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Cooperative Relationship Prediction between Scholars in Heterogeneous Academic Network 23

Cooperative Relationship Prediction between Scholars in Hete...

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23rd IEEE international conference on High Performance Computing and Communications, 7th IEEE international conference on Data Science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Shi, Jia Jin, Hai Xie, Xia National Engineering Research Center for Big Data Technology and System School of Computer Science and Technology Huazhong University of Science and Technology Services Computing Technology and System Lab Cluster and Grid Computing Lab Wuhan China School of Computer Science and Technology Hainan University Haikou China

ISBN: (纸本)9781665494571

the real academic network belongs to a heterogeneous network, therefore, for the link prediction tasks, some information on the network may be lost if only using homogeneous network methods. In order to make good use of the rich semantic information in a heterogeneous network for better predicting the cooperative relationship between scholars, this paper proposes a cooperative relationship prediction (CoRP) model. the CoRP model includes the following three steps. Firstly, a structural feature extraction module is designed based on meta path by using the similarity metric function to measure the meta path similarity between scholars. Secondly, to overcome the defects that the existing methods usually ignore the attribute information on nodes, three attribute feature presentation functions are constructed to fully utilize the attribute information of scholars in the academic network. In the end, a machine learning classifier which combines the structural similarity and attribute similarity is utilized to learn each attribute feature and complete the task of cooperative relationship prediction. the experimental results reveal that compared with the benchmark method, the proposed method has better performance and interpretability with improvement from 3% to 10% of AUC value for the AMiner academic data set. © 2021 IEEE.

关键词： Measurement Smart cities Semantics Machine learning Benchmark testing Predictive models Feature extraction

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Healthify App Using Blockchain with Cloud 7th

Healthify App Using Blockchain with Cloud

引用

7th IFIP TC 12 international conference on Computational Intelligence in Data Science, ICCIDS 2024

作者： Ponmani, S. Sushil Mane, M. Vinita Piola, A. Department of Computer Science Rajalakshmi Engineering College Thandalam Tamil Nadu Chennai India

ISBN: (纸本)9783031699856

In the modern healthcare industry, hospitals still use outdated data management systems for patient data, and the way patient health records are kept and safeguarded does not reflect our technological advancements in this field. Blockchain technology can completely transform the healthcare sector by enhancing the security and storage of medical data and records. this project uses cloud computing to implement blockchain technology in the health sector. If we have an internet connection, cloud storage enables data access on any device, at any time, and from any location. In the healthcare industry, blockchain offers advantages like accurate patient care, and real-time data access. this project proposes hosting a blockchain code on a cloud network to develop a prototype app for the healthcare sector. By utilizing cloud infrastructure, the solution can adapt to the evolving needs of the healthcare industry while meeting regulatory requirements. © IFIP international Federation for information processing 2024.

关键词： Electronic health record

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Design of Power System Remote Video Monitoring System Based on RTP technology 7th

Design of Power System Remote Video Monitoring System Based ...

引用

7th EAI international conference on Advanced Hybrid information processing, ADHIP 2023

作者： Yuan, Liang Information Technology Co. Ltd. Beijing100031 China

ISBN: (纸本)9783031505485

Most of the conventional power system remote video monitoring systems are designed based on the SIP principle. In the actual monitoring operation process, there are problems such as poor real-time monitoring and high packet loss rate. In order to solve this problem, RTP technology is introduced and a remote video monitoring system for power system based on RTP technology is designed. Based on the optimized design of the monitoring system hardware, the monitoring system software and software functions are designed. First, the remote video surveillance image of power system is filtered to remove most of the signal noise in the remote video surveillance image. Secondly, the background of power system remote video monitoring is updated to achieve the ideal segmentation effect of video monitoring image. the remote video monitoring module is designed to carry out remote video real-time monitoring of the operating conditions of the power system. the real-time transmission function of remote video image in power system is designed by using RTP technology. According to the system test results, after the proposed monitoring system is applied, with the increase of system running time, its packet loss rate is below 1%, and the real-time performance of remote video monitoring is high. © ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Packet loss

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A New Hybrid EAES-SI Framework for Secure information Sharing iin WBANS 7

A New Hybrid EAES-SI Framework for Secure Information Sharin...

引用

7th international conference on Electronics, Communication and Aerospace technology, ICECA 2023

作者： Anitha, P. Priya, R. Sree Narayana Guru College K.G.Chavadi Department of Computer Science Tamil Nadu Coimbatore641105 India

ISBN: (纸本)9798350340600

the transition from analog to digital health services, or 'Wireless Body Area Networks (WBAN s)', is often portrayed as a revolution. the vital signs of the patient detected by the sensors are private, valuable information that might be exploited in several ways by malicious parties. this means that successful encryption protection methods are essential for the broad use of WBANs. In this present research, a unique hybrid 'EAES-SI' framework is proposed as a means of protecting the confidentiality and safety of medical records sent through WBAN. To prevent loss of information and fraudulent attempts, an 'Enhanced Advanced Encryption Standard (EAES)' was developed first to encrypt the information while it is sent from the patient's body to the 'Sink Node (SiN)/Base Station (BS)'. the EAES is an improvement over the standard AES when it comes to the amount of data and keys. Next, a 'Swarm Intelligence (SI)' approach is proposed, depicted upon the cooperative behavior of swarming creatures, to determine the most secure and efficient means of transferring data. After an optimum route has been determined, SI will send the encrypted information from EAES down that way. thus, the proposed EAES-SI approach reduces both energy consumption and processing time. the suggested EAES-SI, which uses medical information as its backbone, offers an increased level of confidentiality of the information and an improved privacy ratio. Comparing the 'Security Ratio', 'Energy Consumption Ratio', 'Encryption Time' and 'Decryption Time' of the proposed EAES-SI with the existing BC and ADC frameworks, the proposed EAES-SI framework is shown to be the most secure option. © 2023 IEEE.

关键词： Cryptography

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Plant Diseases Detection Using Image processing and Suggest Pesticides and Managements 7

Plant Diseases Detection Using Image Processing and Suggest ...

引用

7th IEEE international conference for Convergence in technology, I2CT 2022

作者： Sritharan, Lathusha Anjanan, Manikavasagar Gamage, Anjalie Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9781665421683

Various plant diseases affect farmers all over the world and there is a very small amount of solutions available online for free in order to assist. In Sri Lanka, in order to address this issue, we have done a study which outputs a mobile application which utilizes image processing and recommend pesticides according to corresponding disease. the disease detection method includes image acquisition, image pre-processing, image segmentation, feature extraction, and classification. this study looked at methods for identifying plant ailments using photos of their leaves. this work also presented unique segmentation and feature extraction techniques for plant disease identification. For feature extraction, the CNN algorithm is utilized. this research paper may be a revolutionary approach to diagnosing plant illnesses by employing a deep convolutional neural network that has been trained and fine-tuned to suit a database of a plant's leaves gathered independently for distinct plant diseases. At the end of the study we achieved an accuracy of 98 percent in detecting the plant diseases and further on implemented mobile system which can suggest pesticide accordingly. © 2022 IEEE.

关键词： Feature extraction

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A low-light image enhancement network based on unsupervised learning in coal mine 24

A low-light image enhancement network based on unsupervised ...

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7th international conference on Signal processing and Machine Learning, SPML 2024

作者： Li, Xiaoyu Wang, Yiwei School of Electronic Information Engineering Inner Mongolia University China

ISBN: (纸本)9798400717192

the complex lighting conditions in the coal mine lead to the problems of noise interference, low definition, lack of color and texture information, which seriously affect the development of computer vision tasks in the coal mine. In addition, most of the existing image enhancement methods require training on low/normal-light paired image datasets. therefore, in view of the above problems, an image enhancement method based on unsupervised learning model Zero-DCE is proposed, which can effectively overcome the difficulty of collecting low/normal-light paired image datasets in the coal mine. the CBAM attention mechanism is used to express the key features in the low-light image, and enhance the feature information and local contrast of images. the asymmetric convolution block (ACB) is applied to express the local image features and the detail image features, and improve the calculation efficiency of the algorithm. the experimental results show that the proposed method can enhance the texture details effectively and perform well in the image noise reduction. Compared with the Zero-DCE model, the mean of MSE and NIQE are decreased by 6.66% and 2.28%, the mean of PSNR, SSIM and VIF are increased by 1.21%, 1.11% and 17.64%, respectively, which can effectively enhance the low-light images in the coal mine. © 2024 ACM.

关键词： Coal mines

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Adaptive Persymmetric Subspace Detector for Distributed Target 7

Adaptive Persymmetric Subspace Detector for Distributed Targ...

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7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Xie, Zikeng Jian, Tao Wei, Guangfen Huang, Xiaodong Tong, Zhuo Naval Aviation University Research Institute of Information Fusion Shandong Yantai264001 China Shandong Technology and Business University School of Information and Electronic Engineering Shandong Yantai264000 China Naval Aviation University Aviation Service College Shandong Yantai264001 China Yantai First Specialized Secondary School Shandong Yantai264001 China

ISBN: (纸本)9781665478571

In this paper, we deal with the problem of adaptive detection for distributed target in homogeneous Gaussian clutter with unknown persymmetric covariance. the distributed target is located in a multi-rank subspace and its coordinates are unknown. We devise a persymmetric subspace detector by utilizing the one-step Rao criteria. Ultimately, the numerical results show that, the proposed detector is constant false alarm rate (CFAR) with respect to unknown clutter covariance matrix. Moreover, it also has the edge on detection performance by comparing with the existing unstructured detectors, especially in training-limited scenarios. © 2022 IEEE.

关键词： Covariance matrix

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Recognizing the style of a fine-art painting with EfficientNet and Transfer learning 7

Recognizing the style of a fine-art painting with EfficientN...

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7th international conference on Image and Signal processing and their Applications, ISPA 2022

作者： Menai, Baya Lina Chaouki Babahenini, Mohamed Lesia Laboratory Mohamed Khider University Biskra Algeria

ISBN: (纸本)9781665480420

Due to the digitalization of the content of museums and art galleries in the last decades, a huge amount of digital fine art paintings became available on the internet. therefore, the number of digitized paintings databases has increased rapidly, and it became difficult to manipulate their content manually. With the great performance of deep learning approaches and computer vision techniques, we became able to categorize paintings automatically. In this paper, we aim to investigate the effectiveness of the pre-trained EfficientNet models family for the task of identifying the style of a painting and propose custom models based on pre-trained EfficientNet models. We used transfer learning to fine-tune different types of pre-trained EfficientNet models from B0 to B6 on ImageNet. In addition, we added other layers to the base architectures of EfficientNet models to create our custom models. Finally, we analyzed the effect of retraining the last eight layers of our custom models. In our experiments, we used the standard fine art painting classification dataset Painting-91 with the same experimental setup. the deep retraining of the last eight layers of our custom models achieved the best performance with a difference of 5% than the base models. © 2022 IEEE.

关键词： computer vision

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Sharing Confidential Documents Management System for Multiuser 7

Sharing Confidential Documents Management System for Multius...

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7th IEEE/ACIS international conference on Big Data, Cloud Computing, and Data Science, BCD 2022

作者： Han, Sung-Hwa Tonmyong University Dept. of Information Security Busan Korea Republic of

ISBN: (数字)9781665465823

ISBN: (纸本)9781665465823

In an enterprise environment, various types of information are distributed. information to be distributed can be distributed in text, audio, or video types, but the most basic distribution unit is a document file. Some organizations may distribute confidential information by storing it in a file. Only limited users can access these files, and unauthorized access should be blocked. In this study, we propose a confidential document file sharing technique that allows only limited users to access and check the contents. the proposed technique uses encryption technology and uses a key management system. Due to these characteristics, only pre-defined users can access. As a result of verifying the function to confirm the effectiveness of the targeted confidential document technique, it was confirmed that all the targeted functions were provided. Because this study uses encryption technology, the performance is slower than the legacy method. Additional research is needed to improve this. © 2022 IEEE.

关键词： Cryptography

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Classification method of Nickel plated punched steel strip based on improved Lightweight Network 7

Classification method of Nickel plated punched steel strip b...

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7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Li, Jianqi Sun, Xuan Du, Rui Cao, Binfang Liang, Yincong Zhu, Jiang Xiangtan University School of Automation and Electronic Information Xiangtan China Hunan University of Arts and Science School of Computer and Electrical Engineering Changde China Yiyang Power Supply Company of State Grid Yiyang China Hunan University of Arts and Science School of Mathematics and Physics Changde China Jishou University School of Information Science and Engineering Jishou China

ISBN: (纸本)9781665478571

High performance power battery is the core component of electric vehicle. Nickel plated punched steel strip is the key substrate for power battery manufacture. Due to the low degree of automation of key equipment in domestic production line, it can not meet the quality monitoring requirements of high-performance power battery. In order to solve the problem of false detection on punched steel strip brought by manual detection, a classification method of nickel-plated punched steel strip based on improved Lightweight Network is presented. In this method, an efficient bottleneck layer structure is used, and a location association module is presented to enhance the connection between steel strip image pixels. At the same time, the improved Focal Loss is used as the loss function to balance the difficulty and size of samples in the classification process, which improves the average accuracy and detection speed of image classification of nickel-plated punched steel strip. © 2022 IEEE.

关键词： Strip metal

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