Pub Date : 2020-10-24DOI: 10.1109/NILES50944.2020.9257904
A. Hafez, T. Kasem, B. Elhadidi, M. Abdelrahman
A new Finite element model for HVAC applications is introduced. The model incorporates flow turbulence, buoyancy effects and unsteadiness. Also, the model accommodates complicated boundaries due to complex geometries and perforated tiles. Experimental validation is provided and extensive results for flow and temperature contours are presented. Temporal and spatial resolution prove that the model can capture important HVAC features as thermal comfort, buoyancy induced flow, complex boundaries.
{"title":"Efficient Finite Element Modeling of Complex HVAC Applications","authors":"A. Hafez, T. Kasem, B. Elhadidi, M. Abdelrahman","doi":"10.1109/NILES50944.2020.9257904","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257904","url":null,"abstract":"A new Finite element model for HVAC applications is introduced. The model incorporates flow turbulence, buoyancy effects and unsteadiness. Also, the model accommodates complicated boundaries due to complex geometries and perforated tiles. Experimental validation is provided and extensive results for flow and temperature contours are presented. Temporal and spatial resolution prove that the model can capture important HVAC features as thermal comfort, buoyancy induced flow, complex boundaries.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":"120 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":"122916213","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}
Pub Date : 2020-10-24DOI: 10.1109/NILES50944.2020.9257896
Yasmin K. Abdelmagid, Renad T. Nawar, Mennatullah K. Rabie, Ahmed S. Tulan, Ahmed H. Hassan, Andoleet Saleh, H. Mostafa
Memristor, the two-terminal memory-resistance device discovered by Chua in 1971, is a promising solution for future processing problems. Its CMOS integration compatibility and large resistance in small size, makes it very successful candidate for large-scale systems like Neural Networks. In last decade, memristors were used in many Neuromorphic Synapses for its advantage of combining processing (dot-product) and memory in same device. There are different materials that can be used to fabricate memristors. In this paper, a comparison between spintronic and TiO2-resistive memristor in two-transistors-one memristor synapse, is introduced. The work was done on Cadence Virtuoso with using Verilog-A for memristor modeling. The comparison reveals that the synaptic implementation with a spintronic memristor is more efficient when high speed is needed. However, the resistive memristor is more adequate due to its lower power dissipation.
{"title":"Investigation of DW Spintronic Memristor performance in 2T1M Neuromorphic Synapse","authors":"Yasmin K. Abdelmagid, Renad T. Nawar, Mennatullah K. Rabie, Ahmed S. Tulan, Ahmed H. Hassan, Andoleet Saleh, H. Mostafa","doi":"10.1109/NILES50944.2020.9257896","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257896","url":null,"abstract":"Memristor, the two-terminal memory-resistance device discovered by Chua in 1971, is a promising solution for future processing problems. Its CMOS integration compatibility and large resistance in small size, makes it very successful candidate for large-scale systems like Neural Networks. In last decade, memristors were used in many Neuromorphic Synapses for its advantage of combining processing (dot-product) and memory in same device. There are different materials that can be used to fabricate memristors. In this paper, a comparison between spintronic and TiO2-resistive memristor in two-transistors-one memristor synapse, is introduced. The work was done on Cadence Virtuoso with using Verilog-A for memristor modeling. The comparison reveals that the synaptic implementation with a spintronic memristor is more efficient when high speed is needed. However, the resistive memristor is more adequate due to its lower power dissipation.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":"1 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":"122942452","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}
Pub Date : 2020-10-24DOI: 10.1109/NILES50944.2020.9257880
Abdelrahman Ezzeldin Nagib, M. Saeed, Shereen Fathy El-Feky, Ali Khater Mohamed
Over the last two decades, the neural network has surprisingly arisen as an efficient tool for dealing with numerous real-life applications. Optimization of the hyperparameter of the neural network attracted many researchers in industrial and research areas because of its great effect on the quality of the solution. This paper presents a new adaptation for the learning rate with shock (ALRS) as the learning rate is considered one of the most important hyperparameters. The experimental results proved that the new adaptation leads to improved accuracy with a simpler structure for the neural network regardless of the initial value of the learning rate.
{"title":"Neural Network with Adaptive Learning Rate","authors":"Abdelrahman Ezzeldin Nagib, M. Saeed, Shereen Fathy El-Feky, Ali Khater Mohamed","doi":"10.1109/NILES50944.2020.9257880","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257880","url":null,"abstract":"Over the last two decades, the neural network has surprisingly arisen as an efficient tool for dealing with numerous real-life applications. Optimization of the hyperparameter of the neural network attracted many researchers in industrial and research areas because of its great effect on the quality of the solution. This paper presents a new adaptation for the learning rate with shock (ALRS) as the learning rate is considered one of the most important hyperparameters. The experimental results proved that the new adaptation leads to improved accuracy with a simpler structure for the neural network regardless of the initial value of the learning rate.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":"32 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":"124607013","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}
Pub Date : 2020-10-24DOI: 10.1109/NILES50944.2020.9257953
M. Hebaish, Mohamed A. Olwan, M. Ayman, AbdELRahman A. Genidy, W. Habib, N. Hassan, Omar Tarek Seada, E. I. Morgan
Multi-Vehicle Formation is an important step towards an efficient transportation system. In this paper, a 3-tier hybrid formation control architecture for connected vehicles is introduced. This architecture adopts the principle of a Hybrid StateChart in deliberative decision making layer for trajectories assignment, followed by an intermediate executional control layer for vehicles’ trajectory tracking. Finally, a functional control layer for low-level feedback control. The architecture is simulated using a set of miniature vehicles for parallel straight-line vehicle formation trajectory separated with an offset in the lateral direction. Furthermore, an experimental point to point control test was conducted on a single miniature vehicle for verifying the intermediate control layer. Results from the performed simulated experiments illustrate the effectiveness and the high precision of the proposed control architecture in terms of the minimum error between the vehicle’s longitudinal positions for straight-line formation trajectories tracking. While the experimental test illustrate the effectiveness of the used intermediate control layer.
{"title":"Adoption of Hybrid StateChart Principle in a Hierarchical Formation Architecture for Configurable Vehicles","authors":"M. Hebaish, Mohamed A. Olwan, M. Ayman, AbdELRahman A. Genidy, W. Habib, N. Hassan, Omar Tarek Seada, E. I. Morgan","doi":"10.1109/NILES50944.2020.9257953","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257953","url":null,"abstract":"Multi-Vehicle Formation is an important step towards an efficient transportation system. In this paper, a 3-tier hybrid formation control architecture for connected vehicles is introduced. This architecture adopts the principle of a Hybrid StateChart in deliberative decision making layer for trajectories assignment, followed by an intermediate executional control layer for vehicles’ trajectory tracking. Finally, a functional control layer for low-level feedback control. The architecture is simulated using a set of miniature vehicles for parallel straight-line vehicle formation trajectory separated with an offset in the lateral direction. Furthermore, an experimental point to point control test was conducted on a single miniature vehicle for verifying the intermediate control layer. Results from the performed simulated experiments illustrate the effectiveness and the high precision of the proposed control architecture in terms of the minimum error between the vehicle’s longitudinal positions for straight-line formation trajectories tracking. While the experimental test illustrate the effectiveness of the used intermediate control layer.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":"31 4-5 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":"132594343","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}
Traffic Characterization, Application Identification, Per Application Classification, and VPN/Non-VPN Traffic Characterization have been some of the most notable research topics over the past few years. Deep Packet Inspection (DPI) promises an increase in Quality of Service (QoS) for Internet Service Providers (ISPs), simplifies network management and plays a vital role in content censoring. DPI has been used to help ease the flow of network traffic. For instance, if there is a high priority message, DPI could be used to enable high-priority information to pass through immediately, ahead of other lower priority messages. It can be used to prioritize packets that are mission-critical, ahead of ordinary browsing packets. Throttling or slowing down the rate of data transfer can be achieved using DPI for certain traffic types like peer-to-peer downloads. It can also be used to enhance the capabilities of ISPs to prevent the exploitation of Internet of Things (IoT) devices in Distributed Denial-Of-Service (DDOS) attacks by blocking malicious requests from devices. In this paper, we introduce a novel architecture for DPI using neural networks utilizing layers of word embedding, convolutional neural networks and bidirectional recurrent neural networks which proved to have promising results in this task. The proposed architecture introduces a new mix of layers which outperforms the proposed approaches before.
{"title":"nnDPI: A Novel Deep Packet Inspection Technique Using Word Embedding, Convolutional and Recurrent Neural Networks","authors":"Mahmoud Bahaa, Ayman Aboulmagd, Khaled Adel, Hesham Fawzy, Nashwa Abdelbaki","doi":"10.1109/NILES50944.2020.9257912","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257912","url":null,"abstract":"Traffic Characterization, Application Identification, Per Application Classification, and VPN/Non-VPN Traffic Characterization have been some of the most notable research topics over the past few years. Deep Packet Inspection (DPI) promises an increase in Quality of Service (QoS) for Internet Service Providers (ISPs), simplifies network management and plays a vital role in content censoring. DPI has been used to help ease the flow of network traffic. For instance, if there is a high priority message, DPI could be used to enable high-priority information to pass through immediately, ahead of other lower priority messages. It can be used to prioritize packets that are mission-critical, ahead of ordinary browsing packets. Throttling or slowing down the rate of data transfer can be achieved using DPI for certain traffic types like peer-to-peer downloads. It can also be used to enhance the capabilities of ISPs to prevent the exploitation of Internet of Things (IoT) devices in Distributed Denial-Of-Service (DDOS) attacks by blocking malicious requests from devices. In this paper, we introduce a novel architecture for DPI using neural networks utilizing layers of word embedding, convolutional neural networks and bidirectional recurrent neural networks which proved to have promising results in this task. The proposed architecture introduces a new mix of layers which outperforms the proposed approaches before.","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":"132597534","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}
Pub Date : 2020-10-24DOI: 10.1109/NILES50944.2020.9257921
Marwa Zamzam, T. el-Shabrawy, M. Ashour
Edge computing is considered a promising approach to provide cloud computing capabilities at the edge of the network near to the users. However, the limited number of computation and communication resources at the edge have made the problem of offloading and resource allocation a challenging issue for service providers. Game theory analyzes the behavior of the users and succeeds to obtain solutions in this area where all users are satisfied and the problem reaches an equilibrium state. In this paper, first we give a brief background on game theory showing its definition, types and advantages. Second, we give an overview about edge computing system showing its architecture, challenges and kinds of resource management. Third, we provide a survey about significant achievements of applying game theory in edge computing problems. We categorize the state-of-the-art according to the objective function of the problem. It is divided into seven classes: 1) minimizing the latency, 2) minimizing the energy, 3) minimizing the cost, 4) minimizing both latency and energy, 5) minimizing energy and cost, 6) minimizing latency and cost and finally, 7) minimizing all together latency, cost and energy. Moreover, we present the lessons learned and the future research directions.
{"title":"Game Theory for Computation Offloading and Resource Allocation in Edge Computing: A Survey","authors":"Marwa Zamzam, T. el-Shabrawy, M. Ashour","doi":"10.1109/NILES50944.2020.9257921","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257921","url":null,"abstract":"Edge computing is considered a promising approach to provide cloud computing capabilities at the edge of the network near to the users. However, the limited number of computation and communication resources at the edge have made the problem of offloading and resource allocation a challenging issue for service providers. Game theory analyzes the behavior of the users and succeeds to obtain solutions in this area where all users are satisfied and the problem reaches an equilibrium state. In this paper, first we give a brief background on game theory showing its definition, types and advantages. Second, we give an overview about edge computing system showing its architecture, challenges and kinds of resource management. Third, we provide a survey about significant achievements of applying game theory in edge computing problems. We categorize the state-of-the-art according to the objective function of the problem. It is divided into seven classes: 1) minimizing the latency, 2) minimizing the energy, 3) minimizing the cost, 4) minimizing both latency and energy, 5) minimizing energy and cost, 6) minimizing latency and cost and finally, 7) minimizing all together latency, cost and energy. Moreover, we present the lessons learned and the future research directions.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":"1 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":"129347860","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}
Industry is increasingly adopting Reinforcement Learning algorithms (RL) in production without thoroughly analyzing their security features. In addition to the potential threats that may arise if the functionality of these algorithms is compromised while in operation. One of the well-known RL algorithms is the Contextual Multi-Armed Bandit (CMAB) algorithm. In this paper, we explore how the CMAB can be used to solve the Link Adaptation problem – a well-known problem in the telecommunication industry by learning the optimal transmission parameters that will maximize a communication link’s throughput. We analyze the potential vulnerabilities of the algorithm and how they may adversely affect link parameters computation. Additionally, we present a provable security assessment for the Contextual Multi-Armed Bandit Reinforcement Learning (CMAB-RL) algorithm in a network simulated environment using Ray. This is by demonstrating CMAB security vulnerabilities theoretically and practically. Some security controls are proposed for CMAB agent and the surrounding environment. In order to fix those vulnerabilities and mitigate the risk. These controls can be applied to other RL agents in order to design more robust and secure RL agents.
{"title":"Security Assessment of the Contextual Multi-Armed Bandit - RL Algorithm for Link Adaptation","authors":"Mariam El-Sobky, Hisham Sarhan, Mervat Abu-Elkheir","doi":"10.1109/NILES50944.2020.9257955","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257955","url":null,"abstract":"Industry is increasingly adopting Reinforcement Learning algorithms (RL) in production without thoroughly analyzing their security features. In addition to the potential threats that may arise if the functionality of these algorithms is compromised while in operation. One of the well-known RL algorithms is the Contextual Multi-Armed Bandit (CMAB) algorithm. In this paper, we explore how the CMAB can be used to solve the Link Adaptation problem – a well-known problem in the telecommunication industry by learning the optimal transmission parameters that will maximize a communication link’s throughput. We analyze the potential vulnerabilities of the algorithm and how they may adversely affect link parameters computation. Additionally, we present a provable security assessment for the Contextual Multi-Armed Bandit Reinforcement Learning (CMAB-RL) algorithm in a network simulated environment using Ray. This is by demonstrating CMAB security vulnerabilities theoretically and practically. Some security controls are proposed for CMAB agent and the surrounding environment. In order to fix those vulnerabilities and mitigate the risk. These controls can be applied to other RL agents in order to design more robust and secure RL agents.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":"67 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":"132297977","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}
Pub Date : 2020-10-24DOI: 10.1109/NILES50944.2020.9257898
Hady Hafez, S. Maged, A. Osama, M. Abdelaziz
This paper presents the transformation of a 14- seater multi- passenger golf cart to an autonomous level 3 vehicle by the Autotronics Research Lab team in Ain Shams University. The developed vehicle is to be used in closed environments such as campuses, resorts and clubs. Through this paper, we will discuss the mechanical and electrical modifications as well as the sensor suite of the car. In addition, the used algorithms in perception, localization and mapping, and the safety approaches taken in case of emergency for the passenger safety are discussed.
{"title":"Platform Modifications Towards an Autonomous Multi-Passenger Golf Cart","authors":"Hady Hafez, S. Maged, A. Osama, M. Abdelaziz","doi":"10.1109/NILES50944.2020.9257898","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257898","url":null,"abstract":"This paper presents the transformation of a 14- seater multi- passenger golf cart to an autonomous level 3 vehicle by the Autotronics Research Lab team in Ain Shams University. The developed vehicle is to be used in closed environments such as campuses, resorts and clubs. Through this paper, we will discuss the mechanical and electrical modifications as well as the sensor suite of the car. In addition, the used algorithms in perception, localization and mapping, and the safety approaches taken in case of emergency for the passenger safety are discussed.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":"14 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":"128067573","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}
Pub Date : 2020-10-24DOI: 10.1109/NILES50944.2020.9257916
Santiago Ramos Garces, Mayra Yucely Beb, Abdoulaye Boubakari, H. Ammar, Mohamed A. Wahby Shalaby
Over the past decade, mobile autonomous robots have been widely used efficiently for different applications. Recently, self-balancing robots attracted more attention and showed impressive performance. A self-balancing robot is simply a two-wheeled robot; hence it needs to be balanced vertically using a closed-loop control algorithm. In this paper, a new hybrid two-wheeled self-balancing robot is fully designed and implemented, which is able to track objects and to avoid obstacles efficiently. The proposed robot consists of a two-wheeled chassis equipped with an ultrasonic sensor, camera, gyroscope and accelerometer allowing a multi-directional navigation of the robot tracker. Additionally, the Internet of Things (IOT) framework has been used for remote control and monitoring via wireless interface. The Fuzzy Logic Controller is designed considering all the realistic hindrances in order to achieve high performance and meet robust stability. To approximate the position of an object about the robot, vision system and ultrasonic sensor coupled with a camera are used. Finally, it has been observed via simulation and hardware implementation the efficiency of fuzzy control technique which achieved both stability and robustness outcomes; however, due to processing restrictions other control techniques are also successfully implemented. Regarding the experimental results it can be concluded that, balancing and tracking techniques can be achieved by applying sequential algorithm in Simulink combined with vision system and sensors like ultrasonic, accelerometer and gyroscope.
{"title":"Hybrid Self-Balancing and object Tracking Robot Using Artificial Intelligence and Machine Vision","authors":"Santiago Ramos Garces, Mayra Yucely Beb, Abdoulaye Boubakari, H. Ammar, Mohamed A. Wahby Shalaby","doi":"10.1109/NILES50944.2020.9257916","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257916","url":null,"abstract":"Over the past decade, mobile autonomous robots have been widely used efficiently for different applications. Recently, self-balancing robots attracted more attention and showed impressive performance. A self-balancing robot is simply a two-wheeled robot; hence it needs to be balanced vertically using a closed-loop control algorithm. In this paper, a new hybrid two-wheeled self-balancing robot is fully designed and implemented, which is able to track objects and to avoid obstacles efficiently. The proposed robot consists of a two-wheeled chassis equipped with an ultrasonic sensor, camera, gyroscope and accelerometer allowing a multi-directional navigation of the robot tracker. Additionally, the Internet of Things (IOT) framework has been used for remote control and monitoring via wireless interface. The Fuzzy Logic Controller is designed considering all the realistic hindrances in order to achieve high performance and meet robust stability. To approximate the position of an object about the robot, vision system and ultrasonic sensor coupled with a camera are used. Finally, it has been observed via simulation and hardware implementation the efficiency of fuzzy control technique which achieved both stability and robustness outcomes; however, due to processing restrictions other control techniques are also successfully implemented. Regarding the experimental results it can be concluded that, balancing and tracking techniques can be achieved by applying sequential algorithm in Simulink combined with vision system and sensors like ultrasonic, accelerometer and gyroscope.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":"28 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":"129264542","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}
Pub Date : 2020-10-24DOI: 10.1109/NILES50944.2020.9257960
A. Ibrahim, Mohab Mohammed Eid, Nagham Nessim Mostafa, Nour El-Hoda Mohamed Bishady, Samar Hassan Elghalban
The effect of population density on the initial spread of the novel Covid-19 virus has been evaluated using the numerical data of fifty pioneer adopting countries in their first thirty days experience with the disease. The fifty countries were curdled into ten groups that each of them possesses an average population density and each group’s virus’s spread was modeled in a two-dimensional graph with the use of MATLAB curve fitting. The modeling is done based on the exponential growth equation. The stringency index model was also utilized a source of analysis regarding the government responses of the groups in study. Finally, population density was found to be not a significant contributor in controlling Covid-19 epidemic in the very first month of spread; however, countries with denser populations were found better to adopt stricter regulations especially in the first month of spread as Covid-19 outbreak and total number of cases is
{"title":"Modeling the effect of population density on controlling Covid-19 initial Spread with the use of MATLAB numerical methods and stringency index model","authors":"A. Ibrahim, Mohab Mohammed Eid, Nagham Nessim Mostafa, Nour El-Hoda Mohamed Bishady, Samar Hassan Elghalban","doi":"10.1109/NILES50944.2020.9257960","DOIUrl":"https://doi.org/10.1109/NILES50944.2020.9257960","url":null,"abstract":"The effect of population density on the initial spread of the novel Covid-19 virus has been evaluated using the numerical data of fifty pioneer adopting countries in their first thirty days experience with the disease. The fifty countries were curdled into ten groups that each of them possesses an average population density and each group’s virus’s spread was modeled in a two-dimensional graph with the use of MATLAB curve fitting. The modeling is done based on the exponential growth equation. The stringency index model was also utilized a source of analysis regarding the government responses of the groups in study. Finally, population density was found to be not a significant contributor in controlling Covid-19 epidemic in the very first month of spread; however, countries with denser populations were found better to adopt stricter regulations especially in the first month of spread as Covid-19 outbreak and total number of cases is","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":"41 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":"123299069","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}
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