2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)最新文献_第7页

Simple Implementations of the Cole-Cole Models Cole-Cole模型的简单实现

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257936

S. Kapoulea, C. Psychalinos, A. Elwakil

引用次数: 4

Behavioral Assessment of an Optimized Multi-Vehicle Platoon Formation Control for Efficient Fuel Consumption 基于高效油耗的优化多车编队控制行为评估

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257911

Mohamed Maged, Dalia M. Mahfouz, Omar M. Shehata, E. I. Morgan

{"title":"Behavioral Assessment of an Optimized Multi-Vehicle Platoon Formation Control for Efficient Fuel Consumption","authors":"Mohamed Maged, Dalia M. Mahfouz, Omar M. Shehata, E. I. Morgan","doi":"10.1109/NILES50944.2020.9257911","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257911","url":null,"abstract":"Over the past few decades, climate change, air pollution and road safety have been classified as vital problems affecting the globe adversely in terms of transportation. To solve these problems, Intelligent Transportation Systems (ITS) are investigated. One of the important ITS applications is vehicle platooning, which is contemplated to enhance road organization and reduce the overall fuel consumption. In this study a cooperative optimal algorithm is adopted to coordinate several vehicles to form platoons that minimize the total fuel cost by maximizing distance vehicles are in platoon, through the adjustment of the vehicles’ speeds. The algorithm is based on pairwise coordination by which the coordination decision is made between each two vehicles or sub-platoons to form a platoon based on fuel-saving potential. The optimization problem outputs the desired optimal speed profiles for each vehicle offline. These speed profiles are then sent to a cruise controller to control each vehicle’s dynamics to reach the desired optimal speeds. A nonlinear vehicle dynamic model including the powertrain dynamics is investigated. A hierarchical speed control approach is used, having an optimal Model predictive Control (MPC) as the upper level controller and a linear Proportional-Integral-Derivative (PID) as the lower level control approach used to manage the vehicles’ velocities. The coordination algorithm and the controller are tested on a scenario of four scattered vehicles moving on a flat road, having same destination point. The simulation scenario is conducted to test the coordination algorithm and demonstrate the performance of the controller in terms of velocity tracking, realistic control effort and reduced fuel consumption. Results show that the optimization and control objectives are achieved successfully.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115378555","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

Resource Prediction & Allocation in Cloud Radio Access Networks using Machine Learning 基于机器学习的云无线接入网络资源预测与分配

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257926

H. Hesham, G. Yasser, M. Ashour, T. Elshabrawy

{"title":"Resource Prediction & Allocation in Cloud Radio Access Networks using Machine Learning","authors":"H. Hesham, G. Yasser, M. Ashour, T. Elshabrawy","doi":"10.1109/NILES50944.2020.9257926","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257926","url":null,"abstract":"With the evolution of 5G and the need to provide on demand services anywhere anytime in radio services, offloading the radio processing to a centralized cloud where all the computation and processing occurs gives flexibility in the allocation and re-allocation of resources to users according to their demand and capacity. This concept is the essence of Cloud Radio Access Networks. With this technology comes two main challenges: firstly, how much resources are required given the system traffic load, and secondly, which resources should be assigned to which user to guarantee the best quality of service at the best resource utilization. Resources in this paper are considered as both physical resources, servers in the cloud, lightweight Remote Radio Heads (RRHs) and bandwidth resources presented in Resource Blocks (RBs). The optimal allocation of these resources dependent on the user traffic is a non-linear optimization problem that is computationally challenging and time consuming to solve. In the presence of the high frame rate, the delay associated with this computational complexity may affect the quality of service. This paper explores different supervised machine learning algorithms in order to predict the amount of RRHs, BBUs and RBs the Cloud Radio Access Network needs, then allocate those resources in order to avoid the high level computation resource allocation usually requires, leading to an overall decrease in the latency in the system and hence a more practical use of the optimal solutions. Machine learning techniques considered include linear, logistic regression, k-means clustering and further improving the allocation using neural networks in comparison to logistic regression. Results show that the different machine learning techniques used for prediction and allocation are accurate in comparison to the test data derived analytically using a heuristic approach.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122338046","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

Atmospheric Aerosol Prediction over Egypt with LSTM-RNN using NASA’s MERRA-2 利用NASA MERRA-2的LSTM-RNN预测埃及的大气气溶胶

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257885

M. Eltahan, Karim Moharm

引用次数: 0

Modeling the Production Planning and Control System using UML 利用UML对生产计划与控制系统进行建模

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257906

Shahd Yaser Nasr, S. Kassem

引用次数: 3

Efficient Hardware Implementation for IoT Security System 物联网安全系统的高效硬件实现

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257939

A. Shisha, Maha Aboelmaged, Rola Aboshabaan, Amr Hassan, Mariam M. Fouad, M. A. E. Ghany

{"title":"Efficient Hardware Implementation for IoT Security System","authors":"A. Shisha, Maha Aboelmaged, Rola Aboshabaan, Amr Hassan, Mariam M. Fouad, M. A. E. Ghany","doi":"10.1109/NILES50944.2020.9257939","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257939","url":null,"abstract":"With the evolution of IoT and its involvement in everyday life, the amount of data collected by IoT devices is increasing drastically and user’s information is becoming more vulnerable to cyber-attacks. Thus, comes the importance of IoT security and the importance to have a flexible security system which doesn’t affect the IoT devices power consumption and efficiency. In this paper an efficient dynamic security system that uses partial reconfiguration concept in zed board is presented to achieve better data security and faster generation of the encrypted data. Algorithm hopping is used to switch between three different cryptographic cyphers which are AEGIS, ASCON and DEOXYS-II. These ciphers are the main finalists in CAESAR competition as they achieved high security, medium security and low security respectively and each of these ciphers has its own significant attributes. The proposed design targets the improvement of reconfiguration time of the zed board using LZ4 (Lempel-Ziv4) compression and decompression techniques for the input bitstream files. Our research shows a decrease in the reconfiguration time of a minimum 61.3% decrease for the largest bit file in comparison to the previous works in the same field.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127349079","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

Missile Roll Autopilot Redesign Based Advanced Fin Actuation System Modeling 基于先进翼片驱动系统建模的导弹滚转自动驾驶仪设计

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257900

S. Shelan, M. Abozied, H. Hendy, Y. Elhalwagy

{"title":"Missile Roll Autopilot Redesign Based Advanced Fin Actuation System Modeling","authors":"S. Shelan, M. Abozied, H. Hendy, Y. Elhalwagy","doi":"10.1109/NILES50944.2020.9257900","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257900","url":null,"abstract":"The design of missile autopilot is an essential issue as it always shares several challenges. The accuracy of impact is highly affected by designed controller accuracy and robustness against the target maneuver and missile nonlinearity resources. The design of autopilot controllers is highly affected by the derived system transfer function as much as it expresses the detailed system dynamics and nonlinearity resources. In this paper, we highlight the importance of advanced actuation system modeling considering nonlinearity resources. The nonlinear model parameters are derived, identified, and evaluated through simulation of missile roll autopilot. Inserting the developed system model to the three-loop missile autopilot presented a poor performance for the time and frequency stability parameters so in this paper a redesign procedure is proposed for designing a more realized controller. The gain scheduling PID controller based optimized genetic algorithm is developed for selected trim points based on missile dynamic pressure and trajectory parameters. The simulation of roll autopilot loop results presents sufficient efficiency and robustness for the selected trim points different input signals with rapid amplitude and frequency changes for high dynamics systems.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127511269","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

Controller Design and Optimization of Magnetic Levitation System (MAGLEV) using Particle Swarm optimization technique and Linear Quadratic Regulator (LQR) 基于粒子群优化技术和线性二次型调节器的磁悬浮系统控制器设计与优化

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257873

A. A. Abbas, H. Ammar, M. Elsamanty

{"title":"Controller Design and Optimization of Magnetic Levitation System (MAGLEV) using Particle Swarm optimization technique and Linear Quadratic Regulator (LQR)","authors":"A. A. Abbas, H. Ammar, M. Elsamanty","doi":"10.1109/NILES50944.2020.9257873","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257873","url":null,"abstract":"Magnetic Levitation System is one of practical examples which faces some nonlinearities behavior. Such systems require special types of controller parameters consideration for accurate results. In this paper, the process of tuning is to determine the system poles and getting them away from the instability region using state feedback (SF) controller methodology. The resulted controllable system parameters are estimated using LQR controller. Since the desired goal is to minimize vital parameters in the system behavior like the steady state error, settling time, raising time of the system and system overshoot, optimization techniques have been used to minimize cost function of the parameters which need to be optimized and reach for more reliable ones for better performance. Particle swarm optimization (PSO) has been used for tuning process. System operation points should be 0.61 A for electric current and 6 mm distance between coil surface and balanced metal ball, results show that using LQR controller will cause about 33% error percentage as steady state error and about 20% overshoot. Using PSO optimization technique for controller parameters will produce less steady state error of 6.5% with 4% overshoot percentage.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116875766","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

Energy-Efficient Near-Threshold Standard Cell Library for IoT Applications 物联网应用的节能近阈值标准单元库

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257934

AbdelRahman Hesham, A. Nassar, H. Mostafa

引用次数: 1

Modeling and control of variable-mass flight vehicle 变质量飞行器建模与控制

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257895

Mohamed G. Elsamra, M. Khalil, A. Roshdy, Ahmed E. Amin, O. Elfarouk

引用次数: 0