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1945 articles for “and analysis” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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The Contribution of Mathematics to Make Developed India
Abstract: This research paper explores the significant contributions of mathematics to the development of India, tracing its influence from ancient innovations to modern applications across diverse sectors. India has a long-standing mathematical tradition, with foundational achievements such as the invention of zero, the decimal system, and advancements in algebra, trigonometry, and geometry, which profoundly shaped global knowledge systems. These early contributions established India as a pioneering hub of mathematical thought and …
Published in Research & Reviews : Journal of Statistics · Vol. 14, Issue 3, 2025 · pp. 08–15 Read article
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Integrated Spatial and Statistical Assessment of Groundwater Quality in Rupbas Tehsil of Bharatpur, Rajasthan: A WQI-based Approach
Abstract: This study presents a comprehensive evaluation of groundwater quality in Rupbas Tehsil of Bharatpur District, Rajasthan, through the application of the Water Quality Index (WQI) and hydrogeochemical techniques. A total of 32 groundwater samples, 16 collected during the pre-monsoon and 16 during the post-monsoon seasons, were analyzed for key physicochemical parameters including pH, electrical conductivity (EC), total dissolved solids (TDS), dissolved oxygen (DO), oxidation-reduction potential (ORP), total hardness (TH), total …
Published in Journal of Water Pollution & Purification Research · Vol. 12, Issue 3, 2025 · pp. 84–93 Read article
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Depression Detection Using Machine Learning: A Comprehensive Review
Abstract: Depression remains one of the most prevalent mental health conditions globally, yet it frequently goes undiagnosed due to the reliance on subjective evaluation methods. With the growing availability of digital behavioral data and significant progress in machine learning (ML), new possibilities have emerged for the automated detection of depression. This review offers a detailed examination of recent advancements in ML-driven approaches to identifying depressive symptoms. It covers a range of …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 27–32 Read article
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Early Detection of Heart Disease using Machine Learning Techniques
Abstract: Coronary illness stays one of the main sources of death around the world. Exact expectations of coronary illness can altogether work on quiet results by empowering early intercession and customized treatment plans. Throughout the course of many recent years, AI (ML) methods have been extensively investigated for anticipating coronary illness, attribuFig to their remarkable capacity to analyze complex data patterns and generate precise predictions based on historical clinical records. With …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 34–45 Read article
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Epidemiology, Risk Factors, And Prevention Of Typhoid Fever In North India: A Regional Perspective
Abstract: Introduction: Typhoid fever, caused by Salmonella enterica serovar Typhi, remains a major public health concern, particularly in low- and middle-income countries. The disease is transmitted through contaminated food and water, leading to significant morbidity and mortality. Understanding its epidemiology, associated risk factors, and preventive measures is essential for effective control and management. This study aims to provide a comprehensive analysis of typhoid fever's prevalence, risk factors, and recommended interventions, with …
Published in Research and Reviews : A Journal of Immunology · Vol. 15, Issue 3, 2025 Read article
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MentaLLaMA: Advancing Mental Health Insights with Instruction-Finetuned Large Language Models
Abstract: The growing prevalence of mental health challenges in contemporary society has highlighted the urgent need for advanced, interpretable, and reliable artificial intelligence solutions that can support mental health assessment and intervention. In response to this need, this research introduces a novel collection of open-source, instruction-tuned large language models (LLMs) specifically designed to facilitate transparent and accurate mental health evaluations. Leveraging a newly developed dataset, which integrates multiple tasks and diverse …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 08–15 Read article
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Natural Language Processing in Education: A Review of Applications, Challenges, and Future Directions
Abstract: Natural Language Processing (NLP) has increasingly become a transformative force within the field of education, offering innovative solutions and reshaping traditional methods of teaching, learning, assessment, and educational research. This review explores the evolving landscape of NLP applications in education, shedding light on significant advancements, ongoing challenges, and emerging opportunities. The integration of NLP into intelligent tutoring systems has enabled more personalized learning experiences, while automated assessment tools have enhanced …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 11–18 Read article
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Identification of Hazards and Evaluation of Risks in Flyover Construction Site
Abstract: Indore, a rapidly growing city in Madhya Pradesh, India, faces significant traffic congestion challenges. Constructing flyovers has been suggested as an effective measure to resolve this problem. This project of Reti mandi flyover which is 1199.65 long and 37 km wide having six lanes. This review aims to evaluate the feasibility and sustainability of flyover construction in Indore, considering urban infrastructure development, traffic management, environmental impact, and socio-economic factors. The …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 2, 2025 · pp. 17–16 Read article
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Deep Learning-Based Alzheimer’s Disease Detection: A CNN Approach
Abstract: Alzheimer’s disease (AD) is a neurological condition that worsens with time and impairs a patient’s quality of life by causing cognitive loss. For prompt intervention and management of AD, early identification is essential. In this work, we propose a deep learning-based method for automatically classifying Alzheimer’s disease from medical imaging data using convolutional neural networks (CNNs). Our algorithm is intended to evaluate brain MRI images and detect anatomical variations suggestive …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 Read article
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A Review on Lung Cancer Prediction Using Machine Learning
Abstract: Lung cancer continues to be a major contributor to cancer-related mortality across the globe. Timely diagnosis and reliable prediction models play a crucial role in enhancing treatment outcomes and survival rates for patients. The present study focuses on the utilization of machine learning (ML) methods for the prediction of lung cancer. Using datasets that incorporate clinical records, imaging modalities, and genetic profiles, the research assesses the predictive capabilities of multiple …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 3, 2025 · pp. 1–11 Read article
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Kinetics of Crystallization and Microstructural Evolution of Commercial Fluorophlogopite Machinable Glass- Ceramics in the System SrO∙4MgO∙Al2O3∙ 6SiO2∙2MgF2 with Varying in B2O3
Abstract: Glass materials based on fluorophlogopite stoichiometry with varying concentrations of B₂O₃ were synthesized using the melt-casting method, followed by heat treatment at different crystallization temperatures. The resulting glass and glass–ceramic samples were characterized using differential thermal analysis (DTA), scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier-transform infrared (FT-IR) spectroscopy. Kinetic analysis revealed that the activation energies required for the formation of glass–ceramics were 192.77 kJ mol⁻¹ and 210.47 kJ …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 12, Issue 3, 2025 · pp. 1–16 Read article
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The Economic Impact of Land Acquisition for Industrial Projects
Abstract: Land acquisition for industrial projects plays a crucial role in promoting economic development, yet it often leads to significant socio-economic challenges. In India, land acquisition is regulated under the Right to Fair Compensation and Transparency in Land Acquisition, Rehabilitation and Resettlement Act, 2013. While this legislation aims to ensure fair compensation, transparency, and proper rehabilitation for affected individuals, its implementation often faces significant hurdles. Prolonged administrative delays, ongoing legal battles, …
Published in International Journal of Land · Vol. 2, Issue 2, 2025 · pp. 17–24 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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Finite Element Modelling of Contact Stresses in Helical Gear Systems
Abstract: Helical gears are widely used in modern power‐transmission systems because of their high load‐carrying capacity, smooth meshing action, and increased overlapping of gear teeth. However, the design of helical gear pairs is constrained by contact stresses generated at the mating tooth surfaces, which can lead to surface fatigue (pitting), micro-cracking, and ultimately gear failure. Traditional analytical methods, such as those of the American Gear Manufacturers Association (AGMA) or International Organization …
Published in Trends in Machine design · Vol. 12, Issue 3, 2025 · pp. 35–39 Read article
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Assessment of Matrix Cracking and Fiber Breakage in Hybrid Composite Materials.
Abstract: Hybrid composite materials, combining two or more distinct fiber or matrix constituents, have emerged as advanced structural solutions for aerospace, automotive, marine, and civil engineering applications. However, their complex microstructure makes them susceptible to multiple interacting damage mechanisms, particularly matrix cracking and fiber breakage. This study provides a comprehensive assessment of these damage modes, emphasizing their initiation, evolution, and combined effects on the mechanical integrity of hybrid composites. Matrix cracking …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article
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Progress and Uses of Satellite Remote Sensing
Abstract: Satellite remote sensing has become an important tool for watching, studying, and controlling both natural and man-made systems on Earth. Satellite sensors collect electromagnetic radiation that is reflected or transmitted from the Earth's surface. This data is needed for environmental monitoring, resource management, and hazard assessment. Recent improvements in sensor resolution, data processing techniques, and cloud-based platforms have made remote sensing applications much more accurate and easier to use. The …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 8–19 Read article
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SpecForesight: A Predictive Analytics Pipeline for Laptop Price Forecasting
Abstract: This paper frames laptop pricing as a supervised predictive analytics problem, transforming product specifications into feature-rich signals to forecast price with calibrated regression models and operational guardrails against drift. A structured pipeline ingests tabular listings, performs data cleaning, and engineers domain-informed features (e.g., central processing unit (CPU) family and clocks, graphics processing unit (GPU) tiering, memory/storage density, display, and touch capabilities), followed by encoding and normalization to optimize model learnability. …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 61–71 Read article
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Acoustic Sensing for City Flow: Quasi-Supervised Recognition of Sirens and Traffic for Urban Mobility Intelligence
Abstract: This paper frames environmental audio as a mobility telemetry source, extending a benchmark urban-sound corpus with transportation-critical classes—ambulance, firetruck, police, and traffic—and training spectrogram-based models under a quasi-supervised regime to support real-time city operations; leveraging 10-fold protocols, class-weighted objectives, and audiospecific augmentations (time stretch, pitch shift, SpecAugment, PatchAugment), the system benchmarks multiple CNN backbones combined with self-supervised learning paradigms enable the extraction of rich, discriminative acoustic representations, achieving strong multi-class …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 42–50 Read article
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Stability-Indicating Rp-Hplc Development and Validation for the Estimation of Lercanidipine Hydrochloride Content in Tablet Dosage Form
Abstract: A sensitive, stability-revealing, and easy reverse-phase high-performance liquid chromatographic (RP-HPLC) technique was developed and rationalized to be in a position to determine Lercanidipine hydrochloride in ingested dosing preparations. It was separated by chromatography on a C 18 column using a mobile phase containing 10 mM potassium dihydrogen phosphate buffer and methanol (20:80, v/v; pH 4.0) at a flow rate of 1.0 mL/min and UV detected at 258 nm. The retention …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 13, Issue 1, 2026 · pp. 17–26 Read article
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OBD-II Big Data–Driven ML and AI-Based Virtual Sensing for Fuel Economy, Component Health, and Carbon Intelligence
Abstract: The rapid growth of connected vehicles has led to the large-scale availability of high-frequency On-Board Diagnostics II (OBD-II) data; however, much of this data remains underutilised, as existing studies and commercial systems typically address fuel economy, maintenance, or emissions in isolation or rely on additional physical sensors. Such fragmented and sensor-dependent approaches limit scalability and increase system cost, particularly in high-volume and resource-constrained vehicle markets. To address this gap, this …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 39–50 Read article