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365 articles for “experimental approaches”
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Anisotropic Debye-Waller Factors and Debye Temperatures in Hexagonal Close-Packed Elements: A Comprehensive Compilation and Analysis
Abstract: In this study, we have investigated the anisotropic behavior of Debye-Waller factors (DWFs) and Debye temperatures (DTs) in three distinct materials: hexagonal rhenium (Re), osmium (Os), and thallium (Tl). We conducted a comparative analysis, aligning our experimental data on directional Debye temperatures with theoretical calculations. This exercise provided valuable insights into the concurrence between practical and theoretical approaches, thereby offering a critical evaluation of the accuracy and reliability of theoretical …
Published in Journal of Polymer & Composites · Vol. 11, Issue 12, 2023 · pp. 32–39 Read article
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Computational Approaches to Understanding Cellular Signaling Pathways
Abstract: Cellular signaling pathways are fundamental in regulating vital processes, such as cell growth, differentiation, and apoptosis. The intricate and interconnected nature of these signaling networks requires sophisticated methods for their analysis. Computational approaches, including mathematical modeling, network analysis, and machine learning, have revolutionized the way researchers analyze and simulate cellular signaling. This article provides a comprehensive overview of computational strategies employed to model signaling pathways, with a focus on integrating …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 8–13 Read article
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Hybrid Quantum-Classical Reinforcement Learning Enabled Thermal-Aware Electronic Design Automation Framework for Energy-Efficient Next-Generation VLSI Systems Applications
Abstract: Modern Very Large-Scale Integration (VLSI) systems are becoming more complicated, which has increased need for sophisticated Electronic Design Automation (EDA) frameworks that can concurrently optimise thermal behaviour, power consumption, and performance. This study proposes a Hybrid Quantum-Classical Reinforcement Learning (HQCRL) Enabled Thermal-Aware EDA Framework for next-generation energy- efficient VLSI systems. The proposed framework integrates quantum-inspired optimization techniques with classical reinforcement learning algorithms to address the challenges of placement, routing, and …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 2, 2026 Read article
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A Hybrid Mathematical Model for Epidemic Outbreak Forecasting Using Machine Learning and Cloud Computing
Abstract: The increasing frequency of infectious disease outbreaks has emphasized the necessity for intelligent epidemic surveillance systems capable of predicting disease spread at an early stage. Conventional outbreak detection approaches rely heavily on delayed statistical reporting and manual monitoring techniques, resulting in reduced responsiveness during critical periods. This paper presents a mathematical predictive framework for epidemic outbreak detection using machine learning and cloud computing technologies. The proposed framework integrates the Susceptible–Infected–Recovered …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 01–06 Read article
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Optimizing Routing and Placement of VLSI Circuits with Differential Algorithms and Neural Networks
Abstract: The performance of modern VLSI systems is heavily influenced by power constraints, necessitating precise power estimation and effective optimization techniques. Traditional methods, such as gate-level simulations, are often slow and computationally intensive. This paper introduces DRPENN (Differential Algorithm for Routing and Placement Optimization using Neural Networks), an innovative solution that combines a Switching Activity Estimator (SAE) with a neural network-assisted differential algorithm. By leveraging toggle rates from simulations to train …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 2, 2024 · pp. 14–20 Read article
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Artificial Neural Network Based Prediction of Impact Loads and Thickness in CFRP and GFRP Composite Laminates
Abstract: Recent technological advancements, particularly the integration of neural networks, have facilitated a predictive approach to complex engineering problems, especially those involving composite materials with directional properties. The scarcity of literature on predicting impact damage using experimental and ultrasonic flaw detection data motivated this study. Experimental assessment of impact damage on carbon fiber/epoxy (CFRP) and glass fiber/epoxy (GFRP) composites was conducted using low-velocity drop weight impact testing. Damage assessment employed an …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 2, Issue 1, 2024 · pp. 34–45 Read article
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Enhancing Dimensional Accuracy of Affordable 3D-Printed Objects Via Solid Model Tuning For Industrial Manufacturing
Abstract: In the industrial applications of 3D printing (3DP) technologies, achieving precise dimensional accuracy and precision as well as improving surface quality are essential goals. With a focus on cost-effective engineering applications, this experimental research examines how solid model geometry tuning improves the internal and exterior dimensional accuracy of inexpensive 3DP technologies. Dimensional errors in the X, Y, and Z directions were meticulously measured on 3D parts made using Material Extrusion/Fused …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 201–210 Read article
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Conceptualization of An Intelligent Decision Framework for Control Factors and Weld Quality Prediction
Abstract: To improve the robot's welding quality, control welding precision, optimize welding parameters, realize continuous welding quality database optimization, and increase welding defect detection, a fuzzy neural network-based intelligent decision-making system must be built. This study demonstrates how fuzzy control theory and BP neural networks may be used to identify welding issues and enhance process variables. The experimental findings indicate that, with seam classification accuracy close to 90%, enhancing welding parameters …
Published in Journal of Polymer & Composites · Vol. 11, Issue 6, 2023 · pp. 10–19 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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Experimental and Process Optimization Study on Thermal Stress Reduction in TiC–Steel Brazed Joints Using Polymer-Derived Composite Interlayers
Abstract: In this, an experimental investigation aimed at reducing crack formation due to thermal stress in TiC-steel brazed joints through optimization of key process parameters is presented. The primary objective was to develop an integrated and reliable brazing strategy by examining the effects of filler material selection, brazing gap, cooling conditions and type of flux. In this study, polymer-derived composite interlayers were developed through controlled synthesis and nanocomposite engineering to mitigate …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 524–540 Read article
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Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Multi-Parameter Biomedical Sensor-Based Mental State Classification Using EEG And Deep Learning Techniques
Abstract: With mental health concerns becoming increasingly widespread, there is a strong need for systems that can monitor conditions like stress, anxiety, and fatigue in a continuous and non- invasive manner. This research proposes a novel multi-parameter biomedical sensing framework for mental state classification by integrating electroencephalography (EEG) signals with physiological parameters, including body temperature acquired using LM35 sensors, heart rate from pulse sensors, and blood oxygen saturation (SpO₂) measurements. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 Read article
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Enhancing Maintenance Decision-Making in Thermal Power Plants Using Generative AI-Based Fault Diagnosis
Abstract: The growing complexity of operation and power consumption of thermal power stations involve the need to have intelligent fault diagnosis systems that can be used to guarantee reliability and safety in operation. In this research, a Generative AI (GenAI)-based hybrid architecture of early fault detection and predictive maintenance is proposed to improve the decision-making process of the maintenance team. The data-driven analytic approach combines methods of data-driven analytics, Generative AI …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 25–33 Read article
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A Secure Storage Model with Authentication and Optimal Key Generation Based Encryption
Abstract: In digital forensics, ensuring the secure storage of digital evidence is crucial. This paper introduces a new method that uses advanced encryption and key generation techniques to protect digital evidence throughout an investigation. Cloud forensics, a modern approach to digital forensics, aims to safeguard evidence from online hacking. However, storing all evidence in one central location can reduce its reliability. To address this, we propose a digital forensics architecture for …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 7–13 Read article
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Engine Performance Analysis of Cottonseed Based Biodiesel Using Design Expert Statistical Based Tool
Abstract: Biodiesel is a biofuel acquired by substance forms from vegetable oils or creature fats and liquor that can be utilized in diesel engines alone or mixed with diesel oil. It is characterized as the mono-alkyl esters of unsaturated fats got from vegetable oils or creature fats. In basic words biodiesel is the item that gotten when vegetable oil or creature fat is artificially responded with a liquor to deliver unsaturated …
Published in International Journal of Industrial and Product Design Engineering · Vol. 1, Issue 1, 2023 · pp. 1–5 Read article
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A Review of Drug Design Techniques Assisted by Computers to Combat Diabetes
Abstract: Diabetes mellitus is a global health concern characterized by chronic hyperglycemia and associated complications. The creation of innovative medicines with enhanced efficacy and safety profiles continues to be a top focus, notwithstanding improvements in treatment. A useful method in drug development, computer-aided drug design (CADD) makes it easier to identify possible therapeutic candidates and optimise lead molecules. An extensive synopsis of CADD tactics used in the fight against diabetes is …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 1, 2025 · pp. 1–10 Read article
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Design and Assessment of Fixed Dose Combination Containing Fenofibrate and Pravastatin Sodium in Tablet Formulation: A Bioinformatics Approach
Abstract: The aim of this is study is to formulate and evaluate fixed dose combination of Fenofibrate and Pravastatin sodium in tablet dosage for the treatment of Dyslipidemia. For the formulation and optimization of fenofibrate layer, two factor three level factorial design was used as experimental design for optimization with a minimum of nine run. All the nine trial (F1–F9) has been formulated according to the experimental design by wet granulation …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 1, 2024 · pp. 1–20 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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A True Experimental Study to Assess the Effectiveness of Cognitive Behavioral Therapy on Low Self-Esteem Among B.Sc. 1St Year Students in Pt. Jwala Prasad Upadhyay Govt. College Patna, Korea (C.G.)
Abstract: Self-esteem is vital for an individual’s well-being and quality of life. Struggling with low self-esteem can lead to negative behaviors and unfavorable outcomes. Cognitive behavioral therapy (CBT), a well-established psychological approach, effectively addresses mental health issues like low self-esteem. By focusing on unhelpful thought patterns and behaviors, CBT supports individuals in fostering a more positive self-image and enhancing emotional health. This study aimed to evaluate the effectiveness of CBT in …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 1, 2025 · pp. 21–24 Read article
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Integrated Analysis of Stress Patterns in Transparent Polycarbonate Specimens: A Comparative Study between Photoelasticity and FEA Simulation for Compact Circular Testing
Abstract: Photoelasticity stands as a robust experimental technique within the realms of mechanics and materials science, offering a means to visually assess and analyze stress distribution within materials possessing transparency or translucency. This method, a non-destructive testing approach, involves the visualization of stress on a model subjected to a load, leveraging the unique property of materials known as birefringence or double refraction. The procedure entails the careful selection of a suitable …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 79–87 Read article