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

共 47494 条记录，以下是151-160 订阅

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DCS Implementation of Hot Air Bag Filter Cleaning System With controls Using Yokogawa

DCS Implementation of Hot Air Bag Filter Cleaning System Wit...

引用

2025 international conference on Emerging Technologies for intelligent Systems, ETIS 2025

作者： Krishna, Karthika Syamraj, B.S. Providence College of Engineering Department of Computer Science and Engineering Kerala Chengannur Alappuzha India

ISBN: (数字)9798331507541

ISBN: (纸本)9798331507541

Dispersed control Systems (DCS) are a vital enhancement in commercial automation enabling central control plus tracking to boost effectiveness. Lots of Indian plants still make use of analog systems. Some additionally depend on PLC-based systems. Nevertheless, DCS fostering is expanding. It incorporates plant manages right into a solitary console. This paper provides the layout coupled with application of a Hot Air Bag Filter Cleaning System making use of the Yokogawa Centum VP DCS. The system utilizes heat technology to enhance bag filter cleansing guaranteeing far better purification coupled with bit elimination. The Yokogawa Centum VP DCS offers exact control, real-time tracking as well as effective automation. Its application increases performance, decreases downtime, and also makes sure conformity with ecological requirements, establishing a requirement in automation. © 2025 IEEE.

关键词： Air cleaners

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Real-Time Intrusion Detection Method Based on Frequency Domain Simplified Dual-PINN 24

Real-Time Intrusion Detection Method Based on Frequency Doma...

引用

8th international conference on Electronic Information Technology and computer engineering, EITCE 2024

作者： Zhang, Bohan Wang, Zhiwen Miao, Wei Lanzhou University of Science and Technology Gansu Lanzhou China Gansu Ziguang Intelligent Transportation and Control Technology Co Gansu Lanzhou China

ISBN: (纸本)9798400710094

To address the limitations of traditional intrusion detection systems that do not conform to the physical laws governing actual industrial processes, we propose a frequency domain simplified Dual-Physical-Informational Neural Network (Dual-PINN) methodology. This methodology reduces training costs and enhances real-time detection performance, allowing the lightweight detection system to be applicable in resource-constrained industrial environments. Additionally, drawing on the concept of meta-learning, we have partitioned the model into a teacher network and a student network to enhance the robustness of detection. Experimental results demonstrate that our method achieves over 99% detection accuracy on a real-world network traffic dataset, with an average detection time of 0.098 seconds per data packet, effectively enhancing the performance and efficiency of intrusion detection. © 2024 Copyright held by the owner/author(s).

关键词： Network intrusion

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Adaptive Particle Swarm Optimization of U-net Parameters for Marine Aquaculture Image Segmentation 13

Adaptive Particle Swarm Optimization of U-net Parameters for...

引用

13th international conference on intelligent control and Information Processing, ICICIP 2025

作者： Zhao, Jin Wang, Jun Han, Min Fan, Jianchao School of Computer Science and Engineering Chongqing Three Gorges University Chongqing China Department of Computer Science Department of Data Science City University of HongKong Hong Kong School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9798331516147

Marine aquaculture image segmentation plays a crucial role in managing aquatic resources and environmental protection. Traditional deep learning models rely on manual parameter tuning for image segmentation, which limits their efficiency and accuracy. This paper proposes an adaptive Particle Swarm Optimization (PSO) algorithm to optimize the parameters of the U-net model automatically. The algorithm dynamically adjusts the PSO parameters based on the population’s entropy and clustering metrics and employs a hill-climbing algorithm to address the issue of the PSO easily falling into local optima, enhancing the algorithm’s adaptability. The proposed algorithm updates and iterates particles to automatically find suitable model parameters. The remote sensing data used in this experiment were from the Yellow Sea aquaculture area near Dalian, China, with a segmentation accuracy of 91.8%. This method improves segmentation accuracy, reduces the burden of manual parameter tuning, and provides an effective solution for optimizing deep learning models. © 2025 IEEE.

关键词： Aquaculture

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Development of a computer-Assisted Vision-Based Inspection Monitoring System for Quality Assurance 5th

Development of a Computer-Assisted Vision-Based Inspection M...

引用

5th international conference on Innovative Product Design and intelligent Manufacturing Systems, ICIPDIMS 2023

作者： Bhide, Prajwal S. Manivannan, P.V. Department of Mechanical Engineering Indian Institute of Technology Madras Chennai600036 India

ISBN: (纸本)9789819767311

In a product-based manufacturing layout, the operator must inspect multiple similar products, making the process monotonous and strenuous. The quality control stage is mandatory in any manufacturing industry before the final product is dispatched. Of many quality inspection procedures, visual inspection is the most widely used. However, the visual inspection process becomes repetitive due to the vast number of products to be inspected daily. Hence, the operator carrying the inspection process is prone to human limitations like fatigue, which results in error, i.e. missing some of the inspection points. To mitigate this problem, a computer-Assisted Visual Inspection System (CAVIS) has been proposed in this work, which monitors and ensures inspection carried out by the operator. In CAVIS, a hand-tracking model detects and tracks the operator’s hand motion, i.e. the pointing finger used to touch the inspection markings to be checked. The present work is divided mainly into two parts: developing the inspection system algorithm to determine the coordinates of inspection marks in the image captured by a vision camera and subsequently tracking and ensuring the operator touches all the inspection markings using the pointing finger in real time, i.e. validating the developed system through experimental investigation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Inspection

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Edge and Fog Computing in Cyber-Physical Systems

Edge and Fog Computing in Cyber-Physical Systems

引用

2025 international conference on intelligent control, Computing and Communications, IC3 2025

作者： Gangrade, Priyanshi Kushwah, Virendra Singh Date, Saroj S. Jagdale, Archana D. Upreti, Kamal Singh, Vinai K. School of Cse and Ai Vit Bhopal University Sehore India Csmss Chh. Shahu college of Engineering Dept. of Ai and Ds Maharashtra Chh. Sambhajinagar India Barclays Services Corp 745 Seventh Avenue New York United States Department of Computer Science Christ University Delhi Ncr Ghaziabad India Gl Bajaj Group of Institutions Department of Computer Science & Engineering Mathura India

ISBN: (纸本)9798331527495

The benefits of cyber-physical system advances include low latency and high bandwidth data processing in areas such as automotive, healthcare, and business automation. Traditional environments are often located in centralized and remote locations and cannot meet the demand. Edge computing and cloud computing have become fundamental concepts that will bring computing closer to the center of the data. Edge computing can reduce latency and bandwidth consumption by processing data on or near IoT devices. Fog computing adds another layer to this by distributing work and storage across multiple nodes, thus providing a scalable and flexible infrastructure. This article discusses the principles, benefits, and challenges of integrating edge and cloud computing into a CPS environment. It leverages the power of proximity-based edge computing and the centralized capabilities of cloud computing to provide scalable, instantaneous responses to CPS applications or time to optimize services. The demonstration shows a variety of things from smart cities to the use of IoT in healthcare in CPS. The article also covers some specific security and privacy issues and future directions in distributed computing, including the role of AI and 5G, which are supposed to offer additional resources in various applications. © 2025 IEEE.

关键词： Data reduction

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Fine-Tuned Xception Model for Accurate Brain Tumor Classification: A Deep Learning Approach

Fine-Tuned Xception Model for Accurate Brain Tumor Classific...

引用

2025 international conference on intelligent control, Computing and Communications, IC3 2025

作者： Ankushavali, Md Tuteja, Gaurav Nasra, Parul Salami, Zaeid Ajsan School of Computer Science and Artificial Intelligence Sr University Telangana Warangal506371 India Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India College of technical engineering The Islamic University Department of computers Techniques engineering Diwaniyah Iraq College of technical engineering The Islamic University of Al Diwaniyah Department of computers Techniques engineering Najaf Iraq

ISBN: (纸本)9798331527495

The conditions are fatal and therefore the need for early diagnosis and accurate results to enhance on proper treatment. The modern advances in the field of Deep learning show great promises in automating the analysis of medical images and bringing accuracy to diagnostic levels. In this work, the performance effectiveness of the fine-tuned Xception model for classifying brain tumors based on MRI images is investigated. Using glioma, meningioma, pituitary tumor, the Xception model was fine-tuned as a transfer learning strategy to identify appropriate higher-level features that increases classification quality. To make the model less sensitive to both the image size and its orientation additional preprocessing steps were used: resizing, normalization and data augmentation. The proposed model provided approximately 96% classification accuracy, and it was faster than the standard CNN architectures. While precision, recall, and accuracy, as well as the F1-score, provided better evidence across all classes of the model's accuracy. The approach used in the current work demonstrates the effectiveness of using the Xception model in the diagnosis of brain tumors and the need to reduce the manual interpretation process in clinics. Future work also plans to use the framework in real-time diagnostic systems where a broader application of better medical imaging will be more available to the public. © 2025 IEEE.

关键词： Deep learning

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Real-Time Dynamic Image Stitching Using GNN-Based Feature Matching 11

Real-Time Dynamic Image Stitching Using GNN-Based Feature Ma...

引用

11th international conference on Mechatronics and Robotics engineering, ICMRE 2025

作者： Suh, Young Hoon Kim, Eun Ho Choi, Yeong Gwang Jeon, JaeWook Sungkyunkwan University Dept. of Electrical and Computer Engineering Suwon16419 Korea Republic of

ISBN: (纸本)9798331509293

Especially in static situations, image stitching has been routinely used to seamlessly merge many photographs into a panorama. Using it in dynamic and real-time environments, however, presents a number of difficulties, such as managing shifting objects, changing surroundings, and processing limitations. An image stitching look at that works well in dynamic real-time situations is presented in this paper. The method makes use of GNN-based feature matching, dynamic object removal, and real-time synthesis techniques. Comparative studies suggest that, in comparison to traditional methods like SIFT and ORB, the suggested approach meets real-time processing requirements while achieving greater registration precision, lower homography RMSE, and consistent panoramic outputs. The findings imply that the algorithm might be used in fields where precision and efficiency are required in dynamic circumstances, like parking management systems, sports broadcasting, and autonomous driving. © 2025 IEEE.

关键词： Photointerpretation

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A Hybrid Approach Using Cryptography and K-Least Significant Bit Steganography Algorithm in Cloud Computing 1

A Hybrid Approach Using Cryptography and K-Least Significant...

引用

1st international conference on advances in computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Goyal, Anshika Gupta, Bhumika VMSB Uttarakhand Technical University Dept. of Computer Science & Engineering Dehradun India G.B. Pant Institute of Engineering & Technology Dept. of Computer Science & Engineering Pauri India

ISBN: (纸本)9798331518578

The exponential growth of communication technologies has broadened the cloud computing ecosystem horizon to meet main communication needs. However, in-parallel upsurge in online attacks has alarmed industries to ensure optimal data security. The combination of steganography and cryptosystems has been recognized as an enhanced security model for data transfer among the main security systems now in use. In this paper, a hybrid approach using cryptography and K- Least Significant Bit Steganography algorithm in Cloud Computing (HYBC-KLSBS-CC) are proposed. Initially, input text data is retrieved from cloud storage and compressed using Huffman Compression Coding (HCC) to reduce data size. The compressed data is then encrypted with a Hybrid Cryptography Algorithm (Hyb-MRFC-ALC), combining Modified Random Fibonacci Cryptography and Asymmetric Lightweight Cryptography to ensure robust encryption. Finally, encrypted data is embedded within an image using the K-Least Significant Bit (KLSB) steganography technique, providing additional layer of security. The proposed method enhances data confidentiality, integrity, and storage efficiency in cloud environments. The proposed HYBC-KLSBS-CC approach attains 26.89%, 29.49% and 18.64% lower PSNR and 26.89%, 29.49% and 18.64% lower MSE when analyzed through existing techniques like data security dependent on cryptography steganography related with OTP procedure and Huffman coding in the cloud environment (CS-OTP-CE), a novel hybrid cryptographic framework for secure data storage in cloud computing: Integrating AES-OTP and RSA with adaptive key management and Time-Limited access control (AES-OTP-RSA-CC) and Crypto-Stegno dependent model for securing medical information on IOMT platform (CS-SMI-IOMT). © 2025 IEEE.

关键词： Cloud platforms

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Enabling Autonomy Through Voice control: AI-Assisted Mobile Platform 20th

Enabling Autonomy Through Voice Control: AI-Assisted Mobile ...

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20th EAI international conference on computer Science and Education in computer Science, CSECS 2024

作者： Balcheva, Ivelina Gorbounov, Yassen New Bulgarian University Sofia Bulgaria

ISBN: (纸本)9783031843112

The rapid development of the technological sector and the need to automate a wide range of human-aiding activities defines the development and research of autonomous mobile platforms as an increasingly urgent problem. At the same time, artificial intelligence plays the role of an innovative catalyst that increases the functionality, efficiency and convenience of mobile platforms, making them more intelligent and adaptive. The present paper focuses on the study of an autonomous mobile platform that uses voice control and artificial intelligence techniques for effective object recognition in the environment. This platform aims to improve the functionality of robotic systems, providing a more intuitive way to communicate and control. The research combines theoretical analysis, simulation modeling, software algorithm development, and experimental testing. The development process includes studying existing voice recognition and artificial intelligence methods, as well as their applications in the field of autonomous systems. Improving human-machine communication and decision-making processes facilitates the implementation of voice-assisted control. The proposed approach can find application in the improvement of robotic home assistants, in the control of mobile robots in dangerous or hard-to-reach environments, in the construction of remote laboratories, as well as in a number of other fields of technology. © ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering 2025.

关键词： Software testing

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Application of Wireless Sensor Technology in Urban Energy Management 24

Application of Wireless Sensor Technology in Urban Energy Ma...

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8th international conference on Electronic Information Technology and computer engineering, EITCE 2024

作者： Zhang, Yajuan Chen, Jie Gong, Zhijia College of Information Engineering Hainan Vocational University of Science and Technology Hainan Haikou China

ISBN: (纸本)9798400710094

The rapid growth of urbanization has led to an increasing need for efficient energy management systems to optimize energy consumption and reduce environmental impacts. Wireless sensor technology emerges as a pivotal solution, providing advanced capabilities in real-time monitoring, control, and management of urban energy systems. This paper explores the practical applications of wireless sensor networks (WSN) in urban energy management, highlighting their role in smart grids, intelligent building systems, smart street lighting, public transportation, water management, and renewable energy integration. Additionally, it addresses the prominent challenges such as data security, sensor durability, network scalability, data management, energy consumption, and infrastructure integration. [1-2] The paper further discusses optimization pathways to enhance the effectiveness and sustainability of WSNs in urban energy management. By overcoming these challenges and leveraging the potential of wireless sensor technology, cities can achieve significant energy savings, operational efficiencies, and contribute to broader environmental sustainability goals. © 2024 Copyright held by the owner/author(s).

关键词： Green buildings

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