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39th IEEE International Conference on Data engineering, ICDE 2023

作者： Qiu, Rui Ming, Yi Hong, Yisen Li, Haoyu Yang, Tong Peking University School of Computer Science National Engineering Laboratory for Big Data Analysis Technology and Application Beijing China Peking University Academy for Advanced Interdisciplinary Studies China Peng Cheng Laboratory Shenzhen China

ISBN: (纸本)9798350322279

Graphs are good at presenting relational and structural information, making it powerful in the representation of various data. For the efficient storage and processing of graph-like data, graph databases have been rapidly developed and extensively studied. However, graph databases mostly use adjacency lists as their basic data structure (e.g., Neo4j), which could result in poor performance of edge due to the skewed degree distribution of *** design the Wind-Bell Index to address this problem. Wind-Bell Index is a memory-efficient index data structure, which can be attached to existing graph databases to speed up the edge. We have fully implemented our data structure in Neo4j, the most popular graph database today, and conduct theoretical and experimental analysis to evaluate the performance. Theoretical results prove the high query efficiency of our algorithm. And experimental results show that the average edge query speed is increased by hundreds of times compared with the original query interface of Neo4j. We believe that the excellent performance and scalability of Wind-Bell Index make it suitable for the application in a variety of graph databases. © 2023 IEEE.

关键词： Graph Databases

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Knowledge Atlas on the Medical Artificial Intelligence Research-A Bibliometric Analysis Based on CiteSpace and VOSviewer 2

Knowledge Atlas on the Medical Artificial Intelligence Resea...

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2nd Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum, AIBDF 2022

作者： Shi, Li Han, Lingling Huang, Ke Ge, Fangzhen Zhang, Lele School of Computer Science and Technology Huaibei Normal University Huaibei235000 China School of Economics and Management Huaibei Normal University Huaibei235000 China Engineering Research Center of Cognitive Behavioral Intelligent Computing and Application Huaibei235000 China

ISBN: (纸本)9781510663107

In order to draw and analyze the current status of the research on the application of artificial intelligence in the field of health in China and abroad, we explored the hotspots and frontiers of this research field and the evolution path from 2012 to 2022. This research uses 3743 articles included in the core database of Web of science and 728 related research articles contained in CNKI as the basis for data analysis, and uses the advantages of bibliometrics visualization software of CiteSpace and VOSviewer to study institutions, countries, authors and literature keywords. In this research area, the research of medical artificial intelligence is growing day by day. By analyzing and sorting out the current research status, research hotspots and evolution path in this field of research, and trying to point out the deficiencies in the research in this field in China, the paper hopes to provide more references for researchers and practitioners of medical artificial intelligence related research. © 2023 SPIE.

关键词： Data visualization

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Improved DHOA-Fuzzy Based Load Scheduling in IoT Cloud Environment

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computers, Materials & Continua 2022年第5期71卷 4101-4114页

作者： R.Joshua Samuel Raj V.Ilango Prince Thomas V.R.Uma Fahd N.Al-Wesabi Radwa Marzouk Anwer Mustafa Hilal Department of Information Science&Engineering CMR Institute of TechnologyBengaluru560037India Department of Computer Application CMR Institute of TechnologyBangalore560037India School of Computing Woldia Institute of TechnologyWoldia UniversityEthiopia Department of Commerce School of CommerceFinance and AccountancyChrist UniversityBangalore560029India Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Faculty of Computer and IT Sana’a UniversityYemen Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlkharjSaudi Arabia

Internet of things (IoT) has been significantly raised owing to thedevelopment of broadband access network, machine learning (ML), big dataanalytics (BDA), cloud computing (CC), and so on. The development of IoTtechnologies has resulted in a massive quantity of data due to the existenceof several people linking through distinct physical components, indicatingthe status of the CC environment. In the IoT, load scheduling is realistictechnique in distinct data center to guarantee the network suitability by fallingthe computer hardware and software catastrophe and with right utilize ofresource. The ideal load balancer improves many factors of Quality of Service(QoS) like resource performance, scalability, response time, error tolerance,and efficiency. The scholar is assumed as load scheduling a vital problem inIoT environment. There are many techniques accessible to load scheduling inIoT environments. With this motivation, this paper presents an improved deerhunting optimization algorithm with Type II fuzzy logic (IDHOA-T2F) modelfor load scheduling in IoT environment. The goal of the IDHOA-T2F is todiminish the energy utilization of integrated circuit of IoT node and enhancethe load scheduling in IoT environments. The IDHOA technique is derivedby integrating the concepts of Nelder Mead (NM) with the DHOA. Theproposed model also synthesized the T2L based on fuzzy logic (FL) systemsto counterbalance the load distribution. The proposed model finds usefulto improve the efficiency of IoT system. For validating the enhanced loadscheduling performance of the IDHOA-T2F technique, a series of simulationstake place to highlight the improved performance. The experimental outcomesdemonstrate the capable outcome of the IDHOA-T2F technique over therecent techniques.

关键词： Load scheduling internet of things cloud computing metaheuristics fuzzy logic

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A Survey of Dynamic Exploration Symmetric Encryption with Backward & Forward Secrecy

A Survey of Dynamic Exploration Symmetric Encryption with Ba...

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Advance Computing and Innovative Technologies in engineering (ICACITE), International Conference on

作者： Satendra Singh Samriti Bhagat Department of Computer Science Engineering Vivekananda Global University Jaipur India Department of Master of Computer Application Chandigarh School of Business

A sophisticated type of symmetric encryption is called Multiuser Dynamic Searchable Symmetric Encryption. It expands the capabilities of conventional symmetric encryption to enable actions such as adding and removing encrypted data as well as the ability for a verified set of information users to access their preferred encrypted data within the dynamic database. The latter can use using erased data and search results to comprehend the content, while the former allows attackers to discover by performing file injection attacks, keywords from the injected data were exposed. can do. To our knowledge, the available literature has not completely addressed these privacy problems for M-DSSE. In light of this, our attention is directed toward multiuser dynamic searchable symmetric encryption that satisfies the requirements for forwarding and backward security. It uses Inverted indexes are created and updated using random number generator Functions (RNG) and Authenticator primitives search tokens to suggest specific solutions. In the accidental model, the suggested approach is shown to be secure. Additionally, the performance study demonstrates that the suggested approach provides increased security assurances at a fair cost to efficiency.

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Facial Expression Recognition (FER) System Using Deep Learning

Facial Expression Recognition (FER) System Using Deep Learni...

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Humanitarian Technology Conference (KHI-HTC), IEEE Karachi Section

作者： Ooi Juin Yan Humaira Ashraf Uswa Ihsan Nz Jhanjhi Sayan Kumar Ray Kavita Masters of Applied Computing Taylor’s University Selangor Malaysia School of Computer Science SCS Taylor’s University Malaysia Department of Computer science International Islamic University Islamabad Pakistan Department of Computer Science and Engineering Uttaranchal University Dehradun India

Sentiment analysis of both text and images have been widely implemented machine learning application. Facial expression recognition (FER) is a widely known application of sentiment analysis of image data. This application has already been implemented in various industry, but challenges such as the complexities of facial features and different image angle still remain. This project aims to develop a FER system capable of classifying human expressions through facial images using deep learning techniques. A CNN-based architecture was proposed and training using the FER2013 dataset, which is a commonly used facial expression dataset. Overall, the trained model achieved an accuracy of 63.97% through the dataset. The trained CNN model was then employed to develop a web-based prototype of a FER system through Python Flask.

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Accurate Selection of proper network system and concern Cloud Services through computing

Accurate Selection of proper network system and concern Clou...

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Advance Computing and Innovative Technologies in engineering (ICACITE), International Conference on

作者： Amar S. Verma Rajat Kumar Department of Computer Science Engineering Vivekananda Global University Jaipur India Department of Master of Computer Application Chandigarh School of Business

The significant role that networking plays in cloud service provisioning necessitates federated selection of network and cloud services in order to offer the service performance required by distinct applications. In this paper, we describe a strategy based on performance for federated selection of network and cloud services to address the new service selection challenges provided by the Software Defined Cloud Environment (SDCE). The main contribution of this paper is a general interest profile material to different applications, an examination strategy for assessing the reachable presentation of composite organization cloud administrations, and an arrangement for combined choice of organization and cloud administrations in light of execution assessment. The strategy and innovation fostered the critical job that systems administration plays in cloud administration provisioning requires united choice of organization and cloud administrations to offer the help execution expected by particular applications. In this paper, we depict a methodology for execution based federated choice of organization and cloud administrations to address the new help determination challenges given by the Software Defined Cloud Environment (SDCE). The principal commitments of this paper are an examination plan for multiple applications, a general interest profile, and assessing the feasible exhibition of composite organization cloud administrations, and an arrangement for united determination of organization and cloud administrations in light of execution assessment.

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Apple Disease Recognition Based on Comprehensive application of Residual Neural Network 5

Apple Disease Recognition Based on Comprehensive Application...

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5th International Conference on Machine Learning and Intelligent Systems, MLIS 2023

作者： Song, Xiedong Mariano, Vladimir Y. Shi, Xuemei School of Mathematics and Computer Application Technology Jining University Shandong Qufu273155 China Information Engineering Department Yantai Vocational College Shandong Yantai264003 China College of Computing and Information Technologies National University Manila0900 Philippines School of Computer Science Huainan Normal University Anhui Huainan232038 China

ISBN: (纸本)9781643684468

China is the world's largest apple growing country;Apples are affected by various diseases during the planting process, and timely detection of fruit tree diseases is of great significance for improving apple yield. With the development of artificial intelligence technology, The use of deep learning to detect the condition of fruit trees has become a research hotspot in forest science planting. ResNet50 is used to solve the bottleneck problem of recognition accuracy of traditional neural networks, and data enhancement is used to improve the quality of data samples. transfer learning is used to solve the application of small-scale data samples, and loss function is used to balance sample errors. Improve the ability to obtain important feature information by using a dual channel mixed attention mechanism. Finally, a comprehensive network model combining residual neural network, dual channel mixed attention mechanism, transfer learning and loss function is designed. The experimental results show that the effect of this comprehensive ResNet50 model is better than that of the original ResNet50 model and VGG19 model, and its classification accuracy rate can reach 96.87%. This method improves the performance in fruit disease detection, and has wider applicability in practical applications. © 2023 The authors and IOS Press.

关键词： Fruits

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Understanding the Impact AI has on Data Access Performance and Efficiency 3

Understanding the Impact AI has on Data Access Performance a...

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Rege, Pallavi R. Ahluwalia, Gunveen Kumar, Ritesh Narasimhayya, B.E. Yadav, Surendra Karthikeyan, Kavitha Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science and Engineering Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Application Jaipur India Prince Shri Venkateshwara Padmavathy Engineering College Department of Civil Engineering Chennai127 India

ISBN: (纸本)9798350319125

AI has come to be more and more outstanding in recent years in records get entry to overall performance and efficiency. As a result, there were big modifications to how facts are processed and accessed. AI has enabled organizations to extra effectively and efficaciously technique facts, ensuing in accelerated operational efficiency and improved customer satisfaction. This paper presents a comprehensive exploration of the effect of AI on records get entry to performance and performance. It examines the usage of AI to streamline statistics processing and get admission to, and discusses the impact it has on consumer revel in and patron satisfaction. additionally, the paper considers the capacity for future innovation and the way facts get admission to overall performance and performance may be further more desirable via AI. The paper concludes with implications for similarly research and improvement. © 2023 IEEE.

关键词： Capacity Implications Satisfaction Similarly

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SSHTDNS: A Blockchain-Based Secure, Scalable, and High-Throughput Domain Name System

SSHTDNS: A Blockchain-Based Secure, Scalable, and High-Throu...

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Advance Computing and Innovative Technologies in engineering (ICACITE), International Conference on

作者： Baldev Singh Kavita Department of Computer Science Engineering Vivekananda Global University Jaipur India Department of Master of Computer Application Chandigarh School of Business

The Internet's crucial domain name system is in charge of translating domain names into IP addresses. However, because of its dispersed structure with a hub, it is subject to significant security concerns. Since the creation of Bitcoin, blockchain has drawn a lot of attention owing to its decentralized, trustworthy, and secure features. In this article, we suggest SSHTDNS, a brand-brand-new domain name system built on the blockchain. SSHTDNS selects the consortium chain form to ensure the management of Top-Level Domain names, and these consortium nodes use linkable ring signature technology for identity anonymity and vote fairness. Shading protocol is used in multi-chain structures to increase the system's scalability and throughput. A domain name system that combines these methods can be safe, scalable, and high-throughput.

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Quality Prediction of Fruits using Artificial Neural Network and its application in Food science 8

Quality Prediction of Fruits using Artificial Neural Network...

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8th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2024

作者： Saxena, Archana Kumar, Sandeep Saxena, Surabhi Deogaonkar, Anant Goyal, Arti Goyal, Shweta Invertis University Deptt. of Computer Application Uttar Pradesh Bareilly India Tula's Institute Deptt. of Computer Science & Engg. U.K. Dehradun India Graphic Era Hill University School of Management Bhimtal Campus India Ramdeobaba University School of Management Nagpur India Graphic Era Deemed to Be University Deptt. of Electrical Engineering Dehradun India

ISBN: (纸本)9798350367904

The nutritional value of fruit has a significant impact on customer satisfaction. Fruit quality and costeffectiveness would enhance customer fulfillment and revenue, according to retailers. The whole supply chain requires rapid and simple techniques for assessing quality. The strawberry is a popular fruit that is valued for its distinctive taste as well as numerous health benefits, including antioxidants and helpful amino acids, which significantly improve the item's total quality. Therefore, dividing strawberries into desired and undesired groups would help customers and startups decide if the strawberries they buy and sell are desired depending on important factors like color and form. To overcome that, Artificial Neural Networks (ANN) were used in the present research. When Multi-Linear Regression (MLR) was used, unacceptable prediction results were achieved for every variable. In contrast, it was discovered that the interior functionality attributes may be properly anticipated by applying ANNs. This was particularly true for the overall monomeric anthocyanin (R 2=0.943) and antioxidant potential. The current research demonstrated that utilizing color positions with ANNs may effectively assess strawberry quality. © 2024 IEEE.

关键词： Food ingredients

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