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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), International Conference on

作者： Prabu K P Sudhakar School of Computing Science and Engineering Galgotias University Greater Noida India

The rapid evolution of internet technologies has led to a significant proliferation of connected devices, expanding the potential attack surface. This necessitates the implementation of effective countermeasures to safeguard network infrastructures against the detrimental impacts of cyber-attacks. Hence, it is crucial to differentiate personal information and cloud computing worldwide, and to implement specific policies and regulations for information security. The main aim of the security policy and framework in cloud computing is safeguarding users and data, optimizing task operations, ensuring compliance, and setting user behavior standards. Additionally, IDPS-Intrusion Detection and Prevention Systems have gained widespread adoption as solutions for monitoring and analyzing network traffic, identifying anomalies, thereby detecting and preventing the ongoing adversarial activities, which play a crucial role in triggering alerts and autonomously blocking traffic from malicious sources. This study provides a comprehensive outline for a security policy in cloud computing with a focus on critical security tools, policies, and services, placing a particular emphasis on cloud environments to meet the organizational adoption requirements. By establishing vital connections between prerequisites, legal considerations, analytical techniques, and IDPS to mitigate threats, this research study provides strategic recommendations for cloud computing security policies.

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Enabling Autonomous Digital Marketing: A Machine Learning Approach for Consumer Demand Forecasting

Enabling Autonomous Digital Marketing: A Machine Learning Ap...

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computing, Power and Communication Technologies (IC2PCT), IEEE International Conference on

作者： Kanika Singhal J.N. Singh Vishnu Sharma School of Computing Science & Engineering Galgotias University Uttar Pradesh India

This research surveys the integration of Artificial Intelligence (AI) and Machine Learning (ML) to establish an autonomous framework for Digital Marketing, with a primary focus on revolutionizing traditional marketing strategies by forecasting and addressing consumer demands. The proposed approach aims to enhance decision-making processes through the application of advanced algorithms for precise demand predictions. Additionally, the study explores the efficacy of AI through ensemble machine learning, employing decision tree algorithms to optimize digital marketing indicators. The examination emphasizes the utilization of AI-powered ensemble ML to refine cost-effective strategies and maximize profits, using a dataset comprising 6561 possible tuples. Three collaborative ML approaches are working as algorithms to distinguish designs and relationships within the price data, contributing to strategic decision-making. This project uniquely illustrates the possible of replicated data to elevate cost-saving strategies in business contexts. The findings not only contribute to existing works on AI and ML requests in commercial but also highlight the transformative impact ML can have on commercial proprietors, production, and marketing personnel, extending implications to various businesses, counting transport, logistics, and trade, with significant prospects for improving overall performance of 91.75% in operational efficiency.

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Microbe-bridged disease-metabolite associations identification by heterogeneous graph fusion

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BRIEFINGS IN BIOINFORMATICS 2022年第6期23卷 bbac423-bbac423页

作者： Feng, Jitong Wu, Shengbo Yang, Hongpeng Ai, Chengwei Qiao, Jianjun Xu, Junhai Guo, Fei College of Intelligence and Computing Tianjin University Tianjin China School of Chemical Engineering and Technology Tianjin University Tianjin China Zhejiang Shaoxing Research Institute of Tianjin University Shaoxing China School of Computational Science and Engineering University of South Carolina Columbia U.S School of Computer Science and Engineering Central South University Changsha China

Motivation: Metabolomics has developed rapidly in recent years, and metabolism-related databases are also gradually constructed. Nowadays, more and more studies are being carried out on diverse microbes, metabolites and diseases. However, the logics of various associations among microbes, metabolites and diseases are limited understanding in the biomedicine of gut microbial system. The collection and analysis of relevant microbial bioinformation play an important role in the revelation of microbe-metabolite-disease associations. Therefore, the dataset that integrates multiple relationships and the method based on complex heterogeneous graphs need to be developed. Results: In this study, we integrated some databases and extracted a variety of associations data among microbes, metabolites and diseases. After obtaining the three interconnected bilateral association data (microbe-metabolite, metabolite-disease and disease-microbe), we considered building a heterogeneous graph to describe the association data. In our model, microbes were used as a bridge between diseases and metabolites. In order to fuse the information of disease-microbe-metabolite graph, we used the bipartite graph attention network on the disease-microbe and metabolite-microbe bipartite graph. The experimental results show that our model has good performance in the prediction of various disease-metabolite associations. Through the case study of type 2 diabetes mellitus, Parkinson's disease, inflammatory bowel disease and liver cirrhosis, it is noted that our proposed methodology are valuable for the mining of other associations and the prediction of biomarkers for different human diseases. Availability and implementation: https://***/Selenefreeze/***

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Revolutionizing Healthcare with Wearable Devices and IoT Integration for Personalized Health Management in Next-Generation Health Informatics

Revolutionizing Healthcare with Wearable Devices and IoT Int...

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2024 IEEE International Conference on Recent Advances in science and engineering Technology, ICRASET 2024

作者： Parthipan, V. Ramesh, P.S. Gururama Senthilvel, P. Dineshkumar, R. Vennila, G. Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Tamil Nadu Chennai India Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Chennai India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Electronics and Communication Engineering Chennai India Mohan Babu University School of Computing Department of Ai & Ml Andhra Pradesh Tirupati India

ISBN: (纸本)9798350388602

This work outlines a paradigm shift that is created by the integration of wearable devices with the Internet of Things for health consciousness. With the help of the proposed system, the user is given the constant readings of the key heath indicators including heart rate, blood pressure, blood glucose level, physical activity, and the quality of sleep, all the data are transferred in real-time to an IoT platform, and the data analysis supported by machine learning algorithms provide the user with individually tailored heath reports. Wearable Medical today carried out a 90 persons trial over a six-month long program and noted changes in health parameters, user interactions and results. Several client outcomes highlighted that clients' heart rate, blood pressure and glucose levels, physical activity, and sleep quality improved. The system also provided strong control in data protection and the compliance with different regulations which is needed for any company. Although there are issues with device and network integration and the supporting architecture, the study demonstrates the system's capability of decreasing hospital attendance, increasing medication compliance and quality of life, thereby opening up possibilities for exploring wearable health technologies in clinical environments in the future. © 2024 IEEE.

关键词： Electronic health record

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A Lightweight Signaling Solution Based on MQTT for Peer to Peer Video Call System 10

A Lightweight Signaling Solution Based on MQTT for Peer to P...

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10th International Conference on Computer and Communications, ICCC 2024

作者： Yu, Bo Liu, Chengjie Wang, Wei Yang, Chao Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Shenyang China School of Computer Science and Engineering Northeastern University Shenyang China

Along with the popularity of 5G mobile networks and the impact of the epidemic, there is a growing demand for video calls on mobile. The signaling protocol for video calls plays a very important role in maintaining the session state, we propose a lightweight signaling solution for video calls, which is based on MQTT protocol and takes advantage of MQTT's lightweight features. We have tested the system's functionality and signaling traffic consumption, and the results show that the system has complete video call functionality, is very traffic efficient at the signaling level, and has good call establishment delay. © 2024 IEEE.

关键词： Signaling

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Water Quality Monitoring in Eel Aquaculture Using IoT 11

Water Quality Monitoring in Eel Aquaculture Using IoT

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11th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer engineering, UPCON 2024

作者： Thangam, S. Gurupriya, M. Damavarapu, Pooja Mahesh, Kavinya Vardhan, Monesh Harsha Amrita School of Computing Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350378726

In eel aquaculture it is crucial to manage water quality to support the growth, health and longevity of the stock. This study focuses on overseeing indicators such, as temperature, turbidity and water levels in eel farming setups using IoT technology. By incorporating these sensors it becomes simpler to gather and analyze real time data facilitating interventions and precise adjustments to uphold water conditions. The objective is to enhance understanding of the changing water quality factors in eel farming environments and develop strategies for risk prevention and proactive control. The ultimate aim is to boost productivity, efficiency and environmental responsibility, in eel farming practices through the application of sensor technologies. © 2024 IEEE.

关键词： Fisheries

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Improving Facial Recognition: Evaluating CNNs for Detecting Manipulated Images

Improving Facial Recognition: Evaluating CNNs for Detecting ...

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International Conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions)

作者： Prakhar Bansal Ajay Shankar Pratiyush Kumar Nandan Vaid P. Rajakumar School of Computing Science and Engineering Galgotias University Greater Noida India

ISBN: (数字)9798350350357

ISBN: (纸本)9798350350364

The ability to distinguish between real and fake imagery is extremely important in the field of computer vision, especially when it comes to facial recognition. In order to detect real faces from fakes, this study explores the creation and assessment of convolutional neural network (CNN) models. Our study compares the performance of well-known CNN architectures, such as VGG, ResNet, and EfficientNetB0, using the TensorFlow framework. After extensive testing and analysis, EfficientNetB0 stands out as the top performer, attaining a previously unheard-of 99% accuracy. This astounding outcome demonstrates the effectiveness of EfficientNetB0's sophisticated architecture, which is tuned for optimal performance in tasks requiring subtle distinction between real and fake facial images.

关键词： Computational modeling Face recognition Computer architecture Market research Convolutional neural networks Reliability Task analysis

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Design and Development of a Secured Framework equipped with GI Tagging and Blockchain for Enhanced Data Security and Transparency in Healthcare Operations, for Effective Management of Resources in Government Hospitals

Design and Development of a Secured Framework equipped with ...

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Computational Intelligence and computing Applications (ICCICA), International Conference on

作者： Anjali Chennupati Bhamidipati Prahas Bharadwaj Aaditya Ghali Sreevidya B Rajesh M Department of Computer Science and Engineering Amrita School of Computing Bengaluru India

ISBN: (数字)9798350306446

ISBN: (纸本)9798350306453

Traditional logistics systems lack mainly security and authenticity. In any retail distribution network, ensuring authenticity is the most critical challenge. A customer always look for authenticity and an upcoming / newly introduced retail network lacks the aspect of authenticity. Even though there are various marketing strategies exist to overcome or mellow down the impact of authenticity, the researchers are still not yet came up with any formidable solution. This paper investigates the synergistic mix of blockchain innovation with Geological Sign (GI) labeling, introducing a progressive system for getting and ensuring the legitimacy of locale explicit items. Our answer fosters a protected, straightforward, and sealed framework via flawlessly incorporating different innovations, guaranteeing the evident recognizability of items to their geological beginnings. GI tagging ensures the authenticity of items being included in the transaction network which enhances customer satisfaction and customer belief on the network. By utilizing blockchain's decentralized and changeless record, the joining emphatically works on the viability of GI labeling, giving a comprehensive answer for battling falsifying and unapproved replication. As well as strengthening the security of provincial items, this cooperative structure additionally helps protect social legacy while upgrading shopper trust in the genuineness and nature of these special contributions. The decentralized architecture of blockchain enhances the fault tolerance of the overall system.

关键词： Technological innovation Fault tolerance Hospitals Geology Government Fault tolerant systems Tagging

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Interplay of Technology and Social Dynamics: Community Management Applications in Sports Communities

Interplay of Technology and Social Dynamics: Community Manag...

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computing, Power and Communication Technologies (IC2PCT), IEEE International Conference on

作者： Akshita Sharma Aashima Wadhwa Kushal Gupta School of Computing Science and Engineering Galgotias University Greater Noida India

In recent years, sports communities have witnessed significant growth, both in terms of participation and engagement. The advent of digital technology has provided a unique opportunity to enhance the dynamics within these communities, fostering stronger connections among members. To harness this potential, an increasing number of sports enthusiasts are turning to community management applications, which serve as central hubs for communication, organization, and engagement. This research paper explores the development and implications of a comprehensive community management application tailored to sports communities.

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Crop Damage Detection using Machine Learning Approaches

Crop Damage Detection using Machine Learning Approaches

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IEEE Recent Advances in Intelligent Computational Systems (RAICS)

作者： Priyanka C Nair Nalini Sampath P Praneeth Reddy P Sai Shruthi Department of Computer Science and Engineering Amrita School of Computing Bengaluru India

ISBN: (数字)9798350381689

ISBN: (纸本)9798350381696

Agriculture is of vital importance to human life as it is the main source of livestock production and contributes significantly to the country's employment opportunities and economy. Ensuring high standards of production quality is essential. Recent technological advances are merging agricultural and machine learning techniques to help improve crop quality. The main objective of this work is to make use of machine learning approaches to identify the healthy status of the crop. Multi-class classification is applied to the dataset which helps classify crop conditions. As there is an imbalance of data of the 3 classes, Random under- sampling and Tomek under-sampling methods are applied on the dataset. A combination of Tomek undersampling and Smote undersampling has also been performed on this dataset. Various algorithms like Gradient Boosting, Gaussian Naïve Bayes, Neural Network (MLP) and k-Nearest Neighbors were performed on the dataset which helped show that Randomforest was the best model in terms of accuracy and F1 score.

关键词： Accuracy Neural networks Crops Production Pesticides Nearest neighbor methods Boosting

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