2020 15th International Conference on Computer Engineering and Systems (ICCES)最新文献_第2页

Reconfigurable PETPG for External Testing of Digital Circuits 用于数字电路外部测试的可重构PETPG

2020 15th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2020-12-15 DOI: 10.1109/ICCES51560.2020.9334582

Mahmoud Fathy Al-Sawah, M. El-Mahlawy, M. Abbass

引用次数: 0

Mitigating IoT Security Challenges Using Blockchain 使用区块链缓解物联网安全挑战

2020 15th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2020-12-15 DOI: 10.1109/ICCES51560.2020.9334644

Mohamed Elkashlan, Marianne A. Azer

引用次数: 0

Monitoring and Predicting Driving Performance Using EEG Activity 利用脑电图活动监测和预测驾驶性能

2020 15th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2020-12-15 DOI: 10.1109/ICCES51560.2020.9334574

A. Elsherif, Ahmed Karaman, Omar Ahmed, Omar Magdy, R. Shouman, Rita El-Noumier, Ahmed M. Hamed, Hany Eldawlatly, S. Eldawlatly

{"title":"Monitoring and Predicting Driving Performance Using EEG Activity","authors":"A. Elsherif, Ahmed Karaman, Omar Ahmed, Omar Magdy, R. Shouman, Rita El-Noumier, Ahmed M. Hamed, Hany Eldawlatly, S. Eldawlatly","doi":"10.1109/ICCES51560.2020.9334574","DOIUrl":"https://doi.org/10.1109/ICCES51560.2020.9334574","url":null,"abstract":"Human error is considered one of the major causes of car accidents. One potential approach to reduce human driving errors is to continuously monitor the driver’s performance while driving. This could help in detecting potential risks and thus reduce the likelihood of accidents. In this paper, we introduce a machine learning system that analyzes the driver’s brain activity to monitor and predict the driver’s performance. While driving, the system monitors the driver’s mental state by analyzing acquired Electroencephalography (EEG) signals. Additionally, the proposed system acquires EEG activity from the driver before driving and predicts the driving performance along the intended route. The proposed system is tailored for the Automotive Open System Architecture (AUTOSAR) framework. Our results demonstrate the ability of the system to classify the mental state of the driver in real-time into three states (focused, unfocused, and drowsy) with a mean accuracy of 96.5% across three examined subjects. The system also predicts the driver’s performance before driving from the recorded EEG signals with a mean accuracy of 85%. These results indicate the utility of EEG signals analysis in enhancing the safety of futuristic automotive applications.","PeriodicalId":247183,"journal":{"name":"2020 15th International Conference on Computer Engineering and Systems (ICCES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130089845","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: 3

Uplink Multiuser Scheduling Using Machine Learning 基于机器学习的上行多用户调度

2020 15th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2020-12-15 DOI: 10.1109/ICCES51560.2020.9334659

Iman M. Shawky, M. Sadek, H. Elhennawy

引用次数: 1

Modified Ant Colony Placement Algorithm for Containers 改进的集装箱蚁群布局算法

2020 15th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2020-12-15 DOI: 10.1109/ICCES51560.2020.9334671

Asmaa M. Hafez, Amany Abdelsamea, A. El-Moursy, S. Nassar, M. Fayek

{"title":"Modified Ant Colony Placement Algorithm for Containers","authors":"Asmaa M. Hafez, Amany Abdelsamea, A. El-Moursy, S. Nassar, M. Fayek","doi":"10.1109/ICCES51560.2020.9334671","DOIUrl":"https://doi.org/10.1109/ICCES51560.2020.9334671","url":null,"abstract":"Container is an evolving lightweight virtualization innovation that attempts to perfectly capture a function and its library dependencies to be executed seamlessly at the operating system level without pre-installations or s/w setup. Placement of containers at the appropriate platform is essential in the utilization optimization of resources in cloud infrastructures. Efficient resource utilization can be achieved only when the containers are optimally mapped to VMs. Poor placement may cause a bottleneck in the cloud if VMs are loaded heavily and this may affect the response time of a given set of tasks. The ant colony optimization technique was used to schedule tasks and containers on VMs and PMs in the cloud. The disadvantage of typical ACO is its tendency to schedule tasks to the most used (high pheromone intensity) node. If the node is carrying a big load it will have an issue of overhead. By tracking preceding scheduling, this hassle could be solved by lowering the processing time and tracking load on each VM. With concerning the challenges and difficulty of the container placement, this paper proposes Modified Ant Colony Optimization Technique (MACO) for the placement of containers. The new proposal takes into consideration the scheduling history to enhance the scheduling decision. The results of MACO are compared with the basic Ant Colony Optimization technique (ACO) and First Come First Serve algorithm (FCFS). The experimental results show that the MACO is better than FCFS and the basic ACO in terms of response time and throughput.","PeriodicalId":247183,"journal":{"name":"2020 15th International Conference on Computer Engineering and Systems (ICCES)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132022013","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

Studying the Effect of Using a Low Power PV and DC-DC Boost Converter on the Performance of the Solar Energy PV System 研究使用低功率光伏和DC-DC升压变换器对太阳能光伏系统性能的影响

2020 15th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2020-12-15 DOI: 10.1109/ICCES51560.2020.9334581

Eman Hegazy, W. Saad, M. Shokair

{"title":"Studying the Effect of Using a Low Power PV and DC-DC Boost Converter on the Performance of the Solar Energy PV System","authors":"Eman Hegazy, W. Saad, M. Shokair","doi":"10.1109/ICCES51560.2020.9334581","DOIUrl":"https://doi.org/10.1109/ICCES51560.2020.9334581","url":null,"abstract":"Wireless sensor network has become an increasing interest for research. The major limitation in the WSN nodes design is finite battery capacity that can only operate for finite lifetime depending on the duty cycle of the operation. In this paper, a solar photovoltaic PV will be studied with its nonlinear characteristics curves. It can be employed in a solar energy harvesting system to enhance its performance and to address the problem of finite battery capacity in WSN. The solar panels with small size areas linked with a low power harvesting circuits can supply an alternative power source for its node. Simulation of the DC-DC Boost converter will be included. The efficient design for the solar harvesting system components which are PV panel, DCDC converters, Control Unit, and WSN node will be investigated. In general, there are two efficient ways for solar energy harvesting algorithms which are; Pulse Width Modulation and Maximum Power Point Tracking control algorithms. The desired system in this paper focuses on increasing the output voltage, output power and overall solar harvesting system efficiency using two control techniques than the other related works. The design of the solar energy harvesting system models are simulated using MATLAB/SIMULINK. From the simulation results, the desired solar harvesting system model has a higher overall efficiency using maximum power point control algorithm.","PeriodicalId":247183,"journal":{"name":"2020 15th International Conference on Computer Engineering and Systems (ICCES)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125372370","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: 3

Outage Probability Analysis of One-way Distributed Cooperative Relay Selection Networks 单向分布式协同中继选择网络的中断概率分析

2020 15th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2020-12-15 DOI: 10.1109/ICCES51560.2020.9334561

Alhossin K. Aljadai, M. Manna, A. Kharaz

引用次数: 0

Correction of False Diagnosis Recording in the Electrocardiograph Signal by Adaptive Digital Filter 用自适应数字滤波器校正心电图信号中的假诊断记录

2020 15th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2020-12-15 DOI: 10.1109/ICCES51560.2020.9334557

G. Attia

{"title":"Correction of False Diagnosis Recording in the Electrocardiograph Signal by Adaptive Digital Filter","authors":"G. Attia","doi":"10.1109/ICCES51560.2020.9334557","DOIUrl":"https://doi.org/10.1109/ICCES51560.2020.9334557","url":null,"abstract":"Electrocardiogram (ECG) instrument is used to provide diagnostic information about the critical condition of the patient’s heart, but its performance sometimes suffers from some sources of noise such as: 50Hz line frequency, Hum and high frequency (HF) noise. These sources of noise affect the performance of the ECG and hence cause false diagnosis recording that tricks the doctor who uses this machine. The current paper; proposes to tackle the problem of false diagnoses recordings by employing adaptive digital filter based least mean square (LMS) error algorithm in order to refine the ECG signals from the disturbing sources of noise. Based matlab programming; I have studied two different cases of mixing random noise that disturb the performance of the ECG instrument. The first kind of noise is mixing the line frequency 50 Hz with the ECG signal; the second kind of noise is mixing the hum and high frequency noise with the ECG signal. Numerical values for digital filter parameters have been used as: number of taps or order (M = 16), step size (μ = 0.005), sampling frequency (Fs = 1000Hz), interfering line frequency 50Hz, hum noise, and HF noise. The experimental results using Matlab simulation show that; the proposed scheme of employing digital filter based LMS algorithm; can tackle the problem of false diagnoses that causes frustration for the patient and tricks the doctor. The proposed scheme has several advantages such as; simplicity, reliability, practical applicability, adaptability to the change in signal characteristics and cost affordability.","PeriodicalId":247183,"journal":{"name":"2020 15th International Conference on Computer Engineering and Systems (ICCES)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133677769","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

Blade Angle Control Using TLBO Based Modified Adaptive Controller 基于TLBO的改进自适应叶片角度控制

2020 15th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2020-12-15 DOI: 10.1109/ICCES51560.2020.9334607

Ahmed M. Shawqran, A. El-Marhomy, M. Attia

引用次数: 0

Tutorial I: Automotive Software Emerging Standard 教程一:汽车软件新兴标准

2020 15th International Conference on Computer Engineering and Systems (ICCES) Pub Date : 2020-12-15 DOI: 10.1109/icces51560.2020.9334639

Bassem A. Abdullah

引用次数: 0