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1236 articles for “systems modeling”
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Enhancing Energy Efficiency in HVAC Systems: A Comprehensive Study of EC+ Fans, VFDs, and AI Integration
Abstract: This research paper explores the integration of EC+ fans with Variable Frequency Drives (VFDs) and Permanent Magnet (PM) motors to enhance energy efficiency and operational performance in heating, ventilation, and air conditioning (HVAC) systems. An extensive energy audit was conducted at the BidP plant in Bangalore, focusing on air handling units (AHUs) in Hangar 101. The audit revealed substantial variations in fan efficiency, secondary fan performance, power consumption, and airflow …
Published in Trends in Machine design · Vol. 11, Issue 3, 2024 · pp. 44–54 Read article
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Machine Learning Based Sentiment Analysis of Student Feedback in Higher Education
Abstract: Educational institutions routinely collect feedback from students to understand their perceptions of academic programs, infrastructure, and campus facilities, to improve the overall quality of the college environment. In current practice, feedback is often gathered using numerical or grade-based rating systems, which tend to oversimplify student opinions and may overlook important details related to their level of satisfaction. In contrast, open-ended textual feedback allows students to clearly express their views, concerns, …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 01–10 Read article
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An Empirical Study of Hyperparameter Impact on Deep Learning Models for Cardamom Leaf Disease Classification
Abstract: Recent advancements in deep learning models like convolutional neural networks and self- attention mechanisms have achieved great success in the field of plant disease classification. This study investigates the efficacy of two pre-trained models, ConvNeXT-Tiny and Swin Transformer-Tiny, for leaf disease classification in cardamom using a publicly available dataset constituting three categories of leaves, namely Healthy, Colletotrichum Blight and Phyllosticta Leaf Spot. The effectiveness of the models highly depends on …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 48–60 Read article
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Flaws and Defects in Crystals
Abstract: Crystalline materials are defined by their long-range atomic order; however, no real crystal is completely free from imperfections. This article provides a comprehensive overview of the various types of crystal defects and imperfections that occur in solid materials and their significant influence on material properties. Point defects, including vacancies, interstitials, and substitutional atoms, are examined alongside line defects such as edge and screw dislocations, as well as planar defects encompassing …
Published in International Journal of Crystalline Materials · Vol. 2, Issue 2, 2025 · pp. 1–15 Read article
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Emotion Recognition from Electroencephalogram Signal and Eye Movement Based on Deep Learning
Abstract: Emotion recognition from electroencephalogram (EEG) signals has gained significant attention due to its potential in human- computer interaction (HCI), mental health monitoring, and personalized content delivery. This paper presents the use of Convolutional neural networks (CNNs) to classify emotions such as happiness, sadness, fear, neutral, and disgust by leveraging a fusion of EEG signals and eye movements data. Compared to conventional methods of emotion detection, such as those that rely …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 8–15 Read article
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From Cattle to Capital: A Review on SHGs, Dairy Farming, and Gender Empowerment in Rural India
Abstract: Self-Help Groups (SHGs) have emerged as a platform for encouraging women to start their own ventures in rural India, particularly through dairy-based enterprises. This review explores the role of SHGs in enhancing financial support, skill development, market access, and social empowerment among rural women. By utilizing savings and providing microcredit, SHGs enable women to establish and expand dairy ventures, contributing to household income and organized milk production. The integration of …
Published in Research and Reviews : Journal of Dairy Science and Technology · Vol. 15, Issue 2, 2026 Read article
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Generative AI for Designing Sustainable Polymer Composites for Renewable Energy Applications
Abstract: Sustainable polymer composites are increasingly required for renewable energy devices, yet conventional trial-and-error formulation cannot efficiently balance performance, processability, recyclability, and environmental constraints. This study proposes a generative artificial intelligence framework for designing polymer composites for photovoltaic encapsulation, dielectric energy storage, polymer electrolytes, and thermal-management systems. Public polymer-property and composite datasets were curated from open databases and published supplementary records. Chemical descriptors, molecular fingerprints, polymer embeddings, processing variables, and sustainability …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Optimized Utilization of Kota Stone Slurry Waste in Fly Ash–Based Geopolymer Mortar: A Taguchi-Driven Approach
Abstract: The large-scale generation of stone-processing wastes presents a critical sustainability challenge and an opportunity for value-added reuse in construction materials. This study develops a high-performance fly ash geopolymer mortar by partially replacing Class F fly ash with Kota stone slurry waste (KSSW) and optimizing the key mix parameters using a Taguchi design framework. Five governing factors—binder replacement level, NaOH molarity, sodium silicate–to–sodium hydroxide ratio (SS/SH), curing temperature, and alkaline solution-to-binder …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 426–445 Read article
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Intelligent Power Quality Enhancement Strategies for PV-Integrated Smart Distribution Networks: A State-of-the-Art Review
Abstract: The rapid integration of photovoltaic (PV) systems into modern power distribution networks has introduced significant challenges related to power quality. Issues such as voltage fluctuations, harmonic distortion, flicker, and reactive power imbalance arise due to the intermittent and nonlinear nature of solar energy generation. This paper presents a concise literature review of various power quality enhancement techniques employed in PV-integrated networks. Key approaches include the use of active power filters …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 1, 2026 · pp. 30–53 Read article
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Comparative Analysis of Personal Rapid Transit System with Thermoplastic Material for Interconnecting Metro Station with Airport
Abstract: Personal rapid transit (PRT) systems open a slew of new possibilities for solving airport-related transportation issues, both on the ground and in the air. For use in airport applications, the advantages and disadvantages of this mode of transportation are contrasted. An implementation of the ULTra Personal Rapid Transit system to assist passenger and staff vehicle squares at Heathrow is used to showcase the work. The ULTra infrastructure's compact size and …
Published in Journal of Polymer & Composites · Vol. 11, Issue 1, 2023 · pp. 97–108 Read article
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The Theoretical and Experimental Study of the Behavior of the Mercury Drop, Fixed on the Glass Bottom of Vessel with Fluid, Under the Acceleration of Gravity Change
Abstract: At present time, accumulated theoretical material of the studies of the equilibrium forms of the gas bubbles or mercury drops, fixed on the surface of solid material in the fluid or on the glass bottom of vessel with fluid, under the acceleration of gravity change, was carried out either on the basis of geometric similarity laws that greatly simplify the essence of physical processes, or on the basis of theoretical …
Published in Recent Trends in Fluid Mechanics 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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Exploring the Potential of AI-Driven Personalized Learning and Cognitive Interventions for ADHD Management in Indian Children and Adolescents: A Focus on Early Intervention
Abstract: Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental condition that significantly impairs attention, executive functioning, and behavioural regulation in children and adolescents. In India, the management of ADHD is particularly challenging due to low public awareness, social stigma, and a critical shortage of specialized mental health services, especially in rural areas. These systemic barriers often lead to delayed diagnoses and limited access to consistent care. However, with the rapid …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 1–5 Read article
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Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 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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Image-Based Quantitative Mapping of Structure Property Relationships in Polymer Composite Materials
Abstract: The performance of polymer composite materials is intrinsically governed by their microstructural architecture, which is shaped by manufacturing conditions and constituent interactions. Despite extensive experimental characterization efforts, establishing transparent and quantitative structure–property relationships from microstructural images remains a challenge. In this study, an explainable image-driven framework is developed to systematically correlate microstructural features with composite property indicators. Microstructure images are processed to identify voids, fibers, and filler phases, from which …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 188–196 Read article
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Industrial Prognostics via Ensemble Machine Learning: An Uncertainty Aware Framework for RUL Estimation on NASA FD004 Telemetry
Abstract: Estimating the Remaining Useful Life (RUL) of industrial machinery in real-time is now vital for both operational safety and smart resource management. In the aviation industry, turbofan engines deal with constantly shifting flight conditions, making traditional, scheduled maintenance both expensive and prone to error. This paper addresses the flaws in common “point-prediction” AI models, which offer a single failure date without any margin for error, by introducing a new, uncertainty-aware …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Advancing Asthma Management: The Synergy of Systems Biology, Artificial Intelligence, and Next-Generation Therapeutics
Abstract: Asthma is an inflammatory disorder of the respiratory tract that is chronic and heterogeneous in nature and has various effects on millions of people. Being a chronic inflammatory disease, asthma remains incurable and the major conventional treatments offer limited success due to the mask nature of its pathophysiology. Systems biology/(AI), and next-generation has greatly enhanced knowledge and the management of asthma. The approaches based on gene, transcript, protein, and metabolite …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 1–12 Read article
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Wear and Tribological Characteristics of Novel Metal Matrix Composites
Abstract: The development of advanced metal matrix composites (MMCs) with enhanced tribological performance has become increasingly important due to the premature failure of critical engineering components operating under severe wear conditions in automotive, aerospace, marine, defense, and power generation systems. Conventional composites such as Copper–Alumina and Aluminium–Silicon Carbide have demonstrated improved mechanical and wear characteristics; however, their widespread application is often limited by issues including particle agglomeration, non-uniform reinforcement distribution, porosity …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1326–1346 Read article
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Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article