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74 articles for “ML”
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Visualizing Complexity: Navigating Algorithms with Algorithm Visualizer
Abstract: We think that studying algorithms may be amusing and exciting. Many students are currently struggling, but we hope to change that. Our strategy is to emulate gaming while learning. We're building hands-on learning exercises, such as mazes and patterns, to convey key concept. To help students understand how algorithms function in practice, we also use some stunning visualizations. Three major categories of algorithms are under our purview: sorting, pathfinding, CPU …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 1, 2024 · pp. 21–26 Read article
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Data-Driven Predictive Analytics and Decision- Making in FinTech Using MongoDB and High-Throughput Data Pipelines
Abstract: This paper examines the implementation of MongoDB and high-throughput data pipelines within the financial technology (FinTech) sector to drive data-informed predictive analytics and decision-making. The study focuses on the architectural components, scalability, and challenges of integrating NoSQL databases into real-time data ingestion and analytics pipelines. The transformative potential of these technologies in modern financial systems is highlighted through practical use cases such as fraud detection, credit scoring, and personalized financial …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 1–15 Read article
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AI-Powered Defense: Advancing Cybersecurity Through Artificial Intelligence Innovations
Abstract: In the current landscape of escalating cyber threats and increasingly sophisticated attack vectors, integrating artificial intelligence (AI) within cybersecurity strategies has become a critical step forward. This study explores the role of AI in strengthening cybersecurity by utilizing its strengths in data analysis, pattern recognition, and predictive modeling. Through AI, organizations can greatly enhance their ability to detect and respond to threats. Machine learning algorithms enable ongoing adaptation to new …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 1, 2026 · pp. 35–41 Read article
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Sustainable Waste Management Using AI and Robotics
Abstract: The fast increment in squander era around the world has driven to noteworthy natural and open wellbeing concerns. Conventional squander administration strategies, which depend intensely on manual labor and obsolete forms, are battling to keep up with the developing volume, driving to wasteful aspects and environmental harm. AI and Mechanical autonomy give inventive arrangements by improving effectiveness in squander collection, sorting, reusing, and transfer. AI-driven squander sorting frameworks optimize exactness, …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 2, 2025 · pp. 42–48 Read article
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A Systematic Review on The Role of Artificial Intelligence in Assisted Reproductive Technology
Abstract: Artificial Intelligence (AI) has significantly transformed Assisted Reproductive Technology (ART) over the past five years, enhancing diagnostic accuracy, treatment personalization, and overall success rates. AI-driven algorithms and machine learning models have been integrated into various aspects of ART, including sperm selection, embryo grading, and predicting implantation success. Deep learning techniques have improved image-based embryo assessment, reduced human subjectivity and increased efficiency. Additionally, AI-powered predictive analytics have helped optimize ovarian stimulation …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 Read article
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Strategy for Improving Software Maintenance Using Machine Learning for Security Requirements: A Review
Abstract: Within the area of software technical education, the significance of software defect discovery has increased as a research focus to enhance program reliability. By maximizing testing resources and assisting developers in identifying potential problems using program defect predictions, program dependability is increased. Applying software engineering (SE) techniques to critical and intricate systems, like networking and security systems, is imperative. Traditional methods of predicting software maintainability have limitations, particularly in balancing …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 2, 2024 · pp. 36–48 Read article
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AI for Cybersecurity: Deploying Machine Learning for Network Traffic Anomaly Detection
Abstract: The growing sophistication of cyberattacks and the growth of network traffic necessitate sophisticated anomaly detection methods. This study overviews the use of artificial intelligence (AI) and machine learning (ML) to counter these challenges, as noted in current studies. It analyses supervised learning (SVM, Decision Trees), unsupervised learning (K-means, DBSCAN), and deep learning (CNNs, RNNs, Auto-encoders) approaches, considering their strengths and weaknesses. The research integrates current developments in AI/ML-based network anomaly …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article
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Enhancing LAN Security Using Machine Learning
Abstract: The modern Local Area Network (LAN) is a critical component of any organization's infrastructure, facilitating communication, resource sharing, and access to the wider internet. However, this connectivity also brings inherent security risks. Traditional security measures, relying on signature-based detection and rule-based systems, are increasingly struggling to keep pace with the evolving sophistication of cyberattacks. This is where Machine Learning (ML) offers a powerful alternative, enabling proactive threat detection and enhanced …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 07–16 Read article
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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
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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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Quality of Sleep Among Patients with Chronic Renal Failure
Abstract: Renal failure is the partial or complete impairment of kidney function. Inability to eliminate metabolic waste products and water, along with functional disruptions in all bodily systems, result in the condition known as renal failure. Renal failure can be categorized as either acute or chronic. Chronic renal failure refers to the gradual and irreversible deterioration of the nephrons in both kidneys. It is characterized by either kidney damage or a …
Published in International Journal of Emergency and Trauma Nursing and Practices · Vol. 1, Issue 1, 2023 · pp. 22–28 Read article
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Pharma Tech: Leveraging Software for Drug Development & Clinical Research
Abstract: The pharmaceutical sector is progressively adopting software solutions to enhance the drug development process and optimize clinical research results. Drug development is a time-consuming, expensive, and intricate process that traditionally requires extensive laboratory research, preclinical testing, and several stages of clinical trials. Software tools are revolutionizing these stages by improving efficiency, minimizing errors, and speeding up timelines. During preclinical testing, predictive software tools are used to model toxicological effects and …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 1, 2025 · pp. 11–19 Read article
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A Review of Machine Learning Applications in Web Data Mining
Abstract: The rapid development of Internet technology has resulted in a rapidly changing and intricate digital environment that requires new methods for organizing and evaluating online data. This study examines the use of machine learning (ML) in web data mining, focusing on its ability to extract relevant insights from huge amounts of online data. Web data mining, which is divided into three categories: content mining, structure mining, and use mining, uses …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 39–47 Read article
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Automated Suspicious Activity Detection in Video Surveillance Using Deep Learning: A Review
Abstract: In the current era of advanced security systems, video surveillance plays an essential role in ensuring safety by detecting suspicious activities. With the increase in real-time data, manual monitoring has become impractical, paving the way for automated surveillance systems utilizing machine learning (ML) and artificial intelligence (AI) technologies. This paper explores the integration of ML and AI models, specifically convolutional neural networks (CNNs) and long short-term memory (LSTM) networks, for …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 20–27 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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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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Using Machine Learning to Guess Photochemical Reaction Pathways
Abstract: Photochemical reactions are crucial to many activities in the fields of energy conversion, environmental cleanup, and synthetic chemistry. However, predicting their causes and results effectively is still very hard since they entail excited electronic states, nonadiabatic transitions, and complicated potential energy surfaces. Machine learning (ML) has been a powerful technique to go along with classic quantum chemistry methods in the last few years. It offers better prediction capability and lower …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 3, Issue 2, 2025 · pp. 01–12 Read article
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Bayesian Optimization–Driven Operating Parameter Tuning for Maximizing Methane Yield in Anaerobic Digestion
Abstract: To achieve maximum methane production in an anaerobic digestion (AD) process, a combination of various operational parameters must be tuned nonlinearly in the digestion ecosystem. The conventional trial and error optimization methods are slow, resource consuming, and in most instances, cannot model the intricate parameter interaction in biogas production. The current work introduces a Bayesian Optimization-based model to optimize the set of conditions to maximize the level of methane produced …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–8 Read article
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A Study on “Clean" in Beauty: A Machine LearningApproach to Ingredient Transparency and ConsumerTrust
Abstract: The burgeoning "clean beauty" market, while driven by consumer demand for safer and more sustainable products, is plagued by ambiguous definitions and the pervasive challenge of "greenwashing". This ambiguity hinders informed consumer choices and complicates brand authenticity. This study addresses these complexities by developing a novel machine learning (ML) framework designed to objectively analyze cosmetic ingredient lists, classify products based on their "cleanliness" profile, and identify key ingredient attributes that …
Published in Recent Trends in Cosmetics · Vol. 3, Issue 1, 2026 · pp. 1–12 Read article
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Multilingual Education and Language Policy in a Globalized World: Toward Inclusive and Equitable Learning Systems
Abstract: Multilingual education involves teaching and learning in two or more languages, promoting linguistic diversity and enhancing educational outcomes. It acknowledges learners’ native languages and integrates them with dominant or global languages to foster inclusivity and cognitive development. Multilingual education (MLE) serves as a critical framework for promoting inclusivity and equity within increasingly globalized and culturally diverse classrooms. This paper explores the role of MLE and the influence of language policies …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 64–74 Read article