Search
651 articles for “predictive systems”
-
Exploring AI-Driven Student Performance Analysis as a Dimension of an AI-Powered Assessment and Feedback System: A Comprehensive Review
Abstract: The rapid proliferation of artificial intelligence (AI) in educational technology has heralded a paradigmatic transformation in assessment methodologies, transitioning from static, summative evaluations to dynamic, data-driven systems that emphasize continuous formative feedback. This comprehensive review interrogates AI-driven student performance analysis as a cardinal dimension of AI-powered assessment and feedback systems (AI-PAFS), synthesizing findings from forty-five rigorously curated open-access empirical studies published between 2015 and 2024. Employing a methodological lens, the …
Published in Current Trends in Information Technology · Vol. 16, Issue 1, 2025 · pp. 24–31 Read article
-
Role of W.A.R. Score in Predicting Wound Infection
Abstract: In clinical practice, chronic wounds are a major difficulty that are frequently made worse by the infection risk. However, the lack of precise standards for evaluating the risk of infection and establishing the need for and length of time for systemic antibiotics leads to the overuse and abuse of these drugs, which increases the risk of side effects and the development of antibiotic resistance. To close this gap, the development …
Published in Emerging Trends in Personalized Medicines · Vol. 1, Issue 1, 2024 · pp. 33–38 Read article
-
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
-
Integration of GIS and AI in Urban Planning and Disaster Management
Abstract: The rapid pace of urbanization, combined with the increasing frequency and intensity of natural disasters, necessitates the development of innovative solutions for urban planning and disaster management. Geographic information systems (GIS) and artificial intelligence (AI) have emerged as transformative technologies capable of addressing these challenges. GIS provides a robust framework for spatial data analysis, while AI enhances decision-making through predictive analytics and automation. This paper explores the integration of GIS …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 1, 2025 · pp. 20–36 Read article
-
Deep Learning-Based Pneumonia Diagnosis: A Comparative Review of Models and Metrics
Abstract: Pneumonia is a common viral infection that affects a large percentage of people worldwide. It is more common in developing and impoverished areas because of factors like poor sanitation, crowded living quarters, pollution in the environment, and restricted access to medical facilities. In order to improve survival chances and gain access to therapeutic therapies, pneumonia must be diagnosed as soon as possible. A type of artificial intelligence called deep learning …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 Read article
-
Educating Compilers to Learn: Utilizing Machine Learning for More Brilliant Code Optimization
Abstract: This study explores the use of machine learning (ML) approaches to compiler optimization. The now-traditional static compilation techniques are transformed into adaptive, dynamic systems capable of making context-specific advancements. Traditional compilers rely mostly on heuristic or rule-based optimization techniques. While these techniques work well in general cases, they consistently fail to adapt well within the limits of code structures that modern machines display. This limitation is especially acute in today's …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 50–54 Read article
-
Avian Echoes: Convolutional Neural Network for Bird Vocalization Detection
Abstract: Bird species identification is a complex task within ornithology that demands advanced technological solutions. This research presents an approach leveraging Convolutional Neural Networks (CNNs) for bird species recognition based on identification of bird sound, each employing unique datasets and methodologies. The objective involves a two-stage identification process, beginning with the construction of an ideal dataset. The crucial step involves converting 1D audio waveforms to 2D spectrograms, enhancing CNNs' ability to …
Published in Journal of Aerospace Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 26–37 Read article
-
Advancements in Molecular Engineering: Innovations at the Nexus of Chemistry and Technology
Abstract: Molecular engineering, a frontier of chemistry, merges precision and innovation to design and assemble molecular structures with unprecedented control. This abstract explores recent advances, highlighting key breakthroughs and their transformative impacts. Starting with its roots in chemical synthesis and materials science, it traces the evolution towards rational design driven by computational tools and advanced characterization techniques, enabling tailored molecular architectures. A focal point is programmable molecules, where DNA nanotechnology principles …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 2, 2023 · pp. 37–43 Read article
-
Breast Cancer Detection Using Machine Learning: A Comparative Analysis of Supervised Learning Algorithms
Abstract: Globally, breast cancer remains a predominant cause of mortality among women, highlighting the urgent need for timely and precise diagnostic approaches. This research explores the application of machine learning algorithms—including Logistic Regression, SVM, Naïve Bayes, KNN, and Random Forest—on the Wisconsin Breast Cancer Dataset for effective tumor classification. Key pre-processing steps such as missing value handling, feature scaling, and dimensionality reduction were employed to improve model performance. The study evaluated …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 46–52 Read article
-
The Role of Artificial Intelligence in Enhancing Athlete Performance and Training Strategies
Abstract: Artificial Intelligence (AI) is transforming modern sports by improving athlete performance, training methods, and decision-making processes. The integration of AI technologies such as machine learning, data analytics, wearable sensors, and computer vision has enabled coaches and sports scientists to analyze large amounts of performance data with greater accuracy and efficiency. Athletes' physiological indicators, movement patterns, injury risks, and recuperation processes are all monitored by these technology. Training regimens can therefore …
Published in Recent Trends in Sports · Vol. 3, Issue 2, 2026 · pp. 1–7 Read article
-
Polymer–Gel Composite Phase Change Materials: A Functional Polymer Composite Approach for Solar-Thermal Energy Storage in Building Facades
Abstract: This study investigates polymer–composite phase change materials (PCMs) in the form of polymer–gel hybrids as multifunctional systems for solar–thermal energy storage in building façades. Paraffin- and PEG-based PCMs were embedded into polyurethane and acrylic gel matrices to create shape-stabilized polymer–composites with high PCM loading (70–80 wt%). Differential Scanning Calorimetry (DSC) confirmed distinct melting/freezing transitions at ~56°C (paraffin) and ~42°C (PEG), with enthalpy values of 120–150 J/g, closely matching theoretical predictions, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 36–51 Read article
-
Application-Driven Rule-Based Framework for Lubrication Failure Modes in Industrial Systems
Abstract: Modern lubricants increasingly rely on polymer-based composites, integrating synthetic base oils, polymer thickeners and solid additives like MoS₂ and PTFE for high-performance applications. These formulations not only enhance thermal and mechanical stability but also enable low-friction operation across diverse industrial conditions. Lubrication-related failures represent a critical cause of unplanned downtime and reduced reliability in industrial machinery. This paper presents an application-driven, rule-based framework designed to assess and mitigate lubrication failure …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 522–531 Read article
-
Exploring the Development of AI Models Using Open-Source Tools to Predict Patient Outcomes and Optimize Treatment Plans
Abstract: Integrating artificial intelligence (AI) into healthcare offers a transformative opportunity to enhance patient care and clinical decision-making. Through the use of predictive analytics, AI can significantly enhance the accuracy of outcome predictions and assist in developing personalized treatment plans that cater to each patient’s specific needs. This paper delves into the development of AI models using open-source tools, which are increasingly favored for their accessibility, collaborative nature, and capacity for …
Published in Journal of Open Source Developments · Vol. 11, Issue 3, 2024 · pp. 37–49 Read article
-
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
-
Application of Artificial Neural Networks in Optimizing Polyhouse Roof Truss Design
Abstract: Polyhouses are specialised agricultural structures developed to maintain controlled environmental conditions for crop cultivation, thereby ensuring consistent productivity even under adverse climatic circumstances. The performance of these systems largely relies on the structural stability and cost efficiency of the roof truss, which must achieve an effective balance between strength, adaptability, and economy. In this research, an Artificial Neural Network (ANN)-based modelling framework is introduced to optimise the members of polyhouse …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 15–25 Read article
-
Pharmacovigilance And Drug-Induced Toxicities: A Clinical Perspective
Abstract: Pharmacovigilance, which aims to detect, assess, and prevent medication-induced toxicities and adverse drug reactions (ADRs), is a crucial part of healthcare. This study examines the several kinds of drug-induced toxicities, such as idiosyncratic, dose-dependent, and allergic reactions, and emphasizes the function of clinical pharmacists in the tracking and treatment of these illnesses. Pharmacovigilance systems are crucial because they can identify and handle drug-related safety issues that might not surface during …
Published in Research and Reviews: A Journal of Toxicology · Vol. 14, Issue 3, 2024 · pp. 17–30 Read article
-
Atmospheric Determinants of Feed, Fodder, and Forage Contamination in a Changing Climate: Emerging Challenges for Sustainable Livestock Production
Abstract: Feed, fodder, and forage contamination represents a growing constraint to sustainable livestock production under a changing climate. Atmospheric determinants such as rising temperature, altered precipitation patterns, increased humidity, elevated carbon dioxide concentration, and enhanced aerosol and pollutant loads are increasingly recognized as critical drivers of contamination risks across feed supply chains. These atmospheric factors directly and indirectly influence crop growth, fungal proliferation, mycotoxin biosynthesis, microbial survival, and the deposition of …
Published in International Journal of Atmosphere · Vol. 3, Issue 1, 2026 · pp. 1–14 Read article
-
Recent Development to Track Contraband using Muon
Abstract: The muon is one of nature’s fundamental particles discovered in 1937 by Carl Anderson. A muon is an elementary subatomic particle similar to electron, but with a mass approximately 207 times greater and, sometimes it is called as a “heavy electron”. Muons are generated naturally when cosmic rays collide with atoms in earth’s upper atmosphere and, then raining down all the times upon the surface of earth. Muons can be …
Published in International Journal of Universe · Vol. 2, Issue 1, 2026 · pp. 23–34 Read article
-
Heat Sink-PCM Device for PV Efficiency Improvement
Abstract: This paper is focused on the development of a second stage of a previous work where the PV panel efficiency is improved by using a hybrid system made up of a PCM attached to the rear side of the panel. This evolved stage incorporates a heat sink unit to improve the distribution of the heat removed from the panel; this improvement reduces the elapsed time to reach the steady state …
Published in Journal of Thermal Engineering and Applications Read article
-
Remote Sensing and Atmospheric Modelling: Data, Processes, Integration and Future Directions
Abstract: Atmospheric modelling plays a central role in weather forecasting, climate projection, and air quality assessment; however, the availability, accuracy, and representativeness of atmospheric observations fundamentally constrain its reliability. Over the past two decades, rapid advances in remote sensing (RS) have transformed atmospheric observation by providing spatially continuous, multiscale measurements of key atmospheric variables, including aerosols, trace gases, clouds, precipitation, and atmospheric thermodynamic profiles. This review synthesises recent progress in integrating …
Published in International Journal of Atmosphere · Vol. 3, Issue 1, 2026 · pp. 54–67 Read article