2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)最新文献_第6页

Decentralized Intersection Management of Autonomous Vehicles Using Nonlinear MPC 基于非线性MPC的自动驾驶汽车分散交叉口管理

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257893

H. Ali, Samaa Khaled, Omar M. Shehata, E. I. Morgan

{"title":"Decentralized Intersection Management of Autonomous Vehicles Using Nonlinear MPC","authors":"H. Ali, Samaa Khaled, Omar M. Shehata, E. I. Morgan","doi":"10.1109/NILES50944.2020.9257893","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257893","url":null,"abstract":"The rapid population growth and increase in vehicle numbers over the last few decades have caused traffic congestion worldwide, as intersections significantly impact the efficiency of traffic networks in urban areas, this paper focuses on intelligent traffic management at intersections by integrating the technologies of Intelligent Transportation Systems (ITS) and Autonomous Vehicles (AV). In this framework, a physical model represents each vehicle taking into account the dynamic limits. A decentralized Nonlinear Model Predictive Control (NMPC) is proposed to help coordinate the traffic flow of the AV at the intersection. The controller solves a quadratic cost function for the vehicle to ensure a smooth trajectory and minimum energy consumption, while avoiding collisions that is guaranteed using linear constraints and two developed priority assignment methods, Predicted Arrival Time (PAT) and First-Come First-Served (FCFS). The two methods are tested using a developed simulation environment on MATLAB/Simulink and the results are compared, the predicted arrival time method outperformed the FCFS method.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":"5 11 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":"114099286","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

A Universal Model for Defective Classes Prediction Using Different Object-Oriented Metrics Suites 基于不同面向对象度量套件的缺陷类预测通用模型

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257892

F. A. Mohamed, Cherif R. Salama, A. Yousef, Ashraf Salem

{"title":"A Universal Model for Defective Classes Prediction Using Different Object-Oriented Metrics Suites","authors":"F. A. Mohamed, Cherif R. Salama, A. Yousef, Ashraf Salem","doi":"10.1109/NILES50944.2020.9257892","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257892","url":null,"abstract":"Recently, research studies were directed to the construction of a universal defect prediction model. Such models are trained using different projects to have enough training data and be generic. One of the main challenges in the construction of a universal model is the different distributions of metrics in various projects. In this study, we aim to build a universal defect prediction model to predict software defective classes. We also aim to validate the Object-Oriented Cognitive Complexity metrics suite (CC metrics) for its association with fault-proneness. Finally, this study aims to compare the prediction performances of the CC metrics and the Chidamber and Kemerer metrics suite (CK metrics), taking into account the effect of preprocessing techniques. A neural network model is constructed using these 2 metrics suites (CK & CC metrics suites). We apply different preprocessing techniques on these metrics to overcome variations in their distributions. The results show that the CK metrics perform well whether a preprocessing is applied or not, while CC metrics’ performance is significantly affected by different preprocessing techniques. The CC metrics always outperform in the recall, while the CK metrics usually outperform in other performance metrics. Normalization preprocessing results in the highest recall values using either of the two metrics suites.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":"8 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":"114962584","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

Error Detection and Recovery in FPGA-based Pipelined Architectures 基于fpga的流水线结构中的错误检测与恢复

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257894

Beatrice Shokry, G. Alkady, H. Amer, R. Daoud, I. Adly, H. Elsayed

引用次数: 2

Forecasting of renewable energy using ANN, GPANN and ANFIS (A comparative study and performance analysis) 基于ANN、GPANN和ANFIS的可再生能源预测(比较研究与性能分析)

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257963

Omnia Abd Al-Azeem Hussieny, M. El-Beltagy, Samah El-Tantawy

{"title":"Forecasting of renewable energy using ANN, GPANN and ANFIS (A comparative study and performance analysis)","authors":"Omnia Abd Al-Azeem Hussieny, M. El-Beltagy, Samah El-Tantawy","doi":"10.1109/NILES50944.2020.9257963","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257963","url":null,"abstract":"Prediction and forecasting is preserved to be an important stage in diverse problems. The main aim of our manuscript is to forecast the wind speed and the temperature based on data collected months ago. The data and calculations we obtained for the temperatures in about 4 years ago from 2015 till 2018, whereas the statistics calculated for the wind speed were about 20 years from 1996 until 2015. The data of the wind speed and the temperature collected in different regions of Egypt East coast and Alsheihkzayid. The system used for prediction is based on three different methods which are Artificial Neural network (ANN), Genetic algorithm fused with artificial neural network (GPANN) and Adaptive Neuro-fuzzy inference system (ANFIS). They were used to forecast the future temperature and the future wind speed. The results proved that the system is robust, and it can be applicable during real time. The performance of ANFIS with the trapezoidal membership function proved to obtain the highest performance over all other methods. The optimal mean square error (MSE) reached for the wind speed was 7.2989 m/s and for the temperature is 3.8364 C°.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":"8 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":"124892604","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

Meta-heuristic Algorithms for Solving the Multi-Depot Vehicle Routing Problem 求解多车场车辆路径问题的元启发式算法

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257879

Omar M. Khairy, Omar M. Shehata, E. I. Morgan

引用次数: 2

Prediction of Internal Flow’s Characteristics Around Two Cylinders in Tandem using optimal T-S fuzzy 利用最优T-S模糊预测串联两缸内流动特性

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257971

Yusuf T. Elbadry, A. Elshafei, H. Ammar, M. Boraey, A. Guaily

引用次数: 0

Upper Limb Muscle Fatigue Analysis Using Multi-channel Surface EMG 上肢肌肉疲劳多通道表面肌电图分析

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257909

A. Ebied, A. Awadallah, M. Abbass, Y. El-Sharkawy

引用次数: 3

Artificial Potential Field for Dynamic Obstacle Avoidance with MPC-Based Trajectory Tracking for Multiple Quadrotors 基于mpc轨迹跟踪的多旋翼飞行器动态避障人工势场

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257973

Rawan A. Abdellatif, A. El-Badawy

引用次数: 3

Experimental Path tracking optimization and control of a nonlinear skid steering tracked mobile robot 非线性滑移转向履带移动机器人实验路径跟踪优化与控制

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257956

M. Barakat, H. Ammar, M. Elsamanty

{"title":"Experimental Path tracking optimization and control of a nonlinear skid steering tracked mobile robot","authors":"M. Barakat, H. Ammar, M. Elsamanty","doi":"10.1109/NILES50944.2020.9257956","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257956","url":null,"abstract":"The skid steering tracked robot is consider one of the famous robots that used in the autonomous agricultural field. The robot model is considered as a coupled nonlinear model. So, a real kinematic model is required to develop the robot motion which will improve the high quality and quantity of the cultivated crops. So, in this research a mathematical model for the skid steering mobile robot (SSMR) and a mathamtical model has been presented to simulate the robot. The model has been validated based on experimental data for the Skid Steering model. The robot motion as position and velocity has been measured using Inertial Measurement Unit (IMU) and fused with the External Camera measurements. These data used to train a neural network model to develop the equivalent kinematic model that replace the nonlinear model. Then, PID controller was used to perform position and speed control for the two tracks and then to the whole robot body pose. Moreover, metaheuristic techniques were used to improve the PID response by tuning gains based on Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC). The system response for the path tracking and its precision has been optimized based on the developed techniques. Moreover, the extracted results show the high performance of tracking path based on a tuned PID controller based on ABC optimization technique.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":"37 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":"124451669","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

Adaptive Nonlinear Model Predictive Control algorithm for blood glucose regulation in type 1 diabetic patients 1型糖尿病患者血糖调节的自适应非线性模型预测控制算法

2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) Pub Date : 2020-10-24 DOI: 10.1109/NILES50944.2020.9257910

Alaa A. Embaby, Zaki B. Nosseir, Hesham Badr

{"title":"Adaptive Nonlinear Model Predictive Control algorithm for blood glucose regulation in type 1 diabetic patients","authors":"Alaa A. Embaby, Zaki B. Nosseir, Hesham Badr","doi":"10.1109/NILES50944.2020.9257910","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257910","url":null,"abstract":"The pancreas of patients with Type 1 Diabetes Mellitus (T1DM) is unable to produce insulin. Thus, insulin therapy is required for T1DM to maintain Blood Glucose (BG) levels within the normal range. The Artificial Pancreas (AP) is a closed-loop control system that is used by T1D patients to maintain their BG levels at the normal range during daily life. In this work, an Adaptive Nonlinear Model Predictive Control (AMPC) algorithm for BG regulation in T1D patients is developed. The proposed technique uses the Feed Forward Neural Network (FFNN) as a nonlinear blood glucose prediction model to handle the delay between the moment of insulin injection and the moment of insulin interaction with the blood glucose. Also, it uses the Fuzzy Logic Controller (FLC) as a control algorithm to determine the amount of insulin required for regulating the BG level. An adaptation method is also included to adjust the proposed system to compensate for physiological differences among patients. The limits of the output membership functions for the FLC are optimized using the Genetic algorithm (GA). Simulation results for a 36h scenario are demonstrated in nine virtual adult patients. The master findings are the average percentages of these patients for the time spent in the normal range, hypo-, and hyperglycemia. Our results indicate that the proposed closed-loop control system increases the time that BG is in the normal range and causes less hyperglycemia as compared to a published technique studied in a similar scenario and population.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":"50 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":"132648050","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