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检索条件"任意字段=8th IEEE International Conference on Software Engineering and Computer Systems, ICSECS 2023"

共 1546 条记录，以下是931-940 订阅

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CAN Bus Attack Detection Based on Entropy and CNN-SVM 8th

CAN Bus Attack Detection Based on Entropy and CNN-SVM

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Wang, Ziqing Fang, Yuanjie Yue, Mingfei Wang, Jing College of Electrical Engineering Anhui Polytechnic University Anhui Wuhu241000 China School of Electronic Engineering Chaohu University Anhui Chaohu238024 China

ISBN: (纸本)9789819602933

the intelligent development of automobiles has increased the dependence on automotive bus networks, such as real-time power control and maneuvering control of automobiles, all of which require the use of in-vehicle networks as a medium for information transfer. Due to the lack of security measures such as information authentication and identity authentication in Controller Area Network (CAN), it is easy to be invaded by hackers. therefore, in order to improve the security communication guarantee of in-vehicle CAN network, this paper proposes a dual detection method based on the combination of information entropy and CNN-SVM. the method judges the suspicious traffic by preliminary detection based on information entropy, and then further makes more accurate attack judgment on the suspicious traffic based on the deep detection method of CNN extracting features and SVM for classification. the experimental results show that the dual detection model improves the detection effect and has better performance compared with the single model. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Authentication

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Total Supply Capability Evaluation of Distribution systems considering Soft Open Points and Network Reconfiguration

Total Supply Capability Evaluation of Distribution Systems c...

引用

ieee international conference on Power and Power and Renewable Energy (ICPRE)

作者： Shan He Qilin Hou Jing Wang Yuming Zhao Shenzhen Power Supply Company China Southern Power Grid Shenzhen China State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of Macau Macao China Country

the increasing power demands in cities pose great challenges in power supply capacities of distribution networks. this paper introduces an emerged power electronic device, soft open point (SOP), and network reconfiguration to enhance the maximum total supply capability (TSC) of distribution networks. Unlike previous studies usually leverage simplified models, we propose an accurate mixed-integer second-order cone model to evaluate and optimize the TSC of a distribution networks, in which power flows and SOPs are precisely described. Simulation results confirm that employing SOPs can significantly enhance network TSC through active power transmission and reactive power compensation. Moreover, it can also reduce the power loss among the whole systems so that the energy-efficiency can be improved.

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Optimization-Based Algorithm for Detecting Key Information in Yolov7 Literature 8th

Optimization-Based Algorithm for Detecting Key Information i...

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Wang, Jianrong Yu, Xiangqian Zhang, Zeyu Bai, Jujie School of Automation and Software Engineering Shanxi University Taiyuan030006 China School of Engineering and Technology University of Washington-Tacoma TacomaWA98402 United States

ISBN: (纸本)9789819601875

Literature is a reservoir of knowledge, which contains the research results, theoretical discussions and practical experiences of previous generations. Literature key information including title, author, journal name, keywords, DOI and publisher is an important part of scientific and technological literature, and it is also the key basis for scientific and technological literature e-resources repositories and researchers to store, manage and retrieve literature. In order to accurately extract the information, an optimization-based YOLOv7 literature key information detection algorithm is proposed. And the three optimization measures include the introduction of CSPResNet, CSPPAN and SA attention mechanism. the experimental results show that the optimized YOLOv7-based literature key information detection algorithm achieves an average accuracy (AP0.5) of 94.0% and takes 8.99 frames/second, which maintains a faster detection speed while having a better accuracy. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Feature Extraction Key information from the literature Objective detection YOLOv7

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AI Based Smart Cleaner with IOT Integration

AI Based Smart Cleaner with IOT Integration

引用

international conference for Convergence of Technology (I2CT)

作者： Prachi Ambadkar Prashansa Kumbhare Chaitanya Bonde Harsh Shukla Kartik Dharkar Bhushan Vidhale Department of Electronics and Telecommunication G H Raisoni College of Engineering Nagpur India

the usage of self-sufficient systems to complete pertinent and delicate projects is quickly growing. But it is impossible to overstate its importance in a number of industries. In this post, an automatic floor cleaner that uses an Arduino Nano and hand gestures from artificial intelligence is presented. three ultrasonic sensors, an Arduino microcontroller, two tools with DC motors, an RF 433 module, and an accelerometer make up the system. By communicating alerts to a microcontroller through an interface, ultrasonic sensors are used to identify impediments along the robotics route. the micro-controller directs the robotic to move in the other direction by turning on the motors in order to go around the recognized obstruction. Additionally, two DC vehicles for cleaning cloths .With the use of sensors on an Arduino board, a VLSI test bench can be improved quickly, and hand gestures give a human control over the device. Rapid processing and an intuitive user interface are the main benefits. Recent years have seen a significant increase in the number of individuals using open source software and hardware, which has led to the emergence of a new generation by simplifying and enticing complex tasks.

关键词： Microcontrollers Very large scale integration User interfaces Robot sensing systems DC motors Turning Acoustics

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Audio Based Music Genre Classification using Convolutional Neural Networks Sequential Model

Audio Based Music Genre Classification using Convolutional N...

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international conference for Convergence of Technology (I2CT)

作者： Simran Pasrija Shubham Sahu Shweta Meena Department of Software Engineering Delhi Technological University Delhi India

Music recommendation system has high demand in the modern world, and these types of systems recommend music according to music genres. the music combines lyrics and beautiful sounds, and lyrics can be in any language. thus, sound plays an essential role in defining the genres of all music written in different. therefore, the recognition of music genres is a challenging task. However, various studies have been found in this area that performed well. However, the performance of the system can be further increased. thus, the proposed research aims to identify the music genres with good performance. this study used GTZAN Dataset, which is a publicly available dataset. this dataset has ten classes and around 1000 samples for each category. this system used the Convolutional neural network (CNN) model to recognize the performance of the music genres recognition system. the CNN model has ten layers, eight dense and two dropout layers. the achieved accuracy by the proposed model is 98.30%.

关键词： Training Mood Music Metals Rocks Convolutional neural networks Task analysis

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DroneReqValidator: Facilitating High Fidelity Simulation Testing for Uncrewed Aerial systems Developers

DroneReqValidator: Facilitating High Fidelity Simulation Tes...

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ieee international conference on Automated software engineering (ASE)

作者： Bohan Zhang Yashaswini Shivalingaiah Ankit Agrawal Department of Computer Science Saint Louis University Saint Louis MO USA

Rigorous testing of small Uncrewed Aerial systems (sUAS) is crucial to ensure their safe and reliable deployment in the real world. sUAS developers aim to validate the reliability and safety of their applications through simulation testing. However, the dynamic nature of the real-world environment, including factors such as challenging weather conditions and wireless interference, causes unique software faults that may only be revealed through field testing. Considering the high cost and impracticality of conducting field testing in thousands of environmental contexts and conditions, there exists a pressing need to develop automated techniques that can generate high-fidelity, realistic environments enabling sUAS developers to deploy their applications and conduct thorough simulation testing in close- to- reality environmental conditions. To address this need, DroneReqValidator (DRV) offers a comprehensive small Unmanned Aerial Vehicle (sUAV) simulation ecosystem that automatically generates realistic environments based on developer-specified constraints, monitors sUAV activities against predefined safety parameters, and generates detailed acceptance test reports for effective debugging and analysis of sUAV applications. Providing these capabilities, DRV offers a valuable solution for enhancing the testing and development process of sUAS. the comprehensive demo of DRV is available at https://***/watch?v=Fd9ft55gbO8

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A Hybrid Structure Based on VMD-LSSVM and Improved Quantum Particle Swarm Simultaneous Optimization for Wind Speed Prediction 1

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Haotian, Hou Sizhou, Sun Shengpeng, Wang School of Electrical Engineering Anhui Polytechnic University Wuhu241000 China

ISBN: (数字)9789819603138

ISBN: (纸本)9789819603121

To enhance the forecasting performance, a novel short-term wind speed prediction model based on the improved quantum particle swarm optimization algorithm (IQPSO) for synchronous optimization of variational mode decomposition (VMD) and least squares support vector machine (LSSVM) is proposed. In the proposed model, IQPSO is used to optimize the internal parameters including decomposition layers and penalty factors of VMD and the kernel parameters of LSSVM. the typical statistical indicators including mean absolute error (MAE), root mean square error (RMSE) and correlation coefficient (R2) are utilized to evaluate the prediction model. the experimental results show that the statistical indicators RMSE, RMSE and R2 of the improved quantum particle swarm simultaneous optimization VMD-LSSVM model are only 0.62 m/s, 0.47 m/s, and 0.95, which have relatively high accuracy compared with the rest of the prediction models. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Wind forecasting

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Development of a 2D Measurement System for Implementation in Robots Used for Industrial Parts Verification

Development of a 2D Measurement System for Implementation in...

引用

ieee international conference on Control and Robotics engineering (ICCRE)

作者： Delond Angelo Jimenez-Nixon Maycool Jonas Artica-Zelaya Marcio Javier Paz-Cardona Faculty of Engineering Universidad Tecnológica Centroamericana (UNITEC) San Pedro Sula Honduras

Due to the high quality demands in the manufacturing industry, there is a need for strict and reliable quality inspection processes and/or systems. In Honduras there is a large need for robot implementations, some of the main reasons for a lack of high use levels are insufficient financial and training resources. the main objective of this study is to offer a robotic end effector capable of detecting and calculation the dimension of objects in a 2D plane using a lidar sensor and by way of the development of a measurement algorithm using computer vision. With the tools and guidelines obtained using the hierarchical method t was possible to develop a 2D measurement system for implementation in robots used for industrial parts verification. the system counts with the capability to auto adjust and take into account the distance at which the camera is located when detecting and thus measuring object. it is able to measure a number of object obtaining there height and width. the values for precision of the system are 88% obtaining the height and 85% calculating the width. Confirming that the development is capable of detection and measuring object in a 2D plane.

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Smart Grid Tolerance Invasion Control Under False Data Injection Attacks 8th

Smart Grid Tolerance Invasion Control Under False Data Injec...

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Li, Ming Wei, Lisheng Wang, Ruiren Anhui Key Laboratory of Electric Drive and Control Anhui Polytechnic University Wuhu241000 China School of Electrical Engineering Anhui Polytechnic University Wuhu241000 China

ISBN: (纸本)9789819602247

Aiming at the problem of how to maintain stable and secure operation of the smart grid after a false injection attack, the tolerant intrusion control of the system after a false data injection attack is investigated. First, since there is no publicly available FDIA dataset, two datasets are generated: one contains random single-node attacks and the other contains random multi-node attacks. Second, combining AE and Generative Adversarial Network (GAN), and introducing Wasserstein distance and gradient penalty term to avoid the problems of gradient vanishing and pattern collapse that GAN is prone to in adversarial training;at the same time, adversarial training is used to achieve Nash equilibrium, learn spatial relationship between data, and complete the data reconstruction;the method does not need labeled data from measurement instruments, and only requires attack-free historical state data to complete the training, thus it is unsupervised learning. Finally, the simulation results show that the adopted recovery scheme can accurately restore the contaminated state quantities to their pre-attack values, and has high recovery accuracy for FDIA contamination. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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A Novel Advanced Algorithm in Automation of Food and Health Monitoring System using IOT

A Novel Advanced Algorithm in Automation of Food and Health ...

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international conference for Convergence of Technology (I2CT)

作者： Pattem. Sampath Kumar J. Vijayasree K Saikumar Mohammed Ayad Alkhafaji Ahmed J. Obaid Sajad Ali Zearah Malla Reddy Institute of Engineering & Technology Hyderabad India Department of Electronic and Communication Vignan’s Institute of Information Technology (A) Dept of ECE Koneru Lakshmaiah Education Foundation HyderabadR.V.S Nagar Moinabad-Chilkur Rd near AP Police Academy Aziznagar Telangana India Department of Medical Device Industry Engineering College of Engineering Technology National University of Science and Technology Dhi Qar Iraq Faculty of Computer Science and Mathematics University of Kufa Iraq Scientific Research Center Al-ayen University Thi-Qar Iraq

Food is one of the essential factors in human growth and development. the recent results of the internet of things and robots have already shown the beginnings of a new food monitorization. Automation in the restaurants and food sector did not originate technically, so humanoid-related IoT platforms are necessary. In this research, an advanced monitoring algorithm for the automation of food & health system performs using the (IoT). the suggested system develop using food quality sensing devices. Each detector was equipped with the above qualities and connected using breadboards and relay boards. there is tremendous fear and motivation in the thought that there may not be enough food to go around as the human population expands exponentially. To construct a monitoring system that can identify the presence of people, gases, and temperature differences, we employed website creation in combination with the (IoT). the designed application has attained a sensitivity of 97.53%, an accuracy of 98.83%, a recall of 97.98%, and a detection rate of 98.91%. the implemented technology is beneficial to researchers and society. the proposed IoT-based automation of food & health monitoring system compete with present technology and outperforms the methodology.

关键词： Temperature sensors Automation Sensitivity software algorithms Sociology Sensor phenomena and characterization Sensor systems

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