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  • 1.
    Camelo, Guilherme Antonio
    et al.
    Federal University of Rio Grande do Sul, Porto Alegre, Brazil.
    Recena Menezes, Maria Luiza
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS). Federal University of Rio Grande do Sul, Porto Alegre, Brazil.
    Pinheiro Sant'Anna, Anita
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Vicari, Rosa Maria
    Federal University of Rio Grande do Sul, Porto Alegre, Brazil.
    Pereira, Carlos Eduardo
    Federal University of Rio Grande do Sul, Porto Alegre, Brazil.
    Control of Smart Environments Using Brain Computer Interface Based on Genetic Algorithm2016In: Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349, Vol. 9622, p. 773-781Article in journal (Refereed)
    Abstract [en]

    This work deals with the development of an interface to control a smart conference room using passive BCI (Brain Computer Interface). It compares a genetic algorithm developed in a previous project to control the smart conference room with a random control algorithm. The system controls features of the conference room such as air conditioner, lightning systems, electric shutters, entertainment devices, etc. The parameters of the algorithm are extracted from users biosignal using Emotiv Epoc Headset while the user performs an attention test. The tests indicate that the decisions made by the genetic algorithm lead to better results, but in a single execution cannot be considered an effective optimization algorithm. © Springer-Verlag Berlin Heidelberg 2016.

  • 2.
    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.

  • 3.
    Kruusmaa, Maarja
    et al.
    Chalmers University of Technology, Department of Computer Engineering, Gothenburg, Sweden.
    Svensson, Bertil
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    A low-risk approach to mobile robot path planning1998In: Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349, Vol. 1416, p. 132-141Article in journal (Refereed)
    Abstract [en]

    This paper presents a self-organizing approach for mobile robot path planning problems in dynamic environments by using case-based reasoning together with a more conventional method of grid-map based path planning. The map-based path planner is used to suggest new innovative solutions for a particular path planning problem. The case-base is used to store the paths and evaluate their traversability. While planning the route those paths are preferred which, according to former experience, are least risky. As the environment changes, the exploration as well as the evaluation of the paths will allow the system to self-organize by forming a set of low-risk paths that are safest to follow. The experiments in a simulated environment show that the robot is able to adapt in a dynamic environment and learns to use the least risky paths. © Springer-Verlag Berlin Heidelberg 1998.

  • 4.
    Mostowski, Wojciech
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Ulbrich, Mattias
    Karlsruhe Institute of Technology, Karlsruhe, Germany.
    Dynamic Dispatch for Method Contracts Through Abstract Predicates2016In: Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349, Vol. 9800, p. 238-267Article in journal (Refereed)
    Abstract [en]

    Dynamic method dispatch is a core feature of object-oriented programming by which the executed implementation for a polymorphic method is only chosen at runtime. In this paper, we present a specification and verification methodology which extends the concept of dynamic dispatch to design-by-contract specifications.

    The formal specification language JML has only rudimentary means for polymorphic abstraction in expressions. We promote these to fully flexible specification-only query methods called model methods that can, like ordinary methods, be overridden to give specifications a new semantics in subclasses in a transparent and modular fashion. Moreover, we allow them to refer to more than one program state which give us the possibility to fully abstract and encapsulate two-state specification contexts, i.e., history constraints and method postconditions. Finally, we provide an elegant and flexible mechanism to specify restrictions on specifications in subtypes. Thus behavioural subtyping can be enforced, yet it still allows for other specification paradigms.

    We provide the semantics for model methods by giving a translation into a first order logic and according proof obligations. We fully implemented this framework in the KeY program verifier and successfully verified relevant examples. We have also implemented an extension to KeY to support permission-based verification of concurrent Java programs. In this context model methods provide a modular specification method to treat code synchronisation through API methods. © The Author(s) 2016.

  • 5.
    Rögnvaldsson, Thorsteinn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    A Simple trick for estimating the weight decay parameter2012In: Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349, Vol. 7700 LECTURE NO, p. 69-89Article in journal (Refereed)
    Abstract [en]

    We present a simple trick to get an approximate estimate of the weight decay parameter λ. The method combines early stopping and weight decay, into the estimate λ̂ = ||∇E(Wes)||/||2W es||, where Wes is the set of weights at the early stopping point, and E(W) is the training data fit error. The estimate is demonstrated and compared to the standard cross-validation procedure for λ selection on one synthetic and four real life data sets. The result is that is as good an estimator for the optimal weight decay parameter value as the standard search estimate, but orders of magnitude quicker to compute. The results also show that weight decay can produce solutions that are significantly superior to committees of networks trained with early stopping. © Springer-Verlag Berlin Heidelberg 2012.

  • 6.
    Vaiciukynas, Evaldas
    et al.
    Kaunas University of Technology, Kaunas, Lithuania.
    Verikas, Antanas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. Kaunas University of Technology, Kaunas, Lithuania.
    Gelzinis, Adas
    Kaunas University of Technology, Kaunas, Lithuania.
    Bacauskiene, Marija
    Kaunas University of Technology, Kaunas, Lithuania.
    Vaskevicius, Kestutis
    Kaunas University of Technology, Kaunas, Lithuania.
    Uloza, Virgilijus
    Lithuanian University of Health Sciences, Kaunas, Lithuania.
    Padervinskis, Evaldas
    Lithuanian University of Health Sciences, Kaunas, Lithuania.
    Ciceliene, Jolita
    Lithuanian University of Health Sciences, Kaunas, Lithuania.
    Fusing Various Audio Feature Sets for Detection of Parkinson’s Disease from Sustained Voice and Speech Recordings2016In: Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349, Vol. 9811, p. 328-337Article in journal (Refereed)
    Abstract [en]

    The aim of this study is the analysis of voice and speech recordings for the task of Parkinson’s disease detection. Voice modality corresponds to sustained phonation /a/ and speech modality to a short sentence in Lithuanian language. Diverse information from recordings is extracted by 22 well-known audio feature sets. Random forest is used as a learner, both for individual feature sets and for decision-level fusion. Essentia descriptors were found as the best individual feature set, achieving equal error rate of 16.3 % for voice and 13.3 % for speech. Fusion of feature sets and modalities improved detection and achieved equal error rate of 10.8 %. Variable importance in fusion revealed speech modality as more important than voice. © Springer International Publishing Switzerland 2016

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