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1193 articles for “agriculture chat bot.csv dataset”
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Combining Unstructured and Structured Clinical Data in a Hybrid Transformer Model to Enhance Cardiovascular Analytics and Clinical Decision- Making
Abstract: Since cardiovascular disease (CVD) continues to be a major global cause of morbidity and mortality, early and accurate risk prediction is essential for prompt intervention and individualized treatment. This study introduces a new hybrid transformer-based model that combines unstructured clinical narratives, structured data, and customized lifestyle characteristics. A comprehensive understanding of disease progression is made possible by the model's ability to capture contextual, temporal, and patient- specific insights through the …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 · pp. 30–37 Read article
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A Comparative Study of Transfer Learning-Based Deep Learning Models for Breast Cancer Detection
Abstract: Breast cancer is a major concern in the world today, and early and accurate diagnosis is most crucial in the case of breast cancer, as it is among the disorders where the total cost of loss of life is high. Traditional screening processes are subjective and vulnerable to inter-observer reliability issues and diagnostic errors, being primarily based on manual interpretation of medical images. To address these limitations, Deep Learning (DL) …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–34 Read article
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Host Plant Affinity and Trophic Behavior of Lohita grandis name of author (Hemiptera: Largidae)
Abstract: Lohita grandis (Gray) , commonly known as the red cotton bug, is an emerging pest of cotton and several other economically important crops in India. Its sap-sucking feeding habit causes discoloration of fruits, reduction in seed quality, and yield losses, posing serious challenges to sustainable agriculture. The present study investigates the feeding behaviour and host plant preferences of L. grandis across diverse agroclimatic zones of India, with the aim of …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 92–100 Read article
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Bioremediation of Crude Oil-Contaminated Loamy Soil Using Plantain (Musa Paradisiaca) Stem Waste as a Biostimulant
Abstract: Crude oil contamination of soil is a pressing environmental challenge in oil-producing regions, especially in the Niger Delta of Nigeria. It degrades soil fertility, disrupts microbial ecosystems, and poses long-term ecological and health risks. Traditional remediation methods are often cost- prohibitive and environmentally intrusive, prompting the search for sustainable alternatives. This study investigates the potential of plantain (Musa paradisiaca) stem waste – a readily available agricultural byproduct – as a …
Published in Emerging Trends in Chemical Engineering · Vol. 13, Issue 1, 2026 · pp. 1–11 Read article
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An Investigation into the Quality of Distillate Diesel Fuel at Selected Service Stations in Freetown’s Western Area
Abstract: As a critical energy source for global transport and industry, diesel fuel quality is of paramount importance. This study evaluates and compares the quality of diesel fuel samples by analyzing key parameters: sulfur content, density, cetane index, and kinematic viscosity. The properties of diesel fuel samples from six (6) Fuel Stations of various Oil Marketing Companies (OMCs) are compared with National Technical specifications limits of the Sierra Leone Standards Bureau, …
Published in Journal of Petroleum Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 1–14 Read article
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Enhancing Maintenance Decision-Making in Thermal Power Plants Using Generative AI-Based Fault Diagnosis
Abstract: The growing complexity of operation and power consumption of thermal power stations involve the need to have intelligent fault diagnosis systems that can be used to guarantee reliability and safety in operation. In this research, a Generative AI (GenAI)-based hybrid architecture of early fault detection and predictive maintenance is proposed to improve the decision-making process of the maintenance team. The data-driven analytic approach combines methods of data-driven analytics, Generative AI …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 25–33 Read article
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The Impact of Using High-Resolution Satellite Images on Improving Geographic Maps
Abstract: By integrating high-resolution satellite images into pre-existing mapping frameworks, this study tackles the problem of guaranteeing correctness and dependability in geospatial data updates. The main goal is to assess which satellite imagery sources—SuperView, Ikonos, QuickBird, and WorldView—are appropriate for updating maps at 1:2500 and 1:5000 scales. The process entails evaluating radiometric quality, geometric dependability, spatial correctness, and picture resolution and comparing the results to the specifications of different mapping tasks. …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 Read article
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Analysis of Hybrid Photovoltaic Thermal (PV/T) Integrated Solar Dryer: An Experimental Validation
Abstract: In this study, a hybrid photovoltaic thermal (PV/T) integrated solar dryer has been designed, developed, and experimentally analyzed to evaluate its performance in real-world climatic conditions. The system incorporates a UV-stabilized sheet mixed-mode tent house structure, installed on the rooftop of a building located in Bhilai, Chhattisgarh, India. The dryer is equipped with a thermal collector directly connected to the drying chamber to enhance heat transfer efficiency. Experiments were conducted …
Published in Journal of Thermal Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 1–6 Read article
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Machine Learning Assisted Optimization of Nanoscale MOSFET Parameters Using TCAD Simulation
Abstract: This paper presents a machine learning (ML) assisted framework for the multi-objective optimization of nanoscale bulk n-channel metal-oxide-semiconductor field-effect transistors (nMOSFETs) with a 10 nm physical gate length, high-k HfO₂ gate dielectric, and TiN metal gate. Technology computer-aided design (TCAD) simulations employing drift-diffusion transport, Shockley-Read-Hall recombination, Lombardi mobility degradation, and density- gradient quantum correction models are used to generate a parametric dataset of 2,400 device configurations spanning gate length (L), …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 10–19 Read article
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Identification of Hub Genes and Enriched Gene Ontology & Pathways in Idiopathic Pulmonary Fibrosis Through Bioinformatics Approaches
Abstract: Idiopathic Pulmonary Fibrosis (IPF) is a progressive interstitial lung disease marked by aberrant remodeling of lung tissue and excessive extracellular matrix deposition, ultimately leading to respiratory failure. Despite ongoing research, the molecular mechanisms underlying IPF remain incompletely understood. This research aims to uncover differentially expressed genes (DEGs) and related biological pathways through an integrated analysis of microarray data. Two publicly available datasets, GSE110147 and GSE53845, were obtained from the Gene …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 1–13 Read article
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Fractal-Entropy Guided Adaptive Signal Reconstruction for Non-Stationary Biomedical and Communication Systems
Abstract: This paper presents a novel Fractal-Entropy Guided Adaptive Signal Reconstruction (FEG- ASR) framework designed for accurate processing of non-stationary signals in biomedical and communication systems. The proposed approach integrates fractal dimension analysis with entropy- based feature evaluation to capture the intrinsic complexity and irregularity of time-varying signals. By dynamically adapting reconstruction parameters based on fractal-entropy measures, the method effectively separates noise from meaningful signal components while preserving critical information. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 Read article
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Aerodynamic Optimization of UAV Wings Using Machine Learning
Abstract: Unmanned Aerial Vehicles (UAVs) are increasingly deployed across defense, transportation, agriculture, and environmental monitoring, demanding improved aerodynamic efficiency to enhance endurance, stability, and payload capacity. Traditional aerodynamic optimization approaches, relying on computational fluid dynamics (CFD) simulations and wind tunnel experiments, are often time-consuming and computationally expensive. This study proposes a machine learning (ML)-driven framework for the aerodynamic optimization of UAV wing geometries, aiming to significantly reduce design cycles while improving …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 1–7 Read article
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The Future of Farming with IoT-Operated Drones
Abstract: The integration of Internet of Things (IoT) technology with drone systems has revolutionized precision agriculture, offering innovative solutions to address the inefficiencies and environmental concerns linked to conventional pesticide application. This study explores the design, implementation, and impact of IoT-operated drones tailored for automated pesticide spraying. By leveraging real-time sensor data, AI-driven analytics, and cloud-based connectivity, these drones enable dynamic, data-informed decisions to optimize chemical application. Results indicate that IoT-enabled …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 20–26 Read article
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Nitrosamine Accumulation, Processing Variables, and Indigenous Plant Inhibitors in Nigerian Traditionally Processed Meats
Abstract: N-nitrosamines are classified as probable or possible human carcinogens by the International Agency for Research on Cancer. Carcinogenic N-nitrosamines — principally N-nitrosodimethylamine (NDMA) and N-nitrosodiethylamine (NDEA) — are formed in abundance during the preparation of widely consumed Nigerian traditional processed meats including suya, kilishi, and balangu. This original investigation combined a six geopolitical zone of Nigerian market survey with laboratory-controlled model system experiments, effects of processing parameters on N-Nitrosamine formation …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 17, Issue 1, 2026 · pp. 61–72 Read article
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A Comprehensive survey of robust image quality metrics for satellite imagery
Abstract: Satellite imagery is essential for applications like environmental monitoring, urban development, precision agriculture, defence surveillance, and disaster response. The reliability of these applications is closely tied to the quality of the captured images, which may be compromised by atmospheric effects, sensor imperfections, compression artifacts, and transmission noise. As a result, accurate image quality assessment (IQA) is essential to ensure trustworthy analysis and informed decision-making in satellite-based systems. The distinctive properties …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 1, 2026 · pp. 7–20 Read article
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Understanding Sentiment Trends Through Zero-Shot and Few-Shot Learning Models
Abstract: The requirement for large, manually labeled datasets is one of the main barriers to applying sentiment analysis algorithms in specialized or rapidly evolving disciplines in the present natural language processing (NLP) landscape. This work investigates a paradigm shift from traditional fully supervised learning to data-efficient methods, specifically zero-shot learning (ZSL) and few-shot learning (FSL). This study uses the advanced capabilities of instruction-tuned large language models (LLMs), like GPT-4, to assess …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 01–08 Read article
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Predictive Analytics and Adaptive Learning: A Machine Learning Framework for Reducing Learning Gaps
Abstract: Most contemporary digital learning environments encounter persistent challenges when it comes to accurately identifying students who are at-risk of academic underperformance. These challenges often arise due to limited visibility in learners’ engagement levels and gaps in conceptual understanding, particularly during the early stages of a course. To address this issue, the present study proposes an early prediction framework that leverages comprehensive student-related data through the application of machine learning techniques. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 16–21 Read article
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Evaluation of New Fungicides for the Management of Mango Anthracnose Disease Caused by Colletotrichum Gloeosporioides
Abstract: A field experiment was conducted at the field of Plant Pathology Division, Regional Agricultural Research Station (RARS), Bangladesh Agricultural Research Institute (BARI), Jamalpur-2000, Bangladesh during February to July 2024 to assessment the efficacy/effectiveness of thirty-five (35) new fungicides received from Pesticide Technical Advisory Committee (PTAC), Bangladesh with control treatment against anthracnose disease of mango. Most of the fungicides under inspection were able to control the disease successfully. This study suggests …
Published in International Journal of Trends in Horticulture · Vol. 3, Issue 1, 2026 · pp. 1–16 Read article
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A Multivariate Adaptive Regression Splines Based Study of Soil Parameters and Their Impact on Onion Yield in Bhavnagar District
Abstract: Bhavnagar district is one of the prominent onion-growing areas in the Saurashtra region of Gujarat, encompassing key talukas such as Mahuva, Talaja, Ghogha, Jesar, and Palitana. Onion cultivation in the district is carried out across three distinct seasons: rabi, kharif, and late kharif with harvesting periods extending from April to May for the rabi crop and from October to March for the kharif and late kharif crops. The productivity of …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 53–64 Read article
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HirePrep: A Microservice-Based Integrated Placement Preparation Platform with AI Assistance
Abstract: Preparing for campus placements can be a confusing and time-consuming process. Students have to use different platforms for things like practice tests, study materials, talking to people, and getting updates from the administration. This is not a waste of time, but it also makes it harder for students to be productive and clear about what they need to do when they are getting ready for their careers. To make things …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 1, 2026 · pp. 25–37 Read article