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检索条件"任意字段=International Conference on Computer and Automation Engineering"

共 58072 条记录，以下是4921-4930 订阅

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Towards in X-Ray Induced Acoustic Imaging for Nasopharyngeal Carcinoma Radiotherapy with a Multidimensional Information Fusion Network 3

Towards in X-Ray Induced Acoustic Imaging for Nasopharyngeal...

引用

3rd international conference on computer Applications Technology, CCAT 2024

作者： Jiang, Xin Chen, Zhi-Chao Sun, Zheng Liu, Ming-Zhe Chongqing University of Technology School of Artificial Intelligence Chongqing401135 China Chongqing University Cancer Hospital Department of Radiology Chongqing400030 China Chengdu University of Technology College of Nuclear Technology and Automation Engineering Chengdu610000 China Wenzhou University of Technology School of Data Science and Artificial Intelligence Wenzhou325000 China

ISBN: (纸本)9798331539795

X-ray-induced acoustic computed tomography (XACT) imaging is an emerging noninvasive imaging technique with wide applications in various clinical medicine fields. However, traditional XACT imaging methods often suffer from low imaging quality and increased noise artifacts, particularly notable under sparse sampling conditions. To overcome these challenges, we propose a hybrid supervised reconstruction method based on deep learning. Specifically, we extract and integrate information from XACT thermoacoustic signals and XACT images reconstructed by traditional methods to leverage complementary feature information from both modalities. To adapt to imaging under sparse sampling, we define multiple sparse conditions based on real-world imaging environments and validate them using a real radiotherapy dataset of head and neck cancer patients. The results demonstrate the adaptability of our method to sparse conditions and its capability to enhance XACT imaging quality under such circumstances. Additionally, we validate the feasibility of X-ray thermoacoustic imaging for 3D dose monitoring. © 2024 IEEE.

关键词： Radiotherapy

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Calculating System Health Metrics in Dynamic Environments

Calculating System Health Metrics in Dynamic Environments

引用

international conference on computer and automation engineering, ICCAE

作者： Shaine Christmas Robert Davidson Arkady Zaslavsky Kevin Lee School of Information Technology Deakin University Geelong VIC Australia Defence Science and Technology Group (DSTG) Edinburgh SA Australia

ISBN: (数字)9798331533816

ISBN: (纸本)9798331533823

System Health management is increasingly impor-tant for distributed or remote systems management. While some System Health management techniques make inferences based on collected data, these inferences do not support situational awareness. This work presents a methodology and framework for calculating System Health, allowing for the separation of inference and health calculation, while still supporting the application of contextual information to System Health. This work explores this framework with a theoretical example, and application to real-world datasets. System Health largely depends on the weightings of components, which places importance on weight assignment.

关键词： Measurement automation Resilience

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Data Crawling and Research Based on Topic Web Crawler 5

Data Crawling and Research Based on Topic Web Crawler

引用

5th international conference on computer Network, Electronic and automation, ICCNEA 2022

作者： Wang, Zhongsheng Lv, Jieyi Xi'an Technological University School of Computer Science and Engineering Shaanxi China State and Provincial Joint Engineering Lab. of Advanced Network Monitoring and Control No.2 Xuefu Middle Road Weiyang district Shaanxi Xi'an China

ISBN: (数字)9781665491099

ISBN: (纸本)9781665491099

With the popularity of big data, efficient acquisition of existing massive data and multi-angle analysis has become a key technology. In this paper, compared with the traditional general web crawler, the main web crawler strategy adopted in network crawling can be more efficient for grasping targets, so as to carry out data grasping operations more efficiently. Based on the film review data on ***, this paper analyzes and studies the film review data without damaging the operation of the website. By using jieba, matplotlib, wordcloud and other libraries in python library, data can be visualized into wordcloud map, pie chart and line chart, which is helpful for users to see key words and the proportion of favorable and negative comments in movie works directly, which is of great significance to users' preference selection. It also has certain reference significance for accurate software recommendation in the era of big data. © 2022 IEEE.

关键词： Python

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Improving Iris Recognition Systems With CNN Based Image Processing and Machine Learning Approach

Improving Iris Recognition Systems With CNN Based Image Proc...

引用

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

作者： Bhatnagar, Shaleen Raja, S.Pravinth Preeya, Amirtha Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Department of Computer Science and Engineering Manipal India Presidency University School of Cse & Is Karnataka Bengaluru India Presidency University School of Cse & Is Bangalore India

ISBN: (纸本)9798350317060

The principal advancement in iris biometric acknowledgment is the extraction of these striking highlights. The outcome of profound learning innovations can assist us with settling the issues we had with PC vision. The Iris acknowledgment framework has viewed the elements found through CNN as of extraordinary use. In most of validation and personality situations, biometric security confirmation is fundamental. Because of its predictable and astounding surface variety, iris acknowledgment is believed to be the most reliable biometric acknowledgment. While utilizing iris acknowledgment to recognize the people who need an elevated degree of safety, the particular examples are utilized. To work on the viability of acknowledgment, this examination researches a valuable strategy that utilizes support vector machines (SVM) and convolutional brain organizations (CNN) for highlight extraction and characterization, separately. The uniqueness and security of the iris design have made iris acknowledgment frameworks a hotly debated issue in biometric confirmation. This theoretical spotlights on creating iris distinguishing proof frameworks using machine learning and CNN-based image processing. © 2023 IEEE.

关键词： Biometrics

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Time Window Optimization for Riemannian Geometry-based Motor Imagery EEG Classification 46

Time Window Optimization for Riemannian Geometry-based Motor...

引用

46th Annual international conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Zhuo, Fanbo Lv, Bo Tang, Fengzhen Shenyang Institute of Automation The State Key Laboratory of Robotics Shenyang China Chinese Academy of Sciences The Institutes for Robotics and Intelligent Manufacturing Shenyang China The University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350371499

The existing Riemannian geometry-based approaches for brain computer interface (BCI) employ fixed time windows. However, the inherent variability and dynamic changes among subjects necessitate robust and adaptive solutions for time window optimization. Recognizing the current limitations of Riemannian classifiers, we propose a time window selection confidence metric (TWSCM) based on Riemannian geometry. This metric operates on the manifold of symmetric positive definite (SPD) matrices, providing a theoretically grounded and computationally efficient approach for time window optimization. The optimization process is unsupervised, which is able to deal with the online scenario without training labels. Experimental results on the BCI competition IV dataset IIa demonstrate that the classification performance is significantly improved for most subjects. The average performance over six subjects improved by 7.52%. The simulated online experiment shows enhanced performance in comparison to baseline experiments without time window optimization. Additionally, an in-depth analysis of TWSCM provides insights into performance variations among subjects. Overall, this paper introduces the first time window optimization method within the Riemannian geometric framework, presenting an effective and interpretable approach for optimizing time windows in motor imagery classification, providing a novel and promising perspective in EEG signal analysis. © 2024 IEEE.

关键词： Image enhancement

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Resource Allocation Algorithm for T2T and T2G Coexistence Scenarios in Urban Rail Transit 6

Resource Allocation Algorithm for T2T and T2G Coexistence Sc...

引用

6th international conference on computer Information Science and Application Technology, CISAT 2023

作者： Zhang, Ming Wang, Ruifeng Gao, Lei School of Automation and Electrical Engineering Lanzhou Jiaotong University Gansu Lanzhou730070 China Lanzhou Power Supply Company of State Grid Gansu Electric Power Company Gansu Lanzhou730070 China

ISBN: (纸本)9781510668546

A resource allocation strategy based on the improved Marine Predators Algorithm and KM algorithm is proposed to address the interference problem generated by spectrum multiplex in the coexistence scenario of Train to Train(T2T) communication and Train to Ground(T2G) communication in urban rail transit system while ensuring the user communication quality. First, the throughput optimization model under multiple constraints is developed and decomposed into two sub-problems of optimal power allocation and Channel Multiplex matching. Second, considering the problems of premature convergence and easy falling into the local optimum of the original MPA algorithm, a reverse learning strategy is used to optimize the initial population, improve the step size parameter and introduce the search balance parameter to improve the performance of the algorithm, and allocate optimize transmission power for T2T users and T2G users. Finally, the KM algorithm is used to find the best Channel Multiplex combination. Simulation results show that this algorithm improves the overall system throughput by 5.9% and 7.1% compared with Marine Predators Algorithm and Gray wolf optimization algorithm, significantly improving overall system communication performance. © 2023 SPIE.

关键词： Resource allocation

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Feedback-Based Quantum Algorithm for Constrained Optimization Problems 15th

Feedback-Based Quantum Algorithm for Constrained Optimizati...

引用

15th international conference on Parallel Processing and Applied Mathematics, PPAM 2024

作者： Abdul Rahman, Salahuddin Karabacak, Özkan Wisniewski, Rafal Automation and Control Section Department of Electronic Systems Aalborg University Aalborg Denmark Department of Mechatronics Engineering Kadir Has University Istanbul Turkey

ISBN: (纸本)9783031856990

The feedback-based algorithm for quantum optimization (FALQON) has recently been proposed to find ground states of Hamiltonians and solve quadratic unconstrained binary optimization problems. This paper efficiently generalizes FALQON to tackle quadratic constrained binary optimization (QCBO) problems. For this purpose, we introduce a new operator that encodes the problem’s solution as its ground state. Using control theory, we design a quantum control system such that the state converges to the ground state of this operator. When applied to the QCBO problem, we show that our proposed algorithm saves computational resources by reducing the depth of the quantum circuit and can perform better than FALQON. The effectiveness of our proposed algorithm is further illustrated through numerical simulations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Constrained optimization

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Soft Sensors for Industrial Applications: Comparison of Variables Selection Methods and Regression Models

Soft Sensors for Industrial Applications: Comparison of Vari...

引用

2023 international conference on Control, automation and Diagnosis, ICCAD 2023

作者： Leiria, Joana Salles, Rodrigo Mendes, Jerome Sousa, Pedro University of Coimbra Institute of Systems and Robotics Department of Electrical and Computer Engineering Coimbra3030-290 Portugal Oncontrol Technologies Rua Cidade Poitiers Coimbra3000-108 Portugal

ISBN: (纸本)9798350347074

The digitalization of industrial environments has enabled the development of tools that make the production process more efficient and safer. In this sense, the Soft Sensor (SS) plays a fundamental role. Through historical data and indirect measurements, it is possible to estimate the value of important variables that are difficult to measure. This paper presents the SS development process: data collection and pre-processing, variable selection, model selection for SS implementation, model training and testing, and performance evaluation. The selection of variables was made with the help of Pearson Correlation, Mutual Information, and fastTracker algorithm techniques. For the implementation of SS have been tested several models: Multiple Linear Regression, Ridge Regression, Least Absolute Shrinkage and Selection Operator, Elastic Net, Support Vector Regression and Gaussian Mixture Models. Four datasets were used to test the development of the SS. © 2023 IEEE.

关键词： Correlation methods

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Zero-Day Attack Detection and Prevention 7

Zero-Day Attack Detection and Prevention

引用

2023 7th international conference On Computing, Communication, Control And automation, ICCUBEA 2023

作者： Satam, Shruti Sanjay Patil, Akansha Anadrao Narkhede, Devyani Bhagwan Singh, Sumit Pulgam, Namita Ramrao Adik Institute of Technology D y Patil Deemed to Be University Department of Computer Engineering Maharashtra Navi Mumbai India

ISBN: (纸本)9798350304268

Cybercrime is complicated and ever-changing phenomenon. Malicious hackers are becoming more skilled, and they are attracting consumers as well as public and private institutions. As a response, extra defences are required. Since organizations began to use computers to do business, the complexity and financial consequences of cybercrime have grown. More and more hacks are based on software vulnerabilities, resulting in the disclosure of customer data and the destruction of the company image. One of the most difficult tasks in modern cybersecurity is protecting against zero-day attacks. Despite manufacturers improving their detection of zero-day exploits, the number of zero-day threats and their impact continues to rise. By the day, tools and tactics for building zero-day exploits, circulating them, and carrying out zero-day assaults become increasingly complex, pervasive, and simple to use. On the other hand, identifying and blocking ongoing thefts is becoming increasingly difficult due to the complexity of the systems that cybersecurity professionals are working with, as well as the advanced degree of encryption and complexity utilized by malicious programs. This means that there is an increasing demand for precise zero-day attack prevention and detection technologies. © 2023 IEEE.

关键词： Cybercrime Detection Prevention Zero-day attack

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Global-Local Transformer for Unsupervised Person Re-Identification 4

Global-Local Transformer for Unsupervised Person Re-Identifi...

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4th international conference on Artificial Intelligence and Electromechanical automation, AIEA 2023

作者： Xie, Meng-Si Chen, Si-Bao School of Computer Science and Technology Anhui University Hefei230601 China

ISBN: (纸本)9781510666412

Unsupervised person re-identification (Re-ID) focuses on studying the issues of person Re-ID in the open world where there are no available annotated labels for pedestrian images. The original transformer only learns global features. It ignores local features and fails to consider high-level local information on images. Therefore, we introduce a transformer-based multi-branch unsupervised person Re-ID framework, named GLTReID, with learning more robust features of pedestrian images. Specifically, we split the original transformer into one global branch and two local branches, with learning global and local features in parallel. The global branch learns global features of pedestrian images, and two local branches learn local features of different parts of pedestrian images. Numerous experiments are conducted on several person Re-ID datasets, including CUHK03, Market-1501 and MSMT17. Numerous experiments denote that our method is better than most unsupervised learning methods and unsupervised domain adaptation methods in person Re-ID. © 2023 SPIE.

关键词： Learning systems

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