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  • 1.
    Kleyko, Denis
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Wiklund, Urban
    Department of Radiation Sciences, Biomedical Engineering, Umeå University, Umeå, Sweden.
    A Hyperdimensional Computing Framework for Analysis of Cardiorespiratory Synchronization during Paced Deep Breathing2019Ingår i: IEEE Access, E-ISSN 2169-3536, Vol. 7, s. 34403-34415Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Objective: Autonomic function during deep breathing (DB) is normally scored based on the assumption that the heart rate is synchronized with the breathing. We have observed individuals with subtle arrhythmias during DB where autonomic function cannot be evaluated. This study presents a novel method for analyzing cardiorespiratory synchronization: feature-based analysis of the similarity between heart rate and respiration using principles of hyperdimensional computing. Methods: Heart rate and respiration signals were modeled using Fourier series analysis. Three feature variables were derived and mapped to binary vectors in a high-dimensional space. Using both synthesized data and recordings from patients/healthy subjects, the similarity between the feature vectors was assessed using Hamming distance (high-dimensional space), Euclidean distance (original space), and with a coherence-based index. Methods were evaluated via classification of the similarity indices into three groups. Results: The distance-based methods achieved good separation of signals into classes with different degree of cardiorespiratory synchronization, also providing identification of patients with low cardiorespiratory synchronization but high values of conventional DB scores. Moreover, binary high-dimensional vectors allowed an additional analysis of the obtained Hamming distance. Conclusions: Feature-based similarity analysis using hyperdimensional computing is capable of identifying signals with low cardiorespiratory synchronization during DB due to arrhythmias. Vector-based similarity analysis could be applied to other types of feature variables than based on spectral analysis. Significance: The proposed methods for robustly assessing cardiorespiratory synchronization during DB facilitate the identification of individuals where the evaluation of autonomic function is problematic or even impossible, thus, increasing the correctness of the conventional DB scores.

  • 2.
    Kleyko, Denis
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Rahimi, Abbas
    ETH Zurich, Zurich, Switzerland.
    Gayler, Ross W.
    Melbourne, Australia.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Autoscaling Bloom filter: Controlling trade-off between true and false positives2019Ingår i: Neural computing & applications (Print), ISSN 0941-0643, E-ISSN 1433-3058Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A Bloom filter is a special case of an artificial neural network with two layers. Traditionally, it is seen as a simple data structure supporting membership queries on a set. The standard Bloom filter does not support the delete operation, and therefore, many applications use a counting Bloom filter to enable deletion. This paper proposes a generalization of the counting Bloom filter approach, called “autoscaling Bloom filters”, which allows adjustment of its capacity with probabilistic bounds on false positives and true positives. Thus, by relaxing the requirement on perfect true positive rate, the proposed autoscaling Bloom filter addresses the major difficulty of Bloom filters with respect to their scalability. In essence, the autoscaling Bloom filter is a binarized counting Bloom filter with an adjustable binarization threshold. We present the mathematical analysis of its performance and provide a procedure for minimizing its false positive rate.

  • 3.
    de Silva, D.
    et al.
    Research Centre for Data Analytics and Cognition, La Trobe University, Bundoora, Australia.
    Pang, Z.
    ABB Corporate Research, Västeras, Sweden.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Vyatkin, Valeriy
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap. Department of Electrical Engineering and Automation, Aalto University, Helsinki, Finland.
    Guest Editorial: Special Section on Developments in Artificial Intelligence for Industrial Informatics2019Ingår i: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050, Vol. 15, nr 6, s. 3690-3692Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The emergence of artificial intelligence (AI), empowered by robust computing infrastructure and abundance of data, maintains potential for radical transformation of human society, essentially a third phase in evolution. Numerous research endeavor, policy development, and thought-leadership are presently in progress aimed at discovering data-driven intelligent decision-making solutions for smart cities, smart grids, smart homes, and informed citizens as well as addressing potential risks posed by AI workplace automation. Joining this broad effort, this Special Section contributes six research articles that consolidate recent developments in AI for industrial informatics.

  • 4.
    Kleyko, Denis
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Rahimi, Abbas
    University of California at Berkeley, Berkeley.
    Rachkovskij, Dmitri A.
    International Research and Training, Center for Information Technologies and Systems, Kiev, Ukraine.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Rabaey, Jan M.
    University of California at Berkeley, Berkeley.
    Classification and Recall With Binary Hyperdimensional Computing: Tradeoffs in Choice of Density and Mapping Characteristics2018Ingår i: IEEE Transactions on Neural Networks and Learning Systems, ISSN 2162-237X, E-ISSN 2162-2388, Vol. 29, nr 12, s. 5880-5898Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Hyperdimensional (HD) computing is a promising paradigm for future intelligent electronic appliances operating at low power. This paper discusses tradeoffs of selecting parameters of binary HD representations when applied to pattern recognition tasks. Particular design choices include density of representations and strategies for mapping data from the original representation. It is demonstrated that for the considered pattern recognition tasks (using synthetic and real-world data) both sparse and dense representations behave nearly identically. This paper also discusses implementation peculiarities which may favor one type of representations over the other. Finally, the capacity of representations of various densities is discussed.

  • 5.
    Kleyko, Denis
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Papakonstantinou, Nikolaos
    VTT Technical Research Center of Finland.
    Vyatkin, Valeriy
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap. Department of Electrical Engineering and Automation, Aalto University, Finland.
    Hyperdimensional computing in industrial systems: the use-case of distributed fault isolation in a power plant2018Ingår i: IEEE Access, E-ISSN 2169-3536, Vol. 6, s. 30766-30777Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper presents an approach for distributed fault isolation in a generic system of systems. The proposed approach is based on the principles of hyperdimensional computing. In particular, the recently proposed method called Holographic Graph Neuron is used. We present a distributed version of Holographic Graph Neuron and evaluate its performance on the problem of fault isolation in a complex power plant model. Compared to conventional machine learning methods applied in the context of the same scenario the proposed approach shows comparable performance while being distributed and requiring simple binary operations, which allow for a fast and efficient implementation in hardware.

  • 6.
    De Silva, Daswin
    et al.
    Research Centre for Data Analytics and Cognition, La Trobe University, Victoria, Australia..
    Ranasinghe, Weranja
    Research Centre for Data Analytics and Cognition, La Trobe University, Victoria, Australia..
    Bandaragoda, Tharindu
    Research Centre for Data Analytics and Cognition, La Trobe University, Victoria, Australia..
    Adikari, Achini
    Research Centre for Data Analytics and Cognition, La Trobe University, Victoria, Australia..
    Mills, Nishan
    Research Centre for Data Analytics and Cognition, La Trobe University, Victoria, Australia..
    Iddamalgoda, Lahiru
    Research Centre for Data Analytics and Cognition, La Trobe University, Victoria, Australia..
    Alahakoon, Damminda
    Research Centre for Data Analytics and Cognition, La Trobe University, Victoria, Australia..
    Lawrentschuk, Nathan
    Austin Hospital, Heidelberg, Victoria, Australia..
    Persad, Raj
    North Bristol, NHS Trust, Bristol, United Kingdom..
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Gray, Richard
    School of Nursing and Midwifery, La Trobe University, Victoria, Australia..
    Bolton, Damien
    Austin Hospital, Heidelberg, Victoria, Australia..
    Machine learning to support social media empowered patients in cancer care and cancer treatment decisions2018Ingår i: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 13, nr 10, artikel-id e0205855Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    BACKGROUND

    A primary variant of social media, online support groups (OSG) extend beyond the standard definition to incorporate a dimension of advice, support and guidance for patients. OSG are complementary, yet significant adjunct to patient journeys. Machine learning and natural language processing techniques can be applied to these large volumes of unstructured text discussions accumulated in OSG for intelligent extraction of patient-reported demographics, behaviours, decisions, treatment, side effects and expressions of emotions. New insights from the fusion and synthesis of such diverse patient-reported information, as expressed throughout the patient journey from diagnosis to treatment and recovery, can contribute towards informed decision-making on personalized healthcare delivery and the development of healthcare policy guidelines.

    METHODS AND FINDINGS

    We have designed and developed an artificial intelligence based analytics framework using machine learning and natural language processing techniques for intelligent analysis and automated aggregation of patient information and interaction trajectories in online support groups. Alongside the social interactions aspect, patient behaviours, decisions, demographics, clinical factors, emotions, as subsequently expressed over time, are extracted and analysed. More specifically, we utilised this platform to investigate the impact of online social influences on the intimate decision scenario of selecting a treatment type, recovery after treatment, side effects and emotions expressed over time, using prostate cancer as a model. Results manifest the three major decision-making behaviours among patients, Paternalistic group, Autonomous group and Shared group. Furthermore, each group demonstrated diverse behaviours in post-decision discussions on clinical outcomes, advice and expressions of emotion during the twelve months following treatment. Over time, the transition of patients from information and emotional support seeking behaviours to providers of information and emotional support to other patients was also observed.

    CONCLUSIONS

    Findings from this study are a rigorous indication of the expectations of social media empowered patients, their potential for individualised decision-making, clinical and emotional needs. The increasing popularity of OSG further confirms that it is timely for clinicians to consider patient voices as expressed in OSG. We have successfully demonstrated that the proposed platform can be utilised to investigate, analyse and derive actionable insights from patient-reported information on prostate cancer, in support of patient focused healthcare delivery. The platform can be extended and applied just as effectively to any other medical condition.

  • 7.
    Wedekind, Daniel
    et al.
    Institute of Biomedical Engineering, TU Dresden, Dresden Germany .
    Kleyko, Denis
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Malberg, Hagen
    Institute of Biomedical Engineering, TU Dresden, Dresden Germany .
    Zaunseder, Sebastian
    Institute of Biomedical Engineering, TU Dresden, Dresden Germany .
    Wiklund, Urban
    Department of Biomedical Engineering and Informatics, Umea Universitet.
    Robust Methods for Automated Selection of Cardiac Signals after Blind Source Separation2018Ingår i: IEEE Transactions on Biomedical Engineering, ISSN 0018-9294, E-ISSN 1558-2531, Vol. 65, nr 10, s. 2248-2258Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Objective: Novel minimum-contact vital signs monitoring techniques like textile or capacitive electrocardiogram (ECG) provide new opportunities for health monitoring. These techniques are sensitive to artifacts and require handling of unstable signal quality. Spatio-temporal Blind Source Separation (BSS) is capable of processing suchlike multichannel signals. However, BSS's permutation indeterminacy requires the selection of the cardiac signal (i.e. the component resembling the electric cardiac activity) after its separation from artifacts. This study evaluates different concepts for solving permutation indeterminacy. Methods: Novel automated component selection routines based on heartbeat detections are compared with standard concepts, as using higher order moments or frequency-domain features, for solving permutation indeterminacy in spatio-temporal BSS. BSS was applied to a textile and a capacitive ECG dataset of healthy subjects performing a motion protocol, and to the MIT-BIH Arrhythmia Database. The performance of the subsequent component selection was evaluated by means of the heartbeat component. Results: The proposed heartbeat-detection-based selection routines significantly outperformed the standard selectors based on Skewness, Kurtosis and frequency-domain features, especially for datasets containing motion artifacts. For arrhythmia data, beat analysis by sparse coding outperformed simple periodicity tests of the detected heartbeats. Conclusions: Component selection routines based on heartbeat detections are capable of reliably selecting cardiac signals after spatio-temporal BSS in case of severe motion artifacts and arrhythmia. Significance: The availability of robust cardiac component selectors for solving permutation indeterminacy facilitates the usage of spatio-temporal BSS to extract cardiac signals in artifact-sensitive minimum-contact vital signs monitoring techniques.

  • 8.
    Osipov, Evgeny
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Kleyko, Denis
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Papakonstantinou, Nikolaos
    VTT Technical Research Centre of Finland.
    Approximate Sensing with Vector Symbolic Architectures: The case of fault isolation in distributed automation systems2017Ingår i: Proceedings: EWSN ’17 Proceedings of the 2017 International Conference on Embedded Wireless Systems and Networks, New york: ACM Digital Library, 2017, s. 224-225Konferensbidrag (Refereegranskat)
    Abstract [en]

    Due to the stochastic and imprecise nature of sensory data, the current (exact computational) algorithms for their processing introduce unnecessary computational overhead. One of the major trends in the development of computation al elements for processing of sensory data is low-power imprecise electronics and accompanying algorithmic solutions for approximate computing. This poster introduces the usage of hyper-dimensional computing and vector-symbolic architectures in the context of wireless embedded systems. A problem of fault isolation in a distributed automation system is considered as a showcase. The poster presents the performance of the associative sensing approach as well as challenges associated with the design of communication techniques and network protocols for exchanging of VSA information.

  • 9.
    Osipov, Evgeny
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Kleyko, Denis
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Legalov, Alexander
    Siberian Federal University.
    Associative Synthesis of Finite State Automata Model of a Controlled Object with Hyperdimensional Computing2017Ingår i: Proceedings IECON 2017: 43rd Annual Conference of the IEEE Industrial Electronics Society, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, s. 3276-3281Konferensbidrag (Refereegranskat)
    Abstract [en]

    The main contribution of this paper is a study of the applicability of hyperdimensional computing and learning with an associative memory for modeling the dynamics of complex automation systems. Specifically, the problem of learning an evidence-based model of a plant in a distributed automation and control system is considered. The model is learned in the form a finite state automata. 

  • 10.
    Kleyko, Denis
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Senior, Alexander
    Monash University, Melbourne, VIC.
    Khan, Asad
    Monash University, Melbourne, VIC.
    Sekercioglu, Ahmet
    Monash University, Melbourne, VIC.
    Holographic Graph Neuron: a Bio-Inspired Architecture for Pattern Processing2017Ingår i: IEEE Transactions on Neural Networks and Learning Systems, ISSN 2162-237X, E-ISSN 2162-2388, Vol. 28, nr 6, s. 1250-1262Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This article proposes the use of Vector Symbolic Architectures for implementing Hierarchical Graph Neuron, an architecture for memorizing patterns of generic sensor stimuli. The adoption of a Vector Symbolic representation ensures a one-layered design for the approach, while maintaining the previously reported properties and performance characteristics of Hierarchical Graph Neuron, and also improving the noise resistance of the architecture. The proposed architecture enables a linear (with respect to the number of stored entries) time search for an arbitrary sub-pattern.

  • 11.
    Kleyko, Denis
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Khan, Sumeer
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Yong, Suet-Peng
    Department of Computer and Information Sciences, Universiti Teknologi PETRONAS.
    Modality Classification of Medical Images with Distributed Representations Based on Cellular Automata Reservoir Computing2017Ingår i: Proceedings - International Symposium on Biomedical Imaging, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, s. 1053-1056Konferensbidrag (Refereegranskat)
    Abstract [en]

    Modality corresponding to medical images is a vital filter in medical image retrieval systems. This article presents the classification of modalities of medical images based on the usage of principles of hyper-dimensional computing and reservoir computing. It is demonstrated that the highest classification accuracy of the proposed method is on a par with the best classical method for the given dataset (83% vs. 84%). The major positive property of the proposed method is that it does not require any optimization routine during the training phase and naturally allows for incremental learning upon the availability of new training data.

  • 12.
    Gritsenko, Vladimir I.
    et al.
    International Research and Training Center for Information Technologies and Systems of the NAS of Ukraine and of Ministry of Education and Science of Ukraine.
    Rachkovskij, Dmitri A.
    International Research and Training Center for Information Technologies and Systems of the NAS of Ukraine and of Ministry of Education and Science of Ukraine.
    Frolov, Alexander A.
    Technical University of Ostrava.
    Gayler, Ross
    Kleyko, Denis
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Neural Distributed Autoassociative Memories: A Survey2017Ingår i: Cybernetics and Computer Engineering Journal, ISSN 0454-9910, Vol. 188, nr 2, s. 5-35Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Introduction. Neural network models of autoassociative, distributed memory allow storage and retrieval of many items (vectors) where the number of stored items can exceed the vector dimension (the number of neurons in the network). This opens the possibility of a sublinear time search (in the number of stored items) for approximate nearest neighbors among vectors of high dimension.

    The purpose of this paper is to review models of autoassociative, distributed memory that can be naturally implemented by neural networks (mainly with local learning rules and iterative dynamics based on information locally available to neurons).

    Scope. The survey is focused mainly on the networks of Hopfield, Willshaw and Potts, that have connections between pairs of neurons and operate on sparse binary vectors. We discuss not only autoassociative memory, but also the generalization properties of these networks. We also consider neural networks with higher-order connections and networks with a bipartite graph structure for non-binary data with linear constraints.

    Conclusions. In conclusion we discuss the relations to similarity search, advantages and drawbacks of these techniques, and topics for further research. An interesting and still not completely resolved question is whether neural autoassociative memories can search for approximate nearest neighbors faster than other index structures for similarity search, in particular for the case of very high dimensional vectors. 

  • 13.
    Kleyko, Denis
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    No Two Brains Are Alike: Cloning a Hyperdimensional Associative Memory Using Cellular Automata Computations2017Ingår i: Biologically Inspired Cognitive Architectures (BICA) for Young Scientists: First International Early Research Career Enhancement School on BICA and Cybersecurity (FIERCES 2017) / [ed] Alexei V. Samsonovich, Valentin V. Klimov, Cham: Springer, 2017, s. 91-100Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper looks beyond of the current focus of research on biologically inspired cognitive systems and considers the problem of replication of its learned functionality. The considered challenge is to replicate the learned knowledge such that uniqueness of the internal symbolic representations is guaranteed. This article takes a neurological argument “no two brains are alike” and suggests an architecture for mapping a content of the trained associative memory built using principles of hyperdimensional computing and Vector Symbolic Architectures into a new and orthogonal basis of atomic symbols. This is done with the help of computations on cellular automata. The results of this article open a way towards a secure usage of cognitive architectures in a variety of practical application domains.

  • 14.
    Osipov, Evgeny
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Kleyko, Denis
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Shapin, Alexey
    Siberian State University of Telecommunications and Information Sciences.
    An Approach for Self-Adaptive Path Loss Modelling for Positioning in Underground Environments2016Ingår i: International Journal of Antennas and Propagation, ISSN 1687-5869, E-ISSN 1687-5877, Vol. 2016, artikel-id 3424768Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper proposes a real-time self-adaptive approach for accurate path loss estimation in underground mines or tunnels based on signal strength measurements from heterogeneous radio communication technologies. The proposed model features simplicity of implementation. The methodology is validated in simulations and verified by measurements taken in real environments. The proposed method leverages accuracy of positioning matching the existing approaches while requiring smaller engineering efforts.

  • 15.
    Kleyko, Denis
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Rachkovskij, Dmitri A.
    International Research and Training Center for Information Technologies and Systems.
    Modification of Holographic Graph Neuron using Sparse Distributed Representations2016Ingår i: Procedia Computer Science, ISSN 1877-0509, E-ISSN 1877-0509, Vol. 88, s. 39-45Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This article presents a modification of the recently proposed Holographic Graph Neuron approach for memorizing patterns of generic sensor stimuli. The original approach represents patterns as dense binary vectors, where zeros and ones are equiprobable. The presented modification employs sparse binary distributed representations where the number of ones is less than zeros. Sparse representations are more biologically plausible because activities of real neuronsare sparse. Performance was studied comparing approaches for different sizes of dimensionality.

  • 16.
    Shapin, Alexey
    et al.
    Siberian State University of Telecommunications and Information Sciences.
    Kleyko, Denis
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Lyamin, Nikita
    Halmstad University, Siberian State University of Telecommunications and Information Sciences.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Melentyev, Oleg
    Siberian State University of Telecommunications and Information Sciences.
    Performance Peculiarities of Viterbi Decoder in Mathworks Simulink, GNU Radio and Other Systems with Likewise Implementation2016Rapport (Övrigt vetenskapligt)
    Abstract [en]

    The performance of convolutional codes decoding by the Viterbi algorithm should not depend on the particular distribution of zeros and ones in the input messages, as they are linear. However, it was identified that specific implementations of Add-Compare-Select unit for the Viterbi Algorithm demonstrate the decoding performance that depends on proportion of elements in the input message. It is conjectured that the modern commercial hard- and software defined communication equipment may also feature similar implementation and as such their decoding performance could also vary.

  • 17.
    Kleyko, Denis
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Gayler, Ross W.
    La Trobe University.
    Recognizing permuted words with Vector Symbolic Architectures: A Cambridge test for machines2016Ingår i: Procedia Computer Science, ISSN 1877-0509, E-ISSN 1877-0509, Vol. 88, s. 169-175Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper proposes a simple encoding scheme for words using principles of Vector Symbolic Architectures. The proposed encoding allows finding a valid word in the dictionary for a given permuted word (represented using the proposed approach) using only a single operation - calculation of Hamming distance to the distributed representations of valid words in the dictionary. The proposed encoding scheme can be used as an additional processing mechanism for models of word embedding, which also form vectors to represent the meanings of words, in order to match the distorted words in the text to the valid words in the dictionary.

  • 18.
    Wedekind, Daniel
    et al.
    Institute of Biomedical Engineering, TU Dresden.
    Kleyko, Denis
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Malberg, Hagen
    Institute of Biomedical Engineering, TU Dresden.
    Zaunseder, Sebastian
    Institute of Biomedical Engineering, TU Dresden.
    Wiklund, Urban
    Department of Biomedical Engineering & Informatics, Umea University, Umea, Sweden.
    Sparse Coding of Cardiac Signals for Automated Component Selection after Blind Source Separation2016Ingår i: Computing in cardiology, ISSN 2325-8861, E-ISSN 2325-887X, Vol. 43, s. 785-788, artikel-id 7868860Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Wearable sensor technology like textile electrodes provides novel ambulatory health monitoring solutions but most often goes along with low signal quality. Blind Source Separation (BSS) is capable of extracting the Electrocardiogram (ECG) out of heavily distorted multichannel recordings. However, permutation indeterminacy has to be solved, i.e. the automated selection of the desired BSS output. Accordingly, we exploit the sparsity of the ECG modeled as a spike train of successive heartbeats. A binary code derived from a two-item dictionary fpeak, no peakg and physiological a-priori information temporally represents every BSS output component. The (best) ECG component is automatically selected based on a modified Hamming distance comparing the components’ code with the expected code behavior. Non-standard ECG recordings from ten healthy subjects performing common motions while wearing a sensor garment were subsequently processed in 10 s segments with spatio-temporal BSS. Our sparsity-based selection RCODE achieved 98.1% heart beat detection accuracy (ACC) by selecting a single component each after BSS. Traditional component selection based on higher-order statistics (e.g. skewness) achieved only 67.6% ACC.

  • 19.
    Kleyko, Denis
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hostettler, Roland
    Department of Electrical Engineering and Automation, Aalto University.
    Lyamin, Nikita
    School of Information Technology, Halmstad University.
    Birk, Wolfgang
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Wiklund, Urban
    Department of Biomedical Engineering and Informatics, Umeå University.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Vehicle Classification using Road Side Sensors and Feature-free Data Smashing Approach2016Ingår i: 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC 2016), Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2016, s. 1988-1993, artikel-id 7795877Konferensbidrag (Refereegranskat)
    Abstract [en]

    The main contribution of this paper is a study of the applicability of data smashing – a recently proposed data mining method – for vehicle classification according to the “Nordic system for intelligent classification of vehicles” standard, using measurements of road surface vibrations and magnetic field disturbances caused by passing vehicles. The main advantage of the studied classification approach is that it, in contrast to the most of traditional machine learning algorithms, does not require the extraction of features from raw signals. The proposed classification approach was evaluated on a large dataset consisting of signals from 3074 vehicles. Hence, a good estimate of the actual classification rate was obtained. The performance was compared to the previously reported results on the same problem for logistic regression. Our results show the potential trade-off between classification accuracy and classification method’s development efforts could be achieved.

  • 20.
    Dai, William
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Riliskis, Laurynas
    Vyatkin, Valeriy
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Delsing, Jerker
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    A Configurable Cloud-Based Testing Infrastructure for Interoperable Distributed Automation Systems2015Ingår i: IECON 2014: 40th Annual Conference of the IEEE Industrial Electronics Society, Dallas, TX, USA , Oct. 29 2014-Nov. 1 2014, Piscataway, NJ: IEEE Communications Society, 2015, s. 2492-2498Konferensbidrag (Refereegranskat)
    Abstract [en]

    The interoperability between various automation systems is considered as one of the major character of future automation systems. Service-oriented Architecture is a possible interoperability enabler between legacy and future automation systems. In order to prove the interoperability between those systems, a verification framework is essential. This paper proposes a configurable cloud-based validation environment for interoperability tests between various distributed automation systems. The testing framework is implemented in a multi-layer structure which provides automated closed-loop testing from the protocol level to the system level. The testing infrastructure is also capable for simulating automation systems as well as wireless sensor networks in the cloud. Test cases could be automatically generated and executed by the framework.

  • 21.
    Kleyko, Denis
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hostettler, Roland
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system. Luleå tekniska universitet, Institutionen för system- och rymdteknik, CDT.
    Birk, Wolfgang
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Comparison of Machine Learning Techniques for Vehicle Classification using Road Side Sensors2015Ingår i: Proceedings of the 2015 IEEE 18th International Conference on Intelligent Transportation Systems: Las Palmas, 15-18 Sept. 2015, Piscataway, NJ: IEEE Communications Society, 2015, s. 572-577, artikel-id 7313192Konferensbidrag (Refereegranskat)
    Abstract [en]

    The main contribution of this paper is a comparison of different machine learning algorithms for vehicle classification according to the "Nordic system for intelligent classification of vehicles" standard using measurements of road surface vibrations and magnetic field disturbances caused by vehicles. The algorithms considered are logistic regression, neural networks, and support vector machines. They are evaluated on a large dataset, consisting of 3074 samples and hence, a good estimate of the actual classification rate is obtained. The results show that for the considered classification problem logistic regression is the best choice with an overall classification rate of 93.4%.

  • 22.
    Kleyko, Denis
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Papakonstantinou, Nikolaos
    VTT Technical Research Centre of Finland, Espoo.
    Vyatkin, Valeriy
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Mousavi, Arash
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Fault Detection in the Hyperspace: Towards Intelligent Automation Systems2015Ingår i: IEEE International Conference on Industrial Informatics: INDIN 2015, Cambridge, UK, July 22-24, 2015. Proceedings, Piscataway, NJ: IEEE Communications Society, 2015, s. 1219-1224, artikel-id 7281909Konferensbidrag (Refereegranskat)
    Abstract [en]

    This article presents a methodology for intelligent, biologically inspired fault detection system for generic complex systems of systems. The proposed methodology utilizes the concepts of associative memory and vector symbolic architectures, commonly used for modeling cognitive abilities of human brain. Compared to classical methods of artificial intelligence used in the context of fault detection the proposed methodology shows an unprecedented performance, while featuring zero configuration and simple operations.

  • 23.
    Kleyko, Denis
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Björk, Magnus
    Luleå tekniska universitet.
    Toresson, Henrik
    Luleå tekniska universitet.
    Öberg, Anton
    Luleå tekniska universitet.
    Fly-The-Bee: A game imitating concept learning in bees2015Ingår i: Procedia Computer Science, ISSN 1877-0509, E-ISSN 1877-0509, Vol. 71, s. 25-30Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This article presents a web-based game functionally imitating a part of the cognitive behavior of a living organism. This game is a prototype implementation of an artificial online cognitive architecture based on the usage of distributed data representations and Vector Symbolic Architectures. The game emonstrates the feasibility of creating a lightweight cognitive architecture, which is capable of performing rather complex cognitive tasks. The cognitive functionality is implemented in about 100 lines of code and requires few tens of kilobytes of memory for its operation, which make the concept suitable for implementing in low-end devices such as minirobots and wireless sensors.

  • 24.
    Osipov, Evgeny
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Mousavi, Arash
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    How to make a distributed programming course a big fun2015Ingår i: Frontiers in Education Conference, Conference Proceedings, ISSN 1539-4565Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This article presents experiences of teachers from Luleâ University of Technology when enhancing the teaching approach and depth of an undergraduate course on network programming and distributed applications. During the trial run of the course in the fall of 2013 agent-oriented programming and cloud technologies were married to provide students an exciting practical scenario and capability to test the performance of truly large scale distributed systems under extremely high traffic loads.

  • 25.
    Kleyko, Denis
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Gayler, Ross W.
    La Trobe University.
    Khan, Asad I.
    Monash University, Melbourne, VIC, Clayton School of Information Technology, CSIT, Monash University.
    Dyer, Adrian G.
    Media and Communication School, Royal Melbourne Institute of Technology.
    Imitation of honey bees’ concept learning processes using Vector Symbolic Architectures2015Ingår i: Biologically Inspired Cognitive Architectures, ISSN 2212-683X, E-ISSN 2212-6848, Vol. 14, s. 57-72Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This article presents a proof-of-concept validation of the use of Vector Symbolic Architectures as central component of an online learning architectures. It is demonstrated that Vector Symbolic Architectures enable the structured combination of features/relations that have been detected by a perceptual circuitry and allow such relations to be applied to novel structures without requiring the massive training needed for classical neural networks that depend on trainable connections.The system is showcased through the functional imitation of concept learning in honey bees. Data from real-world experiments with honey bees (Avarguès-Weber et al., 2012) are used for benchmarking. It is demonstrated that the proposed pipeline features a similar learning curve and accuracy of generalization to that observed for the living bees. The main claim of this article is that there is a class of simple artificial systems that reproduce the learning behaviors of certain living organisms without requiring the implementation of computationally intensive cognitive architectures. Consequently, it is possible in some cases to implement rather advanced cognitive behavior using simple techniques.

  • 26.
    Riliskis, Laurynas
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Symphony: A Framework for Accurate and Holistic WSN Simulation2015Ingår i: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 15, nr 3, s. 4677-4699Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Research on wireless sensor networks has progressed rapidly over the last decade, and these technologies have been widely adopted for both industrial and domestic uses. Several operating systems have been developed, along with a multitude of network protocols for all layers of the communication stack. Industrial Wireless Sensor Network (WSN) systems must satisfy strict criteria and are typically more complex and larger in scale than domestic systems. Together with the non-deterministic behavior of network hardware in real settings, this greatly complicates the debugging and testing of WSN functionality. To facilitate the testing, validation, and debugging of large-scale WSN systems, we have developed a simulation framework that accurately reproduces the processes that occur inside real equipment, including both hardware- and software-induced delays. The core of the framework consists of a virtualized operating system and an emulated hardware platform that is integrated with the general purpose network simulator ns-3. Our framework enables the user to adjust the real code base as would be done in real deployments and also to test the boundary effects of different hardware components on the performance of distributed applications and protocols. Additionally we have developed a clock emulator with several different skew models and a component that handles sensory data feeds. The new framework should substantially shorten WSN application development cycles.

  • 27.
    Kleyko, Denis
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Brain-like classifier of temporal patterns2014Ingår i: International Conference on Computer and Information Sciences, ICCOINS 2014, Kuala Lumpur, Malaysia, June 03-05, 2014. Proceedings, Piscataway, NJ: IEEE Communications Society, 2014, s. 1-6Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this article we present a pattern classification system which uses Vector Symbolic Architecture (VSA) for representation, learning and subsequent classification of patterns, as a showcase we have used classification of vibration sensors measurements to vehicles types. On the quantitative side the proposed classifier requires only 1 kB of memory to classify an incoming signal against of several hundred of training samples. The classification operation into N types requires only 2*N+1 arithmetic operations this makes the proposed classifier feasible for implementation on a low-end sensor nodes. The main contribution of this article is the proposed methodology for representing temporal patterns with distributed representation and VSA-based classifier.

  • 28.
    Sandin, Fredrik
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    Khan, Asad I.
    Clayton School of Information Technology, CSIT, Monash University.
    Dyer, Adrian G.
    Department of Physiology, Monash University.
    Amin, Anang Hudaya M.
    Faculty of Information Science & Technology (FIST), Multimedia University, Melaka.
    Indiveri, Giacomo
    Institute of Neuroinformatics, University of Zurich and ETH Zurich.
    Chicca, Elisabetta
    Cognitive Interaction Technology, Center of Excellence, Bielefeld University.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Concept Learning in Neuromorphic Vision Systems: What Can We Learn from Insects?2014Ingår i: Journal of Software Engineering and Applications, ISSN 1945-3116, E-ISSN 1945-3124, Vol. 7, nr 5, s. 387-395Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Vision systems that enable collision avoidance, localization and navigation in complex and uncertain environments are common in biology, but are extremely challenging to mimic in artificial electronic systems, in particular when size and power limitations apply. The development of neuromorphic electronic systems implementing models of biological sensory-motor systems in silicon is one promising approach to addressing these challenges. Concept learning is a central part of animal cognition that enables appropriate motor response in novel situations by generalization of former experience, possibly from a few examples. These aspects make concept learning a challenging and important problem. Learning methods in computer vision are typically inspired by mammals, but recent studies of insects motivate an interesting complementary research direction. There are several remarkable results showing that honeybees can learn to master abstract concepts, providing a road map for future work to allow direct comparisons between bio-inspired computing architectures and information processing in miniaturized “real” brains. Considering that the brain of a bee has less than 0.01% as many neurons as a human brain, the task to infer a minimal architecture and mechanism of concept learning from studies of bees appears well motivated. The relatively low complexity of insect sensory-motor systems makes them an interesting model for the further development of bio-inspired computing architectures, in particular for resource-constrained applications such as miniature robots, wireless sensors and handheld or wearable devices. Work in that direction is a natural step towards understanding and making use of prototype circuits for concept learning, which eventually may also help us to understand the more complex learning circuits of the human brain. By adapting concept learning mechanisms to a polymorphic computing framework we could possibly create large-scale decentralized computer vision systems, for example in the form of wireless sensor networks.

  • 29.
    Osipov, Evgeny
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Khan, Asad
    Monash University, Melbourne, VIC.
    Amin, Anang Hudaya
    Holographic Graph Neuron2014Ingår i: International Conference on Computer and Information Sciences, IEEE Communications Society, 2014, s. 1-6Konferensbidrag (Refereegranskat)
    Abstract [en]

    This article proposes the usage of Vector Symbolic Architectures for implementing Hierarchical Graph Neuron. The adoption of VSA representation maintains previously reported properties and performance characteristics of HGN and further makes it suitable for implementation in distributed wireless sensor networks of tiny devices.

  • 30.
    Osipov, Evgeny
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Vyatkin, Valeriy
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Intelligent Industrial Processes: Enabling research challenges by Dependable Communication and Computation2014Rapport (Övrigt vetenskapligt)
  • 31.
    Riliskis, Laurynas
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Maestro: an orchestration framework for large scale WSN simulations2014Ingår i: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 14, nr 3, s. 5392-5414Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Contemporary wireless sensor networks (WSNs) have evolved into large and complex systems and are one of the main technologies used in cyber-physical systems and the Internet of Things. Extensive research on WSNs has led to the development of diverse solutions at all levels of software architecture, including protocol stacks for communications. This multitude of solutions is due to the limited computational power and restrictions on energy consumption that must be accounted for when designing typical WSN systems. It is therefore challenging to develop, test and validate even small WSN applications, and this process can easily consume significant resources. Simulations are inexpensive tools for testing, verifying and generally experimenting with new technologies in a repeatable fashion. Consequently, as the size of the systems to be tested increases, so does the need for large-scale simulations. This article describes a tool called Maestro for the automation of large-scale simulation and investigates the feasibility of using cloud computing facilities for such task. Using tools that are built into Maestro, we demonstrate a feasible approach for benchmarking cloud infrastructure in order to identify cloud Virtual Machine (VM)instances that provide an optimal balance of performance and cost for a given simulation.

  • 32.
    Kleyko, Denis
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Lyamin, Nikita
    Halmstad University.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Modified algorithm of dynamic frequency hopping (DFH) in the IEEE 802.22 standard2014Ingår i: Multiple Access Communications: 7th International Workshop, MACOM 2014, Halmstad, Sweden, August 27-28, 2014. Proceedings / [ed] Magnus Jonsson; Alexey Vinel; Boris Bellalta; Evgeny Belyaev, New York: Encyclopedia of Global Archaeology/Springer Verlag, 2014, s. 75-83Konferensbidrag (Refereegranskat)
    Abstract [en]

    IEEE 802.22 Cognitive Wireless Regional Area Networks is a first standard of wireless terrestrial system relying on cognitive radio concept and operating as an opportunistic system in the the vacant unoccupied frequency spaces of the licensed TV-frequency band. Concept of the proposed standard assumes special functionality to protect the operation of the primary licensed subscribers. Dynamic Frequency Hopping is the mechanism for providing connectionless operation of Wireless Regional Area Networks systems while ensuring protection of transmissions from the primary users. During its operation regular time gaps appear on the involved frequency channels. This paper introduces the concept of the efficient reuse of the vacant frequency resources appearing when using the Dynamic Frequency Hopping mode. The scheme for consecutive-parallel inclusion of the new Dynamic Frequency Hopping Communities-members in the Dynamic Frequency Hopping mode is presented. The proposed approach allows to significantly decrease transition time.

  • 33.
    Kleyko, Denis
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    On bidirectional transitions between localist and distributed representations: The case of common substrings search using Vector Symbolic Architecture2014Ingår i: Procedia Computer Science, ISSN 1877-0509, E-ISSN 1877-0509, Vol. 41, s. 104-113Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The contribution of this article is twofold. First, it presents an encoding approach for seamless bidirectional transitions between localist and distributed representation domains. Second, the approach is demonstrated on the example of using Vector Symbolic Architecture for solving a problem of finding common substrings. The proposed algorithm uses elementary operations on long binary vectors. For the case of two patterns with respective lengths L1 and L2 it requires Θ(L1 + L2 – 1) operations on binary vectors, which is equal to the suffix trees approach – the fastest algorithm for this problem. The simulation results show that in order to be robustly detected by the proposed approach the length of a common substring should be more than 4% of the longest pattern.

  • 34.
    Kleyko, Denis
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Patil, Sandeep
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Vyatkin, Valeriy
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Pang, Zhibo
    ABB AB, Corporate research.
    On Methodology of Implementing Distributed Function Block Applications using TinyOS WSN nodes2014Ingår i: Proceedings of 2014 IEEE 19th International Conference on Emerging Technologies & Factory Automation (ETFA 2014): Barcelona, Spain, 16-19 Sept. 2014, Piscataway, NJ: IEEE Communications Society, 2014, artikel-id 7005107Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper presents a feasibility study of implementing parts of a distributed function block application as TinyOS modules running on Wireless Sensors as a part of Wireless Sensor Network. The paper first briefly describes underlying technologies and gives motivation for implementation of function blocks in TinyOS. The paper then presents implementation details about TinyOS realization of the one of the function block, which is a part of bigger distributed control application with the help of distributed function block application.

  • 35.
    Osipov, Evgeny
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Riliskis, Laurynas
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Lehikoinen, Timo
    VTT Technical Research Centre of Finland, Espoo.
    Kämäräinen, Jukka
    VTT Technical Research Centre of Finland, Espoo.
    Pellinen, Marko
    VTT Technical Research Centre of Finland, Espoo.
    Simulation Based Studies of Machine-to-Machine Communications2014Ingår i: Wireless Networking for Moving Objects: Protocols, Architectures, Tools, Services and Applications, New York: Encyclopedia of Global Archaeology/Springer Verlag, 2014, s. 239-254Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    Simulations are essential for understanding complex systems such as Cyber Physical Systems. The creation of reliable multidisciplinary simulation tools that can be used to support the entire development process has been identified as a major scientific goal in several research roadmaps and agendas for the coming 15 years. This chapter presents two showcases, which highlight the necessity of trustworthy simulation tools, especially in the case of ma- chine-to-machine communications. First the performance of UWB radio technology in context of vehicle automation is evaluated. Second the experiences from performing the entire cycle of protocol development for machine-to-machine communications are presented. The two presented showcases support a conclusion that a successful simulation platform should have a us- er-friendly simulation framework and models that support virtualization. This will enable the incorporation of simulations into day-to-day engineering prac- tice and thereby shrink the gap between the real and the virtual developing environments.

  • 36.
    Osipov, Evgeny
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Riliskis, Laurynas
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Eldstål-Damlin, Albin
    Burakov, Michael
    Nordberg, Mats
    Ericsson.
    Wang, Min
    Ericsson.
    An improved model of LTE random access channel2013Ingår i: 2013 IEEE 77th Vehicular Technology Conference (VTC Spring 2013): 2-5 June 2013, Dresden, Germany, Piscataway, NJ: IEEE Communications Society, 2013Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this article, we report on a mathematical model for the throughput and delay of LTE's Random Access Channel (RACH). The model is an improvement of a cell-level Markov model of Multichannel slotted ALOHA proposed previously in the literature. The improvements concern accounting for a possibility of contention resolution in the case when terminals select same preambles and distinguishing initially-transmitting nodes from retransmitting nodes. The improved model is verified and agrees with measurements obtained from a discrete-time event-based simulator of an LTE cell

  • 37.
    Riliskis, Laurynas
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Coexistence of Cloud Technology and IT Infrastructure in Higher Education2013Ingår i: 2013 Frontiers in Education Conference (FIE 2013): Oklahoma City, Olöahoma, USA, 23-26 October 2013, Piscataway, NJ: IEEE Communications Society, 2013, s. 805-807Konferensbidrag (Refereegranskat)
    Abstract [en]

    Most of the current IT-infrastructures at Universities were designed and deployed at times of mostly campus based education, following the "one solution fits all" approach. Nowadays, with the growing number of courses given on distance and unique requirements on software content in almost every course in all disciplines the existing infrastructure became extremely stiff and inefficient. In many cases it fails providing flexible services with acceptable quality both to teachers and students. Another problem appears with the all growing mobility of students in the scope of Erasmus Mundus programme and numerous bilateral agreements between universities. The uncertainty in number of students to be handled in each semester (even in the scope of a particular course) makes it difficult for the IT departments to estimate the need and to correspondingly dimension the IT-system. Normally, IT administrations at universities over-dimension their infrastructures in order to stay competitive and provide satisfactory quality of experience. This obviously leads to an increased cost associated with purchasing and maintaining the equipment. Besides the economical component the environmental impact becomes one of the critical factors that universities have to deal with nowadays. Universities as governmental organizations need to take environmental considerations into account when implementing European Union policies on ICT sustainability. Cloud technology and specifically infrastructure as a service (IaaS) providers is an excellent alternative to an outdated inefficient local infrastructures. Early 2012 Luleå University of Technology started a project on adopting cloud technology for implementing the university's IT-infrastructure. This work-in-progress article will describe the results of its pre-study phase aiming at understanding a feasibility of integrating and/or migrating key infrastructure components into an IaaS system and opening ways for making university's resources more accessible to wider public. Numbers of logistical, technical and education related challenges, however, make such transition far from being trivial. This article focuses on the educational aspect of the pre-study. Specifically, work flows in education process of several courses in different disciplines in natural and engineering sciences were analysed from the student and teacher perspectives. In the article a schematic of a sustainable IT infrastructure adjusted to the needs of higher education will be drafted. Further, technical readiness and challenges of using cloud technology for university scale IT-infrastructure will be discussed.

  • 38.
    Wolosz, Krzysztof
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Bodin, Ulf
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Eliasson, Jens
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    Cognitive load-control for congested Wireless Sensor Network channels2013Ingår i: 2013 IFIP Wireless Days (WD 2013: Valencia, Spain, 13-15 Nov 2013, Piscataway, NJ: IEEE Communications Society, 2013Konferensbidrag (Refereegranskat)
    Abstract [en]

    Modern wireless sensors transmit at high rates and changing transmission patterns. They may individually or collectively select how much data shall be sent depending on predefined rules tied to properties of measured data. Sending rates thereby change triggered by events appearing in the sensor environment. With wireless technologies such as 802.15.4 (ZigBee) having limited capacity high transmission needs can easily cause overload resulting in decreased throughput. This paper presents a load control mechanism that uses multiple inputs, demand for transmission capacity and perceived quality of each sensor node, to properly configure sending rates of these nodes. The mechanism is based on Fuzzy Logic and quality assessed with utility functions for packet loss and throughput. NS-3 simulation results show clear improvements in overall throughput at high loads with the mechanism compared to without.

  • 39.
    Osipov, Evgeny
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Riliskis, Laurynas
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Educating Innovators of Future Internet of Things2013Ingår i: 2013 Frontiers in Education Conference (FIE 2013): Oklahoma City, Olöahoma, USA, 23-26 October 2013, Piscataway, NJ: IEEE Communications Society, 2013, s. 1352-1358Konferensbidrag (Refereegranskat)
    Abstract [en]

    Clouds, Communicating Machines, Social Networking, Big Data, innovative web-services are the buzz words that currently ramp up the interest in computer science education amongst potential students. The current trend in CS education is to introduce an innovation component into the content of undergraduate and graduate courses facilitating out of the box thinking. In the fall of 2012 the content of three undergraduate courses running in parallel at Luleå University of Technology were aligned in the theoretical and practical parts projecting the individual contents to a holistic scenario of the Internet of Things. The practical goal of the trial was to provide skills of developing innovative, cutting-edge IT solutions. The trial courses were: Wireless sensor networks, Distributed applications, and Network programming. The first two courses are given on the fourth year while the later course is given on the second year of the CS program. The theoretical content of three courses allowed creating a scenario covering the whole technology chain of the Internet of Things: gathering and communicating sensory data; scalable and distributed processing of big data; value-added, human relevant network services. In the practical part students in the three courses (total 60) acted as start-up companies in the respective technology domain. These ``start-ups'' were assigned a task to deliver a common holistic system given time, performance and budget constrains. This task required students in a particular course to constantly communicate to other students outside the course's boundaries. Through these activities students were trained on skills for industrial level development and integration of complex IT systems. On a technical side all courses were conducted using Amazon Web Services as a common computing platform. This choice allowed us to draw interesting conclusions about students work load, the degree of their actual involvement in the learning process as well as economical costs. In the sensor network course a pedagogy-oriented, close-to-reality, real-time simulation environment was used to substantially facilitate experimentation with large quantities of communicating sensors. Using AWS as a platform for the other two courses gave students a possibility of experimenting with hundreds of servers while training the skills in developing commercial scale software. As a result of evaluations in the respective courses we conjecture that the goal of the trial is successfully achieved. The innovative component was highly valued by the majority of students. Most of the students confirmed that exposing them to the ``big picture'' and product-based learning substantially increased their involvement and motivation in the learning process. On the technical side several non-conventional applications of the theoretical content were observed in all three courses. One of the successful resulting systems featured a unique integration of real-time sensory data with a popular social network. The full article will describe the details of the courses' structure along with the associated logistical and technical challenges. We present the illustrative achievements as well as the analysis of students' feedback. The article will be concluded with the discussion of learned positive and negative lessons put in the context of recent theories in CS education.

  • 40.
    Dudin, Alexander
    et al.
    BSU.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Dudin, Sergey
    BSU.
    Schelén, Olov
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Socio-behavioral scheduling of time-frequency resources for modern mobile operators2013Ingår i: Modern Probabilistic Methods for Analysis of Telecommunication Networks: Belarusian Winter Workshops in Queueing Theory, BWWQT 2013, Minsk, Belarus, January 28-31, 2013. Proceedings, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2013, s. 69-82Konferensbidrag (Refereegranskat)
    Abstract [en]

    This article presents a mathematical foundation for scheduling of batch data produced by mobile end users over the time-frequency resources provided by modern mobile operators. We model the mobile user behavior by Batch Markovian Arrival Process, where a state corresponds to a specific user data activity (i.e. sending a photo, writing a blog message, answering an e-mail etc). The state transition is marked by issuing a batch of data of the size typical to the activity. To model the changes of user behavior caused by the environment, we introduce a random environment which affects the intensities of transitions between states (i.e., the probabilities of the user data activities). The model can be used for calculating probability of packet loss and probability of exceeding the arbitrarily fixed value by the sojourn time of a packet in the system conditional that the packet arrives to the system at moments when the random environment has a given state. This allows to compute the realistic values of these probabilities and can help to properly fix their values that can be guaranteed, depending on the state of the random environment, by a service provider

  • 41.
    Riliskis, Laurynas
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Symphony - simulation, emulation and virtualization framework for accurate WSN experimentation2013Ingår i: ICSE 2013: proceedings of the 2013 International Conference on Software Engineering,, New York: ACM Digital Library, 2013, s. 1-6Konferensbidrag (Refereegranskat)
    Abstract [en]

    We have developed a simulation framework for testing and validation of WSN applications which closely resembles processes happening inside real equipment including hardware and software induced delays. The core of the framework consists of a virtualized operating system and an emulated hardware platform integrated with a general purpose network simulator ns-3. Besides an ability of experimenting with the real code base as in the real deployments our framework allows testing the boundary effects of different hardware components on the performance of distributed applications and protocols. All in all the presented framework allows to substantially shorten the development cycle of WSN applications.

  • 42.
    Kleyko, Denis
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Lyamin, Nikita
    Siberian State University of Telecommunications and Information Sciences.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Riliskis, Laurynas
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Dependable MAC layer architecture based on holographic data representation using hyper-dimensional binary spatter codes2012Ingår i: Multiple Access Communications: 5th International Workshop, MACOM 2012, Maynooth, Ireland, November 19-20, 2012. Proceedings / [ed] Boris Bellalta, Heidelberg: Encyclopedia of Global Archaeology/Springer Verlag, 2012, s. 134-145Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this article we propose the usage of binary spatter codes and distributed data representation for communicating loss and delay sensitive data in event-driven sensor and actuator networks. Using the proposed data representation technique along with the medium access control protocol the mission critical control information can be transmitted with assured constant delay in deployments exposing below 0 dB signal-to-noise ratio figures.

  • 43.
    Chaltseva, Anna
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    On passive characterization of aggregated traffic in wireless networks2012Ingår i: Wired/Wireless Internet Communication: 10th International Conference, WWIC 2012, Proceedings, New York: Encyclopedia of Global Archaeology/Springer Verlag, 2012, s. 282-289Konferensbidrag (Refereegranskat)
    Abstract [en]

    We present a practical measurement-based characterization of the aggregated traffic on microseconds time scale in wireless networks. The model allows estimating the channel utilization for the period of time required to transmit data structures of different sizes (short control frames and a data packet of the maximum size). The presented model opens a possibility to mitigate the effect of interferences in the network by optimizing the communication parameters of the MAC layer (e.g. the size of contention window, retransmission strategy, etc.) for the forthcoming transmission. The article discusses issues and challenges associated with the PHY-layer characterization of the network state.

  • 44.
    Osipov, Evgeny
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Riliskis, Laurynas
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Kleyko, Denis
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Lyamin, Nikita
    Siberian State University of Telecommunications and Information Sciences.
    Packet-less medium access approach for dependable wireless event passing in highly noisy environments2012Rapport (Övrigt vetenskapligt)
    Abstract [en]

    In this article we propose the usage of binary spatter codes and distributed data representation for communicating loss and delay sensitive data in event-driven sensor and actuator networks. Using the proposed data representation technique along with the medium access control protocol the mission critical control information can be transmitted with constant delay in deployments exposing below 0 dB signal-to-noise ratio figures.

  • 45.
    Riliskis, Laurynas
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Berdajs, Jan
    University of Ljubljana, Faculty of Computer and Information Science.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Brodnik, Andrej
    University of Ljubljana, Faculty of Computer and Information Science.
    Reality considerations when designing a TDMA-FDMA based link-layer for real-time WSN2012Ingår i: Multiple Access Communications: 5th International Workshop, MACOM 2012, Maynooth, Ireland, November 19-20, 2012. Proceedings / [ed] Boris Bellalta, Encyclopedia of Global Archaeology/Springer Verlag, 2012, s. 93-96Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this article we elaborate on reality considerations when deploying wireless sensor networks with strict end-to-end delay requirement. Our improvements are particularly important for a design and implementation of strict real-time systems while at the same time we decrease overall power consumption. Firstly, we design and implement application tailored TDMA-FDMA medium access protocol with guaranteed end-to-end delay. Secondly, we integrate in the implementation of the protocol the bootstrapping mechanism and thirdly, the time synchronization mechanism. Next, we show that by combining medium access protocol, bootstrapping, and time synchronization mechanisms within the link-layer, we can limit on average clock drift in the network to 0.5 micro seconds, as well as achieve 81 % energy efficiency while keeping collision probability at its minimum of 1 %. Finally, we conclude with challenges and lessons learned in real-world deployment of TDMA/FDMA based link-layer with guaranteed end-to-end delay in wireless sensor networks.

  • 46.
    Khattak, Rabiullah
    et al.
    Luleå tekniska universitet.
    Chaltseva, Anna
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Riliskis, Laurynas
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Bodin, Ulf
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Comparison of wireless network simulators with multihop wireless network testbed in corridor environment2011Ingår i: Wired/wireless internet communications: 9th IFIP TC 6 International Conference, WWIC 2011, Vilanova i la Geltrú, Spain, June 15-17, 2011 ; proceedings / [ed] Xavier Masip-Bruin, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2011, s. 80-91Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper presents a comparative study between results of a single channel multihop wireless network testbed and the network simulators ns-2 and ns-3. We explore how well these simulators reflect reality with their standard empirical radio modeling capabilities. The environment studied is a corridor causing wave-guiding propagation phenomena of radio waves, which challenges the radio models used in the simulators. We find that simulations are roughly matching with testbed results for single flows, but clearly deviate from testbed results for concurrent flows. The mismatch between simulations and testbed results is due to imperfect wireless propagation channel modeling. This paper reveals the importance of validating simulation results when studying single channel multihop wireless network performance. It further emphasizes the need for validation when using empirical radio modeling for more complex environments such as corridors.

  • 47.
    Riliskis, Laurynas
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hostettler, Roland
    Luleå tekniska universitet, Institutionen för system- och rymdteknik.
    Mäkitaavola, Henrik
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    Birk, Wolfgang
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Eliasson, Jens
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    Enabling remote controlled road surface networks for enhanced ITS2011Konferensbidrag (Refereegranskat)
    Abstract [en]

    Intelligent Transportation Systems (ITS) will, in the future, play a key role to improve transportation efficiency and safety. However, cost-benefit of deploying traditional ITS is retarded by expensive equipment, infrastructure, installation and maintenance. The demo presents a replica of a real world experimental ITS application using recently proposed Road Surface Network architecture. The demonstrated "intelligent roundabout'' application is intended to warn and inform drivers about an upcoming roundabout and to prevent driving straight into collision. We show a lab prototype system consisting of: an authentic sensor node platform enabled for car detection, secure multihop communications and the running light application, a base station with system control center.

  • 48.
    Chaltseva, Anna
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    On passive characterization of aggregated traffic in wireless networks2011Rapport (Övrigt vetenskapligt)
    Abstract [en]

    We present a practical measurement-based model of aggregated traffic intensity on microseconds time scale for wireless networks. The model allows estimating the traffic intensity for the period of time required to transmit data structures of different size (short control frames and a data packet of the maximum size). The presented model opens a possibility to mitigate the effect of interferences in the network by optimizing the communication parameters of the MAC layer (e.g. size of contention window, retransmission strategy, etc.) for the forthcoming transmission to minimize the packet collision probability and further increase network's capacity. We also discuss issues and challenges associated with PHY-layer characterization of the network state.

  • 49.
    Osipov, Evgeny
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Riliskis, Laurynas
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    On synthesis of dependable MAC protocol for two real-world WSN applications2011Ingår i: 2011 Baltic Congress on Future Internet Communications (BCFIC Riga), IEEE Communications Society, 2011, s. 41-49Konferensbidrag (Refereegranskat)
    Abstract [en]

    Currently, when matter comes to engineer a communication system for a new WSN application with a unique set of dependability requirements, the developer should undergo a lengthy process of analyzing the existing solutions in order to select appropriate functionality. In this article we argue that because of variety of wireless sensor network applications there is a clear need for a systematic approach to develop application-tailored communication solutions. The core of this methodology constitute functional components with known reliability and security properties and the rules of combining these components in a communication system. On the example of engineering MAC protocol for two real world applications, we demonstrate a line of dependable reasoning and identify components satisfying the dependability requirements of the application.

  • 50.
    Birk, Wolfgang
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Hostettler, Roland
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, CDT.
    Lundberg Nordenvaad, Magnus
    Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle, Industriell Ekonomi.
    Eliasson, Jens
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    Gylling, Arne
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, CDT.
    Delsing, Jerker
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    Mäkitaavola, Henrik
    Project: iRoad2011Övrigt (Övrig (populärvetenskap, debatt, mm))
12 1 - 50 av 85
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