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Entropically damped artificial compressibility for the discretization corrected particle strength exchange method in incompressible fluid mechanics

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arXiv 2023年

作者： Singh, Abhinav Sbalzarini, Ivo F. Obeidat, Anas Technische Universität Dresden Faculty of Computer Science Dresden Germany Max Planck Institute of Molecular Cell Biology and Genetics Dresden Germany Center for Systems Biology Dresden Dresden Germany Cluster of Excellence Physics of Life TU Dresden Dresden Germany Department of Engineering Institute of Computational Engineering University of Luxembourg Luxembourg

We present a consistent mesh-free numerical scheme for solving the incompressible Navier-Stokes equations. Our method is based on entropically damped artificial compressibility for imposing the incompressibility constraint explicitly, and the Discretization-Corrected Particle Strength Exchange (DC-PSE) method to consistently discretize the differential operators on mesh-free particles. We further couple our scheme with Brinkman penalization to solve the Navier-Stokes equations in complex geometries. The method is validated using the 3D Taylor-Green vortex flow and the lid-driven cavity flow problem in 2D and 3D, where we also compare our method with hr-SPH and report better accuracy for DC-PSE. In order to validate DC-PSE Brinkman penalization, we study flow past obstacles, such as a cylinder, and report excellent agreement with previous studies. Copyright © 2023, The Authors. All rights reserved.

关键词： Navier Stokes equations

A Novel Approach for DDoS Attack Detection Using Big Data and Machine Learning

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A Novel Approach for DDoS Attack Detection Using Big Data an...

2021 International Conference on Smart Systems and Advanced Computing, SysCom 2021

作者： Gaurav, Akshat Zhou, Zhili Chui, Kwok Tai Colace, Francesco Chaurasia, Priyanka Hsu, Ching-Hsien Ronin Institute MontclairNJ07043 United States School Engineering Research Center of Digital Forensics Ministry of Education School of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China Hong Kong University of Salerno Italy Ulster University Magee campus Londonderry United Kingdom Department of Computer Science and Information Engineering Asia University Taiwan Department of Computer Science and Information Engineering National Chung Cheng University Taiwan Department of Medical Research China Medical University Hospital China Medical University Taiwan

Due to the developemt in the latest digital technologies, internet service use has surged recently. In order for these online businesses to succeed, they must be able to consistently and effectively supply their services. As a result of the DDoS assault, online sources are impacted in terms of both their availability and their computational capacity. DDoS attacks are useful for cyber-attackers since there is no effective techniqque for the identification of them. In recent years, researchers have been experimenting with duffernet latest techniques like machine learning (ML) approaches to see whether they can build effective methods for detecting DDoS assaults. Machine learning and big data are used to identify DDoS assaults in this research paper. © 2021 Copyright for this paper by its authors.

关键词： Machine learning

Design of Electronically Steerable High Mode Dielectric Resonator Antenna using PIN Diode 2

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Design of Electronically Steerable High Mode Dielectric Reso...

2nd International Conference on Broadband Communications, Wireless Sensors and Powering, BCWSP 2020

作者： Wei, Chew Kew Jusoh, Muzammil Sabapathy, Thennarasan Osman, Mohamed Nasrun Mustafa, W.A. Alaydrus, Mudrik Awal, Md Rabiul Rahim, Hasliza A. Yasin, Mohd Najib Mohd Center of Excellence School of Computer and Communication Engineering Perlis Malaysia Department of Electronics and Instrumentation Kuala Trengganu Malaysia Universitas Mercu Buana Department of Electrical Engineering Jakarta Indonesia

ISBN: (纸本)9781728174495

This paper presents a reconfigurable beam dielectric resonator antenna (DRA) at 2.4 GHz by adopting the yagi-uda concept. Rectangular dielectric resonator antenna (RDRA) have been chosen as the radiator and fed by slot aperture. The antenna is designed in Taconic substrate with permittivity of 2.2. Firstly, a single antenna with two different modes is designed and investigated. The best performance mode in term of gain is then used to design the single driven RDRA with two parasitic RDRA, connected with the four RF pin diode BAR50-02V as switch. The analysis of the gap between driven and parasitic element is investigated. Four different types of switch configuration have been carried out to identify the performance of antenna in different cases. Depending on the switch configurations, the designed antenna can achieved highest gain of 7.386 dB and have steering angle capability at-42°, 42°,-54° and 54°. © 2020 IEEE.

关键词： Microwave antennas

MedFACT: Modeling Medical Feature Correlations in Patient Health Representation Learning via Feature Clustering

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arXiv 2022年

作者： Ma, Xinyu Chu, Xu Wang, Yasha Yu, Hailong Ma, Liantao Tang, Wen Zhao, Junfeng Key Laboratory of High Confidence Software Technologies Ministry of Education Beijing China Department of Computer Science Tsinghua University Beijing China School of Computer Science Peking University Beijing China National Engineering Research Center of Software Engineering Peking University Beijing China Division of Nephrology Peking University Third Hospital Beijing China

In healthcare prediction tasks, it's essential to exploit the correlations between medical features and learn better patient health representations. Existing methods try to estimate feature correlations only from data, or increase the quality of estimation by introducing task-specific medical knowledge. However, such methods either are difficult to estimate the feature correlations due to insufficient training samples, or cannot be generalized to other tasks due to reliance on specific knowledge. There are medical researches revealing that not all the medical features are strongly correlated. Thus, to address the issues, we expect to group up strongly correlated features and learn feature correlations in a group-wise manner to reduce the learning complexity without losing generality. In this paper, we propose a general patient health representation learning framework MedFACT. We estimate correlations via measuring similarity between temporal patterns of medical features with kernel methods, and cluster features with strong correlations into groups. The feature group is further formulated as a correlation graph, and we employ graph convolutional networks to conduct group-wise feature interactions for better representation learning. Experiments on two real-world datasets demonstrate the superiority of MedFACT. The discovered medical findings are also confirmed by literature, providing valuable medical insights and explanations. Copyright © 2022, The Authors. All rights reserved.

关键词： Machine learning

Auto-ICell: An Accessible and Cost-Effective Integrative Droplet Microfluidic System for Real-Time Single-Cell Morphological and Apoptotic Analysis

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arXiv 2023年

作者： Wei, Yuanyuan Lin, Meiai Luo, Shanhang Abbasi, Syed Muhammad Tariq Tan, Liwei Cheng, Guangyao Bai, Bijie Ho, Yi-Ping Yuan, Scott Wu Ho, Ho-Pui Department of Biomedical Engineering The Chinese University of Hong Kong Shatin Hong Kong Department of Biomedical Engineering Shantou University Shantou China Department of Biomedical Engineering National University of Singapore Singapore Department of Electrical Engineering Tsinghua University Beijing China Electrical and Computer Engineering Department University of California Los AngelesCA90095 United States Centre for Biomaterials The Chinese University of Hong Kong Hong Kong Hong Kong Branch of CAS Center for Excellence in Animal Evolution and Genetics Hong Kong State Key Laboratory of Marine Pollution City University of Hong Kong Hong Kong

The Auto-ICell system, a novel, and cost-effective integrated droplet microfluidic system, is introduced for real-time analysis of single-cell morphology and apoptosis. This system integrates a 3D-printed microfluidic chip with image analysis algorithms, enabling the generation of uniform droplet reactors and immediate image analysis. The system employs a color-based image analysis algorithm in the bright field for droplet content analysis. Meanwhile, in the fluorescence field, cell apoptosis is quantitatively measured through a combination of deep-learning-enabled multiple fluorescent channel analysis and a live/dead cell stain kit. Breast cancer cells are encapsulated within uniform droplets, with diameters ranging from 70 μm to 240 μm, generated at a high throughput of 1,500 droplets per minute. Real-time image analysis results are displayed within 2 seconds on a custom graphical user interface (GUI). The system provides an automatic calculation of the distribution and ratio of encapsulated dyes in the bright field, and in the fluorescent field, cell blebbing and cell circularity are observed and quantified respectively. The Auto-ICell system is non-invasive and provides online detection, offering a robust, time-efficient, user-friendly, and cost-effective solution for single-cell analysis. It significantly enhances the detection throughput of droplet single-cell analysis by reducing setup costs and improving operational performance. This study highlights the potential of the Auto-ICell system in advancing biological research and personalized disease treatment, with promising applications in cell culture, biochemical microreactors, drug carriers, cell-based assays, synthetic biology, and point-of-care diagnostics. Copyright © 2023, The Authors. All rights reserved.

关键词： Drops

Normal Vector Direction-based 3D LiDAR Point Cloud Planar Surface Removal for Object Cluster Minimization in Human Activity Monitoring System

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Normal Vector Direction-based 3D LiDAR Point Cloud Planar Su...

IEEE Instrumentation and Measurement Technology Conference

作者： Nova Eka Budiyanta Eko Mulyanto Yuniarno Tsuyoshi Usagawa Mauridhi Hery Purnomo Dept. of Electrical Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia Dept. of Electrical Engineering Dept. of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Computer Science and Electrical Engineering Graduate School of Science and Technology Kumamoto University Kumamoto Japan Dept. of Electrical Engineering Dept. of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember University Center of Excellence on Artificial Intelligence for Healthcare and Society (UCE AIHeS) Surabaya Indonesia

The use of 3-Dimensional Light Detection and Ranging (3D LiDAR) point cloud as the alternative data to reduce privacy exposure in monitoring systems has been carried out in several studies. Unfortunately, various challenges in using point clouds intersect with the amount of data and computational costs. Several studies attempted to optimize the point cloud processing approach by segmenting the ground plane to get the object clusters separated. However, many unnecessary points can still burden the computation process. Since the ground plane mainly represents the horizontal planar plane on the x, y axis, this study tried to reduce the points on the vertical planar plane on the x, z and y, z axes with the x, y horizontal planar plane as well based on the surface normal vector direction of each point. The proposed approach has successfully reduced the raw point cloud by 79.29% removing the point cloud that indicates the planar surface of the three axes while maintaining the essential object of the monitoring system on the KITTI raw dataset. Therefore, the object cluster can be minimized, supporting the computational costs for further research in human activity monitoring systems.

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A Fast Geometric Regularizer to Mitigate Event Collapse in the Contrast Maximization Framework

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arXiv 2022年

作者： Shiba, Shintaro Aoki, Yoshimitsu Gallego, Guillermo Department of Electronics and Electrical Engineering Faculty of Science and Technology Keio University Kanagawa Japan Department of Electrical Engineering and Computer Science Technische Universität Berlin Berlin Germany Einstein Center Digital Future and Science of Intelligence Excellence Cluster Berlin Germany

Event cameras are emerging vision sensors and their advantages are suitable for various applications such as autonomous robots. Contrast maximization (CMax), which provides state-of-the-art accuracy on motion estimation using events, may suffer from an overfitting problem called event collapse. Prior works are computationally expensive or cannot alleviate the overfitting, which undermines the benefits of the CMax framework. We propose a novel, computationally efficient regularizer based on geometric principles to mitigate event collapse. The experiments show that the proposed regularizer achieves state-of-the-art accuracy results, while its reduced computational complexity makes it two to four times faster than previous approaches. To the best of our knowledge, our regularizer is the only effective solution for event collapse without trading off runtime. We hope our work opens the door for future applications that unlocks the advantages of event cameras. © 2022, CC BY.

关键词： Cameras

Fast Event-based Optical Flow Estimation by Triplet Matching

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arXiv 2022年

Event cameras are novel bio-inspired sensors that offer advantages over traditional cameras (low latency, high dynamic range, low power, etc.). Optical flow estimation methods that work on packets of events trade off speed for accuracy, while event-by-event (incremental) methods have strong assumptions and have not been tested on common benchmarks that quantify progress in the field. Towards applications on resource-constrained devices, it is important to develop optical flow algorithms that are fast, light-weight and accurate. This work leverages insights from neuroscience, and proposes a novel optical flow estimation scheme based on triplet matching. The experiments on publicly available benchmarks demonstrate its capability to handle complex scenes with comparable results as prior packet-based algorithms. In addition, the proposed method achieves the fastest execution time (> 10 kHz) on standard CPUs as it requires only three events in estimation. We hope that our research opens the door to real-time, incremental motion estimation methods and applications in real-world scenarios. © 2022, CC BY.

关键词： Cameras

Design and Deployment of a Simulation Platform: Case Study of an Agent-Based Model for Youth Suicide Prevention

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Design and Deployment of a Simulation Platform: Case Study o...

Simulation Winter Conference

作者： Joshua Huddleston Michael C. Galgoczy Kareem A. Ghumrawi Philippe J. Giabbanelli Ketra L. Rice Nisha Nataraj Margaret M. Brown Christopher R. Harper Curtis S. Florence Department of Computer Science & Software Engineering Miami University Oxford OH USA National Center for Injury Prevention and Control Centers for Disease Control and Prevention (CDC) Atlanta GA USA

ISBN: (纸本)9781665476621

Research has examined the process of engaging end-users in co-designing a simulation model and using it within workplace settings. In contrast, few studies document the software development aspect of creating, packaging, and deploying a simulation platform that satisfies end-users' needs. In this case study, we detail these aspects regarding a platform involving Agent-Based Modeling for youth suicide prevention. Goals and constraints are detailed in three categories of needs, each showing how competing demands are addressed via software solutions: 1) data, encompassing data security (e.g., no direct access to individual-level data) and data updates (e.g., changing a model's initialization without coding expertise); 2) deployment, to satisfy security protocols (e.g., secure intranet communications) and the end-users' experience (e.g., ease of installation); 3) accessibility, ensuring that individuals with impairments are not excluded from using simulations. By presenting practical solutions to each category, our case study supports modelers in addressing their own deployment needs.

关键词： Protocols Filtering Employment Ecosystems Packaging software Data models