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2021 Zooming Innovation in Consumer Technologies Conference, ZINC 2021

作者： Sari, Alparslan Butun, Ismail University of Delaware Computer Systems and Networking Department of Electrical and Computer Engineering NewarkDE19716 United States Chalmers University of Technology Network and Systems Division Department of Computer Science and Engineering Gothenburg412 96 Sweden

ISBN: (纸本)9781665404174

In this paper, by targeting low-level code optimization, an instruction scheduler is designed and experimented with a synergistic processor unit (SPU) to show its effectiveness on a basic block and data dependency graph (DDG) called compiler instruction scheduler (CIS). In our methodology, a source C/C++ file is converted to an assembly file via spu-gcc to detect stalls in basic code blocks and CIS generates the DDG of executable code to eliminate stalls to find optimization opportunities and increase the program performance. The CIS simply shuffles the instruction sequences of the assembly code to eliminate CPU stalls in a given basic instruction block. Random and sliding window schedulers are implemented to generate a new assembly code sequence based on DDG and a basic block in parallel. Finally, this paper describes how CIS finds the optimized code sequence for a given file without any conflicts and hazards. Compared to the original code compilation process, we have shown that CIS improves the code execution metrics, and also our evaluated speedup results are found to be promising. © 2021 IEEE.

关键词： Scheduling

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Measuring spatial distances in causal sets via causal overlaps

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Physical Review D 2024年第2期110卷 024008-024008页

作者： Marián Boguñá Dmitri Krioukov Departament de Física de la Matèria Condensada Universitat de Barcelona Institute of Complex Systems (UBICS) Department of Physics Network Science Institute Department of Mathematics Department of Electrical and Computer Engineering

Causal set theory is perhaps the most minimalistic approach to quantum gravity, in the sense that it makes next to zero assumptions about the structure of spacetime below the Planck scale. Yet even with this minimalism, the continuum limit is still a major challenge in causal sets. One aspect of this challenge is the measurement of distances in causal sets. While the definition and estimation of timelike distances is relatively straightforward, dealing with spacelike distances is much more problematic. Here we introduce an approach to measure distances between spacelike separated events based on their causal overlap. We show that the distance estimation errors in this approach vanish in the continuum limit even for the smallest distances of the order of the Planck length. These results are expected to inform the causal set geometrogenesis in general, and in particular the development of evolving causal set models in which space emerges from causal dynamics.

关键词： Quantum gravity

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Industrial Scenario of Renewable Energy-Based Electromobility 3rd

Industrial Scenario of Renewable Energy-Based Electromobilit...

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3rd International Conference on Energy systems, Drives and Automations, ESDA 2020

作者： Szymanski, Jerzy Zurek-Mortka, Marta Faculty of Transport Electrical Engineering and Computer Science Kazimierz Pulaski University of Technology and Humanities Radom Poland Department of Control Systems Lukasiewicz Research Network Institute for Sustainable Technology Radom Poland

ISBN: (纸本)9789811672736

The article presents the concept of a hybrid network topology in the enterprises with the use of a solar power plant and energy storage as well as a drive frequency converter for charging of transportation battery of wheels vehicles and powering of electric caterpillar mining machines. Two important functionalities of the drive frequency converter as a unidirectional EV battery charger and for powering electric motors are presented. The obtained results of the simulation and experimental tests of the presented model confirm the possibility of controlling the DC current value of connected to drive frequency converter of the diode rectifier unit charging the EV battery. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Solar energy

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Mining the Chatbot Brain to Improve COVID-19 Bot Response Accuracy

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computers, Materials & Continua 2022年第2期70卷 2619-2638页

作者： Mukhtar Ghaleb Yahya Almurtadha Fahad Algarni Monir Abdullah Emad Felemban Ali M.Alsharafi Mohamed Othman Khaled Ghilan Department of Information Systems College of Sciences and ArtsUniversity of BishaAl Namas67392Saudi Arabia Department of Computer Science College of Computing and Information TechnologyUniversity of TabukTabuk71491Saudi Arabia Department of Computer Science College of Computing and Information TechnologyUniversity of BishaBisha61922Saudi Arabia Computer Engineering Department Umm Al-Qura UniversityMakkah21955Saudi Arabia Department of Communication Technology and Network Universiti Putra MalaysiaSelangor43400Malaysia Faculty of Public Health and Tropical Medicine Jazan UniversityJazan45142Saudi Arabia

People often communicate with auto-answering tools such as conversational agents due to their 24/7 availability and unbiased ***,chatbots are normally designed for specific purposes and areas of experience and cannot answer questions outside their *** employ Natural Language Understanding(NLU)to infer their *** is a need for a chatbot that can learn from inquiries and expand its area of experience with *** chatbot must be able to build profiles representing intended topics in a similar way to the human brain for fast *** study proposes a methodology to enhance a chatbot’s brain functionality by clustering available knowledge bases on sets of related themes and building representative *** used a COVID-19 information dataset to evaluate the proposed *** pandemic has been accompanied by an“infodemic”of fake *** chatbot was evaluated by a medical doctor and a public trial of 308 real *** obtained and statistically analyzed tomeasure effectiveness,efficiency,and satisfaction as described by the ISO9214 *** proposed COVID-19 chatbot system relieves doctors from answering *** provide an example of the use of technology to handle an infodemic.

关键词： Machine learning text classification e-health chatbot COVID-19 awareness natural language understanding

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Fault Tolerant Neural Control Barrier Functions for Robotic systems under Sensor Faults and Attacks

Fault Tolerant Neural Control Barrier Functions for Robotic ...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Hongchao Zhang Luyao Niu Andrew Clark Radha Poovendran Electrical and Systems Engineering Department McKelvey School of Engineering Washington University in St. Louis St. Louis MO Department of Electrical and Computer Engineering Network Security Lab University of Washington Seattle WA

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Safety is a fundamental requirement of many robotic systems. Control barrier function (CBF)-based approaches have been proposed to guarantee the safety of robotic systems. However, the effectiveness of these approaches highly relies on the choice of CBFs. Inspired by the universal approximation power of neural networks, there is a growing trend toward representing CBFs using neural networks, leading to the notion of neural CBFs (NCBFs). Current NCBFs, however, are trained and deployed in benign environments, making them ineffective for scenarios where robotic systems experience sensor faults and attacks. In this paper, we study safety-critical control synthesis for robotic systems under sensor faults and attacks. Our main contribution is the development and synthesis of a new class of CBFs that we term fault tolerant neural control barrier function (FT-NCBF). We derive the necessary and sufficient conditions for FT-NCBFs to guarantee safety, and develop a data-driven method to learn FT-NCBFs by minimizing a loss function constructed using the derived conditions. Using the learned FT-NCBF, we synthesize a control input and formally prove the safety guarantee provided by our approach. We demonstrate our proposed approach using two case studies: obstacle avoidance problem for an autonomous mobile robot and spacecraft rendezvous problem, with code available via https://***/HongchaoZhang-HZ/FTNCBF.

关键词： Space vehicles Sufficient conditions Fault tolerance Neural networks Fault tolerant systems Robot sensing systems Safety

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Performance Optimization for Vehicular Cooperative Sensing: A Graph Attention Based Reinforcement Learning Approach

Performance Optimization for Vehicular Cooperative Sensing: ...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Li, Xuefei Chen, Mingzhe Liu, Danpu Zhang, Zhilong Quek, Tony Q. S. Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing100876 China University of Miami Department of Electrical and Computer Engineering Institute for Data Science and Computing Coral GablesFL33146 United States Information Systems Technology and Design Pillar Singapore University of Technology and Design 487372 Singapore

ISBN: (纸本)9798350351255

In this paper, the problem of collaborative vehicle sensing is investigated. In the considered model, a set of cooperative vehicles provide sensing information to sensing request vehicles with limited sensing and communication resources. A base station (BS) determines the subset of sensing request vehicles that each cooperative vehicle will serve and the sub-regions that each cooperative vehicle will detect. We formulate an optimization problem aiming to maximize the number of successfully detected sub-regions of sensing request vehicles while satisfying the cooperative sensing energy requirement by jointly determining the cooperative vehicle association and the sensing sub-region selection. To solve this problem, we propose a graph attention based reinforcement learning (RL) algorithm that can generate the graph information vectors based on the correlation between each cooperative vehicle and each sensing request vehicle. Using the learned graph information, the joint cooperative vehicle association and sensing sub-region selection strategy will be determined. Simulation results show that the proposed scheme can improve the number of successfully detected sub-regions of sensing request vehicles by up to 12.5% compared to the conventional RL algorithm without using graph attention networks (GANs). © 2024 IEEE.

关键词： Reinforcement learning

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Analysis and control of complex cyber-physical networks

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Asian Journal of Control 2022年第2期24卷 495-497页

作者： Wen, Guanghui Jalili, Mahdi Ren, Wei Cao, Yongcan Du, Haibo Chen, Guanrong Research Center for Complex Systems and Network Sciences School of Mathematics Southeast University Nanjing China School of Engineering RMIT University MelbourneVIC Australia Department of Electrical Engineering University of California RiversideCA United States Department of Electrical and Computer Engineering University of Texas at San Antonio San AntonioTX United States School of Electrical Engineering and Automation Hefei University of Technology Hefei China Department of Electrical Engineering City University of Hong Kong Hong Kong

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Fast CU Partition for VVC Using Texture Complexity Classification Convolutional Neural network

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computers, Materials & Continua 2022年第11期73卷 3545-3556页

作者： Yue Zhang Pengyu Liu Xiaowei Jia Shanji Chen Tianyu Liu Chang Liu The Information Department Beijing University of TechnologyBeijing100124China School of Physics and Electronic Information Engineering Qinghai Minzu UniversityXining810000China Advanced Information Network Beijing Laboratory Beijing100124China Computational Intelligence and Intelligent Systems Beijing Key Laboratory Beijing100124China Department of Computer Science University of PittsburghPittsburgh15260USA

Versatile video coding(H.266/VVC),which was newly released by the Joint Video Exploration Team(JVET),introduces quad-tree plus multitype tree(QTMT)partition structure on the basis of quad-tree(QT)partition structure in High Efficiency Video Coding(H.265/HEVC).More complicated coding unit(CU)partitioning processes in H.266/VVC significantly improve video compression efficiency,but greatly increase the computational complexity *** ultra-high encoding complexity has obstructed its real-time *** order to solve this problem,a CU partition algorithm using convolutional neural network(CNN)is proposed in this paper to speed up the H.266/VVC CU partition ***,64×64 CU is divided into smooth texture CU,mildly complex texture CU and complex texture CU according to the CU texture ***,CU texture complexity classification convolutional neural network(CUTCC-CNN)is proposed to classify ***,according to the classification results,the encoder is guided to skip different RDO search *** optimal CU partition results will be *** results show that the proposed method reduces the average coding time by 32.2%with only 0.55%BD-BR loss compared with VTM 10.2.

关键词： Versatile video coding(VVC) coding unit partition convolutional neural network(CNN)

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Average Performance Analysis of Multi-Class Classification Based on Error-Correcting Output Codes

Average Performance Analysis of Multi-Class Classification B...

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IEEE International Conference on systems, Man and Cybernetics

作者： Manabu Kobayashi Gendo Kumoi Hideki Yagi Shigeichi Hirasawa Center for Data Science Waseda University Tokyo Japan Department of Information and Management Systems Engineering Nagaoka University of Technology Niigata Japan Department of Computer and Network Engineering University of Electro-Communications Tokyo Japan

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

In machine learning, one of the methods to solve multiclass classification problems is a framework called Error-Correcting Output Codes (ECOC), which constructs a multiclass classifier by combining a lot of binary classifiers. ECOC assigns binary codewords to each category, and the multiclass classification performance varies depending on the code. In this study, we treat each element of the codeword as a random variable and evaluate the average performance of ECOC. As a result, for $M$ class classification if the number of binary classifiers is $O(\log M)$ , then the average error probability of various codes approaches that of MAP estimation. We show that the important points are the ratio between the number of binary classifiers and $\log M$ and the difference between the maximum posterior probability and the second highest posterior probability for the categories.

关键词： Codes Error probability Posterior probability Estimation Machine learning Random variables Performance analysis Cybernetics

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Real-Time Services Robot with an Intelligent System Based on a Radio Frequency Identification Unit.

Real-Time Services Robot with an Intelligent System Based on...

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International Conference on Developments in esystems engineering (DESE)

作者： Yousif Al Mashhadany Mohanad A. Al-Askari Abdullah Al-Ani Taisir Ahmed Yaseen Dawod Alani Sameer Algburi Department of Electrical Engineering University of Anbar Anbar Iraq Information Systems Department University of Anbar Baghdad Iraq Computer Network Department University of Anbar Anbar Iraq College of Engineering Al-Kitab University Kurkuk Iraq

ISBN: (数字)9798350368697

ISBN: (纸本)9798350368703

Technological developments have come a long way in developing service robots and employing them to serve human needs to the fullest extent. Communication between the robot and its user is the most important aspect, and developing a system to train robots and provide them with the necessary capabilities to accomplish specific tasks is important for creating a suitable service robot. This work provides solutions to most of the challenges in developing such systems using smart systems that can implement multiple and complex commands in a short and appropriate time, such as matching data outputs with what is examined by these systems. For this reason, (RFID) was used to compare data and give commands so that the robot can move in complex environments. Another challenge to consider is keeping the robot on the specified path without deviating from its specified path, so a special sensor was developed to track the robot’s deviation and correct the path. Another challenge to consider is if the robot might collide with an object on the path, this problem has been solved by a wireless sensor, all of which is processed and controlled by the microprocessor and motor control unit. Several practical tasks were implemented for the proposed model, and these tasks were in complex and different environments and under difficult conditions. The proposed service robot model was able to implement them with very high accuracy, so it can be relied upon as an advanced service robot model.

关键词： Wireless communication Wireless sensor networks Service robots Tracking Computational modeling Robot sensing systems Smart systems Real-time systems Robots Radiofrequency identification

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