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An Anomalous Traffic Detection Approach for the Private Network Based on Self-learning Model 1

3rd International Conference on Machine Learning for Cyber Security, ML4CS 2020

作者： Han, Weijie Xue, Jingfeng Zhang, Fuquan Zhang, Yingfeng School of Computer Science and Technology Beijing Institute of Technology Beijing China School of Space Information Space Engineering University Beijing China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China Equipment Development Department Beijing100071 China

ISBN: (数字)9783030622237

ISBN: (纸本)9783030622220

Although being isolated from the external network, the private network is still faced with some security threats, such as violations communications, malware attacks, and illegal operations. It is an attractive approach to recognize these security threats by discovering the underlying anomalous traffic. By studying the anomalous traffic detection technologies, an anomalous traffic detection approach is developed by capturing and analyzing the network packets, detecting the anomaly traffic that occurs in the network, and then detects anomalous behaviors of the network timely. In order to enhance its effectiveness and efficiency, a self-learning model is proposed and deployed in the detection approach. Finally, we conduct necessary evaluations about the proposed approach. The test results show that the approach can reach a good effect for detecting the unknown anomalous traffic. © 2020, Springer Nature Switzerland AG.

关键词： Learning systems

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A Power Balance Control Strategy of Wireless Sensor Network with Collaborating Heuristic 16th

A Power Balance Control Strategy of Wireless Sensor Network ...

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16th International Conference on Intelligent information Hiding and Multimedia Signal processing, IIH-MSP 2020 in conjunction with the 13th International Conference on Frontiers of information technology, Applications and Tools, FITAT 2020

作者： Yu, Jie Dao, Thi-Kien Ngo, Truong-Giang Nguyen, Trong-The College of Mechanical and Automotive Engineering Fujian University of Technology Fuzhou350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China Faculty of Computer Science and Engineering Thuyloi University 175 Tay Son Dong Da Hanoi Viet Nam Department of Information Technology Haiphong University of Management and Technology Haiphong18000 Viet Nam

ISBN: (纸本)9789813367562

In order to effort a strong enough signal, nodes in wireless sensor networks (WSN) have to increase their transmission power that continues to maintain the transmission power. However, a vicious circle is iterated that causes a decline in the overall network performance, low utility, and network life cycle shorten. This paper presents a solution to the power balance control strategy for WSN with collaborating heuristic. A distance between the weight factors and obtained nodes interference value is used to establish a useful interference model for enhancing the signal-to-interference-noise ratio (SINR). The utility function of the nodes residual energy and transmission rate is modeled by apply heuristic strategy. The optimal transmission power is obtained after several iterations of the heuristic algorithm. Simulation results show that the proposed approach can prolong the network life cycle and achieve higher network utility. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.

关键词： Heuristic algorithms

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An Optimizing Multilevel Thresholding for Image Segmentation Based on Hybrid Swarm Computation Optimization 16th

An Optimizing Multilevel Thresholding for Image Segmentation...

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作者： Dao, Thi-Kien Wang, Hong-Jiang Yu, Jie Nguyen, Huu-Quynh Ngo, Truong-Giang Nguyen, Trong-The Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350118 China College of Mechanical and Automotive Engineering Fujian University of Technology Fuzhou350118 China Faculty of Computer Science and Engineering Thuyloi University 175 Tay Son Dong Da Hanoi Viet Nam Department of Information Technology Haiphong University of Management and Technology Haiphong Viet Nam

ISBN: (纸本)9789813367562

This paper suggests a solution for the image segmentation (IS) problem with the multilevel thresholding based on one of the latest hybrid swarm computation optimization algorithms, particle swarms, and gravitational search (PSGA). The experimental results are comparable with other state-of-the-art algorithms that show that the PSGA on selected images is better than the competitors. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.

关键词： Image segmentation

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Improved hybrid query tree anti-collision algorithm 8th

Improved hybrid query tree anti-collision algorithm

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8th International Conference on computer Engineering and Networks, CENet 2018

作者： Deng, Hongwei Li, Lang Liang, Xiaoman School of Computer Science and Technology Hengyang Normal University HengyangHunan421002 China School of Information Science and Engineering Central South University ChangshaHunan410083 China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang421002 China

ISBN: (纸本)9783030146795

An improved algorithm based on the hybrid query tree (HQT) algorithm is proposed in this work. Tags are categorized according to the combined information of the highest bit of collision and second-highest bit of collision. Then, these tags are used to decide the postponement of several delayed-response time slots, to diminish the collision probability. The performance analysis results show that this algorithm is superior to the query tree (QT) and HQT algorithms. It reduces the query time and system communication traffic and improves the tag identification efficiency. © Springer Nature Switzerland AG 2020.

关键词： Trees (mathematics)

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A hybridized parallel bats algorithm for combinatorial problem of traveling salesman

A hybridized parallel bats algorithm for combinatorial probl...

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作者： Nguyen, Trong-The Qiao, Yu Pan, Jeng-Shyang Chu, Shu-Chuan Chang, Kuo-Chi Xue, Xingsi Dao, Thi-Kien Intelligent Information Processing Research Center Fujian University of Technology Fujian Fuzhou China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fujian China College of Computer Science and Engineering Shandong University of Science and Technology Qingdao China Department of Information Technology University of Manage and Technology Haiphong Viet Nam

Metaheuristic algorithms have been applied widely for real-world problems in many fields, e.g., engineering, financial, healthcare. Bats algorithm (BA) is a recent metaheuristic algorithm with considering as a robust optimization method that can outperform existing algorithms. However, when dealing with complicated combinatorial problems such as traveling salesman problems (TSP), the BA can be fallen in a local optimum. This paper proposes a new hybridizing Parallel BA (HPBA) with a mutation in local-search to escape such its drawback scenario for TSP. A graph theory mutation method is used to embed for hybridizing BA with exploiting similarities among individuals. The proposed method is extensively evaluated in TSP with series instances of the benchmark from TSPLIB to test its performance. The compared experimental result with the previous method and the best-known solutions (B.K.S) in the literature shows that the proposed approach offers competitive results. © 2020 - IOS Press and the authors. All rights reserved.

关键词： Traveling salesman problem

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Fall Detection Based on Person Detection and Multi-target Tracking

Fall Detection Based on Person Detection and Multi-target Tr...

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IEEE International Symposium on information (IT) in Medicine and Education, ITME

作者： Teng Xu Jian Chen Zuoyong Li Yuanzheng Cai School of Electronic Electrical Engineering and Physics Fujian University of Technology Fuzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou China

ISBN: (纸本)9781728194202

Recently, official statistics reported that the Chinese population aged 60 and above has been 26.402 million, which accounts for 18.70% of total population. It is urgent to develop fall detection technologies for alleviating the risk causing by falling of elder person. In this paper, we propose a real-time, high-precision, and deep learning-based fall detection method with automatic person detection and tracking. Specifically, the proposed method first improves the YOLOv3 network to more efficiently detect person and extract feature maps of the object. Then, it inputs the extracted feature maps from the YOLOv3 into a multi-target tracking network for cascade matching and IOU matching in a Deep SORT algorithm, respectively. Next, it improves YOLOv5 network to detect posture anomalies. Finally, it refines the detected posture anomalies for obtaining the final fall detection result. Experimental results show that the proposed method simultaneously improves accuracy and efficiency of the fall detection.

关键词： Deep learning Sociology Education Object detection Aging Feature extraction Real-time systems

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Real-Time Detection of Tea Chrysanthemums in Complex Outdoor Scenes 26

Real-Time Detection of Tea Chrysanthemums in Complex Outdoor...

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26th International Conference on Industrial technology, ICIT 2025

作者： Zang, Siyang Shu, Lei Han, Ru Zhang, Feiya Zhang, Zhijun Deng, Der-Jiunn College of Artificial Intelligence Nanjing Agricultural University Nanjing210031 China School of Environmental Science and Engineering Guangdong University of Petrochemical Technology Guangdong Provincial Key Laboratory for Green Agricultural Production and Intelligent Equipment Maoming525000 China School of Engineering University of Lincoln LincolnLN67TS United Kingdom National Changhua University of Education Department of Computer Science and Information Engineering Changhua50007 Taiwan

ISBN: (纸本)9798331521950

Picking robots have emerged as a pivotal focus in smart agriculture, with precise target position detection being a key element for realizing robotic picking. However, detecting tea chrysanthemums presents various challenges, including their dynamic appearance, complex environmental conditions, susceptibility to occlusion and lighting variations, and the requirement for real-time embedded systems. When applied to complex outdoor scenes for Tea chrysanthemum targets, existing detection models suffer from drawbacks such as missed detections, low accuracy, and slow processing speeds. To address these challenges, we introduce YOLO-VTC (You Only Look Once-Varieties of Tea Chrysanthemum), a lightweight deep-learning model optimized for the Jetson Xavier NX platform. Detection experiments were conducted on image data capturing eight varieties of tea chrysanthemums in complex outdoor scenes collected in 2023. Results demonstrate that YOLO-VTC achieves an average accuracy of 86.60% and a peak accuracy of 97.10%, surpassing other lightweight networks with remarkable performance. Notably, the model effectively maintains a compact size of 6.58MB and has been successfully deployed on edge device platforms. © 2025 IEEE.

关键词： Deep learning

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On Fixed-Order Book Thickness Parameterized by the Pathwidth of the Vertex Ordering 14th

On Fixed-Order Book Thickness Parameterized by the Pathwidth...

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14th International Conference on Algorithmic Aspects in information and Management, AAIM 2020

作者： Liu, Yunlong Chen, Jie Huang, Jingui Wang, Jianxin Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Normal University Changsha410081 China School of Computer Science and Engineering Central South University Changsha410083 China

ISBN: (纸本)9783030576011

Given a graph (Formula Presented) and a fixed linear order (Formula Presented) of V, the problem fixed-order book thickness asks whether there is a page assignment (Formula Presented) such that (Formula Presented) is a k-page book embedding of G. Recently, Bhore et al.(GD2019) presented an algorithm parameterized by the pathwidth of the vertex ordering (denoted by (Formula Presented)). In this paper, we first re-analyze the running time for Bhore et al.’s algorithm, and prove a bound of (Formula Presented) improving on Bhore et al.’s bound of (Formula Presented). We further show that this parameterized problem does not admit a polynomial kernel unless NP (Formula Presented) coNP/poly. Finally, we show that the general fixed-order book thickness problem, in which a budget of at most c crossings over all pages was given, admits an algorithm running in time (Formula Presented). © 2020, Springer Nature Switzerland AG.

关键词： Budget control

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A Time-Driven Cloudlet Placement Strategy for Workflow Applications in Wireless Metropolitan Area Networks

Research Square

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Research Square 2021年

作者： Zhang, Jianshan Li, Ming Zheng, Xianghan Hsu, Ching-Hsien College of Mathematics and Computer Science Fuzhou University Fuzhou China Fujian Provincial Key Laboratory Network Computing and Intelligent Information Processing Fuzhou China Department of Computer Science and Information Engineering Asia University Taichung Taiwan

With the rapid development of mobile technology, mobile applications have increasing requirements for computational resources, and mobile devices can no longer meet these requirements. Mobile edge computing (MEC) has emerged in this context and has brought innovation into the working mode of traditional cloud computing. By provisioning edge server placement, the computing power of the cloud centre is distributed to the edge of the network. The abundant computational resources of edge servers compensate for the lack of mobile devices and shorten the communication delay between servers and users. Constituting a specific forms of edge servers, cloudlets have been widely studied within academia and industry in recent years. However, existing studies have mainly focused on computation offloading for general computing tasks under fixed cloudlet placement positions. They ignored the impact on computation offloading results from cloudlet placement positions and data dependencies among mobile application components. In this paper, we study the cloudlet placement problem based on Workflow Applications (WAs) in Wireless Metropolitan Area Networks (WMANs). We devise a cloudlet placement strategy based on a Particle swarm optimization algorithm using Genetic algorithm operators with the Encoding Library updating mode (PGEL), which enables the cloudlet to be placed in appropriate positions. The simulation results show that the proposed strategy can obtain a near-optimal cloudlets placement scheme, and compared with other classic algorithms, this algorithm can reduce the execution time of WAs by 15.04%-44.99%. © 2021, CC BY.

关键词： computation offloading

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Advances in Embodied Navigation Using Large Language Models: A Survey

arXiv

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arXiv 2023年

作者： Lin, Jinzhou Gao, Han Feng, Xuxiang Xu, Rongtao Wang, Changwei An, Dong Zhou, Jie Zhang, Man Guo, Li Teng, Xiaoqiang Xu, Shibiao School of Artificial Intelligence Beijing University of Posts and Telecommunications China Aerospace Information Research Institute Chinese Academy of Science China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences China Qilu University of Technology Shandong Academy of Sciences China Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Shandong Fundamental Research Center for Computer Science Jinan250014 China School of Computer and Artificial Intelligence Beijing Technology and Business Unicersitu China

Large Language Models like GPT have gained significant attention for their potential in various practical applications. One notable area of focus is their integration with Embodied Intelligence, particularly in navigation tasks, which require deep environmental understanding and rapid, accurate decision-making. LLMs enhance embodied intelligence systems by providing advanced environmental perception and decision-making support, leveraging their language and image-processing capabilities. This article reviews the symbiosis between LLMs and embodied intelligence, focusing on navigation, and evaluates current models, research methodologies, and datasets. Additionally, it discusses the role of LLMs in the field and forecasts future research directions. A comprehensive list of studies is available at https://***/Rongtao-Xu/AwesomeLLM-EN. Copyright © 2023, The Authors. All rights reserved.

关键词： Optical flows

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