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Relative magnetic field and slipping effect on Casson dusty fluid of two phase fluctuating flow over inclined parallel plate

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South African Journal of Chemical engineering 2023年 44卷 135-146页

作者： khan, Dolat Kumam, Poom Kumam, Wiyada Suttiarporn, Panawan Rehman, Ali Fixed Point Research Laboratory Fixed Point Theory and Applications Research Group Center of Excellence in Theoretical and Computational Science (TaCS-CoE) Faculty of Science King Mongkut's University of Technology Thonburi (KMUTT) 126 Pracha Uthit Rd. Bang Mod Bangkok Thung Khru 10140 Thailand Center of Excellence in Theoretical and Computational Science (TaCS-CoE) Faculty of Science King Mongkut's University of Technology Thonburi (KMUTT) 126 Pracha Uthit Rd. Bang Mod Bangkok Thung Khru 10140 Thailand Applied Mathematics for Science and Engineering Research Unit (AMSERU) Program in Applied Statistics Department of Mathematics and Computer Science Faculty of Science and Technology Rajamangala University of Technology Thanyaburi (RMUTT) Pathum Thani 12110 Thailand Faculty of Science Energy and Environment King Mongkut's University of Technology North Bangkok Rayong Campus Rayong 21120 Thailand Special Interest Group for Modelling and Data Analytics Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu Kuala Nerus 21030 Malaysia

Due to its significant applications in magnetic devices for cell separation, magnetic drugs for cancer tumor treatment, blood flow adjustment during surgery, magnetic endoscopy, and fluid pumping in industrial and engineering processes, magnetohydrodynamics (MHD) has a wide range of applications. Therefore, the aim of this study to investigate the Relative Magnetic Field and slipping effect on Casson dusty fluid of two-phase fluctuating flow over inclined parallel plate. More exactly, the relative magnetic phenomena are fixed relatively to the plate (MFFRP) or fixed relatively to the fluid (MFFRF). The mathematical modeling was established as the set of partial differential equations for dusty Casson fluid. Buckingham's pi theorem is used to find out the dimensionless variables, to make our system dimensionless. The solution in perturb form is to find out by incorporating Poincare–Lighthill perturbation technique (PLPT). To know in-depth different parameters the graphical results for both velocities are plotted with the help of software Mathcad- 15. It is clearly detected that the relative magnetic field performs a vital part in the fluid as well as particle motion. Moreover, the relative magnetic field play a vital role in the decreasing of skin friction of both plates. © 2023

关键词： Brinkman fluid Dust particles Fluctuating vertical plate Inclined relative magnetic field PLPT

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Physique- Based Human Activity Recognition Using Deep Learning Approaches and Smartphone Sensors 8

Physique- Based Human Activity Recognition Using Deep Learni...

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Joint 8th International Conference on Digital Arts, Media and Technology and 6th ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications engineering, ECTI DAMT and NCON 2023

作者： Pravesjit, Sakkayaphop Jantawong, Ponnipa Jitpattanakul, Anuchit Mekruksavanich, Sakorn School of Information and Communication Technology Department of Information Technology University of Phayao Phayao Thailand School of Information and Communication Technology Department of Computer Engineering University of Phayao Phayao Thailand King Mongkut's University of Technology North Bangkok Intelligent and Nonlinear Dynamic Innovations Research Center Department of Mathematics Faculty of Applied Science Bangkok Thailand

ISBN: (纸本)9798350396546

Understanding human actions via the analysis of sensor data captured by wearable sensors is the goal of the complex subject of study known as sensor-based human activity recognition (S-HAR). Human participants' characteristics are only periodically included in deep learning (DL) approaches to S-HAR. Recognizing people was challenging for these DL methods because of the variety of physical characteristics people have. To address this challenge, we introduce a physique-based S-HAR architecture that could support deep learning networks to achieve higher identification a ccuracies a nd F1-scores. The HARSense dataset, a publicly available benchmark S-HAR dataset that compiles raw sensor data acquired from smartphones, was employed to build and evaluate five DL networks. A ccording to the experiments, the five models' detection performance improves dramatically when given access to biological data. © 2023 IEEE.

关键词： Classification (of information)

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An Automatic CNN-based Face Mask Detection Algorithm Tested During the COVID-19 Pandemics

An Automatic CNN-based Face Mask Detection Algorithm Tested ...

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2022 International Conference of Yearly Reports on Informatics, mathematics, and engineering, ICYRIME 2022

作者： De Magistris, Giorgio Iacobelli, Emanuele Brociek, Rafal Napoli, Christian Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Roma00185 Italy Department of Mathematics Applications and Methods for Artificial Intelligence Faculty of Applied Mathematics Silesian University of Technology Gliwice44-100 Poland Institute for Systems Analysis and Computer Science Italian National Research Council Via dei Taurini 19 Roma00185 Italy

The ongoing COVID-19 pandemic has highlighted the importance of wearing face masks as a preventive measure to reduce the spread of the virus. In medical settings, such as hospitals and clinics, healthcare professionals and patients are required to wear surgical masks for infection control. However, the use of masks can hinder facial recognition technology, which is commonly used for identity verification and security purposes. In this paper, we propose a convolutional neural network (CNN) based approach to detect faces covered by surgical masks in medical settings. We evaluated the proposed CNN model on a test set comprising of masked and unmasked faces. The results showed that our model achieved an accuracy of over 96% in detecting masked faces. Furthermore, our model demonstrated robustness to different mask types and fit variations commonly encountered in medical settings. Our approaches reaches state of the art results in terms of accuracy and generalization. © 2022 Copyright for this paper by its authors.

关键词： COVID-19

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A Resilient Distributed Algorithm for Solving Linear Equations

arXiv

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arXiv 2023年

作者： Zhu, Jingxuan Velasquez, Alvaro Liu, Ji The Department of Applied Mathematics and Statistics Stony Brook University United States The Department of Computer Science University of Colorado Boulder United States The Department of Electrical and Computer Engineering Stony Brook University United States

This paper presents a resilient distributed algorithm for solving a system of linear algebraic equations over a multi-agent network in the presence of Byzantine agents capable of arbitrarily introducing untrustworthy information in communication. It is shown that the algorithm causes all non-Byzantine agents' states to converge to the same least squares solution exponentially fast, provided appropriate levels of graph redundancy and objective redundancy are established. An explicit convergence rate is also provided. Copyright © 2023, The Authors. All rights reserved.

关键词： Redundancy

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Numerical Approach of Laser-Induced Spherical Microcavitation Bubbles: Effect of Enthalpy

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Bulletin of the Russian Academy of sciences: Physics 2024年第Suppl 3期88卷 S287-S292页

作者： Ali F. Abu-Bakr Abu-Nab, Ahmed K. AbuShaeer, Zain Department of Mathematics and Computer Science Faculty of Science Menoufia University Shebin El-Koom32511 Egypt Phystech School of Applied Mathematics and Informatics Moscow Institute of Physics and Technology Dolgoprudny Moscow141700 Russia Center for Photonics and 2D Materials Moscow Institute of Physics and Technology Dolgoprudny141700 Russia Department of Basic Science Higher Institute of Engineering and Technology Kafrelsheikh33511 Egypt

Abstract: Over the past decades, interest has increased in studying different techniques to detect the importance of microbubbles in many industrial and medical applications such as mechanisms of hydraulic machinery cavitation erosion, histotripsy, and lithotripsy. The behavior from early irregular oscillations to late regular oscillations of spherical microcavitation bubbles produced by lasers in water was studied by means of plasma photography. Repetition of such delayed oscillations results in quantities of gas/vapour inside the spherical bubbles. Using the modified Gilmore model of cavitation microbubble dynamics, calculations were made for the laser pulse energy, microbubble radius behavior, and microbubble growth rate. Additionally, the pressure evolution inside the bubble, and pressures distribution surrounding of microbubbles in liquid are investigated under the effect of different values of initial cavitation of microbubble radius. The effect of enthalpy is considered into account. The proposed model is solved numerically using numerical techniques as a finite difference method. In addition, the radius of the microbubbles is calculated as a function of time under the influence of the initial radius of these laser-induced microcavitations. Moreover, some physical properties and numerical calculations of the presented mathematical model for cavitation induced by lasers bubbles are deduced, analyzed and investigated. © Pleiades Publishing, Ltd. 2024.

关键词： Cavitation

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Time and frequency domain low order, low frequency approximation of mechanical systems

arXiv

引用

arXiv 2024年

作者： Zwart, Hans Veldman, Daniël W.M. Sharifi, Sahar F. the Department of Applied Mathematics Faculty of Electrical Engineering Mathematics and Computer Science University of Twente P.O. Box 217 Enschede7500 AE Netherlands The Netherlands the Department of Mechanical Engineering Eindhoven University of Technology P.O. Box 513 Eindhoven5600 MB Netherlands the Department of Data Science Friedrich-Alexander Universität Erlangen-Nürnberg Bavaria Erlangen91052 Germany the Department of Applied Mathematics Faculty of Electrical Engineering Mathematics and Computer Science University of Twente P.O. Box 217 Enschede7500 AE Netherlands The Netherlands. She is now with TEMPRESS Radeweg 31 MD Vaassen8171 Netherlands

Control design for linear, time-invariant mechanical systems typically requires an accurate low-order approximation in the low frequency range. For example a series expansion of the transfer function around zero consisting of a mass, velocity, and compliance term. Because computing such a series expansion of the transfer function can be cumbersome, a new method to compute low-order approximations of mechanical systems is developed in this paper. The method does not require an explicit expression for the transfer function, which is not always available for infinite-dimensional systems. The advantages of the proposed method is demonstrated in three *** Codes 93B11, 93C20, 93C05, 93C80, 93C95 © 2024, CC BY.

关键词： Transfer functions

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A Deep Learning-based Model for Human Activity Recognition using Biosensors embedded into a Smart Knee Bandage 9th

A Deep Learning-based Model for Human Activity Recognition u...

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9th International Conference on Information Technology and Quantitative Management, ITQM 2022

作者： Mekruksavanich, Sakorn Jantawong, Ponnipa Jitpattanakul, Anuchit Department of Computer Engineering School of Information and Communication Technology University of Phayao Phayao56000 Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Department of Mathematics Faculty of Applied Science King Mongkut's University of Technology North Bangkok Bangkok Thailand

Today, biosensors are effectively utilized in illness detection, prevention, rehabilitation, patient medical monitoring, and personal health promotion. The advancement of biosensing technology offers rigorous methods for measuring an individual's motor function, which contributes significantly to restoring motor function. An smart knee bandage was recently designed to analyze and decode diverse biosignals recorded by knee bandage-integrated biosensors. This research aims to examine human activity recognition (HAR) using biosignals gathered by a smart knee bandage. To accomplish this, a deep residual neural network was established for biosensor-based HAR. For performance assessment, we utilized a significant public biosensor dataset known as the CSL-SHARE dataset, which gathers electromyography (EMG), electrogoniometer (EGM), and inertial measurement unit (IMU) signals of individuals completing 22 simplex and complicated everyday tasks. Five-fold cross-validation was used to train and assess deep learning models. According to our findings, integrating features derived from the EMG, EGM, and IMU signal produced the maximum accuracy of 91.60% and the highest F1-score of 92.13%. © 2022 The Authors. Published by Elsevier B.V.

关键词： Biosensors

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AI-Driven Drug Discovery: Unravelling the Potential of Generative Adversarial Networks (GANs) in Pharmaceutical Research

AI-Driven Drug Discovery: Unravelling the Potential of Gener...

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Technological Advancements in Computational sciences (ICTACS), International Conference on

作者： Srinivasa Rao Burri Mamadou Yero Diallo Lakshay Sharma Vishal Dutt Western Union Denver CO USA Computer Science & Engineering Sharda University Greater Noida India Computer Science & Applied Mathematics Indraprastha Institute of Information Technology Delhi India Department of CSE Chandigarh University Mohali Punjab India

This paper examines how AI has revolutionised drug development and medical research using the ChEMBL dataset. The primary study areas are AI-driven therapeutic target identification., computational approaches in drug development., drug repurposing for COVID-19 therapies., and AI methods for natural leather flaw detection. Target selection must balance novelty and confidence., and AI-driven therapeutic target identification is considered. Structure-based virtual screening and profound learning predictions of ligand properties and target activities are considered for application in scaling up to broader chemical spaces. AI is used to discover new links between drugs., targets., and diseases and treat COVID-19. The paper also highlights this field's enforcement challenges and offers solutions. A Generative Adversarial Network (GAN)-based automatic flaw identification system for natural leather is another topic of study. The results show that the suggested strategy is economical and accurate., despite limitations and biases. AI has revolutionised medical diagnostics., medication development., and precision medicine., making this work meaningful. This paper”s findings offer a cross-disciplinary perspective on artificial intelligence's potential in healthcare., revealing knowledge gaps and suggesting further research.

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BlockCSDN: Towards Blockchain-Based Collaborative Intrusion Detection in Software Defined Networking

BlockCSDN: Towards Blockchain-Based Collaborative Intrusion ...

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作者： Li, Wenjuan Wang, Yu Meng, Weizhi Li, Jin Su, Chunhua Institute of Artificial Intelligence and Blockchain Guangzhou University China Department of Electronic and Information Engineering The Hong Kong Polytechnic University China Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark University of Aizu Aizuwakamatsu-shi965-8580 Japan

To safeguard critical services and assets in a distributed environment, collaborative intrusion detection systems (CIDSs) are usually adopted to share necessary data and information among various nodes, and enhance the detection capability. For simplifying the network management, software defined networking (SDN) is an emerging platform that decouples the controller plane from the data plane. Intuitively, SDN can help lighten the management complexity in CIDSs, and a CIDS can protect the security of SDN. In practical implementation, trust management is an important approach to help identify insider attacks (or malicious nodes) in CIDSs, but the challenge is how to ensure the data integrity when evaluating the reputation of a node. Motivated by the recent development of blockchain technology, in this work, we design BlockCSDN - a framework of blockchain-based collaborative intrusion detection in SDN, and take the challenge-based CIDS as a study. The experimental results under both external and internal attacks indicate that using blockchain technology can benefit the robustness and security of CIDSs and SDN. © 2022 The Institute of Electronics, Information and Communication Engineers.

关键词： Blockchain

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From Concept to Manufacturing: Evaluating Vision-Language Models for engineering Design

arXiv

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arXiv 2023年

作者： Picard, Cyril Edwards, Kristen M. Doris, Anna C. Man, Brandon Giannone, Giorgio Alam, Md Ferdous Ahmed, Faez Department of Mechanical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Applied Mathematics and Computer Science Technical University of Denmark Lyngby2800 Denmark

engineering design is undergoing a transformative shift with the advent of AI, marking a new era in how we approach product, system, and service planning. Large language models have demonstrated impressive capabilities in enabling this shift. Yet, with text as their only input modality, they cannot leverage the large body of visual artifacts that engineers have used for centuries and are accustomed to. This gap is addressed with the release of multimodal vision-language models (VLMs), such as GPT-4V, enabling AI to impact many more types of tasks. Our work presents a comprehensive evaluation of VLMs across a spectrum of engineering design tasks, categorized into four main areas: Conceptual Design, System-Level and Detailed Design, Manufacturing and Inspection, and engineering Education Tasks. Specifically in this paper, we assess the capabilities of two VLMs, GPT-4V and LLaVA 1.6 34B, in design tasks such as sketch similarity analysis, CAD generation, topology optimization, manufacturability assessment, and engineering textbook problems. Through this structured evaluation, we not only explore VLMs’ proficiency in handling complex design challenges but also identify their limitations in complex engineering design applications. Our research establishes a foundation for future assessments of vision language models. It also contributes a set of benchmark testing datasets, with more than 1000 queries, for ongoing advancements and applications in this field. Copyright © 2023, The Authors. All rights reserved.

关键词： Visual languages

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