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Computer, Vision and intelligent Technology (ICCVIT), International Conference on

作者： Xia Zhang Wenfen Zhang College of Computer and Artificial Intelligence Xiangnan University Chenzhou China The Hunan Engineering Researcher Center of Advanced Embedded Computing and Intelligent Medical Systems Chenzhou China

ISBN: (数字)9798331540043

ISBN: (纸本)9798331540050

In order to solve the problems of daily medication and health and safety care for the elderly, this paper uses the Internet of Things technology to design and implement a home medicine box AI system based on Raspberry PI, which is composed of three parts: medicine cabinet management system, electronic bracelet system and wechat mini program. The medicine cabinet control system utilizes Raspberry PI 4b as the central processing unit, incorporating a timing sensor, voice sensor, and temperature and humidity sensor. The electronic bracelet's control system utilizes STM32 as the primary control board, while the development board incorporates a dual-mode positioning sensor, cardiovascular oxygen sensor, voice module, network module, and six-axis acceleration sensor interconnected with dupont wires. The electronic bracelet control system facilitates functions such as positioning, heart rate acquisition, voice broadcasting, wireless communication, and attitude acquisition. The mobile WeChat mini program enables remote monitoring and control of medicine cabinets and the health status of elderly individuals, providing functions such as temperature and humidity monitoring, timed voice medication reminders, heart rate monitoring, posture monitoring, and positioning. The test results demonstrate the system's stability and reliability, thereby providing robust technical support for home monitoring.

关键词： Temperature sensors Temperature measurement Heart rate Social networking (online) Humidity Message services Control systems Real-time systems Older adults Monitoring

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Admission Experts based on Android+VR, AR Technology and Voice Operation 22

Admission Experts based on Android+VR, AR Technology and Voi...

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Proceedings of the 6th International Conference on Digital Technology in Education

作者： Juan Xiao Weichen Yang Faying Li School of Computer and Artificial Intelligence Xiangnan University China and Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems Xiangnan University China Xiangnan University China

ISBN: (纸本)9781450398091

With the improvement of people's living standards and the increasing abundance of materials, acceptance has become an indispensable part of people's life. Nowadays, the application of smartphone is more and more widely used. A mobile APP based on Android system with the theme of acceptance is developed. Augmented Reality (AR) and Virtual Reality (VR) technologies as well as voice operation functions are applied to bring users a technological, convenient and novel experience of acceptance.

关键词： Admission Experts Voice Operation Virtual Reality (VR) Technology Augmented Reality (AR) Technology Android

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Semivortex solitons and their excited states in spin-orbit-coupled binary bosonic condensates

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Physical Review E 2024年第6期109卷 064201-064201页

作者： Haiming Deng Jinqing Li Zhaopin Chen Yaohui Liu Dong Liu Chunzhi Jiang Chao Kong Boris A. Malomed School of Physics and Electronic-Electrical Engineering Microelectronics and Optoelectronics Technology Key Laboratory of Hunan Higher Education Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems Physics Department and Solid-State Institute Department of Physical Electronics School of Electrical Engineering Faculty of Engineering Instituto de Alta Investigación

It is known that two-dimensional two-component fundamental solitons of the semivortex (SV) type, with vorticities (s+,s−)=(0,1) in their components, are stable ground states (GSs) in the spin-orbit-coupled (SOC) binary Bose-Einstein condensate with the contact self-attraction acting in both components, in spite of the possibility of the critical collapse in the system. However, excited states (ESs) of the SV solitons, with the vorticity set (s+,s−)=(S+,S++1) and S+=1,2,3,..., are unstable in the same system. We construct ESs of SV solitons in the SOC system with opposite signs of the self-interaction in the two components. The main finding is stability of the ES-SV solitons, with the extra vorticity (at least) up to S+=6. The threshold value of the norm for the onset of the critical collapse, Nthr, in these excited states is higher than the commonly known critical value, Nc≈5.85, associated with the single-component Townes solitons, Nthr increasing with the growth of S+. A velocity interval for stable motion of the GS-SV solitons is found too. The results suggest a solution for the challenging problem of the creation of stable vortex solitons with high topological charges.

关键词： Solitons

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Multi layer segmentation method for ophthalmic OCT images based on Gabor filtering 23

Multi layer segmentation method for ophthalmic OCT images ba...

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2023 International Conference on Computer, Vision and intelligent Technology, ICCVIT 2023

作者： Liu, Jiayike Li, Qingbo Liu, Ailin Liu, Dong Liu, Yang Zhang, Tianqiao School of Information and Communication Guilin University of Electronic Technology Guilin541000 China School of Computer and Artificial Intelligence Xiangnan University Chenzhou423000 China Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems Xiangnan University Chenzhou423000 China School of Life and Environmental Sciences Guilin University of Electronic Technology Guilin541000 China

ISBN: (纸本)9798400708701

Optical coherence tomography is a non-destructive optical signal acquisition and processing method for imaging surface tissue structure. OCT has become an important and innovative corneal measurement and diagnostic technology. Propose a multi-layer detection method for ophthalmic OCT retinal images. Firstly, perform 2D Gabor filtering on the OCT image, then binarize the filtered image, and finally perform eight neighborhood contour localization. To provide reference for the quantitative analysis of the thickness of different physiological layers in the anterior segment in the clinical diagnosis and lesion assessment of ophthalmic diseases. © 2023 ACM.

关键词： Optical tomography

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SVM in Classification of stage 0~II and III~IV with Breast Cancer : A Retrospective Cohort Study on a bicentric cohort 23

SVM in Classification of stage 0~II and III~IV with Breast C...

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2023 International Conference on Computer, Vision and intelligent Technology, ICCVIT 2023

作者： Guo, Yeang Tao, Tan Ronglin, Ronglin Xiao, Liangfen Ding, Lijuan Li, Qing Xie, Hui Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems Xiangnan University Chenzhou423000 China School of Medical Imaging Laboratory Science and Rehabilitation Xiangnan University Chenzhou423000 China Faulty of Applied Sciences Macao Polytechnic University 999078 China Department of Radiation Oncology The Third People's Hospital of Chenzhou City Chenzhou423000 China of Xiangnan University Chenzhou423000 China

ISBN: (纸本)9798400708701

Objective: The objective is to develop a predictive model utilizing Support Vector Machines (SVM) for the purpose of classifying the clinical stage of breast cancer. Materials and Methods: Accurate determination of the clinical stage of breast cancer patients holds significant importance in selecting suitable treatment options and minimizing avoidable complications. In this study, we present the application of radiomics and SVM for breast cancer computed tomography (CT) to anticipate the preoperative clinical stage in breast cancer patients. The training dataset encompasses 166 cases obtained from the Affiliated Hospital of Xiangnan University, while the test dataset comprises 91 cases from Chenzhou Third People's Hospital. The integration of clinical parameters with radiomics exhibits the most superior diagnostic efficacy in forecasting the clinical stage of breast cancer. As part of the evaluation, various metrics were calculated, including the area under the curve (AUC), the accuracy (ACC), sensitivity (Sen), specificity (Spe), positive predictive value (PPV) and negative predictive value (NPV). To differentiate between the radiomics model, clinical data model, and fusion model, the Delong test was utilized. The precision of the prediction model was evaluated by generating a calibration curve using 1,000 bootstrap weight samples. Furthermore, the decision curve analysis (DCA) was conducted to assess the model's practicality. Results: The fusion model exhibits superior predictive performance compared to both the single radiomics model and clinical model. The fusion model's test sets of AUC, ACC, Sen, Spe, PPV, and NPV are 0.824, 0.780, 0.932, 0.652, 0.707, and 0.909, respectively. Conclusion: The fusion model exhibits greater efficacy than both the single radiomics model and clinical model, and thus holds significant potential for facilitating the diagnosis of breast cancer stage and the development of individualized treatment *** © 2023 ACM.

关键词： Classification (of information)

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Design and Application of Innovative Cluster Education System Based on Artificial Intelligence Algorithm

Design and Application of Innovative Cluster Education Syste...

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Knowledge engineering and Communication systems (ICKECS), International Conference on

作者： Li Wei Hui Xie Ramachandra A C School of Computer and Artificial Intelligence Xiangnan University Chenzhou Hunan China Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems Chenzhou Hunan China Department of Electronics and Communication Engineering Nitte Meenakshi Institute of Technology Bengaluru India

After entering the Internet era, people are increasingly digitized and algorithmized. Technology platforms often use their technical advantages in data processing and algorithms to generate an implicit right of dominance and control, thus forming a unique artificial intelligence algorithm. Operational logic. The unique operational logic of artificial intelligence algorithms is profoundly changing the previous production methods and lifestyles. As a modern transformation model of concentrated industrial development, industrial clusters have created a special entrepreneurial environment, and their advantages in resource concentration can also help young entrepreneurs increase their chances of success. With the vigorous development of my country's information technology and artificial intelligence algorithms, its derivative services, technologies and their impact on the social market have further promoted the demand for market innovation. Based on the impact of artificial intelligence algorithms on the social market, this study defines the mutual promotion of “professional +” innovation and entrepreneurship education and the development of innovative industry clusters from the background of innovation industry clusters. On the basis of clarifying the positive role of innovation industry cluster system in innovation and entrepreneurship education, this research explores the practice form of innovation and entrepreneurship education system in colleges and universities that is more in line with the needs of innovation industry cluster talent development.

关键词： Industries Knowledge engineering Technological innovation Education Entrepreneurship Clustering algorithms Production

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MR2CPPIS: Accurate prediction of protein–protein interaction sites based on multi-scale Res2Net with coordinate attention mechanism

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Computers in Biology and Medicine 2024年 176卷 108543-108543页

作者： Gong, Yinyin Li, Rui Liu, Yan Wang, Jilong Cao, Buwen Fu, Xiangzheng Li, Renfa Chen, Danny Z. College of Computer Science and Electronic Engineering Hunan University Changsha410082 China Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems Hunan University Changsha410082 China Peng Cheng Laboratory Shenzhen518066 China College of Information and Electronic Engineering Hunan City University Yiyang413002 China Department of Computer Science and Engineering University of Notre Dame Notre DameIN46556 United States

Proteins play a vital role in various biological processes and achieve their functions through protein–protein interactions (PPIs). Thus, accurate identification of PPI sites is essential. Traditional biological methods for identifying PPIs are costly, labor-intensive, and time-consuming. The development of computational prediction methods for PPI sites offers promising alternatives. Most known deep learning (DL) methods employ layer-wise multi-scale CNNs to extract features from protein sequences. But, these methods usually neglect the spatial positions and hierarchical information embedded within protein sequences, which are actually crucial for PPI site prediction. In this paper, we propose MR2CPPIS, a novel sequence-based DL model that utilizes the multi-scale Res2Net with coordinate attention mechanism to exploit multi-scale features and enhance PPI site prediction capability. We leverage the multi-scale Res2Net to expand the receptive field for each network layer, thus capturing multi-scale information of protein sequences at a granular level. To further explore the local contextual features of each target residue, we employ a coordinate attention block to characterize the precise spatial position information, enabling the network to effectively extract long-range dependencies. We evaluate our MR2CPPIS on three public benchmark datasets (Dset 72, Dset 186, and PDBset 164), achieving state-of-the-art performance. The source codes are available at https://***/YyinGong/MR2CPPIS. © 2024 Elsevier Ltd

关键词： Forecasting

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Semi-vortex solitons and their excited states in spin-orbit-coupled binary bosonic condensates

arXiv

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arXiv 2024年

作者： Deng, Haiming Li, Jinqing Chen, Zhaopin Liu, Yaohui Liu, Dong Jiang, Chunzhi Kong, Chao Malomed, Boris A. School of Physics and Electronic-Electrical Engineering Xiangnan University Chenzhou423000 China Microelectronics and Optoelectronics Technology Key Laboratory of Hunan Higher Education Xiangnan University Chenzhou423000 China Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems Xiangnan University Chenzhou423000 China Physics Department Solid-State Institute Technion Haifa32000 Israel Department of Physical Electronics School of Electrical Engineering Faculty of Engineering Tel Aviv University Tel Aviv69978 Israel Instituto de Alta Investigación Universidad de Tarapacá Casilla 7D Arica Chile

It is known that two-dimensional two-component fundamental solitons of the semi-vortex (SV) type, with vorticities (s+, s−) = (0, 1) in their components, are stable ground states (GSs) in the spin-orbit-coupled (SOC) binary Bose-Einstein condensate with the contact self-attraction acting in both components, in spite of the possibility of the critical collapse in the system. However, excited states (ESs) of the SV solitons, with the vorticity set (s+, s−) = (S+, S+ + 1) and S+ = 1, 2, 3, ..., are unstable in the same system. We construct ESs of SV solitons in the SOC system with opposite signs of the self-interaction in the two components. The main finding is stability of the ES-SV solitons, with the extra vorticity (at least) up to S+ = 6. The threshold value of the norm for the onset of the critical collapse, Nthr, in these excited states is higher than the commonly known critical value, Nc ≈ 5.85, associated with the single-component Townes solitons, Nthr increasing with the growth of S+. A velocity interval for stable motion of the GS-SV solitons is found too. The results suggest a solution for the challenging problem of the creation of stable vortex solitons with high topological charges. Copyright © 2024, The Authors. All rights reserved.

关键词： Excited states

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Multi-Agent Reinforcement Learning based Edge Content Caching for Connected Autonomous Vehicles in IoV

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ACM Transactions on Autonomous and Adaptive systems 1000年

作者： Xiaolong Xu Linjie Gu Muhammad Bilal Maqbool Khan Yiping Wen Guoqiang Liu Yuan Yuan School of Software Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services Nanjing University of Information Science and Technology China Changwang School of Honors Nanjing University of Information Science and Technology China Department of Computer and Electronics Systems Engineering Hankuk University of Foreign Studies Korea Department of IT and Computer Science Pak-Austria Fachhochschule-Institute of Applied Sciences and Technology Pakistan School of Computer Science and Engineering Hunan University of Science and Technology China School of Software Nanjing University of Information Science and Technology China School of Computer Science and Engineering Beihang University State Key Laboratory of Software Development Environment Zhongguancun Laboratory China

Connected Autonomous Vehicle (CAV) Driving, as a data-driven intelligent driving technology within the Internet of Vehicles (IoV), presents significant challenges to the efficiency and security of real-time data management. The combination of Web3.0 and edge content caching holds promise in providing low-latency data access for CAVs’ real-time applications. Web3.0 enables the reliable pre-migration of frequently requested content from content providers to edge nodes. However, identifying optimal edge node peers for joint content caching and replacement remains challenging due to the dynamic nature of traffic flow in IoV. Addressing these challenges, this article introduces GAMA-Cache, an innovative edge content caching methodology leveraging Graph Attention Networks (GAT) and Multi-Agent Reinforcement Learning (MARL). GAMA-Cache conceptualizes the cooperative edge content caching issue as a constrained Markov decision process. It employs a MARL technique predicated on cooperation effectiveness to discern optimal caching decisions, with GAT augmenting information extracted from adjacent nodes. A distinct collaborator selection mechanism is also developed to streamline communication between agents, filtering out those with minimal correlations in the vector input to the policy network. Experimental results demonstrate that, in terms of service latency and delivery failure, the GAMA-Cache outperforms other state-of-the-art MARL solutions for edge content caching in IoV.

关键词： Content Caching Reinforcement Learning Connected Autonomous Driving

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