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1193 articles for “agriculture chat bot.csv dataset”
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Stability Analysis of Pontoons under Breakwater and Mooring System
Abstract: Floating pontoons are the new advance method and technology in construction industry. Land issue is very common issue in various countries. Constructing on waters and in the waters is the only option to overcome the land issue. Also, the construction of the bridges and other water-based structures also can be constructed by using pontoons. Pontoons are being used in the construction since ancient time Including temporary bridges and small shelters. …
Published in Journal of Water Resource Engineering and Management Read article
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Stability Analysis of Pontoons Under Breakwater and Mooring System
Abstract: Floating pontoons are the new advanced method and technology in the construction industry. Land issues are very common issues in various countries. Constructing on and in the waters is the only option to overcome the land issue. Also, the construction of the bridges and other water-based structures can be constructed by using pontoons. Pontoons have been used in construction since ancient times. This includes temporary bridges and small shelters. It’s …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 29–37 Read article
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An Analysis of Multimodal Fusion in Deepfake Detection for Video Samples
Abstract: In today’s rapidly evolving digital landscape, deepfake technology stands as both a marvel and a threat to privacy and security. Deepfakes, hyper-realistic synthetic media created using artificial intelligence (AI), can deceive and manipulate on an unprecedented scale, from political propaganda to compromising videos of public figures. This research navigates deepfake detection, focusing on two advanced methodologies: the vision transformers (ViT) image classifier and the Meso4 method. The ViT model utilizes …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 19–27 Read article
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A Study on Distribution of Acridoidea (Orthoptera) of Patna District, Bihar (India)
Abstract: A thorough study of species shows that 12 types of grasshoppers fall into 3 families: Acridoidae, Catantopidae, and Pyrgomorphidae. These families have 7, 3, and 2 species, respectively. The survey places with rich plants and different weather conditions – like rainfall, humidity, and temperature. Researchers did an extensive survey. They checked many crops and habitats to gather grasshoppers from various agricultural spots. These insects were observed in their natural habitat. …
Published in Research & Reviews : Journal of Ecology · Vol. 13, Issue 3, 2024 · pp. 1–5 Read article
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Deep Learning-Based Pneumonia Diagnosis: A Comparative Review of Models and Metrics
Abstract: Pneumonia is a common viral infection that affects a large percentage of people worldwide. It is more common in developing and impoverished areas because of factors like poor sanitation, crowded living quarters, pollution in the environment, and restricted access to medical facilities. In order to improve survival chances and gain access to therapeutic therapies, pneumonia must be diagnosed as soon as possible. A type of artificial intelligence called deep learning …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 Read article
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Enhancing Wildlife Tourism Management Using Deep Learning and Particle Swarm Optimization (PSO) for Animal Detection in Wildlife Sanctuaries
Abstract: Wildlife tourism is one of the most thriving sectors, faced with huge challenges in terms of safeguarding protected areas. As demand for wildlife experiences accelerates, it becomes necessary to find efficient measures that are friendly to conservation. The use of these advanced techniques in this field such as YOLO and PSO algorithm presents a new dimension on managing wildlife tourism. To harness the abilities of these techniques, this research centers …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 41–50 Read article
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A Survey of Several Machine Learning (ML) Algorithms for Security Solution in Internet of Things (IoT) Networks
Abstract: The Internet of Things (IoT) refers to the integration of physical objects with the Internet, allowing for connectivity and monitoring. This idea has garnered immense attention from researchers and users alike, driven by the widespread accessibility of the Internet. It spans a wide range of devices, including smart versions of conventional appliances, innovative tools tailored for Internet-enabled ecosystems, and sensors that leverage connectivity to revolutionize industries such as manufacturing, healthcare, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 1–11 Read article
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Environmental and Health Impacts of Rice Milling: A Case Study of Dinajpur Sadar Upazila, Bangladesh
Abstract: Rice milling plays a crucial role in Bangladesh's agricultural economy but contributes significantly to environmental pollution, affecting air, water, and soil quality, which in turn impacts public health and agricultural productivity. While prior studies have focused on immediate health effects like respiratory problems and reduced crop yields, they often overlook long-term consequences such as chronic diseases, soil degradation, and socio-economic impacts. Additionally, there is limited comparison between traditional and automated …
Published in International Journal of Climate Conditions · Vol. 2, Issue 1, 2025 · pp. 18–28 Read article
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Algae as Bio-Fertilizer
Abstract: Bio-fertilization represents a sustainable agricultural practice that leverages bio-fertilizers to enhance soil nutrient levels, thereby increasing agricultural productivity eco-friendly and feasible substitute for pollution-free agricultural applications, soil microflora has been used to increase biomass production and improve soil fertility. Numerous cyanobacteria, including species like Oscillatoria angustissima, Nostoc sp., and Anabaena sp., are known to be efficient nitrogen-fixing biofertilizers. Acuteodesmus dimorphus, Spirulina platensis, Chlorella vulgaris, Scenedesmus dimorphus, Anabaena azolla, and Nostoc …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 1, 2025 · pp. 32–41 Read article
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Screening Some Sorghum (Sorghum Bicolor L. Moench) Genotypes for Yield and Resistance Against Stem Borer (Sesamia Calamistis) in Nigeria
Abstract: Sorghum is a staple crop with global significance, scientifically it’s known as Sorghum Bicolor, stands as one of the most important cereal crops globally, particularly in regions with arid and semi-arid climates. Sorghum remains a cornerstone of agricultural economies worldwide with its widespread cultivation and diverse applications; however, its production is often hindered by various biotic stresses, with stem borer (Sesamia calamistis) infestation being a significant concern. The stem borer …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 15, Issue 1, 2025 · pp. 50–55 Read article
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Optimizing Data Processing Efficiency in Big Data: Advanced MapReduce Algorithm Innovations
Abstract: The exponential growth of big data in recent years has created an urgent need for innovative and efficient processing frameworks capable of managing and analyzing massive and complex datasets. Among these, MapReduce has gained prominence as a powerful tool for distributed data processing due to its simplicity and scalability. However, traditional MapReduce frameworks often encounter significant limitations in terms of efficiency, scalability, and resource optimization, particularly when handling large-scale and …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 1–7 Read article
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Greenhouse Gas Emissions, Land Use, and Sustainable Natural Resource Management: A Review
Abstract: Greenhouse gas (GHG) emissions, changes in land use, and the exploitation of natural resources are significant obstacles to achieving global sustainable development goals. These interconnected challenges have far-reaching implications for environmental stability, economic growth, and societal well-being.Urbanization, deforestation, and agriculture are examples of land use activities that significantly increase greenhouse gas emissions. Agricultural activities release methane and nitrous oxide, while deforestation leads to carbon dioxide emissions by reducing forest cover, …
Published in International Journal of Sustainability · Vol. 2, Issue 1, 2025 · pp. 7–11 Read article
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Advancements in K-Means Clustering: Boosting Algorithm Performance through Innovations
Abstract: K-Means clustering is a widely used unsupervised learning algorithm for partitioning a dataset into distinct clusters. Despite its popularity and simplicity, K-Means has several limitations, such as sensitivity to initial centroids, convergence to local minima, and inefficiency with large datasets. This paper reviews recent advancements aimed at addressing these challenges and enhancing the performance of the K-Means algorithm. Innovations include improved initialization methods, such as K-Means++, which significantly reduce the …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 30–37 Read article
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Physico-Chemical Analysis of Soil Quality Parameters in Tamilnadu Region An Analytical Approach Towards Life on Land -SDG 15
Abstract: This study examines the physico-chemical properties of soil in Tamilnadu region, supporting SDG 15’s framework for sustainable land management. Soil, as a vital non-living component, plays a crucial role in ecosystem functioning by facilitating nutrient cycling, retaining water, and supporting habitats for a wide range of organisms. The research analysis key physical parameters (colour, texture, structure, porosity, density, consistency, temperature) and chemical properties, focusing on both macro and micronutrients. Various …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 9–15 Read article
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Prediction of Customer Churn Using Machine Learning Classification Models
Abstract: Customer churn prediction is a critical task in both the telecommunication and medical industries, where retaining customers or patients is essential for ensuring long-term profitability and maintaining high-quality service. To address this, a range of machine learning models—including logistic regression, decision trees, random forests, gradient boosting machines, and support vector machines—were employed to accurately forecast churn behavior. Prior to model training, the dataset underwent thorough preprocessing, which included handling missing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 86–92 Read article
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Algorithm for the prediction of cardiovascular disease (CVD)
Abstract: cardiovascular diseases (CVD) still claim a significant number of deaths globally and remain the number one killer with an annual death toll of nearly 17.9 million. While several medical advancements have been made, an early diagnosis is still hard to obtain, which often leads to worsening conditions and intricate treatment options. With the advancement of modern technology, Machine learning has demonstrated to be a miraculous tool which can greatly impact …
Published in Research and Reviews : A Journal of Immunology · Vol. 15, Issue 2, 2025 Read article
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Melanoma Skin Cancer Detection Using Deep Learning
Abstract: Melanoma, a fatal type of skin cancer, is a major global health concern. For better patient outcomes, early and precise detection is essential. A branch of artificial intelligence called deep learning has demonstrated encouraging outcomes in medical image analysis, particularly the identification of skin cancer, in recent years. We present a new method for detecting melanoma skin cancer in this paper by utilizing the ResNet-50 architecture, a deep convolutional neural …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 · pp. 1–9 Read article
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IoT-Based Emergency SOS System for Post-Accident Assistance
Abstract: The increase in road accidents poses significant challenges for timely medical response, often leading to life-threatening delays. This project proposes an IoT-based accident wound detection system that utilizes a night vision camera mounted on either the interior or exterior of a vehicle. The system aims to detect injuries sustained by individuals during a collision and promptly alert emergency services. By employing a night vision camera, the system can operate effectively …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 2, 2025 · pp. 11–19 Read article
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Eye Disease Classification Using K-means Clustering Algorithm and Ensemble Classification Approach
Abstract: In this study, we present a comprehensive approach for the classification of eye diseases, specifically targeting normal, cataract, glaucoma, and diabetic retinopathy conditions. This research uses a dataset from Kaggle, which provides a wide and varied collection of retinal images to ensure good representation. The methodology encompasses advanced image processing and machine learning techniques to ensure accurate diagnosis and prediction. The preprocessing phase involves a series of image enhancement techniques …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 15–27 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