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365 articles for “experimental approaches”
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Revolutionizing Form and Function: Exploring 4D Printing as a Novel Manufacturing Approach for Complex Generative Structures and Customized Formworks
Abstract: This research delves into the transformative potential of 4D printing manufacturing technology, focusing on its innovative application in fabricating intricate generative and computational structures for adaptable formwork in both individualized and mass-customized scenarios. Spanning the interdisciplinary realms of digital design, digital fabrication, and material science, the study comprehensively explores the integration of these diverse fields. Utilizing generative algorithms and parametric design tools, the research employs simulations to realize complex patterns …
Published in International Journal of Manufacturing and Production Engineering · Vol. 1, Issue 2, 2023 · pp. 41–50 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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A Study on Friction Stir Processing Effected on Hardness and Tensile Properties When Single Pass and Double Pass Is Considered Using Al 6061 And Steel Material
Abstract: The principle of friction stir welding was initially employed to build the emerging technology known as friction stir processing, or FSP. FSP has shown to be a successful method of developing face mixes and increasing the material's mechanical parcels. Aluminum blends are among those accoutrements over which the FSP can be performed successfully. The study comprised the careful processing of steel and Al 6061 samples using both single and double …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 2, Issue 1, 2024 · pp. 16–23 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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Viscoelastic Behavior and Wrinkle Formation in Cotton- Polyester Garments: A Data-Driven Approach for Textile Care
Abstract: This study investigates the wrinkle behavior of cotton-polyester blended fabrics by analyzing data from over 1,200 store-handled garments. Integrating concepts from polymer chemistry and computer vision, it aims to establish a smart textile care framework based on fiber-specific wrinkle characteristics. The research identifies how cotton’s hydrophilic and non-elastic structure results in increased wrinkling, while polyester’s thermoplastic and crystalline properties enhance wrinkle resistance. Elastomeric fibers like Lycra contribute to wrinkle recovery …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 50–60 Read article
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Parametric optimization and validation of novel 3D scanning approach for sustainable manufacturing of patient-specific orthodontic retainers
Abstract: The purpose of the proposed study is to identify the ideal procedure parameters for 3D scanning a denture in order to produce customised orthodontic retainers that can be produced sustainably. However, pilot investigations rarely explore parameters like scanning angle, light intensity, or scanning distance. In order to lower acquisition error, the suggested study examines a method for forecasting the ideal values of the previously indicated scanning parameters. Based on the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 265–278 Read article
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Isolation and Evaluation of Aspergillus Niger : A Fungi Implicated in Infectious Diseases and its application as potential Biofertilizer
Abstract: In the quest to improve the agronomic effectiveness of Rock Phosphate (RP), a widely available and cost-effective phosphate fertilizer, this study aimed to overcome its limited solubility by isolating fungal strains capable of solubilizing rock phosphate. Soil samples were collected from Garhmukteshwar, Hapur, for the isolation process. Among several isolates, three strains exhibited the highest rock phosphate solubilization within a seven-day timeframe, coinciding with a significant decrease in soil pH. …
Published in Recent Trends in Infectious Diseases · Vol. 1, Issue 2, 2024 · pp. 29–34 Read article
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In Silico Exploration of Podophyllum Hexandrum-Derived Phytocompounds as Potential Therapeutics Against Small Cell Lung Cancer (SCLC): A Molecular Docking Approach
Abstract: Small Cell Lung Cancer (SCLC) is a fast-growing and aggressive type of lung cancer that spreads quickly strongly associated with smoking. It is characterized by symptoms, such as persistent cough, breathing difficulties, or hoarseness, though it can sometimes be asymptomatic which makes early detection challenging. The tumor suppressor gene TP53 is critical in regulating the cell cycle and preventing uncontrolled cell division. Mutations in TP53 result in the loss of …
Published in International Journal of Molecular Biotechnological Research · Vol. 3, Issue 1, 2025 · pp. 1–11 Read article
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AI-Designed Functionally Graded Polymer Composites for Multifunctional Thin Films
Abstract: The design of multifunctional polymer composite thin films requires simultaneous optimization of mechanical, optical, barrier, and thermal properties—objectives often in conflict when using conventional homogeneous materials. This study presents an artificial intelligence-driven framework for designing functionally graded material (FGM) architectures in polymer nanocomposite thin films. We integrated machine learning with physics-based modeling to optimize compositional gradients across film thickness, achieving superior performance compared to homogeneous and discrete multilayer alternatives. A …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1026–1041 Read article
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Computational Biomodeling: Transforming Drug Design with Advanced Simulations
Abstract: Computational biomodeling has emerged as a transformative approach in the field of drug discovery, significantly enhancing the efficiency and precision of identifying and optimizing potential drug candidates. This article explores the various computational techniques utilized in drug design, including molecular docking, molecular dynamics (MD) simulations, free energy calculations, and virtual screening, and examines how these methods collectively contribute to the drug development process. The integration of these advanced simulations allows …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 24–29 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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A Comparative Study of Inorganic and Natural Coagulants for Dairy Wastewater Treatment using Alum Sulphate and Moringa Oleifera
Abstract: The treatment of dairy wastewater is essential to reduce its environmental impact, particularly in terms of organic load and suspended solids. This study investigates the application of alum sulphate as an inorganic coagulant for dairy wastewater treatment and compares its effectiveness with the natural coagulant Moringa oleifera. The performance of both coagulants was evaluated based on key water quality parameters, including pH, Biochemical Oxygen Demand (BOD), Total Suspended Solids (TSS), …
Published in International Journal of Pollution: Prevention & Control · Vol. 3, Issue 1, 2025 · pp. 01–07 Read article
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Optimizing Manufacturing Processes with Taguchi Method in Production Engineering
Abstract: The Taguchi Method, pioneered by Genichi Taguchi, stands as a powerful optimization tool within the realm of production engineering. This paper delves into the principles, applications, and significance of the Taguchi Method in enhancing manufacturing processes. With a focus on minimizing variation and improving performance, this methodology plays a crucial role in addressing challenges faced by industries in their pursuit of operational excellence. The core components of the Taguchi Method, …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 1, Issue 2, 2023 · pp. 1–8 Read article
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Face Aging Using Generative Adversarial Network
Abstract: This project addresses the challenge of predicting how a person may look in the future or how they appeared in the past using a single photograph. While existing methods mainly focus on altering texture, they often neglect changes in head shape that naturally occur during the aging process, limiting their effectiveness, especially when applied to images of children. To tackle this issue, a novel approach is introduced that employs a …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 41–52 Read article
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Building Scalable Microservices with Micronaut, Kotlin, and AWS DynamoDB: A Comprehensive Architecture Study
Abstract: The evolution of enterprise software has trended steadily toward microservice architectures due to their inherent scalability and resilience advantages over monolithic systems. This research explores a comprehensive implementation approach using Micronaut, an innovative JVM-based framework specifically designed for resource-efficient microservices. The study combines Micronaut with Kotlin programming language and leverages AWS DynamoDB as a scalable NoSQL persistence layer, with Apache Kafka providing event-driven communication capabilities. We explore the critical role …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 2, 2025 · pp. 40–57 Read article
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Integrated Optimization of Solar Photovoltaic Systems Using Taguchi Method and Computational Fluid Dynamics for Enhanced Efficiency
Abstract: The transition to renewable energy demands efficient and reliable photovoltaic (PV) systems to meet rising global energy needs. This study presents an integrated optimization framework combining the Taguchi method and Computational Fluid Dynamics (CFD) to improve the thermal and electrical performance of solar PV systems. A structured experimental design using an L9 orthogonal array evaluates the influence of three key parameters—material type, panel thickness, and cooling mechanism—on system efficiency. Analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 10–25 Read article
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Data-Driven Life Prediction of Fiber-Reinforced Polymer Composites Using IoT Sensing and Machine Learning Algorithms
Abstract: The accurate prediction of fatigue life in fiber-reinforced polymer (FRP) composites remains a major challenge due to their nonlinear, multi-mechanism degradation behavior under variable loading conditions. This study presents a data-driven framework, H-LiProNet, which combines real-time IoT sensing with hybrid machine learning to estimate remaining useful life (RUL) in FRP composites. The proposed system integrates embedded Fiber Bragg Grating (FBG) and acoustic emission (AE) sensors to capture strain and damage …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 116–130 Read article
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Experimental Investigations on Aluminium Composites Materials Using Stir Casting Process
Abstract: In physical operations, accoutrements in motorcars and aeronautical machine factors, aluminium and its alloys are extensively used. In this study an effort is made to ameliorate the properties of aluminium essence matrix compound (A356) for manufacturing of machine rudiments taking High Tensile strength, Hardness, Wear resistance and low coefficient of friction, aluminium alloy (A356) reinforced with aluminium oxide, graphite and silicon carbide. In the current work, A356 as base metal …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 302–323 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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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