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55 articles for “dimensional accuracy”
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Random Forrest Based Man-in-the-Middle Attack Detection in Advanced Metering Infrastructure
Abstract: Advanced metering infrastructure (AMI) plays a central role in the operation of modern smart grid (SG) systems by enabling continuous, two-way communication between utility providers and consumers. Through this communication, AMI supports real-time monitoring, dynamic pricing, and efficient energy management. However, the same connectivity that makes AMI effective also increases its exposure to cyber threats. One of the most critical threats is the man-in-the-middle (MITM) attack, in which an attacker …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 · pp. 1–8 Read article
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Development and Implementation of Indoor Location-based Service in Museums Based on Bluetooth Low Energy Standard and Triangulation Algorithm
Abstract: Location-based services (LBS) in indoor locations are for providing information needed by users, and this information can be provided to users based on a Geofence. The most important component of location-based service systems is the Global Positioning System (GPS), which does not have the ability to determine the location in an indoor location. In this research, LBS Android software was developed for museums with the possibility of providing multimedia information …
Published in International Journal of Wireless Security and Networks · Vol. 2, Issue 2, 2024 · pp. 1–9 Read article
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Environmental Impact Assessment of Ocean Energy Converters Using Quantum Machine Learning
Abstract: The accelerating deployment of ocean energy converters (OECs) across tidal, wave, osmotic, and thermal domains necessitates rigorous, data-intensive environmental impact assessment (EIA) frameworks capable of modelling multi-stressor marine ecosystems in real time. Classical machine learning approaches, while operationally mature, encounter scalability bottlenecks and feature correlation limitations when applied to the high-dimensional, non-linear datasets characteristic of offshore monitoring networks. This paper presents a comprehensive quantum machine learning (QML) framework for the …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 16, Issue 1, 2026 · pp. 22–31 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Digital Innovation in Heritage Management: Exploring possibilities of I-BIM and H-BIM through Borobudur Temple and Dhanyakuriya
Abstract: Heritage buildings are vital links to our past, embodying the architectural, cultural, and historical significance of earlier eras. Their preservation has become increasingly complex due to environmental degradation, structural aging, and the evolving urban landscape. This paper investigates the application of Heritage Building Information Modelling (H-BIM) as a comprehensive methodology for documenting and conserving these structures. H-BIM leverages advanced digital technologies such as photogrammetry, laser scanning, and Geographic Information System …
Published in Journal of Construction Engineering, Technology & Management · Vol. 16, Issue 2, 2026 Read article
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Thermo-Hydraulic Enhancement of Annular Finned Shell-and-Tube Heat Exchangers Using Epoxy-Based Polymer Composites: A Material–Geometry Coupled CFD Investigation
Abstract: Shell-and-tube heat exchangers remain a backbone of industrial thermal systems, yet their performance is often limited by relatively low shell-side heat transfer and the weight and cost associated with conventional metallic components. In this context, the integration of polymer composite materials offers a promising pathway toward lightweight, corrosion-resistant, and performance-tunable heat exchanger designs. The present study investigates the thermo-hydraulic performance of a straight-tube shell-and-tube heat exchanger equipped with annular fins, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 669–684 Read article
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Multi-Scale Analysis of Polymer Based Energy Storage Systems for High Performance Battery Applications
Abstract: The energy storage systems based on polymers are becoming promising materials for the next generation of high performance batteries because of their excellent mechanical flexibility, improved safety, and favorable electrochemical properties. Even with computational tools in Python, polymer-based energy storage systems remain plagued by poor ionic conductivity, complicated electrochemical reactions and potential thermal runaway. Therefore, a multi-scale model is proposed to improve battery performance, thermal stability, reliability, and large-scale deployment …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1035–1048 Read article
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Quasi-Dimensional Thermodynamic Performance and Emission Modelling for Dual-Fuel SI Engine Operation Using Waste-Based Producer Gas and Methane
Abstract: Rising energy crisis and urgent need for better waste-handling techniques have gained significant attention. Integration of wastes-to-wealth and Green Energy evolution techniques are prime sustainable measures towards countering this menace. Moreover, Internal Combustion (IC) engines are significant energy consumers and their emissions play a major factor in global warming and ecological obliteration. Concerning these aspects, investigations should strive at emissions minimization and reutilization of low-impact industrial byproducts. Thus, using methane …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 446–458 Read article
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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
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STRUCTURAL–EPIGENOMIC ATLAS: CNV/SV- DRIVEN PROGNOSTIC REFINEMENT ACROSS CANCERS
Abstract: Structural genomic alterations, including copy number variations (CNVs) and structural variants (SVs), play a central role in cancer initiation and progression. These alterations extend beyond gene dosage effects and interact dynamically with epigenomic mechanisms such as DNA methylation, histone modifications, and three-dimensional chromatin organization. Recent pan-cancer studies have demonstrated that CNV burden and SV signatures reflect key oncogenic processes including chromothripsis, homologous recombination deficiency, enhancer hijacking, and extrachromosomal DNA (ecDNA) …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 1, 2026 Read article
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Integration of Vertical Axis Wind Turbines into Urban Environments: Feasibility and Design Considerations
Abstract: Abstract This study aims to comprehensively investigate the performance of Savonius rotor wind turbines through a combination of numerical simulations and experimental testing. Initially, 3-dimensional CAD software Solidworks and ANSYS will be utilized to design detailed models of the turbines. Numerical meshes will then be generated around these models using FLUENT software, incorporating the k-ε turbulence model to simulate fluid flow fields. Parameters such as drag coefficient, lift coefficient, pressure …
Published in Journal of Aerospace Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 20–25 Read article
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AI-Driven Multi-Objective Optimization of Conductive Polymer Composites for High-Performance Flexible Electronics
Abstract: The development of conductive polymer composites (CPCs) is critical for advancing flexible and wearable electronic technologies. However, the conventional trial-and-error approach to material formulation is time-consuming and often inefficient due to the high-dimensional nature of the design space. This study introduces a novel AI-driven framework that integrates machine learning (ML) with multi-objective optimization to accelerate the discovery of high-performance CPCs. A dataset of 1,000 experimentally reported formulations was compiled, capturing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 734–745 Read article
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Latent Fingerprint Development via Green Synthesis of PbO Nanoparticles Using Helianthus (Sunflower) Extract
Abstract: Fingerprints are crucial evidence in personal identification, categorized into three types: latent (invisible), patent (visible), and plastic (three-dimensional). To make the latent prints visible, various techniques are used like the powder method, chemical method, and different light sources. In the powder method, commercially available powders are used and are effective; however, incorporating nanoparticles enhances their effectiveness. In this study, a novel fingerprint powder is prepared through green synthesis using distilled …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 26, Issue 2, 2024 · pp. 12–17 Read article
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Rapid Forecasting of Short-run Electric Power Demand Profiles of India Using the Statistical Method of Z Scores
Abstract: Power demand profile prediction for a region or nation is a critical part of the energy system design and operational planning process. A simplified method based on non-dimensionalizing power demand data from previous years using Z scores calculated from the mean and standard deviation of the profiles is developed in this study to forecast monthly demand profiles at time resolution of 1 hour for future years. The Z score range …
Published in Research & Reviews : Journal of Statistics · Vol. 14, Issue 1, 2025 · pp. 38–48 Read article
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Exploring Spirituality and Cognitive Styles as a Predictor of Suicidal Ideation in Urban Population
Abstract: Suicidal ideation, or the thought of suicide, is a complicated and multi-dimensional issue of public health that effects individuals globally at a individual level, in families and in society at large. It is one of the main causes of death in the world. Beliefs, practices and experiences pertaining to the transcendence, sacred or divine, are all included in the broad category of spirituality. In cognitive psychology, the term "cognitive style" …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 2, 2025 Read article