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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121-130 订阅

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A Review on the Use of Smart Agriculture Systems to Protect Crops 3

A Review on the Use of Smart Agriculture Systems to Protect ...

引用

3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Kumar, Gulshan Gourshettiwar, Palash Suman, Saurabh Kumar, Shravan Kumar, Dhiraj Raushan, Rahul Faculty of Engineering and Technology Department of Computer Science and Design Maharashtra Wardha India Faculty of Engineering and Technology Department of Computer Science and Medical Engineering Maharashtra Wardha India

ISBN: (纸本)9798331509675

Smart agriculture systems leverage the possibilities offered by cutting-edge technologies such as IoT, AI, and remote sensing to revolutionize conventional farming by enhancing resource utilization, production, and crop damage mitigation. Real-time monitoring of soil and crop health, predictive analytics, pest control, and precision irrigation measures are all enabled by these systems. They are able to address major Indian agriculture issues, consequently boosting yield and profitability and promoting environmental sustainability. The largescale deployment of intelligent agriculture systems will change the agriculture landscape in India and will assure long-term food security for an ever-growing population. Challenges include adequate research and future studies in order to better install and achieve smart agricultural systems to protect crops. intelligent agriculture involves all advanced research, including science and innovations, in national development through space technologies to enhance soil quality, conserve water, and facilitate agriculture information. Space ventures will undergo improved modernization through the introduction of crop sprayers, precision gene editors, epigenetics, big data analytics, IoT, wind and photovoltaic smart energy, AI-enabled robotic applications, and wide-scale desalination technologies. Implementing digital farming systems in developing economies will help their sectors as 85 percent of the global population is set to live in developing countries by 2030. Automation will prove to be necessary since food scarcity is on the rise along with resource wastage. control strategies such as the IoT, aerial imagery, machine learning, and artificial intelligence will boost production and prevent soil degradation. These advanced technologies are also able to alleviate such issues as plant disease detection, pesticide management, and water application. The introduction of the Internet of Things in the agricultural research world has started

关键词： Smart agriculture

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Energy Efficient and SecurityAware Task off Loading for Multi-Tier Edge Cloud Computing Systems 1

Energy Efficient and SecurityAware Task off Loading for Mult...

引用

1st international conference on intelligent Systems and Computational Networks, ICISCN 2025

作者： Divya, S. Saranya, S. Mahendra Engineering College Department of Computer Science and Engineering Namakkal India

ISBN: (纸本)9798331529246

The massive progression of the multi-tier edge cloud computing systems integration has created the possibility of data orchestration and resource control in edge and cloud layers. However, there are many shortcomings, including inappropriate methods of scheduling tasks and security breaches that prevent scalability. To solve these problems, we designed an energy-efficient and security-aware task offloading framework for multi-tier edge cloud computing. Firstly, we estimate the energy ratio of tasks using a Fuzzy Logic Energy Management (FL-EM) algorithm and distribute resources according to different layers. Subsequently, the task-offloading parallel squirrel (TO-PS) method is used to effectively extend the task with better energy consumption and computational efficiency. Finally, it is decided to protect the work data using the Provable Energy-Aware Cryptographic Security (PE-ACS) algorithm. The proposed algorithm achieves a 96.7% success rate in protecting high-level data from cybercrime. Additionally, it enhances security and task performance while reducing energy consumption in multi-tier edge cloud computing systems. © 2025 IEEE.

关键词： Cloud security

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A privacy protection strategy based on homomorphic encryption and neural networks 24

A privacy protection strategy based on homomorphic encryptio...

引用

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

作者： Liu, Lingli Du, Xiongxiong Ma, Mingcheng Wang, Dong Henan International Joint Laboratory of Intelligent Network Theory and Key Technology Henan University Henan Kaifeng China

ISBN: (纸本)9798400710094

In recent years, incidents of data abuse and privacy leakage remind people that improper use of big data technology can bring disastrous consequences. To realize the true value of data, data sharing is needed. This paper adopts a training method for a privacy-protecting neural network model based on homomorphic encryption in a cloud computing environment. It designs a piecewise linear activation function considering the role of the activation function for homomorphic computing. A ciphertext update strategy is proposed to control weight ciphertext noise growth. Combined with cloud computing, complex neural network computing tasks are entrusted to the cloud. Applied to data privacy protection, it is observed that AlexNet’s PPNN takes 293.5 seconds for inference on CIFAR-10 or MNIST. The lightweight architecture SqueezeNet generated by EVA amplifies AlexNet’s layers and adds rescaling. Although homomorphic encryption in SqueezeNet is slower, it reduces the delay to 72.7 seconds and ensures data security. © 2024 Copyright held by the owner/author(s).

关键词： Differential privacy

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Decentralized Federated Learning with Auto-switchable Local Optimizers 13

Decentralized Federated Learning with Auto-switchable Local ...

引用

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

作者： Li, Ting Chang, Zhongyi Pan, Zhiyao Yang, Shaofu Xu, Wenying Chen, Zhongying School of Computer Science and Engineering Southeast University Nanjing211189 China

ISBN: (纸本)9798331516147

In this paper, we propose a novel decentralized learning algorithm over networks, termed as DLAGD, which combines the consensus mechanism with an auto-switchable local optimizer. Specifically, each node updates its local model parameter based on either gradient descent algorithm or Adam-like algorithm, which depends on a local switching function. Such switchable local optimizer can better capture the structure information of local loss function than existing algorithms relying on a fixed local optimizer, then has the potential to accelerate the convergence rate and improve the generalization performance. We theoretically prove that DLAGD can converge to the neighborhood of a stationary point at a sublinear rate for non-convex problems. Finally, numerical experiments are presented to show the superior performance of DLAGD in terms of the training rate and test accuracy. © 2025 IEEE.

关键词： Federated learning

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Fire Suppression Robot with Image Processing for Warehouse Safety 1

Fire Suppression Robot with Image Processing for Warehouse S...

引用

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

作者： Base, James Allen V. Dorosan, Jairus F. Ocampo, Kyle Joshua P. Puma, Aeron Joshua M. Mercado, Mark Angelo T. Niega, Juliet O. Nationial University Philippines Department of Computer Engineering Laguna Calamba City Philippines

ISBN: (纸本)9798331518578

Warehouses are highly vulnerable to fire hazards due to the presence of combustible materials, high-energy equipment, and operational complexities. In response, the proponents propose a solution to the pressing issue of warehouse fire which pose a significant threat globally, including Philippines. The prototype that the proponents developed introduces an advance approach to fire detection and suppression. It is an incorporation of the YOLO algorithm to ensure fire detection with high accuracy, the Raspberry Pi 5 for advanced image processing, and the Arduino Mega for effective hardware control. The overall performance capacity of the robot in terms of detection and suppression shows efficiency as it provides faster response with great productivity, compared to using traditional firefighting techniques with human intervention. With an average of 4.0, or interpreted as good, it confirms that it is effective and reliable in suppressing fire. Recommendations for future improvements include expanding the dataset and enhancing hardware scalability to optimize the system's real-world applications. © 2025 IEEE.

关键词： Fire extinguishers

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advances in Type II Diabetes Prediction: A Comprehensive Review of Machine Learning Techniques

Advances in Type II Diabetes Prediction: A Comprehensive Rev...

引用

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

作者： Kushwah, Virendra Singh Krishnan, Sivaneasan Bala Upreti, Kamal Kumar, Manoj Kshirsagar, Pravin R. Singh, Vinai K. Singapore Institute of Technology Singapore School of Sciences Christ University Department of Computer Science DelhiNCR Ghaziabad India Gurukula Kangri University Department of Mathematics and Statistics Haridwar India J D College of Engineering & Management Department of Electronics & Telecommunication Engineering Nagpur India Gl Bajaj Group of Institutions Department of Computer Science & Engineering Mathura India

ISBN: (纸本)9798331527495

Type II diabetes mellitus, on the other hand has been regarded as one of the growing concerns globally and thus clearly raises the need for making accurate forecasts of diabetes. The risk for Type II diabetes can be predicted using Ma-chine Learning as well as any other form to make the predictions much more enhanced than the traditional methods. This paper aims to give a broad overview of literature that has so far been available on the ML algorithms used in the management of Type II diabetes including such supervised algorithms as logistic regression, alphabet regression, random forest, support vector regression along with other methods such as, ensemble learning, deep learning, and hybrid. Analysis of the main aspects for the performance model such as parameter selection, the way to face and cope with imbalance parameters, interpretability and generalizability across different populations, another aspect that was regarded is the possibility of using real-time data collected with wearable devices and applying tissue and other biomarkers for better prediction. Finally, the key obstacles and future directions towards developing ML algorithms and models explainable and clinically relevant have been introduced to help researchers and practitioners toward effective, personalized, and scalable interventions. © 2025 IEEE.

关键词： Support vector regression

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Optimization of the online collaboration platform: an event queue management algorithm based on debounce and throttle techniques 4

Optimization of the online collaboration platform: an event ...

引用

4th international conference on computer Vision, Application, and Algorithm, CVAA 2024

作者： Xue, Tianbao Lan, Quanxiang School of Mathematics and Computer Science Panzhihua University Sichuan Panzhihua China

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

Against the backdrop of accelerating digital transformation, online collaboration platforms have become indispensable tools for remote work and learning. However, with the increase in the number of users, the problem of high concurrency event processing has become increasingly prominent. Therefore, this paper proposes an event queue management algorithm (EQA-DT) based on debouncing and throttling techniques to optimize the efficiency of event processing in high concurrency scenarios. The EQA-DT algorithm uses a debounce technique to control the frequency of event capture, ensuring that only the last event triggered by the user is recorded within a short period of time. It also uses a throttling technique to periodically push events in the queue to the server, limiting the frequency of events being pushed to the server. We compared the EQA-DT algorithm with traditional event processing methods in an experimental setting. The results showed that in high concurrency scenarios, the EQA-DT algorithm is superior to traditional event processing methods in terms of reducing server pressure, reducing the length of the event queue, and improving system response speed. This algorithm provides an effective solution for improving the performance of online collaboration platforms and lays the foundation for future research in this area. © 2025 SPIE.

关键词： Concurrency control

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Adaptive Video Bitrate Allocation for Remotely Operated Vehicles (ROV) 8th

Adaptive Video Bitrate Allocation for Remotely Operated Vehi...

引用

8th international conference on intelligent Transport Systems, INTSYS 2024

作者： Afi, Eman Sarah Triqui, Ons Sayahi, Sofiane Besbes, Hichem Tlili, Fethi Mediterranean Institute of Technology South Mediterranean University Tunis Tunisia Higher School of Communication of Tunis University of Carthage Ariana Tunisia Innovation Department ACTIA Engineering Services Ariana Tunisia COSIM Lab Higher School of Communication of Tunis University of Carthage Ariana Tunisia GRESCOM Lab Higher School of Communication of Tunis University of Carthage Ariana Tunisia

ISBN: (纸本)9783031863691

Establishing a stable and efficient connection between operators and remotely operated vehicles (ROVs) is essential for successful missions in challenging environments. Real-time video transmission is particularly critical, providing operators with visual feedback to navigate and control the vehicle effectively. This study aims to improve video transmission quality in a multi-camera ROV equipped with six cameras and various sensors. Our focus is to enhance the Quality-Aware Dynamic Rate Allocation (QADRA) system, which optimizes video quality by dynamically adjusting codec parameters like resolution and quantization parameters (QPs) based on expected peak signal-to-noise ratio (XPSNR) predictions. This enhancement addresses the unique challenges of achieving balanced video quality across multiple video streams. The method involves developing a system that dynamically adapts codec parameters for each camera based on predefined bitrates, influenced by an assigned weight to each camera to control bitrate distribution and resulting video quality. By prioritizing certain video streams, this weighted system aims to optimize visual representation and thus improve the operator’s situational awareness. Results from theoretical exploration and analysis indicate that this approach can enhance the internal distribution of video quality across multiple camera feeds, contributing to more effective decision-making during teleoperated vehicle operations. In conclusion, this research advances the multi-camera video transmission capabilities for teleoperated vehicles, addressing limitations in video quality management and improving operational effectiveness in remote vehicle control. © ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering 2025.

关键词： Remotely operated vehicles

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Research and Optimization of SM9 Based on a Modular Design

Research and Optimization of SM9 Based on a Modular Design

引用

2024 international conference on Mechatronics and intelligent control, ICMIC 2024

作者： Wei, Bin Zhao, Qifu Shao, Cuiping Li, Huiyun Gao, Shunxian State Grid Key Laboratory of Power Industrial Chip Reliability Technology Beijing Smart-Chip Microelectronics Technology Co. Ltd. Beijing100192 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Guangdong Shenzhen518055 China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

Since its introduction by the National Cryptography Administration in 2016, the SM9 algorithm has encountered various opportunities and challenges. This study introduces a refined bottom-up modular framework, resulting in a more systematic and comprehensible algorithm structure with standardized naming conventions and clear module component descriptions. At the same time, we have proposed a comprehensive optimization scheme for bilinear pairing, optimizing the internal calculation process and improving the usability and efficiency of the SM9 algorithm. The experimental results at both the software and hardware levels have confirmed the effectiveness of our proposed method. Our work goes beyond previous research that mainly focuses on individual modules or sub-modules, and has made significant progress in promoting the widespread application of the SM9 algorithm in practical scenarios. © 2025 SPIE.

关键词： Mathematical optimization Evolutionary algorithms Design Algorithm development computer hardware computer security Cryptography Logic Nomenclature Standards development

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Adaptive Differentially Private Robust Federated Learning Against Backdoor Attacks 1

Adaptive Differentially Private Robust Federated Learning Ag...

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1st international conference on intelligent Manufacturing and Cloud Computing, ICIMCC 2024

作者： Yao, Ruixiang Wen, Hong Hou, Wenjing Ma, Wendi Sun, Fan Zhao, Ziang School of Aeronautics and Astronautics University of Elec.Science and Tech. of China Chengdu611731 China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Lab. of Sichuan Province UESTC 611731 China Intelligent IoT Communication Technology Engineering Research Center of Sichuan Province UESTC 611731 China

ISBN: (纸本)9781643685779

In federated learning systems, malicious attackers can manipulate training datasets by injecting backdoor triggers to achieve data poisoning. Addressing this vulnerability, this paper proposes a new defense method, the adaptive differential privacy stochastic gradient descent (ADP-SGD) algorithm, which increases the Euclidean distance between malicious and benign updates to enhance aggregation efficiency. Experiments were conducted on typical datasets, and the results show that combining ADP-SGD with the m-Krum aggregation algorithm can effectively defend against backdoor attacks in complex attack environments. While ensuring the accuracy of the main task, it significantly reduces the success rate of backdoor attacks, especially under the condition of unknown proportions of malicious participants, proving to be effective and robust. © 2025 The Authors.

关键词： Federated learning

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