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81 articles for “Integrated modeling”
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Oceanmind Systems: AI-Driven Marine Life Intelligence for Climate Prediction and Ocean Ecosystem Stability
Abstract: Oceans regulate global climate systems, support biodiversity, and serve as critical carbon sinks, yet they remain under-monitored relative to their ecological importance. Traditional oceanographic methods rely heavily on satellite sensing, buoy networks, and periodic marine surveys, which often fail to capture real-time biological dynamics at micro-ecosystem levels. This paper introduces OceanMind Systems, an artificial intelligence (AI)-driven marine intelligence framework that integrates marine life behavior, oceanographic data, and computational modeling to …
Published in International Journal of Marine Life · Vol. 3, Issue 2, 2026 Read article
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Open Educational Resources and Open Access Publishing in Higher Education: Policies, Challenges, and Collaborative Models
Abstract: Open Educational Resources (OER) and Open Access (OA) publishing are transforming higher education by promoting equitable access to knowledge, reducing costs, and fostering collaborative innovation. While OER focus on openly licensed teaching and learning materials, OA ensures unrestricted online access to scholarly research. Together, they form an integrated open knowledge ecosystem aligned with global policy frameworks such as the UNESCO OER Recommendation (2019) and the Budapest Open Access Initiative. This …
Published in International Journal of Trends in Humanities · Vol. 3, Issue 1, 2026 · pp. 7–12 Read article
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The Effect of Rare Earth (RE) Metal Doping of Zno, On Magnetic and Optical Properties of Zno Crystals Structure
Abstract: The magnetic and optical properties of magnetic semiconductors relays on the crystal structure, type and amount of dopant ions, and particle size. Then, the effect of rare earth metal (Dy, Eu, and La) doping on crystal structures, magnetic properties and optical properties are seen. It is revealed that the optical band gap of ZnO decrease down from 3.37eV up on doping with RE metals. Then, the Hamiltonian of the system …
Published in International Journal of Crystalline Materials · Vol. 2, Issue 2, 2025 · pp. 28–40 Read article
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Understanding the Capabilities of ChatGPT for Learning and AI-Powered Assessment
Abstract: This paper investigates the integration of ChatGPT, a generative AI language model developed by OpenAI, into modern educational environments with a focus on its role in learning and assessment. ChatGPT’s ability to understand and generate human- like responses positions it as a powerful tool for enhancing personalized learning experiences, supporting students through interactive tutoring, and assisting educators in administrative and academic tasks such as content creation and automated grading. The …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 101–107 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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Zebra Fish Embryo Assay: A Wonderful Tool for Ecotoxicological Risk Assessment with Special Reference to Heavy Metals - An Overview
Abstract: In recent years, environmental pollution has become a pressing concern, prompting extensive research in aquatic ecotoxicology. With environmental degradation getting worse day by day, ecotoxicology research has gained a lot of attention. This area of study examines how biological communities in aquatic environments are affected by environmental contaminants. To unravel the toxicological mechanisms of these exogenous compounds, scientists turn to biological models. Several aquatic species, including zebrafish, toads, and big …
Published in International Journal of Toxins and Toxics · Vol. 2, Issue 2, 2025 · pp. 56–70 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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Evaluating an ai-supported experiential learning intervention: a quasi-experimental study of the joyful saturday model for student engagement and holistic development
Abstract: Student disengagement, declining academic motivation, and passive classroom participation remain major challenges in modern higher education systems. Traditional lecture-based teaching methods often fail to accommodate diverse learning styles and do not sufficiently promote active participation or collaborative learning. To address these challenges, the present study evaluates the effectiveness of Joyful Saturday, a structured experiential learning initiative designed to improve student engagement, motivation, and holistic development through interactive academic activities supported …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 79–88 Read article
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A study on IoT and AI for Predictive Modeling and Control of Infectious Disease Transmission
Abstract: Background: The global response to novel and recurring infectious diseases is frequently hindered by surveillance systems that are slow, siloed, and reactive. Traditional epidemiology relies on retrospective analysis of clinical reports, often missing the critical early phase of autocatalytic spread. The urgency of modern public health necessitates a shift toward real-time, predictive intelligence. Methods: This study investigates the development and deployment of a synergistic paradigm integrating the Internet of Things …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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A Conceptual Framework for AI-Integrated Metabolomics in Predictive Health Systems for Resource-Constrained Environments
Abstract: The increasing prevalence of non-communicable diseases (NCDs) continues to place a significant strain on healthcare systems, particularly in low- and middle-income regions where access to early diagnostic infrastructure is limited. Conventional healthcare approaches remain largely reactive, often detecting diseases at advanced stages when treatment effectiveness is reduced. This challenge underscores the need for predictive, cost-effective, and data-driven healthcare solutions. This study presents a conceptual framework that integrates metabolomics with artificial …
Published in Emerging Trends in Metabolites · Vol. 3, Issue 2, 2026 Read article
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Personalized Nutrition and Exercise: Pioneering the Path to Precision Medicine
Abstract: Preventive healthcare is about to undergo a major shift thanks to the personalised exercise and nutrition paradigm, which is based on precision medicine concepts. In order to create tailored recommendations for improving health outcomes and preventing chronic diseases, this article explores the integration of genetic profiling, metabolic evaluation, and lifestyle factors. A person's response to food and exercise depends heavily on genetic and metabolic variances, which emphasises the need of …
Published in Emerging Trends in Personalized Medicines · Vol. 1, Issue 2, 2024 · pp. 42–46 Read article
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AI and ML-Driven Immersive Technologies: A New Era in Education
Abstract: The very fast adoption of Artificial Intelligence (AI) and Machine Learning (ML) in education has transformed contemporary teaching and learning ecosystems driven by advances in immersive technologies and the growing engagement of global technology leaders with virtual environments. AI-powered educational platforms enable adaptive and personalized learning pathways by dynamically adjusting content, pace and instructional strategies to learners’ preferences, abilities and learning styles by improving engagement, retention and academic outcomes. Deep …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 116–123 Read article
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Performance Forecasting in Solo Sports: Leveraging Psychometrics, Economic Analysis, and Cultural Insights for Predictive Excellence
Abstract: The science of performance forecasting in solo sports has transcended traditional metrics, embracing a multidisciplinary approach. This paper explores the integration of psychometrics, economic analysis, and cultural insights to predict athletic success. By leveraging psychological profiling, economic factors, and cultural dynamics, this study aims to establish a comprehensive model for forecasting athlete performance with heightened accuracy. In the realm of solo sports, where individual prowess dictates success, traditional performance forecasting …
Published in Recent Trends in Sports · Vol. 1, Issue 1, 2024 · pp. 35–44 Read article
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Agentic AI: Architectures, Types, Capabilities, Mathematical Equations and Governance in the Era of Autonomous Intelligence
Abstract: Agentic Artificial Intelligence (Agentic AI) represents a major advancement in the evolution of intelligent systems by enabling autonomous planning, decision-making, and action execution. Unlike traditional AI models, which are primarily reactive and designed to respond to predefined inputs, Agentic AI systems possess capabilities such as memory, reasoning, goal-oriented planning, tool integration, and dynamic adaptation to changing environments. These characteristics allow them to perform complex, multi-step tasks with minimal human intervention, …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 Read article
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A GIS and MCDA Framework for Land Suitability Analysis in Sustainable Agriculture
Abstract: This study examines land suitability for sustainable agriculture by integrating Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA) as tools to optimize agricultural planning. Sustainable agricultural practices are increasingly critical to meet global food demands without depleting essential land resources. This research focuses on assessing specific parameters that determine the agricultural viability of land, including soil characteristics, topography, climatic conditions, and water availability. These criteria are integral to understanding …
Published in International Journal of Land · Vol. 1, Issue 2, 2024 · pp. 30–34 Read article
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Artificial Intelligence in Entomology: Global Advances, Applications, and Future Directions in Insect Research and Pest Management
Abstract: Artificial Intelligence (AI) is transforming entomology by enabling scalable, data-driven approaches to insect identification, ecological monitoring, and sustainable pest management. This review synthesizes recent global advances in AI applications across taxonomy, behavioral ecology, predictive modeling, and precision agriculture. Machine learning and deep learning techniques—including convolutional neural networks, acoustic classification models, and ensemble predictive algorithms—have demonstrated high classification accuracies (often exceeding 90% under controlled conditions) and improved early detection of pest …
Published in International Journal of Insects · Vol. 3, Issue 1, 2025 · pp. 29–40 Read article
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The Rise of Fractional Calculus: Novel Applications in Engineering and Biological Systems
Abstract: Fractional calculus (FC) is an advanced mathematical framework that generalizes the classical concepts of differentiation and integration to non-integer, or fractional, orders. This extension of traditional calculus allows for the modeling of complex dynamic systems that exhibit behavior not easily captured by integer-order differential equations. Over the last few decades, fractional calculus has seen a rapid rise in popularity, particularly in applied mathematics, engineering, and biological sciences, due to its …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 7–11 Read article
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A Review of Drug Design Techniques Assisted by Computers to Combat Diabetes
Abstract: Diabetes mellitus is a global health concern characterized by chronic hyperglycemia and associated complications. The creation of innovative medicines with enhanced efficacy and safety profiles continues to be a top focus, notwithstanding improvements in treatment. A useful method in drug development, computer-aided drug design (CADD) makes it easier to identify possible therapeutic candidates and optimise lead molecules. An extensive synopsis of CADD tactics used in the fight against diabetes is …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 1, 2025 · pp. 1–10 Read article
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Revolutionizing Petrology and Mineralogy: The Study of AI and Advanced Sensor Technologies
Abstract: Petrology and mineralogy are fundamental to understanding Earth's intricate processes, from crustal evolution to economic resource formation. However, traditional methods, while precise, are often laborious, time-consuming, and occasionally subject to interpretive bias. This abstract explores the transformative potential of integrating cutting-edge Artificial Intelligence (AI) and advanced sensor technologies to revolutionize data acquisition, analysis, and interpretation in these critical geosciences. Advanced sensor technologies, including high-resolution spectral imaging (hyperspectral, Raman), automated X-ray …
Published in International Journal of Minerals · Vol. 2, Issue 2, 2025 · pp. 1–11 Read article
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Emerging Trends in Membrane-Based Gas Separation Technologies
Abstract: Membrane technology has emerged as a groundbreaking solution in various fields, revolutionizing industries such as water treatment, energy production, biomedicine, and environmental protection. Over the past few decades, significant advancements have been made in membrane materials, fabrication techniques, and performance optimization. With the growing global demand for efficient and sustainable separation processes, research has increasingly focused on enhancing membrane permeability, selectivity, and durability to improve performance across various industries, including …
Published in International Journal of Membranes · Vol. 2, Issue 1, 2025 · pp. 16–22 Read article