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Computational Intelligence, Communication Technology and Networking (CICTN), International Conference on

作者： Satya Prakash Yadav Amit Gupta Caio Dos Santos Nascimento Victor Hugo C. de Albuquerque Mahaveer Singh Naruka Sansar Singh Chauhan Department of Computer Science and Engineering G.L. Bajaj Institute of Technology and Management (GLBITM) GreaterNoida U.P. India Graduate Program in Telecommunications Engineering. (PPGET) Federal Institute of Education Science and Technology of Ceará (IFCE) Fortaleza-CE Brazil Computer Science and Engineering Graphic Era Hill University Dehradun Uttarakhand India Department of Teleinformatics Engineering Federal University of Ceará Fortaleza Fortaleza/CE Brazil Computer Science & Engineering GL Bajaj Institute of Technology & Management Greater Noida India

Virtual assistants are improving and providing consumers with greater advantages. The comprehension and fulfilment of requests by virtual assistants will increase as voice recognition and natural language processing continue to grow. Virtual assistants are projected to be employed in more commercial activities as speech recognition technology advances. The main goal of developing personal assistant software (virtual assistant) is to use web-based semantic data sources, user-generated content, and knowledge from knowledge libraries. Basically, main objective of making this Voice-Based Virtual Assistant is to make life easier and having a personal assistant to everyone which can perform many tasks. As the end user interacts with a virtual assistant, the AI programming learns from the data provided and improves its ability to forecast the end user's needs. Virtual assistants are often used to do things like add tasks to a calendar, provide information that would normally be found in a website, and operate and monitor Smart Home devices like lighting and cameras and thermostats. Massive volumes of data are required to fuel virtual assistant technologies, which feed Artificial Intelligence (AI) platforms such as machine learning, natural language processing, and speech recognition. Speech recognition has a lengthy history and has seen several key advancements. On smartphones and wearable devices, speech recognition for dictation, search, and voice commands has become a standard feature. Design of a small, large vocabulary speech recognition system that can run quickly, accurately, and with minimum latency on mobile devices.

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Dirichlet tessellation for high-dimensional RSS clustering in Wi-Fi environment

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ICIC Express Letters 2014年第7期8卷 2043-2048页

作者： Zhou, Mu Tian, Zengshan Xu, Kunjie Tang, Xiaomou Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and Telecommunications No. 2 Chongwen Road Nanan District Chongqing 400065 China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Graduate Telecommunication and Networking Program School of Information Science University of Pittsburgh PA 15260 United States

The received signal strength (RSS) clustering has played a significant role in site surveying and data pre-processing for the location tracking in Wi-Fi environment. To this end, this paper presents a novel clustering algorithm to cluster the raw RSS vectors with large similarities in both the RSS and physical locations together. The clusters of RSS vectors are determined by the cells which are generated by the Dirichlet tessellation in a transformed low-dimensional space. Our algorithm consists of two steps. We first use the Laplacian embedding to transform the raw measurements into a low-dimensional space, while preserving the RSS and location neighborhood relations. Second, after the seeds of cells are carefully selected, we will tessellate the low-dimensional space by the Dirichlet cells to obtain the clustering results. The experiments conducted in an actual public Wi-Fi environment prove that our algorithm can achieve the smallest cluster scattering in both the RSS and locations compared with the existing affinity propagation clustering, K-means clustering and binary support vector classifier (SVC) algorithms. © 2014 ISSN 1881-803X.

关键词： Wi-Fi

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Multivariate Time Series Anomaly Detection with Deep Learning Models Leveraging Inter-Variable Relationships

Multivariate Time Series Anomaly Detection with Deep Learnin...

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Cybersecurity Conference (SVCC), Silicon Valley

作者： Changmin Seong Dongjun Lim Jiho Jang Jonghoon Lee Jong-Geun Park Yun-Gyung Cheong Department of Computer Science Sungkyunkwan University Suwon South Korea Department of Artificial Intelligence Sungkyunkwan University Suwon South Korea Electronics and Telecommunications Research Institute Daejeon South Korea Department of AI Social Innovation Convergence Program Sungkyunkwan University Suwon South Korea

This paper presents a system for multivariate time series anomaly detection using deep learning, with an added module to reflect variable relationships. The system uses an autoencoder to extract latent variables that reflect the time series characteristics of the variables, and calculates variable importance using the similarities among the variables. To evaluate the proposed method, experiments were conducted using three similarity measures: cosine similarity, distance correlation, and DTW. Four time series datasets were used for evaluation, and the results showed that the proposed model outperformed the baseline model in HAI 22.04 and HAI 21.03 datasets. For the WADI dataset, the Fl-score improved only when using cosine similarity, while the TaPR-Fl score improved only when using DTW. However, no performance improvement was observed in the SWaT dataset. These results suggest that the effectiveness of utilizing inter-variable relationships is dependent on the characteristics of the data and the similarity calculation method employed. Therefore, a careful selection of the appropriate similarity calculation method for a given dataset is necessary to achieve optimal performance improvements.

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A parallel architecture for ray-tracing with an embedded intersection algorithm

A parallel architecture for ray-tracing with an embedded int...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Alexandre S. Nery Nadia Nedjah Felipe M.G. França Lech Jozwiak LAM-Computer Architecture and Microelectronics Laboratory Systems Engineering and Computer Science Program COPPE Universidade Federal do Rio de Janeiro Brazil Department of Electrical Engineering-Electronic Systems Eindhovan University of Technology Netherlands Department of Electronics Engineering and Telecommunications-Faculty of Engineering Universidade do Estado do Rio de Janeiro (UERJ) Brazil

Real time rendering of three-dimensional scenes in Ray Tracing is a hard problem. However, parallel implementations have been enabling real time performance, as the algorithm can be highly parallelized. Thus, a custom parallel design in hardware is likely to achieve a good performance. In this paper, we further improve the GridRT architecture overall performance by embedding the ray-triangle intersection computation into the precessing elements that form the architecture. Low cost and high rendering performance are the main concerns in this novel design. The results show that the execution time of each intersection computation is reduced by at least 50%, while the area cost is practically unchanged or even reduced when compared to the original GridRT implementation.

关键词： Ray tracing Registers Equations USA Councils Mathematical model Parallel architectures

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Error analysis for RADAR neighbor matching localization in linear logarithmic strength varying Wi-Fi environment

The Scientific World Journal

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The Scientific World Journal 2014年第1期2014卷 647370页

作者： Zhou, Mu Tian, Zengshan Xu, Kunjie Yu, Xiang Wu, Haibo Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and Telecommunications Chongqing 400065 China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Kowloon Hong Kong Graduate Telecommunications and Networking Program University of Pittsburgh Pittsburgh PA 15260 United States China Internet Research Lab Computer Network Information Center Chinese Academy of Sciences Beijing 100190 China

This paper studies the statistical errors for the fingerprint-based RADAR neighbor matching localization with the linearly calibrated reference points (RPs) in logarithmic received signal strength (RSS) varying Wi-Fi environment. To the best of our knowledge, little comprehensive analysis work has appeared on the error performance of neighbor matching localization with respect to the deployment of RPs. However, in order to achieve the efficient and reliable location-based services (LBSs) as well as the ubiquitous context-awareness in Wi-Fi environment, much attention has to be paid to the highly accurate and cost-efficient localization systems. To this end, the statistical errors by the widely used neighbor matching localization are significantly discussed in this paper to examine the inherent mathematical relations between the localization errors and the locations of RPs by using a basic linear logarithmic strength varying model. Furthermore, based on the mathematical demonstrations and some testing results, the closed-form solutions to the statistical errors by RADAR neighbor matching localization can be an effective tool to explore alternative deployment of fingerprint-based neighbor matching localization systems in the future. © 2014 Mu Zhou et al.

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Hardware Reuse in Modern Application-Specific Processors and Accelerators

Hardware Reuse in Modern Application-Specific Processors and...

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Euromicro Symposium on Digital System Design

作者： Alexandre S. Nery Lech Jozwiak Menno Lindwer Mauro Cocco Nadia Nedjah Felipe M.G. Franca LAM-Computer Architecture and Microelectronics Laboratory Systems Engineering and Computer Science Program COPPE Universidade Federal do Rio de Janeiro Brazil Department of Electrical Engineering-Electronic Systems Eindhoven University of Technology Netherlands Silicon Hive-Intel UMG Netherlands Department of Electronics Engineering and Telecommunications-Faculty of Engineering Universidade do Estado do Rio de Janeiro Brazil

Effective exploitation of the application-specific parallel patterns and computation operations through their direct implementation in hardware is the base for construction of high-quality application-specific (re-)configurable application specific instruction set processors (ASIPs) and hardware accelerators for modern highly-demanding applications. Although it receives a lot of attention from the researchers and practitioners, a very important problem of hardware reuse in ASIP and accelerator synthesis is clearly underestimated and does not get enough attention in the published research. This paper is an effect of an industry and academic collaborative research. It analyses the problem of hardware sharing, shows its high practical relevance, as well as a big influence of hardware sharing on the major circuit and system parameters, and its importance for the multi-objective optimization and tradeoff exploitation. It also demonstrates that the state-of-the-art synthesis tools do not sufficiently address this problem and gives several guidelines related to enhancement of the hardware reuse.

关键词： Hardware Resource management computer architecture Optimization program processors Adders Delay

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Electronic Meeting System Experience at IBM

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Journal of Management Information Systems 1989年第3期6卷 25-43页

作者： Vogel, Douglas R. Nunamaker Jr., Jay F. Martz Jr., William Benjamin Grohowski, Ronald McGoff, Christopher Assistant Professor of MIS College of Business and Public Administration University of Arizona Tucson Head Department of MIS University of Arizona Professor of MIS and Computer Science University of Arizona Chairman Association for Computing Machinery Curriculum Committee on Information Systems University of Arizona Director of MIS and Telecommunications IBM Systems Integration Division Bethesda Maryland IBM Program Manager IBM Systems Integration Division Bethesda Maryland

Electronic meeting systems (EMS) have been introduced inside IBM in a cooperative effort between IBM and the University of Arizona to address the demands of an increasingly competitive and turbulent business environment. This paper presents and integrates the results of two field studies intended to evaluate the implications of electronic meeting system use at IBM. The first study focused on session process and outcome effectiveness, efficiency, and user satisfaction at a single IBM site. The second study collected data on EMS tool use and facilitation approach within sessions at four IBM sites. The two studies are complementary in reflecting the impact of computer-based support on group process and outcome. Effectiveness, efficiency, and user satisfaction are generally enhanced independent of type of activity supported or perspective, e.g., participant, facilitator, or session initiator. Facilitation training is a critical requirement for successful integration and application of electronic meeting system software and procedures in the group processes this paper addresses. [ABSTRACT FROM AUTHOR]

关键词： decision rooms Electronic meetings facilitation of electronic meetings group decision processes

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Journal of Information science and Engineering: Editorial notice

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Journal of Information science and Engineering 2005年第5期21卷 i-ii页

作者： Lee, Der-Tsai Amato, Nancy M. Chang, Shih-Fu Chen, Homer H. Chen, Tsuhan Hsu, Tsan-Sheng Hwang, Jenq-Neng Kuo, Sy-Yen Kuo, Tei-Wei Li, Chung-Sheng Tokuyama, Takeshi Wing, Jeannette Wu, Tzong-Chen Yen, John Computer Science at Texas A and M University United States Parasol Laboratory United States IEEE Transactions on Parallel and Distributed Systems Computing Research Association's Committee on the Status of Women in Computing Research CRA-W's Distributed Mentor Program United States Department of Electrical Engineering Columbia University United States Lab. United States College of Electrical Engineering and Computer Science National Taiwan University Taiwan IEEE Transactions on Circuits and Systems for Video Technology IEEE Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA United States ACM ACM SIGACT IEEE Computer Society IICM Austria Research and Development of the Department Multimedia Signal Processing Technical Committee IEEE Signal Processing Society United States IEEE Transactions on Circuits and systems for Video Technology College of Electrical Engineering and Computer Science National Taiwan Ocean University Keelung Taiwan Department of Electrical Engineering National Taiwan University Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan IEEE Technical Committee on Real-Time Systems Computer Science Division IBM T.J. Watson Research Center United States IBM Research Division Graduate School of Information Sciences Tohoku University Japan ACM IPSJ Mathematical Society of Japan Japan Department of Computer Science Computer Science Department Carnegie Mellon University United States National Academies of Science's Computer Science and Telecommunications Board United States Microsoft's Trustworthy Academic Advisory Board Intel Research Pittsburgh's Advisory Board United States Dartmouth's Institute for Security Technology Studies Advisory Committee Canada Sloan Research Fellowships Program Committee United States ACM Taiwan China Information Sciences and Technology Pennsylvania State University United States Laboratory for Intelligent Agents Penn State's School of Info

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Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization

arXiv

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arXiv 2023年

作者： Du, Hongyang Zhang, Ruichen Liu, Yinqiu Wang, Jiacheng Lin, Yijing Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Cui, Shuguang Ai, Bo Zhou, Haibo Kim, Dong In The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Computer Science and Engineering Nanyang Technological University Singapore The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications China The School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore Shenzhen China The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China School of Electronic Science and Engineering Nanjing University Jiangsu Nanjing210093 China The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy across various applications. The ability to model complex data distributions and generate high-quality samples has made GDMs particularly effective in tasks such as image generation and reinforcement learning. Furthermore, their iterative nature, which involves a series of noise addition and denoising steps, is a powerful and unique approach to learning and generating data. This paper serves as a comprehensive tutorial on applying GDMs in network optimization tasks. We delve into the strengths of GDMs, emphasizing their wide applicability across various domains, such as vision, text, and audio generation. We detail how GDMs can be effectively harnessed to solve complex optimization problems inherent in networks. The paper first provides a basic background of GDMs and their applications in network optimization. This is followed by a series of case studies, showcasing the integration of GDMs with Deep Reinforcement Learning (DRL), incentive mechanism design, Semantic Communications (SemCom), Internet of Vehicles (IoV) networks, etc. These case studies underscore the practicality and efficacy of GDMs in real-world scenarios, offering insights into network design. We conclude with a discussion on potential future directions for GDM research and applications, providing major insights into how they can continue to shape the future of network optimization. © 2023, CC BY.

关键词： Reinforcement learning

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Digital game-based learning in a robotics course

Digital game-based learning in a robotics course

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International Conference on Information, Intelligence, Systems and Applications (IISA)

作者： Márcio Mendonça Konstantinos Papageorgiou Diene Eire de Mello Elpiniki I. Papageorgiou José Augusto Fabri Lucas Botoni de Souza Rodrigo Henrique Cunha Palácios Universidade Tecnológica Federal do Paraná Cornélio Procópio Brazil Departament of Computer Science & Telecommunications University of Thessaly Lamia Greece Departamento de Educação Universidade EStadual de Londrina Londrina PR Brazil Faculty of Technology University of Thessaly Geopolis Campus Larissa Greece Mechanical Engineering Graduate Program (PPGEM) Universidade Tecnológica Federal do Paraná Cornélio Procópio Brazil

ISBN: (数字)9781665422284

ISBN: (纸本)9781665422291

This paper deals with two experiments regarding games developed in Scratch in the course of robotics at the Universidade Tecnológica Federal do Paraná campus Cornélio Procópio (UTFPR-CP) to assist in the learning of an autonomous vehicle using a similar classic game of war tanks, existing since the 80s for the Atari 2600. In the first experiment, applied to the class 2019/2, a student (player) controls a tank using the keyboard in a battle against another autonomous tank. In this game, certain fundamentals are presented, such as pose (position x, y and the angle formed in relation to the x axis), basic notions about controlled and autonomous robots, hierarchy of actions, modeling using state machine. These concepts were extracted through a questionnaire filled out by the students after the end of the games. The second experiment, applied to the 2020/1 class, was based on a game inspired by the classic Pong, using though more degrees of freedom (DOF). In this case, the player must operate the keyboard to reach a ball through a robotic arm with two rotating joints. Moreover, concepts such as workspace (in two dimensions), multiple solutions, inverse and direct kinematics were introduced. Delivery rates were 90% and 80% regarding the first and the second experiment, respectively. Finally, despite the limited number of these experiments, it is believed that the objective of using more modern didactic tools to teach important concepts in the discipline of robotics has been achieved. Thus, students perceived more easily the basic concepts of robotics presented in the experiments than ever before.

关键词： Three-dimensional displays Keyboards Prototypes Games Tools Manipulators Robots

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