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341 articles for “and regression analysis”
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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Empirical Analysis of the Effects of Owner Occupied and Tenant Occupied Housing Units on the Environmental Quality of Enugu, Nigeria
Abstract: AbstractHow occupants of housing units handle the various housing units they occupy has been identified as among the factors affecting the quality of the dwelling units of residential environment of Enugu metropolis. The actions of landlords who own and occupy their housing units in Enugu (as they concern the housing units owned and occupied) are different from those of the tenants who occupy the units on rental basis. These invariably …
Published in Research & Reviews : Journal of Ecology · Vol. 5, Issue 2, 2016 · pp. 33–41 Read article
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Agronomic Performance, Harvest Dynamics, and Oil Yield of Lemongrass Varieties in a Semi‐Arid Ecosystem: Effects of NPK Regime and Harvest Timing
Abstract: This study investigated the agronomic performance, biomass production, and essential oil yield of three lemongrass (Cymbopogon spp.) varieties (CKP-25, Krishna & Pragati) under varying NPK fertilization regimes and harvest timings in a semi-arid ecosystem. A split-plot factorial design with four nutrient levels (Control, 50%, 100%, and 150% of the recommended NPK dose) and two harvest stages (90 and 180 days after planting, DAP) was implemented. Results revealed that both NPK …
Published in Research & Reviews : Journal of Botany · Vol. 15, Issue 1, 2026 · pp. 8–21 Read article
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A Retrospective Analysis of Resin-Based Polymer Composites and Bioactive Glass-Polymer Hybrids Regarding Secondary Caries and Durability
Abstract: Aim- To compare the 2-year clinical survival and failure modes of a Resin-Based Polymer Composites and BioactiveGlass-Polymer Hybrids in Class I and II posterior restorations. Methods-A total of 550 restorations were placed in adult patients across various private dental practices in India to ensure a diverse clinical demographic. Teeth were randomly assigned and restored with either a hybrid composite (Te-Econom, IvoclarVivadent; n=275) or a Resin-Modified Glass Ionomer Cement (GC Gold …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1089–1095 Read article
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Machine Learning-Based Channel Estimation in 5G, Beyond-5G, and 6G Networks: Recent Advances and Future Directions
Abstract: Accurate channel estimation is one of the most fundamental challenges in modern wireless communication systems. In fifth- generation (5G) New Radio (NR) and emerging sixth-generation (6G) networks, precise knowledge of the wireless channel is essential for achieving reliable data transmission, high spectral efficiency, and low Bit Error Rate (BER). Conventional estimation techniques such as Least Squares (LS) and Minimum Mean Square Error (MMSE) rely on mathematical channel models and predefined …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
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Glacier Volume Changes and Their Climatic Causes in Tirungkhad Basin Located in Western Himalaya
Abstract: Normal 0 false false false EN-IN X-NONE X-NONE In the Himalaya, a significant number of glaciers are shrinking due to climatic variations. Monitoring of these glaciers is important to assess future availability of water resources. However, Himalayan glaciers are normally difficult to monitor due to the rugged, mountainous terrain. Therefore, in the present study, Survey of India (SOI) topographical maps (1966) and Landsat datasets as ETM+ (2000, 2006) and TM …
Published in Journal of Remote Sensing & GIS · Vol. 4, Issue 2, 2013 · pp. 35–46 Read article
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CIPHER Intelligence: AI-Powered Global Military Expenditure Analysis and Predictive Modeling
Abstract: Military expenditure analysis has emerged as a critical component of economic and geopolitical intelligence in the modern era. This paper presents CIPHER Intelligence, a comprehensive AI-powered platform for analyzing and predicting global military spending patterns across 211 countries spanning54 years (1970-2024). We employ advanced machine learning techniques, particularly Random Forest regression models, to achieve 99.5% prediction accuracy for military expenditure forecasting based on economic indicators. The platform integrates data from …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 1–8 Read article
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Effect of Malaria Endemic on Socio-Economic Activities in South-East Nigeria: A Study from 2012 to 2023
Abstract: The research investigated the effects of malaria on socio-economic activities in South-East Nigeria between 2012 and 2023, emphasizing the effectiveness of different malaria management strategies. The analysis utilized both primary and secondary data, employing frequency tables and a five-point Likert scale to gauge respondents' levels of agreement. Furthermore, multiple regression models were utilized to explore the relationships among the variables.. Findings indicated that while diverse malaria interventions had a positive …
Published in Research and Reviews: A Journal of Health Professions · Vol. 14, Issue 3, 2024 Read article
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Advanced Lithium-Ion Battery Prognostics: A Comprehensive Review of Machine Learning Approaches for Remaining Useful Life Prediction
Abstract: The lithium-ion battery (LIB), as one of the main sources for portable power systems, has been increasingly popular owing to its widespread applications in electric vehicles, consumer electronics, aerospace and renewable energy. Despite their advantages in high energy density and long cycle life, LIBs suffer from degradation over time of aging and cycling, resulting in loss of performance, safety issues, and economic bottlenecks. Predicting their Remaining Useful Life (RUL) is …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 2, 2025 · pp. 12–27 Read article
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Financial Forecast: Systematic Analysis Using Principal Component Analysis
Abstract: The most popular technique for data exploration and analysis across all scientific disciplines that can influence the classification model's accuracy is principal component analysis (PCA). In this study, the high dimensionality of the stock market is examined in order to forecast market movements using PCA in conjunction with linear regression. While reducing data redundancy, PCA can aid in enhancing the predictive performance of machine learning techniques. The New York Stock …
Published in E-Commerce for Future & Trends · Vol. 9, Issue 2, 2022 · pp. 18–24 Read article
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Evaluation of Penalized Estimation Methods for Big Data Analysis
Abstract: In this paper we described the sparse Laplacian shrinkage (SLS) method which is a penalized method for variable selection and estimation in big data analysis that uses a combination of the minimax concave penalty (MCP) and Laplacian quadratic as the penalty. The SLS uses the MCP to promote sparsity and Laplacian quadratic penalty to encourage smoothness among coefficients associated with the correlated predictors. An important advantage of the MCP over …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 2, Issue 2, 2015 · pp. 49–55 Read article
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Fake News Detection Using N-Gram Analysis and Machine Learning Algorithms
Abstract: Fake news is untrue information presented as news. Fake news easily spread than real news amongst social networking sites. Detection of fake news is an important emerging research area which is gaining popularity. The main challenge in fake news detection is limited availability of resources (datasets). This project work detects fake news using n-gram analysis and machine learning algorithms. Evaluation and comparison between two feature extraction technique namely Term Frequency …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 8, Issue 1, 2021 · pp. 33–43 Read article
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The Milklipidometric Model: A Mathematical Equation-based on Electric Conductivity to Predict Butterfat Concentrations in Bovine Milk
Abstract: The milklipidometric model is a mathematical equation to predict butterfat in raw milk and it is based on electric conductivity principle. The model differs from the existing equations in that it uses variables (electric conductivity, and volume fraction of whole milk ) which can be easily measured and it predicts fat at wide temperature, range of 5–60°C. Accurate results can be obtained even using commercial electrical conductivity meters, hence making …
Published in Research and Reviews : Journal of Dairy Science and Technology · Vol. 8, Issue 1, 2019 · pp. 10–21 Read article
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Evaluating Epidemiological and Physical Risk Factors in the Development of Chemotherapy-induced Peripheral Neuropathy (CIPN): An In-depth Systematic Review and Meta-analysis
Abstract: Background of study: Chemotherapy-induced peripheral neuropathy (CIPN) encompasses a range of adverse effects caused by various cytotoxic medications and stands as a primary source of pain among individuals who have survived cancer. In instances of pronounced and sudden CIPN, it might become necessary to diminish chemotherapy dosages or discontinue their application. Currently, no efficacious strategy exists for proactively preventing CIPN, managing established chronic CIPN is constrained, and the risk factors …
Published in International Journal of Oncological Nursing and Practices · Vol. 1, Issue 2, 2023 · pp. 10–21 Read article
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Predicting and Prohibiting the Risk of Heart Failure Using Machine Learning
Abstract: It is challenging to estimate the likelihood of complex chronic disease while treating conditions like heart failure. The application of machine learning, an area of artificial intelligence, in cardiovascular care is growing quickly. In essence, it defines how computers classify and understand data, or choose a task with or without human intervention. The theoretical underpinnings of machine learning are models that accept input data (such as images or text) and …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 1, 2023 · pp. 15–20 Read article
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A Study on Safety Climate Status in Oil and Gas Industries of Karnataka
Abstract: AbstractIndustrial workers all around the world, mainly oil and gas and construction workers often work at dangerous worksites, where they are constantly exposed to hazardous components. This leads to many catastrophic events and disasters. Safety is an important concept which needs to be followed in all industries in order to avoid accidents. But, very few studies related to the safety climate in oil and gas industries have been conducted in …
Published in Journal of Industrial Safety Engineering · Vol. 5, Issue 1, 2018 · pp. 35–43 Read article
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Emote_X: An AI-Driven Framework for Real-Time Twitter Sentiment Classification Using Machine Learning
Abstract: Social media has become one of the ways people share their thoughts, feelings and responses to what is happening in the world. Twitter, which is now called X is an example. It creates a constant flow of short messages. These messages contain clues about how people feel in areas like business, health care, politics, entertainment and when there is a disaster. Tweets are very messy. They have abbreviations, hashtags, emojis, …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 3, 2026 Read article
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The Impacts of Fluoride Contamination in Groundwater on Public Health in India: Evidence from Skeletal Diseases and Dental Diseases
Abstract: Abstract The objective of this paper is to examine the potential effects of fluoride exposure by analyzing the influence of fluoride contamination in drinking water on health outcomes across various districts of India. The paper will mainly highlight two health outcomes- dental diseases and skeletal diseases. This study also examine the health impacts associated with fluoride contaminated water across the different considered samples with the inclusion of additional demographic and …
Published in Journal of Water Pollution & Purification Research · Vol. 3, Issue 2, 2016 · pp. 43–60 Read article
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Smart-Waste-Management-System
Abstract: The rapid urbanization and increasing waste generation pose significant challenges to traditional waste management systems, necessitating innovative solutions that integrate economic principles and management strategies. In order to enhance trash transportation and recycling procedures, this paper investigates the deployment of a Smart trash Management System that makes use of Internet of Things (IoT) components and machine learning algorithms. By applying economic principles such as cost-benefit analysis and resource allocation, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 18–27 Read article
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Enhancement in Biomedical Polymer Nanocomposites: Biocompatibility and Mechanical Property Predictions using Machine Learning
Abstract: A machine learning (ML)-based framework is developed and validated through experimental analysis and comparative modeling to enhance system dependability and improve prediction performance. The proposed framework includes key stages such as data preprocessing, feature evaluation, model training, and performance benchmarking to determine the most effective prediction technique. Several machine learning models were evaluated, including Ensemble models, Artificial Neural Networks (ANN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 275–296 Read article