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349 articles for “Optimized Machine Learning”
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Role of Quantum Chemistry in Catalysis: A Comprehensive Review
Abstract: Catalysis plays a crucial role in modern chemical manufacturing, energy conversion, and environmental protection by enabling chemical reactions to occur more rapidly, selectively, and with reduced energy consumption. A fundamental understanding of catalytic processes at the atomic and electronic levels is essential for the rational design and optimization of catalysts. Quantum chemistry has emerged as a powerful theoretical and computational framework that enables detailed investigation of electronic structure, reaction energetics, …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 1, 2026 · pp. 01–16 Read article
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A Lightweight Cost-Sensitive Explainable Ensemble Framework for Early Heart Disease Risk Prediction
Abstract: Cardiovascular disease is still one of the leading causes of death, and hence, the early prediction of risk is a very important task in preventive medicine. Although recent studies have shown encouraging results in the application of machine learning algorithms to the prediction of heart disease, it has been noticed that most of the algorithms are more concerned with accuracy-driven optimization than the concerns of safety and false negatives. In …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 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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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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Dynamic Performance Enhancement of Polymer Composites through Metaheuristic machinining optimization
Abstract: This work aims to provide an optimization of meta-heuristic algorithms in order to improve the dynamic behavior of composite materials utilized in various practical engineering tasks. Based on the Comprehensive literature review it has been observed that composite sandwich panels with PVC foam cores accomplished mechanical characteristics superior than those ones that were produced on PU foam core mainly in flexural, compression, and impact tests Thus the study establishes the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 114–129 Read article
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Optimizing Airline Efficiency Using Big Data and Predictive Analytics
Abstract: Recent technological advancements have resulted in the generation of vast volumes of data across industries, including the airline sector, supporting operational control and service quality. Big Data Analytics (BDA) enables organizations to analyze large and complex datasets to derive actionable insights that support informed decision – making and superior operational performance. This review paper systematically analyzes twenty relevant research studies to explore the application of Big Data Analytics (BDA) within …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 1, 2026 Read article
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Advanced Water Purification Techniques for Sustainable Clean Water Management: A Comprehensive Review
Abstract: The growing global demand for safe drinking water, coupled with increasing pollution from industrialization, urbanization, and agricultural activities, has intensified the need for efficient and sustainable water purification technologies. Conventional water treatment processes often fail to remove emerging contaminants such as pharmaceuticals, microplastics, endocrine-disrupting compounds, and heavy metals. Advanced water purification technologies—including membrane filtration, advanced oxidation processes (AOPs), nanotechnology-based adsorbents, photocatalysis, electrochemical treatment, and bio-inspired purification systems—have emerged as promising …
Published in Journal of Water Pollution & Purification Research · Vol. 13, Issue 1, 2026 · pp. 47–52 Read article
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Real-Time Cab Fare and ETA Prediction Using API Integration
Abstract: The exponential proliferation of ride-hailing platforms has necessitated the formulation of sophisticated and highly responsive predictive models for cab fare estimation and estimated time of arrival (ETA) computation. This work elucidates a robust framework leveraging real-time application programming interface (API) integration from Uber and Ola within a Flutter-based ecosystem to enhance predictive analytics. By assimilating real-time geospatial data, dynamic pricing algorithms, and latency-optimized API responses, this study investigates the empirical …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 08–15 Read article
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Tribological Performance and Wear Coefficient Prediction of AA2024–TiC Composites via Python-Based Machine Learning
Abstract: Determining wear coefficient accurately serves as a critical factor to maximize engineering materials' tribological characteristics. The experiment examines the wear characteristics of TiC-reinforced AA2024 aluminum alloy subjected to different tribological operating conditions. A pin-on-disc tribometer performed wear tests under different conditions of load and TiC weight fraction and sliding speed and duration. ANOVA statistical results show that load intensity and TiC reinforcement density stand out as principal variables that affect …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 1099–1112 Read article
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Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article
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Revolutionizing Wireless Communication: AI & ; ML in the Era of 6G
Abstract: With rapid technological advancement, sophisticated techniques are significantly enhancing the performance of wireless networks. In parallel, the growth of artificial intelligence (AI) has empowered systems to perform intelligent decision-making, automate processes, analyze data, generate insights, and predict future outcomes. AI systems are now capable of learning and adapting to dynamic environments. Particularly, machine learning and deep learning techniques have achieved remarkable success across a wide range of applications in recent …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 3, 2025 · pp. 29–36 Read article
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Optimizing Urban Mobility with AI-Based Traffic Management
Abstract: Urban mobility is a pressing concern in modern cities, plagued by issues like traffic congestion and pollution. This research involves, "Optimising Urban Mobility with AI-based Traffic Management", delves into the potential of Artificial Intelligence (AI) to revolutionize traffic management. Focusing on AI algorithms, data analytics, and sensor technologies, the research aims to enhance traffic flow, reduce congestion, and improve overall efficiency. Through statistical analysis and simulations, the research evaluates the …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 34–43 Read article
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Cutting-Edge Developments and Innovations in Amazon Web Services (AWS)
Abstract: In 2025, Amazon Web Services (AWS) continues to dominate the cloud computing industry through groundbreaking innovations in artificial intelligence (AI), strategic partnerships, data center advancements, and expansion into new markets. These initiatives help AWS maintain its position as a top provider of secure, scalable, and efficient cloud services, adapting to the ever-changing demands of businesses across the globe. One of AWS’s most significant advancements is its AI-driven cloud services, which …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 01–08 Read article
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Magnetic and Radioactive Nanoparticles for Improved Theranostics and AI Assisted Radiation Therapy
Abstract: Nanoparticles based therapeutic and theranostics technique is becoming an active area of research in nanomedicine. The sensitivity, biocompatibility, and stability of magnetic and radioactive nanoparticles determine their functionality. This research highlights the impacts of magnetic and radioactive nanoparticles on therapeutic techniques namely, cell therapy, gene therapy, and tissue regeneration. Then, it is intended to brief a principal role of these therapeutic techniques to envisage theranostics medicine and radiation therapy using …
Published in International Journal of Advance in Molecular Engineering · Vol. 3, Issue 2, 2025 · pp. 10–21 Read article
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The Future of Electronic Communication Systems in the Digital Age
Abstract: Electronic communication networks underpin modern society, offering seamless interaction across geographical, social, and economic borders. These systems are transforming into faster, more reliable, and smarter ones as digital technologies improve. This article discusses the future of Electronic Communication Systems in the context of 5G Technology, IoT, AI, and Quantum Communication. These technologies should revolutionise data transfer by increasing capacity, lowering latency, and enabling real-time communication across platforms. Due to need …
Published in Recent Trends in Electronics Communication Systems · Vol. 13, Issue 1, 2026 Read article
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Green AI-Enabled Opto-Electronic Communication Systems for Carbon-Neutral Digital Networks
Abstract: The rapid expansion of digital communication infrastructure, driven by cloud computing, Internet of Things (IoT), 6G networks, and artificial intelligence applications, has significantly increased the energy consumption and carbon footprint of modern communication systems. Conventional optical communication networks often rely on static resource allocation and energy-intensive signal processing mechanisms, resulting in inefficient utilization of network resources and elevated operational costs. This study proposes a Green Artificial Intelligence (Green AI)-Enabled Opto-Electronic …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 2, 2026 Read article
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Reinforcement Learning for Adaptive Sensing with Shape Memory Polymer-Based IoT Nodes
Abstract: The rapid expansion of intelligent sensing in the Internet of Things (IoT) has revealed the pressing need for materials and algorithms capable of self-adaptation in volatile environments. Conventional polymer-based sensors and static control strategies often fail to capture nonlinear thermo-mechanical dynamics, leaving them unsuitable for unpredictable operating conditions. Although prior studies have improved polymer composites or introduced algorithmic optimization independently, few attempts have coupled the adaptability of smart materials with …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 370–391 Read article
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Smart Agriculture: IoT-Based Automation and Monitoring for Enhanced Farming Efficiency
Abstract: This paper presents the development of an innovative agriculture automation and monitoring system designed to improve farming efficiency through the integration of low-cost sensors and microcontrollers. The system utilizes components such as PIR motion sensors, soil moisture sensors, DHT11 humidity sensors, and a relay motor pump for precise automation of irrigation and environmental monitoring. NodeMCU (ESP8266) acts as the primary controller, facilitating real-time data gathering and decision-making. Results show significant …
Published in International Journal of Electronics Automation · Vol. 3, Issue 1, 2025 · pp. 1–11 Read article
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Integrative Machine Learning Approaches for Predicting the Rheological Behaviour of Soft Magnetorheological Elastomers
Abstract: Magnetorheological Elastomers (MREs) are advanced composite materials known for their ability to alter mechanical properties under external magnetic fields, making them highly valuable in adaptive damping systems, vibration control, and smart devices. The accurate prediction of rheological behavior in soft MREs remains a significant challenge due to the complex interplay between material composition and magnetic fields. To address this challenge, this study employs a multi-pronged approach that integrates traditional material …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1083–1096 Read article
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Data-driven Approaches to Mineral Resource Management Using AI: A Brief Review
Abstract: The role of Artificial Intelligence (AI) in the mineral resource sector has become increasingly significant over the past few years, as industries seek to optimize and modernize their operations. AI encompasses a variety of technologies and techniques, such as machine learning, deep learning, and expert systems, that are now widely used in mineral exploration, resource estimation, and mine management. These AI-driven approaches have brought about a transformative shift, enhancing efficiency, …
Published in International Journal of Minerals · Vol. 2, Issue 1, 2025 · pp. 25–29 Read article