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328 articles for “prediction”
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Enhancing Remote Patient Monitoring with Ai-Powered Virtual Assistants
Abstract: Artificial Intelligence (AI) is transforming personalized education by tailoring learning materials to meet the distinct needs, preferences, and progress of individual students. This paper explores how AI technologies—such as machine learning, natural language processing, and adaptive learning systems are improving the effectiveness of personalized learning experiences. Through AI, students benefit from timely feedback, access to intelligent tutoring systems, and data-driven insights that enable educators to enhance their teaching strategies. Additionally, …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 Read article
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IoT-Based Battery Health Monitoring for Electric Vehicles Using Machine Learning
Abstract: With increasing utilization of the Electric Vehicles (EV)s in global scale, battery health management becomes a critical factor which has great impact on vehicle performance, safety and longevity. Battery materials, such as NMC LFP lithium-ion batteries and lithium-ion batteries, degrade over time from charging behaviour, heat stress, discharging voltage profiles and environmental limits. Conventional BMS only offer threshold based health diagnostics and cannot perform accurate degradation prediction. This work presents …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 Read article
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A Structure-based Design Approach to Catharanthus roseus Phytoconstituents as Potential Inhibitors of B-Cell Lymphoma 6 Protein
Abstract: Objectives: Lymphoma is a cancerous disease. It develops into millions of people worldwide. Identify the naturally active compounds from Catharanthus roseus, they have multiple values in the medicinal field of Siddha, and Indian Ayurveda are used as a disease-preventing agent. Drug illness prediction, toxicity prediction, statistical information, molecular docking, as well as absorption, distribution, metabolism, and excretion (ADME) analysis are used to predict the fit ligand as a drug. Methods: …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 1, Issue 2, 2023 · pp. 14–34 Read article
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Performance, Combustion and Emission analysis of Sunflower oil based Biodiesel using Non-Dominated Sorting Genetic Algorithm-II
Abstract: Biodiesel is used as alternate fuel of I. C. Engines for so many years. It is obtained from various edible and non-edible oils including waste cooking oils through trans-esterification process in the presence of catalyst. The suitable amount of biodiesel mix with commercial diesel can be used to run the compression ignition engines. The optimum combination of engine input parameters is the challenging task as required by the design engineer …
Published in International Journal of Energy and Thermal Applications · Vol. 1, Issue 1, 2023 · pp. 1–6 Read article
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AI-driven Flood Surveillance and Dam Control: Advancing Resilience Through Data Science
Abstract: This study presents the development and real-world deployment of an intelligent system for flood monitoring and automated dam gate control using artificial intelligence (AI) and internet of things (IoT) sensors. Supervised machine learning models are developed to predict floods up to 48 h in advance. An automated dam gate operation system is designed to leverage the flood forecasts and real-time stream water levels for emergency control. The complete end-to-end infrastructure …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 2, 2023 · pp. 9–17 Read article
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Precision Medicine for Neurofibromatosis Type 1: Progress and Prospects in Drug Discovery
Abstract: Objective: The development of neurofibromas, café-au-lait spots, and other neurological problems are the hallmarks of neurofibromatosis type 1 (NF1), a hereditary disorder. The dearth of efficacious pharmaceutical therapies underscores the need for novel therapeutic approaches, even in the face of clinical variability. Through very accurate prediction of the binding affinity of possible therapeutic drugs with the target protein, the computational technique known as “molecular docking” has become a potent tool …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 2, Issue 1, 2024 · pp. 01–15 Read article
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InSilico Analysis and Homology Modeling of Tetrahydroprotoberberine Oxide involved in the Berberine Biosynthesis
Abstract: Objective: Berberine, a bioactive compound found in various plant species, exhibits diverse pharmacological properties with potential applications in pharmaceutical research. The biosynthesis of berberine involves several enzymatic steps, with (S)-tetrahydroprotoberberine oxidase playing a pivotal role. This study aimed to elucidate the structural and functional characteristics of (S)-tetrahydroprotoberberine oxidase to better understand its role in berberine biosynthesis and its potential biotechnological applications. Methods: Using bioinformatics tools and computational methods, the physicochemical …
Published in Emerging Trends in Metabolites · Vol. 1, Issue 1, 2024 · pp. 7–26 Read article
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Computational Approaches to Understanding Cellular Signaling Pathways
Abstract: Cellular signaling pathways are fundamental in regulating vital processes, such as cell growth, differentiation, and apoptosis. The intricate and interconnected nature of these signaling networks requires sophisticated methods for their analysis. Computational approaches, including mathematical modeling, network analysis, and machine learning, have revolutionized the way researchers analyze and simulate cellular signaling. This article provides a comprehensive overview of computational strategies employed to model signaling pathways, with a focus on integrating …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 8–13 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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AI For Climate Vulnerability Assessment
Abstract: Climate change is one of the biggest problems we face every day. The main problems are high temperatures, rising sea levels, and changes in weather, which will be worse in the upcoming years. To predict and adapt to these impacts, we need to create data-driven solutions. The main tool for predicting climate change was artificial intelligence, which can also be utilised to predict the weather and alert people of impending …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 1, 2025 · pp. 18–33 Read article
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The Influence of Self-Efficacy on Anxiety and Perfectionism among Dancers
Abstract: The world of dance, while driven by creativity, often imposes significant psychological demands on performers. This study explored how self-efficacy influences anxiety and perfectionism—both adaptive (excellencism) and maladaptive—among dancers, with a focus on gender differences. A sample of 120 dancers (60 males, 60 females) was assessed using standardized scales. Relationships and predictive effects were assessed using statistical techniques, such as regression, Pearson correlation, and t-tests. Findings revealed no significant gender …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 2, 2025 Read article
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Progression of Health and Wellness: Artificial Intelligence (AI) and Deep Learning (DL) for Precision Medicines
Abstract: Deep learning and artificial intelligence in the field of precision medicine is revolutionizing healthcare to make personalized therapeutic approaches desirable based on the unique characteristics of the patient. AI technologies improve diagnostic accuracy by analyzing medical data, spotting patterns and anomalies that human experts may miss. AI-driven models are instrumental in precision medicine, where they can predict patient response to therapies to tailor treatment plans, enhancing outcomes and reducing adverse …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 2, 2025 · pp. 1–5 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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Evaluation of Critical MMAW Welding Defects Using Computer Simulation in Industrial Manufacturing Systems
Abstract: Manufacturing is one of the key sectors of any countries GDP and welding is one of the prime manufacturing processes of the manufacturing sector. Welding has several notable advantages over mechanical joining techniques, including higher structural integrity, design flexibility, and cost and weight lowers. Welded products/structures are subjected to serious issues of residual stresses and distortions. The performance and sturdiness of the welded structures are severely impacted by weld remaining …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 18–26 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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Multi-Layered AI-Driven Security in Wireless Ecosystems
Abstract: The proliferation of next-generation wireless technologies, from 5G/6G networks to the pervasive Internet of Things (IoT), has birthed a hyperconnected digital ecosystem of unprecedented scale and dynamism. This interconnectedness, however, introduces a vast and volatile attack surface, rendering conventional, signature-based security paradigms fundamentally obsolete. This paper posits that the only viable defense is an offensive, self-adaptive one, predicated on the integration of artificial intelligence (AI) directly into the wireless security …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 21–28 Read article
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The Influence of Self-Efficacy on Anxiety and Perfectionism among Dancers
Abstract: The world of dance, though celebrated for its creativity and artistic freedom, often carries considerable psychological demands on performers. Beyond the physical rigor, dancers navigate pressures of performance standards, audience expectations, and internalized goals of perfection. This study examined how self-efficacy—an individual’s belief in their own capability—shapes the experiences of anxiety and perfectionism among dancers, with a particular focus on gender differences. A balanced sample of 120 dancers (60 males …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 37–44 Read article
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Forecasting Climate-Driven Healthcare Demand in Agricultural Regions: A Multi-Modal AI Approach
Abstract: The rapidly increasing instability of world climatic regimes has made past meteorological thresholds irrelevant, especially in the agricultural areas where monetary stability and well-being of humans are closely intertwined with an environmental situation. The more the frequency of 1 in every 1000-year events, i.e., heatwaves and catastrophic flooding increase, the greater the rural healthcare systems are in crisis, i.e., unable to predict a surge in demand because of data scarcity, …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 28–38 Read article
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Fracture Analysis of Functionally Graded Material (FGM) Plates Using Extended Finite Element Method: A Review.
Abstract: Functionally Graded Materials (FGMs), have drawn a lot of interest in various engineering applications due to their superior mechanical properties and ability to withstand extreme conditions. Fracture analysis in FGMs focuses on understanding how cracks initiate and propagate within these complex materials. The stress distribution becomes irregular due to spatial property variations which produces different crack paths than what occurs in homogeneous materials. The examination of FGM plates under fracture …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 4, Issue 1, 2026 · pp. 9–15 Read article
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Explainable Artificial Intelligence in Personalized Medicine: Emerging Clinical Perspectives
Abstract: The convergence of artificial intelligence (AI) and precision medicine has transformed contemporary healthcare by enabling data-driven clinical decision-making, individualized therapeutic interventions, and predictive diagnostics. However, despite remarkable advances in machine learning (ML) and deep learning (DL), the widespread adoption of AI in healthcare remains constrained by the “black-box” nature of many computational systems. Clinicians, regulatory agencies, and patients increasingly demand transparency, interpretability, and trustworthiness in AI-guided medical recommendations. Explainable Artificial …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 13–29 Read article