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1089 articles for “data modelling”
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Bioinformatics-based Preparation and Characterization of Silver Nanoparticles Synthesized from Pterocarpus marsupium
Abstract: Silver nanoparticles were synthesized using Pterocarpus marsupium bark extract in combination with silver nitrate solution through a green synthesis method. Silver nanoparticles formation was confirmed by the formation of dark brown from solution of silver nitrate, where the reduction of silver ion occurs which leads to the formation of silver nanoparticles. The UV–visible spectra showed a peak at 429 nm, confirming the reduction of silver ions and the subsequent synthesis …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 2, 2024 · pp. 21–34 Read article
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Deep Learning-Based Alzheimer’s Disease Detection: A CNN Approach
Abstract: Alzheimer’s disease (AD) is a neurological condition that worsens with time and impairs a patient’s quality of life by causing cognitive loss. For prompt intervention and management of AD, early identification is essential. In this work, we propose a deep learning-based method for automatically classifying Alzheimer’s disease from medical imaging data using convolutional neural networks (CNNs). Our algorithm is intended to evaluate brain MRI images and detect anatomical variations suggestive …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 Read article
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Application of Artificial intelligence in Single Point Incremental Forming for Surface Roughness Prediction
Abstract: The sheet metal forming industries always try to find an emerging trend to form sheet-metal in a cost-effective manner. In this regard, a forming technique is trending termed as single point incremental forming (SPIF) in which a simple forming tool having hemispherical end rod is moving and simultaneously deforming the clamped metal sheet according to predetermined toolpath command and forms a complete shape. The achievement of required surface quality is …
Published in Journal of Polymer & Composites · Vol. 12, Issue 1, 2024 · pp. 237–246 Read article
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AI-Based Criminal Identification System A Breakthrough Approach
Abstract: Identifying and locating a perpetrator is a time-consuming and difficult process. The perpetrators are growing more skilled, leaving no biological evidence or fingerprint impressions at the crime scene. Using cutting-edge face recognition technology is a quick and easy solution. Through the use of linear programming, this research presents an innovative approach to classifying all face tracks collectively. In addition to the following, it incorporates: a novel method for extracting more …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 2, Issue 1, 2024 · pp. 1–14 Read article
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Skin Cancer Detection System Based on Machine Learning for Recognition of Cancerous Images
Abstract: Skin cancer ranks among the most prevalent types of cancer globally and poses significant risks when left untreated. Skin cancer arises when abnormal cells proliferate uncontrollably in the skin. This uncontrolled growth can be triggered by genetic mutations, exposure to ultraviolet (UV) radiation from the sun or artificial sources like tanning beds, or various other factors. In this, the early detection of cancer plays a crucial role in treatment and …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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Development of Sodium Alginate Beads of Telmisartan Using Emulsion Gelation Method: Formulation and In-Vitro Characterization
Abstract: Introduction: The antihypertensive medication Telmisartan (TEL) is a member of BCS class II, which is distinguished by limited oral rate and extent and water solubility. By localizing the medication release in the stomach, gastro-retentive floating bead devices may be able to address the issues related to partial absorption and the low solubility of TEL. The preparation of TEL floating alginate beads was the aim of this investigation. The current work …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 11, Issue 3, 2024 · pp. 13–21 Read article
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Analysis of Steel Chip Fiber Reinforced Composite Dual Pile Under Lateral Load Conditions on Sloping Terrain
Abstract: Pile foundations, in addition to supporting vertical loads from superstructures, are subjected to lateral stresses arising from seismic activities, wind gusts, water currents, and traffic impacts etc. Failure to account for these lateral forces can pose significant risks if the structure is expected to encounter any form of lateral pressure. Previous research has investigated the behavior of individual composite piles under horizontal forces, considering different soil properties, to determine the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 210–220 Read article
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Facial Emotion Detection and Its Applications
Abstract: Facial emotion detection (FED) is an interdisciplinary field that integrates artificial intelligence, computer vision, and machine learning to recognize and interpret human emotions based on facial expressions. The development of FED systems has been propelled by advancements in deep learning, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which enhance recognition accuracy. Feature extraction techniques, including geometric and appearance-based methods, play a crucial role in classifying emotional states. …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 8–12 Read article
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Pneumonia Identification Using Explainable Artificial Intelligence
Abstract: Pneumonia, including tuberculosis (TB), remains one of the leading causes of death worldwide, especially in regions where access to healthcare is limited. Early and accurate diagnosis is critical for effective treatment and better patient outcomes, but traditional methods are time-consuming and require specialized expertise. This study explores the use of advanced deep learning models VGG16, VGG19, and ResNet50 to detect pneumonia and TB from chest X-ray images. By leveraging transfer …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 01–11 Read article
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Digital Enablers of Nanomedicine: Pharmaceutical Software Across the Lifecycle of Nanotechnology‑Based Drug Products
Abstract: Nanotechnology‑based drug products have rapidly evolved from laboratory concepts to clinically relevant therapies, yet their development is constrained by complex design variables, stringent quality requirements, and emerging regulatory expectations specific to nanomaterials. Pharmaceutical software now plays a central role in the nanomedicine lifecycle, enabling in silico design of nano‑carriers, simulation of nano–bio interactions, control of nanoscale quality attributes during manufacturing, and systematic tracking of safety signals in real‑world use. Integrated …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 1, 2025 · pp. 11–16 Read article
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Atmospheric Determinants of Feed, Fodder, and Forage Contamination in a Changing Climate: Emerging Challenges for Sustainable Livestock Production
Abstract: Feed, fodder, and forage contamination represents a growing constraint to sustainable livestock production under a changing climate. Atmospheric determinants such as rising temperature, altered precipitation patterns, increased humidity, elevated carbon dioxide concentration, and enhanced aerosol and pollutant loads are increasingly recognized as critical drivers of contamination risks across feed supply chains. These atmospheric factors directly and indirectly influence crop growth, fungal proliferation, mycotoxin biosynthesis, microbial survival, and the deposition of …
Published in International Journal of Atmosphere · Vol. 3, Issue 1, 2026 · pp. 1–14 Read article
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A Comprehensive Survey of Polymer Detection Techniques and Computer-Based Analysis Methods for Advanced Material Characterization
Abstract: Polymers are widely used in aerospace, automotive, biomedical, packaging, electronics, and manufacturing industries because of their lightweight nature, durability, and versatility. Accurate polymer identification and characterization are essential for quality control, recycling, performance assessment, and the development of advanced materials. Characterization helps determine important properties such as chemical composition, molecular structure, thermal stability, mechanical strength, and surface morphology, which influence material performance and application suitability. Traditional polymer detection methods include …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 921–929 Read article
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A Survey on Hydrogen Storage System using Composite Material and its Alloys
Abstract: The transition to a carbon-neutral energy landscape hinges on the ability to store hydrogen safely, densely, and reversibly. While high-pressure tanks and cryogenic vessels dominate today’s infrastructure, solid-state storage in metallic alloys offers a compelling alternative by combining high gravimetric capacity with intrinsic safety to form a composite material. This work presents a systematic investigation of a family of reversible hydrogen-absorbing composite material alloys—principally Mg-based intermetallics (Mg₂Ni, MgFeMn) and TiV-based …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 Read article
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Harnessing Marine Byproducts and Optimization of Biopolymer Extraction Quality Using Response Surface Methodology and Study of Its Physicochemical Properties
Abstract: Chitosan, a versatile biopolymer derived from chitin, holds immense potential across various industries owing to its antimicrobial, antioxidant, and biocompatible properties. This study aims to optimize the deacetylation process of chitin, sourced from shrimp shells, using Response Surface Methodology (RSM) to produce high-quality chitosan. The Box-Behnken Design (BBD) was employed to evaluate the effects of temperature, time, and alkali concentration on the degree of deacetylation (DD%), a key determinant of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 125–139 Read article
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Brain Tumor Detection by Aggregating Deep Learning and GAN Models for Faster MRI image Synthesis
Abstract: Brain tumors comprise a global health challenge that, in order to be treated and organized, need early and accurate diagnosis. Usually conducted through medical imaging, brain tumor detection techniques have problems of accuracy, efficiency, and confidentiality. Issues of limited datasets, strict privacy laws that provide restrictions on data sharing, and the necessity for specialized expertise on medical image analysis relegates modern methodologies to vulgar charades. For patient prognosis, treatment planning, …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 45–53 Read article
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Deep Learning Enhanced Compressive Sensing for Wireless IoT Data Optimization and Weather Monitoring.
Abstract: This research explores the application of deep learning and compressive sensing in order to optimize data traffic in non-orthogonal multiple access (NOMA)-based wireless internet of things (IoT) networks and weather monitoring. Such a framework would be very effective and overcome pilot attacks and reconstruction losses for secure data transmission. In this regard, a strong communication model has been adopted based on power-domain NOMA for simultaneous wireless transmission by multiple IoT …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 20–36 Read article
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Assessing the Robustness of Machine Learning Models for Wireless Intrusion Detection Under Adversarial Traffic Perturbations
Abstract: As the Internet of Things (IoT) devices and wireless communication networks continue to grow rapidly, protecting systems from cyber threats has become increasingly important. Machine learning–based intrusion detection systems (IDS) have shown strong potential in detecting abnormal and malicious network activities, yet their effectiveness and resilience when facing adversarial attacks are still not sufficiently explored. This research evaluates Machine Learning (ML) models–XGBoost, random forest, and multi-layer perceptron (MLP)—in detecting attacks …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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Comparative Analysis of the Model of DVB-T Model Using Various Modulation Techniques 16 QAM & 64 QAM for the Primary Colors
Abstract: Computerized TV broadcasting is the spirit without bounds transmission. Progressions in advanced innovation, pressure in sound and video flagging and other flag handling systems' improvement lead to qualitative change in the field of digital/computerized TV. Usage of a coaxial link and through satellite and earthbound way, computerized transmission is made conceivable. Digitized TV would execute the convolution coding plan alongside OFDM adjustment strategy. The pressure is done and afterward the …
Published in Recent Trends in Electronics Communication Systems 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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Real-time DDoS Attack Prediction in SDN Environments Using Machine Learning
Abstract: The ever-growing reliance on sdn-based services necessitates robust security measures against Distributed Denial-of-Service (DDoS) attacks that threaten service availability. This project investigates the development of a real-time prediction system for DDoS attacks in sdn environments, leveraging the power of machine learning. The proposed system employs a Decision Tree classification algorithm implemented in Python. To ensure accurate attack identification, the system meticulously addresses data preprocessing challenges inherent in network traffic datasets. …
Published in Journal Of Network security · Vol. 13, Issue 1, 2025 · pp. 16–27 Read article