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69 articles for “massive data”
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A Study on Data Science Analytics: Addressing Challenges, Exploring Open Research Issues: A Literature Centric Approach
Abstract: The rapid growth of data science and analytics has revolutionized industries across the globe. This paper presents a comprehensive examination of the challenges encountered in the field of data science analytics and investigates unresolved research issues through a literature-centric approach. By analyzing recent research papers, articles, and industry reports, this study offers insights into the evolving landscape of data science and the critical challenges that data scientists face. Additionally, it …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 3, 2023 · pp. 70–82 Read article
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Efficient Clustering Techniques for Data Stream Mining
Abstract: Data mining mainly works on a massive database for storing heavy amount of data. It is generally essential for extracting the meaning insights from the massive, continuously growing database. The traditional method often struggles with sheer volume and the dynamic nature of the modern data. Data stream mining allows for the real-time analysis, means insights are generated as the data arrives, and not after the long batch process. This continuous …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 26–32 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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Remote Sensing Classification Based on Improve Ant-Miner Algorithm: A Case Study of Alwar, Rajasthan, India
Abstract: Earth Observation Satellite (EOS) image itself contains image ambiguity. Various conventional methods like minimum distance to mean or maximum likelihood image clustering algorithm do not meet the accuracy that have required by user in the virtue of cost-effective land use/land cover classification. In Ant colony optimization (ACO), association rule mining is a prevalent and well researched method for discovering useful relations between variables in large databases. The proposed work presents …
Published in Journal of Geotechnical Engineering · Vol. 2, Issue 3, 2015 · pp. 1–5 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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The Emerging Golden Age of Astrophysics: Progress, Discoveries, and Future Directions
Abstract: The period between 2024 and 2026 has marked a transformative era in astrophysics, fundamentally reshaping our understanding of the universe and its underlying physical mechanisms. Significant advancements in observational astronomy, computational modeling, and space exploration technologies have enabled scientists to investigate cosmic phenomena with unprecedented precision. Among the most groundbreaking achievements, the James Webb Space Telescope (JWST) has provided high-resolution infrared observations that revealed the large-scale distribution of dark matter, …
Published in International Journal of Universe · Vol. 2, Issue 1, 2026 · pp. 6–9 Read article
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An Overview on AI-Driven IoT Based Decision Making in Climate change Study: KSK approach in Climate Change Study
Abstract: As the Earth’s climate enters a state of unprecedented volatility, the traditional methods of ecological observation—characterized by delayed reporting and fragmented data—are no longer sufficient. This study investigates the paradigm shift toward AI-driven IoT (KSK Approach)-based decision-making frameworks as the primary frontier in climate science. By deploying a "planetary nervous system" of interconnected sensors—measuring everything from soil moisture in the Sahel to glacial melt rates in the Arctic—we generate a …
Published in International Journal of Climate Conditions · Vol. 3, Issue 1, 2026 · pp. 1–10 Read article
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Complications with Malware Identification in IoT and an Overview of Artificial Immune Approaches
Abstract: An immunity is facilitated by lymphocyte T&B-cells that possess a wide range of T&B-cell receptors, respectively. These cells can identify and react to pathogens and diseased cells by presenting peptide antigens by means of significant histocompatibility complexes (MHCs). The amount of data on the repertoire of adaptive immune receptors has increased dramatically in recent years because to advancements in deep sequencing. Furthermore, the presentation of peptides with MHC has been …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 1, 2024 · pp. 54–62 Read article
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Artificial Intelligence in Pharmacovigilance: Improving Drug Safety
Abstract: Artificial intelligence (AI) is revolutionizing pharmacovigilance (PV) by enhancing the detection, assessment, and prevention of adverse drug reactions (ADRs). This review examines how AI technologies – such as machine learning (ML), natural language processing (NLP), and big data analytics – tackle existing challenges in pharmacovigilance (PV), including issues like underreporting, large data volumes, and inefficiencies in data processing. AI improves drug safety by automating data collection, enabling real-time adverse event …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 1–16 Read article
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Modernizing Pharmacovigilance: Leveraging AI,Automation, and Real-World Data for Drug Safety
Abstract: Pharmacovigilance, or PV, is “the pharmacological science relating to the detection, assessment, understanding, and prevention of adverse effects, mainly long term and short-term adverse effects of medicines.” PV’s specific objectives are to increase patient care and safety when using medications and all medical and paramedical therapies; assist in evaluating the benefits, drawbacks, efficacy, and risks of medications, ensuring their safe, prudent, and more effective use; and promote clinical training, education, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 21–30 Read article
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The Integration of AI Technologies in Automating Cyber Defense Mechanisms for Cloud Services
Abstract: The swift growth of cloud computing has transformed how organizations handle and store data, providing greater scalability and adaptability. However, the transition to cloud-based environments has heightened the complexity of cybersecurity challenges, especially in detecting and responding to security incidents. Conventional methods of incident response, which heavily depend on manual efforts, are no longer adequate to address the rapidly evolving and complex nature of modern cyber threats. This study explores …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 1–14 Read article
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Assessing the Effectiveness of Machine Learning Algorithms in Simulating Malware Detection Processes
Abstract: On the information system comprehends, computer virus attacks play a very important role and, by undermining regionally and globally, are considered one of the most critical threats. The traditional malware detection methods, more varied, being based on signature, are incapable of providing sufficient coverage over malicious programs in a short time. This is due to the speed of evolution and growing complexity of malware variants. This situation, in turn, requires …
Published in Journal of Electronic Design Technology · Vol. 14, Issue 3, 2023 · pp. 11–20 Read article
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Role of Artificial Intelligence in Simulation and Therapeutics in Neurodegenerative Diseases
Abstract: Neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, etc., are a cause of significant mortality rates due to a lack of curative treatments and their complex nature. Traditional therapeutic methodologies have several disadvantages such as slow diagnosis and a lack of effective treatments. They mainly focused on the management of the disease rather than curing it. The integration of artificial intelligence in the simulation and therapeutics of neurodegenerative …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 19–29 Read article
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AI Driven IoT based Satellite remote sensing system: KSK Approach in Satellite Remote Sensing
Abstract: The convergence of the Internet of Things (IoT) and satellite remote sensing has traditionally been bottlenecked by massive data latency and limited downlink bandwidth. This paper proposes a decentralized framework for an "AI-Driven IoT-based Satellite Remote Sensing System," which shifts the paradigm from raw data transmission to onboard edge-intelligence. By integrating lightweight convolutional neural networks (CNNs) directly into satellite payloads, the system performs real-time feature extraction and anomaly detection before …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 50–57 Read article
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A Review on Sybil and Sinkhole of Service Attack in VANET
Abstract: AbstractVehicular Ad-hoc Network (VANET) is one of the forms of wireless network. VANET communication is between vehicle to vehicle and vehicle to infrastructure. Vehicular Communication (VC) systems of a practical dealing signal. The safety and security are major issues to secure our network. It prevents critical information from arriving. It also increases the danger to the driver, if it has to depend on the application’s information. For example, malicious node …
Published in Recent Trends in Electronics Communication Systems · Vol. 5, Issue 1, 2018 · pp. 7–11 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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Physics-Informed Neural Networks for Multiphysics Analysis of Biomedical Polymer Composite Systems
Abstract: Physics-Informed Neural Networks (PINNs) offer an effective model of solving coupled multiphysics equations in biomedical polymer composite systems, which are data-driven. In the given work, the PINN method is presented where equations of elasticity, mass diffusion, and heat transfer are integrated to model the complex processes that take place in composite biomaterials. The neural network loss is specified to include the governing partial different equations which enables both the system …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Explainable Artificial Intelligence in Personalized Medicine: Emerging Clinical Perspectives
Abstract: The convergence of artificial intelligence (AI) and precision medicine has transformed contemporary healthcare by enabling data-driven clinical decision-making, individualized therapeutic interventions, and predictive diagnostics. However, despite remarkable advances in machine learning (ML) and deep learning (DL), the widespread adoption of AI in healthcare remains constrained by the “black-box” nature of many computational systems. Clinicians, regulatory agencies, and patients increasingly demand transparency, interpretability, and trustworthiness in AI-guided medical recommendations. Explainable Artificial …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 13–29 Read article
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Parallel Greedy Approach for Phylogenetic Tree Construction in the Context of Marine Species
Abstract: The rebuilding of phylogenetic trees for marine species shows major computing problems because of the massive genomic data and the huge biodiversity inherent in ocean ecosystems. Traditional phylogenetic methods are accurate but become more expensive when they are processing with thousands of marine taxa parallelly. This article shows a critical analysis of parallel greedy algorithms as an adaptable solution for large-scale marine phylogenetics. It examines the main principles of greedy …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 33–45 Read article
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Energy-Aware Task Offloading in 6G-Enabled Mobile Edge Computing Environments
Abstract: The emergence of sixth-generation (6G) wireless communication networks is expected to revolutionize future mobile systems by enabling ultra-low latency communication, extremely high data rates, massive connectivity, and intelligent network management. In parallel, mobile edge computing (MEC) has gained significant attention as a promising paradigm that brings computational resources closer to end users, thereby alleviating network congestion and reducing end-to-end service delays. Despite these advantages, the rapid growth of computation-intensive and …
Published in International Journal of Mobile Computing Technology · Vol. 4, Issue 1, 2026 · pp. 14–19 Read article