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717 articles for “data utility”
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Early Alzheimer's Disease Detection Using Deep Ensemble Learning and MRI Image Analysis
Abstract: Early detection of Alzheimer's disease (AD) is crucial to slowing cognitive decline and enabling timely clinical interventions. Traditional diagnostic methods, including cognitive tests and single-model classifiers, have limited sensitivity during early stages of the disease. This paper presents a deep ensemble learning approach that integrates multiple convolutional neural networks (CNNs) for accurate Alzheimer's disease detection using structural Magnetic Resonance Imaging (MRI) data. The proposed framework utilizes ResNet50, VGG16, and DenseNet121 …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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Parkinson’s Disease Detection on Spiral Images Using CNN with Meta-Classifiers
Abstract: In this work, we provide a detailed method for identifying Parkinson’s Disease (PD) by integrating Convolutional Neural Network (CNN) and meta-classifiers. Through the utilization of a varied dataset consisting of handwritten spiral images, our methodology demonstrates commendable accuracy across a range of models. Specifically, our CNN model with meta-classifiers surpasses alternative approaches, achieving an impressive accuracy rate of 95.07%. By utilizing pre-established VGG16 and ResNet50 architectures as bases, the region-based …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 55–66 Read article
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Real-Time Analysis of E-Waste Monitoring Using Data Visualization in Power BI
Abstract: The exponential growth of electronic waste (e-waste) in India poses significant environmental and public health challenges, necessitating robust monitoring, management, and disposal strategies. This project, Real-time analysis of e-waste generated across different countries in the world and also survey report of India, seeks to provide a comprehensive assessment of e-waste production patterns, utilizing real-time data to capture dynamic shifts in waste generation and collection. By leveraging Power BI for advanced …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 2, 2025 · pp. 1–7 Read article
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Privacy-preserving Multi-keyword Search in Multi-owner Setting Using Blockchain
Abstract: Searchable encryption (SE) has become an essential cryptographic technique, allowing users to securely search through encrypted data. However, most existing SE schemes rely on a single intermediary, such as a cloud server, leading to potential single-point failures, privacy breaches, and untrustworthy results. Many blockchain-based SE schemes have been proposed to address these issues. However, they frequently encounter difficulties such as supporting a multi-keyword, multi-owner model, ensuring query privacy, and maintaining …
Published in Journal of Advances in Shell Programming · Vol. 11, Issue 2, 2024 · pp. 12–18 Read article
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Multiple Disease Prediction Using Machine Learning Algorithms
Abstract: The incorporation of machine learning algorithms into healthcare has transformed disease prediction and diagnosis. This research introduces a method for predicting various diseases using machine learning techniques. A comprehensive dataset, consisting of patient records, medical histories, and key disease-related features, was utilized to build predictive models. Data preprocessing methods, including feature selection and normalization, were implemented to clean and prepare the dataset. Several machine learning algorithms, such as Decision Trees, …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 3, 2024 · pp. 34–38 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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Performance of Artificial Neural Network for Tree Species Identification using Sentinel-2 Data
Abstract: Accurate land cover mapping, especially concerning vegetation, is crucial for effective land use policy planning and sustainable forest management. Hence, achieving accuracy in mapping requires a deep understanding of composition changes, vegetation conditions, and the spatial distribution of tree species. In the spatial context of tree species, it holds significant potential for applications including invasive species monitoring, delineating contaminated areas, and biodiversity conservation. However, traditional methods for tree species identification …
Published in Journal of Remote Sensing & GIS · Vol. 15, Issue 2, 2024 · pp. 12–21 Read article
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A study in Leveraging Deep Learning and IoT Arrays for Dynamic, Hyper-Local Atmospheric Intelligence
Abstract: The critical demand for high-resolution, actionable atmospheric data is challenged by the high cost and sparse coverage of traditional regulatory monitoring stations. This paper explores the synergistic paradigm shift enabled by integrating low-cost, dense Internet of Things (IoT) sensor arrays with advanced Artificial Intelligence (AI) methodologies, specifically Deep Learning (DL) models. We address the primary limitations of low-cost sensors—inherent bias, sensitivity to environmental drift (temperature/humidity), and calibration inconsistency—by utilizing AI …
Published in International Journal of Atmosphere · Vol. 2, Issue 2, 2025 · pp. 50–62 Read article
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RFID Based Smart Trolley Billing System Using IoT
Abstract: Customers experience better retail interactions while operations become more efficient in the modernizing retail industry. Shopping through traditional methods requires lengthy manual scanning for products and billing operations leading retailers to require automation solutions for streamlining these processes. This system consists of RFID detection alongside 8051 microcontroller processing and load cells monitoring and uses IoT communications and relay controls to power an intelligent automated shopping cart. Real-time data tracking functions …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 3, 2025 · pp. 1–8 Read article
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GenChrome-ML: A Machine Learning Framework for Early Detection of Chromosomal Disorders Using Genomic Data
Abstract: The increasing burden of chronic disease and cancer demands innovative, more rapid and effective diagnostic tools in the field of healthcare. The majority of current diagnostic tools are dependent upon clinical symptomology and manual evaluation, leading to delays in early detection and treatment. The development of artificial intelligence (AI) and machine learning (ML), in recent years, has offered opportunities for the enhancement of disease prediction, diagnosis and personalization of treatment …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Data-driven Approaches to Mineral Resource Management Using AI: A Brief Review
Abstract: The role of Artificial Intelligence (AI) in the mineral resource sector has become increasingly significant over the past few years, as industries seek to optimize and modernize their operations. AI encompasses a variety of technologies and techniques, such as machine learning, deep learning, and expert systems, that are now widely used in mineral exploration, resource estimation, and mine management. These AI-driven approaches have brought about a transformative shift, enhancing efficiency, …
Published in International Journal of Minerals · Vol. 2, Issue 1, 2025 · pp. 25–29 Read article
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RTL-to-GDS Implementation of a High-Speed On-Chip 32:1 Serializer Using Open-Source Tools
Abstract: Exploring the RTL-to-GDS implementation of a high-speed on-chip 32:1 serializer, this study investigates the integration of open-source tools within VLSI design, emphasizing sustainable practices in the semiconductor industry while operating at the nanometer scale. Addressing methodologies for optimizing power consumption and chip area utilization, particularly focusing on efficient use of non-renewable resources. The study is set against the backdrop of advanced 7nm FinFET technology, critical for enabling efficient data transmission …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 3, 2024 · pp. 1–10 Read article
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Trend Analysis of Long-Term Rainfall Data for Monsoon Season of Kharun Catchment
Abstract: This research paper investigates the trends in monsoon season rainfall over a 31-year period (1990–2021) using the non-parametric Mann–Kendall test. A range of statistical methods were utilized to analyze the rainfall data, providing valuable insights into its temporal patterns and trends. The correlation coefficient, measured by Kendall's Tau, exhibited a minimal positive correlation of 0.004 between years and their corresponding rainfall, quantities. This implies a slight tendency for increased rainfall …
Published in International Journal of Rural and Regional Development · Vol. 3, Issue 1, 2025 · pp. 12–17 Read article
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In Silico Prediction of Multitarget Mechanism of Quinoline and Its Analogs on Phosphoinositide-3-Kinase Pathway Proteins
Abstract: Objective: Phosphoinositide 3-kinases (PI3Ks), the target of rapamycin (PI3K/Akt/mTOR, PAM), are a family of enzymes that play a role in the growth, proliferation, differentiation, motility, survival, and intracellular trafficking of cells, all of which are essential for healthy cellular function and are also connected to cancer. In this study, quinoline and its derivatives were employed to analyze its inhibition activity on the phosphoinositide-3-kinase pathway. Methods: In this work, eight phytocompounds …
Published in International Journal of Molecular Biotechnological Research · Vol. 1, Issue 1, 2023 · pp. 57–76 Read article
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Using AIML to Enhance Demand Forecasting in Business
Abstract: Artificial intelligence machine learning (AIML) can play a significant role in enhancing demand forecasting in business. AIML is a programming language designed for creating chatbots and conversational agents, but its application extends beyond simple interactions. In the context of demand forecasting, AIML can be utilized to analyze historical data, customer interactions, and market trends. By implementing AIML algorithms, businesses can create intelligent models that learn from past demand patterns, customer …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 35–40 Read article
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In Silico Assessment of Demethoxycurcumin: Molecular Docking and Computational Insights into its various therapeutic Potential
Abstract: Natural compounds are increasingly explored for their therapeutic potential in medical research. Here, we focused on demethoxycurcumin (DMC), a polyphenolic bioactive compound extracted from Curcuma longa, commonly found in turmeric. DMC, with a chemical formula of C20H18O5 and a molecular weight of 340 g/mol, possesses two aromatic ring systems, each featuring a β-diketone moiety connected by a seven-carbon chain. This unique structure allows DMC to engage in tautomerism, which is …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 11, Issue 1, 2024 · pp. 9–15 Read article
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Reconfigurable AES Based AEAD For Multi-Mode Operation with Lightweight Compatibility
Abstract: The proposal is for a lightweight, multi-mode, reconfigurable authenticated encryption system with associated data (AEADs) based on AES. It is challenging to effectively integrate different AEADs in hardware because each one has its own mode of operation and/or subfunctions, even though some major AEADs share several basic components (such as the XOR-Encryption-XOR (XEX) scheme, block chaining, and advanced encryption standard (AES). This paper proposes hardware that effectively combines the basic …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 1, 2025 · pp. 54–68 Read article
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Quantum Mechanics: Revolutionizing Pharmaceutical Sciences
Abstract: Quantum physics and pharmacy have generally been regarded as distinct areas—one investigates the microlevel behavior of non-living matter while the other concentrates on intricate biological systems. Nevertheless, progress in life sciences has increasingly depended on molecular-level insights, whereas quantum physics has advanced beyond basic principles to impact real-world uses. This intersection provides new opportunities for, pharmacy. Quantum entanglement, which allows for instantaneous relationships between particles, can be utilized for secure …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 12, Issue 1, 2025 · pp. 72–77 Read article
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Brain Tumor Detection Using RestNet50 Architecture
Abstract: This paper presents a novel deep learning model for brain tumor diagnosis from MRI scans on the basis of ResNet50 with some modifications. Optimizing the modified layers and pre-trained ResNet50 for improved diagnostic accuracy and reliability in real-world clinical settings is one of the key contributions of this paper. The model was trained on an extremely well-balanced data of 2,577 MRI scans, which were split equally among the tumor and …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 1–13 Read article
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Empowering Vehicle: The Impact of Deep and Reinforcement Learning in IoV
Abstract: Deep learning and reinforcement learning represent two pivotal pillars within the realm of artificial intelligence and machine learning, bearing transformative potential in the domain of the Internet of Vehicles (IoV). This abstract explores the multifaceted applications of these cutting-edge techniques within the IoV framework. Deep learning, exemplified by convolution neural networks (CNNs) and recurrent neural networks (RNNs), empowers IoV systems with the prowess to discern complex patterns in sensory data. …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 2, 2025 · pp. 1–12 Read article