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Genetic Algorithm-Based Data Allocation in Multi Media Using Cloud Computing

Genetic Algorithm-Based Data Allocation in Multi Media Using...

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

作者： Surendra Yadav Ms.Manpreet Kaur Department of Computer Science Engineering Vivekananda Global University Jaipur India Department of Master of Computer Application Chandigarh School of Business Jhanjeri

The recent growth of Internet-of-Things (IoT) applications using cloud computing has been amazing. One of the advancements is heterogeneous cloud computing, which has made it possible to use the cloud for a range of infrastructure solutions, including multimedia big data. The optimizations of on-premise heterogeneous memory have been the subject of several past studies. However, the performance and financial limits brought on by hardware distributions and manipulative techniques are placing restrictions on the heterogeneous cloud memory. It is an NP-hard combinatorial issue to distribute data jobs across dispersed memory with different capacities. In order to provide high performance cloud-based heterogeneous memory service offerings, this study focuses on this problem and suggests a unique solution called Cost-Aware Heterogeneous Cloud Memory Model. It allocates data to the cloud-based memory via genetic programming. In our suggested method, we take into account a number of important elements that have a significant influence on how well Communication expenses, data transfer operating costs, energy performance, and time constraints all play a role in how cloud memories operate. Finally, we put our suggested paradigm to the test via experimental assessments. The trial findings have demonstrated the viability and scalability of our technique as a cost-conscious cloud-based solution.

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The Software Component Reusability: An Efficient Strategy to Develop an Enhanced Software through Using Service-Oriented Architecture (SOA)

The Software Component Reusability: An Efficient Strategy to...

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2022 International Mobile and Embedded Technology Conference, MECON 2022

作者： Akila, D. Elangovan, V.R. Batth, Ranbir Singh Balaganesh, D. Padmavathi, R. Vels Institute of Science Echnology and Advanced Studies Department of Information Technology Chennai117 India Agurchand Manmull Jain College Department of Computer Application Chennai114 India Lovely Professional University School of Computer Science and Engineering Punjab India Lincoln University College Department of Computer Science and Multimedia Malaysia

ISBN: (纸本)9781665420204

In the years hate, aspects of reusability software are very strange and cannot be avoided by building new software arms. Service-oriented architecture (SOA) is a model for organising and leveraging distributed capabilities that may be controlled by several domains. This is a type of software design in which application components use network communication protocols to provide services to other components. In software components, the reusable handling project team is generally very familiar with the use of the source code database, so they can find the code they need and easily enter it into the application. Developers can also apply code to the repository for analysis, approval and inclusion. Developers can also monitor which applications using the UX version received. This is allowed because the library section is permitted. The software development process includes development time, development costs and human power requirements and so on. To reduce these things, programmers can apply technology called Reusability software components. The process of implementing or modifying software systems using existing software components is known as software component use. which can reduce human power, costs, and time. In this paper applying a new framework for SOA architecture in this architecture ensures the reuse of user services, easy maintenance to software, independent platforms, reliability, and scalability. In this framework for reuse and reduce the time and cost of software components to develop enhanced projects in an efficient way. © 2022 IEEE.

关键词： computer software reusability

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Enhancing Thyroid Disease Diagnosis Through Machine Learning: A Classification-Based Approach

Enhancing Thyroid Disease Diagnosis Through Machine Learning...

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Sustainable Communication Networks and application (ICSCNA), International Conference on

作者： Shanti Verma Hetal Modi Jaynesh H Desai Khyati Rami Lokmanya Institute of Management and Computer Application Gujarat Technological University Ahmedabad Gujarat Bhagwan Mahavir College of Computer Application Bhagwan Mahavir University Surat Gujarat Vidyadeep University Surat Gujarat Department of Computer Science SAL Institute of Technology & Engineering Research Ahmedabad Gujarat

ISBN: (数字)9798331530013

ISBN: (纸本)9798331530020

Thyroid disease has recently adopted the related classification which has been worthy in the contemporary system of healthcare delivery because of the advances in diagnostics. This work proposes an automated diagnostic system for thyroid disease using machine learning approach to improve the diagnostic accuracy of the disease. The presented model also uses the features selection and classifiers like SVM and Random Forest for the classification of different thyroid disorders including hypothyroidism, hyperthyroidism, and euthyroidism. Missing values in the dataset are treated to provide actual worth in the results while imbalance is also dealt with. The process involves feeding its input a well-constructed data set after which it is checked for its performance through a validation process. The performance of the model is evaluated based on thyroid disease related parameters and the findings show a better performance compared to conventional diagnosis techniques. In this study, the authors also present their future work on how to possibly incorporate this machine learning framework into clinical practice although the study shows how this framework will help the healthcare workers to make better decisions in relation to thyroid diseases.

关键词： Support vector machines Pathology Accuracy Vectors Medical diagnosis Stress Random forests Monitoring Thyroid Diseases

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Performance Evaluation of Blockchain Platforms

Performance Evaluation of Blockchain Platforms

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IoT, Communication and Automation Technology (ICICAT), International Conference on

作者： Manish Kumar Gupta Rajendra Kumar Dwivedi Annu Sharma Mansoor Farooq Britto Raj S Department of Information Technology & Computer Application Madan Mohan Malaviya University of Technology Gorakhpure UP India Department of Computer Science & Application RajaRajeshwari College of Engineering Bengaluru India Department of Management Studies University of Kashmir Jammu & Kashmir India Department of Computer Science & Engineering RRASE College of Engineering Chennai India

Blockchain (BC) is a cryptographic technology that enables the decentralized storage of an immutable record of transactions. As a result, many industries are interested in integrating BC into their IT systems. Although BC-based platforms are used in enterprise solutions, concerns regarding accessibility, privacy, performance, and scalability are still legitimate. Permissioned Blockchain (PBC) frameworks provide a solution to securely store private records. The main objective of this paper is to focuses on the performance and scalability of popular private BC platforms. To evaluate each platform, we varied the workloads and assessed performance metrics. Our comparative analysis provides valuable insights into the strengths and weaknesses of each platform, enabling enterprises to make informed decisions when choosing a private BC solution.

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Recognizing the Possible Advantages of Big Data Insights for Medical Companies

Recognizing the Possible Advantages of Big Data Insights for...

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

作者： Rainy Sikand Harveer Singh Department of Master of Computer Application Chandigarh School of Business Department of Computer Science Engineering Sanskriti University Mathura Uttar Pradesh India

The potential advantages have not yet been completely realized by the medical industry. While a majority of effort is now concentrating on technology, there is an urgent need for a deeper awareness of the strategic aspects of big data. This paper investigates the evolution, organizational layout, and individual functions of big data analytics in order to fill this gap. We were able to identify five big data analytics features from research method of 26 big data adoption examples in universal health care: analytical capacity for modes of care, unprocessed advanced analysis competence, recommender potential, specific number, and connectivity in the information tech (IT) infrastructural, operating, organizational, executive, and strategy sectors, we also delineated the advantages brought about by big data analytics. Additionally, we suggest five ways for healthcare firms thinking about using big data analytics. Our research will enhance hospital companies' efforts to develop more successful document insights approaches by assisting them in better understanding the capability and advantages of big data analytics.

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Next Generation Digital Health Monitoring System Using Artificial Neural Network

Next Generation Digital Health Monitoring System Using Artif...

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Recent Trends in computer science and Technology (ICRTCST), International Conference on

作者： Yunika Kadayat Sachin Sharma Sakshi Painuly Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun India Department of Computer Science and Engineering Graphic Era Deemed to be University Graphic Era Hill University Dehradun India Department of Computer Application Graphic Era Hill University Dehradun India

ISBN: (数字)9798350351378

ISBN: (纸本)9798350351385

By empowering early identification and provoke reaction within the occasion of health irregularities, another era digital health monitoring systems are basic to guaranteeing people’s prosperity. ANNs, or artificial neural networks, have become successful devices for making exact and successful health monitoring systems. This ponder offers a careful examination of how ANNs are utilized in health monitoring systems. It covers the standards of ANNs, considers how they fit into systems for health monitoring, gives case illustrations, and talks around the obstacles and up and coming advancements in this region.

关键词： Artificial neural networks Market research Electronic healthcare Appraisal Security Protection Monitoring

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A Review on Challenges, Opportunities, And Solutions For 5th Generation Based IoT Using Blockchain & AI

A Review on Challenges, Opportunities, And Solutions For 5th...

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

作者： Krishan Kumar Sharma Amita Salaria Department of Computer Science Engineering Vivekananda Global University Jaipur India Department of Master of Computer Application Chandigarh School of Business Jhanjeri

The Internet of Things (IoT), which connects billions of electrical gadgets over the internet, has completely transformed the digital world. In the present day, as traditional equipment become more autonomous and intelligent, IoT devices are crucial. Increased data transfer is one major problem where 5 g networks world is crucial. However, these Internet of Things (IoT) devices utilizecentralized architecture-based protocols, which may result in a number of security risks for the data. Virtual reality, autonomous robotics, self-driving cars, and security difficulties may all be resolved by integrating artificial intelligence with 5G wireless infrastructure. The main goal of the system is to increase user confidence without relying on external authority. Blockchain has become a crucial technology that keeps track of the network’s event records via a distributed ledger. For IoT devices, blockchain offers a safe, decentralized, and trustworthy ecosystem. IoT and blockchain integration, however, is not without its difficulties. For instance, poor throughput is a key problem. IoT devices need a substantially greater throughput than the 12 to 15 transactions per second that the Ethereum blockchain network can currently handle. On light of this, blockchains are unable to function in an IoT-based 5G network. The blockchain’s network is the factor that restricts throughput. The P2P network’s delayed transaction and block propagation prevents miners and verifiers from quickly mining and, respectively, verifying new blocks. Therefore, the main problem with IoT-based blockchains is network scalability. That is in our past work, we utilized a dispersed blockchain organization to defeat the issue of organization versatility, and in this article, we utilize the Pontoon agreement technique to help the throughput of the blockchain. Security is one more essential worry with IoT organizations. Unfortunately, the blockchain’s dispersed records are available to general society and delic

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BIFT: A federated learning System for Connected and Autonomous Vehicles Based on Blockchain

BIFT: A federated learning System for Connected and Autonomo...

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

作者： Aarti Yadav Amandeep Kaur Department of Computer Science Engineering Vivekananda Global University Jaipur India Department of Master of Computer Application Chandigarh School of Business Jhanjeri

Algorithms for machine learning(ML) are essential for autonomous driving. The vast majority of history’s automated and connected cars send a significant quantity of movement data collected from many automobiles to a central server for regular training. Nonetheless, the info process has made the safety and confidentiality of information essential. Nowadays, the development of federated learning (FL) for data security has the potential to potential to enhance distributed machine learning’s data privacy. The malicious attackers might still target the training process, though. FL is extremely vulnerable because of its total dependency on the central server. We suggest BIFT as a solution to the aforementioned issue, which consists of two parts: 1) a completely decentralized 2) A blockchain-based machine learning system for CAVs that guarantees privacy. With the use of their own driving data, BIFT’s scattered CAVs may train local machine learning models, which they can subsequently upload to improve the global model. In order to fend off potential attackers, BIFT offers a consensus mechanism called Proof of Federated Learning. We assess BIFT’s performance and demonstrate that it is scalable, reliable, and capable of fending off harmful assaults.

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A Multi-Objective Hyper-Heuristic Improved Configuration of Svm Based on Particle Swarm Optimization for Big Data Cyber Security

A Multi-Objective Hyper-Heuristic Improved Configuration of ...

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

作者： Jyoti Shekhawat Tajpal Department of Computer Science Engineering Vivekananda Global University Jaipur India Department of Master of Computer Application Chandigarh School of Business Jhanjeri

Big Data Cyber security analytics is a growingly significant field of study and application that uses big data techniques and technology to analyses security event data in order to safeguard networks, computers, and data from illegal access. There have been several reports on Big Data Cybersecurity Analytic Systems in the literature, but an exhaustive and systematic analysis of the research from an architectural viewpoint is lacking. When In this paper, the SVM design process is organized as a bi-objective optimization problem with accuracy and model complexity as two competing goals. The system presents a novel, problem-independent hyper-heuristic framework for bi-objective optimization. It is novel to create a hyper heuristic for this situation. The hyper-heuristic structure proposed comprises of low-level heuristics and a significant level system. In light of the pursuit execution, the significant level system figures out which low-level heuristic ought to be utilized to create another SVM arrangement. Every one of the low-level heuristics look through the SVM design search space really utilizing an alternate arrangement of rules. To estimate the Pareto set of SVM arrangements, the suggested design adaptively combines the benefits of degradation with Pareto-based strategies for dealing with bi-objective enhancement. Microsoft's anomalous intrusion detection and big data malware classification have been used to gauge the efficiency of the suggested methodology.

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Studying the Effect of an Online Realm Based on Wearable Technology on Learners' Understanding

Studying the Effect of an Online Realm Based on Wearable Tec...

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Artificial Intelligence and Smart Communication (AISC), International Conference on

作者： Kirti Mizan Ali Khan Department of Master of Computer Application Chandigarh School of Business Department of Computer Science Engineering Sanskriti University Mathura Uttar Pradesh India

An interactive system called imperative (AR) creates a realistic and genuine educational and learning environment. The latest crop clearly prefers innovation training over conventional teaching methods. Studies on scientific test techniques are still lacking, despite the fact that earlier research on virtual reality has shown some information on how it might enhance learning results in several subjects. Students need experimental information to better understand the phenomenon. The page discusses the steps involved in constructing & implementing a mobile application for a lab experiment that makes use of augmented reality technology. An extra educational resource for high school seniors is this. The prime purpose of this mobile-based augmented reality program for a scientific experiment is to provide thorough information in addition to conventional processes and educational materials. The experiments that will be shown in ElectroAR include a number of them. An professional review is conducted to evaluate input. In the future, user testing of ElectroAR in actual classroom environments will be conducted.

关键词： Training Technological innovation Interactive systems Crops Mobile applications Artificial intelligence Augmented reality

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