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An Early Warning Model of Telecommunication Network Fraud Based on User Portrait

computers, Materials & Continua 2023年第4期75卷 1561-1576页

作者： Wen Deng Guangjun Liang Chenfei Yu Kefan Yao Chengrui Wang Xuan Zhang Department of Computer Information and Cyber Security Jiangsu Police InstituteNanjingChina Engineering Research Center of Electronic Data Forensics Analysis NanjingChina Department of Public Security of Jiangsu Province Key Laboratory of Digital ForensicsNanjingChina

With the frequent occurrence of telecommunications and networkfraud crimes in recent years, new frauds have emerged one after another whichhas caused huge losses to the people. However, due to the lack of an effectivepreventive mechanism, the police are often in a passive position. Usingtechnologies such as web crawlers, feature engineering, deep learning, andartificial intelligence, this paper proposes a user portrait fraudwarning schemebased on Weibo public data. First, we perform preliminary screening andcleaning based on the keyword “defrauded” to obtain valid fraudulent userIdentity Documents (IDs). The basic information and account information ofthese users is user-labeled to achieve the purpose of distinguishing the typesof fraud. Secondly, through feature engineering technologies such as avatarrecognition, Artificial Intelligence (AI) sentiment analysis, data screening,and follower blogger type analysis, these pictures and texts will be abstractedinto user preferences and personality characteristics which integrate multidimensionalinformation to build user portraits. Third, deep neural networktraining is performed on the cube. 80% percent of the data is predicted basedon the N-way K-shot problem and used to train the model, and the remaining20% is used for model accuracy evaluation. Experiments have shown thatFew-short learning has higher accuracy compared with Long Short TermMemory (LSTM), Recurrent Neural Networks (RNN) and ConvolutionalNeural Network (CNN). On this basis, this paper develops a WeChat smallprogram for early warning of telecommunications network fraud based onuser portraits. When the user enters some personal information on the frontend, the back-end database can perform correlation analysis by itself, so as tomatch the most likely fraud types and give relevant early warning *** fraud warning model is highly scaleable. The data of other Applications(APPs) can be extended to further improve the efficiency of anti-fraud whichhas e

关键词： Crawler user portrait feature engineering deep learning small program development

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Evolving Safety Protocols: Deep Learning-Enabled Detection of Personal Protective Equipment 1

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4th International Conference on computer vision, High-Performance Computing, Smart Devices, and Networks, CHSN 2023

作者： Alahmid, Mustafa Bhimani, Kishankumar Saradva, Khushbu Ghildiyal, Sushil Saeedi, Sayed Aryan Ali, Saraa Yan, Han Filippov, Evgeny Faculty of Computer Science and Technology Saint Petersburg Electrotechnical University "LETI" Saint Petersburg Russia Laboratory on AI for Computational Biology Faculty of Computer Science HSE University Moscow Russia Department of Computer Science and Engineering Indian Institute of Technology Ropar Punjab India Laboratory of Methods for Big Data Analysis Faculty of Computer Science HSE University Moscow Russia Deggendorf Institute of Technology Bavaria Germany

ISBN: (数字)9789819777945

ISBN: (纸本)9789819777938

To give shift in safety protocols, we have employed advanced deep learning algorithms and frameworks (Shrestha and Mahmood in IEEE Access 7:53,040–53,065, 2019 [25]) to construct an innovative AI model. The designed model detects the usage of personal protective equipment (PPE) (Personal protective equipment. Geneva: World Health Organization, 2020 [18]) by workers in high-risk industries such as construction and manufacturing. We have used Google’s TensorFlow object detection API (Sai and Sasikala in Object detection and count of objects in image using tensor flow object detection API, pp 542–546, 2019 [22]) to modify and train a model for dual purposes: PPE detection and face recognition. The state-of-the-art of this research is to substantially enhance safety compliance by addressing the prevalent issue of PPE non-compliance. To emphasis this, we have developed a pioneering software prototype that synergizes PPE detection with a face recognition-based clock-in system. This prototype demonstrates impressive object detection metrics with a mean average precision (mAP) of 0.9 for vests and 0.85 for helmets. Moreover, it exhibited efficient face recognition with a successful threshold range of 17–20%. The implementation of AI in our system promises significant enhancements to worker safety, while concurrently reducing the financial burden associated with big hazards and accidents. Beyond the development and performance of the system, this paper provides a thorough exploration of the encountered challenges, potential real-world applications (particularly in employee monitoring and clock-in systems), and the future implications of this study on research and practical applications in the field of AI-integrated safety compliance. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Software prototyping

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ISAS: AAA Protocol-based Handover and Improved Security Methodology through the Integration Security Authentication System Constitute

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IEIE Transactions on Smart Processing and Computing 2023年第4期12卷 358-367页

作者： Park, Byungjoo Kim, Jaehwan McNair, Janise Department of Multimedia Engineering Hannam University Daeduk-gu Daejeon Korea Republic of Mobile and Multimedia Communication Laboratory Hannam University Daeduk-gu Daejeon Korea Republic of Department of Electrical and Computer Engineering University of Florida GainesvilleFL United States

Security risks were raised during the handover of Mobile Nodes (MNs) in the Mobile Internet Protocol version 6 (MIPv6), which were demonstrated in the instigation of route optimization between the MN and its Correspondent Node (CN). The return routability procedure provides a basic security measure for the communication between the MN and CN, but this security scheme still suffers from various weaknesses and loopholes. Thus, various methodologies in securing the handovers for MIPv6 were incorporated in line with the security agreement with authentication, authorization, and accounting (AAA) infrastructure. This paper proposes an establishment of the Integration Security Authentication System based on the AAA infrastructure to maintain the security level of the fast handover mobility management to provide an improved Quality of Service. Copyrights © 2023 The Institute of Electronics and Information Engineers.

关键词： Quality of service

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GFlowNet Training by Policy Gradients 41

GFlowNet Training by Policy Gradients

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41st International Conference on Machine Learning, ICML 2024

作者： Niu, Puhua Wu, Shili Fan, Mingzhou Qian, Xiaoning Department of Electrical and Computer Engineering Texas A&M University College StationTX United States Department of Computer Science and Engineering Texas A&M University College StationTX United States Computational Science Intiative Brookhaven National Laboratory UptonNY United States

Generative Flow Networks (GFlowNets) have been shown effective to generate combinatorial objects with desired properties. We here propose a new GFlowNet training framework, with policy-dependent rewards, that bridges keeping flow balance of GFlowNets to optimizing the expected accumulated reward in traditional Reinforcement-Learning (RL). This enables the derivation of new policy-based GFlowNet training methods, in contrast to existing ones resembling value-based RL. It is known that the design of backward policies in GFlowNet training affects efficiency. We further develop a coupled training strategy that jointly solves GFlowNet forward policy training and backward policy design. Performance analysis is provided with a theoretical guarantee of our policy-based GFlowNet training. Experiments on both simulated and real-world datasets verify that our policy-based strategies provide advanced RL perspectives for robust gradient estimation to improve GFlowNet performance. Our code is available at: ***/niupuhua1234/GFN-PG. Copyright 2024 by the author(s)

关键词： Generative adversarial networks

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Energy Stress of Non-Gapped Line Arresters Due to Lightning Strikes to a 150 kV Line: Concentrated Tower Grounding System Modeling Effects 24

Energy Stress of Non-Gapped Line Arresters Due to Lightning ...

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24th EEEIC International Conference on Environment and Electrical engineering and 8th I and CPS Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2024

作者： Datsios, Zacharias G. Patsalis, Diamantis G. Stracqualursi, Erika Araneo, Rodolfo Mikropoulos, Pantelis N. Tsovilis, Thomas E. School of Electrical & Computer Engineering Aristotle University of Thessaloniki High Voltage Laboratory Thessaloniki Greece University of Rome 'Sapienza' Department of Astronautical Electrical and Energy Engineering Rome Italy

ISBN: (纸本)9798350355185

This study investigates the impact of the frequency-and current-dependent behavior of concentrated tower grounding systems on the computed fast-front overvoltages across overhead transmission line (OHTL) insulation, the current flowing through line surge arresters (LSAs), and the energy absorbed by LSAs. This investigation is performed via ATP-EMTP simulations of a 150 kV double-circuit OHTL equipped with non-gapped line arresters (NGLAs). Two NGLA installation configurations are studied: 3 and 6 NGLAs at each tower. Four models are used for the concentrated tower grounding systems: (1) a resistor with a fixed resistance (ground resistance of towers), (2) frequency-dependent (FD) response with fixed and (3) FD soil electrical properties, and (4) the CIGRE model for soil ionization. A hybrid code was used to produce the FD grounding system responses. The tower ground resistance was a parameter and low-frequency soil resistivity was varied accordingly. The energy stressing NGLAs decreases notably when soil ionization is included in simulations. The adoption of the tower ground resistance (fixed value) in simulations yields conservative results in terms of NGLA energy stress. © 2024 IEEE.

关键词： Overhead lines

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SmokerViT: A Transformer-Based Method for Smoker Recognition

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computers, Materials & Continua 2023年第10期77卷 403-424页

作者： Ali Khan Somaiya Khan Bilal Hassan Rizwan Khan Zhonglong Zheng College of Mathematics and Computer Science Zhejiang Normal UniversityJinhua321004China School of Electronics Engineering Beijing University of Posts and TelecommunicationsBeijing100876China Department of Electrical Engineering and Computer Science Khalifa University of Science and TechnologyAbu Dhabi127788United Arab Emirates Key Laboratory of Intelligent Education of Zhejiang Province Zhejiang Normal UniversityJinhua321004China

Smoking has an economic and environmental impact on society due to the toxic substances it *** Neural Networks(CNNs)need help describing low-level features and can miss important ***,accurate smoker detection is vital with minimum false *** answer the issue,the researchers of this paper have turned to a self-attention mechanism inspired by the ViT,which has displayed state-of-the-art performance in the classification *** effectively enforce the smoking prohibition in non-smoking locations,this work presents a vision Transformer-inspired model called SmokerViT for detecting ***,this research utilizes a locally curated dataset of 1120 images evenly distributed among the two classes(Smoking and NotSmoking).Further,this research performs augmentations on the smoker detection dataset to have many images with various representations to overcome the dataset size *** convolutional operations used in most existing works,the proposed SmokerViT model employs a self-attention mechanism in the Transformer block,making it suitable for the smoker classification ***,this work integrates the multi-layer perceptron head block in the SmokerViT model,which contains dense layers with rectified linear activation and linear kernel regularizer with L2 for the recognition *** work presents an exhaustive analysis to prove the efficiency of the proposed SmokerViT *** performance of the proposed SmokerViT performance is evaluated and compared with the existing methods,where it achieves an overall classification accuracy of 97.77%,with 98.21%recall and 97.35%precision,outperforming the state-of-the-art deep learning models,including convolutional neural networks(CNNs)and other vision transformer-based models.

关键词： Smoker recognition SmokerViT deep learning transformer for vision

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Accelerated Primal-Dual Projection Neurodynamic Approach With Time Scaling for Linear and Set Constrained Convex Optimization Problems

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1485-1498页

作者： You Zhao Xing He Mingliang Zhou Tingwen Huang Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information EngineeringSouthwest UniversityChongqing 400715China School of Computer Science Chongqing UniversityChongqing 400044China Department of Mathematics Texas A&M University at QatarDoha 23874Qatar IEEE

The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence *** previous studies in this field have primarily concentrated on unconstrained smooth con-vex optimization *** this paper,on the basis of primal-dual dynamical approach,Nesterov accelerated dynamical approach,projection operator and directional gradient,we present two accelerated primal-dual projection neurodynamic approaches with time scaling to address convex optimization problems with smooth and nonsmooth objective functions subject to linear and set constraints,which consist of a second-order ODE(ordinary differential equation)or differential conclusion system for the primal variables and a first-order ODE for the dual *** satisfying specific conditions for time scaling,we demonstrate that the proposed approaches have a faster conver-gence *** only requires assuming convexity of the objective *** validate the effectiveness of our proposed two accel-erated primal-dual projection neurodynamic approaches through numerical experiments.

关键词： Accelerated projection neurodynamic approach lin-ear and set constraints projection operators smooth and nonsmooth convex optimization time scaling.

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MaDEVIoT: Cyberattacks on EV Charging Can Disrupt Power Grid Operation

MaDEVIoT: Cyberattacks on EV Charging Can Disrupt Power Grid...

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2024 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2024

作者： Acharya, Samrat Khan, Hafiz Anwar Ullah Karri, Ramesh Dvorkin, Yury Pacific Northwest National Laboratory RichlandWA99354 United States New York University Department of Electrical and Computer Engineering BrooklynNY11201 United States Johns Hopkins University Ralph o'Connor Sustainable Energy Institute Department of Electrical and Computer Engineering Department of Civil and Systems Engineering BaltimoreMD21218 United States

ISBN: (纸本)9798350313604

This paper examines the feasibility of demand-side cyberattacks on power grids launched via internet-connected high-power EV Charging Stations (EVCSs). By distorting power grid frequency and voltage, these attacks can trigger system-wide outages. Our case study focuses on Manhattan, New York, and reveals that such attacks will become feasible by 2030 with increased EV adoption. With a single EVCS company dominating Manhattan, compromising a single EVCS server raises serious power grid security concerns. These attacks can overload power lines and trip over-frequency (OF) protection relays, resulting in a power grid blackout. This study serves as a crucial resource for planning authorities and power grid operators involved in the EV charging infrastructure roll-out, highlighting potential cyberthreats to power grids stemming from high-power EVCSs. © 2024 IEEE.

关键词： Relay protection

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A power efficiency enhancements of a multi-bit accelerator for memory prohibitive deep neural networks

IEEE Open Journal of Circuits and Systems

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IEEE Open Journal of Circuits and Systems 2021年 2卷 156-169页

作者： Shivapakash, Suhas Jain, Hardik Hellwich, Olaf Gerfers, Friedel Department of Computer Engineering and Microelectronics Chair of Mixed Signal Circuit Design Technical University of Berlin Berlin10587 Germany Department of Computer Engineering and Microelectronics Computer Vision and Remote Sensing Technical University of Berlin Berlin10587 Germany

Convolutional Neural Networks (CNN) are widely employed in the contemporary artificial intelligence systems. However these models have millions of connections between the layers, that are both memory prohibitive and computationally expensive. Employing these models on an embedded mobile application is resource limited with high power consumption and significant bandwidth requirement to access the data from the off-chip DRAM. Reducing the data movement between the on-chip and off-chip DRAM is the main criteria to achieve high throughput and overall better energy efficiency. Our proposed multi-bit accelerator achieves these goals by employing the truncation of the partial sum (Psum) results of the preceding layer before feeding it into the next layer. We exhibit the architecture by inferencing 32-bits for the first convolution layers and sequentially truncate the bits on the MSB/LSB of integer and fractional part without any further training on the original network. At the last fully connected layer, the top-1 accuracy is maintained with the reduced bit width of 14 and top-5 accuracy upto 10-bit width. The computation engine consists of an systolic array of 1024 processing elements (PE). Large CNNs such as AlexNet, MobileNet, SqueezeNet and EfficientNet were used as benchmark CNN model and Virtex Ultrascale FPGA was used to test the architecture. The proposed truncation scheme has 49% power reduction and resource utilization was reduced by 73.25% for LUTs (Look-up tables), 68.76% for FFs (Flip-Flops), 74.60% for BRAMs (Block RAMs) and 79.425% for Digital Signal Processors (DSPs) when compared with the 32 bits architecture. The design achieves a performance of 223.69 GOPS on a Virtex Ultrascale FPGA, the design has a overall gain of 3.63 × throughput when compared to other prior FPGA accelerators. In addition, the overall power consumption is 4.5 × lower when compared to other prior architectures. The ASIC version of the accelerator was designed in 22nm FDSOI CMOS proc

关键词： Deep neural networks

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Astrometric Observations of NEA 1998 HH49 Using the Daocheng 50 cm Telescope

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Research in Astronomy and Astrophysics 2024年第7期24卷 71-78页

作者： Huan Xu Xiang-Ming Cheng Yi-Gong Zhang Teng-Fei Song Zhen-Jun Zhang Qing-Yu Peng Yunnan Observatories Chinese Academy of SciencesKunming 650216China University of Chinese Academy of Sciences Beijing 100049China Key Laboratory of the Structure and Evolution of Celestial Objects Chinese Academy of SciencesKunming 650216China Engineering Laboratory on Applied Astronomical Technology of Yunnan Kunming 650216China School of Information Engineering Kunming UniversityKunming 650214China School of Computer Science and Information Engineering Anyang Institute of TechnologyAnyang 455000China Department of Computer Science Jinan UniversityGuangzhou 510632China Sino-French Joint Laboratory for Astrometry Dynamics and Space ScienceJinan UniversityGuangzhou 510632China

This study details an astrometric observation campaign of the Near-Earth Asteroid 1998 HH49,conducted with the aim of refining our understanding of its physical *** the 50 cm telescope located at the Wumingshan Mountain in Daocheng,Sichuan,images were obtained over four nights,from 2023 October 19 to October *** observations were processed using Astrometrica software,facilitating the precise determination of the asteroid's *** observational results were compared with the ephemerides from three distinct sources to verify accuracy:the Jet Propulsion laboratory(JPL)Horizons System,the Institut de Mécanique Céleste et de Calcul deséphémérides(IMCCE)Miriade,and the Near-Earth Objects Dynamic Site(NEODyS-2).When compared with the JPL ephemeris,a mean observed-minus-calculated(O-C)result of 0.″07 in the *** and-0.″35 in the *** was ***,the comparison with the IMCCE ephemeris yielded mean O-C results of 0.″08 in the *** and-0.″06 in the *** comparison with the NEODyS-2 ephemeris yielded the mean O-C results of 0.″06 in ***-0.″49 in *** study's findings demonstrate a general consistency between the observed data and the ephemeris predictions,with minor discrepancies observed across the data ***,both the JPL and NEODyS-2 ephemerides show that the residuals in the *** exceed those in the *** disparities may result from atmospheric differential color refraction,ephemeris discrepancies,observational errors,and other ***,it is worth noting that further investigation is required due to the potential influence of additional ***,the Daocheng 50 cm Telescope exhibits the ability to conduct high-precision positional measurements.

关键词： astrometry ephemerides time

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