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1481 articles for “Computational Data”
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AI for Cybersecurity: Deploying Machine Learning for Network Traffic Anomaly Detection
Abstract: The growing sophistication of cyberattacks and the growth of network traffic necessitate sophisticated anomaly detection methods. This study overviews the use of artificial intelligence (AI) and machine learning (ML) to counter these challenges, as noted in current studies. It analyses supervised learning (SVM, Decision Trees), unsupervised learning (K-means, DBSCAN), and deep learning (CNNs, RNNs, Auto-encoders) approaches, considering their strengths and weaknesses. The research integrates current developments in AI/ML-based network anomaly …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article
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Blockchain-based Privacy-preserving Data Sharing in Healthcare Systems
Abstract: Healthcare systems contain expansive yet fragmented sensitive data necessitating secure consolidated access mechanisms respecting patient consent preferences continually. This research develops a decentralized blockchain framework orchestrating granular authorization using cryptography while demonstrating efficacy via clinical implementations optimizing cancer diagnostics through aggregated genome analysis otherwise prohibited under isolated datasets. Comparative benchmarking against traditional database models evaluates correctness, interoperability, and auditability improvements using multiparty endorsement affirming consented transactions. Quantified metrics guide technology …
Published in Journal of Advanced Database Management & Systems · Vol. 10, Issue 3, 2023 · pp. 28–34 Read article
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A Computer Based Economic Study on Manufacturing and Marketing of Coir in Tirunelveli District
Abstract: Using the internet to collect data is convenient and can greatly extend sample representativeness; however, the use of internet is not without some risk. During the doctoral research of one of the authors, data were being collected using a mobile computer laboratory with an array of laptop computers, so as to avoid the time-consuming data entry process. Coir industry in India is an agro-based, village and cottage industry. Despite of …
Published in E-Commerce for Future & Trends · Vol. 5, Issue 2, 2018 · pp. 1–5 Read article
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Coarse Grain to Mixed Grain Parallel Computing
Abstract: Parallel computing interests are growing again as a result of multicore processors. History of parallel computing dates back to early 1970’s when supercomputers supported high performance computing demand for scientific applications. Today, highly dense Very Large Scale Integration (VLSI) chips have opened up new opportunities and challenges for parallel computing. In this article, we provide a short synopsis of an evolutionary path of parallel computing from both hardware granularity and …
Published in Recent Trends in Parallel Computing · Vol. 1, Issue 2, 2014 · pp. 1–10 Read article
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Performance Analysis of Deep CNN Architectures
Abstract: A Convolutional Neural Network (CNN) is an artificial neural network renowned for its remarkable ability to handle large image datasets effectively, particularly excelling in tasks such as image recognition and classification. The fundamental structure of a CNN relies on mathematical convolution operations, comprising essential components such as convolutional layers, activation functions, pooling layers, and fully connected layers. These components work synergistically to extract and learn hierarchical features from input data, …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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Predicting Multiple Diseases Using Machine Learning: A Data-Driven Approach
Abstract: The increasing prevalence of chronic and life-threatening diseases highlights the need for innovative healthcare solutions that enable early detection and proactive management. The Multiple Disease Prediction Platform is a web-based system utilizing machine learning (ML) and deep learning (DL) algorithms to analyze user-inputted health data, generating real-time predictions of potential health risks. By leveraging Python’s Streamlit library, the platform provides an interactive and accessible diagnostic experience, eliminating the need for …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 16–35 Read article
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Advanced Private Cloud Security and Privacy Preservation Through the Integration of Machine Learning and Cryptography
Abstract: In modern technological landscapes, private cloud security is of paramount concern due to the ever-increasing volume and complexity of cyber threats. This research work explores the integration of machine learning and cryptography to enhance security within private cloud environments. This study aims to mitigate vulnerabilities that may compromise data integrity, confidentiality, and availability in private cloud infrastructures by using machine learning algorithms and strong cryptography. By detecting anomalous cloud patterns …
Published in International Journal of Advanced Control and System Engineering · Vol. 2, Issue 1, 2024 · pp. 1–10 Read article
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Database Intrusion Detection Using Genetic Support Vector Fuzzy Clustering Learning Model
Abstract: AbstractThe rapid development of computer networks and increasing dependency of almost all companies and government agencies on Internet and cloud computing lead to the problem of stability and security like intrusions in several forms which can cause huge loss to these organizations. During recent years, disaster in data due to intrusions has dramatically increased. The hindrance of such intrusions is entirely dependent on their detection part which can be possible …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 2, 2019 · pp. 32–40 Read article
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ECO Report Analys Achieving SDG 15
Abstract: This project creates automated data processing tool Eco Data Analyser for ecological data analysis for SDG 15: Life on Land conservation and biodiversity. File_picker, Excel, and CSV are used in the Flutter and Dart based cross-platform solution to assist environmental organizations in handling ecological data. Uploading ecological datasets, verifying data, classifying biodiversity indicators, and producing summary reports helps Eco Data Analyser to make conservation data accessible and valuable. User-defined parameters …
Published in International Journal of Land · Vol. 2, Issue 2, 2025 · pp. 1–10 Read article
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Ring Protocol Improvising the Existing Data Link Layer Protocols
Abstract: AbstractRing protocol is an algorithm to improve upon the performance of existing data link layer protocols like Selective Repeat ARQ by reducing the number of acknowledgements and at the same time, reducing the number of retransmissions. A data structure with a ring whose size can be dynamically altered acts as the cornerstone for this algorithm.Keywords: Protocol, computer networks, data link layer, noisy channel, Wi-FiCite this ArticlePrajit TR, Sarala SM. Ring …
Published in Journal Of Network security · Vol. 5, Issue 2, 2017 · pp. 1–5 Read article
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AI-Driven Precision Nutrition: Advancing Personalized Dietary Systems for Public Health Equity in Resource-Constrained Environments
Abstract: The dual burden of malnutrition and diet-related non-communicable diseases (NCDs) represents a growing global public health challenge, particularly in low- and middle-income countries. Traditional dietary guidelines are largely population-based and fail to account for individual variability in genetics, metabolism, lifestyle, and environmental exposure. This limitation has led to the emergence of precision nutrition, an evolving field that integrates biological data and computational intelligence to deliver personalized dietary recommendations. This paper …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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Advances in Lung Cancer Detection and Diagnosis: An Integrative Approach Using Computational Chemistry, Statistics, Bioinformatics, Artificial Intelligence, and Machine Learning
Abstract: Lung cancer is still one of the most common and lethal cancers globally, accounting for more than a million deaths each year. Prompt detection is important, and imaging techniques like chest X-rays, MRIs, PETs, CTs, and molecular imaging have become important tools. But still, even though all these techniques do not provide an accurate classification of the lesion, they have led to the development of computer-based high-resolution image analysis. Computer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Advanced Computational Models for Predicting Molecular Interactions
Abstract: Understanding molecular interactions is essential for a number of disciplines, including biochemistry, materials science, and medication development. Traditional experimental methods, while accurate, are often time-consuming and expensive. Advanced computational models have emerged as powerful tools to predict molecular interactions efficiently. In order to predict the behavior and interactions of molecules at the atomic and subatomic levels, this paper reviews the most recent developments in computational techniques, such as machine learning …
Published in International Journal of Advance in Molecular Engineering · Vol. 2, Issue 1, 2024 · pp. 8–13 Read article
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A Comprehensive survey of robust image quality metrics for satellite imagery
Abstract: Satellite imagery is essential for applications like environmental monitoring, urban development, precision agriculture, defence surveillance, and disaster response. The reliability of these applications is closely tied to the quality of the captured images, which may be compromised by atmospheric effects, sensor imperfections, compression artifacts, and transmission noise. As a result, accurate image quality assessment (IQA) is essential to ensure trustworthy analysis and informed decision-making in satellite-based systems. The distinctive properties …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 1, 2026 · pp. 7–20 Read article
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A Survey on Different Approaches of Attribute based Encryption For Cloud File System
Abstract: Cloud computing has emerged as a solution for organizations that desire services on lease. It enables convenient and on-demand network access to a centralized pool of configurable computing resources. Among many of its applications, File distributing and sharing is one of the most commonly used services in cloud computing. The requirement of data security grows with the faster growing cloud computing. One feasible solution is Attribute based encryption (ABE). In …
Published in Current Trends in Information Technology · Vol. 4, Issue 1, 2014 · pp. 1–3 Read article
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IOT Big Data Techniques for Smart Home: A Study for Applicable in Small City at India
Abstract: AbstractInternet of Things is the connections of embedded technologies that contained physical objects and is used to communicate and intellect or interact with the inner states or the external surroundings, rather than people to people communication, IoT emphasis on machine to machine communication. This paper represents Big Data deployment in smart homes as it was limited for its applicability in IT industry. The proposed architecture can be applied to different …
Published in Journal of Operating Systems Development & Trends · Vol. 7, Issue 3, 2020 · pp. 20–24 Read article
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Feature Selection Using Nature-Inspired Metaheuristics: A Brief Study
Abstract: In recent decades, feature selection (FS) has attracted a lot of attention. The rapid advancement of data and computer science has led to an increase in the number of studies being conducted. The preprocessing method of feature selection plays a significant role in increasing the effectiveness of data mining and analysis across significant real-world applications. To summarize the most recent studies, this research work offers a quick assessment on feature …
Published in Current Trends in Information Technology · Vol. 13, Issue 1, 2023 · pp. 12–21 Read article
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Exploring the Landscape of Big Data: Impact, Tools, Challenges, and Opportunities
Abstract: This study explores the constantly changing field of big data, not merely as a repository of enormous amounts of information, but also as a force that is reshaping our world. It sheds light on the ways in which big data stimulates creativity and drives change in a variety of sectors, including urban planning, finance, healthcare, and environmental sustainability. Through the investigation of state-of-the-art analytics, distributed computing, and data visualization tools, …
Published in Current Trends in Information Technology · Vol. 14, Issue 1, 2024 · pp. 1–4 Read article
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Experiences of Women with the Labour and Delivery Care Received at Mzimba District Hospital, Malawi
Abstract: Aim: The aim of the study was to explore the perceptions of women on the care that they received during normal labour and delivery at Mzimba District Hospital, Malawi. Specific Objectives: To evaluate the aspects of physical care that was rendered to women during labour and delivery, evaluate the psychological care that was rendered to women throughout labour and delivery, assess the perception of women on the attitudes of midwives …
Published in International Journal of Women's Health Nursing And Practices · Vol. 2, Issue 1, 2024 · pp. 37–46 Read article
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Leveraging Deep Learning for Accurate Weed Identification
Abstract: Weed control is very important for all types of agricultural businesses. The project here revolves around the application of computer vision techniques and, more concretely, deep learning techniques, for the effective recognition and classification of weeds. The EfficientNetB4 architecture is an appropriate backbone as its scalability and performance optimization is adequate. The modifier used is Adam optimization algorithm which will serve as a pre- processor for the model. Weeds at …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 90–99 Read article