical Physiology and Nuclear Medicine

  • 47.
    Tzelepis, Georgios
    et al.
    Volvo Technology AB, VGTT, Gothenburg, Sweden.
    Asif, Ahraz
    Volvo Technology AB, VGTT, Gothenburg, Sweden.
    Baci, Saimir
    Volvo Technology AB, VGTT, Gothenburg, Sweden.
    Cavdar, Selcuk
    Volvo Technology AB, VGTT, Gothenburg, Sweden.
    Erdal Aksoy, Eren
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab). Volvo Technology AB, VGTT, Gothenburg, Sweden.
    Deep Neural Network Compression for Image Classification and Object Detection2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    Neural networks have been notorious for being computationally expensive. This is mainly because neural networks are often over-parametrized and most likely have redundant nodes or layers as they are getting deeper and wider. Their demand for hardware resources prohibits their extensive use in embedded devices and puts restrictions on tasks like real-time image classification or object detection. In this work, we propose a network-agnostic model compression method infused with a novel dynamical clustering approach to reduce the computational cost and memory footprint of deep neural networks. We evaluated our new compression method on five different state-of-the-art image classification and object detection networks. In classification networks, we pruned about 95% of network parameters. In advanced detection networks such as YOLOv3, our proposed compression method managed to reduce the model parameters up to 59.70% which yielded 110X less memory without sacrificing much in accuracy.

  • 48.
    David, Jennifer
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Mostowski, Wojciech
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Aramrattna, Maytheewat
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Fan, Yuantao
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Varshosaz, Mahsa
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Karlsson, Patrick
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Roden, Marcus
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Bogga, Anders
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Carlsen, Jakob
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Johansson, Emil
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Andersson, Emil
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Design and Development of a Hexacopter for the Search and Rescue of a Lost Drone2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    Search and rescue with an autonomous robot is an attractive and challenging task within the research community. This paper presents the development of an autonomous hexacopter that is designed for retrieving a lost object, like a drone, from a vast-open space, like a desert area. Navigating its path with a proposed coverage path planning strategy, the hexacopter can efficiently search for a lost target and locate it using an image-based object detection algorithm. Moreover, after the target is located, our hexacopter can grasp it with a customised gripper and transport it back to a destined location. It is also capable of avoiding static obstacles and dynamic objects. The proposed system was realised in simulations before implementing it in a real hardware setup, i.e. assembly of the drone, crafting of the gripper, software implementation and testing under real-world scenarios. The designed hexacopter won the best UAV design award at the CPS-VO 2018 Competition held in Arizona, USA.

  • 49.
    Cooney, Martin
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Berck, Peter
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Designing a Robot Which Paints With a Human: Visual Metaphors to Convey Contingency and Artistry2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    Socially assistive robots could contribute to fulfilling an important need for interaction in contexts where human caregivers are scarce–such as art therapy, where peers, or patients and therapists, can make art together. However, current art-making robots typically generate art either by themselves, or as tools under the control of a human artist; how to make art together with a human in a good way has not yet received much attention, possibly because some concepts related to art, such as emotion and creativity, are not yet well understood. The current work reports on our use of a collaborative prototyping approach to explore this concept of a robot which can paint together with people. The result is a proposed design, based on an idea of using visual metaphors to convey contingency and artistry. Our aim is that the identified considerations will help support next steps, toward supporting positive experiences for people through art-making with a robot.

  • 50.
    Bygstad, B.
    et al.
    Department of Informatics, University of Oslo, Gaustadalléen 23 B, Oslo, Norway.
    Øvrelid, E.
    Department of Informatics, University of Oslo, Gaustadalléen 23 B, Oslo, Norway.
    Lie, T.
    Østfold Hospital, Kalnesveien 300, Grålum, 1714, Norway.
    Bergquist, Magnus
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Människa och Informationsteknologi (MI-lab).
    Developing and Organizing an Analytics Capability for Patient Flow in a General Hospital2019Ingår i: Information Systems Frontiers, ISSN 1387-3326, E-ISSN 1572-9419Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Much of the information produced in hospitals is clinical, and stored for the purposes of documentation. In practice, most of it is never used. The potential of analytics is to reuse this information for other purposes. This is easier said than done, because of technical, semantic, legal and organizational hindrances. In particular, hospitals are not organized to leverage the value of big data. In this study we ask, how can we conceptualize analytics as an integrated part of hospital processes? And, how can we develop and organize an analytics capability in a large hospital? Our empirical evidence is a longitudinal study in a high-tech hospital in Norway, where we followed the development of an analytics capability, and assessed the organizational benefits. We offer two findings. First, we show how the analytics process interacts with the hospital logistics processes in a sense- and respond cycle. Second, we demonstrate how analytics capability is built on the institutionalized network of technology, an analytics team and the administrative and clinical decision makers. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

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