2021 IEEE 3rd International Multidisciplinary Conference on Engineering Technology (IMCET)最新文献_第2页

A Composite Model Predictive and Super Twisting Sliding Mode Controller for Stable and Robust Trajectory Tracking of Autonomous Ground Vehicles 一种用于自动驾驶地面车辆稳定鲁棒轨迹跟踪的复合模型预测和超扭转滑模控制器

2021 IEEE 3rd International Multidisciplinary Conference on Engineering Technology (IMCET) Pub Date : 2021-12-08 DOI: 10.1109/imcet53404.2021.9665575

Hassan El Atwi, Naseem A. Daher

{"title":"A Composite Model Predictive and Super Twisting Sliding Mode Controller for Stable and Robust Trajectory Tracking of Autonomous Ground Vehicles","authors":"Hassan El Atwi, Naseem A. Daher","doi":"10.1109/imcet53404.2021.9665575","DOIUrl":"https://doi.org/10.1109/imcet53404.2021.9665575","url":null,"abstract":"In this work, we propose a novel composite control system for stable and robust trajectory tracking of autonomous ground vehicles (AGVs) in the presence of bounded disturbances and uncertainties. A nominal model predictive control (MPC) system is combined with a second-order super twisting sliding mode controller (STSMC) to formulate the proposed control system under the umbrella of tube-based MPC, with the aim of tackling the trajectory tracking challenge for AGVs in uncertain environments. The proposed system's stability is analyzed and guaranteed via Input-to-State Stability (ISS) in coordination with Lyapunov stability theory. For the first time, this combined control structure is applied to the nonlinear kinematic model of AGVs, where STSMC plays the role of an auxiliary controller in the feedback loop to handle disturbances and uncertainties that cause deviation from the nominal model. A comparative simulation study is presented to demonstrate the effectiveness and robustness of the proposed composite scheme in the presence of disturbance effects.","PeriodicalId":181607,"journal":{"name":"2021 IEEE 3rd International Multidisciplinary Conference on Engineering Technology (IMCET)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129245943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Trip-based prediction of hybrid electric vehicles velocity using artificial neural networks 基于行程的混合动力汽车速度人工神经网络预测

2021 IEEE 3rd International Multidisciplinary Conference on Engineering Technology (IMCET) Pub Date : 2021-12-08 DOI: 10.1109/imcet53404.2021.9665641

Nay Abi Akl, Jawad El Khoury, C. Mansour

{"title":"Trip-based prediction of hybrid electric vehicles velocity using artificial neural networks","authors":"Nay Abi Akl, Jawad El Khoury, C. Mansour","doi":"10.1109/imcet53404.2021.9665641","DOIUrl":"https://doi.org/10.1109/imcet53404.2021.9665641","url":null,"abstract":"In this paper, a high-performance Long Short-Term Memory (LSTM) neural network vehicle velocity predictor considering the case of countries with no vehicle to infrastructure or vehicle to vehicle data available. This fact restricts the amount of information that can be used for the network training process. The study takes into consideration the computational complexity of the developed predictor since it will ultimately be implemented as part of a real-time car controller. Two real-world driving cycles from developed and developing countries were collected from multiple drivers in order to make sure that the created datasets cover multiple driving patterns and scenarios. The considered trips include multiple driving conditions such as a highway, urban road, and intersections. Two architectures of time series prediction models are evaluated: the Non-linear AutoRegressive with eXogenous inputs (NARX) and LSTM neural networks. The proposed paper also explores the possibility of expanding the features of the networks beyond technical inputs to tackle macro-features such as the date, time of day, holiday etc., in order to test their effect on the overall prediction as well as the computational efficiency of the proposed velocity predictor. Results show that the LSTM model outperforms the NARX model and accurately predicts multi-step ahead vehicle velocity under various weather and traffic conditions while maintaining a low computational complexity.","PeriodicalId":181607,"journal":{"name":"2021 IEEE 3rd International Multidisciplinary Conference on Engineering Technology (IMCET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125022507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

A Modified RC-pLMS Adaptive Beamformer for Secure Digital Communication 一种用于安全数字通信的改进RC-pLMS自适应波束形成器

2021 IEEE 3rd International Multidisciplinary Conference on Engineering Technology (IMCET) Pub Date : 2021-12-08 DOI: 10.1109/imcet53404.2021.9665588

G. Akkad, A. Mansour, B. Elhassan, E. Inaty

{"title":"A Modified RC-pLMS Adaptive Beamformer for Secure Digital Communication","authors":"G. Akkad, A. Mansour, B. Elhassan, E. Inaty","doi":"10.1109/imcet53404.2021.9665588","DOIUrl":"https://doi.org/10.1109/imcet53404.2021.9665588","url":null,"abstract":"A modified reduced complexity parallel least mean square (mRC-pLMS) adaptive beamforming algorithm for high precision directivity and secure data communication is proposed in this paper. A high performance RC-pLMS algorithm has been proposed, recently, to eliminate the tradeoff between the LMS steady state error and its convergence speed while maintaining a low computational complexity structure. RC-pLMS is obtained by simplifying the two stages parallel LMS (pLMS) and adding a filter to the inputs, thus eliminating the need of an additional LMS filter. To further improve the RC-pLMS convergence speed and accuracy for fast and secure data communication we propose a modified RC-pLMS algorithm. mRC-pLMS is obtained by updating the RC-pLMS weight update equation to make use of the filtered input signal rather than the original input. Numerical simulations reflected by the mean square error convergence behavior and beam pattern, demonstrate the superior performance of the mRC-pLMS in providing faster convergence, lower steady state error and better interference attenuation while maintaining identical RC-pLMS resource requirements.","PeriodicalId":181607,"journal":{"name":"2021 IEEE 3rd International Multidisciplinary Conference on Engineering Technology (IMCET)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121959247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Examination and optimization of the design parameters for the thermal hysteresis phenomenon of the phase change material 相变材料热滞现象设计参数的校核与优化

2021 IEEE 3rd International Multidisciplinary Conference on Engineering Technology (IMCET) Pub Date : 2021-12-08 DOI: 10.1109/imcet53404.2021.9665566

K. Sandy, Maatouk Chantal, E. Khalil, Khatounian Flavia

{"title":"Examination and optimization of the design parameters for the thermal hysteresis phenomenon of the phase change material","authors":"K. Sandy, Maatouk Chantal, E. Khalil, Khatounian Flavia","doi":"10.1109/imcet53404.2021.9665566","DOIUrl":"https://doi.org/10.1109/imcet53404.2021.9665566","url":null,"abstract":"The current paper examines the influence of the thermal hysteresis phenomenon on the results of the simulation and optimization of the design parameters for a modelled Phase Change Material (PCM) sphere and for a large scale Thermal Energy Storage (TES) system integrated with PCMs. It first investigates the accuracy of the simulation results with and without taking into account the thermal hysteresis by relying on the effective heat capacities of the heating and cooling enthalpy-temperature curves compared to the equivalent heat capacity in accordance with the melting time, energy output and usage temperature. In addition, the paper assesses the influence of the design parameters and capsule envelope material variation when the the thermal hysteresis phenomenon is exhibited by the spherical PCM capsule. Second, the study examines the impact of the thermal hysteresis phenomenon on the accuracy of the design parameters optimization for the large scale TES system by applying the adaptive simulated annealing algorithm to seek for the optimal parameters. The study highlights that the thermal hysteresis contributes to a variation in the simulation outputs for the modelled sphere by increasing the amount of recovered energy from 3.03 to 4.5 kJ and reduces the melting time from 8 to 5 min. The difference in the simulation results is not observed during the optimization of the energy content, hence, considering, or not the hysteresis phenomenon during the optimization process, contributes to similar optimum design parameters.","PeriodicalId":181607,"journal":{"name":"2021 IEEE 3rd International Multidisciplinary Conference on Engineering Technology (IMCET)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126861457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A Simple Neural Network for Efficient Real-time Generation of Dynamically-Feasible Quadrotor Trajectories 一种用于四旋翼飞行器动态可行轨迹实时生成的简单神经网络

2021 IEEE 3rd International Multidisciplinary Conference on Engineering Technology (IMCET) Pub Date : 2021-12-08 DOI: 10.1109/imcet53404.2021.9665549

M. Lakis, Naseem A. Daher

引用次数: 0

Bidirectional Manipulation of a Buoy With a Tethered Quadrotor UAV 用系留四旋翼无人机双向操纵浮标

2021 IEEE 3rd International Multidisciplinary Conference on Engineering Technology (IMCET) Pub Date : 2021-12-08 DOI: 10.1109/imcet53404.2021.9665578

Ahmad Kourani, Naseem A. Daher

引用次数: 3

A Review on Electric Vehicles Battery Chargers and AC/DC Converters for Fast Charging Stations 电动汽车电池充电器及快速充电站AC/DC转换器研究进展

2021 IEEE 3rd International Multidisciplinary Conference on Engineering Technology (IMCET) Pub Date : 2021-12-08 DOI: 10.1109/imcet53404.2021.9665577

Sandy Atanalian, K. Al-haddad, Rawad F. Zgheib, H. Kanaan

引用次数: 8

Human Firewall: Cyber Awareness using WhatApp AI Chatbot 人类防火墙:使用WhatApp AI聊天机器人的网络意识

2021 IEEE 3rd International Multidisciplinary Conference on Engineering Technology (IMCET) Pub Date : 2021-12-08 DOI: 10.1109/imcet53404.2021.9665642

Georges El Hajal, Roy Abi Zeid Daou, Y. Ducq

{"title":"Human Firewall: Cyber Awareness using WhatApp AI Chatbot","authors":"Georges El Hajal, Roy Abi Zeid Daou, Y. Ducq","doi":"10.1109/imcet53404.2021.9665642","DOIUrl":"https://doi.org/10.1109/imcet53404.2021.9665642","url":null,"abstract":"The use of technology is a necessary component for the success of business operations. Yet cyber risks related to technology are well known. In previous works, three different layers were defined to be responsible of the cyber physical security of any given system: the network layer, the device layer and the human factor layer. However, statistics and experience have proven that the third factor is the weakest link in the cyber security of any company. This factor is divided into two subsections: the ignorance of the user (which will be treated in this paper) and the malignancy of the user. As the two previous layers were presented in previous works, this paper will focus on enhancing security by raising the cyber awareness of users thus creating a human firewall. For that, an AI-based conversational bot that focuses on cyber threat awareness and acts as a personal assistant relating to security issues was developed. This bot is based on AI-approach and it is used to make the interaction with the user appealing and friendly through the use of WhatsApp as a mean of communication. The implementation and testing of this bot has shown great interest for the users who have tried it due to its simplicity, the quality of deliverable data and the evaluation technique.","PeriodicalId":181607,"journal":{"name":"2021 IEEE 3rd International Multidisciplinary Conference on Engineering Technology (IMCET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126131593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Detecting Mental Disorders through Social Media Content 通过社交媒体内容检测精神障碍

2021 IEEE 3rd International Multidisciplinary Conference on Engineering Technology (IMCET) Pub Date : 2021-12-08 DOI: 10.1109/imcet53404.2021.9665555

Rami Kanaan, Batoul Haidar, R. Kilany

引用次数: 1

On Data Bias and the Usability of Deep Learning Algorithms in Classifying COVID-19 based on Chest X-ray 基于胸片的深度学习算法在COVID-19分类中的数据偏差及可用性研究

2021 IEEE 3rd International Multidisciplinary Conference on Engineering Technology (IMCET) Pub Date : 2021-12-08 DOI: 10.1109/imcet53404.2021.9665574

Hassan Ezzeddine, M. Awad, Alain S. Abi Ghanem, Bassem Mourani

{"title":"On Data Bias and the Usability of Deep Learning Algorithms in Classifying COVID-19 based on Chest X-ray","authors":"Hassan Ezzeddine, M. Awad, Alain S. Abi Ghanem, Bassem Mourani","doi":"10.1109/imcet53404.2021.9665574","DOIUrl":"https://doi.org/10.1109/imcet53404.2021.9665574","url":null,"abstract":"SARS-COV-2 is a new strain of virus that was first detected in China. It quickly spread across the world affecting millions of people. For this reason, early detection of the virus is mandatory in order to limit the spread of the virus. Real-time reverse transcription polymerase chain reaction (RT-PCR) and the antibody test are the main tests used to detect the virus. Chest X-rays (CXRs) and computerized tomography (CT) scans are also used to detect the virus although the American college of Radiology does not recommend using medical imaging as a diagnostic tool. Like other medical imaging, convolutional neural networks are used to classify the images. We believe that developing a model to detect COVID-19 has no clinical value regardless of the accuracy achieved since 58% of CXRs seem to be normal. During literature review, several papers with suspicious accuracy of 90% and higher were found. We believe that the dataset used to train and validate the network is biased and is not appropriate for deep learning as any model we train using the same dataset has achieved high accuracy. Our experiments on Cohen's Covid dataset, augmented with Wang dataset, shows that any model trained on Cohen dataset can easily achieve high accuracy. This was further validated with two experienced radiologists who participated in this study were only able to classify 60% as being Covid. Our study highlight the importance of addressing bias in data and developing trustworthy and explainable ML models based on well curated data.","PeriodicalId":181607,"journal":{"name":"2021 IEEE 3rd International Multidisciplinary Conference on Engineering Technology (IMCET)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127671091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1