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1193 articles for “agriculture chat bot.csv dataset”
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Quasar: Quantum-Accelerated Sustainable Anomaly Recognition in Climate Systems
Abstract: Accurate detection of climate anomalies is vital for disaster alleviation and policy making in a sustainable manner, but customary detection methods face the challenges of computational inefficiency and physical inconsistency. In this study, we propose a novel approach called Quantum-Optimized Fuzzy Physics-Informed Neural Networks (QFuzzy-PINNs), which integrates quantum computing, fuzzy logic, and physics-informed deep learning. As a first step, we employ quantum annealing for conventional optimization to adjust multiple Gaussian …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 18–27 Read article
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Image-Based Crack Morphology Characterisation for Electrical Failure Analysis in Conductive Polymer Composites
Abstract: Electrical performance in conductive polymer composites is strongly governed by crack-network evolution, yet failure analysis typically relies on qualitative image inspection or electrical anomaly detection in isolation. This work proposes an end-to-end framework that converts optical/SEM crack imagery into a standardised crack morphology signature and quantitatively links it to electrical degradation indicators. A two-stage learning strategy is adopted: crack-representation pretraining using the public Concrete Crack Images for Classification dataset, followed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1375-1386 Read article
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Climate variability analysis over the state of Himachal Pradesh, India
Abstract: Longterm daily temperature and rainfall data (2000–2024) for thirty-five locations ranging from ~350 to >4000 m amsl were obtained from the NASA POWER database. The variability and trends in maximum, minimum temperature and rainfall were worked out by using different statistical tools and Mann-Kendal test trend analysis. The mean annual maximum temperature of the state was 20.3°C (CV = 3.9%), declining from 27.4°C in the low hills to 7.2°C at …
Published in International Journal of Climate Conditions · Vol. 3, Issue 1, 2026 · pp. 51–64 Read article
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Smart E-Health Consultation Portal
Abstract: The Smart E-Health Consultation Portal is an e-healthcare application that allows access to high-quality, efficient, and accessible medical care services via remote consultation of doctors & patients. Patients can communicate with their healthcare provider through video, voice, or chat communication which eliminates geographic and temporal boundaries. Factors that influence a patient's perception of satisfaction consist of clear and timely responses from their healthcare provider, a guarantee of privacy when using …
Published in Research and Reviews: A Journal of Health Professions · Vol. 16, Issue 1, 2026 Read article
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Blockchain-Based Smart Agri-Food Supply Chain Management System with User-Centric Design for Enhanced Consumer Trust
Abstract: Existing blockchain-based solutions for agri-food supply chains primarily focus on internal traceability and efficiency while neglecting consumer-facing functionalities. Building consumer trust requires not only a secure and transparent supply chain but also user-friendly interfaces for easy access to product information and journey tracking. This study addresses this gap by implementing a blockchain-based agri-food supply chain system with a user-centric design. Beyond internal transparency, the system features an intuitive consumer interface …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 1, 2026 Read article
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Optimizing Airline Efficiency Using Big Data and Predictive Analytics
Abstract: Recent technological advancements have resulted in the generation of vast volumes of data across industries, including the airline sector, supporting operational control and service quality. Big Data Analytics (BDA) enables organizations to analyze large and complex datasets to derive actionable insights that support informed decision – making and superior operational performance. This review paper systematically analyzes twenty relevant research studies to explore the application of Big Data Analytics (BDA) within …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 1, 2026 Read article
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Automated Healthcare Support System with AI
Abstract: The Automated Healthcare Support System with Artificial Intelligence (AI) presents a smart and scalable digital solution aimed at improving the accessibility and efficiency of healthcare services. The system is designed to provide preliminary medical guidance, perform symptom-based analysis, and deliver health-related insights through an intuitive user interface. By enabling early identification of potential health conditions, it assists users in determining the necessity of professional medical consultation. The proposed platform utilizes …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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A Comprehensive Study of Natural Language Processing Systems Using Modern Programming Languages: Techniques, Architectures, Experimental Evaluation, and Applications
Abstract: Natural Language Processing is a key field of study within artificial intelligence that focuses on enabling machines to understand and work with human language. This is because there is much digital text data everywhere. Natural Language Processing is what this study is about. It looks at new ways of doing Natural Language Processing. The old ways are like machine learning and the new ways are like learning. This study compares …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 Read article
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SmartTrack : Advanced Attendence System using LR RFID
Abstract: This project presents the design and implementation of a long-range RFID attendance system aimed at transforming how educational institutions track attendance by making the process faster, more accurate, and completely contactless. Tradi- tional methods, whether manual roll calls or short-range RFID scanners, often interrupt class routines and leave room for errors or proxy attendance. To address these issues, the proposed system integrates long-range RFID readers, beam sensors, and ESP32 microcontrollers …
Published in Journal of Semiconductor Devices and Circuits · Vol. 13, Issue 1, 2026 Read article
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Mechanical and Functional Performance of PET–Kenaf Fiber Hybrid Composites for Domestic Household Applications
Abstract: This research presents a hybrid composite of recycled polyethylene terephthalate (PET) and Kenaf fibers for sustainable household applications. Polyethylene terephthalate from consumer bottles was reinforced with Kenaf fibers at volume fractions of 10–30% and composites were created through compression molding. Mechanical characterization involved tensile, flexural, impact, and hardness testing where appropriate and was standardized according to ASTM standards, while their interfacial interactions were characterized by imaging through SEM. Linear and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1482–1498 Read article
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Comprehensive Evaluation of Quercetin from Bauhinia purpurea for Its Anti-Acne and Anti-Inflammatory Potential, Including Advances in Quercetin-Loaded Nanogel Formulation
Abstract: Acne vulgaris is among the most prevalent chronic inflammatory dermatoses in clinical dermatology, afflicting a substantial proportion of the global adolescent and adult population. Conventional pharmacotherapies — including topical retinoids, benzoyl peroxide, and systemic antibiotics — remain the therapeutic mainstay; however, their long-term utility is progressively undermined by adverse cutaneous reactions, systemic toxicity, and the rising prevalence of antibiotic-resistant Cutibacterium acnes strains. These limitations have intensified scientific interest in plant-derived …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 13, Issue 2, 2026 Read article
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Machine Learning Optimization for VARTM Carbon Polymer Laminates
Abstract: Vacuum-assisted resin transfer moulding (VARTM) is a key low-cost, out-of-autoclave process for manufacturing large-scale carbon-fibre reinforced polymer (CFRP) laminates crucial to aerospace wings, wind-turbine blades, marine hulls, and automotive structures. Unpredictable resin flow often leads to voids, dry spots, and race-tracking defects, resulting in 27.9% scrap rates and lengthy, costly trial-and-error design cycles. Although surrogate models provide rapid impregnation predictions for simple flat-plate geometries, vision-based monitoring is limited to idealized …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 229–245 Read article
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The Early Brain Hemorrhage Prediction System Using Machine Learning
Abstract: Brain hemorrhage is a critical medical emergency that requires immediate attention, as delays in diagnosis can result in severe neurological damage or death. The condition involves bleeding within or around brain tissues, leading to increased intracranial pressure and disruption of normal brain function. Although imaging techniques such as CT scans and MRI provide accurate diagnosis, their availability is limited in emergency and rural settings. In recent years, machine learning has …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 Read article
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DFT/Data Guided Predictive Modelling of Absorption Maxima in the OLED Rubrene Derivatives
Abstract: This study investigates the optical properties of rubrene derivatives to develop an accurate predictive model for absorption maxima using computational chemistry and chemoinformatic techniques. We benchmarked various quantum chemical methods, identifying that the M06-2X/aug-cc-pVDZ method in dichloromethane (DCM) provided the strongest correlation with experimental data. Key molecular descriptors such as band gap, ionization potential, and electrophilicity index were calculated and analyzed using principal component analysis (PCA) to identify significant factors …
Published in International Journal of Cheminformatics · Vol. 4, Issue 1, 2026 · pp. 41–56 Read article
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Adaptive Drift Correction in Polymer-Based Wearable Biosensors via Data-Driven Signal Modeling
Abstract: Polymer-based wearable biosensors have emerged as a promising technology for continuous health monitoring due to their mechanical flexibility, biocompatibility, and suitability for long-term physiological interfacing. However, prolonged exposure to biofluids, environmental variability, and mechanical deformation introduces signal drift, which significantly degrades measurement accuracy and limits clinical reliability. This paper presents a data-driven methodology for compensating signal drift in polymer-based wearable biosensors using adaptive signal processing and machine learning techniques. The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 131–139 Read article
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Structure–Property Modeling of Cement-Based Multi-Component Composites Using Ensemble Machine Learning and Explainable Feature Attribution
Abstract: Accurate prediction of compressive strength is central to structure–property optimization, quality control, and sustainability-driven design in cement-based composite materials. Cementitious systems represent heterogeneous multi-phase composites composed of reactive binder matrices and dispersed aggregate phases, whose macroscopic mechanical performance emerges from complex nonlinear interactions among constituents and curing-dependent microstructural evolution. This study develops a data-driven structure–property modeling framework to quantify the nonlinear dependence of compressive strength on multi-component composite composition and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 112–131 Read article
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Machine Learning in Nuclear Medical Applications: A Review of Research Frontiers
Abstract: Nuclear medicine, encompassing PET, SPECT, and targeted radionuclide therapy, generates high-dimensional, quantitative data uniquely suited for machine learning (ML) analysis. This review synthesizes current research applications of ML across six key domains. Positron emission tomography (PET), single-photon emission computed tomography (SPECT), and targeted radionuclide therapy are examples of nuclear medicine modalities that generate high- dimensional, quantitative datasets that are particularly well-suited for machine learning (ML)-driven analysis. These imaging methods provide …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 19–24 Read article
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Polymer Composite-Supported Jackfruit Peel Adsorbent for Enhanced Copper (II) Removal from Wastewater: Batch Equilibrium and Isotherm Analysis
Abstract: The increasing concern of disposal of copper-containing effluents into the environment has led to heightened interest in designing cost-effective, eco-friendly and scalable adsorbent systems. Traditional metals and synthetically engineered sorbents prove to be effective; however, these systems are energy intensive. Agricultural residues entrapped in polymer composite systems constitute an economically feasible solution to this environmental challenge. This work reports on the design, characterization and performance evaluation of an economical adsorbent …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 375–390 Read article
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Machine Learning Assisted Design and Analysis of Polymer Composite Materials for Sustainable Renewable Energy Systems
Abstract: Accurate prediction and optimization of polymer composite properties is of paramount importance in the design of these lightweight, durable, and sustainable materials within renewable energy technologies. This work will provide a holistic machine learning-assisted framework that unites materials informatics with domain-specific features and state-of-the-art ML methodologies in the prediction of the mechanical properties of polymer composites, such as tensile strength. This includes embedding several ensemble models, including Random Forest and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 391–402 Read article
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Explainable Machine Learning Integrated with Polymer-Based Diagnostic Technologies for Liver Health Classification
Abstract: Early and reliable assessment of liver health is essential for timely treatment, yet most machine-learning approaches face limitations such as class imbalance and low clinical interpretability. This study proposes a polymer-integrated, explainable machine-learning framework that combines SMOTE-based data balancing, Logistic Regression, and XAI techniques (SHAP and LIME) for transparent liver-health classification. In addition to ML modelling, the study emphasizes the emerging role of polymer-based biosensors, microfluidic polymer chips, polymer nanomaterials, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 631–643 Read article