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1939 articles for “data” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Enhancing Data Processing and Storage in Computing Environments: A Survey on the Use of NVMe SSDs
Abstract: In the current era of fast pace technological growth, the efficiency of data processing and storage systems has become a key factor of various computing environments. This survey explores the transformative role of Non-Volatile Memory Express (NVMe) Solid-State Drives (SSDs) across different domains, including Big Data processing, Cloud Computing, High Performance Computing (HPC), and containerized applications. The motivation behind this comprehensive review is to understand how NVMe SSDs, known for …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 3, 2025 · pp. 01–21 Read article
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Passenger car fuel economy: Insights from big data analytics
Abstract: The increasing availability of real-world vehicle telematics through On-Board Diagnostics II (OBD-II) systems has enabled data-driven evaluation of passenger car fuel economy beyond conventional laboratory-based test cycles. While standardized certification procedures ensure repeatability, they often fail to capture the influence of real-world traffic conditions, driver behaviour, and transient vehicle operation. This study presents a structured Big Data Analytics (BDA) approach for analysing high-frequency OBD-II data collected from a gasoline passenger …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 8–19 Read article
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Predicting Dielectric Constants of Polymers Using Molecular Structural Descriptors and Explainable Machine Learning: A Data-Driven Approach
Abstract: Accurate prediction of dielectric constants in polymeric materials is fundamental to the rational design of advanced electronic components, energy storage capacitors, flexible substrates, and high-frequency communication circuits. Conventional approaches to identifying suitable polymer dielectrics rely on extensive experimental synthesis and characterisation, which are both time-consuming and resource-intensive. In this work, an explainable machine learning framework is developed to predict the dielectric constant of polymers directly from molecular structural descriptors derived …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 297–304 Read article
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Design and Performance Assessment of Light Weight Data Security System for Secure Data Transmission in IoT
Abstract: The Internet of Things (IoT) is expected to provide an interface for future technologies’ small processing tools. It is expected to provide more communication data and information security can risky. Data pinnacles and information security can be a risk. This size of the gadget in this engineering is essentially little, low power utilization. Many rounds of encryption are essentially a misuse of requirements Gadget vitality. Less convoluted calculation, be that …
Published in Journal Of Network security Read article
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Challenges in Parallel Computing for Big Data Analytics
Abstract: The integration of parallel computing into the realm of big data analytics promises accelerated processing speeds and enhanced scalability, but it is not without its formidable challenges. This study explores the multifaceted hurdles faced in the pursuit of efficient parallel processing for large-scale data analytics. The intricate task of distributing and partitioning massive datasets across multiple processing units demands adept strategies to ensure equitable workloads. Load balancing emerges as a …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 1, 2024 · pp. 1–6 Read article
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Interest Level Prediction in Rental Properties Using Data Science
Abstract: A key component of forecasting home prices and rental patterns is real estate market analysis. Data science, data mining methodologies, and statistical models are some of the strategies that have been created in recent years to solve this problem. A few problems are still required to be resolved, such as the obstacles caused by the availability and quality of the data; the presence of outliers, missing values, and inconsistent formats …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 1, 2024 · pp. 28–34 Read article
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Big Data Analytics in Healthcare: Revolutionizing Patient Care with IoT
Abstract: Patient care is undergoing a transformation thanks to the Internet of Things (IoT) and Big Data Analytics, which are enabling more accurate, proactive, and customized medical interventions. This paper explores how the integration of IoT devices with advanced data analytics can transform healthcare delivery. By collecting and analyzing vast amounts of real-time data from wearable devices, remote monitoring systems, and smart medical equipment, healthcare providers can gain valuable insights into …
Published in Recent Trends in Sensor Research & Technology · Vol. 11, Issue 2, 2024 Read article
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Data Recovery Using Brute Force Algorithm: A Review
Abstract: This article delves into the intriguing field of data recovery, with a particular emphasis on the brute force approach, a powerful yet frequently underappreciated method. We begin by exploring the evolution of data recovery techniques since the 1970s and 1980s, examining traditional methods used to retrieve lost or corrupted data. Following this historical perspective, the article provides a brief overview of various methodologies employed in data recovery, including techniques that …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 10–16 Read article
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Innovative Approaches to Reducing Data Traffic in IoT Networks Using Deep Learning and Compressive Sensing
Abstract: The exponential growth of internet of things (IoT) devices has posed unprecedented challenges in managing the massive data generated by real-time monitoring, automation, and analytics. Existing network infrastructures lack scalability, bandwidth, and suffer from latency problems, further making data transmission less efficient. This study surveys innovative approaches using deep learning and compressive sensing to reduce IoT data traffic. Deep learning is able to upgrade data processing by means of very …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 46–62 Read article
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Healthcare IT Innovations: Blockchain Technology for Healthcare Data Security and Privacy
Abstract: The healthcare sector has undergone a significant digital transformation, leading to the generation and sharing of vast quantities of sensitive medical data. While this digitization has improved patient care and outcomes, it has also introduced critical challenges related to data security and privacy. The increasing rate of data breaches in healthcare puts patient confidentiality at risk, mainly leading to identity theft, financial fraud, and loss of public trust in healthcare …
Published in International Journal of Information Security Engineering · Vol. 3, Issue 2, 2025 · pp. 01–12 Read article
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A Data-Driven Analysis of Machine Learning Classification Models for Reliable Crop Yield Prediction
Abstract: The adoption of ML technologies in agriculture is reshaping farming practices, empowering producers to make informed, data-oriented decisions that improve yields, sustainability, and long-term resilience. In mango cultivation, ML analyzes data from weather, soil, and pests to optimize irrigation, fertilization, and pest control. Predictive analytics help forecast ideal farming practices, minimizing resource wastage and improving yield. Real-time monitoring and image-based disease detection allow timely interventions to maintain plant health and …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 1, 2026 · pp. 12–17 Read article
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A Comparison of NoSQL and Relational Database Management Systems (RDBMS)
Abstract: The new aspirant is a non-relational abstracts abundance which is widely deployed in large website environments where there is less reliance on relational databases, leading to enhanced performance in the field of data retrieval. NoSQL are additionally accepted as non-relational databases adulation relational databases and are now acclimated by the world's bigger organizations such as Facebook, Amazon, and Google. Both models are acceptable in specific areas and for specific applications. …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 33–37 Read article
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Advancements in Data Structures: Bridging the Gap Between Theory and Real-world Applications
Abstract: In the rapidly advancing landscape of computer science, this study unfolds a comprehensive exploration of Data Structures, spanning from foundational principles to cutting-edge innovations. Data structures form the backbone of computational processes, and this study aims to dissect and illuminate their pivotal role. Beginning with fundamental concepts such as Arrays, Linked Lists, Stacks, and Queues, the narrative progresses to intricate structures like Trees, Graphs, and Hash Tables. Practical applications in …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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TensorFlow-Based Big Data Analytics for IoT Networks: A Study
Abstract: Internet of Things (IoT) has exploded in recent years, connecting billions of devices generating massive amounts of data. This deluge presents both a significant opportunity and a considerable challenge. While the potential insights hidden within this data are transformative, customary data processing techniques frequently fall short when handled with the velocity, volume, and variety of IoT-generated data. This is where Big Data technologies step in, offering the tools and infrastructure …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 31–38 Read article
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Modeling Dispersed Count Data: Evaluating the Conway–Maxwell–Poisson Regression with COVID-19 Mortality Data
Abstract: Count data are prevalent in diverse fields such as biology, healthcare, psychology, and marketing, characterized by non-negativity and inherent heteroskedasticity, often exhibiting overdispersion or underdispersion. Traditional Poisson regression, which assumes equal mean and variance, is inadequate for such dispersed data. To address this, various generalized linear models (GLMs) and their extensions, including negative binomial (NB) and Conway–Maxwell–Poisson (CMP) regressions, are utilized. This study evaluates the performance of CMP regression compared …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 18–26 Read article
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Data Privacy in AI: Securing the Sensitive Information Through Homomorphic Encryption
Abstract: Artificial intelligence (AI) technology increasingly relies on sensitive user data, particularly finance and healthcare. While legacy encryption technologies safeguard data in transit and at rest, they are of no use when data must be decrypted to be processed. This is a bleak privacy threat, particularly in AI applications that call for constant processing of data. The objective of this study is to apply homomorphic encryption, a feature in which operations …
Published in International Journal of Information Security Engineering · Vol. 3, Issue 2, 2025 · pp. 25–30 Read article
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Webpage Extraction and Retrieval Chatbot
Abstract: Web scraping is a fundamental technique for automating data extraction in big data applications. While multiple implementations exist, few leverage Python’s Beautiful Soup library for efficient and structured data retrieval. This project aims to develop a web scraper and retrieval system that extracts relevant information from web pages, stores it in a vector database (Milvus), and enables intelligent querying using semantic search and generative AI. The system is designed to …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 1–7 Read article
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The Influence of Data Analytics on Sports Performance
Abstract: Data analytics has drastically changed how we evaluate, improve, and maintain athletic performance. Coaches used to use subjective observations as well as only limited numbers of statistics to consider player performance; however, tracking technology is now advancing at a fast pace. There are now very large amounts of real-time data available on athletes in regards to speed, movement patterns, fatigue, efficiency, etc. This enables all teams to more accurately make …
Published in Recent Trends in Sports · Vol. 3, Issue 1, 2026 · pp. 15–21 Read article
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Learning Data Structures: Key to Good Programming
Abstract: Data structures are the most crucial feature of good programming and are needed to solve hard computational problems. This model makes use of two different recurrent neural network architectures, specifically long short-term memory (LSTM), and gated recurrent unit (GRU) networks. It explains how selecting and using the correct data structures may speed up computations, optimize memory, and scale code. How data structures and algorithms relate and how to think about …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 29–39 Read article
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Big Data Analytics for Effective Decision Making in Business Intelligence
Abstract: In this study, we explore the significance of Big Data Analytics (BDA) in enhancing decision-making processes within Business Intelligence (BI) frameworks. It involves processing vast volumes of data from various sources, enabling businesses to identify patterns, trends, and correlations that were previously unnoticed. This analytical power enhances strategic planning, customer understanding, operational efficiency, and competitive advantage. Through advanced algorithms and machine learning techniques, businesses can predict future trends, optimize operations, …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 1, 2024 · pp. 23–28 Read article