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182 articles for “ML algorithms”
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An Experimental Approach of Machine Learning Algorithms to Detect Botnet DDoS Attacks
Abstract: Botnets are one of the threats in a network to hamper the quality of the network by disrupting theresources of the network. These Botnets can be controlled remotely by Botmaster. The Machine Learning Algorithms play a major role to detect and control the Botnets that cause to DDoS attacks, malwares and phishing attacks that are vulnerable to network resources. The DDoS attacks are most dangerous malware events that disrupt whole …
Published in Journal Of Network security · Vol. 10, Issue 3, 2022 · pp. 7–14 Read article
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Visual Analytics with Machine Learning for Data-Driven Investigations of Product State Transmission in Production System
Abstract: In recent years, the significance of effectiveness and productivity has grown. Furthermore, the industry has been able to improve production system performance thanks to advances in processing power and advanced analytics. A better understanding of intermediate product stages is therefore required to take the relevant measures. To highlight the importance of this field of study, a study on data-driven probabilistic ML algorithms and their real-time applications to smart energy systems …
Published in Journal of Computer Technology & Applications · Vol. 13, Issue 2, 2022 · pp. 1–7 Read article
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Assessing the Effectiveness of Machine Learning Algorithms in Simulating Malware Detection Processes
Abstract: On the information system comprehends, computer virus attacks play a very important role and, by undermining regionally and globally, are considered one of the most critical threats. The traditional malware detection methods, more varied, being based on signature, are incapable of providing sufficient coverage over malicious programs in a short time. This is due to the speed of evolution and growing complexity of malware variants. This situation, in turn, requires …
Published in Journal of Electronic Design Technology · Vol. 14, Issue 3, 2023 · pp. 11–20 Read article
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A Review on Predicting Wear and Friction of PTFE Composites - Fillers to Machine Learning Models
Abstract: Polytetrafluoroethylene (PTFE) composites, a self-lubricating material with low friction, became an indispensable material in engineering applications where load carrying capacity and wear are crucial. The pure PTFE has poor mechanical strength and wear resistance which can be enhanced by the addition of fillers in appropriate volume fraction. The wear performance is dependent on various factors such as fillers, operating parameters, environmental conditions as well as manufacturing attributes. This makes the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 114–128 Read article
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An Analytical Review of Machine Learning Methodologies
Abstract: Machine Learning (ML) is a dynamic and rapidly developing area of computer science that enables the system to learn from data and improve its performance without clear programs. Rooted in statistical theory and computer algorithms, ML has become a major technology that progresses in artificial intelligence. It strengthens the detection of the recommendations and speech for extensive applications from autonomous vehicles and medical diagnoses. This paper has reviewed the basics …
Published in Recent Trends in Mathematics · Vol. 3, Issue 1, 2026 · pp. 13–21 Read article
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Comparison of Machine Learning Classification Algorithms for Prediction of Early-stage Diabetes
Abstract: Diabetes is the most widespread and gruesome disease spread all around the globe. It is a chronic metabolic disease which has mild symptoms which are hard to spot at the initial stage. It is well known that diabetes causes a high blood sugar level. This is because insulin is not able to carry sugar from your blood into your cells in order to be stored or used for energy as …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 10, Issue 1, 2023 · pp. 1–5 Read article
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Aerodynamic Optimization of UAV Wings Using Machine Learning
Abstract: Unmanned Aerial Vehicles (UAVs) are increasingly deployed across defense, transportation, agriculture, and environmental monitoring, demanding improved aerodynamic efficiency to enhance endurance, stability, and payload capacity. Traditional aerodynamic optimization approaches, relying on computational fluid dynamics (CFD) simulations and wind tunnel experiments, are often time-consuming and computationally expensive. This study proposes a machine learning (ML)-driven framework for the aerodynamic optimization of UAV wing geometries, aiming to significantly reduce design cycles while improving …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 1–7 Read article
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Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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Emerging Paradigms: Leveraging Artificial Intelligence and Machine Learning for Enhanced Wireless Network Security
Abstract: Wireless networks have now become an indispensable component of our contemporary communication infrastructure, offering both connectivity and convenience. Nonetheless, the increasing complexity and constantly evolving nature of wireless networks present substantial security challenges. This work investigates the utilization of artificial intelligence (AI) and machine learning (ML) techniques to tackle these security issues in wireless networks. We delve into the principles and practices of applying AI and ML algorithms to enhance …
Published in Journal Of Network security · Vol. 11, Issue 2, 2023 · pp. 18–25 Read article
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Machine Learning for Finding Materials for Membranes
Abstract: Traditionally, finding and improving membrane materials has depended on trial-and-error experiments, which can take a long time, cost a lot of money, and only cover a small area. Recent improvements in machine learning (ML) have the potential to change the way membrane materials are designed by making it possible to make predictions about performance, selectivity, and stability based on data. ML algorithms can find hidden links between the structure, composition, …
Published in International Journal of Membranes · Vol. 3, Issue 1, 2026 · pp. 1–7 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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A Survey On Leveraging Machine Learning for Phishing Attack Prediction and Detection
Abstract: Phishing is one of the biggest cybersecurity threats that exploits user trust by masquerading as a legitimate site or email to steal personal and sensitive information. A state- of-the-art-phishing detection systems survey, this review showcases the evolution from traditional list-based techniques, including blacklisting and whitelisting to machine learning and deep learning models. While list-based systems cannot evolve to detect new and zero-day attacks, the ML algorithms of Decision Tree, Random …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 3, 2025 · pp. 1–10 Read article
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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
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Smart Bionic Hand: Combining Hardware and AI For Adaptive Prosthetic Functionality
Abstract: This research paper presents the development and integration of a bionic arm that leverages both hardware components and artificial intelligence (AI) models for enhanced functionality and user interaction. The hardware design includes key components such as servo motors, an Arduino UNO microcontroller, electromyography (EMG) sensors, and a lithium-ion battery. The EMG sensors detect muscle signals, which serve as inputs for controlling the arm's movements, while the servo motors are responsible …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 1–7 Read article
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Integrated, Geospatial Risk Assessment of Air, Water, and Soil Pollution Impacts on Agricultural Sustainability using Advanced Digital Technologies
Abstract: The systemic threat posed by the convergence of air, water, and soil contaminants represents a critical challenge to global agricultural resilience and food security. Traditional, site-specific pollutant monitoring methods are insufficient for capturing the dynamic, diffuse, and often nonlinear nature of environmental risk pathways that permeate agrarian landscapes. This study presents a robust framework for comprehensive risk assessment utilizing a synergistic suite of modern tools designed for spatial, temporal, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 28–37 Read article
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Enhancing Mutual Fund Investment Decision-making Using Machine Learning: A Survey
Abstract: In India, a significant portion of individuals save a part of their income for a secure future. Government and various public sector financial companies also provide some saving schemes through banks, post offices, and Life Insurance Corporation (LICs) such as Recurring Deposit (RD), Public Provident Fund (PPF), Sukanya Samridhhi Account (SSA) fixed deposits, etc. Over the past decade, many individuals have shifted their saving schemes to vigorously searching for investment …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 1, 2024 · pp. 43–51 Read article
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Diabetes Prediction Using ML Techniques
Abstract: Diabetes mellitus, commonly referred to as diabetes, denotes a cluster of prevalent endocrine disorders characterized by persistent elevated levels of blood sugar. Diabetes is classified into two main types: type 1 and type 2. Type 1 diabetes arises when the body is unable to produce insulin, while type 2 diabetes involves either insulin resistance or insufficient insulin production. Early detection and intervention are essential to reduce its harmful impacts. The …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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Computational Simulations in Drug Discovery: Modeling Protein Folding and Drug Binding
Abstract: Computational simulations have become essential tools in drug discovery, offering unprecedented insights into molecular behavior at the atomic level. These simulations, particularly in the domains of protein folding and drug binding, allow for the exploration of complex biological systems that are often difficult to study experimentally. Protein folding, a critical aspect of drug discovery, involves the transition of a polypeptide chain from an unfolded to a biologically active structure. Understanding …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 23–29 Read article
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Advances in Medical Robotics: Surgical Automation and Rehabilitation Systems
Abstract: Medical robotics has emerged as a groundbreaking technology, transforming modern healthcare through advancements in surgical automation and rehabilitation systems. Robotic-assisted procedures machine learning (ML), and artificial intelligence (AI) have all been used to improve patient recovery consequences, reduce invasiveness, and increase surgical precision. These developments have redefined traditional medical techniques by opening the door for more effective, precise, and tailored therapies. By improved dexterity, stability, and vision, surgical robots has …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 1, 2025 · pp. 31–38 Read article
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AI and Big Data for Optimized Water Resource Management in Arid Regions
Abstract: Water scarcity in arid regions is an escalating global challenge, driven by climate change, population growth, and increasing demands from urban, industrial, and agricultural sectors. Effective water resource management (WRM) is crucial for sustaining livelihoods, economic stability, and infrastructure resilience. Emerging technologies such as artificial intelligence (AI), machine learning (ML), and big data offer innovative solutions for optimizing water use, enhancing efficiency, and improving sustainability in water-scarce environments. This paper …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 1–5 Read article