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776 articles for “data evaluation”
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Heavy Metal Exposure in Industrial Workers of Punjab
Abstract: Background: Particularly for those in sectors such textiles, metallurgy, and electronics, heavy metal exposure in industrial environments is a major health issue. A range of negative health effects can result from metal exposure including lead (Pb), cadmium (Cd), chromium (Cr), arsenic (As), and nickel (Ni), including neurological, pulmonary, and renal ones. There is little information available on the degree of heavy metal exposure industrial workers in Punjab, India experience. Objective: …
Published in Research and Reviews: A Journal of Toxicology · Vol. 15, Issue 3, 2025 · pp. 1–7 Read article
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GenChrome-ML: A Machine Learning Framework for Early Detection of Chromosomal Disorders Using Genomic Data
Abstract: The increasing burden of chronic disease and cancer demands innovative, more rapid and effective diagnostic tools in the field of healthcare. The majority of current diagnostic tools are dependent upon clinical symptomology and manual evaluation, leading to delays in early detection and treatment. The development of artificial intelligence (AI) and machine learning (ML), in recent years, has offered opportunities for the enhancement of disease prediction, diagnosis and personalization of treatment …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Remote Sensing and Atmospheric Modelling: Data, Processes, Integration and Future Directions
Abstract: Atmospheric modelling plays a central role in weather forecasting, climate projection, and air quality assessment; however, the availability, accuracy, and representativeness of atmospheric observations fundamentally constrain its reliability. Over the past two decades, rapid advances in remote sensing (RS) have transformed atmospheric observation by providing spatially continuous, multiscale measurements of key atmospheric variables, including aerosols, trace gases, clouds, precipitation, and atmospheric thermodynamic profiles. This review synthesises recent progress in integrating …
Published in International Journal of Atmosphere · Vol. 3, Issue 1, 2026 · pp. 54–67 Read article
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Assessing the Knowledge and Attitudes of Eligible Couples Regarding Small Family Norm in a Selected Rural Area of Gwalior
Abstract: This study aimed to determine the level of knowledge and attitude of eligible couples toward permanent family planning methods in a selected rural area of the district. The research method was an evaluation. Sixty couples were chosen at random who met the inclusion and exclusion criteria. The primary purpose of this research is to evaluate the level of understanding and satisfaction with permanent family planning methods among eligible couples in …
Published in International Journal of Community Health Nursing And Practices · Vol. 1, Issue 2, 2023 Read article
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Development and Assessment of Levetiracetam Microspheres Utilizing Synthetic and Natural Polymers: A Biomedical Engineering Perspective
Abstract: In the present study, comparative study of Levetiracetam loaded microspheres using Ethyl cellulose as synthetic and Sodium alginate as natural polymers was done. Solvent evaporation and ionic gelation technique has been successfully employed to produce Levetiracetam loaded ethyl cellulose and sodium alginate microspheres with optimal drug encapsulation that sustained the drug release over a period of time. Based on the pre-formulation studies E1 to E4 and S1 to S4 batches …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 2, Issue 1, 2024 · pp. 1–18 Read article
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Study on Single-Slope Solar Still for Experimental and Data-Driven Analysis for Improving Productivity with Different Basin Materials.
Abstract: This study investigates the single-slope solar still under the diurnal variation of water temperature and distillate yield under identical operating conditions. Experimental analysis was conducted to evaluate the performance enhancement through the incorporation of natural basin materials, namely hemp and sand. The water distillation process is focused on improving potable water productivity and thermal behaviour. The inclusion of hemp and sand in the basin leads to noticeable differences in productivity …
Published in Emerging Trends in Chemical Engineering · Vol. 13, Issue 2, 2026 · pp. 31–46 Read article
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Multimodal Data Fusion with Hybrid Machine Learning for Enhanced Prediction of Li-Ion Battery Remaining Useful Life and State of Charge
Abstract: Lithium-ion battery materials used in modern energy storage systems are required to exhibit high reliability, safety, and long lifecycle performance under varying operational and environmental conditions. Accurate prediction of Remaining Useful Life (RUL) and State of Charge (SoC) is therefore essential for understanding material degradation behavior, improving manufacturing quality, and enabling effective lifecycle management. However, nonlinear electrochemical aging, load variability, and thermal uncertainty significantly complicate accurate estimation of these parameters. …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 4, Issue 1, 2026 · pp. 1–5 Read article
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Evaluating Advancements and Identifying Research Gaps in Automotive Spare Parts Demand Forecasting
Abstract: The automotive industry, a key driver of global economic activity, relies heavily on the effective management of spare parts to ensure vehicle longevity and reliability. Accurate prediction of demand for these components is imperative to uphold ideal stock levels, minimize expenditures, and elevate customer contentment. This review of literature assesses recent progressions in demand prediction methodologies for automotive spare parts, with a specific emphasis on conventional statistical methods and contemporary …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 47–58 Read article
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AI-Optimized Itinerary Design: Transforming the Future of Travel Planning
Abstract: The travel industry is struggling to meet the rising demand for efficient and personalized trip planning. Traditional methods often lack real-time updates and fail to adapt to individual preferences, necessitating innovative solutions. This study presents an AI-powered travel planner utilizing the Gemini API to enhance itinerary creation. By analyzing user preferences, interests, and real-time data, the system delivers tailored travel recommendations. Leveraging advanced technologies such as cloud computing, machine learning, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 74–82 Read article
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In-silico Approach of Few Selected Phytoconstituents on Newer Cancer Targets
Abstract: Background: Cancer’s high death rates are mainly due to, drug resistance and unmet medical demands. It necessitates novel anticancer medications. AI tools aid in efficient and faster drug discovery by analyzing data, modeling processes and optimizing pipeline stages. Aim: The aim of this present study is to evaluate phytoconstituents against novel and newer cancer targets. Methodology: The ligands Daidzein, Resveratrol and Genistein were targeted against the Glutamate dehydrogenase (PDB ID …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 3, 2024 · pp. 12–17 Read article
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In Silico Analysis and Molecular Docking Studies of COX-2 Inhibitors for Anti-Inflammatory Activity
Abstract: Although nonsteroidal anti-inflammatory drugs (NSAIDs) are frequently used to treat pain, lower fevers, and control inflammation, they frequently cause gastrointestinal side effects because they inhibit the COX-1 and COX-2 enzymes. Despite their effectiveness and lack of gastrointestinal side effects, selective COX-2 inhibitors have been linked to cardiovascular risks. To find new COX-2 inhibitors that are safer and more effective, this study uses in silico techniques, such as molecular docking and …
Published in International Journal of Molecular Biotechnological Research · Vol. 3, Issue 1, 2025 · pp. 38–55 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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Effectiveness of Public Health Campaigns in Reducing Oral Cancer Incidence in Urban Maharashtra
Abstract: Introduction: Oral cancer is a major public health problem in urban Maharashtra which can be attributed to high consumption of tobacco, late presentation, and poor awareness. To tackle these issues, public health campaigns have been established to encourage early diagnosis, lifestyle modification, and availability of health resources. This study assesses the impact of these campaigns on the reduction of oral cancer incidence and awareness level in the population. Methods: This …
Published in International Journal of Evidence Based Nursing And Practices · Vol. 3, Issue 2, 2025 · pp. 1–8 Read article
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Elderly Healthcare Using Federated Learning Approach
Abstract: The healthcare system for elderly people faces several challenges, which can be addressed using advanced machine learning models. These models can help monitor chronic diseases, detect falls, and provide personalized health recommendations. The study uses comprehensive datasets like MIMIC-III/IV, WESAD, and UCIHAR to explore human movements, device limitations, and the differences in fall occurrences. A detailed review of existing literature discusses current technologies for activity monitoring and fall detection, focusing …
Published in Current Trends in Information Technology · Vol. 16, Issue 1, 2025 · pp. 13–23 Read article
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Experimental Exploration of Crack and Damage Dynamics of Hybrid FRP Nano Composites
Abstract: Fiber-reinforced polymer (FRP) composites have become essential materials in modern engineering structures because of their excellent strength-to-weight ratio, corrosion resistance, and adaptability in design. Among different fracture modes, Mode I interlaminar fracture where cracks propagate under tensile opening stresses is one of the most critical forms of damage in layered composites. Since delamination occurs within the matrix-rich regions between plies, improving the matrix properties plays a key role in enhancing …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 220–232 Read article
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Integrate AI and IoT to Develop Sustainable Polymer Structural Materials Processing Optimization: Enabled Monitoring Strategies for Performance and Lifecycle Assessment
Abstract: The need for long-lasting structural polymer materials that are both environmentally friendly and highly mechanically effective is driving demand for these materials as the industrial sector continues to grow. Optimizing processes, saving energy, detecting faults, and monitoring structures are all hindered by conventional polymer manufacture. This study suggests an AI-IoT system for environmentally friendly production of structural polymer materials to get around these problems. Tools for evaluating system performance and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 169–192 Read article
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An Efficient CNN Model for Automated Cotton Leaf
Abstract: Timely and accurate identification of cotton leaf diseases are essential for maintaining healthy crop production and minimizing agricultural losses. Early detection allows farmers to take preventive or corrective measures, reducing the risk of disease spread and improving overall yield. In this study, we propose a Convolutional Neural Network (CNN) based model for the automated classification of cotton leaf diseases using image-based detection techniques. The model is trained on a diverse …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 3, 2025 · pp. 01–10 Read article
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Inhibition of PI3K/Akt/mTOR Signaling Pathway by Vitis Vinifera Phytocompounds: A Promising Strategy for Supressing Colorectal Cancer Growth and Metastasis
Abstract: Objectives: Colorectal cancer was not typically identified a few decades ago. Today, with almost 900 000 fatalities each year, it is the fourth most dangerous cancer in the world. Colorectal cancer is responsible for about 10% of all cancer diagnoses annually and cancer-related deaths worldwide. It is the second most common type of cancer in women and the third most common type in men. Incidence and death are roughly 25% …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 1, Issue 2, 2023 · pp. 64–75 Read article
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Modernizing Pharmacovigilance: Leveraging AI, Automation, and Real-World Data for Drug Safety
Abstract: Pharmacovigilance, or PV, is “the pharmacological science relating to the detection, assessment, understanding, and prevention of adverse effects, mainly long term and short-term adverse effects of medicines.” PV’s specific objectives are to increase patient care and safety when using medications and all medical and paramedical therapies; assist in evaluating the benefits, drawbacks, efficacy, and risks of medications, ensuring their safe, prudent, and more effective use; and promote clinical training, education, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 12–21 Read article
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Real Time Automobile - Caused Air Pollution Monitoring System
Abstract: The system proposed in this paper aims to be a novel approach for real-time detection and quantification of vehicular emissions, integrated into smart city infrastructures. The structured workflow enhances accuracy and efficiency. The license plate is captured by OCR, while the ground clearance is simultaneously measured, allowing the thermal camera to dynamically adjust its position to align with the tailpipe level. The emission data is collected and transmitted to a …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 1, 2025 · pp. 49–55 Read article