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1940 articles for “pre” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Time Series Methods in Meteorology: A Review of Predictive Models and Applications
Abstract: The accurate prediction of time series data holds substantial significance in various fields, enabling informed decision-making and resource optimization. In this study, temperature variations over time are predicted using the Autoregressive Integrated Moving Average (ARIMA) model. Reliable temperature projections are more important now than ever because of climate change and its effects. For time series prediction problems, the ARIMA model—which is well-known for its ability to capture temporal dependencies in …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 35–46 Read article
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A Cross-cultural Analysis of the Utilization and Efficacy of Traditional Herbal Medicine to Cure High Blood Pressure Among People of Rawalakot
Abstract: Safety and efficacy of herbal medicines have not yet been established in treating hypertension. The current study examined the prevalence of herbal medicine use among hypertensive patients in Rawalakot, Poonch, Azad Jammu and Kashmir. The study included 100 hypertensive patients using systemic random sampling. The independent variables were herbal medicine and conventional medicine, while the dependent variable was hypertension. The most known and used herbal medicine was garlic followed by …
Published in International Journal of Biochemistry and Biomolecule Research · Vol. 2, Issue 1, 2024 · pp. 21–32 Read article
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Advanced Computational Models for Predicting Molecular Interactions
Abstract: Understanding molecular interactions is essential for a number of disciplines, including biochemistry, materials science, and medication development. Traditional experimental methods, while accurate, are often time-consuming and expensive. Advanced computational models have emerged as powerful tools to predict molecular interactions efficiently. In order to predict the behavior and interactions of molecules at the atomic and subatomic levels, this paper reviews the most recent developments in computational techniques, such as machine learning …
Published in International Journal of Advance in Molecular Engineering · Vol. 2, Issue 1, 2024 · pp. 8–13 Read article
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A Framework for Privacy-preserving AI Models in Cloud Computing: Challenges and Solutions
Abstract: The growing adoption of cloud computing for deploying artificial intelligence (AI) models has led to significant advancements in sectors such as healthcare, finance, and e-commerce. However, the integration of AI with cloud computing raises critical privacy concerns, particularly when handling sensitive data. This paper presents a comprehensive framework for implementing privacy-preserving AI models in cloud environments, addressing the unique challenges, and proposing effective solutions. The suggested framework employs advanced privacy-preserving …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 1–12 Read article
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DVT in Athletes: A Physiotherapist’s Approach to Prevention, Early Detection, and Rehabilitation
Abstract: Deep vein thrombosis (DVT) is a serious medical condition where blood clots develop in the deep veins, most often in the lower limbs. While it is traditionally associated with immobility, athletes are also at risk due to factors like prolonged travel, injuries, dehydration, and genetic predispositions. This paper explores the role of physiotherapists in preventing, detecting, and rehabilitating DVT in athletes. Preventive strategies include promoting hydration, active recovery, circulatory exercises, …
Published in Research and Reviews : Journal of Surgery · Vol. 14, Issue 1, 2025 · pp. 11–16 Read article
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Modular and Prefabricated Design: Shaping the Future of Interior Spaces
Abstract: This paper explores the emerging trend of modular and prefabricated design in the interior design industry, highlighting its potential to revolutionize the creation of residential and commercial spaces. The study examines the advantages of these approaches, including cost efficiency, sustainability, and design flexibility, while also addressing the challenges such as design constraints and regulatory hurdles. Through the analysis of contemporary projects and innovative case studies, the research demonstrates how modular …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 1, 2024 · pp. 12–19 Read article
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The Rising Burden of Heart Attacks: Causes, Trends, and Prevention Strategies
Abstract: Heart attacks, or myocardial infarctions, remain a leading cause of morbidity and mortality worldwide, with their incidence rising steadily across diverse populations. This review explores the increasing prevalence of heart attacks, emphasizing traditional risk factors, such as poor diet, physical inactivity, smoking, and medical conditions like hypertension, diabetes, and hyperlipidemia. It also highlights emerging risk factors, such as chronic infections, pollutants, substance abuse, and the lasting cardiovascular effects of COVID-19. …
Published in Research and Reviews : Journal of Surgery · Vol. 14, Issue 2, 2025 · pp. 1–11 Read article
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The Impact of a Video-Assisted Teaching Program on the Prevention of Homicide Among Undergraduate Nursing Students at Selected Nursing Colleges in Bagalkot
Abstract: Nomophobia, or the fear of being without a mobile phone, has emerged as a prevalent psychological concern in the 21st century, significantly affecting individuals' mental well-being, particularly among younger populations. This phobia can lead to feelings of anxiety, stress, and even depression, resulting from the constant dependence on mobile devices for communication and social interaction. The study aimed to evaluate the effectiveness of a video-assisted teaching program in preventing nomophobia …
Published in International Journal of Evidence Based Nursing And Practices · Vol. 3, Issue 1, 2025 · pp. 67–73 Read article
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Machine Learning-Based Disease Prediction: A Comparative Analysis for Diabetes, Brain Tumor, and Parkinson's Disease
Abstract: This paper presents a web-based disease prediction system that integrates machine learning and deep learning techniques to assist in the early detection of Parkinson’s Disease, Diabetes, and Brain Tumors. By utilizing clinical data and MRI images, the platform provides rapid and interpretable predictions to support proactive health management. Logistic Regression models are applied to classify structured datasets for predicting Parkinson’s disease and Diabetes, making use of their effectiveness in binary …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 44–54 Read article
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Real Time Alcohol Detection with Accident Prevention System Using Arduino
Abstract: The aim of our research work is to present a project designed to make human driving safer and to significantly reduce road accidents caused by drunk driving. This project integrates an MQ3 alcohol sensor with an Arduino-based system using the ATmega328 processor, which offers enhanced functionality compared to conventional microcontrollers. The MQ3 sensor is capable of detecting alcohol content in a person’s breath and has a sensitivity range of approximately …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 · pp. 19–26 Read article
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Accuracy Improvement for Propeller Cavitation Noise Prediction Using UDF
Abstract: Recently, there has been an increase in demand for propulsion systems with higher hydrodynamic performance and lower underwater-radiated noise, as environmental issues are gaining more attention in addition to the traditional military necessity. It is important to reduce cavitation noise when designing propellers of the ships, especially for oceanographic research vessels because they use acoustic instruments and cavitation noise can interfere with their operation. It is well known that, when …
Published in Journal of Experimental & Applied Mechanics · Vol. 16, Issue 2, 2025 · pp. 18–26 Read article
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Comprehensive Strategies for the Prevention and Management of Genital Thrush in Males and Females: A Public Health Approach in Punjab (September 2024 to February 2025)
Abstract: Background: Genital thrush, a common fungal infection caused mainly by Candida albicans, affected both men and women, leading to itching, discomfort, and recurrent infections. In Punjab, high humidity, poor hygiene awareness, excessive antibiotic use, and limited access to healthcare contributed to its widespread occurrence. Without effective prevention and management strategies, the condition significantly impacted quality of life. Addressing this issue through a public health approach was essential for reducing its …
Published in Research and Reviews: A Journal of Medicine · Vol. 15, Issue 3, 2025 Read article
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A Machine Learning-Based Non-Invasive System for Blood Group Prediction Using Fingerprint Biometrics
Abstract: The research is targeted at the creation of innovative solution "Fingerprint Based Blood Group Prediction" for instant, non-invasive blood group determination from analysis of finger impressions, a breakthrough possibility in emergency health care. Sophisticated machine learning can be employed to map fingerprint patterns to corresponding blood group information and overcome the current lack of a direct connection between the two. Integration of various technologies: employed React for frontend development, Flask …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 9–18 Read article
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Knowledge, Attitude, and Practice Regarding Breast Cancer and Its Prevention Among Adolescent School-Going Girls
Abstract: Introduction: Breast cancer claims the lives of over 500,000 women globally each year. In low-resource settings, most women are diagnosed at an advanced stage of the disease, resulting in low 5-year survival rates, typically ranging between 10 and 40%. However, in regions where early detection and basic treatment are both available and accessible, the 5-year survival rate for early-stage localized breast cancer can exceed 80%. Objectives of the Study: The …
Published in International Journal of Community Health Nursing And Practices · Vol. 3, Issue 2, 2025 · pp. 1–9 Read article
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Effectiveness of a Structured Teaching Programme on Knowledge and Attitude Regarding the Causes, Transmission, and Prevention of Sexually Transmitted Infections Among Rural Women in the Field Practice Area of RHTC, Yadwad, Dharwad District
Abstract: Sexually Transmitted Infections (STIs) pose serious long-term health risks, particularly for women and newborns. Women in rural areas often face significant social consequences due to inadequate STI awareness, which can lead to unsafe sexual practices. This study aimed to assess the knowledge and attitudes of rural women aged 15 to 49 years regarding the causes, transmission, and prevention of selected STIs in the RHTC Yadwad field practice area. Additionally, the …
Published in International Journal of Women's Health Nursing And Practices · Vol. 3, Issue 2, 2025 · pp. 51–78 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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Experimental Validation and Implementation Framework for Optimized Methane Yield Prediction in Anaerobic Digestion
Abstract: The correct validation and realistic application of optimized anaerobic digestion (AD) models are essential steps in transferring biogas production systems to real-life. This paper outlines an experimental validation and deployment pipeline of an AI-optimized model of the methane yield prediction model based on the application of more advanced machine learning and Bayesian optimization methods. Others The validated surrogate-assisted optimization model was tested with controlled laboratory-scale AD experiments at optimized operating …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 25–32 Read article
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Skin Disease prediction and classification from dermoscopy images using Neural Network
Abstract: Skin diseases are among the most common health-related problems affecting people of all age groups, and their occurrence often varies with seasonal and environmental conditions. Delayed or incorrect diagnosis of skin disorders can lead to severe complications, making early and accurate detection extremely important for effective treatment and prevention. In recent years, rapid advancements in deep learning and neural network technologies have significantly contributed to the development of automated medical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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AI-Driven Lightning Strike Prediction Using Polymer-Integrated Sensor Platforms for Climate-Resilient Energy Systems in India
Abstract: Lightning strikes are a major climate-related threat to India, resulting in severe human injuries as well as regular damages to the power transmission network and renewable energy infrastructure. This research aims to introduce the concept of an AI-based lightning strike prediction and mitigation system with the integration of polymers for making climate-resilient energy infrastructure. Multidata are collected based on satellite images, climate variables, as well as surface-based sensing modules, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 234–242 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