Search
662 articles for “machine learning method”
-
Machine Learning–Assisted Design of High-Performance Biomedical Polymer Composites
Abstract: The high-performance biomedical polymer composite design needs to represent a trade-off between the strength, biocompatibility, and degradation that cannot be accomplished using conventional design methods. The study aims to develop a predictive and optimization framework of composite properties with the help of machine learning. The methods include ANN, SVM, Random Forest, and Gradient Boosting with experiment and simulation data. The results of Gradient Boosting show that the accuracy is 95.9 …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
Modern Computer-aided Drug Design Methods: A Review
Abstract: Computer-aided drug design (CADD) has emerged as a crucial tool in the drug discovery process, offering a time-efficient and cost-effective approach to identifying potential drug candidates. This review aims to provide an overview of modern CADD methods, including high-throughput screening (HTS), structure-based drug design (SBDD), ligand-based drug design (LBDD), structure-based virtual screening (SBVS), and ligand-based virtual screening (LBVS). We discuss the basic principles, applicability, and limitations of each method, highlighting …
Published in Research and Reviews: A Journal of Dentistry · Vol. 15, Issue 2, 2024 · pp. 14–20 Read article
-
Renewable Solar Energy Prediction in India : 2025-2030
Abstract: As India endeavors to realize its objective of achieving 500 GW of renewable energy capacity by the year 2030, the precise forecasting of solar power generation is rendered increasingly essential. This scholarly article conducts a comprehensive review of the utilization of machine learning (ML) methodologies in the prediction of solar energy across diverse Indian states, underscoring their potential to address the complexities associated with the variability of solar irradiance. Conventional …
Published in Journal of Power Electronics and Power Systems · Vol. 14, Issue 3, 2024 · pp. 41–46 Read article
-
Federated Learning: A Comprehensive Review of Models, Algorithms, and Business Applications
Abstract: In an age where data privacy is a significant concern, federated learning (FL) has become a game-changing method in machine learning. This decentralized model enables various parties to work together on training models without exchanging their raw data, effectively tackling the issues posed by data silos and privacy regulations. This article explores the current state of FL, including its underlying models and algorithms, practical applications, benefits, challenges, and future directions. …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 1–9 Read article
-
A Review: Identification of Credit Card Fraud Using Machine Learning and Anomaly Detection Approach’s on Imbalanced Data
Abstract: Credit cards are among the most widely used payment methods in today's culture, and online purchases have become quite popular. Credit card fraud has emerged as a problem in this industry as a direct result of its popularity. The issue of credit card fraud is becoming a global problem. Credit card fraud has increased due to the widespread use of these payment methods. Thanks to credit card use, e-commerce has …
Published in Recent Trends in Programming languages · Vol. 10, Issue 3, 2023 · pp. 27–40 Read article
-
A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression
Abstract: Early diagnosis of genetic diseases is crucial for effective treatment, especially in the case of Leukemia, a type of blood cancer characterized by abnormal proliferation of white blood cells. This paper presents a systematic review of recent computational techniques for the detection and classification of Leukemia using gene expression data obtained from DNA microarray analysis. The study explores diverse methodologies including machine learning (ML), deep learning (DL), and bio-inspired algorithms …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 2, 2025 Read article
-
Comparison and Analysis of Facial Emotion Detection Using Various Deep Learning Neural Networks
Abstract: Facial emotion recognition employs Convolutional Neural Networks (CNNs), Residual Networks (ResNet), Long Short-Term Memory (LSTM) networks, and Deep Neural Networks (DNNs) to automatically identify various emotions, including disgust, anger, fear, happiness, sadness, surprise, and neutrality. This study utilizes transfer learning along with data preprocessing techniques such as rotation, flipping, brightness adjustment, and enhancement methods. Traditional machine learning models achieve an accuracy range of 45 to 50%. In contrast, our proposed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 37–42 Read article
-
A Machine Learning-based Analysis of Climate Change
Abstract: Climatic variations are a pressing global challenge that demands immediate and comprehensive attention. A wealth of articles has been published on climate change mitigation and adaptation, yet there remains a need for innovative methods to explore the complexities of climatic variations and to devise more efficient and effective strategies for adjustment and alleviation. With technological advancements, machine learning (ML) and deep learning (DL) approaches have derived significant popularity across various …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 1–10 Read article
-
Customer Churn Prediction in Life Insurance
Abstract: In order to forecast customer churn and keep consumers, life insurance firms frequently struggle to use their data efficiently. New opportunities have emerged for tackling this problem due to advancements in categorization models within the field of machine learning. In this study, we suggest an innovative method that uses machine learning classification models to forecast client churn and boost customer retention rates in the life insurance sector. Our proposed system …
Published in E-Commerce for Future & Trends · Vol. 10, Issue 1, 2023 · pp. 23–34 Read article
-
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
-
Vehicle Insurance Fraud Detection Using Supervised Neural Network Model
Abstract: Vehicle insurance fraud is a serious problem that causes huge financial losses to insurance companies. In recent years, developing fraud detection models using machine-learning techniques has been of great interest. This study proposes a novel approach for vehicle insurance fraud detection using Supervised Neural network model on the Kaggle Vehicle Insurance Fraud Detection dataset. The initial step in this study involves performing data pre-processing and feature extraction on the dataset, …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 10, Issue 1, 2023 · pp. 32–39 Read article
-
Use of Intelligent Control Systems to Manage Traffic Effectively and Productively
Abstract: Intelligent control system is the advanced technology in which the collected data is provided to A.I. and with the help ofvarious methods like machine learning, neural networks, Bayesian probability, fuzzy logic the solution to a particularproblem is found.In a country’s growth the traffic management plays a great role as the maximum industries depends on the highways orroads and when it is well planned it can reduce the commute time and …
Published in Trends in Mechanical Engineering & Technology · Vol. 13, Issue 1, 2023 · pp. 22–27 Read article
-
Machine Learning Techniques Utilised for Autism Spectrum Disorder Detection
Abstract: A neurological developmental illness called autism spectrum disorder impacts a person’s ability to connect, communicate, and learn. Autism spectrum disorder influences individuals in distinct ways, as do the severity and its manifestations. Often, this illness is diagnosed in individuals between the ages of 1 and 5 years, and the symptoms include unique behaviours, interests, and potential social difficulties. In order tTo lessen the rise in instances of autism, it must …
Published in Journal of Control & Instrumentation · Vol. 14, Issue 1, 2023 · pp. 32–37 Read article
-
Counter Terrorism Prediction and Risk Evaluation (C-TRIP)
Abstract: The global landscape in the 21st century is marked by complex and evolving security challenges, none more pressing than the threat of terrorism. Acts of terror have left a profound impact on societies, economies, and governments worldwide, underscoring the critical importance of effective counter terrorism strategies. The “Counter Terrorism Prediction and Risk Evaluation (C-TRIP)” represents a significant stride in addressing this ever-pressing challenge. In a time marked by global security …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 2, 2024 · pp. 14–24 Read article
-
Sentiment Analysis of X (Formerly Twitter) Using Machine Learning
Abstract: Sentiment analysis is a methodology to determine the nature and behavior of each and every user for the content posted on the social media platform in the form of post and feed. Consumers of the online platform are encouraged to post reviews of the product that they purchase. Little attempt is created by Amazon to confine or limit the content of these reviews. The number of reviews for various merchandise …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 11, Issue 2, 2024 · pp. 28–37 Read article
-
Epidemiology and transmission of infectious diseases study using Machine learning
Abstract: Infectious diseases remain a formidable global health challenge, characterized by rapid evolution and complex transmission dynamics that often outpace traditional epidemiological surveillance and response mechanisms. This study investigates the transformative potential of machine learning (ML) methodologies to enhance our understanding and prediction of infectious disease epidemiology and transmission. Leveraging diverse datasets—including clinical records, genomic sequences, environmental factors, social mobility data, and real-time digital footprints—we studies and presented various ML models …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
-
Artificial Intelligence for Tracking Cognitive Deviation in Aging Populations: A Comprehensive Review of Techniques, Challenges, and Ethical Concerns
Abstract: Population aging is accelerating worldwide, and with it the burden of cognitive health conditions such as mild cognitive impairment (MCI), Alzheimer’s disease (AD), and dementia. Detecting and monitoring cognitive change early is central to timely intervention, yet conventional diagnostic tools often miss the subtle signals that appear before overt symptoms. Artificial intelligence (AI) has emerged as a promising complement to clinical assessment because it can work through high-dimensional data and …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 27–37 Read article
-
Analyzing the Role of Fiber Composition in Drying Behavior: A Comparative and Predictive Approach
Abstract: This research presents a comprehensive analysis of the drying behavior and thermal response of three distinct fabric types: 100% Cotton, 100% Polyester, and a Polyester blend (65/35), under meticulously controlled environmental conditions. The Polyester blend (65/35) consists of 65% Polyester and 35% Cotton, combining characteristics of both fibers. The investigation focuses on understanding how fiber composition impacts drying time, moisture retention, and thermal characteristics. Experimental trials were conducted using standardized …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 1–11 Read article
-
A Review of Blocking Side-Channel Threats in Parallel Cloud Systems
Abstract: Side-channel attacks (SCAs) pose a critical security threat to parallel computing systems, particularly in shared cloud environments where multi-tenancy and resource contention create exploitable vulnerabilities. This study presents a comprehensive review of SCAs in parallel architectures, analyzing attack vectors such as cache-based exploits (e.g., Prime + Probe, Flush + Reload), timing attacks, power analysis, and network-based covert channels. We examine real-world cases including Spectre and Meltdown vulnerabilities that exposed fundamental …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 15–25 Read article
-
Looking into how modern technology combines sensors and Artificial Intelligence
Abstract: The combination of sensors and Artificial Intelligence (AI) is changing modern technology by making it possible to collect, analyse, and make decisions based on data in real time. Sensors are the main link between the real and digital worlds. They collect several types of data, like temperature, motion, pressure, and visual information. When used with AI methods like machine learning and deep learning, this data may be processed in a …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 1, 2026 · pp. 14–26 Read article