Search
911 articles for “Integrated modeling”
-
Integrated Analysis of Stress Patterns in Transparent Polycarbonate Specimens: A Comparative Study between Photoelasticity and FEA Simulation for Compact Circular Testing
Abstract: Photoelasticity stands as a robust experimental technique within the realms of mechanics and materials science, offering a means to visually assess and analyze stress distribution within materials possessing transparency or translucency. This method, a non-destructive testing approach, involves the visualization of stress on a model subjected to a load, leveraging the unique property of materials known as birefringence or double refraction. The procedure entails the careful selection of a suitable …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 79–87 Read article
-
Enhancing Surface Roughness of Polylactic Acid (PLA) 3D-Printed Parts Using CO₂ Laser Scanning: An Experimental Study on Parameter Optimization
Abstract: Fused deposition modeling (FDM) of polylactic acid (PLA) often suffers from poor surface finish due to the inherent layer-by-layer deposition process, limiting its use in high-precision applications. This study investigates CO₂ laser scanning as an efficient post-processing technique to reduce the surface roughness (Ra) of PLA parts while maintaining structural integrity. Specimens (100 × 80 × 5 mm) were fabricated with varying infill densities (35%, 70%, and 100%) to assess …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 503–511 Read article
-
Future Challenges of Photocatalytic Water Splitting: Sustainability
Abstract: Photocatalytic water splitting has emerged as a promising technology for sustainable hydrogen production through the direct utilization of solar energy. This process mimics natural photosynthesis, using semiconductor materials to absorb light and drive the decomposition of water into hydrogen and oxygen. The method provides a sustainable and eco-friendly solution to the global energy challenge by enabling the reduction of carbon emissions. Among various solar-to-chemical energy conversion approaches, photocatalytic water splitting …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 3, Issue 2, 2025 · pp. 43–48 Read article
-
Enhanced Multimodal Disease Prediction Using Hybrid Ensemble Learning and AutoML Techniques
Abstract: The integration of hybrid ensemble learning and automated machine learning (AutoML) is revolutionizing disease prediction by addressing the complexity, imbalance, and high dimensionality inherent in medical datasets. This paper proposes an advanced pipeline that combines diverse ensemble learning models with AutoML-based optimization to predict chronic diseases such as kidney diseas-e, Parkinson’s disease, and lung cancer. Publicly available datasets from UCI and PhysioNet repositories were preprocessed using outlier removal, normalization, and …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
-
Emerging Digital Trends in Virology Software: Optimizing Viral Discovery, Surveillance,and Patient Management.
Abstract: Virology and antiviral therapeutics are being reshaped by rapid advances in computational tools, automation platforms, and virus-focused digital health applications. Software systems now span the entire virology value chain, from in silico viral target identification and antigen design, to AI-supported clinical trial management for vaccines and antivirals, to post-marketing pharmacovigilance and patient-facing mobile tools. This review examines current and emerging software trends relevant to virus studies, emphasizing applications in viral …
Published in International Journal of Virus Studies · Vol. 3, Issue 1, 2026 · pp. 29–38 Read article
-
Intelligent Earth: AI As A Catalyst For Climate Action
Abstract: Artificial Intelligence (AI) is assuming an increasingly influential role in climate science, providing advanced tools capable of interpreting vast, complex, and multi-dimensional environmental datasets. Traditional climate modeling approaches, while grounded in physical principles, frequently struggle to deliver high-resolution, real-time, and region-specific forecasts because of heavy computational demands, incomplete observations, and uncertainties in representing small -- scale processes. Artificial intelligence (AI) techniques, especially machine learning and deep learning, provide strong substitutes …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 48–52 Read article
-
A Thorough Examination of How Artificial Intelligence is Affecting the Transformation of Agriculture in India and Throughout the World
Abstract: By providing creative ways to increase crop yields, maximize resource usage, and advance sustainability, artificial intelligence (AI) is revolutionizing agriculture. AI technologies, such as machine learning, computer vision, and robotics, are being increasingly used in precision farming, crop monitoring, disease detection, and decision-making as the global agricultural sector faces pressing challenges like food security, population growth, and climate change. AI enables farmers to make data-driven decisions, optimize irrigation systems, monitor …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 39–45 Read article
-
Polymers and Composites in the Design and Construction of Unmanned Aerial Vehicles: A Comprehensive Technical Review
Abstract: The emergence of Unmanned Aerial Vehicles (UAVs) over the last few years has mostly been made possible by breakthroughs in material science. This review is concerned with an overview of some of the polymers and composites that are being commonly used in drone manufacturing in recent times, especially in relation to the influence of material choice on drone performance and capability. It sheds light on the drastic change in the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 874–882 Read article
-
Explainable GeoAI-Based Multi-Temporal Remote Sensing Framework for Early Detection of Climate-Induced Land Cover Transformation
Abstract: Climate change has emerged as one of the primary drivers of rapid land cover transformation, affecting ecosystems, agricultural productivity, biodiversity, and regional sustainability. Traditional remote sensing approaches often face challenges in detecting subtle and early-stage land cover changes due to limitations in temporal analysis and model interpretability. This study proposes an Explainable GeoAI-based multi-temporal remote sensing framework for the early detection of climate-induced land cover transformation using multi-source satellite imagery …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 2, 2026 Read article
-
IoT Integration in Sustainable Agriculture
Abstract: The increasing demand for food production, environmental concerns, and resource limitations have necessitated the adoption of Internet of Things (IoT)-based innovative farming solutions. The current paper introduces an IoT-based system that integrates hydroponics, aquaponics, and poultry to promote sustainability, resource utilization, and agricultural productivity. Conventional farming practices are riddled with ineffective use of resources, uncertain environmental effects, and expensive operations. The new system facilitates real-time monitoring, automated decision support, and …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 69–84 Read article
-
A Review of Electrification Trends in Agricultural Tractors: New Developments, Difficulties, and Opportunities
Abstract: A farmer is constantly searching for methods to make farming easier and use less money or labor. The main factor contributing to the high cost of farming is the use of tractors. Tractors are more expensive due to their high fuel consumption. But technology has intervened and provided an answer. The electrical engineering world’s idea to switch from fuel to DC batteries has made electric tractors more accessible and reliable …
Published in Trends in Transport Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 17–23 Read article
-
Analysis of White Matter, Gray Matter, and Cerebrospinal Fluid Alterations in Neurological Disorders: A Deep Learning Approach
Abstract: This paper investigates the role of white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) alterations in the pathophysiology of neurological disorders, including Alzheimer’s disease, Parkinson’s disease, schizophrenia, and epilepsy. By leveraging advanced deep learning methodologies, we aim to automate the segmentation and analysis of brain structures from MRI scans, enabling a more detailed and precise evaluation of their roles in disease progression. These techniques allow for the identification …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 3, 2024 · pp. 21–27 Read article
-
The Digital Frontier: How Computers Are Shaping the Future of Space Exploration
Abstract: The integration of computers and space technology has revolutionized the way we explore and understand space. Advanced computing systems play a pivotal role in space missions, from spacecraft navigation and communication to data processing and analysis. These technologies enable accurate modelling, simulation, and mission planning, allowing scientists and engineers to overcome the challenges of space exploration. Computers have also facilitated innovations such as artificial intelligence in autonomous spacecraft and real-time …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 1, 2025 · pp. 1–10 Read article
-
Artificial intelligence-integrated nanobiotechnology for precision medicine, smart diagnostics, and sustainable environmental applications
Abstract: Background: Nanobiotechnology integrates nanoscale materials with biological systems, enabling breakthroughs in drug delivery, biosensing, and environmental monitoring. However, the complexity of biological interactions and the vast parameter space of nano‑bio interfaces limit conventional design. Artificial intelligence (AI) offers powerful tools for modelling, predicting, and optimising these systems. Objective: This review provides a systematic, STM‑compliant overview of AI‑integrated nanobiotechnology across three domains: precision medicine (AI‑optimised nanocarriers, personalised therapeutics), smart diagnostics (AI‑powered …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 Read article
-
Entomo-Analytics: Insect Behavioral Intelligence for Climate-Smart Environmental Monitoring Systems
Abstract: Rapid environmental change driven by climate variability, urbanization, and ecological degradation has intensified the need for innovative monitoring systems capable of providing real-time ecological intelligence. Traditional environmental monitoring methods often rely on satellite imaging and stationary sensors, which may lack fine-scale biological sensitivity. In contrast, insects—due to their abundance, ecological diversity, and rapid responsiveness to environmental shifts—offer a powerful yet underutilized source of bio-sensing data. This paper introduces the concept …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 17–26 Read article
-
Modelling and Interpretation of A Novel Battery-Motor amalgamated Thermal Management System using rGO/CO3O4 based Hybrid Nano-composite Coolant for Electric Vehicle Applications
Abstract: Battery and motor have to be given equivalent importance to maintain the lifetime, thermal characteristics, efficiency and safety of Electric Vehicles (EVs). Thermal management of EVs need to be considered for battery and motor because of dynamic loading conditions. This research proposes a novel Battery-Motor Integrated Thermal Management System (BMITMS) for EV applications. An EV assembled with LiFePO4 battery pack and a three-phase induction motor has been considered on this …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 225–243 Read article
-
Advanced Airline Operations Control System Using NodeJS
Abstract: This research paper presents the development of an Advanced Airline Operations Control System (AAOCS) using NodeJS, a lightweight and scalable JavaScript runtime environment. Leveraging NodeJS's event-driven architecture and non-blocking I/O model, the system facilitates efficient management of flight operations, crew scheduling, resource allocation, and real-time decision-making in the aviation industry. Key features include real-time decision support tools, a microservices-based architecture for scalability, integration with external data sources and APIs, and …
Published in Journal of Control & Instrumentation · Vol. 15, Issue 1, 2024 · pp. 45–51 Read article
-
Unified Ensemble Techniques for Enhanced DDoS Attack Prevention and Detection
Abstract: Today’s world is entirely reliant on the internet. The internet is a worldwide information source that all users rely on, hence its accessibility is critical. There have been reports in recent years, particularly in the information and technology division of significant organizations worldwide, of data breaches where the terms denial-of-service (DoS) and DDoS are consistently present in the stolen material. Network security is seriously threatened by DoS attacks. They have …
Published in International Journal of Wireless Security and Networks · Vol. 2, Issue 2, 2024 · pp. 20–27 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
-
Open Source Software Empowering Artificial Intelligence, Machine Learning, and Cyber Security: A Comprehensive Research Study
Abstract: Open Source Software (OSS) has become a foundational pillar for rapid innovation across Artificial Intelligence (AI), Machine Learning (ML), and Cybersecurity. This paper delivers a comprehensive, journal-length analysis of OSS-driven ecosystems, emphasizing collaborative development, transparency, and accelerated deployment. By providing freely available libraries, tools, and frameworks, OSS makes it easier for developers and researchers to experiment, build models, and deploy solutions quickly. This study examines how OSS can be combined …
Published in Journal of Open Source Developments · Vol. 13, Issue 1, 2026 Read article