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检索条件"任意字段=2023 International Conference on Computer Science and Automation Technology, CSAT 2023"

共 69059 条记录，以下是1701-1710 订阅

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A Review of Adversarial Machine Learning for Cyber security in Intelligent Systems using Image Classification & Signal Classification Analysis 3

A Review of Adversarial Machine Learning for Cyber security ...

引用

3rd IEEE international conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Jahan, Tasneem Lnct University Department of Computer Science & Engineering Bhopal India

ISBN: (纸本)9798350343274

Machine learning models with adversarial examples must be trained to differentiate between genuine and invading data. Cyber computing technology and tools face huge intrusion attacks and malicious programs. Tampered QR code for online payments, malicious face and biometric detection, incorrect facial recognition, object and sign detection are the adversarial examples in real-life scenarios. Convolutional neural networks often fail to image classification tasks due to high vulnerability. The Intelligent systems comprising computer vision, self-driving cars, radio signals, IoT Devices, industrial production and automation are prone to cyber attack with adversarial data in machine learning models. The goal of this paper is to summarize the various Convolutional Neural Network models and Recurrent Neural Network approaches used in machine learning for malicious image classification. The analysis aims to identify the area of attacks using adversarial machine learning in cyber physical systems and intrusion detection systems. © 2023 IEEE.

关键词： Cybersecurity

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Use of Business Games in the Learning Process 64

Use of Business Games in the Learning Process

引用

2023 IEEE 64th international Scientific conference on Information technology and Management science of Riga Technical University, ITMS 2023

作者： Amolins, Janis Katalnikova, Sabina Prokofyeva, Natalya Uhanova, Marina Ziborova, Viktorija Riga Technical University Faculty of Computer Science and Information Technology Riga Latvia

ISBN: (纸本)9798350370294

This study is dedicated to issues related to the use of business games at Riga Technical University. This article contains three sections: the first introduces the concept of educational business games, the second describes business games used in the computer science and Information technology Faculty courses 'Algorithmization and Programming of Solutions' and 'Software Development Technologies', the third section presents the results of student surveys, their opinions about the use of business games in the educational process, as well as the impact of business games on academic performance. The authors of the study believe that the organization of business games is important for solving professional tasks of improving the quality of education and enhancing student motivation. © 2023 IEEE.

关键词： Software design

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Control-Oriented Aerodynamic Modeling with Automatic White-Box Structure Based on Dendrite Net 13

Control-Oriented Aerodynamic Modeling with Automatic White-B...

引用

13th IEEE international conference on CYBER technology in automation, Control, and Intelligent Systems, CYBER 2023

作者： Huang, Jun Liu, Ke Wang, Qingfeng Qiao, Wenyou Liu, Zhiqin Wang, Yaobin School of Computer Science and Technology Southwest University of Science and Technology Mianyang621010 China Southwest University of Science and Technology Research Center of Combustion Aerodynamics Mianyang621010 China

ISBN: (纸本)9798350315196

The establishment of an aerodynamic surrogate model is the basis of the optimization and control design for aerial vehicles. The fitting expression construction based on data relation relies on empirical studies to estimate polynomial structures, which is fast but troublesome in structure selection. The complexity of polynomial structure selection can be avoided by using large amounts of data to train the neural network with a large number of neurons, but the black box model of neural network is not conducive for optimization iteration due to its poor interpretability and large amounts of computation. In this study, a control-oriented aerodynamic modeling method with automatic white-box structure based on Dendrite Net is proposed to construct the explicit expressions with strong interpretability that does not depend on empirical studies. First, the Dendrite Net model is built to demonstrate that its prediction accuracy and training speed are better than the typical BP network. Second, by using the white-box property of Dendrite Net, the polynomial expression can be automatically constructed to predict aerodynamic performance based on the coefficient spectrum of the Dendrite Net. The experimental verification shows that the polynomial established in this paper is superior to the related method of artificial structural analysis, in terms of the accuracy of polynomial and the simplicity of expression construction. The proposed method has the advantages of fast computation, strong interpretability, accurate expression of results, and independent of empirical studies, which not only has the advantages of polynomial fitting and neural network fitting, but also overcomes their disadvantages. © 2023 IEEE.

关键词： Polynomials

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Performance of Data Segmentation ANN Model for Elemental Sulfur Solubility Prediction in Natural Gas Transportation Pipeline 15

Performance of Data Segmentation ANN Model for Elemental Sul...

引用

15th international conference on computer and automation Engineering, ICCAE 2023

作者： Piemjaiswang, Ratchanon Khaisri, Sakarin Sema, Teerawat Chalermsinsuwan, Benjapon Nimmanterdwong, Prathana Chulalongkorn University Environmental Research Institute Bangkok Thailand Ptt Public Company Limited Ptt Innovation Institute Bangkok Thailand Chulalongkorn University Faculty of Science Department of Chemical Technology Bangkok Thailand Mahidol University Faculty of Engineering Department of Chemical Engineering Nakhon Pathom Thailand

ISBN: (纸本)9798350396225

During the gas transportation, the pressure differential along the pipeline leads to the formation of unwanted impurities including elemental sulfur. The elemental sulfur formation is interestingly limited by the solubility of sulfur in the vapor phase. Our work applied the LM-ANN method (Levenberg-Marquardt Artificial Neural Network) to provide accurate and fast prediction of sulfur solubility in natural gas pipeline. Various sulfur solubility models were developed using the proposed method in order to predict sulfur solubility under two operating pressure ranges including;models for data with pressure lower than 25 MPa (LP model) and pressure higher than 25 MPa (HP model). The proposed models could capture the variation of gas composition and conditions (temperature and pressure) while the empirical model was required to be adjusted as the changing values of input variables. The proposed models provided a promising performance with R2 and RMSE increased from the base model up to 0.9841 and 0.036 for LP model and 0.9913 and 0.0093 for HP model, respectively. The proposed models have advantages over the empirical models as they could cover the variation of gas composition and conditions while the traditional model require to be adjusted as the values of input variables change. © 2023 IEEE.

关键词： Solubility

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Smart City Transport Updater

Smart City Transport Updater

引用

2023 international conference on IoT, Communication and automation technology, ICICAT 2023

作者： Kavitha, C.B. Singh, Pallavi Vardhan, K. Leela Deepak, D. Hindustan Institute of Technology and Science Department of Electronics & Communication Engineering Chennai India

ISBN: (纸本)9798350302820

The rapid growth in population and increase in energy demand caused a great increase in people using public transport. While public transport is cheap and affordable, the probability of finding a bus or train is quite uncertain. This work introduces an innovative approach of a digital transport updater, that gives information about the local buses and their timings. It also tells the pricing and the last bus service on a particular route. This model also acts as a digital bulletin system for tracking bus numbers and routes. It also enables the provision of digital ticketing. This system allows users and commuters to have smooth and comfortable bus rides without any hassle and provides an SOS service along with digital ticketing. This is modeled using AVR Atmega 328p8 Bit Controller, and a loyalty card system is used to avail all of the services. © 2023 IEEE.

关键词： Costs

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Dockomation System 14

Dockomation System

引用

14th international conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Dhanse, Saqlain Chandane, M.M. Chavan, Amol V.J.T.I. Computer Engineering Mumbai India V.J.T.I. Computer Engineering and Information Technology Mumbai India Dell Emc Data Protection Appliance Pune India

ISBN: (纸本)9798350335095

Delivering a good quality product is the prime requirement for software development process in which the quality aspects include consistency, reproducibility, environment dependency, etc. wherein execution time is a decisive factor for grading any software. automation plays a crucial role in reducing time, effort, cost and manual errors to ensure high quality results by surpassing human errors. Most of the software automation tools currently being used are based on virtual machines. One of such prominently used tools is Jenkins. However it suffers from configuration time, execution time, complex user interface, cronjob triggering and host environment dependency. A docker based automation system (Dockomation) has been proposed to address the outset issues. The proposed system has been implemented in python and tested in the real time environment. The comparative assessment with Jenkins in terms of configuration time, execution time, etc. shows that Dockomation outperforms Jenkins. © 2023 IEEE.

关键词： Grading

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A Deep Learning Method to Translate Phonocardiogram (PCG) Signals to Electrocardiogram (ECG) Waveforms 13

A Deep Learning Method to Translate Phonocardiogram (PCG) Si...

引用

13th IEEE international conference on CYBER technology in automation, Control, and Intelligent Systems, CYBER 2023

作者： Chen, Wei Li, Zhi Zhang, Guanglie College of Computer Science and Software Engineering Shenzhen University Shenzhen China City University of Hong Kong Department of Mechanical Engineering Hong Kong Hong Kong City University of Hong Kong Shenzhen Research Institute Shenzhen China

ISBN: (纸本)9798350315196

In clinical practice, an electrocardiogram (ECG), which analyzes the electrical activity of the human heart, is a common cardiovascular diagnostic test. The ECG data can be stored and diagnosed effectively. However, precise positioning of the ECG electrodes is necessary for a reliable ECG tracing. This has an impact on how ECG monitors are used to check on patients at home. On the other hand, the Phonocardiogram (PCG) is a standard method for quantifying the properties of heart sounds in order to monitor and assess cardiac activity. With the advancement of wearable sensors, it is now simpler to record the heart's sound. We proposed a deep learning approach to translating PCG signals to ECG waveforms. This technique can be utilized to monitor cardiovascular disease in consumer wearable device development. The proposed method is evaluated on a benchmark dataset of normal and anormal cardiac data. Experimental results show that our proposed approach is reasonable and effective. The generated ECG outputs can achieve a high accuracy, and the root mean squared error (RMSE) is 0.053. © 2023 IEEE.

关键词： Electrocardiograms

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AUV Local Path Planning Based on Fusion of Improved DWA and RRT Algorithms 20

AUV Local Path Planning Based on Fusion of Improved DWA and ...

引用

20th IEEE international conference on Mechatronics and automation, ICMA 2023

作者： Li, Juan Zhang, Zihao Harbin Engineering University Science and Technology on Underwater Vehicle Technology China Harbin Engineering University College of Intelligent Systems Science and Engineering Harbin150001 China

ISBN: (纸本)9798350320831

For the local path planning problem of autonomous underwater vehicle (AUV) in unknown complex obstacle environment, the traditional Dynamic Window Approach (DWA) algorithm has problems such as easy to fall into local stagnation in complex obstacles. A path planning algorithm based on the fusion of Improved DWA and Rapid-exploration Random Tree (RRT) algorithms is proposed. The improved DWA algorithm velocity space is generated according to the period of the whole dynamic window and resets the evaluation function;the improved RRT algorithm plans guide points in the local known space to help DWA out of the local stagnation state. The two algorithms are fused to achieve local path planning for AUV in unknown complex underwater environment. Simulation shows that this fusion algorithm can plan a safe and feasible navigation path for AUV in unknown complex obstacle environment. © 2023 IEEE.

关键词： Autonomous underwater vehicles

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Smart Meter Modbus RS-485 Intrusion Detection by Federated Learning Approach 15

Smart Meter Modbus RS-485 Intrusion Detection by Federated L...

引用

15th international conference on computer and automation Engineering, ICCAE 2023

作者： Hossain, Md Delwar Ochiai, Hideya Khan, Latifur Kadobayashi, Youki Nara Institute of Science and Technology Division of Information Science Nara Ikoma Japan The University of Tokyo Grad. School of Info. Science and Tech. Tokyo Japan The University of Texas at Dallas Department of Computer Science Dallas United States

ISBN: (纸本)9798350396225

To accelerate digital transformation and assemble "connecting the world,"the IoT has been invented. To make and made more convenient in our daily life activities, billions of devices have been connected so far. Recently, we have noticed how they are helping cyber-physical systems (CPSs) to reach more elevated levels of evolution. Amidst diverse CPSs entities, the smart grid, Advanced Metering Infrastructure (AMI), is among the foremost essential entities since its rapid transformations. Wherein the Modbus RS-485 protocol is typically used in smart meters for physical layer communication. The key concern resides in fact that an attacker may easily compromise the smart meter systems since it lacks authentication and encryption mechanisms. As a countermeasure, an intrusion detection system (IDS), by applying a Federated Learning (FL) approach, could be an effective solution to detect the malicious activities of the RS-485 communication network, ensuring data protection from intruders. Since its built-in data protection mechanism and model could train without sharing sensitive private data. Henceforth, this research proposes a Federated Learning-based IDS for detecting critical attacks against the smart meter. We experiment with Modbus Attack DataSet for AMI (MAMI) datasets, and experiment results depict that the FL approach is reasonably effective in detecting critical smart meter attacks, moreover, protects the data privacy concern. The Multilayer Perceptron (MLP) classifier outperforms, which achieves a detection accuracy and detection rate of 99.98%, respectively. © 2023 IEEE.

关键词： Smart meters

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An Empirical Study on Hybrid Scheduling Algorithms in Cloud Computing 28

An Empirical Study on Hybrid Scheduling Algorithms in Cloud ...

引用

28th international conference on automation and Computing, ICAC 2023

作者： Abbas, Bushra Shah, Munam Ali Comsats University Islamabad Department of Computer Science Islamabad Pakistan

ISBN: (纸本)9798350335859

With the flourishment of Internet technology, cloud computing has become the most expedient way to get tasks done without purchasing costly machines. From small businesses to well-established organizations are all availing the cloud services. As millions of users are connected to the cloud, the demand for cloud resources is increasing day by day. This is the reason, the maintenance of streamlined workflow, communication, productivity, service delivery, resource availability, computational cost, load balancing, and performance has become a critical challenge for cloud service providers. To optimally utilize cloud resources, many resource scheduling algorithms exist. In this paper, our contribution is twofold. Firstly, a critical analysis of the heuristics, metaheuristics, and hybrid resource scheduling algorithms in cloud computing is presented by targeting throughput, response time, makespan, load balance, energy efficiency, cost, and resource utilization over the period 2012-2022. Secondly, we discuss the workflow of cloud resource allocation and scheduling techniques and we provide an easy and concise view of the underlying model adopted by each cloud architecture. Our experimental evaluations aim to present the suitability and appropriateness of different resource optimization algorithms in cloud computing. © 2023 IEEE.

关键词： Scheduling algorithms

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