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134 articles for “Performance measurement approach”
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Automated Machine Learning System for Model Selection and Hyperparameter Optimization
Abstract: The proliferation of machine learning applications in various scientific and industrial domains has given rise to an urgent need for developing principled, automated techniques for optimal architecture selection and hyperparameter tuning for machine learning models without human expert intervention. In this paper, we introduce the Automated Machine Learning System for Model selection and hyperparameter Optimization (AMLSMO)—a state-of-the-art, all-encompassing AutoML system that combines the power of meta-learning-based warm-starting, Bayesian Optimization with …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 15–23 Read article
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Comparison Of With Base Isolation And Without Base Isolation Building for G+15 High Rise Structures
Abstract: Reinforced concrete is a important construction material in civil engineering. This investigation serves as a case study to evaluate the ultimate capacity of the selected bearing system in reinforced concrete structures. The study aims to compare the performance between fixed base buildings and base isolated buildings. Specifically, the research focuses on assessing the appearance and ultimate capacity of the bearing system in both types of structures, aiming to provide insights …
Published in Journal of Construction Engineering, Technology & Management · Vol. 13, Issue 1, 2023 · pp. 28–34 Read article
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House Price Estimation Using Linear Regression: A Machine Learning Perspective
Abstract: House price prediction plays a crucial role in the real estate industry, helping buyers, sellers, and investors make well-informed decisions. Accurate estimation of property values enables stakeholders to assess market trends, plan investments, and minimize financial risks. This study focuses on the application of linear regression, a fundamental and widely used machine learning algorithm, to predict house prices based on multiple influencing factors. These factors include location, property size, number …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 21–29 Read article
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A Survey on Quality Team Effectiveness in Modern Service Factories
Abstract: In today’s increasingly competitive environment, service‐oriented factories—i.e., operations that deliver services rather than physical goods but use a factory‐style process (such as outsourcing centres, shared service centres, processing hubs, digital service factories)—are under pressure to enhance both quality of output and team effectiveness. This survey paper explores the role of quality teams within modern service factories, and investigates the factors influencing their effectiveness, the mechanisms by which they contribute to …
Published in Journal of Production Research & Management · Vol. 15, Issue 3, 2025 · pp. 25–30 Read article
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Experimental Investigations on the Durability of PMMA Microfluidic Devices Fabricated by Hot Embossing Lithography with Plasma Processing for Bioengineering Applications
Abstract: In this research paper, total 1290 individual static contact angles of different working liquids have been measured and recorded on the flat polymethylmethacrylate (PMMA) surfaces. Total 474 individual PMMA microfluidic devices have been fabricated by the maskless lithography, hot embossing lithography and direct bonding technique inside the cleanroom laboratory and mechanical engineering workshop to determine the durability of these microfluidic devices. Total nine individual working liquids have been used to …
Published in Emerging Trends in Chemical Engineering · Vol. 3, Issue 3, 2016 · pp. 1–18 Read article
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Pharmacy Teachers' Contribution to Preserving Education's Integrity and Quality in the AI Era
Abstract: Artificial Intelligence through its modern approach supports the development of pharmacy education through customized methods and automatic evaluation systems and computerized training exercises. Students benefit from AI tools which include intelligent tutoring systems together with virtual assistants and simulation platforms because these tools improve their knowledge of pharmacology and drug formulation as well as clinical practice. The transition to AI-controlled education creates new academic integrity issues and ethical problems and …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 20–42 Read article
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A Physics-Informed Graph Neural Network Framework for Real- Time Thermal-Aware Fault Prediction and Adaptive Power Optimization in Heterogeneous System-on-Chip Architectures
Abstract: Heterogeneous System-on-Chip (SoC) architectures are increasingly adopted in edge computing, artificial intelligence, autonomous systems, and high-performance embedded platforms due to their superior computational efficiency and flexibility. However, increasing integration density and workload diversity introduce severe thermal hotspots, accelerated device degradation, and unexpected hardware faults that adversely affect system reliability and energy efficiency. This study proposes a Physics-Informed Graph Neural Network (PI-GNN) framework for real-time thermal- aware fault prediction and adaptive …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 · pp. 19–28 Read article
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Design and Analysis of Quality Improvement for Radiator Manufacturing Industry
Abstract: This study investigates the design and analysis of quality control measures for the radiator manufacturing industry through the utilization of various nanofluids. Both experimental techniques and computational fluid dynamics (CFD) simulations using ANSYS software are employed to assess the performance of different nanofluids in enhancing the efficiency and reliability of radiators. The experimental aspect involves testing the heat transfer characteristics and thermal conductivity of nanofluids, while CFD simulations provide insights …
Published in International Journal of Energy and Thermal Applications · Vol. 2, Issue 2, 2024 · pp. 24–28 Read article
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IoT-Based Structural Health Monitoring and Damage Detection in Fiber Reinforced Polymer Composite Structures
Abstract: Applications of fiber-reinforced polymer (FRP) composite in the aerospace, civil infrastructure and renewable energy systems are increasing due to the fact that the composite possesses high ratio of strength to weight and can resist corrosion. However, processes of internal damages such as the cracking of the matrix, delamination and fiber fracture, are likely to take place without being visible on the surface and therefore a periodic check of the structure …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1076–1100 Read article
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High Gain Observer and Moving Horizon Estimation for Parameters Estimation and Fault Detection of an Induction Machine: A Comparative Study
Abstract: The synthesis of a high gain observer (HGO) and moving horizon estimation (MHE) for the on-line estimation of the rotor fluxes, the rotor speed of the induction motor from the current and voltage measurements is presented. This paper presents two approaches for estimating the parameters of an induction machine during normal and faulty functionning. These approaches are based on the HGO and MHE. Simulation results show that we can identify …
Published in Journal of Control & Instrumentation · Vol. 8, Issue 2, 2017 · pp. 15–26 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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A Low-Cost Multi-Sensor IoT System for Real-Time Segregation of Polymer Waste
Abstract: Segregation of solid waste is a critical aspect of waste management, especially in settings where technical and financial constraints limit the adoption of sophisticated technologies. The proposed low cost, sensor-driven smart waste sorting system combines a variety of sensing technologies with an integrated decision-making system. The system employs an inductive sensor, moisture sensor and capacitive sensor to measure the physical properties of waste items, allowing segregation into metal, wet and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 90–`107 Read article
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Cementing Sustainability: Utilizing Waste Foundry Sand to Enhance Concrete Performance and Reduce Environmental Impact
Abstract: The incorporation of waste foundry sand into concrete production represents an environmentally conscious and cost-effective approach. This method involves substituting discarded foundry sand for a portion of traditional fine aggregates in concrete mixtures. The primary objective is to address environmental concerns associated with waste disposal while simultaneously achieving cost efficiency in construction materials. By integrating waste foundry sand into concrete, this practice promotes sustainability by reducing landfill waste and conserving …
Published in Journal of Construction Engineering, Technology & Management · Vol. 14, Issue 1, 2024 · pp. 13–21 Read article
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Machine Learning-Based Quantification of Polymer Structure Property Relationships for Predictive Material Design
Abstract: Polymer structures exhibit complex, hierarchical arrangements that strongly influence macroscopic properties, yet consistent quantification remains challenging due to nonlinear interactions and limited unified modeling strategies. Existing approaches inadequately capture generalized structure–property mappings across diverse polymer systems. This research aims to establish a machine learning-based quantification model for polymer structure–property relationships to support predictive material design. A Polymer Structure Property Dataset of 5,000 polymer samples includes structural descriptors and experimentally measured …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 737–754 Read article
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Fractal-Entropy Guided Adaptive Signal Reconstruction for Non-Stationary Biomedical and Communication Systems
Abstract: This paper presents a novel Fractal-Entropy Guided Adaptive Signal Reconstruction (FEG- ASR) framework designed for accurate processing of non-stationary signals in biomedical and communication systems. The proposed approach integrates fractal dimension analysis with entropy- based feature evaluation to capture the intrinsic complexity and irregularity of time-varying signals. By dynamically adapting reconstruction parameters based on fractal-entropy measures, the method effectively separates noise from meaningful signal components while preserving critical information. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 · pp. 22–33 Read article
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Automated Healthcare Support System with AI
Abstract: The Automated Healthcare Support System with Artificial Intelligence (AI) presents a smart and scalable digital solution aimed at improving the accessibility and efficiency of healthcare services. The system is designed to provide preliminary medical guidance, perform symptom-based analysis, and deliver health-related insights through an intuitive user interface. By enabling early identification of potential health conditions, it assists users in determining the necessity of professional medical consultation. The proposed platform utilizes …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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Randomized Latent Vectors for Enhanced Reinforcement Learning Exploration
Abstract: This paper investigates Random Latent Exploration (RLE), a novel reinforcement learning technique that enhances exploration using randomized latent vector conditioning. I evaluate RLE’s performance across various environments, including discrete control tasks (FourRoom), continuous control (IsaacLab), and complex visual domains (Atari games). The core approach augments traditional reward functions with intrinsic rewards, calculated as the dot product between state features and periodically resampled latent vectors. The policy and value networks are …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 19–25 Read article
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AI-Accelerated Development of Gradient Polymer Nanocomposite Thin Films
Abstract: Gradient polymer nanocomposite thin films are an active field of materials research due to the fact that it enables scientists to de-facto regulate the optical, electrical, and mechanical properties of a film by merely altering its composition on a layer-by-layer basis. This type of control opens the gate to the improved flexible electronics, long lasting protective coats, and the new smart gadgets. The problem is, though, that it is a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 456–469 Read article
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Axial Compression Behavior of Aluminum (Al), Glass/Epoxy (GFRP) and Hybrid Al-GFRP Crash-box: An Experimental and Digital Image Correlation Approach
Abstract: The study aims to understand the axial compression characteristics and fracture of cylindrical Aluminum (Al), Glass/epoxy (GFRP) composite and Hybrid Al-GFRP crash-boxes. The hollow Al tubes are fabricated by rolling and bonding a thin aluminum sheet followed by rivet joints. The GFRP samples are manufactured using the wet-hand layup technique followed by the vacuum bagging method. Hybrid samples are manufactured by covering GFRP tubes with aluminum sheets on the outer …
Published in Journal of Polymer & Composites · Vol. 12, Issue 1, 2024 · pp. 304–313 Read article
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Non-Contact Quantification of Swelling-Induced Deformation in Polymer Hydrogels Using Image Analysis
Abstract: Swelling of polymer hydrogels governs transport, mechanics, and functional performance in biomedical systems, yet it is often reported using bulk ratios that conceal spatially heterogeneous deformation and boundary-driven instabilities. This study presents a non-contact image-analysis framework to quantify swelling-induced deformation by tracking shape and boundary evolution from time-lapse imaging. The approach segments the hydrogel region, extracts a sub-pixel refined contour, and computes boundary displacement descriptors including mean and upper-percentile normal …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1499–1509 Read article