Search
1059 articles for “Model optimization”
-
Multi-Objective Optimization of Polymer-Based Functionally Graded Composites for Lightweight Structures
Abstract: Functionally graded composites (FGCs) improve lightweight structural performance by allowing material properties to change smoothly across a component. Polymer-based FGCs (P-FGCs), in particular, are gaining prominence in aerospace, automotive, and biomedical industries due to their excellent strength-to-weight ratio, tunability, and ease of processing. However, optimizing these materials for lightweight structural applications requires addressing conflicting design objectives, such as maximizing stiffness while minimizing weight or enhancing thermal resistance while maintaining manufacturability. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 961–973 Read article
-
Intelligent Design Approaches in Microwave Engineering Using Machine Learning Techniques
Abstract: In microwave engineering, machine learning (ML) has become a potent technology allowing quicker design cycles, improved modelling accuracy, and automatic optimisation of complicated systems. Recent developments in the use of ML methods to microwave components and systems, including antennas, filters, and high-frequency circuits, are summarised in this study. In the framework of electromagnetic simulation, surrogate modelling, and parameter extraction, supervised and unsupervised learning algorithms are addressed. Moreover, the study looked …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 31–38 Read article
-
Feature Selection and Weighted Based Optimized Weight based Multi-Tier Stacked Ensemble (WMTSE) Classification for Twitter Sentiment Analysis
Abstract: AbstractThis research work concentrates on both feature selection and classification methods for utilizing twitter data. A new classifier is introduced for classifying “tweets” into positive, negative and neutral sentiment. The system contains four steps: Preprocessing by Tokenization, Text Cleaning, Part of Speech (PoS) Tagging, Stemming and Stop Words Removal, Feature Extraction by Bag-of-words (BoW), Lexicon-based features and Term Frequency- Inverse Document Frequency(TF-IDF), Feature Selection by Binary Swallow Swarm Optimization (BSSO) …
Published in Journal Of Network security · Vol. 8, Issue 3, 2020 · pp. 20–23 Read article
-
Exploring the Influence of Machining Parameters on Geometric Form and Orientation Controls (23 Design)
Abstract: This work explores the influence of machining parameters using on geometric form controls flatness and straightness as well as orientation control parallelism using an aluminum 6061 workpiece. Due to its good strength, machinability and cost- effectiveness, aluminum 6061 is widely used. In this experimental work, full factorial design is used and each factor has two levels. The response parameters chosen include flatness, straightness, and parallelism, which govern the form and …
Published in Journal of Experimental & Applied Mechanics · Vol. 16, Issue 1, 2025 · pp. 10–16 Read article
-
Dosing Control of Urea in Selective Catalytic Reduction (SCR) to enhance the reduction of Nitrogen oxides
Abstract: Selective Catalytic Reduction (SCR) is an effective aftertreatment technique designed to comply with rigorous emission criteria established by global regulatory authorities for the elimination of nitrogen oxides from exhaust streams. Since NOx and ammonia reagents are poisonous and an excess of either is therefore very undesired, it poses an intriguing control problem, particularly at high conversion. SCR systems must reduce NOx emissions as much as possible and reduce the possibility …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 110–120 Read article
-
A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression
Abstract: Early diagnosis of genetic diseases is crucial for effective treatment, especially in the case of Leukemia, a type of blood cancer characterized by abnormal proliferation of white blood cells. This paper presents a systematic review of recent computational techniques for the detection and classification of Leukemia using gene expression data obtained from DNA microarray analysis. The study explores diverse methodologies including machine learning (ML), deep learning (DL), and bio-inspired algorithms …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 2, 2025 Read article
-
Dynamic Modeling and Simulation of Multi-Body Mechanical Systems: A Comprehensive Review of Methods, Tools, and Applications
Abstract: The dynamic modeling and simulation of multi-body mechanical systems (MBS) form a cornerstone in modern mechanical engineering, enabling in-depth analysis of the kinematic and kinetic behaviors of interconnected rigid and flexible components. MBS are foundational to a range of critical applications, from automotive suspensions and aerospace mechanisms to robotics and biomechanical structures. As system complexity and performance requirements increase, accurate and scalable modeling techniques are essential for both design validation …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 35–42 Read article
-
A Study on Chatter Marks in Crankshaft Pin Grinding Process Using Taguchi Technique
Abstract: Crankshaft pin grinding is a vital machining process in automotive industry. It is a finishing operation to the crankshaft of the engine, which if neglected could lead to a significant cost to the manufacturer of warranty claims. The study aims at identifying significant process parameters that are influencing the chatter marks and also setting the process parameters of the machine to get a good quality product. Chatter marks are the …
Published in Journal of Mechatronics and Automation · Vol. 5, Issue 1, 2018 · pp. 1–5 Read article
-
Enhancement of Flexural Strength in FDM-Printed Components through Taguchi-Based Process Parameter Optimization
Abstract: Additive manufacturing (AM), especially Fused Deposition Modeling (FDM), has emerged as a widely adopted and versatile method for producing three-dimensional components. The process involves the deposition of a thermoplastic filament in a semi-molten state, which solidifies in successive layers to form the final structure. While this method enables the production of complex geometries at relatively low cost, the printed parts often exhibit inferior surface quality and reduced mechanical performance compared …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 272–280 Read article
-
Optimization of FDM 3D Printer Process Parameters For PETG Material Using TOPSIS Technique
Abstract: 3D printing is a quickly evolving process that builds the desired shape by layering on material. In the era of modern production, additive manufacturing has grown in significance due to its user-friendliness. By using this technique, one can produce complex & intricate geometries with much ease when compared to conventional manufacturing. With the increased demand for 3D printing, consideration towards strength quality and other mechanical properties is also increasing progressively. …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 601–609 Read article
-
Leveraging Deep Learning for Accurate Weed Identification
Abstract: Weed control is very important for all types of agricultural businesses. The project here revolves around the application of computer vision techniques and, more concretely, deep learning techniques, for the effective recognition and classification of weeds. The EfficientNetB4 architecture is an appropriate backbone as its scalability and performance optimization is adequate. The modifier used is Adam optimization algorithm which will serve as a pre- processor for the model. Weeds at …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 90–99 Read article
-
Algorithm for the prediction of cardiovascular disease (CVD)
Abstract: cardiovascular diseases (CVD) still claim a significant number of deaths globally and remain the number one killer with an annual death toll of nearly 17.9 million. While several medical advancements have been made, an early diagnosis is still hard to obtain, which often leads to worsening conditions and intricate treatment options. With the advancement of modern technology, Machine learning has demonstrated to be a miraculous tool which can greatly impact …
Published in Research and Reviews : A Journal of Immunology · Vol. 15, Issue 2, 2025 Read article
-
AI-Driven Topology Optimization of Woven Fiber-Reinforced Composite Chassis Structures for Electric Vehicles Under Crash Loading
Abstract: The structural design of an electric vehicle (EV) chassis represents a unique engineering challenge to achieve minimal weight while meeting occupants' safety requirements during high-energy crash conditions without compromise to the battery housing's integrity or the geometrical constraints of the electric powertrain package. In this paper, a single framework is proposed to integrate physics-based artificial intelligence (AI) surrogate models using PINNs, CNN-accelerated topology optimization, and FEA to design woven fiber-reinforced …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 72–89 Read article
-
AI-Driven Sustainable Supply Chain Framework for Polymer Composite Production
Abstract: As polymer composite processes become more difficult and environmental concerns increase, old supply chain models that just look at cost and operations have shown significant weaknesses when it comes to sustainability. The rising demand for environmentally friendly practices throughout a product’s life cycle requires a new process that makes sustainability a key element in making supply chain choices. The proposed framework was developed in response to this need by using …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 219–235 Read article
-
Tribological Performance and Wear Coefficient Prediction of AA2024–TiC Composites via Python-Based Machine Learning
Abstract: Determining wear coefficient accurately serves as a critical factor to maximize engineering materials' tribological characteristics. The experiment examines the wear characteristics of TiC-reinforced AA2024 aluminum alloy subjected to different tribological operating conditions. A pin-on-disc tribometer performed wear tests under different conditions of load and TiC weight fraction and sliding speed and duration. ANOVA statistical results show that load intensity and TiC reinforcement density stand out as principal variables that affect …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 1099–1112 Read article
-
Thermo-Mechanical Behavior and Intelligent Optimization of Contact Temperature During Ultrasonic Vibration-Assisted Single-Pole Magnetic Abrasive Finishing of Zinc Alloy
Abstract: This study proposes a new integration of the experimental analysis, multi-physics finite element modelling (FEM) and machine learning (ML) optimisation of contact temperature (CT) in ultrasonic vibration-assisted single pole magnetic abrasive finishing (UV-SPMAF) of zinc alloy. The three gaps of the research are addressed: (i) The absence of a multi-physics FEM model that can couple electromagnetic, thermal and structural fields for UV-SPMAF of zinc; (ii) No quantified contribution of the …
Published in International Journal of Manufacturing and Production Engineering · Vol. 4, Issue 2, 2026 Read article
-
Effect of 3D Printing Process Parameters on the Tensile Strength of Polylactic Acid (PLA)
Abstract: This study employs the Taguchi approach to systematically analyze and optimize critical Fused Deposition Modeling (FDM) parameters, focusing on their effect on the tensile strength of 3D-printed Polylactic Acid (PLA) components. The study explores three levels of layer thickness (0.15 mm, 0.25 mm, and 0.3 mm), infill densities (25%, 50%, and 75%), and nozzle temperatures (200°C, 205°C, and 210°C) across three infill patterns: Triangular, Gyroid, and Zig-zag. A total of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 128–140 Read article
-
AI-based Drug Discovery-Revolutionizing Pharmaceutical Research
Abstract: The traditional drug discovery process is often costly, time-consuming, and prone to high failure rates. The advent of Artificial Intelligence (AI) has revolutionized this field by significantly enhancing efficiency, reducing costs, and improving success rates. AI-driven approaches, including machine learning (ML), deep learning (DL), and natural language processing (NLP), have transformed key areas such as drug target identification, molecular screening, lead optimization, and clinical trial design. AI models can analyze …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 30–44 Read article
-
Improving Plastic Bottle Waste Management System of India using RVMs
Abstract: India is ranked first as the most populous country in the world, and plastic waste management has been a major ongoing concern for India. With the growing economy and population, the growth of plastic waste generation has been exponential but plastic waste management has been underachieved. The excess utilization and mishandling of single-use plastic have depreciated the performance of the plastic waste management system of India. This study emphasizes on …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 14, Issue 3, 2024 · pp. 31–41 Read article
-
Deep Learning Meets IoT: Hybrid Approaches for Botnet Detection
Abstract: Rapid advancement in the Internet of Things (IoT) changed everything, making it possible for seamless interconnectivity of devices and altering data-driven decision processes. This study delves into the intersection of IoT with deep learning approaches and hybrid approaches for managing botnet in IoT systems, especially security, efficiency, and performance optimization. Leveraging deep learning models, for example, CNNs and RNNs, will help the network achieve more intrusion detection and data analysis. …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 1, 2025 · pp. 18–27 Read article