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

共 46884 条记录，以下是4911-4920 订阅

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Reinforcement Learning for Supply Chain Attacks Against Frequency and Voltage control 22

Reinforcement Learning for Supply Chain Attacks Against Freq...

引用

22nd IEEE international conference on Machine Learning and Applications, ICMLA 2023

作者： Mohamed, Amr S. Lee, Sumin Kundur, Deepa University of Toronto The Edward S. Rogers Sr. Department of Electrical & Computer Engineering Canada

ISBN: (纸本)9798350345346

The ongoing modernization of the power system, involving new equipment installations and upgrades, exposes the power system to the introduction of malware into its operation through supply chain attacks. Supply chain attacks present a significant threat to power systems, allowing cybercriminals to bypass network defenses and execute deliberate attacks at the physical layer. Given the exponential advancements in machine intelligence, cybercriminals will leverage this technology to create sophisticated and adaptable attacks that can be incorporated into supply chain attacks. We demonstrate the use of reinforcement learning for developing intelligent attacks incorporated into supply chain attacks against generation control devices. We simulate potential disturbances impacting frequency and voltage regulation. The presented method can provide valuable guidance for defending against supply chain attacks. © 2023 IEEE.

关键词： cyber- physical security cyberattacks frequency control reinforcement learning Supply chain attacks voltage regulation

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Violence Detection Through Surveillance Videos Using Combination of VGG16 and LSTM

Violence Detection Through Surveillance Videos Using Combina...

引用

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

作者： Shubhangi Kale School of Computer Engineering MIT Academy of Engineering Alandi(D.) Pune India

ISBN: (数字)9798350364828

ISBN: (纸本)9798350364835

Now-a-days in India, population is increasing. So, it affects crowd and violence in metro cities. As a citizen, it is our responsibility to prevent the violence among the people. To aim this, human surveillance is generally chosen but it results in many human errors. So an intelligent and automated system is needed to achieve this. A proposed system is decided where a combination of deep learning model such as VGG16 and a Sequential Model using LSTM layer and various dense layers. The Kaggle Dataset used is Hockey dataset containing videos with different activities like running, fighting, walking, etc. The modelis giving around 95%. Accuracy and minimum loss.

关键词： Surveillance Computational modeling Urban areas Sociology Neural networks Data models Statistics

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Turbine bearing fault diagnosis based on embedded system 7

Turbine bearing fault diagnosis based on embedded system

引用

2024 7th international conference on intelligent Manufacturing and Automation, IMA 2024

作者： Zhao, Zhikang Wei, Chuankang Zhao, Rentao North China University of Technology School of Electrical and Control Engineering Beijing100144 China

Failure of the main components of the transmission mechanism of large machinery and equipment usually uses sensors to collect real-time vibration or audio information, followed by data processing on the computer to analyze whether the equipment is operating normally. In this paper, a multi-core embedded fault diagnosis platform based on ARM and DSP is designed. It is small in size. It can independently set the signal types, ranges, and filter parameters of multiple acquisition channels, and synchronously set high-precision acquisition and storage of voltage signals output from various sensors. The DSP adopts the fast Fourier algorithm to analyze the multi-channel sampling data in real time and extracts the fault characteristics through the analysis of envelope demodulation. The operation results show that the system can meet the routine online fault diagnosis of mechanical equipment transmission mechanism, and the fault analysis and diagnosis can reach 95% accuracy within one minute, with high real-time accuracy. © Published under licence by IOP Publishing Ltd.

关键词： Failure analysis

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Portable Executable Header Based Ransomware Detection using Power Iteration and Artificial Neural Network 6

Portable Executable Header Based Ransomware Detection using ...

引用

6th international conference on Information Systems and computer Networks, ISCON 2023

作者： Singh, Mahendra Pratap Karkhur, Yash National Institute of Technology Karnataka Surathkal Department of Computer Science and Engineering Mangaluru575025 India

ISBN: (纸本)9798350346961

In the present world, the dependency on different devices connected to the internet is increasing at a rapid rate day by day. Devices like smart watches, mobile phones, personal computers, etc., are part of our day-to-day life. We rely on them for most of our daily tasks. Since these devices are frequently used, they contain users' personal information and other essential data. More and more people use the internet due to emerging technology and intelligent devices, increasing the risk of misusing confidential information and other user-specific crucial data. With the development of cryptocurrency, Ransomware is one of the emerging attacks that prevent authentic users from accessing systems, resources, or data and enables adversaries to control access to such information. This paper presents an Artificial Neural Network (ANN) based model that uses the 'Power Iteration' method and Portable Executable (PE) Headers to detect various types of Ransomware. We analyze the performance of the proposed model by experimenting with a dataset created using the PE files collected from multiple sources and demonstrate its better detection capability.. © 2023 IEEE.

关键词： Neural networks

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A Privacy Preserving Decision Tree Classification Algorithm for Prediction of Health Care Monitoring System 3rd

A Privacy Preserving Decision Tree Classification Algorithm ...

引用

3rd international conference on intelligent Systems and Sustainable Computing, ICISSC 2023

作者： Raj, Thaluka Mohan Maheswari, K. Raju, K. Srujan Shweta, N. Dharmireddi, Srinivasarao Reddy, Avala Raji Department of Computer Science and Engineering CMR Technical Campus Hyderabad India

ISBN: (纸本)9789819783540

In recent years, health monitoring systems have become popular due to increasing medical costs and advances in wireless technology. Organisations use information systems to develop and distribute information as well as gather, filter, and process data. Patients are responsible for sharing information with particular types of healthcare providers in order to make an accurate diagnosis and decide on the most appropriate model of treatment. In health monitoring systems, hospitals outsource clinical decision-making models to cloud service providers, who then use the models to make clinical decisions based on the biomedical information they receive from remote clients. Biomedical data as well as clinical decision-making models must be protected since privacy issues are extremely serious. An effective categorization technique for health monitoring systems using a privacy-preserving decision tree (PPDT) is given in this analysis. Decision tree classification with privacy preservation is carried out by using the encrypted token to search the encrypted index. According to a performance analysis, PPDT is extremely effective in terms of accuracy, time, storage, and communication. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electronic health record

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Revolutioning IIot: A Smart Appliance of an Internet of Things over Industrial Manufacturing Unit to Make Error-Free Circumstances

Revolutioning IIot: A Smart Appliance of an Internet of Thin...

引用

2024 international conference on Cybernation and Computation, CYBERCOM 2024

作者： Ravi, Kiran Chand Vaishnavi, T. Princy, Anni Kandaswamy, Vijay Anand Dinesh, M. Lakshmisridevi, S. MLR Institute of Technology Department of ECE Hyderabad India Vel Tech Rangarajan Dr. Sagunthala RandD Institute of Science and Technology Department of ECE Tamil Nadu Chennai India Panimalar Engineering College Department of Artificial Intelligence and Machine Learning Tamil Nadu Chennai India R.M.K. Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India Saveetha University Department of VLSI Microelectronics Tamil Nadu Chennai India Chennai Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331542344

A future where cyberspace and the real world are inseparable is the goal of the Internet of Things (IoT). The potential for the development of robust industrial services and applications, colloquially known as the Industrial Internet of Things (IIoT), is enormous. From the acquisition of raw materials to the provision of customer service and support, the Internet of Things (IoT) was utilized across numerous sectors by industries. The Internet of Things (IoT) offers a great opportunity to develop significant manufacturing-related services and applications, and it is widely regarded as a crucial technology of the industrial revolution. In addition, it facilitates communication between intelligent devices, allowing them to exchange information and data-crucial for complex systems to make decisions in the here-And-now. In this paper, a new method called Error-Free Smart Industrial control System (EFSICS) is introduced to improve the efficiency of industrial operations through the use of IIoT. To test how well this method works, it is cross-validated with the traditional model called Classical Industrial control System (CICS). Regarding the manufacturing aspects in particular, the suggested method is well-suited to the effects of the Internet of Things on sustainable development. Researchers are now at the forefront of cyber integrated manufacturing research, which will further illuminate the present state of the internet of things (IoT) in manufacturing. © 2024 IEEE.

关键词： Smart manufacturing

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The Fault Diagnosis System for Constant Wind Speed control Device based on Expert System

The Fault Diagnosis System for Constant Wind Speed Control D...

引用

2022 IEEE international conference on advances in Electrical engineering and computer Applications, AEECA 2022

作者： Lu, Haihua Cao, Weilin Huang, Zhuofan Chen, Sixiao Shen, Miaojie Chen, Liang Sun, Shunkai China Tobacco Zhejiang Industry Co. Ltd Ningbo Cigarette Factory Ningbo China

ISBN: (数字)9781665480901

ISBN: (纸本)9781665480901

The constant wind speed control device requires higher diagnostic ability for the characteristics of high integration, complex control structure and difficult maintenance. Therefore, an online fault diagnosis system based on expert system was proposed in this paper. Firstly, the knowledge base was established by using the knowledge and experience of domain experts, in order to build the fault tree model. Then through the working state monitoring of the constant wind speed control device, the inference engine was formed through the working status and fault tree model for forward and reverse reasoning. The testing results demonstrated that the proposed system could use sensor information and expert knowledge to infer the correct cause of the fault and improve the efficiency of fault diagnosis dramatically. © 2022 IEEE.

关键词： Fault detection

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A Predictive Approach For Assessing Medication Responsiveness in Breast Cancer Through Analysis of Gene Data

A Predictive Approach For Assessing Medication Responsivenes...

引用

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

作者： Gupta, Kimmi Singh, Jagendra Singh, Harender Pratap Singh, Manoj Kumar Gupta, Nitin Roohani, Basudeo Singh School of Computer Science Engineering & Technology Bennett University Greater Noida India Ghaziabad India Ims Engineering College Computer Science & Engineering Ghaziabad India S. D. College of Engineering and Technology Department of Cse Muzaffarnagar India

ISBN: (纸本)9798331527495

Breast cancer remains one of the leading causes of cancer-related deaths worldwide, with treatment responses varying wildly among patients. The inability to predict how an individual patient will respond to a given particular medication is an essential area in optimising treatment plans and better outcomes in such deadly diseases. This research aims to address the challenge of predicting medication responsiveness in breast cancer, analysing genomic data by exploiting publicly available datasets from both The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). The datasets are comprised of gene expression profiles, somatic mutations, and clinical data such as patient demographics, tumour subtypes, and treatment outcomes. Preprocessing involved cleaning and normalisation of gene expression values, imputation to address missing data, and selection of essential genes that were most relevant for drug response using feature selection techniques. Its dimensionality was reduced using Principal Component Analysis (PCA). Four machine learning models, including artificial neural networks (ANN), Convolutional Neural Networks (CNN), recurrent neural networks with long short-term memory (RNN-LSTM), and autoencoders, are used in this research. All models were trained, validated, and tested against accuracy, precision, recall, F1 score, and AUC-ROC in that the highest performance was achieved at 98.89% accuracy using the CNN model. The findings point towards the fact that deep learning models, especially CNN, open promising avenues for personalised breast cancer treatment. The findings, therefore, hold significant importance for the application of AI in precision medicine, potentially enabling more accurately targeted therapies, minimising side effects, and ultimately improving patient outcomes in oncology. © 2025 IEEE.

关键词： Long short-term memory

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Crack Detection Algorithm Based on Improved YOLOv11n Network

Crack Detection Algorithm Based on Improved YOLOv11n Network

引用

computer Science, Electronic Information engineering and intelligent control Technology (CEI), IEEE international conference on

作者： Yuxin He Ailing Ding School of Information Engineering Changan University Xi'an China

ISBN: (数字)9798350378542

ISBN: (纸本)9798350378559

The detection algorithms for various engineering structure cracks often suffer from missed detections, false positives, and low accuracy. This paper proposes an improved crack detection model based on Yolov11, integrating RFCBAM and Triplet Attention mechanisms. Experimental results show that this model performs better in detection compared to the original model and those improved by a single mechanism. The metrics for Precision (P), Recall (R), mAP 50 , and mAP 50−95 all reach high levels.

关键词： YOLO computer science Attention mechanisms Accuracy Sensitivity Target recognition Data mining Detection algorithms Monitoring intelligent control

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intelligent control Strategy of Power Grid Based on System Optimal Configuration 7

Intelligent Control Strategy of Power Grid Based on System O...

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7th international Symposium on advances in Electrical, Electronics, and computer engineering

作者： Zhang, Xiaohua Wang, Haikuan Ma, Yu State Grid Northeast Power Control Subcenter Shenyang110180 China Northeast Branch of State Grid Corporationg of China Shenyang110180 China State Grid Shenyang Electric Power Supply Company Shenyang110000 China

ISBN: (纸本)9781510656437

With the rapid development of the electricity market, the idea of improving the flexibility of the power system has gradually shifted to the load side. The load side is regulated by means of Demand Response (DR) so as to reduce the regulation pressure of the power supply side, change the situation that the traditional grid power supply passively follows the load change, and realize the two-way response of the source and load. Load is no longer a simple deterministic model but a probabilistic model. The power balance relationship will also be transformed from one-way type to source-load complementary type. In this paper, the effect of load side flexibility regulation means on the system optimization configuration of power supply side regulation capability is studied. The electricity price type and incentive demand side response are applied to the power grid to study the intelligent regulation strategy of the power grid to obtain the improvement of the flexibility performance of the power grid. On this basis, in view of the call priority of all kinds of flexibility resources, the adjustment ability and capacity ratio of all kinds of flexibility resources on both sides of the source and load are comprehensively considered to complete the priority division of flexibility resources on both sides of the source and load. © 2022 SPIE. All rights reserved.

关键词： Electric power system control

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