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检索条件"任意字段=Proceedings of the 3rd International Conference on Control and Computer Vision"

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Time Delay Estimation Method for X-ray Pulsars Based on The Optimal Number of Bispectral Feature Points

Time Delay Estimation Method for X-ray Pulsars Based on The ...

引用

computer Communication and Artificial Intelligence (CCAI), international conference on

作者： Zhiwei Huang Hua Zong Yujia Xie Nuoqi Xu National Key Laboratory of Science and Technology on Aerospace Intelligent Control Beijing Aerospace Automatic Control Institute Beijing China School of Economics and Management Beijing Electronic Technology Vocational College Beijing China

To enhance the accuracy and efficiency of X-ray pulsars time delay estimation, a novel time delay estimation method for X-ray pulsars based on the optimal number of bispectral feature points is proposed. The approach establishes the relationship between the time delay estimation error and the number of bispectral feature points used under different signalto-noise ratios, and gives a method to determine the optimal number of bispectral feature points involved in the estimation. We conduct simulation experiments for HXMT-Insight satellite observations of the Crab pulsar on Matlab R2017b. Results indicate that the average running time of the proposed algorithm is 50ms and the average error during observation intervals below 50s is 99. 0083us. Compared to the traditional bispectrum method, the proposed algorithm exhibits slightly higher accuracy and significantly improved running time.

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Constant current water supply system design based on fuzzy PID control 3

Constant current water supply system design based on fuzzy P...

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3rd international conference on Intelligent control, Measurement and Signal Processing and Intelligent Oil Field, ICMSP 2021

作者： Liu, Cong Feng, Xuejie Xu, Lenian Guo, Chenglong College of Electronic Information Engineering Shandong University of Science and Technology Qingdao China

ISBN: (纸本)9781665437158

Aiming at the poor adaptive and limited application range of traditional PID control in constant current water supply system, a constant current water supply system based on intelligent control was designed. The electromagnetic flowmeter collected the real-time flow data, and the signal converter was designed to upload the real-time flow data to the upper computer. The real-time error and error change rate were obtained by comparing with the expected value of the flow. PLC controller realized the fuzzy PID control and adjusted the frequency converter in real time to get the steady flow rate more quickly. The simulation experiment is carried out by using Simulink in Matlab. The time of traditional PID control and fuzzy PID control to reach the steady flow is 17s and 11s respectively, and the fuzzy PID has a smaller overshoot. Compared with the traditional PID control, the fuzzy PID control has obvious advantages in adjustment time and overshoot, and the control effect is better and the practical value is greater. © 2021 IEEE.

关键词： Three term control systems

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A Study on Application of Artificial Intelligence in College English Teaching Management and Evaluation 3

A Study on Application of Artificial Intelligence in College...

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3rd international conference on Electronic InformationTechnology and Smart Agriculture, ICEITSA 2023

作者： Feng, Tao Deng, Jianjie Liu, Yiwen Gao, Yanxia Peng, Ling Fu, Jinrong School of Foreign Languages Huaihua University Hunan Huaihua418000 China School of Computer and Artificial Intelligence Huaihua University Hunan Huaihua418000 China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Hunan Huaihua418000 China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Hunan Huaihua418000 China School of Computing Science University of Glasgow GlasgowG12 8QQ United Kingdom

ISBN: (纸本)9798400716775

With the rapid development of artificial intelligence, AI technology has been widely applied in various industries, including education. In English teaching, AI technology provides teachers with objective and instructive feedback, offers students a more personalized learning experience, helping them improve their English language skills, etc., and brings new development opportunities and challenges to English teaching as well. However, there are still some problems that need to be solved in college English teaching in our university. For this reason, based on the application of AI technology in college English teaching, this paper mainly explores the impact and application countermeasures of AI on college English teaching from the following four aspects: individuals with differences, teaching management, classroom teaching and teaching evaluation. In addition, the profound integration of college English education and AI will foster the advancement and transformation of college English instruction, ultimately serving as a catalyst for its reform. © 2023 ACM.

关键词： Artificial intelligence

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Deep-OCTA: Ensemble Deep Learning Approaches for Diabetic Retinopathy Analysis on OCTA Images 25th

Deep-OCTA: Ensemble Deep Learning Approaches for Diabetic R...

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25th international conference on Medical Image Computing and computer-Assisted Intervention , MICCAI 2022

作者： Hou, Junlin Xiao, Fan Xu, Jilan Zhang, Yuejie Zou, Haidong Feng, Rui School of Computer Science Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai China Academy for Engineering and Technology Fudan University Shanghai China Department of Ophthalmology Shanghai General Hospital School of Medicine Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9783031336577

The ultra-wide optical coherence tomography angiography (OCTA) has become an important imaging modality in diabetic retinopathy (DR) diagnosis. However, there are few researches focusing on automatic DR analysis using ultra-wide OCTA. In this paper, we present novel and practical deep-learning solutions based on ultra-wide OCTA for the Diabetic Retinopathy Analysis Challenge (DRAC). In the first task of segmentation of DR lesions, we utilize UNet and UNet++ to segment three lesions with strong data augmentation and model ensemble. In the second task of image quality assessment, we create an ensemble of Inception-V3, SE-ResNeXt, and vision Transformer models. Pre-training on the large dataset as well as the hybrid MixUp and CutMix strategy are both adopted to boost the generalization ability of our models. In the third task of DR grading, we build a vision Transformer and find that the model pre-trained on color fundus images serves as a useful substrate for OCTA images. Extensive ablation studies demonstrate the effectiveness of each designed component in our solutions. The proposed methods rank 4th, 3rd, and 5th on the three leaderboards of DRAC, respectively. Our code is publicly available at https://***/FDU-VTS/DRAC. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Optical tomography

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Early Stage Skin Cancer Detection Using Image Processing

Early Stage Skin Cancer Detection Using Image Processing

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Pervasive Computing and Social Networking (ICPCSN), international conference on

作者： Lanke Govinda Rajulu Parul Madan Neeraj Varshney Dinesh Yadav Ashok Kumar Set Anil Thakur ResMed Digital Health Technology USA Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India Department of Computer Engineering and Applications GLA University Mathura Lloyd Institute of Engineering and Technology Greater Noida Quantum University Roorkee Uttarakhand India Lloyd Law College Greater Noida India

Early stage malignant cancer detection has gain utmost research importance in recent times. Carcinoma, which is currently acknowledged as the deadliest form of cancer in humans, appears in various types such as skin cancer, basal cell carcinoma, squamous cell carcinoma, and the relatively unexpected malignant melanoma. Timely identification of malignant melanoma is crucial for providing effective treatment. computer vision systems have played a significant role in medical image classification, offering valuable contributions in this field. In this study, we propose a computer-aided method that relies on images to detect melanoma, a type of skin cancer. The system takes an image of a skin lesion as input and employs innovative image processing techniques to assess and determine the presence or absence of skin cancer. By analyzing factors such as texture, size, and segmentation, lesion image analysis tools examine a wide range of features associated with melanoma, including spatial characteristics, contours, color, diameter, and more. Based on derived feature parameters, the images are classified as either indicating melanoma or representing benign skin lesions.

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Detecting Diabetic Retinopathy Using Deep Learning Techniques

Detecting Diabetic Retinopathy Using Deep Learning Technique...

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Intelligent Technologies (CONIT), international conference on

作者： Sreenivasa Sumadithya Fathima Nihla Latheef Mustafa Sameer Rubell Marion Lincy G Department of Computer Science and Engineering Indian Institute of Information Technology Kottayam Kottayam India Department of Mathematics Indian Institute of Information Technology Kottayam Kottayam India Department of Electronics and Communication Engineering National Institute of Technology Patna Patna India

Diabetic Retinopathy (DR) is a common complication of diabetes that can lead to vision loss. Diabetic Macular Edema (DME) is a related condition where fluid accumulates in the macula, leading to retinal thickening. Early detection of both DR and DME is critical for effective treatment. However, current detection methods are timeconsuming and challenging. In this paper, we propose a novel approach using Capsule Networks and GAN to automatically detect and classify DR and DME using retinal images. We also investigate the correlation between the two conditions and develop a cross-disease grading system using image-level supervision. Our proposed model is tested on two publicly available datasets, Messidor and IDRiD, and achieves promising results. Our approach represents a significant advance in the automated detection of DR and DME using deep learning techniques.

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Capacitor-Current PID Feedback control Method for Grid-Connected Inverter to Improve System Stability and Harmonic Rejection Ability

Capacitor-Current PID Feedback Control Method for Grid-Conne...

引用

Power Electronics, computer Applications (ICPECA), IEEE international conference on

作者： Cui Xie Jianze Wang Jiakun Xie Yue Guo Xu Liu School of Electrical Engineering & Automation Harbin Institute of Technology Harbin China

The wide variation of the grid impedance can easily cause system resonance or even system instability of LCL-type grid-connected inverter in weak grid, and the injected grid current is severely distorted due to grid voltage harmonics. To address this issue, a capacitor-current PID feedback control method is proposed in this paper to correct inverter system impedance. It makes the output impedance of inverter and the equivalent virtual impedance of the filter capacitor in parallel have a nonnegative real part within the Nyquist frequency, while increasing the inverter output impedance’s low-frequency gain. Then, the design guideline for the parameters of capacitor-current PID feedback coefficient is given. The proposed method has the ability to significantly enhance system stability and harmonic suppression capability, simultaneously enhancing system robustness to variation in grid impedance. Finally, simulation results verify the effectiveness of the proposed method and parameter design.

关键词： Design methodology Simulation Power system stability Harmonic analysis Inverters Stability analysis Robustness

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Real – Time Accident Alerting System Using Convolutional Neural Network

Real – Time Accident Alerting System Using Convolutional Ne...

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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), international conference on

作者： Yogapriya M K. Nagarathna Mahalakshmi Natarajan S. Asvin Department of CSE-AIML Chennai Institute of Technology Chennai Tamil Nadu Department of CSE Chennai Institute of Technology Chennai Tamil Nadu Department of BME Chennai Institute of Technology Chennai Tamil Nadu Department of CSE-AIML Thiagarajar college of engineering Madurai Tamil Nadu

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

The purpose of the research is to solve the problem by utilizing easily accessible devices and equipment in order to make a safety mechanism at a significantly reduced cost. The system offers one of its benefits, which includes a smart camera with wireless control, night vision, tracking, and human detection. This particular system utilizes night vision in the detection of minor and major traffic accidents on the highways. It then passes the information to the control room and transmits picture footage to the database for verification. The system is orientated to allow 360-degree sensing. It will be built with a time latency of at least 30 seconds in order to view the mishaps and establish that they were serious ones. This can be made to store the information onto the cloud without the problems of space mishaps of data loss. With the application of CNN's deep learning algorithm along with Python programming, it is possible to locate the accident location precisely and alert the emergency services immediately. This paper is focused on safety precautions taken once the accident has been detected. This means that there is a necessity to save precious human life by having this implemented in real life.

关键词： Night vision Wireless sensor networks Smart cameras Programming Sensors Convolutional neural networks Servers Smart phones Accidents Vehicles

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In-depth Analysis of Interior Gateway Protocols in a Large-scale Enterprise Topologies

In-depth Analysis of Interior Gateway Protocols in a Large-s...

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Sciences and Techniques of Automatic control and computer Engineering MI-STA, IEEE international Maghreb Meeting of the conference on

作者： Saleh Hussein Al-Awami Ali Tahir Abu Raas Emad Awadh Ben Srity Department of Data Communications and Computer Networks University of Benghazi Benghazi Libya

Interior gateway protocols are among the routing protocols with the fastest expanding usage in networking technologies because they provide features that enable these algorithms to communicate together in a standard and flexible way. Network devices communicate through internal gateway protocols in autonomous systems (AS). This paper makes a contribution in this field using (Graphical Network Simulator) GNS3 version 2.2.34 software to simulate a ten-router setup to mimic a complex real-time enterprise-level network. Every protocol is put into practice using the intended ***/Statistical Analysis: The interior gateway, Open Shortest Path First (OSPF), Enhanced Interior Gateway Routing Protocol (EIGRP), and Intermediate System to Intermediate System (IS-IS) are in-depth analyzed in a complex enterprise-level network, which made up to 30 multiple paths of routing data packets for each examined routing protocol, with consideration of link failure while employing various network ***: End-to-end delay, jitter, and convergence time for each protocol have been measured for comparison in a large-scale (a complex enterprise) fixed topology. Finding the best practical interior gateway routing protocol is the study's main goal.

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Don't Walk Away! Virtual Safety Boundaries for Collaborative Virtual Reality Learning Environments 53

Don't Walk Away! Virtual Safety Boundaries for Collaborative...

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53rd IEEE ASEE Frontiers in Education international conference, FIE 2023

作者： Araya, Raquel Cabrera Chen, Yanwen Rojas-Muñoz, Edgar School of Performance Visualization & Fine Arts Texas A&m University College StationTX United States

ISBN: (纸本)9798350336429

This Work-in-Progress Research paper explores how to design and implement Collaborative Virtual Reality Learning Environments (CVRLE) taking Teacher-Student Dynamics (TSD) into account. CVRLEs engage students in a virtual representation of a learning space. However, they do not incorporate TSDs, which are key elements of in-person teaching. The current work explores how to recreate one specific TSD: the watchfulness teachers have over the students' location during a field trip. We propose and compare seamless approaches to recreate this TSD inside CVRLEs via virtual safety boundaries around the teacher. These boundaries keep students in proximity to their instructor as they explore the CVRLE. The current work explores five approaches: 1) an invisible wall (used as baseline), 2) sound-based feedback, 3) a virtual companion, 4) a translucent rope connected to the teacher and 5) a translucent dome mesh around the teacher. The approaches were validated by five middle school teachers, who provided feedback about them from an educator's point of view. The interviews highlighted the importance of subtle and simple approaches that provide a sense of freedom to the students and minimize cognitive load while maintaining the TSDs. Overall, the vision of this Work-in-Progress is to solidify CVRLEs into a plausible method to perform teaching and learning when co-presence between teacher and students cannot be guaranteed. The design guidelines from this project will inform the creation of future interactive CVRLEs. © 2023 IEEE.

关键词： Human-computer Interaction Learning Environments User Experience Virtual Reality

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