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  • 1.
    Fan, Yuantao
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Aramrattana, Maytheewat
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Shahbandi, Saeed Gholami
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Nemati, Hassan Mashad
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Åstrand, Björn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Infrastructure Mapping in Well-Structured Environments Using MAV2016In: Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349, Vol. 9716, p. 116-126Article in journal (Refereed)
    Abstract [en]

    In this paper, we present a design of a surveying system for warehouse environment using low cost quadcopter. The system focus on mapping the infrastructure of surveyed environment. As a unique and essential parts of the warehouse, pillars from storing shelves are chosen as landmark objects for representing the environment. The map are generated based on fusing the outputs of two different methods, point cloud of corner features from Parallel Tracking and Mapping (PTAM) algorithm with estimated pillar position from a multi-stage image analysis method. Localization of the drone relies on PTAM algorithm. The system is implemented in Robot Operating System(ROS) and MATLAB, and has been successfully tested in real-world experiments. The result map after scaling has a metric error less than 20 cm. © Springer International Publishing Switzerland 2016.

  • 2.
    Mashad Nemati, Hassan
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Data-Driven Methods for Reliability Evaluation of Power Cables in Smart Distribution Grids2017Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    This research aims to develop data-driven methods that automatically exploit historical data in smart distribution grids for reliability evaluation, i.e., analyzing frequency of failures, and modeling components’ lifetime. The results enable power distribution companies to change from reactive maintenance to predictive maintenance by deriving benefits from historical data. In particular, the data is exploited for two purposes: (a) failure pattern discovery, and (b) reliability evaluation of power cables. 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 an easy-to-understand 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, i.e., estimating the function that describes changes in the rate of failure depending on age. 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 Cox 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 show that the conclusions about different factors in PHM and cables ranking will be misleading if one considers the cables as non-repairable components. The developed methods of (a) 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) are applied on data from HEM Nät.

  • 3.
    Mashad Nemati, Hassan
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Fan, Yuantao
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Alonso-Fernandez, Fernando
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Hand Detection and Gesture Recognition Using Symmetric Patterns2016In: Studies in Computational Intelligence, ISSN 1860-949X, E-ISSN 1860-9503, Vol. 642, p. 365-375Article in journal (Refereed)
    Abstract [en]

    Hand detection and gesture recognition is one of the challenging issues in human-robot interaction. In this paper we proposed a novel method to detect human hands and recognize gestures from video stream by utilizing a family of symmetric patterns: log-spiral codes. In this case, several log-family spirals mounted on a hand glove were extracted and utilized for positioning the palm and fingers. The proposed method can be applied in real time and even on a low quality camera stream. The experiments are implemented in different conditions to evaluatethe illumination, scale, and rotation invariance of the proposed method. The results show that using the proposed technique we can have a precise and reliable detection and tracking of the hand and fingers with accuracy about 98 %.

  • 4.
    Mashad Nemati, Hassan
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Gholami Shahbandi, Saeed
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Åstrand, Björn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Human Tracking in Occlusion based on Reappearance Event Estimation2016In: ICINCO 2016: 13th International Conference on Informatics in Control, Automation and Robotics: Proceedings, Volume 2 / [ed] Oleg Gusikhin, Dimitri Peaucelle & Kurosh Madani, SciTePress, 2016, Vol. 2, p. 505-512Conference paper (Refereed)
    Abstract [en]

    Relying on the commonsense knowledge that the trajectory of any physical entity in the spatio-temporal domain is continuous, we propose a heuristic data association technique. The technique is used in conjunction with an Extended Kalman Filter (EKF) for human tracking under occlusion. Our method is capable of tracking moving objects, maintain their state hypothesis even in the period of occlusion, and associate the target reappeared from occlusion with the existing hypothesis. The technique relies on the estimation of the reappearance event both in time and location, accompanied with an alert signal that would enable more intelligent behavior (e.g. in path planning). We implemented the proposed method, and evaluated its performance with real-world data. The result validates the expected capabilities, even in case of tracking multiple humans simultaneously.

  • 5.
    Mashad Nemati, Hassan
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Pinheiro Sant'Anna, Anita
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Nowaczyk, Sławomir
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Jürgensen, Jan Henning
    KTH Royal Institute of Technology, Stockholm, Sweden.
    Hilber, Patrik
    KTH Royal Institute of Technology, Stockholm, Sweden.
    Reliability Evaluation of Power Cables Considering the Restoration CharacteristicManuscript (preprint) (Other academic)
    Abstract [en]

    This paper presents the use of the parametric proportional hazard model (PHM) for reliability ranking of power cables. Here, the Weibull PHM is used to estimate the failure rate of every individual cable based on the age of the cables and a set of explanatory factors. The required information for the proposed method is obtained by exploiting available historical data. This data-driven method does not require any additional measurements on the cables. After individual failure rate estimation, the cables are ranked for maintenance prioritization and repair actions.

    Furthermore, the results of reliability analysis of power cables when considered as repairable or non-repairable components are compared. The paper demonstrates that the methods which estimate the time-to-the-first failure (for non-repairable components) leads to incorrect conclusions about reliability of repairable power cables. The results show that the conclusions about different factors in PHM and cables ranking will be misleading if the cables are considered as non-repairable components. The proposed method is used to calculate the failure rate of each individual Paper Insulated Lead Cover (PILC) underground cables in a distribution grid in the south of Sweden.

  • 6.
    Mashad Nemati, Hassan
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Sant´Anna, Anita
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Nowaczyk, Sławomir
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Bayesian Network Representation of Meaningful Patterns in Electricity Distribution Grids2016In: 2016 IEEE International Energy Conference (ENERGYCON), 2016Conference paper (Refereed)
    Abstract [en]

    The diversity of components in electricity distribution grids makes it impossible, or at least very expensive, to deploy monitoring and fault diagnostics to every individual element. Therefore, power distribution companies are looking for cheap and reliable approaches that can help them to estimate the condition of their assets and to predict the when and where the faults may occur. In this paper we propose a simplified representation of failure patterns within historical faults database, which facilitates visualization of association rules using Bayesian Networks. Our approach is based on exploring the failure history and detecting correlations between different features available in those records. We show that a small subset of the most interesting rules is enough to obtain a good and sufficiently accurate approximation of the original dataset. A Bayesian Network created from those rules can serve as an easy to understand visualization of the most relevant failure patterns. In addition, by varying the threshold values of support and confidence that we consider interesting, we are able to control the tradeoff between accuracy of the model and its complexity in an intuitive way. © 2016 IEEE

  • 7.
    Mashad Nemati, Hassan
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Sant'Anna, Anita
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Nowaczyk, Sławomir
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Overview of Smart Grid Challenges in Sweden2014In: The SAIS Workshop 2014 Proceedings, Swedish Artificial Intelligence Society (SAIS) , 2014, p. 155-164Conference paper (Refereed)
    Abstract [en]

    Smart grids are advanced power grids that use modern hardware and software technologies to provide clean, safe, secure, reliable, ecient and sustainable energy. However, there are many challenges in the eld of smart grids in terms of communication, reliability, interoperability, and big data that should be considered. In this paper we present a brief overview of some of the challenges and solutions in the smart grids, focusing especially on the Swedish point of view. We discuss thirty articles, from 2006 until 2013, with the main interest on datarelated challenges.

  • 8.
    Mashad Nemati, Hassan
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Sant'Anna, Anita
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Nowaczyk, Sławomir
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Reliability Evaluation of Underground Power Cables with Probabilistic Models2015In: DMIN'15: The 2015 International Conference on Data Mining, 2015, p. 37-43Conference paper (Refereed)
    Abstract [en]

    Underground power cables are one of the fundamental elements in power grids, but also one of the more difficult ones to monitor. Those cables are heavily affected by ionization, as well as thermal and mechanical stresses. At the same time, both pinpointing and repairing faults is very costly and time consuming. This has caused many power distribution companies to search for ways of predicting cable failures based on available historical data.

    In this paper, we investigate five different models estimating the probability of failures for in-service underground cables. In particular, we focus on a methodology for evaluating how well different models fit the historical data. In many practical cases, the amount of data available is very limited, and it is difficult to know how much confidence should one have in the goodness-of-fit results.

    We use two goodness-of-fit measures, a commonly used one based on mean square error and a new one based on calculating the probability of generating the data from a given model. The corresponding results for a real data set can then be interpreted by comparing against confidence intervals obtained from synthetic data generated according to different models.

    Our results show that the goodness-of-fit of several commonly used failure rate models, such as linear, piecewise linear and exponential, are virtually identical. In addition, they do not explain the data as well as a new model we introduce: piecewise constant.

  • 9.
    Mashad Nemati, Hassan
    et al.
    Islamic Azad University, Abhar branch, Abhar, Iran.
    Åstrand, Björn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Tracking of People Using Laser Range Sensor in Occlusion Situations2011In: Proceedings of 2011 International Conference on Information and Computer Technology (ICICT), 2011Conference paper (Refereed)
  • 10.
    Nemati, Hassan
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Åstrand, Björn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Tracking of People in Paper Mill Warehouse Using Laser Range Sensor2014In: UKSim-AMSS Eighth European Modelling Symposium on Computer Modelling and Simulation, EMS 2014 / [ed] David Al-Dabass, Valentina Colla, Marco Vannucci & Athanasios Pantelous, Los Alamitos, CA: IEEE Computer Society, 2014, p. 52-57, article id 7153974Conference paper (Refereed)
    Abstract [en]

    In this paper a laser scanner based approach for simultaneous detection and tracking of people in an indoor environment is presented. The operation of an autonomous truck, for transporting paper reels in a dynamic environment shared with humans, is considered as the application setting for this work. Here, a human leg detection procedure and an Extended Kalman Filter (EKF) based tracking method are employed for real-time performance. Several experiments with different data sets collected from an autonomous forklift truck in a paper mill warehouse have been performed in an offline situation. The results show how the system is able to detect and track multiple moving people. ©2014 IEEE.

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