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Influence analysis of calculated horizontally layered soil parameters on grounding parameters

High Voltage 2023年第2期8卷 421-430页

作者： Yihua Dan Junjun Yin Jian Yang Huizhang Yang Department of Electronic Engineering Tsinghua UniversityBeijingChina School of Computer&Communication Engineering University of Science and Technology BeijingBeijingChina

Calculated parameters(soil layer resistivity,soil layer thickness,and the number of soil layers)of horizontally layered soil are usually obtained based on the measured apparent resistivity under different measurement distances,which are significant for the design,operation,and maintenance of grounding *** existing calculation methods of soil parameters are just trying to make the calculation results approach the measurement data,ignoring the relationship among measurement data,the calculated soil parameters,and grounding parameters,which would increase the workload of the *** better balance the distance range of the measurement data and the influence of the calculated horizontally layered soil on grounding parameters,this paper systematically studies the relationship among measured apparent soil resistivity,calculated horizontally layered soil parameters,and grounding *** basic theories of apparent resistivity measurement,soil parameter calculation,and grounding parameter calculation are given,the influence of soil layer thickness on the measured apparent resistivity is studied,and the influence of the calculated soil parameters on the grounding resistance of different grounding models is *** on different scales of grounding grids,the results give a corresponding reference distance range of measured apparent soil ***,this paper can help decrease the workload of soil resistivity measurement during grounding parameters analysis,which has far-reaching engineering significance.

关键词： soil parameters apparent

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STPM: Spatial-Temporal Token Pruning and Merging for Complex Activity Recognition

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IEEE Transactions on Circuits and Systems for Video technology 2024年第6期35卷 5407-5418页

作者： Su, Yumeng Zhang, Jiachao Yan, Rui Li, Pengpeng Xie, Guosen Shu, Xiangbo Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing210094 China Nanjing Institute of Technology Artificial Intelligence Industrial Technology Research Institute Nanjing211167 China Nanjing University Department of Computer Science and Technology Nanjing210023 China

Lightweight video representation techniques have advanced significantly for simple activity recognition, but they still encounter several issues when applied to complex activity recognition: (i) The presence of numerous individuals and varying spatial positions makes it difficult for traditional token pruning methods to maintain accuracy. (ii) Simply discarding entire frames may result in the loss of crucial clues. (iii) To maintain parallel computing, applying the same pruning rate to every frame leads to significant redundancy in frames with low information content. To this end, we propose a lightweight and novel Spatial-Temporal Token Pruning and Merging (STPM) framework, specifically designed for complex action videos where human actors occupy a small spatial resolution within video frames. Our framework considers two critical factors: semantic importance and spatial-temporal redundancy, to further reduce overhead. For semantic importance, STPM captures class-specific attention scores by learning multiple class tokens within the transformer to guide token pruning. For spatial-temporal redundancy, STPM employs an anchor graph and temporal attention to perform spatial and temporal token merging, preserving appearance and temporal cues while eliminating semantic duplication and redundancy. We conduct extensive experiments on JRDB-PAR primarily using recently introduced video transformer backbones, e.g., MViT and ViT. Our framework achieves similar results while requiring 40% less computation. © 1991-2012 IEEE.

关键词： Economic and social effects

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Identify information sources with different start times in complex networks based on sparse observers

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Chinese Physics B 2024年第11期33卷 467-479页

作者： Yuan-Zhang Deng Zhao-Long Hu Feilong Lin Chang-Bing Tang Hui Wang Yi-Zhen Huang School of Computer Science and Technology Zhejiang Normal UniversityJinhua 321004China School of Physics and Electronic Information Engineering Zhejiang Normal UniversityJinhua 321004China School of Information Engineering Jinhua PolytechnicJinhua 321016China

The dissemination of information across various locations is an ubiquitous occurrence,however,prevalent methodologies for multi-source identification frequently overlook the fact that sources may initiate dissemination at distinct initial *** there are many research results of multi-source identification,the challenge of locating sources with varying initiation times using a limited subset of observational nodes remains *** this study,we provide the backward spread tree theorem and source centrality theorem,and develop a backward spread centrality algorithm to identify all the information sources that trigger the spread at different start *** proposed algorithm does not require prior knowledge of the number of sources,however,it can estimate both the initial spread moment and the spread *** core concept of this algorithm involves inferring suspected sources through source centrality theorem and locating the source from the suspected sources with linear *** experiments from synthetic and real network simulation corroborate the superiority of our method in terms of both efficacy and ***,we find that our method maintains robustness irrespective of the number of sources and the average degree of *** with classical and state-of-the art source identification methods,our method generally improves the AUROC value by 0.1 to 0.2.

关键词： complex networks information spread source identification backward spread centricity

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Trust management in online computing environment: a complete review

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Journal of Ambient Intelligence and Humanized Computing 2024年第1期15卷 491-545页

作者： Singh, Ashish Chatterjee, Kakali School of Computer Engineering KIIT Deemed to be University Odisha Bhubaneswar751024 India Department of Computer Science and Engineering National Institute of Technology Bihar Patna800005 India

Nowadays, trust management plays a significant role in different applications like commercial applications, Internet of Things (IoT) based applications, social networking applications, cloud computing-based applications, sensor networks, online services, and many more. Thus, it is an important research area for industry and engineering research communities. The concept of trust is mainly derived from long-term sociological and psychological human behaviour. It is used for decision-making purposes in different contexts and perspectives. Many growing research studies address the development of trust computation models using different approaches in different areas, such as cloud computing, P2P networks, online social network, etc. Still, most of the prior work does not provide a comprehensive systematic review of different trust management systems nor provide sufficient details about the computation process. In this paper, we have discussed a systematic review of the existing trust management systems by indicating the limitation of previous works. A systematic review started with research question identification, followed by searching and filtration of relevant works, and ended with a comparison and final report. A detailed comparative study of trust computational models will help understand the security and privacy aspects of trust. This survey provides a detailed study of each trust taxonomy and computation model in different online computing environments. The survey result finds several trust computation techniques. The results also say that trust in the online computing environment provides greater security and protection against several threats and attacks. Despite the potential benefits of trust, the results also included challenges and open research issues that are still opportunities for new researchers. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023.

关键词： Cloud computing

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Review the Deep Learning Strategies for Enhancing the Security of Body Area Networks Against Adversarial Attack

Review the Deep Learning Strategies for Enhancing the Securi...

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2024 International Conference on Advances in Computing Research on science engineering and technology, ACROSET 2024

作者： Nagdiya, Jagrati Goyal, Rajeev Amity School of Engineering and Technology Computer Science and Engineering Gwalior India

ISBN: (纸本)9798350388800

Thereis an urgent need for strong security measures to protect Body Area Networks (BANs) from malicious threats, as their use in health monitoring and telemedicine continues to grow. To improve BAN security, this research presents a new method that makes use of deep learning approaches. Data breaches, unauthorised access, and other cyberattacks that target the particular weaknesses of BANs are among the many cybersecurity threats that our approach uses sophisticated neural network designs to detect and mitigate. Typical network traffic events and simulated adversarial attacks are both included in the extensive dataset that our deep learning model is trained on. The model can then learn to identify suspicious behaviour by observing complicated patterns and outliers. The design of the device is such that it can run smoothly on very little power while still achieving excellent efficiency. © 2024 IEEE.

关键词： Adversarial machine learning

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A Novel Fuzzy Marine White Shark Optimization Based Efficient Routing and Enhancing Network Lifetime in MANET

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WIRELESS PERSONAL COMMUNICATIONS 2023年第4期132卷 2363-2385页

作者： Devi, K. Lalitha Bhat, C. Rohith Devi, K. Lalitha KSR College of Engineering Tiruchengode Namakkal India Department of Computer Science and Engineering Saveetha School of Engineering SIMATS Chennai Tamil Nadu 602105 India Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India

A mobile ad hoc network (MANET) is an independent wireless temporary network established by employing a set of mobile nodes (i.e. laptops, smartphones, iPods, etc.) appropriate for the environment in which the network infrastructures are not fixed. The most common problems faced by MANET are energy efficiency, high energy consumption, low network lifetime as well as high traffic overhead which create an impact on overall network topology. Hence, it is necessary to provide an energy-effective CH election to take steps against such issues. Therefore, this paper proposes a novel model to enhance the network lifetime and energy efficiency by performing a routing strategy in MANET. In this paper, an optimal CH is selected by proposing a novel Fuzzy Marine White Shark optimization (FMWSO) algorithm which is obtained by integrating fuzzy operation with two optimization algorithms namely the marine predator algorithm and white shark optimizer. The proposed approach comprises three diverse stages namely Generation of data, Cluster Generation and CH selection. A novel FMWSO algorithm is proposed in such a way to determine the CH selection in MANET thereby enhancing the network topology, network lifetime and minimizing the overhead rate, and energy consumption. Finally, the performance of the proposed FMWSO approach is compared with various other existing techniques to determine the effectiveness of the system. The proposed FMWSO approach consumes minimum energy of 0.62 mJ which is lower than other approaches.

关键词： MANET Cluster head Fuzzy Marine White Shark Cluster generation Network lifetime Energy consumption

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Proactive Caching at the Wireless Edge:A Novel Predictive User Popularity-Aware Approach

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computer Modeling in engineering & sciences 2024年第8期140卷 1997-2017页

作者： Yunye Wan Peng Chen Yunni Xia Yong Ma Dongge Zhu Xu Wang Hui Liu Weiling Li Xianhua Niu Lei Xu Yumin Dong College of Computer Science Chongqing UniversityChongqing400044China School of Computer and Software Engineering Xihua UniversityChengdu610039China School of Computer and Information Engineering Jiangxi Normal UniversityNanchang330022China Electric Power Research Institute of State Grid Ningxia Electric Power Co. Ltd.Yinchuan750002China College of Mechanical and Vehicle Engineering Chongqing UniversityChongqing400030China School of Computer Science and Technology Beijing Institute of TechnologyBeijing100083China School of Computer Science and Technology Dongguan University of TechnologyDongguan523808China School of Emergency Management Xihua UniversityChengdu610039China College of Computer and Information Science Chongqing Normal UniversityChongqing401331China

Mobile Edge Computing(MEC)is a promising technology that provides on-demand computing and efficient storage services as close to end users as *** an MEC environment,servers are deployed closer to mobile terminals to exploit storage infrastructure,improve content delivery efficiency,and enhance user ***,due to the limited capacity of edge servers,it remains a significant challenge to meet the changing,time-varying,and customized needs for highly diversified content of ***,techniques for caching content at the edge are becoming popular for addressing the above *** is capable of filling the communication gap between the users and content providers while relieving pressure on remote cloud ***,existing static caching strategies are still inefficient in handling the dynamics of the time-varying popularity of content and meeting users’demands for highly diversified entity *** address this challenge,we introduce a novel method for content caching over MEC,i.e.,*** synthesizes a content popularity prediction model,which takes users’stay time and their request traces as inputs,and a deep reinforcement learning model for yielding dynamic caching *** results demonstrate that PRIME,when tested upon the MovieLens 1M dataset for user request patterns and the Shanghai Telecom dataset for user mobility,outperforms its peers in terms of cache hit rates,transmission latency,and system cost.

关键词： Mobile edge computing content caching system average cost deep reinforcement learning collaborative mechanism

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A Real Time Prediction Model for Round Winners of Counter Strike:Global Offensive 3

A Real Time Prediction Model for Round Winners of Counter St...

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3rd International Conference on Sentiment Analysis and Deep Learning, ICSADL 2024

作者： Paul, Rosebell Sajeer, Rihan Vaishnav, M.V. Abraham, Savio Vinu Sahajan, Shreya SCMS School of Engineering and Technology Department of Computer Science and Engineering India

ISBN: (纸本)9798350396157

This research study aims to create a full time winner predictor program for Counter-Strike Global Offensive tournaments that can predict the round winner of the game being spectated. The algorithm creates accurate predictions of the round winner. The data required for the prediction has to be extracted from the game servers. The data is collected from the game servers using an API. The prediction can be viewed live by the user with the help of a GUI. The project can provide CS:GO enthusiasts and bettors with real-time insights and predictions for round winners in competitive matches. System aims to enhance the user's understanding of match dynamics and support informed decision making. © 2024 IEEE.

关键词： Forecasting

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Recommendation algorithm for agricultural and sideline products on e-commerce platforms based on deep learning

Recommendation algorithm for agricultural and sideline produ...

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2024 International Conference on Artificial Intelligence, Deep Learning and Neural Networks, AIDLNN 2024

作者： Chen, Lisi School of Computer Science and Engineering Guangzhou Institute of Science and Technology China

ISBN: (纸本)9798331520816

Aiming at the problem of low accuracy in e-commerce platform recommendation of agricultural and sideline products, an agricultural and sideline product recommendation algorithm based on deep learning was studied. Fully analyze the problems existing in the process of recommending agricultural and sideline products, study the mechanism of item-based collaborative filtering algorithm, and combine the document topic and matrix decomposition hybrid algorithm. Highlighting the advantages of both, a topic weighted fusion collaborative filtering algorithm was formed. Through experiments, this algorithm can effectively improve the recommendation effect of agricultural and sideline products on e-commerce platforms. Compared with the simple item collaborative filtering algorithm, the algorithm studied in this study can effectively improve the accuracy of recommended targets by about 5%, and also has a 2% improvement in the diversity of recommended targets. In terms of accuracy of prediction results, through experimental comparison, the root mean square error of this algorithm is also lower than other comparative algorithms, which proves the advantages of this algorithm. © 2024 IEEE.

关键词： Agricultural and sideline products E-commerce platform New media Recommendation algorithm

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Prevention of Attacks in Vehicular Adhoc Networks

Prevention of Attacks in Vehicular Adhoc Networks

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2024 IEEE International Students' Conference on Electrical, Electronics and computer science, SCEECS 2024

作者： Anjali, Thuvva Goyal, Rajeev G.n, Balaji Amity University Computer Science and Engineering Amity School of Engineering and Technology Gwalior India Vellore Institute of Technology Computer Science and Engineering School of Cse Vellore India

ISBN: (纸本)9798350348460

Over the past years, numerous methods have been developed to identify anomalies in traditional VANETs networks. A survey of VANET anomaly detection and mitigation methods is presented in this analysis. This survey looks into a variety of VANET research projects, attack types, anomaly detection methods, and mitigation strategies. VANETs provide wireless communication among vehicles as well as between vehicles and infrastructure. Its major objective is to improve road safety, comfort, and convenience. VANET varies from ad hoc networks due to its specific features. Several methods for identifying anomalies in conventional VANET networks have been developed over time. This work examines VANET anomaly detection and prevention technologies. Various VANET research studies, different types of attacks, anomaly detection, and VANET protection measures. The current investigation seeks to address various sorts of vehicle network assaults as well as existing security methods for coping with these attacks. This work will help academics understand the taxonomy of automotive network security vulnerabilities, which can subsequently be researched further to develop unique solutions. © 2024 IEEE.

关键词： Identity Based Signature Intelligent Transport System Intrusion Detection System Vehicle to Vehicle Vehicular Adhoc Network

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