Search
1732 articles for “Predicting”
-
Evaluation of Diagnostic Sensitivity of Rapid Immuno-Chromatographic Card Test (ICT) Against IgM ELISA for Serological Diagnosis of Scrub Typhus: An Experience at a Tertiary Care Centre in South-Eastern Rajasthan
Abstract: Introduction: Scrub typhus (ST) is a common but under-reported rickettsial disease in rural/sub-urban population of our country often resulting in severe complications and high mortality. Evaluation of ‘point of care’ tests like Rapid Immuno-Chromatographic Card Test (ICT) for diagnosis of ST is important to ascertain its utility in diagnosis of the disease in remote and peripheral settings. Aims: The present study was designed to evaluate the diagnostic sensitivity of Rapid …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 9, Issue 1, 2019 · pp. 85–91 Read article
-
Magnitude and Factors associated with Voluntary Blood Donation Practice among Adult Mekelle Population, North Ethiopia: A Community-based Cross-sectional Study
Abstract: Globally, around 107 million blood donations are collected annually. However, only two million units are donated in sub-Saharan Africa where the need is enormous. Hence, the aim of the study was to assess the magnitude and factors affecting blood donation practice among adult Mekelle population. A community-based cross-sectional study design was conducted. Using multistage sampling technique and a pre-tested structured interview questionnaire, data were collected from 845 study participants. Collected …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 4, Issue 3, 2015 · pp. 5–13 Read article
-
Principles of Interpolating Prognostication in Oncology
Abstract: AbstractThe precise prediction in oncology plays a critical role in prevention, treatment, assessment of the effectiveness of methods of treatment and treatment outcomes for cancer patients. Some medical researches claim that statistical processing (factor analysis) permits to precisely individualize the prognosis, which determines the possibility of an individual approach to monitoring and postoperative treatment of patients. However, factor analysis permits only creating a matrix of factors that can significantly describe …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 9, Issue 2, 2020 · pp. 39–51 Read article
-
Evaluating the Role of Arterial Duplex Ultrasound in Diabetic Foot Ulcer Patients with Normal Ankle Brachial Pressure Index and Peripheral Pulses
Abstract: Background: Requesting a arterial duplex scan has been a recent trend in management of diabetic foot ulcer, as it is considered the gold standard modality of investigation for diagnosing peripheral arterial diseases. Nevertheless, increased burden of the diabetic foot ulcer patients and limited availability of the facilities and trained radiologists prompts us to use this investigation judiciously. Most of the studies focus on role of abnormal ABPI as a predictor …
Published in Research and Reviews : Journal of Surgery · Vol. 11, Issue 2, 2022 · pp. 28–33 Read article
-
Statistical and AI Approaches to Measure Sustainability Performance of Enterprises
Abstract: Measuring sustainability performance has become a critical priority for enterprises facing increasing regulatory pressure, stakeholder expectations, and global sustainability challenges. Traditional assessment methods, largely based on static indicators and manual reporting, often struggle to capture the multidimensional, dynamic, and data-intensive nature of sustainability. This study explores the integration of statistical and artificial intelligence (AI) approaches to evaluate and enhance the sustainability performance of enterprises in a more robust, accurate, and …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 30–36 Read article
-
Wildfire Detection and Tracking System
Abstract: To create a precise forecast of the wildfire, it is crucial to possess the capability to recognize it and anticipate how it will distribute. The devastation of vegetation, the loss of assets, the rise in greenhouse gases, the extinction of Numerous animal species and even human fatalities can all result from wildfires. To trim back this danger, there must be a mechanism capable of detecting a fire the moment it …
Published in International Journal on Drones · Vol. 2, Issue 2, 2026 · pp. 21–29 Read article
-
Thermo-Mechanical Behavior and Intelligent Optimization of Contact Temperature During Ultrasonic Vibration-Assisted Single-Pole Magnetic Abrasive Finishing of Zinc Alloy
Abstract: This study proposes a new integration of the experimental analysis, multi-physics finite element modelling (FEM) and machine learning (ML) optimisation of contact temperature (CT) in ultrasonic vibration-assisted single pole magnetic abrasive finishing (UV-SPMAF) of zinc alloy. The three gaps of the research are addressed: (i) The absence of a multi-physics FEM model that can couple electromagnetic, thermal and structural fields for UV-SPMAF of zinc; (ii) No quantified contribution of the …
Published in International Journal of Manufacturing and Production Engineering · Vol. 4, Issue 2, 2026 Read article
-
Generative AI-Driven Design Optimization of Lightweight Polymer Composites for Electric Vehicles
Abstract: Lightweight polymer composites are increasingly important for electric vehicles, where mass reduction must be achieved without compromising structural performance, thermal stability, manufacturability, or material reliability. This study develops a generative AI-driven inverse-design framework for identifying experimentally credible lightweight polymer-composite configurations under coupled EV-oriented constraints. Public experimental polymer-composite datasets were integrated through leakage-controlled preprocessing and group-aware validation. A multi-task neural surrogate predicted mechanical response, while a conditional variational autoencoder explored feasible …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
Intelligent Biocomposites for Real-Time Health Monitoring Applications
Abstract: Intelligible biocomposites are emerging as an enhanced material in the sense that they provide the capability to monitor health in real time because they have the inbuilt sensing and adjusting features. In this paper, the concepts of the intelligent biocomposites that have the ability to capture both mechanical and biochemical cues are to be presented as an informatics of designing, fabricating, and modeling. Multiphysics is used to couple mechanical deformation …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
Physics-Informed Neural Networks for Multiphysics Analysis of Biomedical Polymer Composite Systems
Abstract: Physics-Informed Neural Networks (PINNs) offer an effective model of solving coupled multiphysics equations in biomedical polymer composite systems, which are data-driven. In the given work, the PINN method is presented where equations of elasticity, mass diffusion, and heat transfer are integrated to model the complex processes that take place in composite biomaterials. The neural network loss is specified to include the governing partial different equations which enables both the system …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
AI Based Dental Care Solution System
Abstract: The AI-Based Dental Care Solution System is a web-based healthcare application developed using the MERN stack (MongoDB, Express. js, React.js, and Node.js) and integrated with Artificial Intelligence techniques to support early and accessible dental self-assessment. The system assists users in preliminary dental consultation by collecting symptoms such as tooth pain, sensitivity, swelling, bleeding gums, and bad breath through both structured forms and a conversational chatbot interface. Using Natural Language Processing …
Published in Research and Reviews: A Journal of Dentistry · Vol. 17, Issue 2, 2026 Read article
-
AI-Optimized Biodegradable Polymer Composites for Medical Applications
Abstract: The value of biodegradable polymer composites in the medical practice has been massive as the composites may be deployed to provide temporary structural support, and they are also safe to degrade within the human body. However, the conventional material design process is trial and error, which is ineffective and inefficient. The article proposes a hybrid model involving experimental characterization, as well as an artificial intelligence (AI)-based model, to optimize biodegradable …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
Smart Polymer Composite Scaffolds for Tissue Engineering with Integrated Machine Learning Feedback
Abstract: Another potential solution to improving the results of tissue engineering is smart polymer composite scaffolds, which are capable of dynamic adaptation to changing biological factors, but typical scaffolds cannot change dynamically. This paper suggests a comprehensive system to integrate biodegradable polymer composite scaffolds with sensing and machine learning-based feedback to allow the real-time monitoring and active regulation of tissue regeneration events. The system uses biocompatible materials of PLA/PCL composite of …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
Evaluating the Performance and Efficiency of Control Strategies in the Context of Reconfigurable Battery Architectures for Fast- Charging Electric Vehicle Stations
Abstract: Electric vehicles (EVs) are becoming very popular because they help to reduce pollution and save energy. But one big problem is charging, because normal charging take very long time. Many researchers study fast charging methods to make EV charging faster, safe and more efficient. Recent studies show that reconfigurable battery systems can help a lot. These system can change their connection or structure to charge faster and reduce loss. Recent …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 2, 2026 Read article
-
AI-Driven Intelligent Energy Management System for Enhancing Electric Vehicle Efficiency and Range
Abstract: Electric Vehicles (EVs) are crucial in mitigating the emission of greenhouse gases and facilitating sustainable transportation. Their performance is however limited by the capacity of the battery, unpredictable weather conditions and ineffective use of energy. The paper suggests an AI-based Intelligent Energy Management System (IEMS) to increase EV efficiency and driving range. The suggested system combines machine learning (ML), model predictive control (MPC), and real-time data analytics to optimize power …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 2, 2026 Read article
-
Measuring Microstructure, Wear Resistance, and Mechanical Reliability Enhancement in Polymer Nanocomposites via Data-Driven Analysis with Deep Learning
Abstract: Polymer nanocomposites have gained great attention owing to their superior mechanical performance, better wear resistance and customizable microstructural properties for aerospace, automotive, medicinal and industrial engineering applications. However, the correct evaluation of the link between the microstructure evolution and the material reliability is a huge issue due to the intricacy of nanoscale interactions and diverse material characteristics. In this study, we propose a data-driven approach that integrates deep learning and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
Finite Element, Experimental, and Machine Learning-Based Optimization of Machining Stability for Polymer Composite Material Processing
Abstract: The machining of polymer composite materials, particularly fibre-reinforced polymer-matrix composites, requires stable spindle-tool performance to avoid delamination, fibre pull-out, matrix cracking, thermal softening, poor surface integrity, and premature tool wear. In line with the scope of the Journal of Polymer & Composites, this study presents an integrated finite element, experimental, and machine learning framework for improving machining stability during end-milling of composite material systems. The spindle-tool assembly is modelled using …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
Bioinformatics and Medicine: Bringing Data to the Bedside
Abstract: From being an empirical and experience-based practice, modern medicine has transformed into a codified and research-based discipline, known as Evidence-Based Medicine (EBM). Though EBM has greatly enhanced the quality of medical practice through population-scale clinical trials, it still has limitations in managing biologically diverse patient populations, especially when dealing with clinical outliers who respond in an unusual way to standard treatments. With the rapid progress in genomics, proteomics, and high-throughput …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 · pp. 41–46 Read article
-
Fire Risk Assessment and Safety Improvement Strategies in Industrial Facilities: A Comprehensive Review
Abstract: Fire incidents in industrial facilities continue to pose significant threats to human life, infrastructure, production continuity, and the environment despite continuous advancements in industrial safety practices. The increasing complexity of manufacturing processes, the widespread use of flammable materials, and the integration of automated systems have intensified the need for systematic fire risk assessment and effective safety management. This review paper examines the major sources of fire hazards in industrial environments, …
Published in Journal of Industrial Safety Engineering · Vol. 13, Issue 2, 2026 · pp. 36–47 Read article
-
From Quantum Chemistry to Bioprocess Intensification: Advanced Computational Modeling and Enzyme-Based Catalytic Platforms for Green Chemical Transformations
Abstract: Green chemistry requires the development of sustainable catalytic systems that minimize waste generation, reduce energy consumption, and improve process efficiency. Computational chemistry and biocatalysis have emerged as complementary approaches for environmentally responsible chemical manufacturing. Computational techniques such as quantum chemistry, density functional theory (DFT), molecular dynamics, and machine learning provide mechanistic insights into catalytic reactions and support the rational design of efficient catalysts. These approaches enable the prediction of reaction …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 2, 2026 · pp. 45–52 Read article