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共 35127 条记录，以下是4721-4730 订阅

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Insider Threat Detection Using Bidirectional Encoder Representations from Transformers and Optimized AdaBoost Classifier

Insider Threat Detection Using Bidirectional Encoder Represe...

引用

2024 international conference on Circuit, systems and Communication, ICCSC 2024

作者： Kumpf, Katarina Protic, Mihajlo Jovanovic, Luka Cajic, Miroslav Zivkovic, Miodrag Bacanin, Nebojsa Singidunum University Faculty of Informatics and Computing Belgrade Serbia University 'Union Nikola Tesla' Faculty of Information Technology and Engineering Belgrade Serbia

ISBN: (纸本)9798350365306

cybersecurity plays an increasingly vital role in contemporary times, particularly as large companies face escalating threats and substantial losses, with ransomware attacks standing out as one of the more sophisticated forms of intrusion. In such attacks, hackers infiltrate systems, encrypt crucial company data, and then demand a ransom for data decryption or the restoration of control over the system. The application of natural language processing (NLP) emerges as a promising avenue, offering the potential to analyze attack patterns and recognize malicious intentions before actual attempts occur. Given the inherent specificity of each system, fine-tuning AI algorithms with special settings becomes imperative for optimal efficiency. This research delves into the synergy of NLP and robust classification algorithms to detect cyber attacks through website content analysis. Recognizing that classifier performance hinges on the judicious selection of hyperparameters, we explore a modified version of the recently introduced red fox algorithm (RFO). This adaptation is combined with bidirectional encoder representations from transformers to identify malicious intent in email content. The proposed approach undergoes testing on a real-world dataset, with the best models demonstrating an accuracy of 0.975822 suggesting viability. © 2024 ieee.

关键词： Natural language processing systems

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Construction of intelligent Economic Distribution Management System Based on Neural Network Algorithm 3

Construction of Intelligent Economic Distribution Management...

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3rd international conference on Artificial Intelligence and Autonomous Robot systems, AIARS 2024

作者： Xing, Jianping Huang, Ming School of Economics and Management Hunan Open University Changsha China

ISBN: (纸本)9798350376173

Since its inception, neural network technology has achieved rapid development and plays an important role in intelligent economic distribution management. Compared with traditional manual calculation methods, neural network technology has a series of shortcomings such as low efficiency and poor real-time performance. In order to solve these problems, this article uses genetic algorithm to optimize the design of the neural network, and uses MATLAB software as the simulation platform to establish a model to realize the processing and storage functions of input and output data, and at the same time, it can also automatically update and perform decision-making control. By combining neural network technology with other computer technologies, a system simulation model with practical significance can be formed, which can effectively solve some of the shortcomings faced by traditional mathematical theoretical methods. Judging from the test results, the smaller the parallel number of the test data set, the higher the accuracy. The highest accuracy can reach 100%, but the lowest accuracy is also 92%;the platform's running data time is within 6 seconds and the latency of distributing data is within 5 seconds. This enables timely detection of data anomalies and adjustments to prevent failures, thereby improving operational efficiency. © 2024 ieee.

关键词： Data accuracy

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Modeling and control of a Grid-Connected Photovoltaic System

Modeling and Control of a Grid-Connected Photovoltaic System

引用

2023 ieee international conference on Artificial Intelligence and Green Energy, ICAIGE 2023

作者： Hadj Brahim Kechiche, Olfa Bel Mallat, Mariem HSousse4011 Tunisia University of Sousse École Nationale d'Ingenieurs de Sousse LATIS-Laboratory of Advanced Technology and Intelligent Systems Sousse4023 Tunisia Université de Sousse ESSTHSousse HSousse 4011 Tunisia

ISBN: (纸本)9798350325539

The purpose of the work was to modeling and control of a grid connected photovoltaic system. The system consists of photovoltaic panels, voltage inverter with MPPT control, filter, Phase Looked Loop (PLL) and three phase grid. The connection of the inverter to the grid is provided by an inductive filter (R, L). The MPPT control is established using Perturb & Observe (P&O) algorithm. A control strategy based on Lyapunov approach is adopted to obtain a Power Factor (PF) equal to 1 and stabilize the grid-connected PV module system. The simulation results have been performed in MATLAB/Simulink® software and show the performance control of photovoltaic systems in different illumination conditions. © 2023 ieee.

关键词： Solar panels

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An End-to-End Radio Signal Drone Detection and Recognition Algorithm Based on Hard Example Mining

An End-to-End Radio Signal Drone Detection and Recognition A...

引用

2024 ieee international conference on Unmanned systems, ICUS 2024

作者： Wu, Hao Cui, Xiongwen Liu, Peizhou Jiang, Li Department of Electronic Engineering Tsinghua University Beijing China Chengdu SkyDefence Technology Co.Ltd. Chengdu China School of Telecommunication Engineering Xidian University Xi'an China

ISBN: (纸本)9798350384185

Radio signal drone detection and recognition, which is widely applied in radio monitoring and radio countermeasures, is an important direction in the intelligent processing of radio *** paper proposes an end-to-end algorithm for radio signal drone detection and recognition based on hard example ***, a novel backbone network for one-dimensional radio frequency spectrum data is devised by optimizing VGG ***, multi-scale features are employed to address the scale variation in the frequency domain of radio signal ***, a new cross-entropy loss function in conjunction with a negative sample enhancement strategy is proposed to improve the performance on challenging *** results demonstrate that,in comparison to existing methodologies, the proposed approach exhibits superior accuracy and efficiency in detecting and recognizing radio signal targets. © 2024 ieee.

关键词： Frequency domain analysis

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A Parameter Identification Method for Robust Model Predictive control of Virtual Synchronous Generator Based on Two Sliding Mode Observers 3

A Parameter Identification Method for Robust Model Predictiv...

引用

3rd international conference on intelligent Power and systems, ICIPS 2023

作者： Li, Chengshuai Liu, Zhenkun Liu, Hui Henan Jiuyu EPRI Electric Power Technology Co. Ltd. Zhengzhou China College of Electrical and Information Engineering Zhengzhou University of Light Industry Zhengzhou China

ISBN: (纸本)9798350328691

The conventional model predictive control (MPC) method for virtual synchronous generator (VSG) is sensitive to the parameter uncertain changes, resulting in poor voltage control performance. To solve this problem, in this paper, a parameter identification method for robust MPC of VSG based on two sliding mode observers is proposed. In this paper, the theories of the VSG as well as the MPC are first reviewed. Next, based on the mathematical model of the inverter with a LC filter, a current sliding mode observer and a voltage sliding mode observer are designed. Then, by analyzing the parameter sensitivity of the proposed current and voltage sliding mode observer to the filter capacitance and inductance, a capacitance as well as an inductance closed-loop identification method are designed using proportional-integral controller. Eventually, dynamic state experimental studies are con-ducted, which verify the effectiveness of proposed parameter identification method and the parameter identification-based robust MPC method for VSG. ©2023 ieee.

关键词： Model predictive control

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Design and Calibration Method for Built-In Temperature Sensor in Rocker Arm of the Shearer

Design and Calibration Method for Built-In Temperature Senso...

引用

2023 ieee international conference on Unmanned systems, ICUS 2023

作者： Wang, Tianyi Zou, Xiaoyu Pan, Jie Wang, Zhongbin Zhao, Yihui School of Information and Electrical Engineering China University of Mining and Technology Xuzhou China School of Mechanical and Electrical Engineering China University of Mining and Technology Xuzhou China Xi'an Coal Mining Machinery Co. Ltd Xi'an China

ISBN: (纸本)9798350316308

The intelligent coal shearer has introduced unmanned systems and fault diagnosis technology, achieving automation in many tasks, reducing reliance on manpower, and improving work safety. By monitoring and analyzing the operational data of the equipment, the fault diagnosis system can timely detect potential issues and provide corresponding solutions. Accurate and timely preventative maintenance can reduce equipment failures and downtime, thereby improving production efficiency and *** study proposes a built-in sensor system, including design, installation, and communication scheme, for rocker arm of the shearer. The system aims to achieve high-quality data and conduct real-time monitoring for fault diagnosis of rocker arm in a shearer. Unlike traditional vibration sensor which contains intense noise from coal cutting, the designed built-in sensor system enables real-time acquisition of infrared images on the gear tooth surface, thus providing more intuitive information for fault diagnosis. Additionally, a temperature calibration method named Poly-Forest Bagging (PFB) is proposed to solve the nonlinearity and drift problems in temperature measurement using infrared sensors. This algorithm integrates polynomial regression and random forest under the framework of bagging. Through calibration experiments and comparisons with individual models, it demonstrates that the PFB algorithm exhibits superior accuracy, overfitting resistance, and robustness compared to individual models, significantly enhancing sensor precision. © 2023 ieee.

关键词： Fault detection

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VESC-SLAM: A Visual Information Enhanced Multi-Robot Synchronous Collaborative SLAM

VESC-SLAM: A Visual Information Enhanced Multi-Robot Synchro...

引用

2024 ieee international conference on Unmanned systems, ICUS 2024

作者： Yu, Jingyu Cheng, Longbo Zhou, Jianshan Duan, Xuting Ren, Chenghao Chen, Ken State Key Lab of ITS Beihang University Beijing China Zibo Vaucrefly Intel. Tech. Co. Ltd. Zibo China Zhejiang Rongqe Technology Co. Ltd. Zhejiang China

ISBN: (纸本)9798350384185

The collaborative Simultaneous Localization and Mapping (SLAM) system between unmanned aerial vehicles and unmanned ground vehicles in low-light environments faces the problem of poor quality such as blurred and missing visual information. This study constructs a collaborative SLAM system based on deep neural networks to solve this problem. The system significantly i mproves t he p ositioning a ccuracy and map construction quality of unmanned aerial vehicles and unmanned ground vehicles under low-light conditions through the cooperation of the front-end image enhancement module, the collaborative SLAM core processing module, and the intelligent data collaboration and resource optimization module. The system has been validated on the Euroc dataset processed by darkening and its performance has been compared with other robot cluster collaborative SLAM. © 2024 ieee.

关键词： Deep neural networks

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A Novel Transparent Object Detection Approach Based on Segmentation-Depth Reconstruction

A Novel Transparent Object Detection Approach Based on Segme...

引用

2023 ieee international conference on Real-Time Computing and Robotics, RCAR 2023

作者： Li, Zhonglin Luo, Yang Jiang, Yunxiang Zhang, Bi Song, Guoli Zhao, Xingang Zhao, Yiwen Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China Liaoning University Shenyang110036 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics China

ISBN: (纸本)9798350327182

Detecting transparent objects using visual sensors has always been a challenge in the industry. In this paper, a pipeline for depth completion of transparent objects is proposed. The first stage utilizes the input RGB image for semantic segmentation, obtaining the segmentation map of the transparent object. The second stage predicts surface normals and performs boundary detection. The third stage combines the results obtained in the first two stages to complete the depth reconstruction of the transparent object. In addition, in the first stage, a semantic segmentation method for transparent objects is proposed, and boundary optimization is performed on the segmentation results to obtain more refined segmentation results. Experiments demonstrate the effectiveness and precision of the proposed approach. © 2023 ieee.

关键词： Semantic Segmentation

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Development of Unmanned Traffic Technologies in the Subway System 7

Development of Unmanned Traffic Technologies in the Subway S...

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7th international Youth conference on Radio Electronics, Electrical and Power Engineering, REEPE 2025

作者： Aukhadeev, Aver E. Litvinenko, Ruslan S. Le, Thihn K. Sagirov, Shamil I. Vakhitov, Khalil F. Bitsheva, Irina G. Kazan State Power Engineering University Electrotechnical Complexes and Systems Department Kazan Russia Kazan National Research Technological University Department of Physical Education and Sports Kazan Russia

ISBN: (纸本)9798331531836

The article highlights the development challenges of unmanned technologies for public transportation, with the example of the autonomous electric train operation project being implemented in the Kazan Metro. The authors have substantiated the necessity of an integrated approach that requires a system-built program to develop the unmanned transport industry. It is noted that rapidly evolving technologies to manufacture advanced electric rolling stock and build-up of intelligent systems of control and monitoring of traffic parameters demonstrated by leading major specialized enterprises urge the need to develop a new and update the existing regulatory, technical and legal framework in the autonomous unmanned transport industry. Moreover, the potential vulnerability of the information infrastructure of autonomous unmanned transport systems to cyber-attacks requires the development of cutting-edge cyber security technologies. Such technologies should be underpinned by the concept of implementing control systems and ensuring traffic safety based on circuitry solutions and Russian-made components, which will require great responsibility from manufacturers in the matter of import substitution. Another important aspect for the development of the industry is the organization of a system of training qualified specialists based on specialized institutions of secondary and higher professional education. © 2025 ieee.

关键词： Electric railroads

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Architecture and Key Technologies of Parallel Dispatching System for Railway Technical Operation Stations

Architecture and Key Technologies of Parallel Dispatching Sy...

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2023 international Annual conference on Complex systems and intelligent Science, CSIS-IAC 2023

作者： Xiong, Gang Yang, Donghu Xu, Wei Li, Runmei Chen, Shichao Song, Bing Dong, Xisong Zhu, Fenghua Institute of Automation Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing100190 China Institute of Automation Chinese Academy of Sciences Beijing Engineering Research Center of Intelligent Systems and Technology Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Signal and Communication Research Institute China Academy of Railway Science Corporation Limited Beijing100081 China The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100081 China Beijing Huairou Academy of Parallel Sensing Beijing101400 China Chinese Academy of Sciences Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Dongguan523808 China

ISBN: (纸本)9798350309003

A railroad technical operation station is an extensive and complex operation system and a variety of random disturbing factors further increase the complexity of its command and dispatching. To enhance the railroad technical operation stations' intelligence, and integration level, and enhance its dispatching management ability of complex operation plans, based on the ACP approach, this paper designs the parallel dispatching system (PDS) architecture, and describes its key technologies including the artificial dispatching system (ADS), computing experiments, parallel execution, etc. On the basis of the artificial dispatching system, computational experiments can optimize various types of technical operations and the overall operational process, to achieve parallel execution between the actual dispatching system and ADS. PDS can provide more efficient and intelligent command and dispatching solutions for railroad technical work stations, and promote the development of the railroad transportation industry in the direction of higher quality and efficiency. © 2023 ieee.

关键词： Railroads

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