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786 articles for “model-based approach”
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Issues and Challenges for Computing in Embedded System
Abstract: The reliability of any software system is very important for us. As we continue the process of error detection and error correction on the software system, the reliability of the software keeps on increasing. So, for modeling this growth in the reliability of any system, many formulations in the form of Software Reliability Growth Models has been proposed. Among these approaches, maximum approaches are based on NHPP. In this paper, …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 6, Issue 2, 2018 · pp. 18–21 Read article
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Comprehensive Study of Least Squares Estimation in Fast Fading MIMO-OFDM Systems
Abstract: MIMO-OFDM technology is now the foundation for modern wireless communication systems, allowing dramatic improvements in spectral efficiency, power efficiency, and transmission rate. On the other hand, the least accurate channel estimation is still a critical task, especially when they are in fast-fading environments. This study gives a comprehensive survey of LSE-based approaches and their applications on different fast-fading channel models for MIMO-OFDM systems. Techniques like Pilot Assisted Channel Estimation (PACE), …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 1, 2025 · pp. 13–21 Read article
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Performance, Combustion and Emission analysis of Sunflower oil based Biodiesel using Non-Dominated Sorting Genetic Algorithm-II
Abstract: Biodiesel is used as alternate fuel of I. C. Engines for so many years. It is obtained from various edible and non-edible oils including waste cooking oils through trans-esterification process in the presence of catalyst. The suitable amount of biodiesel mix with commercial diesel can be used to run the compression ignition engines. The optimum combination of engine input parameters is the challenging task as required by the design engineer …
Published in International Journal of Energy and Thermal Applications · Vol. 1, Issue 1, 2023 · pp. 1–6 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
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Enhance Thermal and Conductive Properties through Graph Neural Network-Based Machine Learning-Driven Advanced Polymer Material Design
Abstract: Advanced polymer materials are widely used in modern engineering and manufacturing because of their lightweight nature, flexibility, durability, and adaptability to different applications. However, designing polymer materials with enhanced thermal and electrical properties remains a challenging task. The performance of polymers is influenced by a complex combination of molecular structures, filler materials, processing parameters, and nanoscale interactions. Conventional optimization methods often require extensive experimental trials and computational resources, making it …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 386–407 Read article
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Bland-Altman Analysis for Evaluating AHP-based Wildlife Habitat Suitability Models
Abstract: The paper targets in establishing the potential of Bland-Altman analysis integrated with geospatial approach in habitat suitability ecological studies for species conservation. Assessing agreement between two measurement methods can be done by using Bland-Altman plots and calculating limits of agreement and hence compares two assay methods. This method is tried in this study for evaluating suitable habitats for tiger. The study incorporates Geographic Information System – Multi-Criteria Decision Analysis (GIS-MCDA) …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 4, Issue 2, 2015 · pp. 11–18 Read article
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A Comprehensive survey of robust image quality metrics for satellite imagery
Abstract: Satellite imagery is essential for applications like environmental monitoring, urban development, precision agriculture, defence surveillance, and disaster response. The reliability of these applications is closely tied to the quality of the captured images, which may be compromised by atmospheric effects, sensor imperfections, compression artifacts, and transmission noise. As a result, accurate image quality assessment (IQA) is essential to ensure trustworthy analysis and informed decision-making in satellite-based systems. The distinctive properties …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 1, 2026 · pp. 7–20 Read article
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Delhi Ladli Scheme 2008: A Parental Perspective
Abstract: An exploratory study to assess the knowledge and utilization of ‘Ladli scheme 2008’ among parents of girl child who are eligible to avail the benefits of this scheme in a selected community of Delhi with a view to develop Information Guidelines was conducted. The main objectives of the study were to (i) Identify the parents of girl child who are eligible to avail the benefits of ‘Ladli scheme 2008’. (ii) …
Published in Journal of Nursing Science & Practice · Vol. 4, Issue 3, 2014 · pp. 43–48 Read article
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Participatory Risk Management Model for Construction Projects Using Expert Systems
Abstract: Construction involves processing of numerous interdependent risks. But risk management in the sector is still largely intuitive and mere system compliance. Meticulous efforts towards a system-based approach is lacking. These lapses emphasized the need for developing an easy to use participatory model for risk management at construction project sites. A model that would not only enhance the effectiveness of the risk management process but also generate essential knowledge that can …
Published in Journal of Construction Engineering, Technology & Management · Vol. 6, Issue 2, 2016 · pp. 17–24 Read article
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Ethical AI and Data Protection in the Era of Industry 5.0
Abstract: This paper provides a comprehensive analysis of the critical intersection between Responsible AI (RAI), data privacy, and the Industry 5.0 paradigm. Industry 5.0, defined by its human-centric, sustainable, and resilient pillars, introduces a fundamental paradox: its core requirement for human-AI collaboration necessitates the collection and processing of granular human data, creating direct conflicts with emerging global data privacy and AI regulations. This research utilizes a systematic integrative review methodology, analyzing …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article
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An approach to adding knowledge constraints to a data-driven generative model for Carnatic rhythm sequence
Abstract: Computational models for generative music have been a recent trend in AI based technology developments. However, an entirely data-driven strategy often falls short of capturing the naturally occurring rhythmic grouping. Guedes et al. [1,2] had proposed dictionary based and stroke-grouping based approaches to generate novel sequences in the 8-beat cycle of Aditala. More recently an attempt of incorporating arithmetic partitioning, as conceived by performers, was made [3] to get rid …
Published in Trends in Electrical Engineering · Vol. 9, Issue 3, 2019 · pp. 11–17 Read article
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Deep Reinforcement Learning-Based Intelligent Energy Management Strategy for Battery–Supercapacitor Hybrid Energy Storage Systems in Electric Vehicles
Abstract: As the number of EVs increases, smart solutions for energy management are needed that will optimize energy use, prolong battery life and boost vehicle performance. The application of conventional rule based and optimization-based Energy Management Strategies (EMS) for Battery–Supercapacitor Hybrid Energy Storage Systems (HESS) often leads to sub-optimal power management, supercapacitor mismatch and battery degradation when subjected to varying driving conditions. This study aims to design an intelligent energy management …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 2, 2026 Read article
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Identifying Trends in Landuse/Landcover Changes in Hisar Tehsil: A LCM Based Approach
Abstract: Land is a source of all basic human needs, (e.g., agriculture, forest, water supply etc.) which is being continuously depleted by various agents. Urban growth and urbanization are considered as one of the major factors responsible for change in landcover dynamics and depletion of land resources. As compared with other landcover classes such as agricultural land, urban land has smaller area coverage but its impact to the surrounding environment is …
Published in Journal of Remote Sensing & GIS · Vol. 8, Issue 1, 2017 · pp. 1–8 Read article
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Model Based Clustering using Finite Mixture Models of Lognormal Distribution
Abstract: AbstractModel-based clustering consists of fitting a mixture model to data and identifying cluster with its components. This study discusses model-based clustering using a finite mixture of a univariate lognormal distribution with k components. In this study, lognormal mixture models for skewed data and also the estimation of mixing proportion by distance-based clustering have been considered. Parameter estimation is carried out by expectation maximization (EM) algorithm using different initialization approach using …
Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 3, 2018 · pp. 58–67 Read article
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Enhanced Sustainable Concrete Mix Design Using LLMs and Advanced Machine Learning Techniques
Abstract: Large Language Models (LLMs) are emerging as transformative tools in materials science, offering human-like reasoning, zero-shot problem solving, and the ability to integrate fuzzy laboratory knowledge with structured data. This study extends and reinterprets the original systematic benchmark for using LLMs in sustainable concrete design, particularly for Alkali-Activated Concrete (AAC). We introduce an enhanced, multi-model framework combining LLM-based inverse design, Random Forest regression, Gaussian Process Regression (GPR), and a lightweight …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 26–33 Read article
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A New Approach for Modeling the Dynamics of Output Variables of a Spatially Distributed System
Abstract: This paper addresses the development of an average-value based model for the processing system having some peculiar physical constraints which prevent their process variables to have a steady and stable value. As a result, the maintenance of steady balance of the system will become tedious. The continuous observation of that process variable, fixation of its average value on real-time basis, and mathematical model development of above-average value as base factor …
Published in Journal of Power Electronics and Power Systems · Vol. 2, Issue 2, 2012 · pp. 20–33 Read article
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Multi-Modal Iris and Retina Recognition System using Discrete Hidden Markov Model based Score Fusion Technique
Abstract: The contribution of this work is to propose a model of multi-modal iris and retina recognition system where Hidden Markov Model based score fusion technique has been used for decision fusion approach. Two different uni-modal techniques such as iris recognition and retina recognition outputs are combined by using baseline reliability ratio based score fusion technique. CASIA iris dataset and DRIVE retinal dataset have been used to acquire the iris and …
Published in Current Trends in Information Technology · Vol. 5, Issue 2, 2015 · pp. 7–12 Read article
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Signal Drift Compensation in Polymer-Based Wearable Biosensors Using Data Processing Techniques
Abstract: Polymer-based wearable biosensors have emerged as promising platforms for continuous physiological monitoring due to their mechanical flexibility, low operating voltage, and compatibility with soft biological interfaces. However, their long-term deployment remains challenging because of signal drift caused by polymer ageing, hydration–dehydration cycles, ionic trapping, and environmental variations. These effects introduce baseline fluctuations and sensitivity degradation, which compromise the reliability and interpretability of physiological measurements. This study proposes a data-processing–driven framework …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 197–207 Read article
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AI-Enabled Recycling of Thermoplastic Polymer Waste in Hospitals: A Circular Economy Pathway Toward Green Hospital Certification
Abstract: This review research explores the latest role of AI in improving thermoplastic waste management for hospitals in terms of segregation accuracy, operational efficiency, and circular economy outcomes. Seventy-five relevant studies were analysed, and it was reported that AI-based systems, especially CNNs, YOLO models, and sensor-fusion approaches, achieved high accuracy in the identification and sorting of medical plastics, often above 90%. Early evidence also reveals improvements in the reduction of contaminants, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 170–182 Read article
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Structure–Property Modeling of Cement-Based Multi-Component Composites Using Ensemble Machine Learning and Explainable Feature Attribution
Abstract: Accurate prediction of compressive strength is central to structure–property optimization, quality control, and sustainability-driven design in cement-based composite materials. Cementitious systems represent heterogeneous multi-phase composites composed of reactive binder matrices and dispersed aggregate phases, whose macroscopic mechanical performance emerges from complex nonlinear interactions among constituents and curing-dependent microstructural evolution. This study develops a data-driven structure–property modeling framework to quantify the nonlinear dependence of compressive strength on multi-component composite composition and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 112–131 Read article