| 1. |
- Camarinha-Matos, Luis M, et al.
(författare)
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Emerging Trends in Technological Innovation : First IFIP WG 5.5/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2010, Costa de Caparica, Portugal, February 22-24, 2010. Proceedings
- 2010
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Bok (refereegranskat)abstract
- Doctoral programs in science and engineering are important sources of innovative ideas and techniques that might lead to new products and technological innovation. Certainly most PhD students are not experienced researchers and are in the process of learning how to do research. Nevertheless, a number of empiric studies also show that a high number of technological innovation ideas are produced in the early careers of researchers. The combination of the eagerness to try new approaches and directions of young doctoral students with the experience and broad knowledge of their supervisors is likely to result in an important pool of innovation potential.The DoCEIS doctoral conference on Computing, Electrical and Industrial Engineering aims at creating a space for sharing and discussing ideas and results from doctoral research in these inter-related areas of engineering. Innovative ideas and hypotheses can be better enhanced when presented and discussed in an encouraging and open environment. DoCEIS aims to provide such an environment, releasing PhD students from the pressure of presenting their propositions in more formal contexts.The first edition of DoCEIS, which was sponsored by SOCOLNET, IFIP and IEEE Industrial Electronics Society, attracted a considerable number of paper submissions from a large number of PhD students (and their supervisors) from 15 countries. This book comprises the works selected by the International Program Committee for inclusion in the main program and covers a wide spectrum of topics, ranging from collaborative enterprise networks to microelectronics. Thus, novel results and ongoing research in the following areas were presented, illustrated, and discussed:Value systems alignment in enterprise networksCollaborative networks governance and supportInformation modelling and management- Risk assessment and decision support based on imprecise informationEvolvable manufacturing systems and cooperative roboticsSystems modelling and controlAdvances in telecommunications and electronicsSensorial perception and signal processingEnergy systems and novel electrical machineryAs a gluing element, all authors were asked to explicitly indicate the (potential) contribution of their work to technological innovation.We expect that this book will provide readers with an inspiring set of promising ideas, presented in a multi-disciplinary context, and that by their diversity these results can trigger and motivate new research and development directions.We would like to thank all the authors for their contributions. We also appreciate the dedication of the DoCEIS Program Committee members who both helped with the selection of articles and contributed with valuable comments to improve their quality.February 2009LuÌs M. Camarinha-MatosPedro PereiraLuis Ribeiro
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| 2. |
- Stankovic, Milos S., et al.
(författare)
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On Consensus-Based Distributed Blind Calibration of Sensor Networks
- 2018
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Ingår i: Sensors. - : MDPI. - 1424-8220. ; 18:11
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Forskningsöversikt (refereegranskat)abstract
- This paper deals with recently proposed algorithms for real-time distributed blind macro-calibration of sensor networks based on consensus (synchronization). The algorithms are completely decentralized and do not require a fusion center. The goal is to consolidate all of the existing results on the subject, present them in a unified way, and provide additional important analysis of theoretical and practical issues that one can encounter when designing and applying the methodology. We first present the basic algorithm which estimates local calibration parameters by enforcing asymptotic consensus, in the mean-square sense and with probability one (w.p.1), on calibrated sensor gains and calibrated sensor offsets. For the more realistic case in which additive measurement noise, communication dropouts and additive communication noise are present, two algorithm modifications are discussed: one that uses a simple compensation term, and a more robust one based on an instrumental variable. The modified algorithms also achieve asymptotic agreement for calibrated sensor gains and offsets, in the mean-square sense and w.p.1. The convergence rate can be determined in terms of an upper bound on the mean-square error. The case when the communications between nodes is completely asynchronous, which is of substantial importance for real-world applications, is also presented. Suggestions for design of a priori adjustable weights are given. We also present the results for the case in which the underlying sensor network has a subset of (precalibrated) reference sensors with fixed calibration parameters. Wide applicability and efficacy of these algorithms are illustrated on several simulation examples. Finally, important open questions and future research directions are discussed.
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