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arXiv 2021年

作者： Wang, Yingxu Karray, Fakhri Kwong, Sam Plataniotis, Konstantinos N. Leung, Henry Hou, Ming Tunstel, Edward Rudas, Imre J. Trajkovic, Ljiljana Kaynak, Okyay Kacprzyk, Janusz Zhou, Mengchu Smith, Michael H. Chen, Philip Patel, Shushma University of Calgary Canada FIEEE Dept. of Electrical & Computer Engineering University of Waterloo ON Canada FIEEE Department of Computer Science City University of Hong Kong Hong Kong FIEEE Dept. of Electrical & Computer Engineering University of Toronto ON Canada SMIEEE Toronto Research Centre DRDC Canada FIEEE Autonomous & Intelligent Systems Dept. Raytheon Technologies Research Center United States Óbuda University Budapest Hungary FIEEE School of Engineering Science Simon Fraser University BurnabyBC Canada FIEEE Bogazici University Bebek Istanbul Turkey FIEEE Systems Research Institute Polish Academy of Sciences Warsaw Poland FIEEE Dept. of Computer Science New Jersey Institute of Technology NJ United States SMIEEE Furaxa Inc. OrindaCA United States FIEEE School of Computer Science and Engineering South China University of Technology Guangzhou China FBCS Faculty of Computing Engineering and Media De Montfort University LeicesterLE1 9BH United Kingdom

Symbiotic Autonomous systems (SAS) are advanced intelligent and cognitive systems exhibiting autonomous collective intelligence enabled by coherent symbiosis of human-machine interactions in hybrid societies. Basic research in the emerging field of SAS has triggered advanced general AI technologies functioning without human intervention or hybrid symbiotic systems synergizing humans and intelligent machines into coherent cognitive systems. This work presents a theoretical framework of SAS underpinned by the latest advances in intelligence, cognition, computer, and system sciences. SAS are characterized by the composition of autonomous and symbiotic systems that adopt bio-brain-social-inspired and heterogeneously synergized structures and autonomous behaviors. This paper explores their cognitive and mathematical foundations. The challenge to seamless human-machine interactions in a hybrid environment is addressed. SAS-based collective intelligence is explored in order to augment human capability by autonomous machine intelligence towards the next generation of general AI, autonomous computers, and trustworthy mission-critical intelligent systems. Emerging paradigms and engineering applications of SAS are elaborated via an autonomous knowledge learning system that symbiotically works between humans and cognitive robots. © 2021, CC BY-NC-ND.

关键词： Cognitive systems

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State of the Art of Audio- and Video-Based Solutions for AAL

arXiv

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arXiv 2022年

作者： Aleksic, Slavisa Atanasov, Michael Agius, Jean Calleja Camilleri, Kenneth Čartolovni, Anto Climent-Pérez, Pau Colantonio, Sara Cristina, Stefania Despotovic, Vladimir Ekenel, Hazım Kemal Erakin, Ekrem Florez-Revuelta, Francisco Germanese, Danila Grech, Nicole Sigurðardóttir, Steinunn Gróa Emirzeoğlu, Murat Iliev, Ivo Jovanovic, Mladjan Kampel, Martin Kearns, William Klimczuk, Andrzej Lambrinos, Lambros Lumetzberger, Jennifer Mucha, Wiktor Noiret, Sophie Pajalic, Zada Pérez, Rodrigo Rodriguez Petrova, Galidiya Petrovica, Sintija Pocta, Peter Poli, Angelica Pudane, Mara Spinsante, Susanna Salah, Albert Ali Santofimia, Maria Jose Islind, Anna Sigríður Stoicu-Tivadar, Lacramioara Tellioğlu, Hilda Zgank, Andrej Leipzig University of Applied Sciences Germany TU Wien Austria Department of Anatomy University of Malta Malta Centre for Biomedical Cybernetics Faculty of Engineering Department of Systems and Control Engineering Malta Catholic University of Croatia Croatia Universidad de Alicante Spain Institute of Information Science and Technologies The National Research Council of Italy Italy Department of Systems and Control Engineering University of Malta Malta University of Luxembourg Luxembourg Dept. of Computer Engineering Istanbul Technical University Turkey Reykjavik University School of Computer Science Iceland Sağlık Bilimleri Fakültesi Fizyoterapi ve Rehabilitasyon Karadeniz Technical University Research Information System Turkey TU Sofia Bulgaria Singidunum University Belgrade Serbia University of South Florida United States SGH Warsaw School of Economics Poland Department of Communication and Internet Studies Cyprus University of Technologies Cyprus Technical University of Vienna Austria VID Specialized University Oslo Norway Getafe University Hospital Spain Riga Technical University Latvia University of Zilina Slovakia Università Politecnica Marche Italy Utrecht University Netherlands Universidad de Castilla-La Mancha Spain Reykjavik University Iceland University Politehnica Timisoara Romania University of Maribor Slovenia

It is a matter of fact that Europe is facing more and more crucial challenges regarding health and social care due to the demographic change and the current economic context. The recent COVID-19 pandemic has stressed this situation even further, thus highlighting the need for taking action. Active and Assisted Living (AAL) technologies come as a viable approach to help facing these challenges, thanks to the high potential they have in enabling remote care and support. Broadly speaking, AAL can be referred to as the use of innovative and advanced Information and Communication Technologies to create supportive, inclusive and empowering applications and environments that enable older, impaired or frail people to live independently and stay active longer in society. AAL capitalizes on the growing pervasiveness and effectiveness of sensing and computing facilities to supply the persons in need with smart assistance, by responding to their necessities of autonomy, independence, comfort, security and safety. The application scenarios addressed by AAL are complex, due to the inherent heterogeneity of the end-user population, their living arrangements, and their physical conditions or impairment. Despite aiming at diverse goals, AAL systems should share some common characteristics. They are designed to provide support in daily life in an invisible, unobtrusive and user-friendly manner. Moreover, they are conceived to be intelligent, to be able to learn and adapt to the requirements and requests of the assisted people, and to synchronise with their specific needs. Nevertheless, to ensure the uptake of AAL in society, potential users must be willing to use AAL applications and to integrate them in their daily environments and lives. In this respect, video- and audio-based AAL applications have several advantages, in terms of unobtrusiveness and information richness. Indeed, cameras and microphones are far less obtrusive with respect to the hindrance other wearable sensors may

关键词： computer vision

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Model transformations via XSLT 17

Model transformations via XSLT

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17th Annual International Workshop on Databases, Texts, Specifications, and Objects, DATESO 2017

作者： Pavlát, Jakub Richta, Karel Richta, Tomáš Janoušek, Vladimír Czech Technical University in Prague Faculty of Electrical Engineering Dept. of Computer Science Karlovo nám. 13 Praha 2121 35 Czech Republic Brno Institute of Technology Faculty of Information Technology Dept. of Intelligent Systems Božetěchova 2 Brno612 66 Czech Republic

ISBN: (纸本)9788001061381

Many present systems are conceived as a set of autonomous agents that communicate together in solving problems. Petri nets are commonly used for a specification of parallel systems. An interesting question is whether we can implement arbitrary system by a set of Petri nets agents. These agents could be specified by Petri nets, but such a description is not sufficiently user-friendly. Our idea is to define these agents by classical workflow models and then transform them into a set of Petri nets. Such transformation would support development of software systems, whose specification is based on classical workflow models, but the implementation is based on Petri nets. Each net of the resulting system is translated into a specific target representation called Petri Nets Byte Code (PNBC). These codes are interpreted by the special Petri Nets Virtual Machines (PNVM), which are installed on all nodes of the system, under the Petri Nets Operating system (PNOS). This paper deals with the one step of this process, which is an implementation of required transformations from workflow model into Petri nets with the help of XSLT. © K. Richta, P. Moravec (Eds.): Dateso 2017.

关键词： Petri nets

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News selection method considering the user’s interests for an intelligent conversation system

News selection method considering the user’s interests for ...

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2016 International Conference on Artificial Intelligence, ICAI 2016 - WORLDCOMP 2016

作者： Yoshimura, Eriko Imono, Misako Tsuchiya, Seiji Watabe, Hirokazu Dept. of Intelligent Information Engineering and Sciences Faculty of Science and Engineering Doshisha University Kyo-Tanabe Kyoto Japan Dept. of Information Systems Computer Science Course School of Informatics Daido University Minami-ku Nagoya Japan

ISBN: (纸本)1601324383

This paper proposed the news selection method for computer conversation. The method is user’s matched news selection based user’s personal information and the method is high topicality news selection considering generally importance. In this proposed method, we used association mechanism is not based only the notation information of the word. The proposed system conceptualized several information and news by using this mechanism and it was able to calculate association quantitatively between information and news. CSREA Press ©.

关键词： Artificial intelligence

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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Benchmarking intelligent service robots through scientific competitions: The RoboCup@Home approach

Benchmarking intelligent service robots through scientific c...

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2013 AAAI Spring Symposium

作者： Holz, Dirk Iocchi, Luca Van Der Zant, Tijn Autonomous Intelligent Systems Group Department of Computer Science VI University of Bonn Germany Dept. of Computer Control and Management Engineering Sapienza University of Rome Italy Dept. of Artificial Intelligence Faculty of Natural Sciences University of Groningen Netherlands

ISBN: (纸本)9781577356011

The dynamical and uncertain environments of domestic service robots, which includehumans, require rethinking of the benchmarking principles for testing these robots. Since 2006 RoboCup@Home has used statistical procedures to track and steer the progress ofdomestic service robots. This paper explains the procedures and shows outcomes of these international benchmarking efforts. Although aspects such as shopping in a supermarket receive a fair amount of attention in the robotics community, the authors believe that a recently implemented test is the most important outcome of RoboCup@Home, namely the benchmarking of robot cognition. © 2013, Association for the Advancement of artificial intelligence.

关键词： Benchmarking

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Structured coprime factorizations description of linear and time-invariant networks

Structured coprime factorizations description of linear and ...

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52nd IEEE Conference on Decision and control, CDC 2013

作者： SabǍu, Şerban OarǍ, Cristian Warnick, Sean Jadbabaie, Ali Electrical and Computer Engineering Dept. Stevens Institute of Technology United States Faculty of Automatic Control Dept. University Politehnica Bucharest Romania Faculty of Computer Science Department Information and Decision Algorithms Laboratories Brigham Young University United States Faculty of Electrical and Systems Engineering Dept. University of Pennsylvannia United States

ISBN: (纸本)9781467357173

In this paper we study state-space realizations of Linear and Time-Invariant (LTI) systems. Motivated by biochemical reaction networks, Gonçalves and Warnick have recently introduced the notion of a Dynamical Structure Functions (DSF), a particular factorization of the system's transfer function matrix that elucidates the interconnection structure in dependencies between manifest variables. We build onto this work by showing an intrinsic connection between a DSF and certain sparse left coprime factorizations. By establishing this link, we provide an interesting systems theoretic interpretation of sparsity patterns of coprime factors. In particular we show how the sparsity of these coprime factors allows for a given LTI system to be implemented as a network of LTI sub-systems. We examine possible applications in distributed control such as the design of a LTI controller that can be implemented over a network with a pre-specified topology. ©2013 IEEE.

关键词： Factorization

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Hierarchical fuzzy approaches for a piloted Quality Management system

Hierarchical fuzzy approaches for a piloted Quality Manageme...

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International Conference on control, Decision and Information Technologies (CoDIT)

作者： H. Ben Mahmoud R. Ketata T. Ben Romdhane S. Ben Ahmed Dept. of Physics and Instrumentation Engineering INSAT: National Institute of Applied Science and Technology Dept. of Physics and Instrumentation Engineering ICOS: Research Unit on Intelligent Control Tunis Tunisia Dept. of Physics and Instrumentation Engineering MOSIC Research Unit on Methods and Tools for Complex Computer Systems Tunis Tunisia

In this paper, two approaches, Hierarchical Fuzzy Signature (HFS) and Neuro-Fuzzy Hierarchical Hybrid (NFHH), have been proposed for piloting a Quality Management system (QMS). These approaches have been applied for real company which presents a major problem for controlling the quality level of production. HFS structure has reduced complexity in the number of input and output meta-levels of hierarchy. Also NFHH model has presented better performance in terms of precision and number of parameters without losing the universal approximation property of neural networks (NN) and fuzzy systems.

关键词： Companies IP networks Production Complexity theory Fuzzy logic Artificial neural networks Pragmatics

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Structured coprime factorizations description of Linear and Time-Invariant networks

Structured coprime factorizations description of Linear and ...

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IEEE Conference on Decision and control

作者： Şerban Săbau Cristian Oară Sean Warnick Ali Jadbabaie Stevens Institute of Technology Hoboken NJ US Faculty of the Automatic Control Dept. University “Politehnica” Bucharest Romania The Faculty of the Computer Science Department Brigham Young University Faculty of the Electrical and Systems Engineering Dept University of Pennsylvannia

关键词： Transfer functions Equations Indium phosphide Mathematical model Network topology Topology Electronic mail

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A sophisticated ad hoc cloud computing environment built by the migration of a server to facilitate distributed collaboration

A sophisticated ad hoc cloud computing environment built by ...

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26th IEEE International Conference on Advanced Information Networking and Applications Workshops, WAINA 2012

作者： Mori, Tatsuya Nakashima, Makoto Ito, Tetsuro Dept. Computer Science and Intelligent Systems Faculty of Engineering Oita University Oita-shi Japan

ISBN: (纸本)9780769546520

A sophisticated ad hoc cloud computing environment (SpACCE) providing calculation capacity of PCs is proposed to facilitate distributed collaboration. Distributed collaboration is now indispensable in daily work and mainly occurs ad hoc in offices and laboratories. However, computer resources in offices and laboratories are under-utilized, while conventional cloud computing environments composed of dedicated servers are not suited to flexibly deploying applications ad hoc. A SpACCE can be built according to the needs that occur at any given time on a set of personal, i.e., non-dedicated, PCs and dynamically migrate a server for application sharing to another PC. CollaboTray, an application-sharing system, indispensable to share any application without modification, is employed to realize the migration of a server. By migrating a server, the redundant calculation capacity of PCs used for individual work can be utilized to produce a sophisticated ad hoc cloud computing environment, where the response time of the application shared among the users is improved. The level of calculation capacity required to execute the migration of a server and the effectiveness of the migration were clarified by building a SpACCE in a university research room. © 2012 IEEE.

关键词： Cloud computing

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