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1976 articles for “bending-mode piezoresistivity” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Synthesis and Evaluation of New Coumarin Derivatives for Inflammatory Bowel Disease Against DSS-Induced Acute Ulcerative Colitis Mice Model
Abstract: Objective: The discovery of the now numerous mouse models of intestinal inflammation has increased our understanding of the intestinal inflammation that occurs in inflammatory bowel disorders (IBD). This study aimed to investigate the use of a standardized animal model subjected to coumarin derivative treatment, and the action of synthesized molecule administration of dextran sodium sulphate (DSS)- induced colitis in experimental mice. Materials and Methods: We generated a variety of unique …
Published in Journal of Modern Chemistry & Chemical Technology Read article
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Continuous-Time Modelling of the Two-Input Fourth Order DC_DC Converter
Abstract: Two-input fourth-order integrated (TIFOI) converter is designed to process the power from two different sources Vg1 and Vg2. This converter facilitates regulation of dc-bus voltage and LVS current. In the power conversion process it performs bucking operation for first dc source Vg1, buck-boost operation for the second source Vg2. Power stage dynamics of the TIFOI converters is modeled using the state-space analysis. The system modelling plays an important role in …
Published in Journal of Control & Instrumentation Read article
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Artificial Neural Network Modelling to Optimize Micro-Drilling Parameters of ECDM of Developed Novel Zn/(Ag+Fe)-MMC
Abstract: Several engineering fields have increased their use of metal matrix composites (MMCs) in the past few years. Due to the increase in composites, the demand for accurate machining has also become important. Specifically, pertaining to biomaterial applications, accuracy factor with desired surface finish is critical. While the near-net shape manufacturing process has advanced, MMCs frequently require post-mould machining to achieve surface quality, and dimensional tolerances. In the present study, a …
Published in Journal of Polymer & Composites · Vol. 11, Issue 1, 2023 · pp. 01–13 Read article
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Designing a Novel Insider Threat Model for Enhanced Cybersecurity
Abstract: Designing a novel insider threat model is a critical imperative in the realm of cybersecurity. As organizations face an ever-expanding threat landscape, insider threats, whether deliberate or inadvertent, present a formidable challenge to the safeguarding of sensitive data and critical assets. This abstract encapsulates the significance, challenges, and innovations inherent in crafting an effective insider threat model for enhanced cybersecurity. The necessity for novel insider threat models arises from the …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 2, 2023 · pp. 24–27 Read article
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Describing Microbial Growth Rate in Solid Suspended Media using Monod and Haldane Models
Abstract: This work details the procedure for curve fitting the Monod and Haldane’s growth models in for solid suspended media such as food waste; in order to determine their parameters for solid suspended media such as food waste. Seven different batch runs; each with initial substrate concentration were studied at constant temperature. A modified method was used to quantify the mass of microbes during the rection process and data obtained were …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 11, Issue 1, 2024 Read article
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Deep Learning-Based Pneumonia Diagnosis: A Comparative Review of Models and Metrics
Abstract: Pneumonia is a common viral infection that affects a large percentage of people worldwide. It is more common in developing and impoverished areas because of factors like poor sanitation, crowded living quarters, pollution in the environment, and restricted access to medical facilities. In order to improve survival chances and gain access to therapeutic therapies, pneumonia must be diagnosed as soon as possible. A type of artificial intelligence called deep learning …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 Read article
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The Intersection of Bioinformatics and Cellular Function in Disease Modeling
Abstract: The integration of bioinformatics and cellular biology has revolutionized our understanding of disease mechanisms, offering unprecedented opportunities to model complex biological systems. Bioinformatics is an interdisciplinary field that merges biology, computer science, and statistics, offering advanced tools to analyze vast biological datasets. Cellular functions, including gene expression, protein interactions, and metabolic pathways, form the foundation of physiological and pathological states. Disruptions in these processes can result in diseases like cancer, …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 1–7 Read article
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Simulation and Analysis of Battery Pack Using the Multi Scale Multi-Domain Battery Model
Abstract: The creation of sophisticated simulation models has been made necessary by the need for reliable and effective battery packs in energy storage systems and electric vehicles. This study focuses on the simulation and analysis of battery packs using a multi-scale multi-domain battery model. The model enables a thorough knowledge of battery pack behavior across a range of operating situations by integrating the electricity, thermal, and mechanical domains. Multi-scale modeling bridges …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 2, 2024 · pp. 31–46 Read article
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Statistical Models for Predicting Genetic Variability and Disease Susceptibility
Abstract: Differences in genetics are key to understanding why some individuals are more prone to certain diseases than others. Recent advancements in genomic research, combined with statistical modeling techniques, have made significant strides in predicting disease risk based on genetic factors. This review explores the application of statistical models for predicting genetic variability and their role in disease susceptibility. We discuss traditional methods like linear regression and genome-wide association studies (GWAS), …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 30–34 Read article
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Affect of Finite Element Modelling on Static Behavior of Underwater Shell
Abstract: The objective of the present study is to compare and contrast different numerical models based on their mesh quality and material properties in predicting the response of an underwater shell under an external pressure of 1 MPa. Two different mesh qualities with the same element size are developed for solid geometries without and with slicing the solids at geometric discontinuities to enhance the element quality. From the static response of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 154–163 Read article
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Swarm Intelligence in Software Engineering: A Systematic Review of Crowd-Based Development Models
Abstract: The crowd-based software production model has emerged as a transformative paradigm, leveraging global collaboration, decentralized governance, and artificial intelligence (AI)-driven automation to develop software efficiently. Traditional software development models, characterized by centralized control and in-house teams, are increasingly giving way to distributed, community-driven efforts. Key advancements such as blockchain-based decentralized autonomous organizations (DAOs), AI-assisted coding and debugging, and edge computing applications are reshaping the landscape of software engineering. DAOs provide …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 2, 2025 · pp. 01–11 Read article
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A Review on Predicting Wear and Friction of PTFE Composites - Fillers to Machine Learning Models
Abstract: Polytetrafluoroethylene (PTFE) composites, a self-lubricating material with low friction, became an indispensable material in engineering applications where load carrying capacity and wear are crucial. The pure PTFE has poor mechanical strength and wear resistance which can be enhanced by the addition of fillers in appropriate volume fraction. The wear performance is dependent on various factors such as fillers, operating parameters, environmental conditions as well as manufacturing attributes. This makes the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 114–128 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
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Physical Modeling of Mass Transport Processes in Extraterrestrial Landscapes
Abstract: Currently the progress in physical models based on mass transport in both the Earth's surface and extraterresterial landscape has been growing. It is a frame work involving different natural and made made processes including aeline process, fluid flow process, magmal movement, Geomagnetic stroms, and clould flow modesl etc. These process encorporates Physical models and appraches which help to simulate, compute and experiment in order to reduce complexity. However, their operating …
Published in International Journal of Universe · Vol. 1, Issue 2, 2025 · pp. 47–54 Read article
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Kinematic and Dynamic Modelling of a 6-DOF Robotic Manipulator for Industrial Applications
Abstract: The rapid evolution of industrial automation has intensified the need for highly accurate, flexible, and intelligent robotic systems capable of operating in dynamic and demanding environments. Among these systems, six-degree-of-freedom (6-DOF) robotic manipulators have emerged as a versatile solution due to their superior dexterity, large workspace, and human-arm-like motion capabilities. This research focuses on the comprehensive kinematic and dynamic modelling of a 6-DOF robotic manipulator designed for various industrial tasks …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 2, 2025 · pp. 27–32 Read article
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Phase – Field Modeling of Brittle and Ductile Fracture Under Complex Loading Conditions
Abstract: Phase-field modeling has emerged as a powerful computational framework for predicting fracture behavior in engineering materials, offering a unified description of crack initiation, propagation, branching, and coalescence without the need for explicit crack tracking. This study presents an in-depth examination of phase-field modeling applied to both brittle and ductile fracture under complex loading conditions, including multiaxial stress states, cyclic loading, thermal gradients, and dynamic impact. The phase-field approach regularizes the …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 2, 2025 · pp. 13–18 Read article
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Combining Unstructured and Structured Clinical Data in a Hybrid Transformer Model to Enhance Cardiovascular Analytics and Clinical Decision- Making
Abstract: Since cardiovascular disease (CVD) continues to be a major global cause of morbidity and mortality, early and accurate risk prediction is essential for prompt intervention and individualized treatment. This study introduces a new hybrid transformer-based model that combines unstructured clinical narratives, structured data, and customized lifestyle characteristics. A comprehensive understanding of disease progression is made possible by the model's ability to capture contextual, temporal, and patient- specific insights through the …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 · pp. 30–37 Read article
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A Comparison of Different Generative AI Models
Abstract: Generative models have significantly advanced the field of artificial intelligence by allowing machines to produce complex and realistic outputs such as images, text, and other forms of data. Among the leading frameworks in this domain are generative adversarial networks (GANs), variational autoencoders (VAEs), and architectures based on Transformers. Each model offers specific benefits and drawbacks concerning design structure, training demands, and range of applications. This paper provides a detailed comparison …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 · pp. 16–22 Read article
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Fundamental Principles of Fluid Behavior and Emerging Trends in Modern Fluid Mechanics Research
Abstract: Fluid behavior forms the foundation of numerous engineering technology and scientific applications, including aerospace flows, energy systems, and environmental processes. This paper presents a comprehensive overview of the fundamental principles governing fluid behavior, with a strong emphasis on their relevance to recent trends in fluid mechanic’s research. Core concepts such as fluid statics, fluid dynamics, and conservation laws are discussed to establish a solid theoretical framework. The study further examines …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 1, 2026 · pp. 14–21 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