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IEEE Transactions on Green Communications and Networking 2024年

作者： Xie, Kengyuan Cai, Guofa Ning, Ting He, Jiguang Kaddoum, Georges Guangdong University of Technology School of Information Engineering Guangzhou510006 China Chongqing University of Posts and Telecommunications Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing400065 China Great Bay University School of Computing and Information Technology China University of Oulu Centre for Wireless Communications Oulu90014 Finland University of Quebec Electrical Engineering Department École de Technologie Supérieure MontrealQCH2L 2C4 Canada Lebanese American University Artificial Intelligence and Cyber Systems Research Center Lebanon

This paper proposes an energy buffer aided cooperative wireless-powered non-orthogonal multiple access (NOMA) system, which includes a base station (BS), a near user (NU), and a far user (FU). To consider a more general case and improve the system performance as much as possible, both the NU and FU are equipped with energy buffers. Two different energy management policies are considered at the NU and FU, namely the best-effort policy (BEP) and on-off policy (OOP). In the proposed system, the NU and FU first collect and store radio frequency based energy from the BS. Then, the FU uses the stored energy to transmit its signal to both the BS and NU. The NU decodes the received signal from the FU and uses the stored energy to transmit the superimposed signal that consists of its own signal and the decoded FU signal to the BS. The outage probability and throughput expressions of the proposed system with BEP and OOP are derived over Rayleigh fading channels. Results reveal that the proposed system can significantly improve the performance of FU compared to the energy buffer aided non-cooperative wireless-powered NOMA system, and can outperform the buffer-less cooperative wireless-powered NOMA system. © 2017 IEEE.

关键词： Fading channels

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Distributed Coverage Hole Prevention for Visual Environmental Monitoring with Quadcopters via Nonsmooth control Barrier Functions

arXiv

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arXiv 2022年

作者： Funada, Riku Santos, María Maniwa, Ryuichi Yamauchi, Junya Fujita, Masayuki Sampei, Mitsuji Egerstedt, Magnus The Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo152-8550 Japan The Department of Mechanical and Aerospace Engineering Princeton University PrincetonNJ08544 United States The Department of Information Physics and Computing The University of Tokyo Tokyo113-8656 Japan The Department of Electrical Engineering and Computer Science University of California Irvine IrvineCA92697 United States

This paper proposes a distributed coverage control strategy for quadcopters equipped with downward-facing cameras that prevents the appearance of unmonitored areas in between the quadcopters' fields of view (FOVs). We derive a necessary and sufficient condition for eliminating any unsurveilled area that may arise in between the FOVs among a trio of quadcopters by utilizing a power diagram, i.e. a weighted Voronoi diagram defined by radii of FOVs. Because this condition can be described as logically combined constraints, we leverage nonsmooth control barrier functions (NCBFs) to prevent the appearance of unmonitored areas among a team's FOV. We then investigate the symmetric properties of the proposed NCBFs to develop a distributed algorithm. The proposed algorithm can support the switching of the NCBFs caused by changes of the quadcopters composing trios. The existence of the control input satisfying NCBF conditions is analyzed by employing the characteristics of the power diagram. The proposed framework is synthesized with a coverage control law that maximizes the monitoring quality while reducing overlaps of FOVs. The proposed method is demonstrated in simulation and experiment. Copyright © 2022, The Authors. All rights reserved.

关键词： Sensor networks

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Single-shot blind deconvolution with coded aperture

arXiv

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arXiv 2022年

作者： Muneta, Hideyuki Horisaki, Ryoichi Nishizaki, Yohei Naruse, Makoto Tanida, Jun Department of Information and Physical Sciences Graduate School of Information Science and Technology Osaka University 1-5 Yamadaoka Osaka Suita565-0871 Japan Department of Information Physics and Computing Graduate School of Information Science and Technology The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Systems and Control Laboratory Environmental Technology Research Division Osaka Research Institute of Industrial Science and Technology 1-6-50 Morinomiya Joto-ku Osaka536-8553 Japan

In this paper, we present a method for single-shot blind deconvolution incorporating a coded aperture (CA). In this method, we utilize the CA, inserted on the pupil plane, as support constraints in blind deconvolution. Not only an object but also a point spread function of turbulence are estimated from a single captured image by a reconstruction algorithm with the CA support. The proposed method is demonstrated by a simulation and an experiment in which point sources are recovered under severe turbulence. © 2022, CC BY.

关键词： Convolution

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Logical-combinatorial approaches in dynamic recognition problems

arXiv

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arXiv 2021年

作者： Aslanyan, Levon H. Krasnoproshin, Viktor V. Ryazanov, Vladimir V. Sahakyan, Hasmik A. Institute for Informatics and Automation Problems NAS RA Armenia Belarusian State University Department of Information Management Systems Belarus Dorodnitsyn Computing Centre Federal Research Center Computer Science and Control RAS Russia

A pattern recognition scenario, where instead of object classification into the classes by the learning set, the algorithm aims to allocate all objects to the same, the so-called "normal" class, is the research objective. Given the learning set L;the class K! is called "normal", and the reminder l classes K", K#,..., K$ from the environment K are "deviated". The classification algorithm is for a recurrent use in a "classification, action" format. Actions A% are defined for each "deviated" class K%. Applied to an object X ∈ K%, the action delivers update A%(x) of the object. The goal is in constructing a classification algorithm that applied repeatedly (small number of times) to the objects of L, moves the objects (correspondingly, the elements of K) to the "normal" class. In this way, the static recognition action is transferred to a dynamic domain. This paper is continuing the discussion on the "normal" class classification problem, its theoretical postulations, possible use cases, and advantages of using logical-combinatorial approaches in solving these dynamic recognition problems. Some light relation to the topics like reinforcement learning, and recurrent neural networks are also provided. Copyright © 2021, The Authors. All rights reserved.

关键词： Recurrent neural networks

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A Learning Convolutional Neural Network Approach for Network Robustness Prediction

arXiv

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arXiv 2022年

作者： Lou, Yang Wu, Ruizi Li, Junli Wang, Lin Li, Xiang Chen, Guanrong The Department of Computing and Decision Sciences Lingnan University Hong Kong The Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China The College of Computer Science Sichuan Normal University Chengdu610066 China The Department of Automation Shanghai Jiao Tong University Shanghai200240 China The Institute of Complex Networks and Intelligent Systems Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai201210 China The Department of Control Science and Engineering Tongji University Shanghai200240 China The Department of Electrical Engineering City University of Hong Kong Hong Kong

Network robustness is critical for various societal and industrial networks again malicious attacks. In particular, connectivity robustness and controllability robustness reflect how well a networked system can maintain its connectedness and controllability against destructive attacks, which can be quantified by a sequence of values that record the remaining connectivity and controllability of the network after a sequence of node- or edge-removal attacks. Traditionally, robustness is determined by attack simulations, which are computationally very time-consuming or even practically infeasible. In this paper, an improved method for network robustness prediction is developed based on learning feature representation using convolutional neural network (LFR-CNN). In this scheme, higher-dimensional network data are compressed to lower-dimensional representations, and then passed to a CNN to perform robustness prediction. Extensive experimental studies on both synthetic and real-world networks, both directed and undirected, demonstrate that 1) the proposed LFR-CNN performs better than other two state-of-the-art prediction methods, with significantly lower prediction errors;2) LFR-CNN is insensitive to the variation of the network size, which significantly extends its applicability;3) although LFR-CNN needs more time to perform feature learning, it can achieve accurate prediction faster than attack simulations;4) LFR-CNN not only can accurately predict network robustness, but also provides a good indicator for connectivity robustness, better than the classical spectral measures. © 2022, CC BY.

关键词： Complex networks

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A Survey of Robot Manipulation in Contact

arXiv

引用

arXiv 2021年

作者： Suomalainen, Markku Karayiannidis, Yiannis Kyrki, Ville Center of Ubiquitous Computing Faculty of Information Technology and Electrical Engineering University of Oulu Finland Systems and Control Department of Electrical Engineering Chalmers University of Technology Gothenburg Sweden Intelligent Robotics research group Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Helsinki Finland

In this survey, we present the current status on robots performing manipulation tasks that require varying contact with the environment, such that the robot must either implicitly or explicitly control the contact force with the environment to complete the task. Robots can perform more and more manipulation tasks that are still done by humans, and there is a growing number of publications on the topics of 1) performing tasks that always require contact and 2) mitigating uncertainty by leveraging the environment in tasks that, under perfect information, could be performed without contact. The recent trends have seen robots perform tasks earlier left for humans, such as massage, and in the classical tasks, such as peg-in-hole, there is a more efficient generalization to other similar tasks, better error tolerance, and faster planning or learning of the tasks. Thus, in this survey we cover the current stage of robots performing such tasks, starting from surveying all the different in-contact tasks robots can perform, observing how these tasks are controlled and represented, and finally presenting the learning and planning of the skills required to complete these tasks. © 2021, CC BY.

关键词： Surveys

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Method of Robotic Process Automation in Software Testing Using Artificial Intelligence

Method of Robotic Process Automation in Software Testing Usi...

引用

International Conference on Advanced Computer information Technologies (ACIT)

作者： Nataliya Yatskiv Solomiya Yatskiv Anatoliy Vasylyk Department for Information and Computing Systems and Control Ternopil National Economic University Ternopil Ukraine Department of Computer Science Ternopil National Economic University Ternopil Ukraine

ISBN: (数字)9781728167602

ISBN: (纸本)9781728167619

Robotic process automation (RPA) offers numerous benefits over typical software for test automation. It allows saving money and freeing up human resources without any modifications in the processes and implemented solutions. Despite many advantages, RPA solution has limited functionality and it is not able to automatically adapt to changes in the system without human interaction. One of the technologies that may be used to leverage these disadvantages is Artificial Intelligence (AI). AI can facilitate process automation by using the intelligent decision making and interface analysis. In this paper the main approaches of RPA usage, their advantages and disadvantages are investigated. This paper describes the proposed method for software test automation with RPA which allows to make RPA software more flexible and decrease human involvement in the support processes.

关键词： Automation Artificial intelligence Software Tools Business Computer vision

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Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Learning

Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Lea...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Weipeng Cao Xuyang Yao Zhiwu Xu Yinghui Pan Yixuan Sun Dachuan Li Bohua Qiu Muheng Wei Guangdong Laboratory of Artificial Intelligence and Digital Economy (Shenzhen) Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Stony Brook University New York United States Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China ZhenDui Industry Artificial Intelligence Co. Ltd Shenzhen China Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

Realizing Generalized Zero-Shot Learning (GZSL) based on large models is emerging as a prevailing trend. However, most existing methods merely regard large models as black boxes, solely leveraging the features output by the final layer while disregarding potential performance enhancements from other layers. Indeed, numerous researchers have visually depicted variations in the features learned across different layers of neural networks. Motivated by this observation, we propose a Vision Transformer (ViT)-based GZSL method named Depth-Aware Multi-Modal ViT (DAM2ViT), which exploits multi-level features of ViT. DAM2ViT incorporates a multi-modal interaction block to align semantic information of categories across multiple layers, thereby augmenting the model's capacity to learn associations between visual and semantic spaces. Extensive experiments conducted on three benchmark datasets (i.e., CUB, SUN, AWA2) have showcased that DAM2ViT achieves competitive results compared to state-of-the-art methods.

关键词： Visualization Adaptation models Semantics Zero shot learning Neural networks Termination of employment Transformers Market research Sun Optimization

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A Lossless Image Compression Algorithm Based On Group Encoding

A Lossless Image Compression Algorithm Based On Group Encodi...

引用

International Conference on Advanced Computer information Technologies (ACIT)

作者： Vasyl Koval Vasyl Yatskiv Igor Yakymenko Diana Zahorodnia Department of Information Computing Systems and Control Ternopil National Economic University Ternopil city 8 Chekhova str. Ukraine Department of Cyber Security Ternopil National Economic University Ternopil city 8 Chekhova str. Ukraine

ISBN: (数字)9781728167602

ISBN: (纸本)9781728167619

This paper considers a new lossless image compression algorithm that provides reduction of data redundancy in video processing systems. To achieve the high compression level group encoding approach is proposed. The experimental research shows that proposed algorithm provides 1.33 times better compression quality index than the Run Length Encoding (RLE) algorithm.

关键词： Image coding Image color analysis Channel coding Image segmentation Arrays

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Conception of Ontology for Computer Methods of Paintings Analysis

Conception of Ontology for Computer Methods of Paintings Ana...

引用

2019 International Multi-Conference on Engineering, Computer and information Sciences, SIBIRCON 2019

作者： Beloozerov, Viktor Murashov, Dmitrij Trusova, Yuliya Berezin, Aleksej Ivanova, Ekaterina All-Russia Institute for Scientific and Technical Information Department for Classification Systems Development Moscow Russia Institute of Educational Informatics Federal Research Center 'Information and Control' Moscow Russia A. A. Dorodnicyn Computing Center Federal Research Center 'Information and Control' Moscow Russia State Historical Muzeum Restoration Department Moscow Russia Ilya Glazuvov Russian Academy of Painting Sculpture and Architecture Department of Painting Restoration Moscow Russia

ISBN: (纸本)9781728144016

This paper describes the procedure of developing the 'OntArt' ontology for the subject area 'Attribution and restoration of works of easel oil painting'. Special attention is paid to the domain of computer methods application. The basis of the work is a previously developed thesaurus of this domain. The conceptual shell of the original thesaurus descriptors is the standard CIDOC CRM framework, which binds domain concepts to abstract philosophical categories. In order to connect particular concepts with abstract categories, it is proposed to include 21 intermediate-level conceptual classes in the CIDOC CRM structure. Thus, we have built a formalized structure of concepts for the area of attribution and restoration of painting, ranging from the highest philosophical abstractions to specialized methods of computer analysis of picture images. This structure includes about 1300 terms in Russian. The English part has about 500 terms and is replenished as the interlanguage equivalence of the terms is agreed. In the part of vocabulary of computer methods, we have a full bilingual ontology with one-To-one correspondence of the Russian and English versions. The current version of the ontology is implemented as a TiddlyWiki software module and is publicly available. © 2019 IEEE.

关键词： Ontology

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