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2024 IEEE International Conference on Control science and Systems engineering, ICCSSE 2024

作者： Yu, Jiyang Huang, Dan He, Xiaobao Han, Yong Wang, Jianyu Sun, Kaiwen Beijing Institute of Spacecraft System Engineering China Academy of Space Technology Beijing China China Research and Development Academy of Machinery Equipment Chongqing University of Technology Beijing Chongqing China College of Computer Science and Engineering Chongqing University of Technology Chongqing China

ISBN: (纸本)9798331517199

An improved imitation learning algorithm based on Markov chain is proposed, aiming to enhance the performance of autonomous driving in complex environments. Imitation learning learns task execution by observing expert behavior, while Markov chains are used to model state transition processes. The existing imitation learning algorithms have limited ability to handle complex tasks, especially in natural environments. The algorithm proposed in this article improves learning efficiency and autonomous control performance by introducing strategy iteration and reward function design for sudden obstacles. The core idea is to introduce Markov decision processes into traditional imitation learning frameworks to improve learning efficiency and performance. By acquiring a refined strategy, the objective is to mimic the agent's actions within the environment to closely resemble those of the expert. To achieve this, first train an initial strategy using expert examples. Then, use this strategy to generate new examples and update the strategy using these examples. This process iterates continuously until the strategy converges. The experimental results show that on the lunar environment autonomous driving datasets, the accuracy of our algorithm reaches 95% with a mean square error of 0.02, while the accuracy of the comparative algorithm is the highest at 90% with a mean square error of 0.05. This indicates that the improved algorithm can more accurately learn and imitate the driving behavior of experts. In addition, the performance of the algorithm is stable at different iteration times, indicating good convergence. © 2024 IEEE.

关键词： Contrastive Learning

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Development of a Real-time Location Monitoring App with Emergency Alert Features for Android Devices 4

Development of a Real-time Location Monitoring App with Emer...

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4th IEEE Global Conference for Advancement in technology, GCAT 2023

作者： Gowda, Dankan V. Prasad, K.D.V. Shekhar, R. Srinivas, Rachakonda Srinivas, Kale Naga Venkata Lakineni, Prasanna Kumar Department of Electronics and Communication Engineering BMS Institute of Technology and Management Karnataka Bangalore India Pune India Department of Computer Science and Engineering Alliance University Karnataka Bangalore India Department of Computer Science and Engineering Aditya Institute of Technology and Management Tekkali India Department of Computer Science and Engineering Aditya College of Engineering Surampalem India Department of CSE GITAM School of Technology GITAM University Visakhapatnam India

ISBN: (纸本)9798350305258

Smartphones have completely altered the mobile communication scene. Wi-Fi, global positioning system navigation, high-resolution cameras, and touchscreens with high-speed internet access are just some of the cutting-edge capabilities that these devices offer, allowing users to stay in constant contact with the present. Since many of these features are embedded deeply in the mobile operating system, they are typically inaccessible to the average user. However, Google released Android, a revolutionary operating system. Because of its open system architecture, this platform encourages third-party development and a debugging environment that users may change to create their own unique apps. In this research project, we examine the development of an Emergency Based Remote Collateral Tracking System app on the Android mobile platform from Google. There are three main forms of emergencies: those involving the heart, those involving personal safety, and those involving the roads. Users who own and operate motor vehicles are the primary focus of this app. Our program can keep tabs on the driver's pulse by connecting to a heart rate monitor. Our application has a backup function in case of anomalies. First, it sends SMS messages containing the user's location data after using GPS to do so. © 2023 IEEE.

关键词： Android application development Emergency alert system GPS tracking Location monitoring app Location sharing Real-time location tracking

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An Ensemble Based Approach for Sentiment Classification in Asian Regional Language

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computer Systems science & engineering 2023年第3期44卷 2457-2468页

作者： Mahesh B.Shelke Jeong Gon Lee Sovan Samanta Sachin N.Deshmukh G.Bhalke Daulappa Rahul B.Mannade Arun Kumar Sivaraman Department of Computer Science and Information Technology Dr.Babasaheb Ambedkar Marathwada UniversityAurangabadMaharashtra431004India Division of Applied Mathematics Wonkwang University460Iksan daeroIksan SiJeonbuk54538Korea Department of Mathematics Tamralipta MahavidyalayaTamlukWest Bengal721636India Department of Electronics and Telecommunication Engineering AISSMSCOEPuneMaharashtra411001India Department of Information Technology Govemment College of EngineeringAurangabadMaharashtra431005India School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India

In today’s digital world,millions of individuals are linked to one another via the Internet and social *** opens up new avenues for information exchange with *** analysis(SA)has gotten a lot of attention during the last *** analyse the challenges of Sentiment Analysis(SA)in one of the Asian regional languages known as Marathi in this study by providing a benchmark setup in which wefirst produced an annotated dataset composed of Marathi text acquired from microblogging websites such as *** also choose domain experts to manually annotate Marathi microblogging posts with positive,negative,and neutral *** addition,to show the efficient use of the annotated dataset,an ensemble-based model for sentiment analysis was *** contrast to others machine learning classifier,we achieved better performance in terms of accuracy for ensemble classifier with 10-fold cross-validation(cv),outcomes as 97.77%,f-score is 97.89%.

关键词： Sentiment analysis machine learning lexical resource ensemble classifier

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Dynamic Simulation Research of Metamorphic Parallel Manipulator Based on ADAMS 5

Dynamic Simulation Research of Metamorphic Parallel Manipula...

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5th International Conference on Artificial Intelligence Technologies and Applications, ICAITA 2023

作者： Lin, Sian Wang, Jirong Xiao, Yihao Li, Jun College of Mechanical and Electrical Engineering Qingdao University Qingdao266071 China College of Computer Science and Technology Qingdao University Qingdao266071 China Weihai Innovation Research Institute of Qingdao University Weihai264200 China

ISBN: (纸本)9781643684840

Ancient shipwrecks are important marine archaeological objects, for the different shapes of ceramics in ancient shipwrecks are difficult to salvage this problem, a metamorphic parallel manipulator with different grasping configurations for different shapes of ceramics in ancient shipwrecks is designed. In this paper, three types of gripping configurations of the metamorphic parallel manipulator are studied, and the kinematic simulation of the three types of gripping configurations of the metamorphic parallel manipulator is carried out by using ADAMS software to analyse the trend of speed and acceleration change of the relevant driving joints during gripping under the three types of configurations, and to verify that gripping action can be realized. © 2024 The Authors.

关键词： Salvaging

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Syn-BERT: Bi-level Synonymous Data Augmented Self-supervised Embedding-based Information Retrieval with BERT 5

Syn-BERT: Bi-level Synonymous Data Augmented Self-supervised...

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5th IEEE International Conference on Pattern Recognition and Machine Learning, PRML 2024

作者： Yu, Zhaojian Huang, Tianlin Chen, Rong Chen, Haosheng Lin, Shuyuan College of Cyber Security Jinan University Guangzhou510632 China School of Mathematics and Computer Science Quanzhou Normal University Quanzhou362000 China Information Engineering College Xizang Minzu University Shanyang712082 China College of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing Key Laboratory of Image Cognition Chongqing400065 China

ISBN: (纸本)9798350355925

Information retrieval, which seeks to locate the most relevant documents from a document pool given a user query, is critical in a wide range of applications. However, current embedding-based retrieval models require a high quantity of labeled documents as training data to construct appropriate target training tasks, which can be expensive and difficult to obtain in practical applications. In this paper, we present a Synonymous BERT (Syn-BERT) model with strong training data augmentation with the aim of building an effective and efficient retrieval system on unlabeled documents. Unlike most existing embedding-based retrieval models, which require high-quality labeled documents to learn the semantic connections between original documents and labels, the proposed Syn-BERT generates synonymous queries and irrelevant queries for each original document in unlabeled documents and exploits the distances between them to obtain better embeddings. We evaluated the proposed Syn-BERT on two publicly-available Frequently Asked Question datasets, with the experimental results demonstrating that the proposed Syn-BERT achieved state-of-the-art results in embedding-based retrieval tasks with unlabeled documents. © 2024 IEEE.

关键词： Semantics

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A dynamic displacement map based on deep Q-network to assist the rendering of stylised 3D models

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International Journal of Wireless and Mobile Computing 2023年第3-4期24卷 226-234页

作者： Zheng, Hao Yang, Houqun Huang, Mengshi Wang, Yizhen School of Computer Science and Technology Hainan University Haikou Hainan China School of Computing and Artificial Intelligence Southwest Jiaotong University Chengdu Sichuan China College of Physics and Electronic Engineering Hainan Normal University Haikou Hainan China

In the process of rendering with NPR, there will often be a problem of reduced perception of the NPR effect caused by the fixed spatial structure of the static mesh. Therefore, this research first establishes a convolutional neural network to conduct supervised training on numerous hand-drawn target stylised images, and perform continuous angle recognition through stylised images then output its angle vector. Secondly, the displacement map is generated in realtime by inputting the observation angle through the fully connected neural network model. After that, the real-time displacement map is sampled to dynamically generate the deformation of the model. In the end, the goal of breaking the model's sense of space and enhancing the NPR rendering effect can be achieved. Besides, the experimental results of this study verify the effectiveness of the method. © 2023 Inderscience Enterprises Ltd.

关键词： Neural network models

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A Scan Slice Reordering Algorithm Based on Minimizing Entropy to Enhance Test Data Compression Efficiency

A Scan Slice Reordering Algorithm Based on Minimizing Entrop...

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International Test Conference in Asia (ITC-Asia)

作者： Minghe Zhang Guanglun Huang Guoliang Ji Zhiqiang You Qiang Wu Jianyu Cao School of Computer Science and Information Security Guilin University of Electronic Technology Guilin China No.208 Research Institute China Ordnance Industries Beijing China College of Computer Science and Electronic Engineering Hunan University Changsha China

ISBN: (数字)9798331540333

ISBN: (纸本)9798331540340

To improve test data compression efficiency, the order of the scan unit need be adjusted, which indirectly changes the content of the test pattern. Scan chain partitioning is a common method that utilises this concept. However, current scan chain partitioning methods can still be optimised in terms of entropy and test data compression efficiency, and lack universality. To enhance the efficiency of code-based compression efficiency, we propose a scan slice reordering algorithm that minimizes entropy. This algorithm first calculates the rank of each scan slice or column vector of the test set, and then dynamically adjusts the order of the scan slices according to the descending order of these ranks in the pursuit of minimizing the entropy of the test set. By iterating through this process, the optimal position of each scan slice in the test set is ultimately determined. Compression experiments should be performed on all test patterns using different code-based schemes. This not only reduces the entropy of the test set but also significantly improves the efficiency of different codes. Compared to traditional scan chain partitioning method, FDR encoding achieved an average compression ratio increase of 6.16%, and RL-Huffman encoding achieved an average compression ratio increase of 4.96%. The experimental results demonstrate that our proposed algorithm is feasible, effective, and universal.

关键词： Codes Test data compression Heuristic algorithms Asia Entropy Encoding Vectors

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Online Pareto optimal control of mean-field stochastic multi-player systems using policy iteration

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science China(Information sciences) 2024年第4期67卷 21-37页

作者： Xiushan JIANG Yanshuang WANG Dongya ZHAO Ling SHI College of New Energy China University of Petroleum(East China) Department of Electronic and Computer Engineering Hong Kong University of Science and Technology

In this study, the Pareto optimal strategy problem was investigated for multi-player mean-field stochastic systems governed by It? differential equations using the reinforcement learning(RL) method.A partially model-free solution for Pareto-optimal control was derived. First, by applying the convexity of cost functions, the Pareto optimal control problem was solved using a weighted-sum optimal control problem. Subsequently, using on-policy RL, we present a novel policy iteration(PI) algorithm based on the Hrepresentation technique. In particular, by alternating between the policy evaluation and policy update steps,the Pareto optimal control policy is obtained when no further improvement occurs in system performance,which eliminates directly solving complicated cross-coupled generalized algebraic Riccati equations(GAREs).Practical numerical examples are presented to demonstrate the effectiveness of the proposed algorithm.

关键词： mean-field stochastic systems Pareto optimal control policy iteration scheme ℌ-representation

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M-Net: A Lightweight Network Based on Multilayer Perceptron for Massive MIMO CSI Feedback

M-Net: A Lightweight Network Based on Multilayer Perceptron ...

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2023 IEEE Globecom Workshops, GC Wkshps 2023

作者： Yu, Yaxin Tengl, Yinglei Wang, Binghui Liu, An Lau, Vincent School of Electronic Engineering Beijing University of Posts and Telecommunications China College of Information Science and Electronic Engineering Zhejiang University China Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong

ISBN: (纸本)9798350370218

In FDD massive multiple-input multiple-output (MIMO) systems, user equipments (UEs) are required to send back the downlink channel state information (CSI) to base stations (BSs). However, the high-dimentional CSI souring proportional to antennas leads to unacceptable feedback overhead. Recently, deep learning (DL) has shown its unique powerful ability to compress and reconstruct CSI. In this paper, a novel Multilayer Perceptron (MLP) based feedback network, named M-Net, is proposed, where the specific spatial correlation of channels is emphasized by tailored feature processing modules. To meet the practical requirements of lightweight networks and ensure low inference latency, M-Net adopts parameter sharing to reduce network complexity and eliminates complex operations. Additionally, to leverage the computational resources at the BSs, we design a scalable decoder to further improve the performance of the network. Simulation results show that the proposed M-Net achieves almost the state-of-the-art (SOTA) performance with the lowest computational complexity, while exhibiting a remarkable 49.63% reduction in the inference delay compared to TransNet. Finally, we demonstrate that the M-Net variants achieve the SOTA performance by only deep enning the M-Net decoder. The open source codes are available at https://***/Password-YYX/M-Net. © 2023 IEEE.

关键词： CSI feedback deep learning Massive MIMO multilayer perceptron

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Privacy-Preserving Techniques for IoT Data Sharing 9

Privacy-Preserving Techniques for IoT Data Sharing

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9th International Conference on science, technology, engineering and Mathematics, ICONSTEM 2024

作者： Karthikeyan, P. Teotia, Shashiraj Pawan, Toralkar Reena, B. Ardly Melba Vibhakar, Chirag Kalai Priya, V. Velammal College of Engineering And Technology Department of Electronics And Communication Engineering Tamil Nadu Madurai625009 India Swami Vivekanand Subharti University Department of Computer Application Meerut250005 India Madanapalle Institute of Technology & Science Department of Artificial Intelligence Andhra Pradesh Madanapalle517325 India Saveetha University Department of Computer Science And Engineering Tamil Nadu Chennai600124 India Gujarat Power Engineering &. Research Institute Mevad Mehsana Gujarat Technological University Department of Electrical Engineering Gujarat Ahmedabad382710 India Rmk College of Engineering And Technology Department of Computer Science And Engineering Tamil Nadu Puduvoyal601206 India

ISBN: (纸本)9798350365092

In aperiod dominated by the Internet of Effects (IoT), the sharing of data has become an integral aspect of technological advancements. still, the ubiquitous nature of IoT raises significant enterprises regarding stonerse questration. Thisexploration paper delves into innovatives equestration conservingwaysacclimatized for securing the sharing of IoT-generated data. The explores cryptographic protocols, anonymisation strategies, and decentralized fabrics toguard sensitive information while easing meaningful data exchange. Addressing the contradiction between datamileage and individuals equestration, the paper proposes new methodologies that intricately balance the need for dataparticipation with the imperative tocoverstoner confidentiality. By introducing a comprehensive analysis of sequestration-conserving mechanisms with in the IoT eco system, this exploration contribute sprecious perceptivity to the ongoingconverse on securing the digitalgeography. The findings offer a foundation for developing robustfabrics that harmonize the imperatives of dataparticipating with the consummatesignificance of securing stoner sequestration in the expanding realm of Io'Toperations. © 2024 IEEE.

关键词： Privacy-preserving techniques

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