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检索条件"任意字段=International Conference on Advances in Intelligent Control and Computer Engineering"

共 47513 条记录，以下是291-300 订阅

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Cooperative control of slip rate of distributed drive electric vehicles based on modularization and Multi-agent 3

Cooperative control of slip rate of distributed drive electr...

引用

3rd international conference on intelligent Mechanical and Human-computer Interaction Technology, IHCIT 2024

作者： Niu, Qiang Wei, Wenjun School of Automation and Electrical Engineering Lanzhou Jiaotong University Lanzhou730070 China

ISBN: (纸本)9781510683105

To solve the drive slip prevention problem of distributed drive electric vehicles under extremely complex road conditions, this paper proposes a multi-agent body distributed control method based on modularized architecture. Firstly, the modular approach is used to reconstruct the whole vehicle structure, consider each hub motor wheel as an independent agent, and establish the slip rate model of each wheel agent. Then, a distributed model predictive control method based on multi-agent is designed to solve the drive anti-slip problem considering multi-constraints and multi-objectives. Finally, the anti-slip performance is verified by simulation under low adhesion and split road conditions. The results show that the distributed control strategy under the modularized architecture can synergistically control the wheels to achieve good anti-slip effect. This provides a theoretical and practical reference for further development of modular vehicle in the future. © 2024 SPIE.

关键词： Predictive control systems

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Event-Based Sensing for Improved Traffic Detection and Tracking in intelligent Transport Systems Toward Sustainable Mobility

Event-Based Sensing for Improved Traffic Detection and Track...

引用

international conference on Interdisciplinary Approaches in Civil engineering for Sustainable Development, IACESD 2023

作者： Chakravarthi, Bharatesh Manoj Kumar, M. Pavan Kumar, B.N. School of Computing and Augmented Intelligence Arizona State University S Mill Avenue TempeAZ85281 United States Computer Science and Engineering Jyothy Institute of Technology Off Kanakapura Road Karnataka Bengaluru560082 India Computer Science and Engineering Indian Institute of Information Technology Sri City Gnan Marg Andhra Pradesh Sri City517646 India

ISBN: (纸本)9789819996094

This paper presents a pipeline that utilizes a TorchScript model to implement event-based detection in challenging traffic scenarios, aligning with the theme of advances in intelligent Transport Systems (ITS) for Sustainable Mobility. The pipeline incorporates intuitive interfaces for visualizing event streams in both 2D and 3D, enhancing the understanding of traffic dynamics. It also integrates adaptive rate control and optical flow estimation techniques to improve detection and tracking capabilities. The model demonstrates promising results in accurately detecting and tracking vehicles and pedestrians. To validate the model’s performance, we analyze the spatio-temporal distribution of events using histogram difference computation and exponential-decay time surface analysis, which provide valuable visual insights. By effectively utilizing event-based sensing and incorporating innovative techniques, this research contributes to the advancement of vision-based traffic monitoring for sustainable mobility within the field of intelligent Transport Systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Surface analysis

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A Novel Approach to Forecasting Crude Oil Price Based on LSTM and Online Learning

A Novel Approach to Forecasting Crude Oil Price Based on LST...

引用

2024 international conference on advances in Data engineering and intelligent Computing Systems, ADICS 2024

作者： Sai, Aditya Bajpai, Aindri Rohan, M. Subburaj, Brindha Subramanian, Girish H. School Of Computer Science And Engineering Vellore Institute Of Technology Chennai India School Of Business Administration Penn State Harrisburg PA United States

ISBN: (纸本)9798350364828

Crude Oil, a mixture of petroleum liquid and gases, extracted from the ground, is undoubtedly the fuel that drives the modern civilization. It affects the economic situation, often very directly in many countries. In this paper, we introduce a novel approach to forecasting crude oil price by combining existing machine learning paradigms namely, Online Learning and Long Short-Term Memory (LSTM). In our approach, we combine LSTM with a sliding window approach, so that the model gets updated as it receives new data, and captures the changing trends as soon as a new price is available in a more accurate way. The experiment results, compared with the existing LSTM Model of the same architecture using performance metrics like Mean Absolute Error, as well as Root Mean Squared Error and Directional Accuracy (DA), show that our model, with an RMSE of 1.65, MAE of 1.36 and the Directional Accuracy of 65.52% for the best scenarios dominates in terms of less error rate and more accuracy and achieves better Directional Accuracy. © 2024 IEEE.

关键词： Long short-term memory

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An intelligent System For Skin Cancer Detection Using Deep Learning Techniques

An Intelligent System For Skin Cancer Detection Using Deep L...

引用

2024 international conference on advances in Data engineering and intelligent Computing Systems, ADICS 2024

作者： Rajasekar, Vani Nirmala Devi, K. Sathya, K. Santhosh, A. Saran, S. Senthilvel, K. Kongu Engineering College Computer Science And Engineering Erode India

ISBN: (纸本)9798350364828

Skin cancer diagnosis poses significant challenges in the medical field due to its varying presentations and the expertise required for accurate classification. The complexity of skin lesions and the need for specialized expertise often hinder efficient diagnosis. The proposed work provides a reliable and effective method for classifying skin cancer using convolutional neural networks. The CNN model uses deep learning to automatically identify complex patterns and features. The model allows for the accurate and automated classification of skin lesions into benign and malignant categories. The proposed model is trained on a vast and diverse dataset that includes different types of skin cancer, specifically the 'Skin Cancer MNIST HAM10000' dataset, which comprises 10,000 images of various skin lesions. Data augmentation approaches are utilized to enhance performance even more, allowing the model to generalize well over a range of skin textures, lighting situations, and lesion sizes. In addition to expediting the identification of skin cancer, the suggested CNN-based method demonstrates impressive accuracy, achieving an overall accuracy rate of approximately 98.10%. The automatic classification system is a valuable addition to a doctor's toolkit, as skin cancer cases increase. Early detection aids in the fight against this crippling sickness, which ultimately leads to progress. © 2024 IEEE.

关键词： Convolutional neural networks

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Enhancing Diagnostic Accuracy in Lung Disease:A VIT Approach

Enhancing Diagnostic Accuracy in Lung Disease:A VIT Approach

引用

2024 international conference on advances in Data engineering and intelligent Computing Systems, ADICS 2024

作者： Ajitha, E. Abishekkumaran, S. Deva, J.C. St Joseph's Institute Of Technology Department Of Computer Science And Engineering Chennai India

ISBN: (纸本)9798350364828

In the realm of medical diagnostics, where limited data availability poses a challenge, this project addresses the detection of pulmonary diseases, tuberculosis, Corona Virus using chest X-Radiation images from modest datasets containing fewer than a thousand samples. By harnessing the potential of deep Vision Transformer approach is employed for lung disease classification. A distinctive pipeline is established, encompassing image preceding classification. Comparative analysis with existing frameworks showcases the efficacy of this approach. Remarkably, the study reveals that pretrained models and even simpler classifiers like shallow neural networks can rival complex systems. The framework is also validated against publicly available lung datasets, positioning it as a competitive solution. This method achieves accuracy levels akin to state-of-the-art models while embracing the advantage of fewer trainable parameters. Importantly, the MobileViT based model showcases performance parity with superior solutions, effectively reconciling computational efficiency with diagnostic accuracy. This project pioneers an innovative pathway, transcending data constraints to empower accurate and accessible pulmonary disease detection through a resource-efficient framework. © 2024 IEEE.

关键词： COVID-19

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Design and Research of Terminal Image Measurement System Based on Human-computer Interaction and Object Detection 4

Design and Research of Terminal Image Measurement System Bas...

引用

4th international conference on computer Science, Electronic Information engineering and intelligent control Technology, CEI 2024

作者： Guo, Fang Guo, Jun Jiang, Fuzhen Wang, Xiuping Weifang Engineering Vocational College Shandong Qingzhou China

ISBN: (纸本)9798350378542

In order to solve the problem that the current terminal section of the wire harness is difficult to complete the quality inspection by human eye, a set of terminal image measurement and analysis software system is developed based on software design and development and image measurement and analysis technology. First of all, according to the manual inspection process, the software demand analysis and functional process design are carried out to form a standardized industrial software architecture and framework module. Then, combined with the camera software control development and image acquisition analysis, the image measurement task set is realized, and the measurement purpose of each dimension of the terminal image target is achieved. Finally, the image measurement module is integrated into the software system, and integrated into user login management, dongle management, database management and report management to achieve an industrial software system that meets the commercial landing standards. The experimental test results show that the system is conducive to reducing the burden of manual visual inspection, and improves the accuracy and efficiency of wire harness terminal quality inspection. © 2024 IEEE.

关键词： Software testing

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Path Planning for Mobile Robot Based on Improved Aquila Optimizer 4

Path Planning for Mobile Robot Based on Improved Aquila Opti...

引用

4th international conference on computer Science, Electronic Information engineering and intelligent control Technology, CEI 2024

作者： Zhang, Jiakai Meng, Huan Li, Tongtong Zhao, Jingbo School of Information and Control Engineering Qingdao University of Technology Qingdao China Qingdao Product Quality Testing Research Institute Qingdao China

ISBN: (纸本)9798350378542

In this paper, we propose an improved Aquila optimizer (IAO) addressing the path planning problem of mobile robots. First, chaos mapping is used to initialize the population, enhancing the algorithm's global exploration abilities. To escape local optima, Cauchy- Gaussian mutation perturbations are introduced. Finally, to overcome the limitations of the traditional Aquila optimizer, the energy switching mechanism of the Harris hawks optimization (HHO) are introduced. Achieving an effective balance between global exploration. We present the experimental results of benchmark function tests and global exploration strategies. The comparative experimental results and robot path planning show that improved Aquila optimizer exhibits a faster convergence speed and better optimization capability. It demonstrates high effectiveness and stability in mobile robot path planning. © 2024 IEEE.

关键词： Microrobots

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Web Application for Identifying Emerging Trends and Technologies using Scopus and OpenAI APIs

Web Application for Identifying Emerging Trends and Technolo...

引用

2024 international conference on advances in Data engineering and intelligent Computing Systems, ADICS 2024

作者： Harshavardhan, Telugu Vasisht, Nalmas Praneeth, Mukka Deepika, Namani Hariharan, Shanmugasundaram Kukreja, Vinay Vardhaman College Of Engineering Department Of Computer Science And Engineering Hyderabad India Chitkara University Institute Of Engineering And Technology Chitkara University Punjab India

ISBN: (纸本)9798350364828

Emerging trends and technologies are reshaping the landscape of various domains. Identifying these trends is crucial for researchers, practitioners, and industry professionals. This research paper introduces a methodology for identifying emerging trends and technologies within a designated domain through user-specified keywords The method uses the advanced capabilities of OpenAI's GPT-3 model to extract and refine keywords accurately, and the Scopus API to access scholarly articles. The method is implemented in a user-friendly web application. Users can enter a keyword and receive a detailed list of related emerging trends and technologies. The results of the study show that the method is effective in extracting relevant and refined keywords, providing valuable insights into the development of new technologies and trends in specific areas. This innovative approach demonstrates the potential of combining advanced language models and scholarly databases. It also enables users to stay informed about the latest developments in their areas of interest. The research provides a foundation for a dynamic and efficient tool for identifying trends, making it a valuable resource for researchers, practitioners, and industry professionals looking to understand and take advantage of the constantly changing landscape of emerging technologies. © 2024 IEEE.

关键词： Application programming interfaces (API)

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4th international conference on computer Science, Electronic Information engineering and intelligent control Technology, CEI 2024

作者： Zhou, Xulang Wen, Yongdiao Hu, Wenhui Li, Gang Li, Tie Xidian University School of Electric Engineering Xi'an China Science and Technology on Electromechanical Dynamic Control Laboratory Xi'an China

ISBN: (纸本)9798350378542

To address the challenge of effectively evaluating ISAR image similarity under multi-precision fusion processing, this paper proposes a Fine-Grained Weighted Entropy (FGWE)-based image similarity evaluation method. This approach fully considers the subtle structural features in radar images by assigning different entropy weights to various regions, thereby emphasizing the differences of the important structural information and then reflecting accurately the similarity between images. Experimental results demonstrate that, compared with traditional methods, when FGWE was used to evaluate radar images, it showed a greater sensitivity to structural feature differences, and more accurately trapped the image information loss which derived from multi-precision processing. The mentioned FGWE reveals great potential in the field of radar image precision evaluation. © 2024 IEEE.

关键词： Radar imaging

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A Novel Proxy Re-Encryption Technique for Secure Data Sharing in Cloud Environment

A Novel Proxy Re-Encryption Technique for Secure Data Sharin...

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2024 international conference on advances in Data engineering and intelligent Computing Systems, ADICS 2024

作者： Reddy, K.V. Narasimha Reddy, DoddaVenkata Babu, Padamata Ramesh Anantha Raman, G.R. Balasubramani, S. Andhra Pradesh Narasaraopeta India Jawaharlal Nehru Technological University Department Of Computer Science And Engineering Andhra Pradesh Kakinada India Koneru Lakshmaiah Education Foundation Department Of Cse Andhra Pradesh Vaddeswaram India

ISBN: (纸本)9798350364828

In general, Cloud Computing refers to the storage and access of data through the internet rather than on a local computer hard drive. Cloud services assist in reducing the amount of space and money required for data storage. Data that must be accessed from the cloud must be protected. However, cloud owners and users have a big hurdle in terms of security and personal data privacy. Due to the data owners' lack of trust, they save their data in an encrypted format that is inaccessible to outsiders. The phrase 'proxy re-encryption' (PRE) refers to a popular way of delivering encrypted data stored in the cloud. When a data owner wants to share encrypted data with both the data user and the cloud server (proxy), the data owner generates re-encryption data and sends it to the proxy, which can use it to convert the data holder's ciphertexts into the user's plaintexts without having to look at the plaintexts beneath. The implementation demonstrates that our proposed work protects privacy while also allowing for secure data sharing via cloud computing. © 2024 IEEE.

关键词： Quality of service

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