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

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Deep Learning Classification and Segmentation of Brain MRI Images

Deep Learning Classification and Segmentation of Brain MRI I...

引用

2023 international conference on New Frontiers in Communication, automation, Management and Security, ICCAMS 2023

作者： Pooja Ahuja, S. Likhith, S.R. Shiva Balan, A. Navya, K. Bengaluru India Bio-intelligence Lab Presidency University Department of School of Computer Science and Engineering and Information Science Bengaluru India Nagarjuna College of Engineering and Technology Department of Ise Bengaluru India

ISBN: (纸本)9798350317060

Unique Clinical pictures have a basic impact on the specialist's capability to the right conclusion and in the treatment of the patient. Diagnostic imaging can quickly identify lesions thanks to sophisticated algorithms, and it is essential to glean characteristics from photographs. In a number of studies, a number of algorithms have been incorporated into imaging in medicine. Using convolutional neural network, CNN's fundamental architecture is constructed using picture component extraction. To be able to circumvent the limitations imposed by both machine vision and human vision, the study is extended to include CNN with multiple input channels for visual feature extraction. This study uses approximately 3300 MRI samples from Kaggle to investigate four classifications: tumors of the pituitary gland, meningioma, glioma, and none. The implemented BrainNet has a accuracy of 98.31 percent and a validation accuracy of 87.80 percent. In order to determine which strategy performed better, deep architectures like InceptionNet and ResNet were also put through tests with or without learning through transfer. © 2023 IEEE.

关键词： Image segmentation

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Prediction and Analysis of Various Cyber Attack Models in Cyber Physical System in Virtual Environment 2

Prediction and Analysis of Various Cyber Attack Models in Cy...

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2nd international conference on Augmented Intelligence and Sustainable Systems, ICAISS 2023

作者： Dutta, Chiranjit Maheswari, M. Saravanan, K.G. Dhaliwal, Navdeep Pandey, Akhilesh Sophia, S. Srm Institute of Science and Technology Department of Computer Science and Engineering Uttar Pradesh Ghaziabad India Dmi College of Engineering Department of Information Technology Tamil Nadu Chennai India Sona College of Technology Department of Mechanical Engineering Tamil Nadu Salem India Lovely Professional University Division of Research and Development Punjab Phagwara India Uttaranchal University Division of Research and Innovation Uttarakhand Dehradun India Karunya Institute of Technology and Sciences Department of Computer Science and Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9798350325799

The Cyber Physical System (CPS) is referred as the amalgamation of physical system with control system mechanisms. CPS is largely used in versatile process from automation, controlling and monitoring process. This is the process of converting the physical system into a digital platform through sensing, data storage and monitoring process. Due to the advancement in the Internet of Things (IoT), the cyber security has become a complex parameter. Thus they need to be considered. To overcome the constraints, the machine learning is implemented to provide security concerns for the cyber physical systems. The machine learning provides a platform for the intrusion detection system. The machine learning helps in the classification and detection of the cyber-attacks. This is done through the optimization techniques, which helps to provide the solution for reducing the complexity. The internet of system paved way for the sensing, control, monitoring and communication of information. The attacks in the networking system are identified through the machine learning that enable smart applications in diverse fields. © 2023 IEEE.

关键词： Cyber Physical System

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Fault Diagnosis of Electric Drive Systems Based on Dynamic Independent Component Analysis and A Hidden Markov Model 8

Fault Diagnosis of Electric Drive Systems Based on Dynamic I...

引用

8th IEEE international conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Wang, Jingkun Wang, Hongmei Cheng, Chao Chen, Hongtian School of Computer Science and Engineering Changchun University of Technology Changchun China Shanghai Jiao Tong University Department of Automation Shanghai China

ISBN: (纸本)9798350300178

Due to the rapid development of high-speed trains, the fault diagnosis of electrical drive systems is a hot issue. A fault diagnosis method for electrical drive systems based on dynamic inner independent component analysis and the hidden Markov model is proposed. First, the offline data of the electric drive systems under different operating states are processed by using the dynamic inner independent component analysis algorithm. The dynamic features in the offline data are extracted by establishing equations that maximize the non-Gaussianity of the predicted latent variables. Second, these dynamic features are used to train a Hidden Markov Model to represent various states of the electric drive systems. Finally, the online data are injected into the Hidden Markov Model for fault diagnosis, and the experimental results on the electric drive systems simulation platform show the effectiveness of the method. © 2023 IEEE.

关键词： Failure analysis

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Evolutionary Algorithms and Fuzzy Systems for Enabling Smart Technologies across Industries 1

Evolutionary Algorithms and Fuzzy Systems for Enabling Smart...

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1st IEEE international conference on Emerging Research in Computational science, ICERCS 2023

作者： Refonaa, J. Poornima, D. Shabu, S.L. Jany Kanipriya, M. Surya, V. Sathyabama Institute of Science & Technology Department of Computer Science and Engineering Chennai India Srmist Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350359756

Smart technology have end up an increasing number of vital in today's rapidly evolving generation panorama. automation, records-pushed decision-making, and streamlined operations are all being revolutionized by means of the usage of clever era. However, there are some of boundaries that save you their effective deployment, which include as converting conditions, complicated device interactions, and the requirement for instantaneous flexibility. Fuzzy Logic Control for Smart technology Optimization (FLC-STO) is a way that makes use of the complementary nature of Evolutionary Algorithms and Fuzzy Systems (EA-FS) to achieve optimization in smart era. FLC-STO is a dynamic and adaptive technique for optimizing smart generation for maximum performance over a great form of situations. FLC-STO has proven to be powerful via simulation evaluation in optimizing smart generation in practical settings. It demonstrates how the proposed method works in workout, demonstrating how common performance, performance, and flexibility are all improved in the face of dynamic surroundings and complex interactions. The FLC-STO method gives a effective framework for permitting and optimizing clever generation throughout industries due to its fusion of Evolutionary Algorithms and Fuzzy Systems. The studies presented here allows to enhance clever technology and encourage their fashionable reputation with the aid of addressing the difficulties confronted with the aid of converting contexts, complex gadget interconnections, and the need for actual-time variation. © 2023 IEEE.

关键词： Evolutionary algorithms

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Structure and Content of the Quantum Architectures (Q-AR) Knowledge Unit (KU) Proposal for the CS2023 Report: Curricular Maps and Analysis of Industry Feedback 2023

Structure and Content of the Quantum Architectures (Q-AR) Kn...

引用

28th Annual conference on Innovation and technology in computer science Education (ITiCSE)

作者： German, Dan-Adrian Pias, Marcelo Xiang, Qiao Chen, Pei-Ying Indiana Univ Luddy Sch Informat Comp & Engn Bloomington IN 47405 USA Fed Univ Rio Grande Comp Sci Ctr C3 Rio Rande RS Brazil Xiamen Univ Sch Informat Xiamen Fujian Peoples R China

ISBN: (纸本)9798400701399

Continuing a process that began more than 50 years ago with the publication of Curriculum 68 ACM, IEEE-computer Society and AAAI have sponsored five efforts to establish international curricular guidelines for undergraduate programs in computing on a roughly 10-year cycle. Over the last 15 years significant advances in quantum technologies have led to a new awareness about their impact on computing (QC). There are now 60 companies worldwide that build quantum computers. In the US the Quantum Economic Development Consortium (QED-C) was created in 2018 to accelerate the quantum industry by establishing a robust supply chain and infrastructure, including workforce and standards. But the continued absence of any serious education in quantum mechanics in a large fraction of traditional US engineering programs, including computer engineering and the closely related CS and data science programs, present many BS degree STEM graduates with the daunting problem of how to get trained quickly and efficiently to pursue the new opportunities in Quantum Information science and technology (QIST). To address this issue the ACM Board of Education has teamed up with the QED-C Workforce Development TAC and has developed (for the first time ever and over a period of 18 months) a Quantum Architectures (Q-AR) Knowledge Unit (KU) for CS2023. In November 2022 we asked the QED-C members (industry, academia, national labs, and government agencies) to comment on the proposed competency-based curricular plans along with the selected topics and learning outcomes. We present the analysis of the data we collected during that process.

关键词： quantum architectures for the CS undergraduate curriculum

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Research on Vertical Guidance and Mode Switching Control technology of Helicopter Flight Management System 2

Research on Vertical Guidance and Mode Switching Control Tec...

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2nd international conference on Artificial Intelligence and computer Information technology, AICIT 2023

作者： Zhai, Mo Chen, Hongzheng Tian, Jia Sheng, Shouzhao College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (纸本)9798350302950

In view of the development requirements of civil helicopter flight management system and the problem of vertical guidance and control, the typical sub-modes of vertical guidance were analyzed, and the guidance law was designed. Then, based on the theory of finite state machine, the Stateflow tool is used to study the management of vertical guidance mode switching logic. Finally, considering the problem of control channel switching in the process of mode switching, the smooth mode switching technology with rate limit and amplitude limit is developed, which provides method guidance and experimental basis for the vertical profile design of civil aircraft flight management system. The experimental results show that the proposed method is reasonable and feasible, and has certain theoretical and practical value. © 2023 IEEE.

关键词： Air navigation

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Driving behavior recognition method based on trajectory data detected by millimeter wave radar 3

Driving behavior recognition method based on trajectory data...

引用

3rd international conference on Consumer Electronics and computer Engineering, ICCECE 2023

作者： Zhang, Rui Liu, Haiqing College of Transportation Shandong University of Science and Technology Qingdao China College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China

ISBN: (纸本)9798350331578

In this paper, a multi-step vehicle driving behavior recognition method based on roadside millimeter-wave radar detecting trajectory data is proposed. The time and vehicle radial speed in trajectory data are selected as characteristic parameters. By analyzing the characteristic parameters of vehicles, different vehicle driving behaviors are classified. The proposed method marks and judges single driving behaviors, continuous driving behaviors, and complete driving behaviors in the state of RA (rapid acceleration), RD (rapid deceleration), GA (general acceleration), GD (general deceleration), and CS (constant speed) by calculating acceleration, interval time, and duration. The identification of vehicle driving behavior is completed finally. Using the vehicle trajectory data of continuous traffic flow scenarios at urban signal intersections as a sample, the established recognition method is applied for recognition and the results are compared with the actual driving behaviors of the sample. The identification results are consistent with the driving behavior reflected by the sample time-speed variation curves. It shows that the identification method proposed in this paper can effectively identify five types of driving behavior, and the accurate identification results of vehicle driving behavior have significance for traffic safety and traffic congestion improvement decision-making. © 2023 IEEE.

关键词： Vehicles

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Improvement of Social Force Model Based on Expected Rate Model 23

Improvement of Social Force Model Based on Expected Rate Mod...

引用

23rd IEEE/ACIS international conference on computer and Information science, ICIS 2023

作者： Chen, Boyu Hu, Xuesong Du, Jinfu School of Automation Wuhan University of Technology Wuhan China

ISBN: (纸本)9798350345841

The social force model is one of the most commonly used models for microscopic modeling of pedestrian movement and crowd evacuation. A large number of researchers have conducted continuous research on it, which makes the social force model suitable for pedestrian movement and crowd evacuation modeling in a variety of complex environments. The prerequisite for the effective use of the social force model in actual scenarios is the need to check and verify the social force model according to the application scenario. Therefore, it is necessary to confirm the correct realization of the social force model structure from the perspective of theory and practical application. The expected velocity parameter has an important impact on the movement of the crowd, including evacuation time and flow rate, so the expected velocity also needs to be considered during model validation. In addition, the performance of the social force model is also sensitive to the expected rate, measured by entropy. However, research and analysis on the desired rate setting is still lacking. In this paper, the optimal selection of the expected rate sub-model in the social force model is carried out in a data-driven manner, so that the social force model can more realistically reflect the movement of crowds, so that it can be better used in crowd control based on modeling and simulation. © 2023 IEEE.

关键词： Data Driven Expected rate model social force model

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Simulation of Nuclear Reactor Accident Scenarios using Physics-Informed Neural Networks and Transfer-Learning 4

Simulation of Nuclear Reactor Accident Scenarios using Physi...

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4th international conference on Electronic Information Engineering and computer science, EIECS 2024

作者： Yu, Yang Xie, Yufei Wang, Wenlin Wu, Guohua Lan, Haitao Lin, Enbo An, Ping Sun, Zibin Zhang, Haichuan Wu, Yixian National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing Changsha China Nuclear Power Institute of China Science and Technology on Reactor System Design Technology Laboratory Chengdu China School of Automation Wuhan University of Technology Wuhan China Sino-German College of Intelligent Manufacturing Shenzhen Technology University Shenzhen China Institute of Automotive Engineers Hubei University of Automotive Technology Shiyan China Nuclear Power Institute of China Chengdu China

ISBN: (纸本)9798331531409

In a Loss of Coolant Accident (LOCA), reactor core temperatures can rise rapidly, leading to potential fuel damage and radioactive material release. This research presents a groundbreaking method that combines the power of Monte Carlo Sampling and Physics-Informed Neural Networks (PINNs) to simulate and effectively address the challenging Loss of Coolant Accidents (LOCA) in nuclear reactors. In the event of a LOCA, reactor core temperatures can soar rapidly, posing a significant threat to fuel integrity and potentially leading to the release of radioactive materials. By leveraging the strengths of both Monte Carlo Sampling and PINNs, this approach aims to provide a comprehensive and accurate simulation framework for assessing and mitigating the consequences of such accidents. The method yields high prediction accuracy (MAE: 0.033, RMSE: 0.098, R2: 0.814) and demonstrates robustness through transfer learning, maintaining strong performance (MAE: 0.064, RMSE: 0.163, R2: 0.735). © 2024 IEEE.

关键词： Coolants

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Application of X-ray fluorescence technology in lithology discrimination

Application of X-ray fluorescence technology in lithology di...

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2023 international conference on computer Application and Information Security, ICCAIS 2023

作者： Liu, Guili Zhai, Juan Zhang, Wei Lai, Wanchang Zhao, Ziqi Li, Wen Wang, Guangxi Yang, Qiang Chen, Ran College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu610059 China Chengdu Institute of Product Quality Inspection Co. Ltd. Sichuan Chengdu610100 China Chengdu Zhongfu Technology Co. Ltd. Sichuan Chengdu610100 China

ISBN: (纸本)9781510675032

X-ray fluorescence data are not only an important indicator in petroleum exploration, but they are also an advantage in lithology discrimination. From the perspective of the application of nuclear technology in drilling and exploration, in this paper, the X-ray fluorescence count rate of the core is used as the basic data for core logging, and the geology and multivariate statistical data are analyzed to analyze the lithology of the core. X-ray fluorescence analysis can provide the fluorescence count rates of 35 elements in a core sample. If there are n core samples, an n*35 matrix can be created. If 35 types of fluorescence count rates are used as the independent variables to directly identify the lithology, the dataset is very large, and some of the independent variables are not strongly correlated. Therefore, the discrimination effect is insufficient for achieving the purpose. Therefore, based on the diagenetic characteristics of sedimentary rocks and the main rock-forming elements and using multivariate statistical methods, in this paper, the count rates of five elements (i.e., Si, Fe, Al, K, and Ca) are selected as independent variables for the lithology discrimination. It is reasonably transformed to obtain the matrix coefficients before dimensionality reduction. The original five-dimensional dataset is reduced to two dimensions using matrix coefficients. Then, Fisher's discriminant method is applied to the dimensionally reduced data to discriminate and classify the lithology. Based on the discrimination results, the X-ray fluorescence count rate and mathematical statistics can be used to obtain a good effect in lithology discrimination. © 2024 SPIE.

关键词： Lithology

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