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检索条件"任意字段=Scientific Conference on Mechatronics Engineering and Computer Science"

共 38324 条记录，以下是981-990 订阅

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Research on Optimization Strategy of Web cache replacement algorithm 5

Research on Optimization Strategy of Web cache replacement a...

引用

5th International conference on mechatronics and computer Technology engineering, MCTE 2022

作者： Yang, Cheng Zhou, Tianhong Qu, Chengzhang Department of Information Engineering Wuhan Business University Wuhan China

ISBN: (纸本)9781510661073

Cache technology has greatly improved the efficiency of data query response in distributed systems, especially in e-commerce and other fields. However, with the expansion of the user scale of the system, it is difficult to meet the requirements of fast query response by relying on a single cache structure. In the highly concurrent request environment, the efficiency of the Web cache replacement algorithm will affect the user's query experience directly. Based on the existing classical cache replacement algorithm, this paper proposes an optimization strategy for the cache weight replacement algorithm. It optimizes the existing cache weight replacement algorithm and partitions the cache space to improve the hit rate of the cache replacement algorithm. © 2022 SPIE.

关键词： Efficiency

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Brain-computer Interface Rehabilitation System Design Based on Motor Imagery 6

Brain-Computer Interface Rehabilitation System Design Based ...

引用

6th IEEE Information Technology and mechatronics engineering conference, ITOEC 2022

作者： Wei, Quanpeng Wei, Airong Peng, Fulai Zhang, Xikun Wang, Xingwei Wang, Zhiyong Li, Peiran School of Control Science and Engineering Shandong University Jinan China Shandong Institute of Advanced Technology Chinese Academy of Sciences Jinan China

ISBN: (纸本)9781665431859

To improve the rehabilitation efficacy for stroke patient, a brain-computer interface (BCI) rehabilitation system based on motor imagery (MI) is investigated in this paper. Firstly, the Electroencephalogram (EEG) signals are preprocessed by Laplacian spatial filter and Butterworth band pass filter with cutoff frequency of 8Hz24Hz to enhance the interesting components of the EEG signals. Then, the logarithmic band power (LBP) features are extracted and the motion intentions classification model is established based on linear discriminant analysis (LDA) algorithm. Finally, the correct motion intentions recognition results are converted to executive command of our designed rehabilitation hand. The motion imagery dataset from OpenVibe is used to validate our system. Results show that the rehabilitation hand is driven to effectively actuate the hand to perform the pre-set actions according to the MI recognition results. © 2022 IEEE.

关键词： Cutoff frequency

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Quantile Methods for Assessing Investment Risk in Cryptocurrencies 19

Quantile Methods for Assessing Investment Risk in Cryptocurr...

引用

19th IEEE International conference on computer science and Information Technologies, CSIT 2024

作者： Hrytsiuk, Petro Omelianiuk, Andrii National University of Water and Environmental Engineering Department of Computer Technology and Economic Cybernetic Rivne Ukraine

ISBN: (纸本)9798331542627

In this study, the daily returns of the ten largest-cap cryptocurrencies have been analyzed. It is shown that the returns of cryptocurrencies most often follow a Laplace distribution. Analytical expressions have been obtained for assessing the investment risk of cryptocurrencies using the VaR method. Numerical risk estimates have been calculated using VaR and CVaR methods. Our analysis indicates that the Conditional Value at Risk (CVaR) is 40-45% higher than the Value at Risk (VaR), suggesting that the VaR method underestimates potential losses. © 2024 IEEE.

关键词： Risk assessment

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GPMN: Human Pose Explicit Modeling Network based on Graph Model 7

GPMN: Human Pose Explicit Modeling Network based on Graph Mo...

引用

7th IEEE Information Technology and mechatronics engineering conference, ITOEC 2023

作者： Zhang, Yuru Zhao, Jiayuan Su, Xiaodong Xu, Hongyan Harbin University of Commerce College of Computer and Information Engineering Harbin China Heilongjiang Provincial Key Laboratory of Electronic Commerce and Information Processing Harbin China

ISBN: (纸本)9798350334197

The human pose estimation task requires the use of visual cues and anatomical relationships between joints to locate key points. Due to the structural dependencies between human joints, it is difficult to model the dependencies between joints with a convolutional neural network-based approach. In this paper, we propose a graph pose modeling network (GPMN) based on a graph model, which constructs a structural graph model between joints and then uses a convolutional neural network to explicitly model the dependencies between joints. Specifically, this method extracts features through a backbone network and uses a graph model to obtain proximity joint dependencies. At the same time, a cross-cross-attention mechanism is used to obtain the distant joint dependencies for reinforcing challenging key points. To solve the problem that the challenging key points of the network are weakened during the training process, this paper uses a focal loss function to make the network focus more on the challenging key points, such as knees and ankles. Under the same experimental conditions, HRNet, the highest accuracy feature extraction network, and ResNet, the classical feature extraction network, are used as the backbone network. The accuracy of the algorithm with HRNet network as the backbone is improved by 2.6% compared with the original network. © 2023 IEEE.

关键词： Extraction

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Malicious PE File Detection Using Machine Learning: An Analysis of Header Features

Malicious PE File Detection Using Machine Learning: An Analy...

引用

2024 IEEE International conference on Computing, Semiconductor, mechatronics, Intelligent Systems and Communications, COSMIC 2024

作者： Shyam Kumar, S. Shetty, Jyothi Department of Cyber Security Nitte574 110 India Department of Computer Science and Engineering Nitte574 110 India

ISBN: (纸本)9798331517892

Portable Executable (PE) files serve as the foundation of the Windows operating system, containing executable code, object code, and Dynamic Link Libraries (DLLs). Their importance lies in their capacity to execute tasks and run programs within the Windows environment, rendering them essential to software execution. Comprehension of PE files is crucial in cybersecurity due to their prevalence and potential for harboring malicious software. Analysis of PE files enables researchers and analysts to uncover insights into their structure, behavior, and dependencies, which is essential for detecting and categorizing potential threats. PE file analysis provides critical information about a program's characteristics, facilitating the identification of indicators of compromise and potential security risks. Through examination of PE headers, sections, and attributes, analysts can gain insights into the file's functionality, dependencies, and potential security vulnerabilities. This knowledge equips cybersecurity professionals to develop robust detection and mitigation strategies, safeguarding systems and networks against cyber threats. In this paper, we examine the intricate details of PE files, utilizing tools such as PE-bear, PEinfo, CFF Explorer, and PEStudio to conduct comprehensive analysis. Our study employs machine learning techniques, specifically the Random Forest algorithm, to enhance malware detection capabilities. By preprocessing and augmenting the dataset with new executable files, we aim to enhance the efficacy of our analysis and provide valuable insights for cybersecurity research and defense strategies. © 2024 IEEE.

关键词： Cybersecurity

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Career Craft AI: A Personalized Resume Analysis and Job Recommendations System 1

Career Craft AI: A Personalized Resume Analysis and Job Reco...

引用

1st International conference on Innovative Sustainable Technologies for Energy, mechatronics and Smart Systems, ISTEMS 2024

作者： Rajput, Akshay Dubey, Akanksha Thakur, Rishabh Singh, Deepak Singh, Upendra Pratap Graphic Era Deeemed to Be University Dept. of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350384246

In the today's era of endless career options, the challenge to get that one ideal job that aligns best with individual's skills and interests is absent due to lack of personalized recommendations and lack of guidance about resume making it becomes challenging to find best jobs and get shortlisted for the hiring process of a company. This paper introduces a novel approach to address these challenges by the development of a Career Crafter AI - A Resume analysis and Job Recommendation System. Knowing the limitations of existing recommendations systems that primarily rely on individuals provided interests, our system, implemented on the e-learning platform for skill building, Level Up, goes beyond the traditional approach of recommendation system. Using Vector Machine algorithm and the cosine similarity our system classifies the users based on their skills and profile mentioned on the platform and Natural Language Processing enables to provide the tips and recommendation to improve our resume and get the insights about the user for better recommendation. The recommendation engine utilizes these insights to provide accurate and best fit jobs to the users and as well as provide potential candidate for job roles to the recruiters This research paper aims to provide a one stop destination for learners to improve their resume for getting an edge during shortlisting and interviews and to transform and optimize the job recommendation systems by offering a more personalized and effective approach, empowering individuals to navigate their career paths with confidence and precision. © 2024 IEEE.

关键词： Support vector machines

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Development of a Current-Position Control Strategy for Motion Systems Utilizing Nonlinear Reluctance Actuators 63

Development of a Current-Position Control Strategy for Motio...

引用

63rd IEEE conference on Decision and Control, CDC 2024

作者： Al Saaideh, Mohammad Al-Rawashdeh, Yazan M. Alatawneh, Natheer Aljanaideh, Khaled Boker, Almuatazbellah Al Janaideh, Mohammad Memorial University St. John's Department of Electrical and Computer Engineering NLA1B 3X5 Canada University of Jordan Electrical Engineering Department at Al-Zaytoonah 130 Amman 11733 Jordan Memorial University St. John's Department of Mechanical and Mechatronics Engineering NLA1B 3X5 Canada Jordan University of Science and Technology Faculty of Engineering Department of Aeronautical Engineering Irbid22110 Jordan Virginia Tech Department of Electrical and Computer Engineering BlacksburgVA24060 United States University of Guelph School of Engineering GuelphON N1G 2W1 Canada

ISBN: (纸本)9798350316339

Reluctance actuators (RA) can replace the current Lorentz actuators in the next generation of positioning and scanning motion systems, such as the wafer stage in lithography machines. However, the nonlinear output force characteristic and the gap dependency of the RA are the main challenges in using the RA to drive motion systems. In this paper, we design a two-loop control approach for a reluctance actuator motion system (RAMS) to achieve tracking performance for a desired motion profile. First, the current control loop linearizes the RA under different conditions. Next, the position control loop is designed using a PID control based on an extended-high gain observer to achieve a desired motion profile considering unknown dynamics in the system. The simulation results show the efficiency of the proposed current control in linearizing the dynamic behavior under different desired forces and nominal air gaps and achieving a frequency response similar to the spring-mass-damper system. Moreover, the position control can achieve different long-stroke and short-stroke motion profiles with different amplitudes and ranges of motion. © 2024 IEEE.

关键词： Proportional control systems

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Collaborative filtering recommendation algorithm combining tag information and rating difference 6

Collaborative filtering recommendation algorithm combining t...

引用

6th IEEE Information Technology and mechatronics engineering conference, ITOEC 2022

作者： Ji, Lu Yu, Wanjun Chen, Ying School of Computer Science and Information Engineering Shanghai Institute of Technology Shanghai China

ISBN: (纸本)9781665431859

Aiming at the problem of the low calculation accuracy of similarity between users in the traditional collaborative filtering recommendation algorithm, a collaborative filtering recommendation algorithm combining tag information and rating difference is proposed. Firstly, the algorithm introduces time weights to describe the dynamic change of users' interest, and defines users' preference values for tags according to tag information so as to calculate the interest similarity between users. Secondly, considering the influence of rating difference between users on recommendation effect, the algorithm uses the mean ratings as the benchmarks to calculate the rating difference between them. Finally, the algorithm comprehensively considers interest similarity and rating difference between users, generates target user's nearest neighbors and makes recommendations. The experimental results based on movieLens dataset show that the proposed algorithm effectively improves the calculation accuracy of similarity between users and the recommendation performance. © 2022 IEEE.

关键词： Collaborative filtering

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A P300 Based Brain-computer Interface LabVIEW Instrument for Controlling an Experimental Prototype of Juices Vending Machine Using the Unicorn EEG Headset 17th

A P300 Based Brain-Computer Interface LabVIEW Instrument for...

引用

17th International conference on Interdisciplinarity in engineering, INTER-ENG 2023

作者： Rușanu, Oana Andreea Product Design Mechatronics and Environment Department Transilvania University of Brașov Brașov Romania

ISBN: (纸本)9783031546730

The brain-computer interface (BCI) research field provides advanced biomedical technology based unique assistive or rehabilitative solutions aimed at helping people with neuromotor disabilities. The purpose of this paper is to develop a new brain-computer interface for controlling both a virtual simulation and a real experimental system of a vending machine or an automated machine for delivering various juices by transmitting commands based on detecting the P300 evoked biopotentials detected from the GTEC Unicorn headset embedding 8 EEG sensors. Therefore, after using the GTEC Unicorn Recorder official software to check the quality of the acquired raw EEG signals, the BCI commands are generated by triggering the P300 evoked biopotentials in the GTEC Unicorn Speller official board. The resulted EEG based P300 packets are sent in the LabVIEW instrument by the UDP communication protocol. The original LabVIEW application comprises two State-Machine programming sequences both for pictures-based simulation of delivering juices and the real experimentation of a physical Vending Machine controlled by the Arduino Mega 2560 development board. Also, the proposed LabVIEW instrument includes a programming code sequence facilitating the Bluetooth communication between the computer and the Arduino to enable the transmission of commands for controlling the DC pump air motors. The presented experimental prototype should be employed as a training or educational tool both for people with neuromotor disabilities and novice researchers into the brain-computer interface scientific field. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Brain computer interface

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Study on Control Strategy of the Vascular Interventional Surgical Robot Based on LADRC 20

Study on Control Strategy of the Vascular Interventional Sur...

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20th IEEE International conference on mechatronics and Automation, ICMA 2023

作者： Zhang, Wenqiang Guo, Jian Guo, Shuxiang Fu, Qiang Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Applications Complicated Systems and Intelligent Robot Laboratory Binshui Xidao Extension 391 Tianjin300384 China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen518100 China Beijing Institute of Technology Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science No.5Zhongguancun South Street Beijing100081 China

ISBN: (纸本)9798350320831

As a medical device used in surgery, the vascular interventional surgical robot itself needs to have good control accuracy to ensure the safety of the surgery process. Given this security problem, this paper selects the Line Active Disturbance Rejection Control (LADRC) as the control strategy of the vascular interventional robot, aiming at improving the master-slave tracking accuracy of the vascular interventional robot. This article compares the LADRC and PID(Proportional-Integral-Derivative) control strategies through simulation and experiments. The experimental results show that LADRC has good control performance for master-slave tracking and can be applied to the vascular interventional surgical robots. © 2023 IEEE.

关键词： Robotic surgery

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