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201 articles for “dimensional”
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Free Vibration of Curved Sandwich Beams with Laminated Composite Facings Using Finite Element Method
Abstract: The present work is focussed on the free vibration analyses of singly curved sandwich beams using three-dimensional finite element method in ABAQUS software. Three different layers are considered for soft core and stiff face sheets in ABAQUS solid modelling to accurately represent the effects of transverse shear deformation of sandwich structure. To validate the model, obtained natural frequencies from present model are first compared with the results available in the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 549–561 Read article
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Development of 3D Printing Filaments from Industrial Waste Plastics
Abstract: The global plastic waste crisis has prompted innovative approaches to sustainable material reuse, particularly in additive manufacturing. Simultaneously, the accumulation of plastic waste presents significant environmental concerns. Recycling plastic into filament supports eco-friendly innovation and brings us closer to a circular economy where materials are reused instead of thrown away. This study investigates the development of 3D printing filaments from industrial waste plastics, including polypropylene (PP), acrylonitrile butadiene styrene (ABS), …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 1, 2025 · pp. 12–17 Read article
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ML-Based Predictive Modeling of Mechanical Properties in 3D-Printed Polymer Composites for IoT Applications
Abstract: This study aims to develop an interpretable and high-accuracy machine learning framework for predicting the mechanical properties of 3D-printed fiber-reinforced polymer composites, with a focus on structure–property correlations relevant to polymer processing and functional performance. Composite specimens based on PLA and ABS matrices were fabricated using FDM with varying weight fractions (5–20 wt%) of carbon and glass fibers. Standardized mechanical testing (ASTM D638, D256, D790) was performed to evaluate tensile …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 61–78 Read article
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The Role of Optimization and Probability in Shaping Artificial Intelligence
Abstract: This study discusses the basic roles of optimization algorithms and the theory of probability in the process of evolution and development of Artificial intelligence (AI). First, we introduce the role played by the next generation of leading-edge optimization algorithms developed since gradient descent to evolutionary strategies with respect to the learning of high-level AI models and how to enable them to learn to effectively explore high-dimensional parameter spaces. At the …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 123–128 Read article
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Squeeze Casting of Hybrid Aluminum Matrix Composites: A Critical Review of Process Optimization, Reinforcement Strategies, and Performance Outcomes
Abstract: Increasing demand for lightweight, performance-oriented components in automotive, aerospace, and defense industries has driven advancements in squeeze casting, a hybrid technique merging forging and die-casting advantages to produce near-net-shape aluminum matrix composites (AMCs) with superior mechanical-tribological properties. This review critically examines the interplay of process parameters (e.g., squeeze pressure: 70–150 MPa, melt temperature: 650–800°C), reinforcement characteristics (volume fraction ≤10%, particle size: 10–71µm), and interfacial engineering strategies (flux-assisted bonding, ultrasonic dispersion) …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 2, 2025 · pp. 52–60 Read article
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Role of Reinforcement Learning in Improvement of Semiconductor Doping
Abstract: The semiconductor industry faces increasing challenges in achieving optimal doping profiles as device dimensions shrink and performance requirements intensify. Traditional doping optimization methods, while effective, often struggle with the complex, multi-dimensional parameter spaces characteristic of modern semiconductor manufacturing. This study explores the transformative role of reinforcement learning (RL) in improving semiconductor doping processes, examining how RL algorithms can autonomously optimize doping parameters to enhance device performance, reduce manufacturing costs, and …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 2, 2025 · pp. 23–34 Read article
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Exploring Spirituality and Cognitive Styles as a Predictor of Suicidal Ideation in Urban Population
Abstract: Suicidal ideation, or the thought of suicide, is a complicated and multi-dimensional issue of public health that effects individuals globally at a individual level, in families and in society at large. It is one of the main causes of death in the world. Beliefs, practices and experiences pertaining to the transcendence, sacred or divine, are all included in the broad category of spirituality. In cognitive psychology, the term "cognitive style" …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 2, 2025 Read article
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Variation In Wave Steepness and Wave Age-A Case Study in The Arabian Sea from Buoy Measurements During Post-Monsoon
Abstract: The National Institute of Ocean Technology (NIOT) moored buoy measurements in the Central Arabian Sea (AS) at AD07 location (68.87 E, 15.07 N) during the year 2015 are utilized to understand wind and wave growth characteristics at this location during the post- monsoon season covering the three-month period from October to December (OND). The wave direction followed the wind from Northeast while the swells were predominantly from the Southern Indian …
Published in Journal of Offshore Structure and Technology · Vol. 12, Issue 2, 2025 · pp. 10–21 Read article
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Feature Extraction and Analysis of Bearing Faults: A Review
Abstract: One of the most important steps in identifying bearing problems is feature extraction. In order to provide a more meaningful dataset, it entails locating and extracting pertinent features from raw bearing vibration signals. Tasks involving categorization and prediction can then make use of these attributes. In many practical applications, such as monitoring rotating machinery or electronic components, the raw signals collected (e.g., vibration, current, temperature) are often complex, high-dimensional, and …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 20–28 Read article
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A Review on Parametric Optimization of WEDM Technique for OHNS Steel
Abstract: In this study, the Wire Electrical Discharge Machining (WEDM) process for OHNS (Oil Hardened Non-Shrinking) steel, a high-performance material frequently used in the production of dies, punches, and precision tooling components, is optimized parametrically and validated experimentally. A continuously moving wire electrode and a sequence of electrical discharges are used in WEDM, a non-traditional machining method, to erode material and produce intricate and precise profiles, particularly in materials that are …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 29–35 Read article
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Topology and Geometry in Data Science: Persistent Homology and Beyond
Abstract: In recent years, the interplay between topology, geometry, and data science has gained substantial momentum, offering powerful frameworks to analyze and interpret complex datasets. Traditional statistical and machine learning methods often rely on linear or metric- based assumptions, which may fail to capture the intrinsic structure of high-dimensional or nonlinear data. In contrast, topological and geometric methods provide shape-oriented, scale- invariant tools that focus on the continuity, connectivity, and global …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 21–27 Read article
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Controlled Release Drug Delivery Using 3D Printing Techniques: A Current Scenario In Personalized Medicine
Abstract: Three-dimensional (3D) printing is particularly influencing the pharmaceutical manufacturing sector in the creation of controlled release drug delivery systems. This technology enables the precise fabrication of personalized medicines with tailored drug release profiles, dosages, and geometries, marking a significant advancement over traditional mass production methods. An array of 3D printing techniques, including extrusion-based, powder-based, and others, can be used to build complex dosage forms that regulate drug release through processes …
Published in Trends in Drug Delivery · Vol. 12, Issue 3, 2025 · pp. 28–43 Read article
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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
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Support Vector Machine Inspired Load Forecasting of a State University in Haryana
Abstract: Estimating the possible environmental impact and determining probable capital requirements are made easier with a solid grasp of electricity demand. Beginning in the middle of the 20th century, demand forecasting for electric power networks was studied theoretically. Prior to that, the study of demand forecasting had not developed because of the small scale of power networks. With the use of statistical prediction techniques, plans for the electric power industry have …
Published in Trends in Electrical Engineering · Vol. 15, Issue 2, 2025 · pp. 33–40 Read article
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Rethinking Consumer Preferences for Broiler Meat: Addressing Public Concerns for Sustainable Development
Abstract: Broiler meat is a crucial component of global protein consumption, yet its acceptance is often hindered by concerns related to health, animal welfare, environmental sustainability, and consumer perception. This study examines the factors influencing consumer preferences for broiler meat and explores strategies to address public concerns while promoting sustainable development. Misinformation regarding antibiotic residues, growth promoters, and broiler welfare has contributed to negative consumer sentiment, leading to a preference for …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
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Robust Classification of Traffic Signs Using Relief Feature Reduction Technique
Abstract: Ensuring driver safety amidst the rapid growth of global population and vehicular density continues to be a paramount challenge for transportation authorities and governments worldwide. With the rise of smart mobility solutions and autonomous driving technologies, the ability to detect, classify, and respond to traffic signs accurately has become critically important, especially under diverse and adverse environmental conditions such as rain, fog, or poor lighting. Reliable traffic sign recognition not …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 30–37 Read article
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Exploring Type-II Diabetes Potential of Phyto-Derived Carbon Dots
Abstract: The integration of phytoconstituents with carbon dots (C-dots) presents a novel and sustainable approach to the development of nanotherapeutics for type 2 diabetes mellitus (T2DM). C-dots, zero-dimensional carbon-based nanomaterials, exhibit unique physicochemical properties including high fluorescence, tunable surface chemistry, biocompatibility, and low toxicity. Their ability to enhance the solubility, bioavailability, and targeted delivery of poorly soluble phytochemicals renders them highly suitable for biomedical applications. This study explores the synthesis of …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 3, 2025 · pp. 08–25 Read article
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Influence of Static Sequences on the Thermal Behavior of Eco-Friendly Pineapple/Ramie Composites
Abstract: The increasing demand for sustainable and environmentally responsible materials has driven the exploration of natural fiber-reinforced polymer composites as potential alternatives to conventional synthetic materials. Among various natural fibers, pineapple leaf fiber (PALF) and ramie fiber are notable for their complementary characteristics—PALF offers excellent insulating behavior and lightweight structure, while ramie provides high thermal stability and strength. In the field of Eco-friendly composite product manufacturing, the processing temperature holds significant …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 732–742 Read article
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Influence of Hybrid Fiber Reinforcement on the Interfacial Bonding and Fracture Toughness of Epoxy-Based Polymer Composites Under Cyclic Loading
Abstract: This study investigates the influence of hybrid fiber reinforcement on the interfacial bonding and fracture toughness of epoxy-based polymer composites under cyclic loading. Carbon, glass, and aramid fibers, both individually and in hybrid combinations, were incorporated into the epoxy matrix to evaluate their thermal, mechanical, and fatigue-resistant properties. Thermal characterization revealed distinct material behaviors, with carbon fibers exhibiting superior thermal conductivity, while glass and aramid fibers provided enhanced thermal stability. …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 799–824 Read article
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Disease Prediction Using Ensemble Learning Models: A Comprehensive Approach
Abstract: In recent years, ensemble learning techniques have become pivotal in advancing predictive analytics within healthcare, particularly for early disease detection. The inherent variability and complexity of medical data, often characterized by high dimensionality, class imbalance, and noise, make it challenging for standalone classifiers to maintain high predictive accuracy. Ensemble learning, by integrating multiple models through bagging, boosting, or stacking, offers a more robust and generalizable approach. This study explores the …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 3, 2025 · pp. 26–33 Read article