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IEEE Conference on Vehicular Technology (VTC)

作者： Aamer Mohamed Huroon Yu-Chih Huang Li-Chun Wang Department of Electrical Engineering and Computer Science International Graduate Program National Yang Ming Chiao Tung University Institute of Communications Engineering National Yang Ming Chiao Tung University Department of Electrical and Computer Engineering National Yang Ming Chiao Tung University

In this paper, we study the transmission strategy of a ground-based beyond diagonal reconfigurable intelligent surface (BD-RIS), a.k.a RIS 2.0, in a network where multiple unmanned aerial vehicles (UAVs) simultaneously transmit signals to the respective groups of users. It is assumed that each group is assigned subcarriers orthogonal to those assigned to other groups and rate splitting multiple access (RSMA) is adopted within each group. A corresponding mixed integer nonlinear programming problem (MINLP) is formulated, which aims to jointly optimize 1) allocation of BD-RIS elements to groups, 2) BD-RIS phase rotations, 3) rate allocation in RSMA, and 4) precoders. To solve the problem, we propose using generalized benders decomposition (GBD) augmented with a manifold-based algorithm. GBD splits the MINLP problem into two sub-problems, namely the primal and the relaxed master problem, which are solved alternately and iteratively. In the primal problem, we apply block coordinate descent (BCD) to manage the coupling of variables effectively. Moreover, we recognize the manifold structure in the phase rotation constraint of BD-RIS, enabling the Riemannian conjugate gradient (RCG). Simulation results demonstrate the effectiveness of the proposed approach in maximizing spectral efficiency.

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Flow-Based Synthesis of Reactive Tests for Discrete Decision-Making Systems with Temporal Logic Specifications

arXiv

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arXiv 2024年

作者： Graebener, Josefine B. Badithela, Apurva S. Goktas, Denizalp Ubellacker, Wyatt Mazumdar, Eric V. Ames, Aaron D. Murray, Richard M. Graduate Aerospace Laboratories of California Institute of Technology PasadenaCA91125 United States Control and Dynamical Systems California Institute of Technology PasadenaCA91125 United States Department of Computer Science Brown University ProvidenceRI02912 United States Department of Computing and Mathematical Sciences California Institute of Technology PasadenaCA91125 United States

Designing tests to evaluate if a given autonomous system satisfies complex specifications is challenging due to the complexity of these systems. This work proposes a flow-based approach for reactive test synthesis from temporal logic specifications, enabling the synthesis of test environments consisting of static and reactive obstacles and dynamic test agents. The temporal logic specifications describe desired test behavior, including system requirements as well as a test objective that is not revealed to the system. The synthesized test strategy places restrictions on system actions in reaction to the system state. The tests are minimally restrictive and accomplish the test objective while ensuring realizability of the system’s objective without aiding it (semi-cooperative setting). Automata theory and flow networks are leveraged to formulate a mixed-integer linear program (MILP) to synthesize the test strategy. For a dynamic test agent, the agent strategy is synthesized for a GR(1) specification constructed from the solution of the MILP. If the specification is unrealizable by the dynamics of the test agent, a counterexample-guided approach is used to resolve the MILP until a strategy is found. This flow-based, reactive test synthesis is conducted offline and is agnostic to the system controller. Finally, the resulting test strategy is demonstrated in simulation and experimentally on a pair of quadrupedal robots for a variety of specifications. © 2024, CC BY-NC-ND.

关键词： Software testing

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Opportunities and Challenges from Using Animal Videos in Reinforcement Learning for Navigation

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IFAC-PapersOnLine 2023年第2期56卷 9056-9061页

作者： Vittorio Giammarino James Queeney Lucas C. Carstensen Michael E. Hasselmo Ioannis Ch Paschalidis Division of Systems Engineering Boston University Boston MA 02215 USA Center for Systems Neuroscience Department of Psychological and Brain Sciences and Graduate Program for Neuroscience Boston University Boston MA 02215 USA College of Engineering and Hariri Institute for Computing & Computational Science & Engineering Boston University Boston MA 02215 USA

We investigate the use of animal videos (observations) to improve Reinforcement Learning (RL) efficiency and performance in navigation tasks with sparse rewards. Motivated by theoretical considerations, we make use of weighted policy optimization for off-policy RL and describe the main challenges when learning from animal videos. We propose solutions and test our ideas on a 2D navigation task. We show how the use of animal videos improves performance over RL algorithms that do not leverage such observations.

关键词： Learning for Control Reinforcement Learning Deep Learning RL with demonstrations Imitation Learning Bio-inspired Control

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Transistor placement for automatic cell synthesis through Boolean satisfiability 52

Transistor placement for automatic cell synthesis through Bo...

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52nd IEEE International Symposium on Circuits and Systems, ISCAS 2020

作者： Cardoso, Maicon Bubolz, Andrei Cortadella, Jordi Rosa, Leomar Marques, Felipe Graduate Program in Computing Federal University of Pelotas Pelotas Brazil Department of Computer Science Universitat Politècnica de Catalunya Barcelona Spain

ISBN: (纸本)9781728133201

This paper presents a new transistor placement method applied to the ASTRAN EDA tool, an open-source solution for the automatic design of complex digital gates. Although it currently reaches an optimized solution through a Threshold Accepting approach, ASTRAN does not guarantee a minimum-width placement. In this paper, a method based on Boolean satisfiability is proposed, ensuring an optimal solution for the transistor placement task through modeling the problem into a set of Boolean variables and clauses aware of four design rule constraints. Experiments comparing the proposed method and the current ASTRAN placement technique have shown reductions in the layout area. Furthermore, our method achieved a significant improvement regarding runtime, an essential feature for designing digital circuits and systems on-demand. © 2020 IEEE

关键词： Transistors

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Expression of Concern for: Analyzing the Impact of Deep Learning Approaches on Real-Time Data Analysis in Machine Learning

Expression of Concern for: Analyzing the Impact of Deep Lear...

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International Conference on Power Energy, Environment and Intelligent Control (PEEIC)

作者： Deepti Mounika Nalluri Chinna babu Mupparaju Aruna Sri Rongali Sohong Dhar P. Ajitha Sloan School of Management Sloan Fellow Candidate 2023 MIT Masters in Computer Information Systems Murray State University USA Masters in Computer Science university of central Missouri warrensburg USA Graduate Doctoral Information Technology/Graduate (Information Technology Emphasis/Information Technology Ph.D.) University of The Cumberlands US Azure Microsoft library & information science Jadavpur University India School of Computing Sathyabama Institute of science and technology Chennai

ISBN: (数字)9798350357769

ISBN: (纸本)9798350357776

Deep learning is a powerful subset of synthetic intelligence, and it has the potential to significantly enhance the skills of machine getting to know. it's miles primarily based on the idea of artificial neural networks, which might be laptop fashions that are capable of gaining knowledge of from records and making decisions, just like the manner a human mind works. Deep mastering isn't the same as traditional system mastering algorithms in that it can technique complex inputs with multiple layers of abstraction, main to greater accurate evaluation. Deep studying algorithms are capable of unexpectedly examine raw facts and generate styles, making them perfect for actual-time statistics analysis. Deep studying is capable of as it should be predicting behaviors and trends, which may be used to optimize procedures and enhance operational efficiencies. Deep studying models can also be used for automated fault detection and predictive renovation, permitting businesses to count on and prevent capacity troubles. Additionally, deep mastering models frequently offer quicker consequences than other device studying or conventional techniques, as well as permitting an extra diploma of control over the resolution of the data being analyzed. This has widespread implications for real-time programs, such as medical diagnostics, independent automobiles, and manufacturing monitoring.

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Unsupervised Multi-document Summarization for News Corpus with Key Synonyms and Contextual Embeddings 33

Unsupervised Multi-document Summarization for News Corpus wi...

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33rd Conference on Computational Linguistics and Speech Processing, ROCLING 2021

作者： Huang, Yen-Hao Pornvattanavichai, Ratana Alvarado, Fernando Henrique Calderon Chen, Yi-Shin Institute of Information Systems and Applications National Tsing Hua University Hsinchu Taiwan Department of Computer Science National Tsing Hua University Hsinchu Taiwan Social Networks and Human-Centered Computing Program Institute of Information Sciences Academia Sinica Taipei Taiwan

ISBN: (纸本)9789869576949

Information overload has been one of the challenges regarding information on the Internet. It is no longer a matter of information access, instead, the focus has shifted towards the quality of the retrieved data. Particularly in the news domain, multiple outlets report on the same news events but may differ in details. This work considers that different news outlets are more likely to differ in their writing styles and the choice of words, and proposes a method to extract sentences based on their key information by focusing on the shared synonyms in each sentence. Our method also attempts to reduce redundancy through hierarchical clustering and arrange selected sentences on the proposed orderBERT. The results show that the proposed unsupervised framework successfully improves the coverage and coherence, while also reducing the redundancy for a generated summary. Moreover, due to the process through which the dataset is obtained, a data refinement method is proposed to alleviate the problem of undesirable texts, which result from the process of automatic scraping. © 2021 ROCLING 2021 - Proceedings of the 33rd Conference on Computational Linguistics and Speech Processing. All rights reserved.

关键词： Redundancy

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Content and Skills for Teaching Software Process Improvement in the computer science Course: A Mapping of ACM / IEEE, SBC, SWEBOK, CMMI and MR-MPS-SW Assets

Content and Skills for Teaching Software Process Improvement...

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Frontiers in Education (FIE) Conference

作者： Adolfo Francesco De Oliveira Colares Julio Cezar Costa Furtado Sandro Ronaldo Bezerra Oliveira Graduate Program in Computer Science (PPGCC) Institute of Exact and Natural Sciences Federal University of Pará (UFPA) Belém Pará Brazil Department of Exact and Technological Sciences Federal University of Amapá Macápa Amapá Brazil

This Research to Practice Full Paper seeks to map the assets of ACM / IEEE, SBC and SWEBOK guide specifically in the knowledge area of Software Process Improvement (SPI) to create a set of contents and competences to be addressed in the classroom, aligned with international and Brazilian references using the good practices of CMMI DEV v2.0 and MR-MPS-SW 2023. The teacher is the main gear for conducting teaching, research, and extension, being responsible for selecting the methods to be used to improve the teaching-learning process. SPI is a set of partially ordered steps with the intention of achieving a goal within the context of software development and involves understanding existing processes and changing them to increase product quality and / or reduce costs and development time. Thus, teaching SPI needs to be addressed in computing courses to meet the wishes of the software industry.

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Analyzing the Impact of Deep Learning Approaches on Real-Time Data Analysis in Machine Learning

Analyzing the Impact of Deep Learning Approaches on Real-Tim...

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International Conference on Power Energy, Environment and Intelligent Control (PEEIC)

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Enhanced Keypoint-Based Approach for Identifying Copy-Move Forgery in Digital Images

Enhanced Keypoint-Based Approach for Identifying Copy-Move F...

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International Conference on Contemporary computing and Informatics (IC3I)

作者： Girish Singh Bisht Arpit Jain Vandna Bansla Khemraj Sharma Rudramani Bhutia Vikas Kumar Department of Computer Science & Engineering Tula’s Institute Dehradun India Department of Computer Science & Engineering Koneru Lakshamaiah Education Foundation Vadessahwaram A.P. India Shivalik Engineering College Dehradun India Department of Business Administration Doctoral Program in Management Sciences Nanhua University Dalin Chiayi Taiwan R.O.C. Department of Computer Science & Engineering Koneru Lakshmaiah Education Foundation A.P. India School Engineering and Computing Dev Bhoomi Uttrakhand University Dehradun Uttrakhand India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

Copy-move forgeries often exploit homogeneous regions in images with large-scale attacks to either highlight or conceal target objects. These manipulations are simple to execute but challenging to notice. Forgery detection techniques like Copy-Move Forgery Detection (CMFD) cannot detect these forged documents because they are unable to identify a sufficient number of effective keypoints in homogeneous areas, leading to inaccurate and inefficient results. SURF stands for Speeded-Up Robust Features and is used in this paper along with A-KAZE and Scale-Invariant Feature Transforms. According to our experiment, A-KAZE offers superior detection performance under diverse attacks, especially when it comes to large-scale attacks targeting homogeneous regions. A-KAZE is found to be more accurate than SIFT, SURF, and A-KAZE when applied to the NB-CASIA dataset, achieving detection accuracies of $\mathbf{8 9. 2 \%}, \mathbf{9 3. 9 \%}$ and $\mathbf{9 8. 9 8 \%}$.)

关键词： Accuracy Digital images Forensics Transforms Forgery Computational efficiency Reliability Informatics Software development management

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Measurement of Water Diffusion Coefficient in Cross-Linked Gelatins Using the Terahertz Time-Domain Spectroscopy Technique

Measurement of Water Diffusion Coefficient in Cross-Linked G...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Walden, D. Chakraborty, D. Cheng, J. Straksys, A. Stirke, A. Melo, W.C.M.A. Jukna, A. Komissarov, I. Sobolewski, Roman Department of Physics and Astronomy University of Rochester RochesterNY14627 United States Laboratory for Laser Energetics University of Rochester RochesterNY14623-1299 United States Materials Science Graduate Program University of Rochester RochesterNY14627 United States State Research Institute Center for Physical Sciences & Technology Vilnius Lithuania Department of Physics Vilnius Gediminas Technical University Vilnius Lithuania Department of Electrical and Computer Engineering University of Rochester RochesterNY14627 United States

A novel method has been developed to evaluate the water diffusion dynamics in gelatin-based gels, based on transient terahertz time-domain spectroscopy measurements. Such gels are widely used models for human skin. &#... 详细信息

ISBN: (纸本)9781957171395

关键词： Transient analysis

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