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821 articles for “process modelling”
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The Green Cost of Generative Ai: Environmental Sustainability Implications of Large-Scale Ai Systems
Abstract: Generative Artificial Intelligence (GenAI) has advanced rapidly in scale and complexity, enabling powerful capabilities in automated content creation, multimodal reasoning and real-time decision support across sectors. While these systems offer significant technological and economic benefits, their environmental implications are not fully examined. Large-scale GenAI models rely on high-performance computing infrastructure that consumes substantial energy and resources throughout their lifecycle, raising critical sustainability concerns. This paper offers a sustainability-oriented assessment of …
Published in International Journal of Sustainability · Vol. 3, Issue 1, 2026 · pp. 12–20 Read article
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A Review on Loan Approval Prediction Based on Machine Learning Techniques
Abstract: The banking industry has also benefited greatly from technological advancements. An increasing number of individuals are submitting loan applications on a daily basis. When deciding which loan applicants to approve, the bank must take certain rules into account. The bank needs to choose the best one for approval based on certain characteristics. The process of carefully verifying every person and recommending them for loan approval is laborious and fraught with …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 1–11 Read article
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Integrated Qualitative Response Assessment System
Abstract: Examinations for universities and yearboards are traditionally administered offline, with a significant number of students opting for subjective exams. This preference stems from the labor-intensive nature of evaluating subjective responses, which requires considerable time and effort from educators. Additionally, subjective grading can be influenced by the evaluator’s mood, leading to inconsistencies. In contrast, multiple-choice and objective questions are prevalent in entrance and competitive exams due to their ease of automated …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 3, 2024 · pp. 18–24 Read article
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Google Play Store Analysis
Abstract: Google play store consists of millions of applications and several thousand apps are added on the play store every day. The competition is so fierce that it is really difficult for the developers to find out whether the app that is the product of his hard work is going to be successful or not. The main goal of the study is to create a tool that helps developers and organizations …
Published in Journal of Open Source Developments Read article
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AI Approaches in Gait and Posture Analysis: A Review
Abstract: This review synthesizes current research on the application of artificial intelligence (AI) in gait and posture analysis, focusing on methodologies, algorithms, and clinical applications. It examines the use of machine learning (ML) and deep learning (DL) techniques to extract relevant features from sensorderived data, offering objective, and automated assessments that surpass traditional methods. A systematic literature review was conducted, analyzing studies that utilized AI for gait and posture analysis with …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 1–3 Read article
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AI-Driven Inverse Design of Functionally Graded Bio-Nanocomposites for Sustainable High-Barrier Packaging
Abstract: Multilayer plastic packaging realizes high barrier performance through laminated heterogeneous structures, but the heterogeneous structure has severe end-of-life challenges caused by the interfacial incompatibility of materials and the poor recyclability. This study proposes the inverse design of functionally graded PLA-nanoclay composite films by reinforcement learning as a monolithic alternative to traditional multilayer systems. Twin-screw extrusion is designed as a continuous control Markov decision process, and proximal policy optimization (PPO) is …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1547–1564 Read article
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Evolution of Kitchen Robots: A Review
Abstract: Robots are the machines designed and developed by humans which are more capable and efficient in doing such works and tasks which humans are unable to do or do with less efficiency. These machines are able to perform the tasks which are hard or impossible for humans. There are many robots which resemble like human, animal or even insects and are employed in different sectors. For example, dogs in bomb …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 1, 2024 · pp. 32–47 Read article
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Symmetry Breaking in Mathematical Models: Bifurcation, Chaos, and Pattern Formation
Abstract: Symmetry breaking serves as a central organizing principle in the understanding of nonlinear systems across physics, biology, chemistry, and engineering. When a system transitions from a symmetric state to an asymmetric configuration, it often signals the onset of new structures, dynamic behaviors, or even chaotic regimes. This review explores symmetry breaking from the theoretical and mathematical perspectives of bifurcation theory, chaos theory, and pattern formation. We discuss how small parameter …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 2, 2025 · pp. 25–30 Read article
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Role of Beowulf Clusters in Next-Generation Military Applications: A Comprehensive Study
Abstract: Beowulf clusters, which utilize cost-effective commodity hardware combined with open-source software for parallel computing, have emerged as a viable and efficient solution for high-performance computing needs. This paper explores their growing relevance and practical applications in modern and future military technologies. Contemporary military operations increasingly rely on rapid data processing, real-time intelligence, high-fidelity simulations, and autonomous decision-making systems. Beowulf clusters offer scalable and adaptable computational power that supports these demands …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 01–07 Read article
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Federated Learning: A Comprehensive Review of Models, Algorithms, and Business Applications
Abstract: In an age where data privacy is a significant concern, federated learning (FL) has become a game-changing method in machine learning. This decentralized model enables various parties to work together on training models without exchanging their raw data, effectively tackling the issues posed by data silos and privacy regulations. This article explores the current state of FL, including its underlying models and algorithms, practical applications, benefits, challenges, and future directions. …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 1–9 Read article
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Role of Fatigue and Creep in Structural Damage: A Comprehensive Review
Abstract: Fatigue and creep are two critical degradation mechanisms that significantly influence the structural integrity and longevity of engineering materials. These phenomena arise due to different loading and environmental conditions but often coexist in various industrial applications, leading to severe material degradation over time. Fatigue primarily results from cyclic loading, where repeated stress variations induce microstructural damage and crack initiation, ultimately causing catastrophic failure. Conversely, creep occurs under sustained stress at …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 1, 2025 · pp. 22–26 Read article
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Estimation of Soil Erosion Using GIS in Pune District, Maharashtra
Abstract: The Varandha Ghats pans approximately 14.62 km 2 , where changes in temperature, vegetation, topography, and soil characteristics are causing continuous soil erosion. Catchment heterogeneity and climatic variations cause spatial variability in hydrological processes. Differences in land use, soil type, topography, and rainfall patterns influence how water moves and accumulates across regions, resulting in diverse hydrological responses. This complexity challenges accurate modeling and effective water resource management strategies across variable …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 2, 2025 · pp. 26–33 Read article
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Review and Analysis of Biodegradable Polymer Composites for Sustainable Hotel Packaging Applications
Abstract: Given the fast expansion in the hospitality and tourism industry, the decline in single use packaging materials has greatly amplified the quantity of plastic wastes, as well as the destruction of the environment. The present review is dedicated to the design and use of biodegradable polymer composites (BPCs) as the sustainable solution to the hotel packaging. The paper will be a synthesis of recent developments in the field of natural …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 348–365 Read article
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AI-Assisted Gain Scheduling for Real-Time Temperature Control in Chemical Reactors
Abstract: Temperature control in continuous stirred-tank reactors (CSTR) represents a critical challenge in chemical process industries due to inherent nonlinearities, time-varying dynamics, and parametric uncertainties. Conventional proportional-integral-derivative (PID) controllers with fixed gains often fail to maintain optimal performance across varying operating conditions, leading to temperature excursions that compromise product quality and safety. This paper presents a novel AI-assisted gain scheduling framework that integrates artificial neural networks (ANN) with adaptive PID control …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 24–33 Read article
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Parametric optimization and validation of novel 3D scanning approach for sustainable manufacturing of patient-specific orthodontic retainers
Abstract: The purpose of the proposed study is to identify the ideal procedure parameters for 3D scanning a denture in order to produce customised orthodontic retainers that can be produced sustainably. However, pilot investigations rarely explore parameters like scanning angle, light intensity, or scanning distance. In order to lower acquisition error, the suggested study examines a method for forecasting the ideal values of the previously indicated scanning parameters. Based on the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 265–278 Read article
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An Experimental Investigation on Surface Roughness of Laser Beam Machining of Aluminium Alloy
Abstract: Laser beam machining (LBM) is a cutting-edge technique widely utilized for precision machining of advanced materials. This experimental investigation focuses on the surface roughness of aluminum alloy (Al 6061) during LBM. The study systematically examines the impact of process parameters such as laser power, cutting speed, and gas pressure on surface roughness (Ra). The significance of surface roughness in determining the quality and functionality of machined components is emphasized. The …
Published in Journal of Polymer & Composites · Vol. 12, Issue 6, 2024 · pp. 82–104 Read article
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Secure Coding Practices for Enhancing the Art of Ethical Hacking: A Comprehensive Study
Abstract: In the quickly developing scene of network safety, secure coding, and moral hacking are essential for strengthening computerized environments. Secure coding systems and moral hacking are linked to digital strength. This study examines the relationship between secure coding and moral hacking, emphasizing the importance of a hierarchical culture that focuses on secure coding standards. Attention to detail in software development can protect against malicious exploits. Security considerations are integrated throughout …
Published in International Journal of Wireless Security and Networks · Vol. 2, Issue 1, 2024 · pp. 21–29 Read article
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Early Autism Diagnosis: Machine Learning Models and Their Effectiveness
Abstract: Diagnosis is of utmost importance for timely intervention and support. However, traditional diagnosis methods, which are based on subjective assessment, are delayed. This project explores the role that machine learning techniques might play in enhancing the accuracy and effectiveness of ASD detection. Several state-of-the-art classification algorithms were benchmarked using a dataset from Kaggle. Logistic Regression, XG Boost, Random Forest, Decision Tree, and Gradient Boosting were taken into consideration. Other performance …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article
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Determination of Effect of Temperature on Bacteria and Fungi (Salt and Fresh Water)
Abstract: This study investigates the effect of temperature on bacterial and fungal activity in fresh and saltwater environments contaminated with crude oil. Utilizing standard characterization techniques, pure cultures of bacteria and fungi were isolated and identified. A bioreactor setup was employed to assess microbial growth and heat generation at varying temperatures (15°C to 120°C) over a 6-hour period. The results demonstrated that temperature significantly influences microbial activity, with bacterial growth rates …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 01–08 Read article
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Optimizing Marketing Campaigns Using Random Forest and A/B Testing
Abstract: Marketing initiatives play a vital role in driving business growth by reaching targeted consumer segments through tailored strategies across multiple channels. The success of these initiatives is influenced by various factors, including the type and duration of the campaign, the characteristics of the target audience, the communication channels employed, and the overall efficiency of each strategy. These factors collectively impact key performance metrics such as conversion rates, customer acquisition costs, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 01–09 Read article