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检索条件"任意字段=2023 International Conference on Computer Science and Automation Technology, CSAT 2023"

共 68658 条记录，以下是221-230 订阅

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An Enhanced Intrusion Detection Model with FeedForward Neural Network Classifier 27

An Enhanced Intrusion Detection Model with FeedForward Neura...

引用

27th international conference on Advanced Communications technology, ICACT 2025

作者： Amirjon, Asadov Gain, Mrityunjoy Oh Kim, Keon Hong, Choong Seon Department of Computer Science and Engineering Kyung Hee University Yongin Korea Republic of Department of Artificial Intelligence Kyung Hee University Yongin Korea Republic of

ISBN: (纸本)9791188428137

A major obstacle in the face of increasingly complex cyberattacks is network security. Proactive security measures require effective intrusion detection systems (IDS) that can precisely classify and categorize network threats. In order to improve network attack detection and classification, this paper proposes a reliable method utilizing a Feedforward Neural Network (FFNN) supplemented with Adaptive Synthetic (ADASYN) sampling. We created a model using the UNSWNB15 dataset that efficiently handles high-dimensional datasets by preprocessing data using a combination of polynomial feature transformation and one-hot encoding. The FFNN model is optimized for binary and multi-class classification tasks. It consists of layers of dense units with dropout and batch normalization. Our method’s efficacy is proven by rigorous training and validation procedures, where the model significantly increased its ability to handle class imbalances and improve classification accuracy. The synthesis of new training data by ADASYN was crucial in improving model performance, especially in underrepresented classes. Evaluation measures that highlight the potential of deep learning in network security applications are ROC-AUC scores and classification reports, which show a notable improvement in our IDS’s detection capabilities. The results show that advanced machine learning techniques can be used to enhance conventional intrusion detection systems and provide a means to build stronger network security designs. Copyright 2025 Global IT Research Institute (GIRI). All rights reserved.

关键词： Network intrusion

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Electrical Contact Performance Simulation for Power Electromechanical Relay Under Inrush Current Conditions

Electrical Contact Performance Simulation for Power Electrom...

引用

international conference of Electrical, Electronic and Networked Energy Systems, EENES 2024

作者： Zhou, Yu Wu, Chengchuang Zhang, Chao Ren, Wanbin School of Electrical Engineering and Automation Harbin Institute of Technology Harbin150001 China School of Instrumentation Science and Engineering Harbin Institute of Technology Harbin150001 China

ISBN: (纸本)9789819618675

Enough high inrush current could cause the closed contacts to repulse each other, and further contact welding failures. This paper analyzes the mechanism of contact repulsion in relays and proposes a method for evaluating the endurance capability of relay contacts under inrush current conditions based on the commercial software COMSOL Multiphysics. The electrodynamic repulsion force between contacts and the contact-spring component are calculated. Furthermore, the relationship between contact force, peak inrush current and the repulsion behavior of relay contacts is analyzed. The relevant test rig is designed, and the obtained experimental results validate the feasibility of the proposed simulation method. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Electrodynamic Repulsion Force Electromechanical Relay Inrush Current

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Experimental Paradigm of Abnormalities Detection in Human-Robot Collaboration with Brain-computer Interaction Techniques 30th

Experimental Paradigm of Abnormalities Detection in Human-Ro...

引用

30th international conference on Computational and Experimental Engineering and sciences

作者： Yu, Xinjia Zhou, Yang Duan, Jian Shi, Tielin Cheng, Tao Huazhong Univ Sci & Technol Sch Mech Sci & Engn Wuhan 430074 Peoples R China Shenzhen Technol Univ Sch Urban Transport & Logist Shenzhen 518118 Peoples R China

ISBN: (纸本)9783031774911;9783031774898;9783031774881

By analyzing the current development process of human-computer collaboration (HRC) and combining the realistic development needs of complex collaborative environments, an experimental paradigm for detecting the abnormalities of the HRC system is constructed by taking collaborative assembly of mobile phone panels as a case study. Brain-computer Interaction (BCI) technique is employed to assess the similarities and differences between normal and abnormal signals, thereby addressing the issue of the inability to predict and model abnormalities in the work of human-computer collaborative assembly (HRCA). The results demonstrate that smaller perceptual differences result in significant similarities and differences between major electroencephalogram (EEG) components, such as N1, N2 and P3. This suggests that the design of the paradigm and experiment is reasonable and feasible. This paper also discusses the next part of the work, which is to generate a mapping model of thinking and intention by extracting multi-dimensional data features, transforming the process of human behaviour - neural response - data features into abnormalities - intention model system task, which will provide an important idea for the systems and robots to better understand and perceive human beings.

关键词： Human-Robot Collaboration (HRC) Brain-computer Interaction (BCI) Abnormalities detection experimental paradigm Electroencephalogram (EEG)

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DM-Vis: A Graph-Based Data Reconnaissance System for Multi-domain Urban Data 41st

DM-Vis: A Graph-Based Data Reconnaissance System for Multi...

引用

41st computer Graphics international conference, CGI 2024

作者： Wang, Hesong Wang, Song Wang, Yanru Long, Hao School of Computer Science and Technology Southwest University of Science and Technology Mianyang China

ISBN: (纸本)9783031818059

As urbanization accelerates, data on the diverse aspects of urban life, including the environment, finance, and transportation, are increasing exponentially. Single-domain data analysis falls short for complex tasks, necessitating multi-source data integration to offer decision-makers a holistic view of interconnections and trends. However, challenges arise in effectively representing data associations and swiftly identifying relevant datasets. This paper proposes techniques to integrate multi-domain urban data relationships and facilitate the acquisition of target datasets. We introduce a method to transform data entities into association graphs and a data extraction method to aid users in understanding data relationships and acquiring target datasets. Using these methods, we developed DM-Vis, a data reconnaissance visual analysis system, to facilitate data integration and exploration from multiple sources. Real-data case studies and positive feedback from users and experts validate the utility and reliability of our approach. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： data extract data integration data reconnaissance multi-domain data query embedding

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Controllable False Data Injection Attack 5th

Controllable False Data Injection Attack

引用

5th international conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Kokkonda, Jayasree Jahnavi, M. Department of Information Technology G. Narayanamma Institute of Technology and Science Hyderabad India Department of Computer Network and Information Security Narayanamma Institute of Technology and Science Hyderabad India

ISBN: (纸本)9789819780426

Yet the Internet of Things continues to grow significantly. A cyber-physical system faces a variety of security challenges due to the network connections made by the various kinds of devices and large systems that make up national infrastructures like a smart grid. Here, For the forward flow and the feedback path of a control system, respectively, we suggest two fake data injection attacks. Both are made using a variable parameter that determines the degree of deterioration. On the forward path, a linear forward assault is created together with the least squares approach. The Kalman filter is constructed on the feedback route. According to the numerical analysis, the suggested assaults govern how much the performance of the control system declines. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Kalman filters

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ASHA: Machine Learning-Based Polycystic Ovary Syndrome (PCOS) Detection and Prediction System 1

ASHA: Machine Learning-Based Polycystic Ovary Syndrome (PCOS...

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1st international conference on AIML-Applications for Engineering and technology, ICAET 2025

作者： Dixit, Jayati Rai, Anshuman Tandon, Pulak Pandey, Dhiraj JSS Academy of Technical Education Noida Information Technology Department Noida India JSS University Noida Computer Science and Engineering Department Noida India

ISBN: (纸本)9798350355611

About 17.5% of adults worldwide are infertile, which emphasizes the urgent need for cutting-edge reproductive healthcare solutions. Based on statistics from June 2023. According to the World Health Organization (WHO), 8-13% of females on earth who are in their reproductive age have PCOS, and about 70% of cases go undiagnosed. With the integration of PCOS detection, IVF success rate prediction, and a period tracking system, this work offers a comprehensive women's health application. In addition, a large percentage of women suffer from menstruation abnormalities, such as dysmenorrhea (38.1%) and irregular frequency (80.7%). This approach improves early illness detection and fertility planning by using data analysis and machine learning. The techniques used are Random Forest, K-Nearest Neighbor, Logistic Regression, Naive Bayes, Decision Tree and SVM;which provides us better accuracy than previous works. © 2025 IEEE.

关键词： Nearest neighbor search

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Numerical Investigation on Mechanical-Electrical-Thermal Characteristics of Contact Pairs with Rough Surface

Numerical Investigation on Mechanical-Electrical-Thermal Cha...

引用

international conference of Electrical, Electronic and Networked Energy Systems, EENES 2024

作者： Wu, Chengchuang Zhou, Yu Zhang, Chao Ren, Wanbin School of Electrical Engineering and Automation Harbin Institute of Technology Harbin150001 China School of Instrumentation Science and Engineering Harbin Institute of Technology Harbin150001 China

ISBN: (纸本)9789819620494

Contact resistance and contact spot temperature rise directly determine the electrical contact reliability of electrical switches. This paper establishes an electrical contact simulation model which can take into account the surface morphology of contacts. The real contact spot morphology, contact spot temperature rise, and possible melting area are calculated and extracted using commercial software COMSOL Multiphysics. And the evolution of real contact area in the mechanical loading process is given in detail. Through simulation, the relationships between contact force, peak value of inrush current, and the temperature rise in the contact area were established. The experimental results demonstrate the feasibility of the proposed simulation method. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Enterprise software

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MetaHG: Enhancing HGNN Systems Leveraging Advanced Metapath Graph Abstraction 25

MetaHG: Enhancing HGNN Systems Leveraging Advanced Metapath ...

引用

20th European conference on computer Systems, EuroSys 2025, co-located 30th ACM international conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2025

作者： He, Haiheng Liu, Haifeng Zheng, Long Huang, Yu Shen, Xinyang Huang, Wenkan Cao, Chuaihu Liao, Xiaofei Jin, Hai Xue, Jingling National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China School of Computer Science and Engineering University of New South Wales Australia

ISBN: (纸本)9798400711961

Heterogeneous Graph Neural Networks (HGNNs) are pivotal for extracting semantic and structural information from heterogeneous graphs. Traditional HGNN implementations often grapple with the challenges of excessive metapath instances, requiring substantial storage or incurring high instance-matching overhead. These methods typically suffer from redundant instance encoding and costly semantic graph construction. Addressing these issues, we introduce an advanced Metapath Graph (MG) abstraction that encapsulates the structural information of all metapath instances within a compact representation. This approach significantly reduces storage demands, eliminates redundant instance encodings, and foregoes the need for constructing semantic graphs, thereby facilitating rapid HGNN inference. Our software-based system, MetaHG, leverages layerwise encoding and aggregation to avoid redundancies without the necessity of semantic graphs. It incorporates a fast, lightweight partitioning method to efficiently manage large graphs. Distinctively, MetaHG seamlessly integrates with both dynamic HGNNs and homogeneous GNNs, unlike conventional systems. Comparative evaluations demonstrate that MetaHG surpasses the state-of-the-art BFS- and DFS-based HGNN systems, MAGNN and the software implementation of MetaNMP, by 42.5× and 4.53×, respectively, on average. © 2025 Copyright held by the owner/author(s).

关键词： Encoding (symbols)

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Design and implementation of infant crying monitoring and analysis system based on deep learning 24

Design and implementation of infant crying monitoring and an...

引用

8th international conference on Electronic Information technology and computer Engineering, EITCE 2024

作者： Huang, Jiayuan Li, Linfeng Gong, Fan Wang, Ziyan Zhan, Huijiong Guangzhou Institute of Science and Technology Guangdong Guangzhou China

ISBN: (纸本)9798400710094

Aiming at the problems that the design functions of intelligent baby monitoring products on the market are too single, such as only equipped with basic environmental monitoring functions and low accuracy of crying recognition caused by only sound sensors for baby cry monitoring, a baby monitoring system based on deep learning and multi-sensor combination is designed. The system uses Jetson Nano B01 as the model deployment terminal, combined with the single-chip microcomputer equipped with sensors and K210 visual processing unit to realize the functions of infant crying monitoring, environment and sign data detection, and based on neural network design. The function of emotional analysis of infant crying is expected to’ translate’ the potential needs and health signals of infant crying. Finally, through the analysis of the algorithm data and the actual test of the system, it is shown that the system can meet the design requirements and achieve the target function, which better solves the shortcomings of the current intelligent infant monitoring products and improves the intelligent level of infant monitoring products. © 2024 Copyright held by the owner/author(s).

关键词： Microcomputers

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Quantum Run-length Encoding: Optimizing Data Compression on Quantum computers with Exponential Resource Efficiency

Quantum Run-length Encoding: Optimizing Data Compression on ...

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2025 IEEE international conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Zhang, Jiale Che, Xilong Jin, Shiyong Pan, Kaifan Peng, Shun Hu, Juncheng College of Computer Science and Technology Jilin University Changchun China Computer Network Information Center University of Chinese Academy of Science Beijing China

ISBN: (纸本)9798350368741

Quantum computers, leveraging superposition and entanglement, offer significant qubit efficiency for data processing compared to classical systems. However, encoding classical data into quantum states, given the current limitations of quantum hardware, often results in higher runtime complexity than classical methods, thus limiting the perceived quantum advantage. Previous quantum data compression methods, primarily based on Amplitude Encoding and mixed-state systems, result in lossy data recovery and necessitate extensive preprocessing. In this work, we propose Quantum Run-Length Encoding (QRLE), a novel lossless quantum data compression method that integrates Basic Encoding with Run-Length Encoding principles. By encoding repeated data sequences with their run lengths, QRLE achieves efficient and accurate data recovery on quantum computers, while exponentially reducing both qubit costs and runtime complexity compared to existing quantum data storage models. We further explore QRLE's application in image processing, where it significantly optimizes quantum resource utilization over recent quantum image representation techniques. Experiments conducted on both quantum simulators and IBM's superconducting quantum computer validate the efficiency of QRLE and confirm its compatibility with current quantum hardware. © 2025 IEEE.

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