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An Outline of Data Encryption Standard (DES) Tools and Its Facets within the Realm of Cloud Computing

An Outline of Data Encryption Standard (DES) Tools and Its F...

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2023 International Conference on Advances in Computation, Communication and Information Technology, ICAICCIT 2023

作者： Kukreti, Riya Kavitha, R. Joshi, Apoorva Tula's Institute Department of Computer Science and Engineering Dehradun India Department of Computer Science and Information Technology Bangalore India Noida Institute of Engineering and Technology Computer Applications Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350344387

The development of Discrete Event Simulation (DES) systems for enhancing decision-making and research in cloud computing has experienced a substantial growth. The growing diversity of cloud systems makes it extremely challenging to effectively manage cloud resources and services inside data centers. The increasing prevalence of Internet of Things (IoT) gadgets, smartphone apps, and cloud services, together with the introduction of concepts like Edge and Fog Computing, have made this system more complex. A significant amount of time and effort must be invested in these tasks. In intricate hyperscale computer environments, decision assistance is provided by the safe and dependable DES technology. This study aims to provide a comprehensive evaluation of DES systems made especially for cloud computing environments. The study carefully evaluates these instruments in a number of categories and is based on a thorough investigation of recent literature. This study goes beyond conventional stand-alone simulation systems by incorporating custom extensions and add-ons designed for certain cloud computing tasks. In addition to highlighting CloudSim's increasing significance as the main platform for simulated research, this also draws attention to the lack of tools made expressly for distributed execution. © 2023 IEEE.

关键词： Cloud computing Cloud Simulation Tools Data Centre Fog Computing

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A Comparative Analysis of Different Machine Learning Techniques For Medical Insurance Premium Prediction 1

A Comparative Analysis of Different Machine Learning Techniq...

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1st International Conference on Cognitive, Green and Ubiquitous Computing, IC-CGU 2024

作者： Dash, Satyabrata Panigrahi, Bhawani Sankar Sanikommu, Vijay Venkata Bhaskar Reddy Madhavi, B.K. Sahoo, Susanta Kumar Department of Computer Science & Engineering Vishakhapatnam India Vardhman College of Engineeing Department of Information Technology Telangana Hyderabad India Ramachandra College of Engineering Department of Computer Science & engineering Andhra Pradesh Eluru India Indira Gandhi Institute of Technology Department of Computer Science Engineering & Applications Odisha Sarang India

ISBN: (纸本)9798350361780

Predicting health insurance premiums is a crucial task for both insurance companies and policyholders. This paper explores the use of regression approaches to predict health insurance premiums. The study uses a dataset of insurance premiums and related variables, including age, gender, BMI, and location to determine the factors that have the biggest effects on insurance rates. The study found that age and BMI were the main predictors of insurance rates, with gender and location having a relatively little influence. To create predictive models, the study combined various regression approaches, including logistic regression, Random Forest Regression, Decision Tree Regression, Gradient Boosting Regression, and linear regression. The predictive models were highly accurate, with a mean absolute error of less than 5% across all examined samples. The findings have significant implications for both insurers and customers, as accurate premium pricing is essential for insurers to maintain their financial health and offer customers coverage at reasonable prices. Accurate premium forecasts help policyholders plan their spending wisely for insurance costs and make informed decisions regarding their healthcare coverage. © 2024 IEEE.

关键词： Health insurance

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Image encryption using XOR-based continuous tone MSS and Cellular Automata 6

Image encryption using XOR-based continuous tone MSS and Cel...

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6th International Conference on Information Systems and computer Networks, ISCON 2023

作者： Akanksha Garg, Hitendra Shivani, Shivendra GLA University Dept. of Computer Engineering and Applications Mathura India Thapar Institute of Engineering and Technology Dept. of Computer Science Patiala India

ISBN: (纸本)9798350346961

Online communication has become quicker and simpler as a result of the growth of the internet and the advancement in technology. People are using multimedia data in almost all spheres of life. The amount of multimedia data transmitted has been increasing at a massive rate. Multimedia data delivered over open and unreliable networks are susceptible to unauthorized access. As a result, a cryptographic standard is needed to securely and efficiently transmit multimedia data such as images over the networks. This study uses cellular automata and an XOR-based continuous tone MSS approach to create an image encryption method. The suggested approach has eliminated VC's drawbacks, including secret/share quantity constraints, unpredictable share patterns, codebook requirements, and pixel extension in shares and recovered secret pictures. The recommended approach uses an (n,n) multi-secret sharing system that can send n secret photos simultaneously. At the time of encoding, the master share overcomes been made using the secret key, and it may be successfully retrieved when decoding using a comparable secret key. The exploratory results and security examination shows the proficiency of the given approach. The complexity of the proposed approach can be adjusted by using the different combinations of cellular automata rules.. © 2023 IEEE.

关键词： Cellular automata

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MediGlove: Integrating IoT and Machine Learning for Personalized Remote Health Care 2

MediGlove: Integrating IoT and Machine Learning for Personal...

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2nd International Conference on Data science and Information System, ICDSIS 2024

作者： Nanda, K.V. Keerthan Kumar, T.G. Achyutha Prasad, N. Raviprakash, M.L. Anand Babu, J. Naveen Kumar, M.R. Sri Siddhartha Institute Of Technology Master Of Computer Applications Tumkur India Siddaganga Institute Of Technology Information Science And Engineering Tumkur India East West Institute Of Technology Computer Science And Engineering Bangalore India Kalpataru Institute Of Technology Artificial Intelligence And Machine Learning Tiptur India Malnad College Of Engineering Information Science And Engineering Hassan India Vidyavardhaka College Of Engineering Information Science And Engineering Mysore India

ISBN: (纸本)9798350381665

Mobile operating systems have advanced significantly in recent decades, with Android emerging as a widely used open-source platform. Simultaneously, the Internet of Things (IoT) has transformed computer equipment by enabling seamless data transfer over networks without human involvement. This study makes use of intelligent gloves equipped with various sensors, as well as IoT and Android applications, to improve healthcare. In this work, we introduce a pioneering framework that combines IoT and Android technology to revolutionize remote health monitoring called IoT-enabled Smart Gloves for Remote Health Monitoring using an Android-based solution approach (MediGlove). MediGlove uses intelligent smart gloves with robust sensors to continuously collect crucial health data. The solution works with IoT devices to send data quickly to a cloud-based server. The cloud server provides real-time health metric analysis with great precision by utilizing cutting-edge algorithms and machine learning techniques. A simple Android software acts as a dynamic health dashboard, allowing users to track their health in real-time. The framework generates real-time alerts for problematic health markers, allowing prompt medical action. Extensive testing validates the system's efficacy and dependability in health monitoring and the seamless integration of smart gloves with Android applications. © 2024 IEEE.

关键词： Internet of things

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Double Encryption Technique for Sharing and Storing the Images in the Cloud Environment 4

Double Encryption Technique for Sharing and Storing the Imag...

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4th International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Anusha, P. Maruthi, R. Kumar, D. Maghesh Begum, H. Parveen Periyar Maniammai Institute of Science and Technology Department of Software Engineering Tamil Nadu Thanjavur India Hindustan Institute of Technology and Science Department of Computer Applications Tamil Nadu Chennai India

ISBN: (纸本)9798350343670

Cryptography is used by all organizations to protect the data files and ensures confidentiality mainly at the time of sharing and storing in the cloud data storage. The cloud service providers use a wide range of tools and techniques for encryption and storage technologies. The intruders are finding number of ways to break or attack the cryptographic systems, so that new ways are constantly being explored to safeguard our files from the attackers This paper explores double encryption cryptographic technique based on Elliptic curve cryptography (ECC) and Advanced Encryption Standard (AES) to perform end-to end encryption for sharing and storing files in the cloud environment. © 2024 IEEE.

关键词： Advanced Encryption Standard Cloud Cryptography Elliptic Curve Cryptography File Sharing

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A Novel Approach to Optimize EV's Dealing and Charging

A Novel Approach to Optimize EV's Dealing and Charging

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Vijay, Sandip Gobi, N. Sharma, Ambrish Kumar Tula's Institute Department of Computer Science and Engineering Dehradun India Department of Computer Bangalore India Computer Applications Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350357769

It's an interesting idea to investigate the energy market as a potential means of reducing the power costs related to charging electric cars at public charging stations. Through intraday energy markets., several nations allow electricity trading until just before the delivery time. This research utilizes the market as an illustration to investigate the possibility of lowering power prices via intraday market trading. After conducting extensive simulations., the results show that charging schedule optimization combined with intraday trading in the markets may result in cost savings of around 9% when compared to obtaining all needed energy from the energy provider. A further 2% or more of cost savings may be realized by giving the charging station manager the ability to resell energy to the everyday electricity market. The research explores how the intraday electricity market's lead time and trading unit affect total expenses in addition to any possible cost savings. Lead time is shown to have a major impact on feasible power prices., whereas each trading unit has a negligible impact on the total cost dynamics. © 2023 IEEE.

关键词： charging schedule Electric vehicles (EV's) electricity costs mixed-integer linear programming trading

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5G in Smart Cities: Enhancing Urban Futures for Sustainable Growth

5G in Smart Cities: Enhancing Urban Futures for Sustainable ...

引用

2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Rajvanshi, Anita Mahajan, Prerna Singh, Alka Tula's Institute Department of Computer Science and Engineering Dehradun India Department of Computer Bangalore India Noida Institute of Engineering and Technology Computer Applications Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350357769

This essay delves into the concept of 'Smart Cities,' outlining its numerous benefits. It elucidates the diverse applications and services essential for transforming a city into a Smart City, underscoring the pivotal role of Information and Communication Technology (ICT) in their realization. Furthermore, it scrutinizes the challenges posed by the deployment of Smart Cities for contemporary ICT systems. The study investigates the promised attributes of 5G technology and its potential as a linchpin for the efficient implementation of urban smart cities. Additionally, it provides a catalog of 5G-enabled Smart City use cases, emphasizing how 5G will serve as the bedrock for the Internet of Things (IoT), fostering the evolution of smart cities. © 2023 IEEE.

关键词： 5G technology ICT infrastructure Information and Communication Technology Internet of Things Quality of Life Smart Cities Smart ICT infrastructure Sustainable City Urban Transit and City Governance

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Quantum Machine Learning Techniques based on Nurturing Agri-Ontology Framework in Agricultural science 3

Quantum Machine Learning Techniques based on Nurturing Agri-...

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3rd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Deepa, R. Jayalakshmi, V. Thilakavathy, P. Bennet Prabhu, A. Surendran, R. Srm Institute of Science and Technology School of Computing Department of Computing Technologies Chennai India Drbccc Hindu College Department of Computer Applications Chennai India Computer Science and Engineering Vels Institute of Science and Engineering Vels Institute of Science Technology and Advanced Studies Chennai India Kone Elevator India Technology & Engineering Centre Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350375190

The absence of a consistent ontological framework often impedes efficient knowledge organization and sharing within the agricultural community, despite the quantity of data created in agricultural research. The lack of defined vocabulary and conceptual frameworks hinders data integration, agricultural research, and innovation by preventing interoperability between databases and systems. To address these issues, this research work proposes the Nurturing Agri-Ontology Framework (NAOF), which offers a systematic approach to creating and updating agricultural ontologies. Ontologies that faithfully portray agricultural ideas and connections can be more easily created with the help of NAOF, which combines ideas from knowledge management, agricultural science, and ontology engineering. NAOF aims to ensure that the ontologies produced reflect the wide range of viewpoints and terminology used in agricultural research by encouraging cooperation among stakeholders, ontology engineers, and domain specialists. In this study, the improvement of knowledge organization, sharing and integration in the agricultural area is shown with the application of NAOF. Using this research study, scientists can build ontologies that improve agricultural decision-making, data interoperability, and the discovery of new information. Using quantum machine learning techniques, a strong foundation of knowledge can be laid for several agricultural applications, such as precision agriculture, crop management, and the formulation of agricultural policies. Ontology coverage, interoperability, scalability, and usability are established evaluation parameters that are used to assess the efficacy of NAOF in this research work. The analysis shows that NAOF effectively solves the problems and creates a better agricultural knowledge ecosystem by thoroughly evaluating it using these standards. © 2024 IEEE.

关键词： Ontology

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Experimental Analysis on Banking Customer Segmentation using Machine Learning Techniques

Experimental Analysis on Banking Customer Segmentation using...

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2023 IEEE Global Conference on Information Technologies and Communications, GCITC 2023

作者： Pandey, Trilok Nath Navya Kala, S.V. Amrutha, S. Dash, Bibhuti Bhusan Patra, Sudhansu Shekhar Vellore Institute of Technology School of Computer Science and Engineering Chennai India Kiit Deemed to Be University School of Computer Applications Bhubaneswar India

ISBN: (纸本)9798350308167

The intent of customer segmentation is primarily to aid institutions to custom-make their marketing techniques and methods to suit the specific requirements of every consumer group. As this helps to solve the segregating of the groups of customers for banks efficiently and helps provide more custom-made services for customers of each group better, applying the customer segmentation for banking data can provide many insights that can be beneficial to banks as well as their customers. This increases the effectiveness of customer interaction and can maximize selling opportunities. It makes marketers more efficient in terms of time, money, and other resources. © 2023 IEEE.

关键词： Customer segmentation Gaussian mixture model clustering hierarchical agglomerative clustering hyper parameter tuning k-modes

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Observing Different Machine Learning Approaches for Students’ Performance Using Demographic Features 6th

Observing Different Machine Learning Approaches for Students...

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6th International Conference on Innovative Computing and Communication, ICICC 2023

作者： Srivastava, Neeraj Kumar Pandey, Prafull Mishra, Manoj Kumar Mishra, Vikas Department of Computer Science and Engineering United Institute of Technology Prayagraj Naini India Department of Computer Science and Engineering United College of Engineering and Research Prayagraj Naini India Department of Computer Applications United Institute of Management Prayagraj Naini India

ISBN: (纸本)9789819930098

The use and importance of educational data mining (EDM) are growing very fast as the entire world is going digital. The predictions of EDM [1, 2] are playing very important role not only in improving the academic performance of individual students but also are very useful for institutions, policy makers, administrators to plan and design new policies that will certainly help them to achieve high academic performance of their students. On this basis, this paper approaches students’ performance in secondary school of two Portuguese schools. The informational elements comprise demographic, societal, and educational [3] features. Although there are many ML [4, 5] algorithms, yet in this paper, five ML classifiers such as random forest, Naïve Bayes, logistic regression, decision tree, and support vector machine have been used to predict the students’ performance that on the basis of given features, whether a student can be passed in secondary education or not. On the dataset, the Naïve Bayes classifier gives the best performance than other classifiers, when the dataset is partitioned into 80–20 ratio as training and test datasets. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Decision trees

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