Ändra sökning
Avgränsa sökresultatet
12 1 - 50 av 88
RefereraExporteraLänk till träfflistan
Permanent länk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Träffar per sida
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sortering
  • Standard (Relevans)
  • Författare A-Ö
  • Författare Ö-A
  • Titel A-Ö
  • Titel Ö-A
  • Publikationstyp A-Ö
  • Publikationstyp Ö-A
  • Äldst först
  • Nyast först
  • Skapad (Äldst först)
  • Skapad (Nyast först)
  • Senast uppdaterad (Äldst först)
  • Senast uppdaterad (Nyast först)
  • Disputationsdatum (tidigaste först)
  • Disputationsdatum (senaste först)
  • Standard (Relevans)
  • Författare A-Ö
  • Författare Ö-A
  • Titel A-Ö
  • Titel Ö-A
  • Publikationstyp A-Ö
  • Publikationstyp Ö-A
  • Äldst först
  • Nyast först
  • Skapad (Äldst först)
  • Skapad (Nyast först)
  • Senast uppdaterad (Äldst först)
  • Senast uppdaterad (Nyast först)
  • Disputationsdatum (tidigaste först)
  • Disputationsdatum (senaste först)
Markera
Maxantalet träffar du kan exportera från sökgränssnittet är 250. Vid större uttag använd dig av utsökningar.
  • 1.
    Birk, Wolfgang
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Eliasson, Jens
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    Lindgren, Per
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Riliskis, Laurynas
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Road surface networks technology enablers for enhanced ITS2010Ingår i: 2010 IEEE Vehicular Networking Conference, VNC 2010: Jersey City, NJ ; 13-15 Dec 2010, Piscataway, NJ: IEEE Communications Society, 2010, s. 152-159Konferensbidrag (Refereegranskat)
    Abstract [en]

    The increased need for mobility has led to transportation problems like congestion, accidents and pollution. In order to provide safe and efficient transport systems great efforts are currently being put into developing Intelligent Transport Systems (ITS) and cooperative systems. In this paper we extend proposed solutions with autonomous on-road sensors and actuators forming a wireless Road Surface Network (RSN). We present the RSN architecture and design methodology and demonstrate its applicability to queue-end detection. For the use case we discuss the requirements and technological solutions to sensor technology, data processing and communication. In particular the MAC protocol is detailed and its performance assessed through theoretical verification. The RSN architecture is shown to offer a scalable solution, where increased node density offers more precise sensing as well as increased redundancy for safety critical applications. The use-case demonstrates that RSN solutions may be deployed as standalone systems potentially integrated into current and future ITS. RSN may provide both easily deployable and cost effective alternatives to traditional ITS (with a direct impact independent of penetration rate of other ITS infrastructures - i.e., smart vehicles, safe spots etc.) as well as provide fine grain sensory information directly from the road surface to back-end and cooperative systems, thus enabling a wide range of ITS applications beyond current state of the art.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 2.
    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))
  • 3.
    Birk, Wolfgang
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    On the design of cooperative road infrastructure systems2008Ingår i: Reglermöte 2008: proceedings / [ed] Thomas Gustafsson; Wolfgang Birk; Andreas Johansson, Luleå: Luleå tekniska universitet, 2008Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    This paper discusses the design of cooperative road infrastructure systems for infrastructure-based driving support functions. The background of such systems is mapped out and it is shown that there is a need for a cross disciplinary approach. Using an example of a support function, namely the overtaking support, it is shown that such a system is feasible. The different challenges and technological problems that are identified are given and the future work is indicated.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 4.
    Birk, Wolfgang
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Eliasson, Jens
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, EISLAB.
    iRoad - cooperative road infrastructure systems for driver support2009Ingår i: 16th World Congress and Exhibition on Intelligent Transport Systems 2009: 16th ITS World Congress ; Stockholm, Sweden, 21 - 25 September 2009, Red Hook: Curran Associates, Inc., 2009Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper discusses the design and implementation of a cooperative road infrastructure systems, which uses an intelligent road surface. Using an overtaking assist feature as an example it is shown how such a feature can be designed and implemented on a road infrastructure and integrated with drivers and passengers using IMS. The feasibility of this feature is assessed from a functional and communication perspective. Moreover, first results from real-life tests on the Swedish highway E4 are presented which motivate the next research and development steps.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 5.
    Birk, Wolfgang
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Riliskis, Laurynas
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hesler, Alban
    NEC.
    Modular design and performance ranking of communication protocols2009Rapport (Övrigt vetenskapligt)
    Abstract [en]

    In this deliverable we present a systematic approach towards designing modularized protocols and rank a contribution of their components to the overall system performance. In the nutshell, this approach is based onthree steps: 1.) identifying adjustable parameters in existing protocols, 2.) ranking their influence on the system-level performance metrics and 3.) defining protocol modules exposing the parameters of the highest rank. To this end we present the definition of the components for constructing MAC protocols based on ranking of the impact of adjustable parameters on the overall system performance. We also overview a ranking method for functional blocks of protocols on the routing layer.

  • 6.
    Buttyan, Levente
    et al.
    BME.
    Acs, Gergely
    BME.
    Schaffer, Peter
    BME.
    Farkas, Karoly
    BME.
    Bencsath, Boldizsar
    BME.
    Thong, Ta Vinh
    BME.
    Laszka, Aron
    BME.
    Grilo, Antonio
    INOV.
    Hessler, Alban
    NEC.
    Riliskis, Laurynas
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Perito, Daniele
    INRIA.
    Castelluccia, Claude
    INRIA.
    Dependability concepts, models, and analysis of networking mechanisms for WSANs2009Rapport (Övrigt vetenskapligt)
    Abstract [en]

    In this deliverable, we report on the results of Work Package 3 (Dependable Networking) obtained in the first year of the WSAN4CIP Project. These results are related to the identification of the design principles of dependable networking mechanisms for WSANs. In our work, and hence, in this deliverable, we follow the layered model of networking protocol stacks: We identify the most important dependability concepts and models at the physical, MAC (Medium Access Control), routing, and transport layers, and we analyze existing networking protocols from the different layers proposed in the literature with respect to the identified dependability properties.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 7.
    Chaltseva, Anna
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Empirical cross-layer model of TCP throughput in multihop wireless chain2010Rapport (Övrigt vetenskapligt)
    Abstract [en]

    Analysis of TCP throughput in multihop wireless networks is a continuously important research topic. Yet a neat and practically useful formula for the TCP transfer rate similar to the macroscopic model of TCP in the Internet, however, capturing the cross-layer dependencies is unavailable for wireless networks. In this paper we statistically analyze the significance of parameters on physical, MAC and transport layers in a multihop wireless chains and derive a practically usable cross-layer throughput formula. The resulting model allows estimation of the throughput with less than 2% error.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 8.
    Chaltseva, Anna
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Empirical predictor of TCP throughput on a multihop wireless path2010Ingår i: Smart spaces and next generation Wired/Wireless networking: third Conference on Smart Spaces, ruSMART 2010, and 10th international conference, NEW2AN 2010, St. Petersburg, Russia, August 23-25, 2010 ; proceedings / [ed] Sergey Balandin; Roman Dunaytsev; Yevgeni Koucheryavy, Encyclopedia of Global Archaeology/Springer Verlag, 2010, s. 323-334Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper addresses a question of predicting TCP throughput over a multihop wireless path. Since it is useful for a variety of applications it is desirable that TCP throughput prediction technique introduces low-overhead while avoiding active measurement techniques. Analytical derivation of the throughput predictor for multihop wireless networks is difficult if not impossible at all due to complex cross-layer dependencies. In this article we statistically analyze the significance of parameters on physical, MAC and transport layers in a multihop wireless chain and empirically derive a practically usable throughput predictor. The resulting model allows prediction of the throughput with less than 2% error.

  • 9.
    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.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 10.
    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.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 11.
    Cheng, Haibo
    et al.
    Shenyang Institute of Automation, Chinese Academy of Sciences,Lab. of Networked Control Systems,Shenyang,China.
    Han, Xiaoning
    Shenyang Institute of Automation, Chinese Academy of Sciences,Lab. of Networked Control Systems,Shenyang,China.
    Zeng, Peng
    Shenyang Institute of Automation, Chinese Academy of Sciences,Lab. of Networked Control Systems,Shenyang,China.
    Yu, Haibin
    Shenyang Institute of Automation, Chinese Academy of Sciences,Lab. of Networked Control Systems,Shenyang,China.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Vyatkin, Valeriy
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    ANN based Interwell Connectivity Analysis in Cyber-Physical Petroleum Systems2019Ingår i: Proceedings: 2019 IEEE 17th International Conference on Industrial Informatics (INDIN), IEEE, 2019, s. 199-205Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    In cyber-physical petroleum systems (CPPS), accurate estimation of interwell connectivity is an important process to know reservoir properties comprehensively, determine water injection rate scientifically, and enhance oil recovery effectively for oil and gas (O&G) field. In this study, an artificial neural network (ANN) based analysis method is proposed to estimate interwell connectivity. The generated neural network is used to define the mapping function between production wells and surrounding injection wells based on the historical water injection and liquid production data. Finally, the proposed method is applied to a synthetic reservoir model. Experimental results show that ANN based approach is an efficient method for analyzing interwell connectivity.

  • 12.
    Cheng, Haibo
    et al.
    State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China. Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, China. Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China. University of Chinese Academy of Sciences, Beijing 100049, China.
    Vyatkin, Valeriy
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap. Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Zeng, Peng
    State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China. Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, China. Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China.
    Yu, Haibin
    State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China. Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, China. Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China.
    LSTM Based EFAST Global Sensitivity Analysis for Interwell Connectivity Evaluation Using Injection and Production Fluctuation Data2020Ingår i: IEEE Access, E-ISSN 2169-3536, Vol. 8, s. 67289-67299Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In petroleum production system, interwell connectivity evaluation is a significant process to understand reservoir properties comprehensively, determine water injection rate scientifically, and enhance oil recovery effectively for oil and gas field. In this paper, a novel long short-term memory (LSTM) neural network based global sensitivity analysis (GSA) method is proposed to analyse injector-producer relationship. LSTM neural network is employed to build up the mapping relationship between production wells and surrounding injection wells using the massive historical injection and production fluctuation data of a synthetic reservoir model. Next, the extended Fourier amplitude sensitivity test (EFAST) based GSA approach is utilized to evaluate interwell connectivity on the basis of the generated LSTM model. Finally, the presented LSTM based EFAST sensitivity analysis method is applied to a benchmark test and a synthetic reservoir model. Experimental results show that the proposed technique is an efficient method for estimating interwell connectivity.

  • 13.
    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.

  • 14.
    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.

  • 15.
    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.

  • 16.
    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

  • 17.
    Elkotob, Muslim
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Enabling communication service reconfigurability via guided cross layering2009Rapport (Övrigt vetenskapligt)
    Abstract [en]

    A system architecture which natively supports cross-layer design in a general sense is an essential prerequisite for enabling communication services in the future heterogeneous Internet. A multitude of cross-layer approaches ranging from clean slate designs to actual implementations of cross-layer links in the standard TCP/IP stack have been suggested during the last decade. Yet, there is no agreement on a systematic integration of cross-layering into the actual Internet architecture. In this article we present a Guided Cross-layering Framework and a roadmap for its deployment in the Internet. We elaborate its key issue of identifying functional invariants in the present communication model. The invariants are the clean protocol stubs of the current TCP/IP stack. We describe the concept of meta-protocols and a design-deployment methodology for the framework. Our main postulate that promises an acceptance of the proposed architecture is the evolutionary, market-driven transformation of the current Internet architecture. On the example of the new ICSP (Integrated Communication and Signaling Protocol) protocol, we demonstrate the integration of CARD (Candidate Access Router Discovery), MIP (Mobile IP), and SIP (Session Initiation Protocol) in our framework which jointly optimize the performance and economic utilities of a multi-cell wireless network operator and the end user.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 18. Elkotob, Muslim
    et al.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    iRide: a cooperative sensor and IP multimedia subsystem based architecture and application for ITS road safety2009Ingår i: Communications Infrastructure, Systems and Applications: First International ICST Conference, EuropeComm 2009, London, UK, August 11-13, 2009, Revised Selected Papers / [ed] R. Mehmood, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2009Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper we present iRide (intelligent ride), an IP Multimedia Subsystem (IMS) application for warning drivers about hazardous situations on the road. iRide takes real-time information about road conditions and traffic situations from a wireless sensor network installed directly in the road surface. Upon logging to the iRide system, users start to receive periodic updates about the situation on the road along their route ahead. iRide is able to predict hazardous situations like slippery surface or dangerous distance to the nearest car and help drivers avoid accidents. We describe the service and the supporting network architecture of iRide. We discuss the major challenges associated with designing an IMS application for ITS, an intelligent transport system. Having a prototype implementation working on a small scale, we take it to the next step to perform system dimensioning and then verify the feasibility of having such a system using OPNET simulations.

  • 19. Granlund, Daniel
    et al.
    Gylling, Arne
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, CDT.
    Åhlund, Christer
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Brännström, Robert
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Jacquier, Anna
    Elkotob, Muslim
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, CDT.
    Åhl, Anneli
    Project: BASICNET2008Övrigt (Övrig (populärvetenskap, debatt, mm))
    Abstract [en]

    Broadband Access Services In Converging NETworks

  • 20.
    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. 

  • 21.
    Jardak, Christine
    et al.
    RWTH Aachen University.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Mähönen, Petri
    RWTH Aachen University.
    Distributed information storage and collection for WSNs2007Ingår i: Proceedings, 4th IEEE International Conference on Mobile Ad-hoc and Sensor Systems, Piscataway, NJ: IEEE Communications Society, 2007Konferensbidrag (Refereegranskat)
    Abstract [en]

    Distributed data storage is an important component of wireless sensor networks, which protects the mission critical information from unexpected node failures or malicious destruction of parts of the network. In this paper we present DISC, a protocol for distributed information storage and collection. The two major mechanisms in DISC which make our solution distinct from the related approaches are probabilistic choice of storing nodes and a search engine based on the usage of Bloom filters. In comparison to the deterministic choice of the backup node, the random selection strategy makes it virtually impossible for an attacker to determine and destroy the exact node keeping a particular piece of information. The usage of Bloom filters in the information search engine makes the navigation to a specific data fast and efficient. We show that with DISC the amount of recovered information is more than two times higher than that in deterministic storage schemes.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 22. Johansson, Tomas
    et al.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Carr-Motyckova, Lenka
    Interference aware construction of multi- and convergecast trees in wireless sensor networks2008Ingår i: Next Generation Teletraffic and Wired/Wireless Advanced Networking: 8th International Conference, NEW2AN 2008 and ruSMART, St. Petersburg, Russia, September 3-5, 2008 ; proceedings / [ed] Sergey Balandin; Dimitri Moltchanov; Yevgeni Koucheryavy, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2008, s. 72-87Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper we consider a problem of building a forwarding tree for multicast and convergecast traffic in short-range wireless sensor networks. Interference awareness and energy efficiency are the major design objectives for WSN protocols in order to maximize the network lifetime. The existing multicast algorithms aim at constructinglow-energy cost trees. Adding interference-awareness, however, leads to increased throughput and further reduces the energy consumption by avoiding unnecessary retransmissions due to interference-induced packetlosses. We propose a Localized Area-Spanning Tree (LAST) protocol for wireless short-range sensor networks. Unlike previous similar protocols, the LAST protocol reaches all the nodes in a given geographical area,rather than only specific individual nodes. When creating the tree, the protocol jointly optimizes the energy cost and the interference imposed by the structure.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 23.
    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.

  • 24.
    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%.

  • 25.
    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.

  • 26.
    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.

  • 27.
    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.

  • 28.
    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.

  • 29.
    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.

  • 30.
    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.

  • 31.
    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.

  • 32.
    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.

  • 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.
    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.

  • 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.
    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.

  • 35.
    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.

  • 36.
    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.

  • 37.
    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.

  • 38.
    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.

  • 39.
    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.

  • 40.
    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 Comprehensive Study of Complexity and Performance of Automatic Detection of Atrial Fibrillation: Classification of Long ECG Recordings Based on the PhysioNet Computing in Cardiology Challenge 20172020Ingår i: Biomedical Physics & Engineering Express, E-ISSN 2057-1976, Vol. 6, nr 2, artikel-id 025010Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Objective: The 2017 PhysioNet/CinC Challenge focused on automatic classification of atrial fibrillation (AF) in short ECGs. This study aimed to evaluate the use of the data and results from the challenge for detection of AF in longer ECGs, taken from three other PhysioNet datasets. Approach: The used data-driven models were based on features extracted from ECG recordings, calculated according to three solutions from the challenge. A Random Forest classifier was trained with the data from the challenge. The performance was evaluated on all non-overlapping 30 s segments in all recordings from three MIT-BIH datasets. Fifty-six models were trained using different feature sets, both before and after applying three feature reduction techniques. Main Results: Based on rhythm annotations, the AF proportion was 0.00 in the MIT-BIH Normal Sinus Rhythm (N = 46083 segments), 0.10 in the MIT-BIH Arrhythmia (N = 2880), and 0.41 in the MIT-BIH Atrial Fibrillation (N = 28104) dataset. For the best performing model, the corresponding detected proportions of AF were 0.00, 0.11 and 0.36 using all features, and 0.01, 0.10 and 0.38 when using the 15 best performing features. Significance: The results obtained on the MIT-BIH datasets indicate that the training data and solutions from the 2017 Physionet/Cinc Challenge can be useful tools for developing robust AF detectors also in longer ECG recordings, even when using a low number of carefully selected features. The use of feature selection allows significantly reducing the number of features while preserving the classification performance, which can be important when building low-complexity AF classifiers on ECG devices with constrained computational and energy resources.

  • 41.
    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.

  • 42.
    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 positives2020Ingår i: Neural computing & applications (Print), ISSN 0941-0643, E-ISSN 1433-3058, Vol. 32, nr 8, s. 3675-3684Artikel 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.

    Ladda ner fulltext (pdf)
    fulltext
  • 43.
    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.

  • 44.
    Nunes, Renato
    et al.
    INOV.
    Pereira, Paulo
    INOV.
    Peter, Steffen
    IHP.
    Piotrowski, Krzysztof
    IHP.
    Winkler, Rita
    IHP.
    Riliskis, Laurynas
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Tools and methods for systematic WSAN engineering2009Rapport (Övrigt vetenskapligt)
    Abstract [en]

    The goal of this deliverable is to research an application-centric communication system engineering framework that supports system engineers in analysing and defining requirements as well as providing tool support during the selection of particular network mechanisms to be used within the WSAN under development. For this purpose we present a general design flow to help engineering WSAN applications. The semantic centreis a knowledge base it allows to describe requirements, environment, components and the whole system. The presented model-driven scheme as part of the component description is able to predict the properties of theoverall system based on static properties of components in context of the given environment. For more complex dynamic properties a novel simulation approach is presented that combines network simulations with actual properties of the operating system and the software stack. Operations of the development flow are supported by various tools. First examples indicate the effectiveness of the proposed design flow and promiseto improve engineering of WSAN system in future.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 45.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Aktivitet: International Conference on Wired/Wireless Internet Communications2010Övrigt (Övrig (populärvetenskap, debatt, mm))
  • 46. Osipov, Evgeny
    Extending the ad hoc horizon for TCP over IEEE 802.11 networks2005Ingår i: Proceedings. 5th Scandinavian Workshop on Wireless Ad-hoc Networks: ADHOC'05, Stockholm: Wireless at KTH, Royal institute of technology , 2005Konferensbidrag (Refereegranskat)
  • 47. Osipov, Evgeny
    On the practical feasibility of fair TCP communications in IEEE 802.11 based multihop ad hoc wireless networks2005Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    In the center of this dissertation is the question whether it is practically feasible to achieve deterministically good quality for traditional network services such as le transfer and Web browsing in multihop wireless mobile ad hoc networks (MANETs). Despite the straight forward benets of MANETs such as quick installation due to the absence of wireline infrastructure, and the virtue of dynamic re-conguration, these networks mainly exist in research labs so far. One of the stumbling blocks which prevents MANETs from wide deployment and popularization, is the poor and unstable performance of the TCP protocol which underlies le transfer and Web trafc. In particular, the problem considered in this thesis is the severe unfairness between multiple TCP sessions in a wireless context. Overall, the thesis explores the operational range of MANETs in which the quality of network services is acceptable for an end user. The rst part of our work reveals that this range is extremely narrow for the plain combination of TCP and wireless communication according to IEEE 802.11. The second part of this work studies the interactions of TCP and IEEE 802.11 assuming static routing in the network. It gives a systematic view on fairness in MANETs. The max-min fairness model from the wireline Internet is adapted to the specics of the wireless environment. The resulting solution presented in this thesis is an adaptive distributed capacity allocation scheme for multihop wireless networks. It leads to a dramatic improvement of TCP performance and a signicant extension of the operation range. The third part analyzes the effect of ad hoc routing on the quality of TCP sessions. The routing trafc itself is one of the reasons for unfair TCP communications. Finally, the thesis addresses implementation issues of the suggested fairness model. It describes a distributed protocol for the dynamic control of the network load, which is implemented both for a network simulator and a real-world operating system.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 48. Osipov, Evgeny
    The design and application of a simplified guaranteed service for the Internet2003Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
  • 49.
    Osipov, Evgeny
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    tinyLUNAR: one-byte multihop communications through hybrid routing in wireless sensor networks2007Ingår i: Next Generation Teletraffic and Wired/Wireless Advanced Networking: 7th international conference, NEW2AN 2007, St. Petersburg, Russia, September 10-14, 2007 ; proceedings / [ed] Yevgeni Koucheryavy; Jarmo Harju; A. Sayenko, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2007, s. 379-392Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper we consider a problem of implementing a hybrid routing protocol for wireless sensor networks, which natively supports data-centric, geographic-based and address-centric communication paradigms. We demonstrate the feasibility of such protocol by presenting tinyLUNAR, an adapted to the specifics of sensor networks reactive routing scheme originally developed for mobile wireless ad hoc networks. In addition to the support for several communications paradigms tinyLUNAR implements highly efficient multihop forwarding using only 1 B field that can be directly encoded in the standard IEEE 802.15.4 MAC header.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 50. Osipov, Evgeny
    Проблемы реализации надёжной передачи данных в самоорганизующихся и сенсорных сетях2006Ingår i: Elektrosvyaz', ISSN 0013-5771, nr 6Artikel i tidskrift (Övrig (populärvetenskap, debatt, mm))
12 1 - 50 av 88
RefereraExporteraLänk till träfflistan
Permanent länk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf