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检索条件"任意字段=2023 International Conference on Computer Science and Automation Technology, CSAT 2023"

共 68829 条记录，以下是721-730 订阅

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Multi-source Weighted Domain Adaptive Network for Bearing Fault Diagnosis 3

Multi-source Weighted Domain Adaptive Network for Bearing Fa...

引用

3rd international conference on Testing technology and automation Engineering, TTAE 2023

作者： Huang, Yingjie Fu, Qiang Electrical engineering and automation Changsha University of Science & Technology Changsha410000 China

ISBN: (纸本)9781510674769

Bearing failure is one of the common faults in rotating mechanical systems, significantly impacting the reliability and performance of the machinery. However, due to variations in operating conditions and environmental factors, bearing failure data exhibits a multi-source domain issue, posing challenges for traditional fault diagnosis methods to be effectively applied. In this paper, a new multi-source weighted domain adaptive (MSWDA) framework is proposed, which is implemented by feature weighted and multi-layer feature extraction structure. To achieve feature-level distribution alignment, the minimum slice Wasserstein distance is used as a measure to measure the difference in feature distribution. Extensive experiments are conducted on the CWRU bearing datasets to validate the effectiveness of the proposed model. © 2024 SPIE.

关键词： Failure analysis

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Fixed-time cooperative control dichotomous consistency of multi-agent system with perturbations 24

Fixed-time cooperative control dichotomous consistency of mu...

引用

2nd international conference on Frontiers of Intelligent Manufacturing and automation, CFIMA 2024

作者： Qin, Wei Ren, Yan Liu, Shangyuan Wang, Qi Li, Xinwei Inner Mongolia University of Science and Technology Baotou China Inner Mongolia Normal University Tourism College Baotou China

ISBN: (纸本)9798400710681

Aiming at the fixed-time dichotomous consistency control problem of a first-order nonlinear multi-intelligence body system with external interference, this paper designs a fixed-time dichotomous consistency control algorithm based on system interaction information. Under the action of this algorithm, the first-order nonlinear multi-intelligent body system is able to track the leader’s trajectory in fixed time, and then realize the dichotomous consistency tracking. The control algorithm for this first-order leader-following nonlinear multi-intelligent body system is tested through numerical simulation experiments. Different input conditions are considered in the experiments and their operation results are simulated. The simulation results verify the effectiveness of the designed control algorithm and prove its good performance in solving the fixed-time consistency tracking problem. © 2024 Copyright held by the owner/author(s).

关键词： Nonlinear simulations

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Design and Implementation for AltaRica 3.0 Model Visualization Method Based on ANTLR 5

Design and Implementation for AltaRica 3.0 Model Visualizati...

引用

5th international conference on Internet of Things, automation and Artificial Intelligence, IoTAAI 2023

作者： Huang, Ximeng Hu, Jun Wang, Lisong Computer Science and Technology Nanjing University of Aeronautics and Astronautics China

ISBN: (纸本)9798400716485

With the advancement of technology, the current systems are constantly developing towards complexity, and the security and reliability requirements of complex systems are becoming more urgent. AltaRica3.0 is a formal modeling language for system security analysis. In response to the current lack of visualization methods for AltaRica3.0 models in China, this article designs and implements a method for generating hierarchical graph models from AltaRica3.0 models, analyzing the hierarchical structure and flow relationships of components of the models. A case study was conducted on the MSAT tool using Wheel Brake System as an example to verify the feasibility and effectiveness of the method. © 2023 ACM.

关键词： Visualization

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A NOA-AP based Typical Process Route Automatic Discovery Approach for Intelligent Manufacturing 7

A NOA-AP based Typical Process Route Automatic Discovery App...

引用

7th international conference on Robotics, Control and automation Engineering, RCAE 2024

作者： Cao, Xinyu Xu, Binzi Huang, Dengchao Wang, Chun Anhui Polytechnic University School of Electrical Engineering Wuhu241000 China Huaibei Normal University School of Computer Science and Technology Huaibei235000 China

ISBN: (纸本)9798350355642

With the continuous advancement of intelligent manufacturing, the efficient extraction of reusable typical process routes based on artificial intelligence for computer-aided process planning (CAPP) has emerged as a critical necessity. Because a good process route can not only effectively improve the efficiency of process planning, but also promote the transformation of traditional manufacturing to intelligent manufacturing. To address this situation, this paper proposes a Nutcracker Optimization Algorithm (NOA) enhanced Affinity Propagation (AP) algorithm under the consideration of clustering effectiveness to automatic discover the typical process routes from the massive historical data. First, two soft constraints (i.e., quantity constraint and size constraint) are introduced simultaneously in the clustering process to ensure the quality and validity of the obtained typical process routes according to the actual demand. In addition, previous research has emphasized that the selection of preference value and damping factor in the AP algorithm significantly influences clustering outcomes. Hence, NOA is implemented to identify the optimal individual within the search space to determine suitable preference values and damping factors, thereby enhancing the clustering quality of the AP algorithm. The numerical illustration shows that the proposed NOA-AP could improve the clustering quality and discover more representative and effective typical process routes. © 2024 IEEE.

关键词： Smart manufacturing

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Blockchain based tomato supply chain management 2

Blockchain based tomato supply chain management

引用

2nd international conference on Advancements in Electrical, Electronics, Communication, Computing and automation, ICAECA 2023

作者： Sudha, V. Aswini, D. Akiladevi, R. Government Polytechnic College Computer Engineering Coimbatore India Kumaraguru College of Technology Computer Science and Engineering Coimbatore India Computer Science and Engineering Rajalakshmi Engineering College Chennai India

ISBN: (纸本)9798350306811

Supply chain in agriculture field is very important as the cultivated goods are sensitive for time and temperature. Most of the time, middlemen act as the price-fixing authorities. The farmer's profit declines as the number of people increases. Additionally, there is no provision for tracking the status of the farming goods throughout transportation. Tomatoes are one of the many products that are time, temperature, and container sensitive. These parameters could be tracked by a centralized system, which would be more advantageous. Blockchain is a distributed database providing tamper proof storage of data. The management of the tomato supply chain based on blockchain is suggested in this research. Customers can use this method to learn how the produce is grown and how the shipping process works. Here, the farmer uses the smart contract to periodically update the blockchain with the crop status. The farmer grows it and sells it once it is ripe for cultivation. As a result, the proposed system enables the customer to be fully informed about the crop and commodities. Additionally, it helps the farmer keep track of their products and maximize their yield's profit. © 2023 IEEE.

关键词： Smart contract

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Exploring The Data science 7

Exploring The Data Science

引用

2023 7th international conference On Computing, Communication, Control And automation, ICCUBEA 2023

作者： Kumar, Amodh Kapil, Akshat Ahlawat, Deepak Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350304268

Data science is a rapidly expanding field in technology that has attracted a lot of concentration recently due to the enormous influence it has on many different companies and domains. The field encompasses a wide range of techniques and tools aimed at extracting meaningful insights and knowledge from large and complex datasets. This study seeks to offer a thorough review of the field of Data science by exploring its history, fundamental concepts, and current trends. It also highlights the current trends and developments in the field, such as big data, cloud computing, and the Internet of Things (IoT). The paper concludes by discussing the future of Data science and the impact it will have on various industries, including healthcare, finance, and retail. © 2023 IEEE.

关键词： Artificial Intelligence Deep Learning Machine Learning Natural Language Processing

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Airport Pedestrian Target Tracking Algorithm Based on Surf and Improved Correlation Filtering 9

Airport Pedestrian Target Tracking Algorithm Based on Surf a...

引用

9th international conference on computer and Communications, ICCC 2023

作者： Wan, Hao Xie, Yukang Yang, Zekai Zeng, Ming Deng, Feiqi Wan, Tong South China University of Technology School of Automation Science and Engineering China Guangdong Airport Baiyun Information Technology China Guangzhou Baiyun International Airport Co. Ltd China

ISBN: (纸本)9798350317251

Tracking target pedestrians in airport terminals has always been a challenge, a pedestrian target tracking algorithm based on surf and improved correlation filtering is proposed. Firstly, the SURF bidirectional matching algorithm is used to automatically identify the surveillance video where the target is located, and the state information of the target in the video image is extracted;Then, the hog feature and the color statistical feature of the target are extracted, and the correlation filter and the foreground background model based on the color statistical feature are trained respectively. The target confidence map is obtained through the feature fusion, so as to predict the location of the target and realize the tracking of the specified pedestrian target. The performance of this algorithm is verified by the comparative experiment with the KCF algorithm;Finally, the effectiveness and real-time performance of this algorithm are verified by the target tracking experiment in the real-time video of the airport terminal. © 2023 IEEE.

关键词： Color

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Blood Vessel Segmentation for Retinal Fundus Disease Detection

Blood Vessel Segmentation for Retinal Fundus Disease Detecti...

引用

2023 international conference on computer Communication and Informatics, ICCCI 2023

作者： Sivakumar, Rishikesh Singh, Nidhi Kumar, C. Jothi Prasath, N. SRM Institute of Science and Technology Computing Technologies Chennai India SRM Institute of Science and Technology Networking and Communications Chennai India

ISBN: (纸本)9798350348217

Multiple eye diseases can be easily detected from the orientation of the fundus and the blood vessels on the fundus of the eye. Most of the already present methodologies use methods like Gaussian filter, channel extraction and other preprocessing techniques for blood vessel segmentation. Which does not really solve the problem of giving faster and better results. Our approach involves data augmentation on the obtained samples as the number of samples is less and augmentation of these samples would result in better performance and efficiency of our model. We use an Encoder-Decoder Model, which is coded for segmenting the blood vessels from the samples. Hence providing more clear and accurate segmentation. Deep Learning Models like VGG-16, VGG-19, and ResNet50 can be applied to the blended images for predicting if the patient suffers from Retinal Disease or not. Since we use deep learning techniques and complex models, highly accurate results are obtained. This could be a very efficient alternative to reduce the efforts of an ophthalmologist and a major step towards automation in the field of ophthalmology. © 2023 IEEE.

关键词： Blood vessels

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Efficient Hybrid Model for Botnet Detection Using Machine Learning 4

Efficient Hybrid Model for Botnet Detection Using Machine Le...

引用

4th international conference on Computation, automation and Knowledge Management, ICCAKM 2023

作者： Saxena, Priti Patel, R.B. Uttarakhand Technical University Computer Science and Engineering Dehradun India Chandigarh College of Engineering and Technology Computer Science and Engineering Chandigarh India

ISBN: (纸本)9798350393248

In recent years, with the advancements in technology, threats to internet security have also been increased and botnets are among those threats. Botnet is a very critical and important area of research in the field of cybersecurity. Botnets are basically a network of computers or other internet-connected devices that are infected by malware and controlled by a cybercriminal. They are used for various malicious purposes like spamming, phishing, DDoS (Distributed Denial of Service) attacks, and so on. One of the most dangerous uses of botnets involves perpetrating fraud which can even lead to financial losses for individuals as well as organizations. Detecting botnet fraud is a challenging task because of its complexity and sophistication. Therefore, it requires a high level of research for its detection. In the current research paper, ML (Machine learning) algorithms have been used for botnet fraud detection. A hybrid model (KNN, Random Forest, and Logistic regression) is built on the dataset which has yielded 86.97 percent accuracy, 81.76 percent precision, 98.25 percent recall, and 89.25 percent F1-score in detecting botnet attacks. We have also discussed the challenges associated with botnet detection and have identified potential future directions for research in this area. © 2023 IEEE.

关键词： Denial-of-service attack

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Optimizing Search and Sort Algorithms: Harnessing Parallel Programming for Efficient Processing of Large Datasets 2

Optimizing Search and Sort Algorithms: Harnessing Parallel P...

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2nd international conference on automation, Computing and Renewable Systems, ICACRS 2023

作者： Maurya, Ipsit Sinha, Subhratha Suguna, M. School of Computer Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (纸本)9798350340235

This research study investigates the impact of parallel programming techniques on the performance of searching and sorting algorithms. Traditional sequential algorithms have been the foundation of data processing for decades, but the increasing availability of parallel computing resources opens new possibilities for improving efficiency and reducing execution times. By leveraging parallel programming models, such as shared memory and distributed memory systems, this study explores how the parallelization of search and sort algorithms can enhance their speed and scalability. Through comprehensive experimentation and analysis, this study aims to provide valuable insights into the benefits and challenges of parallel programming in the context of searching and sorting algorithms. © 2023 IEEE.

关键词： Parallel programming Performance optimization Scalability analysis Searching algorithms Sorting algorithms

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