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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Sakhare, Nitin N. Thangarasu, N. Rajarajeswari, S. Dedgaonkar, Suruchi G. Rengarajan, A. Pareek, Ravi Kant Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Karpagam Academy of Higher Education Department of Computer Science Coimbatore India Prince Shri Venkateshwara Padmavathy Engineering College Department of Science and Humanities Chennai India Vishwakarma Institute of Information Technology Department of Information Technology Pune India Department of Computer Science and Information Technology Karnataka Bangalore India Vivekananda Global University Department of Civil Engineering Jaipur India

ISBN: (纸本)9798350319125

Latest advances in artificial intelligence (AI) have given upward push to automated mastering engines which can be capable of leveraging big quantities of records to become aware of and extract applicable information with top notch accuracy. This has enabled more green records retrieval strategies, which has capability to revolutionize how human beings use and get admission to facts. computerized studying engines are capable of acting complex duties consisting of natural language processing, sentiment analysis, and object recognition, all of which require extensive computation strength. because of this possibilities for more suitable statistics retrieval systems are getting an increasing number of available to *** automatic mastering engine is particularly beneficial in situations wherein there's an abundance of statistics. The engine is able to filter and narrow down the facts to identify and extract simplest the most beneficial data. This allows to keep away from clutter and false positives from the hunt consequences, accordingly main to greater accurate and reliable results. moreover, their capacity to examine from the records they process way that they can be tailor-made to particular use instances, thereby making searches greater green and powerful. furthermore, automated mastering engines can perform at a miles quicker fee than traditional seek techniques. through automating the technique of statistics collection, evaluation, and usage, time is stored and the efficiency of the whole information retrieval system is substantially improved. this may have a ways-reaching implications. © 2023 IEEE.

关键词： information positives quicker system traditional

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Asymptotics-Aware Multi-View Subspace Clustering

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IEEE Transactions on Multimedia 2025年 27卷 3650-3663页

作者： Xu, Yesong Chen, Shuo Li, Jun Yang, Jian Anhui Polytechnic University School of Computer and Information Wuhu241000 China RIKEN Center for Advanced Intelligence Project Tokyo103-0027 Japan Nanjing University of Science and Technology PCA Laboratory Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Nanjing210094 China Nanjing University of Science and Technology Jiangsu Key Laboratory of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing210094 China

Recently, multi-view subspace clustering has attracted extensive attention due to the rapid increase of multi-view data in many real-world applications. The main goal of this task is to learn a common representation of multiple subspaces from the given multi-view data, and most existing methods usually directly merge multiple groups of features by the single-step integration. However, there may exist large disparities among different views of the data, and thus the conventional single-step practice can hardly obtain a generally consistent feature representation for the multi-view data. To overcome this challenge, we present a novel approach dubbed "Asymptotics-Aware Multi-view Subspace Clustering (A2 MSC)"to pursue a consistent feature representation in a multi-step way, which iteratively conducts the data recovery to gradually reduce the differences between pairwise views. Specifically, we construct an asymptotic learning rule to update the feature representation, and the iteration result converges to a consistent feature vector for characterizing each instance of the original multi-view data. After that, we utilize such a new feature representation to learn a clustering-oriented similarity matrix via minimizing a self-expressive objective, and we also design the corresponding optimization algorithm to solve it with convergence guarantees. Theoretically, we prove that the learned asymptotic representation effectively integrates multiple views, thereby ensuring the effective handling of multi-view data. Empirically, extensive experimental results demonstrate the superiority of our proposed A2 MSC over the state-of-the-art multi-view subspace clustering approaches. © 2025 IEEE.

关键词： Data assimilation

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A DeBERTa-GPLinker-Based Model for Relation Extraction from Medical Texts 36

A DeBERTa-GPLinker-Based Model for Relation Extraction from ...

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36th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2024

作者： Deng, Zhiqi Gong, Shutao Luo, Xudong Liu, Jinlu School of Computer Science and Engineering Guangxi Key Lab of Multi-source Information Mining and Security Guangxi Key Lab of Education Blockchain and Intelligent Technology of Ministry of Education Guangxi Normal University Guilin541004 China

ISBN: (纸本)9798331527235

Extracting causal relationships in medical texts is essential for improving clinical decision support systems and constructing comprehensive medical knowledge graphs. This paper presents a novel model for extracting causal, conditional, and hypernym relationships from Chinese medical texts, combining DeBERTa's advanced contextual encoding with GPLinker's efficient entity and relationship extraction mechanisms. Our approach computes the score matrix of entities and their causal relationships, followed by a decoding process to obtain the final predictions. On the CMedCausal dataset, comparative experiments highlight our model's superior performance in terms of precision, recall, and F1 score, demonstrating its robustness and effectiveness in managing overlapping and nested entities and accurately extracting causal relationships in Chinese medical texts. © 2024 IEEE.

关键词： DeBERTa GPlinker Medical text Pre-trained model Relation ex-traction

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A Design Study on Integrated Complex Coefficient Filters with Peripheral Circuits for Accurate Frequency Response Measurement

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, information and Systems 2025年第1期145卷 16-24页

作者： Shouno, Kazuhiro Sato, Lina Fukagawa, Kanta Tanimoto, Hiroshi Muto, Cosy Division of Information Engineering University of Tsukuba 1-1-1 Tennoudai Ibaraki Tsukuba305-8573 Japan Graduate School of Science and Technology Degree Programs in Systems and Information Engineering Master’s Program in Computer Science University of Tsukuba Japan Kitami Institute of Technology 165 Koen-cho Hokkaido Kitami090-8507 Japan Faculty of Education Nagasaki University 1-14 Bunkyo-machi Nagasaki852-8521 Japan

This paper proposes a measurement technique for an integrated complex filter. The proposed method is based on two measurement methods with integrated circuitry for calibration. It is accomplished by applying square waves to an FUT (Filter Under Test) instead of sinusoidal waves or by superposing transfer characteristics obtained by applying a single sinusoidal wave to an FUT. In both of the above methods, the output signal connected to the external measurement equipment via a 50 Ω coaxial cable and so on. In this case, the output signal of the FUT should be amplified by internal or external amplifiers, which degrades the response. However, it is cancelled out by the proposed calibration circuitry with some analog switches. In addition to the above, for the RC polyphase filter, the source resistance and the load capacitance degrade the measurement results and their effect is discussed. The validity of the proposal is confirmed through computer simulation for a third-order RCPF whose passband is 8–40 MHz fabricated by Phenitec 0.6 µm CMOS process. It is shown that the measurement error is −1.10 dB for the square-wave method and −1.00 dB and −0.43 degrees for the superposition method at 40 MHz. © 2025 The Institute of Electrical Engineers of Japan.

关键词： Capacitance

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Examining the Challenges in Implementing AI-Driven Systems for Automated Data Science 15

Examining the Challenges in Implementing AI-Driven Systems f...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Vanaja, T. Shelke, Priya M. Gautam, Sandeep Yadav, Rakesh Kumar Chowhan, Santosh Ravivarman, G. Department of Information Technology Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Department of Information Technology Vishwakarma Institute of Technology Pune India Department of Computer Science & Engineering Vivekananda Global University Jaipur India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Karnataka BangaloreEmail India Department of Electrical and Electronics Engineering Karpagam Academy of Higher Education Coimbatore641021 India

ISBN: (纸本)9798350370249

this paper provides an overview brand new the contemporary in employing synthetic Intelligence (AI) strategies to automate statistics technological know-how procedures. It highlights state-of-the-art the demanding situations related to the mixing of those structures with current infrastructure and implementations, as well as ability solutions. It also outlines the significance trendy thinking about a broad range latest AI-driven system, which include supervised and unsupervised studying, Deep Neural network (DNN) architectures, version-based reinforcement present day, and lively state-of-the-art. The paper in addition discusses how every of these systems can be used to automate sure components modern the records technology system, and the way their use can bring about stronger accuracy and effectiveness brand new records science operations. In the end, it evaluates latest the important thing concerns which want to be taken into account while defining and implementing an AI-pushed device for computerized information technological know-how. ©20XX IEEE.

关键词： Network architecture

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Artificial Intelligence in Next-Generation Networking: Energy Efficiency Optimization in IoT Networks Using Hybrid LEACH Protocol

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SN computer Science 2024年第5期5卷 1-22页

作者： Khan, Surbhi Bhatia Kumar, Ankit Mashat, Arwa Pruthviraja, Dayananda Imam Rahmani, Mohammad Khalid Mathew, Jimson School of Science Engineering and Environment University of Salford Salford United Kingdom Department of Information Technology Guru Ghasidas Vishwavidyalaya Chhattisgarh Bilaspur India Department of Information Systems Faculty of Computing and Information Technology King Abdulaziz University Rabigh 21911 Saudi Arabia Department of Information Technology Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Karnataka Manipal 576104 India Department of Computer Science College of Computing and Informatics Saudi Electronic University Riyadh 11673 Saudi Arabia Department of Computer Science and Engineering Indian Institute of Technology Patna Bihar Patna India

The convergence of the Internet of Things (IoT) and Artificial Intelligence (AI) is significantly transforming the landscape of future networking. The Internet of Things (IoT) is a technological paradigm that encompasses embedded systems, wireless sensors, and automation, facilitating the integration of various applications ranging from smart homes to wearable devices. In addition, the advent of artificial intelligence (AI) amplifies this influence by providing data-driven analytics, optimising processes, and presenting novel opportunities for growth. Nevertheless, the widespread adoption of devices within Internet of Things (IoT) networks gives rise to apprehensions regarding increased energy consumption. In order to ensure the longevity of network operations, it is imperative to employ energy-efficient protocols for sensor nodes that possess limited power resources. One example of a protocol that demonstrates this concept is the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. This protocol effectively divides networks into clusters and dynamically adjusts the cluster heads to optimise the transmission of data to the base stations. Our study enhances the LEACH protocol by incorporating digital twin simulation, thereby enhancing the efficiency of IoT systems. Virtual network models and AI analytics are employed to assess energy consumption and performance. Cache nodes play a crucial role within this framework as they collect data from cluster heads in order to transmit it to the base station. By leveraging artificial intelligence (AI) and simulation techniques, we are able to improve the energy efficiency and reliability of the Internet of Things (IoT) systems. The findings indicate a significant reduction of 83% in non-functioning nodes and a notable increase of 1.66 times in energy levels of nodes compared to conventional approaches. This study highlights a potential direction for energy-efficient, AI-enhanced Internet of Things (IoT) networking through

关键词： Cluster head Clustering Data aggregation Gateway Internet of things LEACH Lifetime

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A Legal Multi-Choice Question Answering Model Based on DeBERTa and Attention Mechanism 36

A Legal Multi-Choice Question Answering Model Based on DeBER...

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36th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2024

作者： Luo, Ying Luo, Xudong Chen, Guibin School of Computer Science and Engineering Guangxi Normal University Guangxi Key Lab of Multi-source Information Mining and Security Guangxi Key Lab of Education Blockchain and Intelligent Technology of Ministry of Education Guilin541004 China

ISBN: (纸本)9798331527235

This paper presents a novel multi-choice question answering model tailored for the legal domain, which integrates a DeBERTa-based framework with bilinear attention mechanisms. The model is designed to enhance the interpretation of complex legal texts, utilising vector similarity searches to align questions with pertinent statutes and a neural network to analyse this data effectively. It aims to improve the accuracy of legal question answering by employing advanced techniques of natural language processing. A binary classifier is also incorporated to assess answer options and generate conclusive responses. Experimental results demonstrate the model's superiority over traditional methods, particularly in handling intricate legal questions. This study underscores the model's potential to advance legal AI technology significantly, offering substantial benefits for judicial examinations and legal professionals. © 2024 IEEE.

关键词： Bilinear attention mechanism Legal article matching Legal question answering Natural language processing Neural network

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Impacts of Different Altitudes on 5G Performance: A Case Study of a Public Hospital in Central Bangkok 8

Impacts of Different Altitudes on 5G Performance: A Case Stu...

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8th IEEE International Conference on Recent Advances and Innovations in engineering, ICRAIE 2023

作者： Chatchalermpun, Surachai Daengsi, Therdpong Pornpongtechavanich, Phisit Phanrattanachai, Kritphon Sriamorntrakul, Pakkasit Chukusol, Chawin SAU Computer Engineering Bangkok Thailand RMUTP Sustainable Industrial Management Engineering Bangkok Thailand RMUTR Information Technology Prachuap Khiri Khan Thailand PCRU Computer Engineering Phetchabun Thailand PBRU Technology and Innovation in Education Phetchaburi Thailand

ISBN: (纸本)9798350315516

This paper presents an evaluation of the performance of 5G when the altitude of the test points is changed. In this study, the high-rise building in the crowded public hospital in the urban area of Bangkok that supports a lot of patients every Monday to Friday was selected as the place for the field tests. Two smartphones from the same vendor, which supports 5G, that were installed with the Speedtest application were used as the tools for this study. The tests were conducted on the first floor and the twenty-fourth floor for data gathering. After the analysis using a statistical technique, it has been found from the analyzed results that the download speeds tend to decrease when the altitude of the test points is increased. This means that the indoor coverage improvement of 5G is required for high-rise buildings. © 2023 IEEE.

关键词： Floors

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Character Classification and Actor Recognition in Yakshagana Images Using Machine Learning Techniques and Facial Makeup Pattern Analysis 8

Character Classification and Actor Recognition in Yakshagana...

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8th IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2024

作者： Murthy, Anantha Prathwini Kulkarni, Sanjeev Savitha, G. Nitte Karkala Institute of Computer Science and Information Science Srinivas University Department of Master of Computer Applications India Department of Master of Computer Applications Karkala India Srinivas University Institute of Engineering and Technology Department of Computer Science and Engineering Mangalore India Manipal Institute of Technology Manipal Academy of higher Education Manipal Department of Data Science and Computer Applications India

ISBN: (纸本)9798350350593

Yakshagana, a traditional theater form from Karnataka, India, features a unique combination of vibrant costumes, dynamic dance movements, and elaborate facial makeup, making character and actor identification a challenging task for automated systems. This research work presents a novel approach to classify Yakshagana characters into two primary categories, Vaishnava and Shaiva, and to identify the actors performing these characters using advanced machine learning techniques. Our research employs a Cyclic Gated Recurrent Neural Network (Cyclic GRNN) for classification and identification tasks. For character category classification, we integrate YOLOv3 and Faster R-CNN models, achieving an accuracy of 92.85% with YOLOv3 and 88.285% with Faster R-CNN. The categorization is specifically focused on distinguishing between Vaishnava and Shaiva characters. Additionally, for actor name identification, we utilize a RESNET-50 model, attaining a high accuracy of 95.60%. The results demonstrate the efficacy of Cyclic GRNN combined with state-of-the-art object detection and image classification models in accurately recognizing and categorizing Yakshagana characters and actors. This research contributes to the preservation and digital documentation of Yakshagana by providing robust tools for automated identification, thereby facilitating cultural heritage studies and enhancing audience engagement with this traditional art form. © 2024 IEEE.

关键词： Recurrent neural networks

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Fuzzy Concession Strategy for Emotional Human-computer Negotiation 36

Fuzzy Concession Strategy for Emotional Human-Computer Negot...

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36th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2024

作者： Luo, Xudong Luo, Ying Sun, Kaili Li, Yanling School of Computer Science and Engineering Guangxi Normal University Guangxi Key Lab of Multi-source Information Mining and Security Guangxi Key Lab of Education Blockchain and Intelligent Technology of Ministry of Education Guilin541004 China

ISBN: (纸本)9798331527235

This paper proposes an emotion-based human-computer negotiation system. Existing systems handle basic dialogues but struggle with complex negotiations involving human emotions. To address this, we design a fuzzy concession strategy that adjusts tactics through sentiment analysis, managing states like anger, happiness, and anxiety. Experiments show significant improvement in negotiation success and overall gains when considering emotional factors. Results demonstrate that this model enhances customer satisfaction and user experience by achieving agreements that satisfy users. This research highlights the potential of integrating fuzzy reasoning, sentiment analysis, and natural language processing into AI systems, laying the foundation for more intelligent, human-like dialogue agents and improving human-computer interaction and e-commerce engagement. © 2024 IEEE.

关键词： Natural language processing systems

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