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1059 articles for “Model optimization”
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Predicting Dielectric Constants of Polymers Using Molecular Structural Descriptors and Explainable Machine Learning: A Data-Driven Approach
Abstract: Accurate prediction of dielectric constants in polymeric materials is fundamental to the rational design of advanced electronic components, energy storage capacitors, flexible substrates, and high-frequency communication circuits. Conventional approaches to identifying suitable polymer dielectrics rely on extensive experimental synthesis and characterisation, which are both time-consuming and resource-intensive. In this work, an explainable machine learning framework is developed to predict the dielectric constant of polymers directly from molecular structural descriptors derived …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 297–304 Read article
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Design and Comparative Analysis of UAV Body Prototype with ABS and CF + ABS as Structural Materials
Abstract: The small multi-rotor helicopters called drones consist in a fuselage “hanged” under a set of fixed pitch propellers each powered by an electric motor. These vehicles have great potentials and research in this topic is increasing aimed to reduce the structure weight to maximize flight time, range and payload. Multiple complex components involved in a single prototype in these vehicles put up a key challenge for 3D modelling, optimization and …
Published in Journal of Experimental & Applied Mechanics · Vol. 11, Issue 3, 2020 · pp. 1–12 Read article
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Mathematical Modelling and Comprehensive Review on the Application of Evolutionary Strategies in Design Optimization of Shell and Tube Heat Exchangers
Abstract: This review article presents the application of different evolutionary algorithms which have been utilized for design and optimization of shell and tube heat exchangers in the last decade. The traditional trial and error design approaches can be replaced by such evolutionary algorithms. These evolutionary techniques do not need information of derivatives and hence it can be implemented in various heat exchangers geometry without much complication. Many such EA’s are successfully …
Published in Trends in Mechanical Engineering & Technology · Vol. 7, Issue 3, 2017 · pp. 67–78 Read article
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Exploring the Development of AI Models Using Open-Source Tools to Predict Patient Outcomes and Optimize Treatment Plans
Abstract: Integrating artificial intelligence (AI) into healthcare offers a transformative opportunity to enhance patient care and clinical decision-making. Through the use of predictive analytics, AI can significantly enhance the accuracy of outcome predictions and assist in developing personalized treatment plans that cater to each patient’s specific needs. This paper delves into the development of AI models using open-source tools, which are increasingly favored for their accessibility, collaborative nature, and capacity for …
Published in Journal of Open Source Developments · Vol. 11, Issue 3, 2024 · pp. 37–49 Read article
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A Sustainable EOQ Model for Declining Products Incorporating Cubic Demand, Variable Deterioration, Partial Backlogging, and Carbon Emission Optimization
Abstract: In this paper proposes a sustainable Economic Order Quantity (EOQ) model for inventory systems involving decaying items under cubic time-dependent demand, variable decaying rates, and partial backlogging while absolutely considering carbon emission costs. The model reflects practical market actions where demand initially increases and afterwards declines over time, and decay depends on the age of the item. To demonstrate the current model's applicability as well as evaluate the trade-off between …
Published in International Journal of Industrial and Product Design Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article
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Optimizing Handoff Probability in GSM Networks: A Comprehensive Review of Pathloss Modeling Techniques
Abstract: Because wireless networks are becoming more and more popular, it is necessary to combine several heterogeneous networks in order to give users access to global information. An intriguing and modern concept called vertical handoff aims to combine several network interfaces. Battery power is the single most essential parameter that affects specific mobile nodes. The battery life of some mobile nodes is nearly depleted at the conclusion of algorithm execution because …
Published in Journal of Microwave Engineering and Technologies · Vol. 10, Issue 2, 2023 · pp. 22–29 Read article
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Optimization of Maximum Charge Per Delay Using Site-Specific Ground Vibration Prediction Models for Safe Blasting in an Opencast Coal Mine
Abstract: Drilling and blasting are critical operations in opencast coal mining that directly influence rock fragmentation, excavation efficiency, and production performance. However, excessive blast-induced ground vibration and air overpressure can create safety and environmental concerns, particularly in mines located near villages and sensitive structures. The present study was conducted at Chapapur-II Colliery, Mugma Area, Eastern Coalfields Limited (ECL), with the objective of optimizing blast design through the determination of safe maximum …
Published in Journal of Geotechnical Engineering · Vol. 13, Issue 2, 2026 · pp. 1–13 Read article
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Optimum Mixture Proportioning of Sawdust Ash Blended Sand-Stone Dust Blocks Using Scheffe’s Regression Theory
Abstract: This study carried out an experimental investigation on the compressive strength of sawdust ash blended sand-stone dust block of size 450 x 225 x 150 mm using Scheffe’s (5, 2) regression theory. The compressive strength of sawdust ash blended sand-stone dust blocks obtained based on fifteen trial mix ratios were used to develop the mathematical model while the results of the compressive strength values obtained based on the additional fifteen …
Published in Journal of Construction Engineering, Technology & Management · Vol. 13, Issue 2, 2023 · pp. 33–40 Read article
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Enhanced Multimodal Disease Prediction Using Hybrid Ensemble Learning and AutoML Techniques
Abstract: The integration of hybrid ensemble learning and automated machine learning (AutoML) is revolutionizing disease prediction by addressing the complexity, imbalance, and high dimensionality inherent in medical datasets. This paper proposes an advanced pipeline that combines diverse ensemble learning models with AutoML-based optimization to predict chronic diseases such as kidney diseas-e, Parkinson’s disease, and lung cancer. Publicly available datasets from UCI and PhysioNet repositories were preprocessed using outlier removal, normalization, and …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 10–20 Read article
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HFSS-Based Helix Antenna Design Optimization and Simulation
Abstract: This project uses HFSS (High-Frequency Structure Simulator) to simulate, develop, and analyze the performance of a helix antenna for (a particular purpose, such as broadband wireless or satellite communication). Because of their distinctive structural characteristics, helix antennas are well-suited for a variety of high-frequency applications by balancing compactness, high gain, and wide bandwidth. In this work, we parametrically analyze important design parameters including pitch, radius, number of turns, and wire …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 1, 2025 · pp. 29–35 Read article
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Statistical Modeling of Heat Transfer and Fluid Dynamics: Application in Mechanical Engineering Design
Abstract: Understanding and optimizing the intricate processes involved in heat transfer and fluid dynamics—two concepts essential to mechanical engineering design—require statistical modeling. Engineers can forecast, regulate, and enhance the performance of systems including heat exchangers, turbines, cooling mechanisms, and different fluid machinery by using statistical approaches. In order to address uncertainties, variability in material properties, boundary conditions, and operational parameters, this work investigates the integration of statistical modeling tools in the …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 2, 2024 · pp. 18–22 Read article
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Optimization of Liquid Metal Nanocomposites and Biogas Addition Rate Using ANN-GA
Abstract: In this study, the liquid metal nanocomposites were investigated using artificial neural network (ANN) prediction capabilities for Compression Ignition (CI) engine performance. The independent input variables selected were load (20-100%), Liquid-metal nanocomposites Doped Rate (NDR, 0-50 ppm), and Biogas Flow Rate (BFR, 0.5-1.0 kg/h). The Central Composite Face-Centered Design (CCFCD) was used in conjunction with the selected input variables and output parameters to assist in the preparation of the Design …
Published in Journal of Polymer & Composites · Vol. 11, Issue 11, 2023 · pp. 12–27 Read article
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Codal Validation and Optimization of Gantry Girders Under Variable Wheelbase and Impact Loads: A Review of Analytical, Numerical, and Codal Approaches
Abstract: Gantry girders serve as critical structural elements in industrial facilities such as steel plants, workshops, and heavy manufacturing units, where electric overhead traveling (EOT) cranes operate. The design of these girders is governed by stringent codal provisions to ensure safety under bending, shear, and deflection. However, discrepancies between codal predictions, analytical formulations, and finite element analysis (FEA) results, particularly under variable wheelbase and dynamic impact loads, have been widely reported. …
Published in Journal of Offshore Structure and Technology · Vol. 12, Issue 3, 2025 · pp. 23–29 Read article
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Enhancing Wildlife Tourism Management Using Deep Learning and Particle Swarm Optimization (PSO) for Animal Detection in Wildlife Sanctuaries
Abstract: Wildlife tourism is one of the most thriving sectors, faced with huge challenges in terms of safeguarding protected areas. As demand for wildlife experiences accelerates, it becomes necessary to find efficient measures that are friendly to conservation. The use of these advanced techniques in this field such as YOLO and PSO algorithm presents a new dimension on managing wildlife tourism. To harness the abilities of these techniques, this research centers …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 41–50 Read article
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Enhancing Surface Roughness of Polylactic Acid (PLA) 3D-Printed Parts Using CO₂ Laser Scanning: An Experimental Study on Parameter Optimization
Abstract: Fused deposition modeling (FDM) of polylactic acid (PLA) often suffers from poor surface finish due to the inherent layer-by-layer deposition process, limiting its use in high-precision applications. This study investigates CO₂ laser scanning as an efficient post-processing technique to reduce the surface roughness (Ra) of PLA parts while maintaining structural integrity. Specimens (100 × 80 × 5 mm) were fabricated with varying infill densities (35%, 70%, and 100%) to assess …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 503–511 Read article
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Educating Compilers to Learn: Utilizing Machine Learning for More Brilliant Code Optimization
Abstract: This study explores the use of machine learning (ML) approaches to compiler optimization. The now-traditional static compilation techniques are transformed into adaptive, dynamic systems capable of making context-specific advancements. Traditional compilers rely mostly on heuristic or rule-based optimization techniques. While these techniques work well in general cases, they consistently fail to adapt well within the limits of code structures that modern machines display. This limitation is especially acute in today's …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 50–54 Read article
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Improving Polymer Composite Properties Through Reinforcement Learning Guided Prototyping A Novel Approach for Material Engineering
Abstract: Innovative approaches integrating reinforcement learning (RL) and machine learning (ML) into the fields of polymer composite prototyping and soft actuator manufacturing for applications. This new an algorithm utilizing RL optimizes polymer composite fabrication parameters to enhance material properties efficiently. By iteratively adjusting parameters based on predefined objectives, the RL agent guides the prototyping process, promising to revolutionize polymer composite engineering. A finest control method for locked loop control of Shape …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 208–218 Read article
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A Comparative Study of Transfer Learning-Based Deep Learning Models for Breast Cancer Detection
Abstract: Breast cancer is a major concern in the world today, and early and accurate diagnosis is most crucial in the case of breast cancer, as it is among the disorders where the total cost of loss of life is high. Traditional screening processes are subjective and vulnerable to inter-observer reliability issues and diagnostic errors, being primarily based on manual interpretation of medical images. To address these limitations, Deep Learning (DL) …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–34 Read article
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Evolving Perspectives: Innovations in Object Detection and Identification
Abstract: One of the most important developments in computer vision has been the creation of object detection and identification systems, which have allowed robots to perceive and understand visual data similarly to humans. These systems locate each object by drawing a bounding box around it, in addition to detecting and classifying every object in an image or video. This study suggests a novel method for item identification and detection that makes …
Published in Trends in Opto-electro & Optical Communication · Vol. 13, Issue 3, 2023 · pp. 23–27 Read article
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AI-Optimized Biodegradable Polymer Composites for Medical Applications
Abstract: The value of biodegradable polymer composites in the medical practice has been massive as the composites may be deployed to provide temporary structural support, and they are also safe to degrade within the human body. However, the conventional material design process is trial and error, which is ineffective and inefficient. The article proposes a hybrid model involving experimental characterization, as well as an artificial intelligence (AI)-based model, to optimize biodegradable …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article