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1193 articles for “agriculture chat bot.csv dataset”
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IS-Aligned Strategic Evaluation of Fire Protection Systems for Improving Fire Safety in Mixed-Occupancy High-Rise Buildings
Abstract: This paper presents a substantially reworked Indian-context evaluation of fire protection systems in a 14-building high-rise sample from Indore. The study reuses the original field dataset but replaces the earlier code mix with an explicitly IS-aligned and NBC-oriented analytical framework. Physical observation, document review and interview inputs were screened against requirements related to means of egress, compartmentation, fire detection and alarm, hydrants and hose reels, extinguishers, emergency lighting, smoke control, …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 2, 2026 Read article
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Zero-Concentrate Feeding in Dairy Cows: A Sustainable Approach to Milk Quality, Animal Health, and Welfare
Abstract: The study explores the benefits of eliminating concentrate feeds in dairy cow nutrition. As sustainability becomes a central concern in agriculture, zero-concentrate feeding offers a promising solution to reduce the environmental footprint of dairy farming while promoting optimal animal health and welfare. This approach primarily focuses on maximizing the use of high-quality forages, such as grasses and legumes, to meet the nutritional needs of dairy cows. By minimizing the use …
Published in Research and Reviews : Journal of Dairy Science and Technology · Vol. 15, Issue 1, 2026 · pp. 30–47 Read article
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Enhanced Sustainable Concrete Mix Design Using LLMs and Advanced Machine Learning Techniques
Abstract: Large Language Models (LLMs) are emerging as transformative tools in materials science, offering human-like reasoning, zero-shot problem solving, and the ability to integrate fuzzy laboratory knowledge with structured data. This study extends and reinterprets the original systematic benchmark for using LLMs in sustainable concrete design, particularly for Alkali-Activated Concrete (AAC). We introduce an enhanced, multi-model framework combining LLM-based inverse design, Random Forest regression, Gaussian Process Regression (GPR), and a lightweight …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Machine Learning Assisted Timing Violation Prediction in Sub-7nm VLSI Physical Design
Abstract: The continuous scaling of semiconductor technology into the sub-7nm regime has introduced significant challenges in timing closure due to process variability, interconnect delay, power density, and manufacturing uncertainties. Conventional static timing analysis techniques often require extensive computational resources and iterative optimization cycles, resulting in increased design complexity and longer turnaround time. This research proposes a Machine Learning Assisted Timing Violation Prediction framework for sub-7nm VLSI physical design to improve early-stage …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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Cognitive AI-Based Quality Control and Operational Optimization of Polymer Composites for Healthcare Applications
Abstract: The use of polymer composite materials in healthcare is on the rise because of their adjustable mechanical characteristics, biocompatibility and structural flexibility. Yet, it is difficult to ensure stable quality of such composites due to process-related defects, heterogeneity of the material and the lack of real-time adaptive control. The proposed study suggests the use of cognitive AI-based framework of quality control and optimization of operation of polymer composite systems which …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 571–591 Read article
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Disaster Impact Assessment Using Multi-Sensor Satellite Data: An AI-Based Remote Sensing Approach
Abstract: Natural disasters such as floods, earthquakes, and wildfires cause significant damage to human life and infrastructure every year. Rapid and accurate assessment of the affected areas is essential for effective disaster response and recovery planning. Traditional image-based analysis using single-sensor data often fails under adverse conditions such as cloud cover, smoke, or poor lighting. To overcome these limitations, this study proposes a novel framework for disaster impact assessment using multi-sensor …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 10–22 Read article
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Data-Driven Digital Twin Model for Real-Time Strength Estimation in Polymeric Materials
Abstract: The real-time prediction of mechanical properties in polymeric materials is essential for ensuring quality, consistency, and operational efficiency in modern manufacturing systems. As industrial processes become increasingly complex, traditional trial-and-error approaches to material characterization are no longer sufficient to meet the demands of high-throughput production environments. This study introduces a digital twin-integrated machine learning approach for the real-time estimation of tensile strength in polymeric materials by combining simulation-driven insights with …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 246–257 Read article
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Differential Gene Expression Analysis of Human Atrial Fibroblasts Reveals Dysregulation of RNA Metabolism and Translational Machinery in Atrial Fibrillation
Abstract: Atrial fibrillation (AF) is a complex cardiac arrhythmia characterized by extensive structural remodeling and the activation of atrial fibroblasts, which drive the progression of fibrosis. To identify the underlying transcriptomic alterations, we analyzed six human atrial fibroblast RNA-Seq datasets (three control and three AF) retrieved from the Sequence Read Archive. After performing rigorous quality control and adapter trimming, we aligned the reads to the GRCh38 human reference genome using a …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 · pp. 15–25 Read article
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Machine Learning-Based Quantification of Polymer Structure Property Relationships for Predictive Material Design
Abstract: Polymer structures exhibit complex, hierarchical arrangements that strongly influence macroscopic properties, yet consistent quantification remains challenging due to nonlinear interactions and limited unified modeling strategies. Existing approaches inadequately capture generalized structure–property mappings across diverse polymer systems. This research aims to establish a machine learning-based quantification model for polymer structure–property relationships to support predictive material design. A Polymer Structure Property Dataset of 5,000 polymer samples includes structural descriptors and experimentally measured …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 737–754 Read article
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Antimicrobial Resistance: - A Growing Serious Threat for Global Public Health
Abstract: Antibiotics, among the most significant discoveries of the 20th century, have prevented infectious diseases from claiming millions of lives. However, their widespread use and misuse have created strong selection pressure, enabling microbes to develop antimicrobial resistance (AMR) to many drugs. Over time, AMR has spread primarily through human-to-human contact, both within healthcare settings and in the community. It is driven by a complex interplay of healthcare and agricultural factors, including …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 17, Issue 2, 2026 Read article
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Diabetes Risk Prediction from Survey Data Using Machine Learning Algorithms
Abstract: Diabetes mellitus represents one of the most significant global health challenges, affecting millions worldwide and leading to severe complications if left undiagnosed or poorly managed. Early detection and risk assessment are crucial for preventing the progression of this chronic condition. This research presents a comprehensive machine learning approach for predicting diabetes risk using survey-based health parameters. The study implements and compares four prominent classification algorithms: Logistic Regression, K-Nearest Neighbors (KNN), …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Minerals: A Comprehensive Review of Classification, Properties, Formation, and Their Role in Modern Technology and Sustainability
Abstract: Minerals are naturally occurring, inorganic, solid elements with a definite chemical composition and a characteristic crystal structure. They are the building blocks of rocks. Minerals are the key to the development and progress of human civilization. They are used for the development of infrastructure, electronic gadgets, agriculture, and medicine. This research paper aims to present an exhaustive overview on the field of mineralogy, which includes the definition, classification, physical and …
Published in International Journal of Crystalline Materials · Vol. 3, Issue 1, 2026 · pp. 25–33 Read article
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Architectured Multiphase Polymeric Carriers with Microstructural Gradients: Synergistic Filler Effects for the Precision Delivery in Tuberous Plant Systems
Abstract: In this paper, 50 papers were reviewed to analyse the design, techniques, and applications of polymer composite systems for delivering agrochemicals against major tuberous plant pathogens, including fungi, bacteria, and nematodes. Primary tuber plant pathogens affecting yield are studied, followed by a study of control strategies. This is followed by a study of the basic properties of polymer composites, including the significance of natural and synthetic polymers. Then, the study …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 940–949 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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High-Energy Astrophysics: Exploring the Extreme Universe Through Radiation, Relativistic Phenomena, and Cosmic Cataclysms
Abstract: High-energy astrophysics is a fast-developing area of astrophysical research dedicated to exploring the universe’s most powerful and extreme events. It involves investigating dense and energetic cosmic objects and phenomena, including black holes, neutron stars, supernova remnants, gamma-ray bursts, and active galactic nuclei. These sources emit radiation predominantly in the X-ray and gamma-ray regions of the electromagnetic spectrum and are often associated with high-energy particles, including cosmic rays and neutrinos. Investigating …
Published in International Journal of Universe · Vol. 2, Issue 1, 2026 · pp. 10–15 Read article
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Real-Time Attendance System using Face Recognition Using OpenCV and Firebase Realtime Database
Abstract: The Facial Recognition Attendance System now a days revolutionizes traditional attendance tracking by seamlessly integrating cutting-edge image processing with the capabilities of Firebase Realtime Database. This user-friendly solution simplifies and transforms the attendance management experience. Imagine an intuitive interface utilizing facial recognition technology to effortlessly track attendance. Leveraging advanced face detection algorithms and the enchantment of computer vision, our system ensures accurate face recognition, making each individual unmistakably identifiable. Beyond …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 2, 2026 Read article
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Polymeric Materials in the Anthropocene: Environmental Accumulation, Human Health Concerns, and Cultural Response
Abstract: Polymers made via conventional techniques are very useful because of their strength, adaptability, and cheap. Plastics are not degradable naturally, which creates lots of environmental issues. As plastic products degrade over time, they decompose into microplastics which enter the environment. These microscopic particles called microplastics have been identified in agricultural soils, freshwater and marine environments, and atmospheric dust, enabling their continuous movement through ecosystems and food webs. Recent research shows …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1016–1034 Read article
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The Impact of AI-Driven Real-Time Feedback Systems on Students’ Self-Regulated Learning and Academic Persistence in Secondary Schools, Nigeria
Abstract: Self-regulated learning (SRL) is essential for secondary school students to achieve academic success and lifelong learning competencies, particularly in contexts requiring greater learner autonomy. This expository article examines the potential of Artificial Intelligence (AI)-driven real-time feedback systems to support SRL processes—planning (forethought), monitoring (performance/control), and reflection—within Nigerian secondary education. Grounded in Zimmerman’s cyclical SRL model and Bandura’s Social Cognitive Theory, the paper conceptualises AI tools (e.g., intelligent tutoring systems, learning …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 2, 2026 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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Automatic Car Controller Based on Sign Board using Deep Learning and IOT
Abstract: The rapid growth of intelligent transportation systems has increased the demand for safer and more efficient driving solutions. Conventional vehicles often rely heavily on human intervention, which can lead to accidents due to negligence, fatigue, or poor visibility of traffic signs. This project proposes an automated car control system that utilizes deep learning and Internet of Things (IoT) technologies to recognize traffic signboards and respond accordingly. The primary objective is …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 2, 2026 Read article