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1193 articles for “agriculture chat bot.csv dataset”
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Satellite Sensing in Climate Change Study: A Review
Abstract: Satellite remote sensing has revolutionized our understanding of climate change, providing a global and continuous perspective on Earth's climate system. This study highlights the crucial role of satellite observations in monitoring key climate variables, such as sea surface temperature, ice sheet extent, vegetation cover, and atmospheric composition. From monitoring greenhouse gas concentrations in the atmosphere to mapping ice sheet thickness and sea level rise, satellite instruments offer invaluable data for …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 14, Issue 2, 2025 · pp. 1–11 Read article
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Review of Research on Pozzolanic Materials for Cement Blending and Concrete Applications
Abstract: The growing environmental concerns associated with cement production, particularly its high carbon footprint, have driven research into sustainable alternatives such as supplementary cementitious materials (SCMs) derived from agricultural and industrial waste. This study synthesizes findings from recent investigations into the pozzolanic potential of basil plant ash (BPA), rice husk ash (RHA), and stockpiled fly ash (FA), evaluating their processing methods, microstructural characteristics, and performance in concrete applications. BPA, being derived …
Published in Recent Trends in Civil Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 1–6 Read article
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Enhanced Diabetes Prediction: A Comparative Study of Machine Learning Models
Abstract: Excessively high blood glucose levels lead to diabetes, a condition that can be better managed with early detection, resulting in a longer life and improved health. Machine learning models are essential tools in diagnosing diabetes, especially when trained on appropriate and relevant datasets. In this study, a combination of ensemble methods and nine distinct machine learning algorithms were utilized to develop a predictive model for diabetes diagnosis based on a …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 2, 2025 · pp. 1–10 Read article
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The Role of Artificial Intelligence in Mental Health: Applications in Neurodegenerative Disorders
Abstract: Artificial intelligence (AI) has significantly changed many aspects of medical care, particularly the early evaluation, therapy, and management of neurodegenerative illnesses like Alzheimer's, disease, Parkinson's diseases, and Huntington's diseases. The current research explores the application of AI in mental health with respect to neurological disorders, especially advancements in cognitive examination, neuroimaging analysis, predictive modeling, and customized therapy modalities. Artificial intelligence (AI) systems have shown enormous potential in detecting minute biomarkers …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 15, Issue 3, 2025 · pp. 34–40 Read article
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Machine Learning Approach to Predict the Performability and Emissions of Diesel Engine Fueled with Doped Biodiesel Blend
Abstract: Enhancing the performability and emission characteristics of diesel engines has been a difficult task in light of growing concerns about global warming and other negative effects, as diesel accounts for 70% of global energy demand. In this study, engine performance and exhaust emissions for various fuel blends were thoroughly evaluated using machine learning techniques to predict engine emission and performance behavior. We focused on biodiesel blend and nanoparticle additive concentration …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 1–12 Read article
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Multimodal Disease Detection Using Deep Learning
Abstract: Artificial Intelligence (AI) is playing an increasingly pivotal role in modern healthcare, particularly in improving the speed and accuracy of disease detection. With the evolution of Machine Learning (ML), Deep Learning (DL), and high-performance computing, AI-based solutions are now capable of processing extensive medical datasets, ranging from patient records to diagnostic images, with remarkable efficiency. These systems offer immense potential for early intervention, improved clinical decision-making, and alleviating pressure on …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 129–139 Read article
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Enhancing Glaucoma Diagnosis with Deep Learning: A Study Using ResNet-50 and DenseNet-121
Abstract: Glaucoma is a leading cause of irreversible blindness worldwide, mainly resulting from progressive optic nerve damage, often related to elevated intraocular pressure. Early detection is essential to prevent vision loss, but traditional diagnostic methods rely on specialized equipment and trained professionals, making large-scale screening difficult. This study uses a publicly available fundus imaging dataset to explore the effectiveness of deep learning models for glaucoma detection. These datasets provide medical images, …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 9–18 Read article
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Study of Social Trends Prediction Using AI
Abstract: AI (Artificial Intelligence) has fundamentally changed the ability to analyze social trends by using large datasets to develop predictions about human behavior, public sentiment, and global events. Using methodologies such as Natural Language Processing (NLP), Time-Series Forecasting, and Graph-Based Social Network Analysis, AI is able to find hidden correlations in a variety of available datasets, from social media to economic indicators to public records, and fundamentally changes decision-making based on …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 19–29 Read article
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Plant Disease Detection Using Machine Learning
Abstract: Plant diseases significantly threaten global crop yields and affect both nutritional safety and farmer income. Accurate and early detection of plant diseases is essential for effective intervention and treatment. In this study, we used the CNN model (convolutional neural network) to explore a deep learning-based approach for plant disease classification. The model was trained and evaluated on a large dataset encompassing 38 different classes of plant disease, including healthy leaves. …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 2, 2025 · pp. 07–19 Read article
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Cybersecurity of AI and IoT Integrated for Mechanical Industries
Abstract: By facilitating the concept of Industry 4.0, the intersection of artificial intelligence (AI) and the Internet of Things (IoT) has changed the mechanical industries. When combined, these technologies are advancing process optimization, predictive maintenance, real-time condition monitoring, and smarter automation. In order to give proactive system control and intelligent decision-making, AI algorithms mine large datasets generated via IoT devices for relevant patterns. In the meanwhile, IoT guarantees smooth communication between …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 27–33 Read article
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Classification of Plant Leaf Diseases Using Deep Learning Concepts
Abstract: Agriculture is vital to the economy of a country like India, where 70% of the workforce is employed in this sector. Plants suffering from illnesses experience a significant reduction in output. Delays in the identification of plant diseases lead to decreased yield and plant mortality. The cost of manufacturing is increased since it takes a big number of experts to manually detect plant diseases over several acres of land. The …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 46–55 Read article
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A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression
Abstract: Early diagnosis of genetic diseases is crucial for effective treatment, especially in the case of Leukemia, a type of blood cancer characterized by abnormal proliferation of white blood cells. This paper presents a systematic review of recent computational techniques for the detection and classification of Leukemia using gene expression data obtained from DNA microarray analysis. The study explores diverse methodologies including machine learning (ML), deep learning (DL), and bio-inspired algorithms …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 2, 2025 Read article
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Robust Classification of Traffic Signs Using Relief Feature Reduction Technique
Abstract: Ensuring driver safety amidst the rapid growth of global population and vehicular density continues to be a paramount challenge for transportation authorities and governments worldwide. With the rise of smart mobility solutions and autonomous driving technologies, the ability to detect, classify, and respond to traffic signs accurately has become critically important, especially under diverse and adverse environmental conditions such as rain, fog, or poor lighting. Reliable traffic sign recognition not …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 30–37 Read article
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A Comprehensive Review of Metabolite
Abstract: Metabolites, tiny chemicals, are essential to physiology, signalling, and biological function. This extensive review classifies metabolites into primary and secondary categories by biological relevance. Alkaloids, flavonoids, and terpenoids contribute to ecological interactions and defence systems, while amino acids, nucleotides, and carbohydrates directly affect development and cellular function. The article examines metabolic pathways, mass spectrometry, NMR, and metabolomics, a growing field. Metabolites play a crucial role in various scientific and practical …
Published in Emerging Trends in Metabolites · Vol. 2, Issue 2, 2025 Read article
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Ecological, Economic, and Medical Roles of Fungi: Insights from Mycology in Addressing Global Challenges"
Abstract: The large and diverse kingdom of fungi is vital to ecosystems, industry, agriculture, and medicine. Due to its ecological and biotechnological value, mycology has grown in importance. Fungi are crucial to natural systems and human life, decomposing organic materials, developing mutualistic interactions with plants, and producing antibiotics and fermented products. Recent advancements in molecular biology and genomics have significantly enhanced our understanding of fungal diversity, physiology, and evolutionary processes. These …
Published in International Journal of Fungi · Vol. 2, Issue 2, 2025 Read article
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Exploring Type-II Diabetes Potential of Phyto-Derived Carbon Dots
Abstract: The integration of phytoconstituents with carbon dots (C-dots) presents a novel and sustainable approach to the development of nanotherapeutics for type 2 diabetes mellitus (T2DM). C-dots, zero-dimensional carbon-based nanomaterials, exhibit unique physicochemical properties including high fluorescence, tunable surface chemistry, biocompatibility, and low toxicity. Their ability to enhance the solubility, bioavailability, and targeted delivery of poorly soluble phytochemicals renders them highly suitable for biomedical applications. This study explores the synthesis of …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 3, 2025 · pp. 08–25 Read article
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Comprehensive Review of Nanomaterials Synthesis Methods, Characterization and Multifaceted Applications in Medical Field
Abstract: Nanomaterials associated by special qualities derived from their nanoscale size nanomaterials have tremendous potential in a variety of industries like, medicine & healthcare. Due to today busy life & unhealthy life schedule many abnormal cell growth take place in our body & affect the other organ. Sometimes it may leads to cancer & others dangerous diseases, nanomaterials such as nanotubes, liposomes & polymeric micelles are help for designing the drugs …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 657–669 Read article
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Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 Read article
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Evaluating the Performance of Test Cricket Players Using Principal Component Analysis and the Weighted Average Method
Abstract: This study evaluates cricket player performance using Principal Component Analysis (PCA) and a weighted average approach. In order to achieve this, we analyzed detailed batting and bowling datasets from the International Cricket Council (ICC) to calculate player performance based on various performance indicators. The datasets included comprehensive statistics from multiple matches and tournaments, allowing for an in-depth evaluation of players’ skills and contributions. PCA ranked players according to their participation …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 20–30 Read article
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Innovative Applications of AI and Machine Learning in Voice-Driven Systems: Friday AI 2.0
Abstract: The development of artificial intelligence (AI) has enabled the development of increasingly sophisticated models that can understand and react to human questions. This study introduces Friday AI-2.0, a cutting-edge AI model that improves user engagement by using natural language processing (NLP) and voice synthesis technologies to produce text-based and audio-based responses. By increasing engagement through an intuitive and engaging interface, Friday AI-2.0 seeks to improve the user experience. By describing …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 3, 2025 · pp. 01–09 Read article