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321 articles for “Scaling Model”
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Fundamental Principles of Fluid Behavior and Emerging Trends in Modern Fluid Mechanics Research
Abstract: Fluid behavior forms the foundation of numerous engineering technology and scientific applications, including aerospace flows, energy systems, and environmental processes. This paper presents a comprehensive overview of the fundamental principles governing fluid behavior, with a strong emphasis on their relevance to recent trends in fluid mechanic’s research. Core concepts such as fluid statics, fluid dynamics, and conservation laws are discussed to establish a solid theoretical framework. The study further examines …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 1, 2026 · pp. 14–21 Read article
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Record Linkage in Knowledge Discovery Process Using Angle Based Machine Learning
Abstract: Record linkage is a critical data cleansing step in the knowledge discovery process, aimed at identifying and resolving inconsistencies across datasets. This study proposes an enhanced record linkage framework tailored for uncertain and large-scale data using a combination of distance measurement, probabilistic modeling, and semantic reasoning. A novel angle-based distance measurement technique is introduced to optimize matching between candidate records. To further boost match accuracy, a Finite Mixture Model (FMM) …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1157–1170 Read article
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Productivity of Hydraulically Fractured Calcite Rich Shale Reservoirs Enhanced by Acid
Abstract: The current low oil prices have highlighted the need for enhancement to current production from shale formations. Prolonging the production life and increasing productivity of the fracture network in the shale plays can be a way to improve the economics. Many shale wells, drilled and completed based on current completion strategies, show sharp decline after initial flash production. One of the reasons behind this can be attributed to closure of …
Published in Journal of Petroleum Engineering & Technology · Vol. 6, Issue 1, 2016 · pp. 54–68 Read article
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Comparative of Encryption-Decryption Performance of (Binary, Gray- Scale, Color) Images Using Discrete Fractional Fourier Transform (DFRFT)
Abstract: The Discrete Fractional Fourier transform (DFRFT) provides an effective model of image encryption by further developing the classic Fourier transform by adding fractional orders, which increase the degrees of freedom. Owing to the omnipresence of digital media in many industries like education, healthcare, and entertainment, the mobility of visual data has become a significant issue to keep confidential. Images form one of the main ways of exchanging information and, therefore, …
Published in Research & Reviews : Journal of Physics · Vol. 15, Issue 1, 2026 · pp. 54–65 Read article
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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
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Project Management Maturity Model (PMMM) in Construction Industry
Abstract: Construction industry has a major role in social and economic development. However, high investment and large scale operation are some of the major problems in this industry, which is in sharp contrast with inferior management and low benefit. So project directors are seeking ways to improve their organizational management company's level to complete and control the implementation of their projects efficiently. The competition in the markets of construction industry is …
Published in Journal of Construction Engineering, Technology & Management · Vol. 6, Issue 1, 2016 · pp. 1–13 Read article
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Effect of Malaria Endemic on Socio-Economic Activities in South-East Nigeria: A Study from 2012 to 2023
Abstract: The research investigated the effects of malaria on socio-economic activities in South-East Nigeria between 2012 and 2023, emphasizing the effectiveness of different malaria management strategies. The analysis utilized both primary and secondary data, employing frequency tables and a five-point Likert scale to gauge respondents' levels of agreement. Furthermore, multiple regression models were utilized to explore the relationships among the variables.. Findings indicated that while diverse malaria interventions had a positive …
Published in Research and Reviews: A Journal of Health Professions · Vol. 14, Issue 3, 2024 Read article
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Computational Simulations in Drug Discovery: Modeling Protein Folding and Drug Binding
Abstract: Computational simulations have become essential tools in drug discovery, offering unprecedented insights into molecular behavior at the atomic level. These simulations, particularly in the domains of protein folding and drug binding, allow for the exploration of complex biological systems that are often difficult to study experimentally. Protein folding, a critical aspect of drug discovery, involves the transition of a polypeptide chain from an unfolded to a biologically active structure. Understanding …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 23–29 Read article
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Land surface dynamics: A Multiphysics Approach to Modeling Mass Transport
Abstract: Land surface dynamics are governed by complex interactions among hydrological, atmospheric, and geomorphological processes that collectively drive the transport of mass across terrestrial environments. Traditional modeling approaches often isolate individual mechanisms, limiting their ability to capture the coupled feedbacks that shape landscape evolution. This study presents a multiphysics framework for modeling mass transport on land surfaces, integrating fluid flow, sediment transport, heat exchange, and chemical reactions within a unified computational …
Published in International Journal of Land · Vol. 2, Issue 2, 2025 · pp. 31–36 Read article
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Viscoelastic Behavior, Interfacial Mechanics, and Reliability of Polymer Interlayers in Laminated Glass Composites: A Comprehensive Review
Abstract: The laminated glass systems are regarded as hybrid polymer–glass composites where the viscoelastic behavior of polymer interlayers mostly controls mechanical response. These interlayers (polyvinyl butyral (PVB), ionoplast, ethylene-vinyl acetate (EVA), etc.) have time-, temperature- and rate-dependent properties which significantly affect shear transfer, energy dissipation, and fracture resistance. But the baseline polymer-relevant processes at the molecular and interfacial level are to a large extent unknown [1]. This review provides a materials-focused …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 258–268 Read article
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New Analytical Expression of OPRA Over InverseGamma Shadowed Fading Channel with Selection Combining Diversity
Abstract: Abstract: Considering wireless communications, different factors are responsible for attenuation and degradation of signal which is term as fading. Generally fading is divided into two parts large scale fading and small scale fading. It is very essential to develop a fading model that characterizes the channel considering that effects. In this paper analysis of channel capacity under Optimal Power Rate Adaption (OPRA) over Inverse-Gamma shadowed distribution with Selection Combining diversity …
Published in Journal of Microelectronics and Solid State Devices · Vol. 6, Issue 1, 2019 · pp. 18–21 Read article
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Performance of Artificial Neural Network for Tree Species Identification using Sentinel-2 Data
Abstract: Accurate land cover mapping, especially concerning vegetation, is crucial for effective land use policy planning and sustainable forest management. Hence, achieving accuracy in mapping requires a deep understanding of composition changes, vegetation conditions, and the spatial distribution of tree species. In the spatial context of tree species, it holds significant potential for applications including invasive species monitoring, delineating contaminated areas, and biodiversity conservation. However, traditional methods for tree species identification …
Published in Journal of Remote Sensing & GIS · Vol. 15, Issue 2, 2024 · pp. 12–21 Read article
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Optimized Machine Learning Framework for Battery State Prediction in Smart Charging Systems
Abstract: Good estimation of battery states, including State-of-Charge (SoC), State-of-Health (SoH), and Remaining Useful Life (RUL), are important in managing energy wisely and controlling the adaptive charging. This work introduces a streamlined machine learning model based on the ability to use multi-dimensional sensor measurements in terms of voltage, current, temperature, and cycle number to forecast battery conditions with high accuracy. Decent preprocessing, such as noise elimination, feature scaling, and calculated features, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 55–66 Read article
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A Mathematical Perspective on Recent Cloud-Computing Trends for Scalable and Secure Social-Media Platforms
Abstract: Cloud computing underpins modern social-media platforms by providing elastic compute, storage, and data-processing pipelines capable of absorbing highly bursty workloads. This paper surveys recent cloud-native trends—serverless and event-driven design, container orchestration, edge/CDN offload, streaming analytics, and privacy-enhancing security controls—and formalizes their impact through a compact mathematical model. We express workload volatility using arrival-rate functions, use queueing-based capacity sizing to derive auto-scaling rules, and formulate an optimization objective that balances cost …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 35–40 Read article
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A Comprehensive Analysis of Classification Methods for Churn Prediction in Financial Services
Abstract: Persistent issues that affect long-term revenue in the banking sector include excessive client attrition. Customary churn models depend on measures related to customer satisfaction, which often result in low predictive accuracy due to their subjective nature. This study proposes an effective early warning model to address customer churn in financial services. Data is preprocessed through cleaning, one-hot encoding, Z-score normalization, and Min-max scaling. To handle class imbalance, the SMOTE algorithm …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 2, 2025 · pp. 47–61 Read article
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Numerical Simulation and Modeling of Self Heating in SOI MOSFET
Abstract: Abstract As the device size has been reduced the temperature increment of high-performance very large scale integrations (VLSIs) becomes a major issue. The self-heating effect and non-uniform power distribution in VLSIs, affect the performance of device. In this paper numerical simulation of self heating in SOI MOSFET has been performed. Poisson's equation, continuity equation, energy balance equation and heat flow equations have been solved self consistently using finite element method …
Published in Journal of Semiconductor Devices and Circuits · Vol. 5, Issue 3, 2018 · pp. 18–23 Read article
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Thermal Engineering: Principles, Evolution, and Comparative Analysis with Classical Approaches
Abstract: Thermal engineering is the study of heat transfer, thermodynamics and energy conversion systems. However, through the years it has progressed from classical theories, which relied on empirical correlations, to enhanced computed and nanotechnology based approaches. This paper highlights the principles of thermal engineering, its important systems and latest developments of thermal engineering and provides extensive comparisons between the classical (traditional) methods and the most recent developments or innovations such as …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 4, Issue 2, 2026 Read article
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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
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Advanced Anomaly Detection in Cloud Infrastructures Using Deep Learning Algorithms
Abstract: It is critical to guarantee the stability and security of cloud environments as cloud computing is becoming the backbone of contemporary IT infrastructures. Neglecting to quickly identify and resolve anomalies, which might point to security breaches, performance problems, or system breakdowns, can lead to disastrous outcomes. The increasing size and complexity of cloud infrastructures are challenging the effectiveness of traditional anomaly detection methods. These approaches often depend on rule-based systems …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 1–11 Read article
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Additive Manufacturing of Polymer-Based Advanced Composites: Mechanical Properties and Performance Evaluation
Abstract: Fabrication of large-scale and geometrically complex polymer-based advanced composites via fused deposition modelling (FDM) has been shown to be a promising technology for the production of such materials, however there are challenges in using short carbon fibre-reinforced polylactic acid (CF-PLA) which include obtaining high mechanical performance and maintaining dimensional accuracy with dynamic robot motion and complex interactions occurring between process parameters. The conventional approaches are mostly static feed rates or …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1326–1335 Read article