Pub Date : 2020-02-01DOI: 10.1109/AECT47998.2020.9194204
Alaa Saggah, R. Campion, A. Atkins
The paper aims to pragmatically develop a method to support teachers to transfer their pedagogical knowledge into game requirements for educational purposes. The paper utilizes a qualitative approach, ‘think aloud’ interview protocol. The case study includes six teachers from a varied background and teaching experience in the Kingdom of Saudi Arabia (KSA). The analogy between teachers’ in-theory categorization and practical task design was used to validate the practicality of the framework components in helping teachers to identify game requirements from a pedagogical point of view. The outcome of this research identifies the factors that facilitate the collaboration between both teachers and game developers. An Agile Holistic Gamified Pedagogical Design framework(AHGPD) has been developed to provide a structured guidance for teachers regardless of their technical knowledge level. Future work will be to integrate the AH-GPD framework to produce a practical Pedagogical Game Design Document that can be used to build a repository of games requirements for educational purposes and enable faster roll out to support teachers in school environments.
{"title":"An Agile Holistic Framework to Support Teachers in Pedagogical Gamification Design","authors":"Alaa Saggah, R. Campion, A. Atkins","doi":"10.1109/AECT47998.2020.9194204","DOIUrl":"https://doi.org/10.1109/AECT47998.2020.9194204","url":null,"abstract":"The paper aims to pragmatically develop a method to support teachers to transfer their pedagogical knowledge into game requirements for educational purposes. The paper utilizes a qualitative approach, ‘think aloud’ interview protocol. The case study includes six teachers from a varied background and teaching experience in the Kingdom of Saudi Arabia (KSA). The analogy between teachers’ in-theory categorization and practical task design was used to validate the practicality of the framework components in helping teachers to identify game requirements from a pedagogical point of view. The outcome of this research identifies the factors that facilitate the collaboration between both teachers and game developers. An Agile Holistic Gamified Pedagogical Design framework(AHGPD) has been developed to provide a structured guidance for teachers regardless of their technical knowledge level. Future work will be to integrate the AH-GPD framework to produce a practical Pedagogical Game Design Document that can be used to build a repository of games requirements for educational purposes and enable faster roll out to support teachers in school environments.","PeriodicalId":331415,"journal":{"name":"2019 International Conference on Advances in the Emerging Computing Technologies (AECT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127899200","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 : 2020-02-01DOI: 10.1109/AECT47998.2020.9194169
S. Aslam, S. Aslam, H. Herodotou, Syed Muhammad Mohsin, Khursheed Aurangzeb
This study investigates the energy cost and carbon emission reduction problem in geographically distributed cloud data centers (DCs), where each DC is connected with its own renewable energy resources (RERs) for green energy generation. We consider four cloud DCs that are operated by a single cloud service provider. They consume energy from both RERs and from the commercial grid to meet the demand of cloud users. For energy pricing, we consider four different energy markets that offer varying energy prices per hour. Additionally, our proposed strategy enables DCs to sell excess electricity to the commercial grid in peak-price hours and purchase in low-cost hours according to power trading. This work also exploits energy storage devices (ESDs) to store energy for future use. We utilize real-time data requests, weather data, and pricing data for performing simulations and results affirm the effectiveness and productiveness of our proposed method to mitigate the energy cost and carbon emission of cloud DCs.
{"title":"Towards Energy Efficiency and Power Trading Exploiting Renewable Energy in Cloud Data Centers","authors":"S. Aslam, S. Aslam, H. Herodotou, Syed Muhammad Mohsin, Khursheed Aurangzeb","doi":"10.1109/AECT47998.2020.9194169","DOIUrl":"https://doi.org/10.1109/AECT47998.2020.9194169","url":null,"abstract":"This study investigates the energy cost and carbon emission reduction problem in geographically distributed cloud data centers (DCs), where each DC is connected with its own renewable energy resources (RERs) for green energy generation. We consider four cloud DCs that are operated by a single cloud service provider. They consume energy from both RERs and from the commercial grid to meet the demand of cloud users. For energy pricing, we consider four different energy markets that offer varying energy prices per hour. Additionally, our proposed strategy enables DCs to sell excess electricity to the commercial grid in peak-price hours and purchase in low-cost hours according to power trading. This work also exploits energy storage devices (ESDs) to store energy for future use. We utilize real-time data requests, weather data, and pricing data for performing simulations and results affirm the effectiveness and productiveness of our proposed method to mitigate the energy cost and carbon emission of cloud DCs.","PeriodicalId":331415,"journal":{"name":"2019 International Conference on Advances in the Emerging Computing Technologies (AECT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128372385","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 : 2020-02-01DOI: 10.1109/AECT47998.2020.9194185
Md Shihabul Islam, L. Khan
The growing adoption of IoT devices in our daily life engendered a need for secure systems to safely store or analyze sensitive data, as well as a decentralized data processing system to handle vast amount of streaming data. The cloud services used to store data and process sensitive data are often come out to be vulnerable to outside threats. Moreover, to analyze enormous streaming data swiftly, they are in need of a fast and efficient system. In this paper we propose a framework to maintain confidentiality and integrity of IoT data, which is of paramount importance, and manage large-scale data anaytics. We design the framework to preserve data privacy utilizing Trusted Execution Environment (TEE) such as Intel SGX, and end-to-end data encryption mechanism. In addition, we utilize Apache Spark for fast real-time streaming data processing from many IoT devices. We evaluate the framework by performing simple decision making in the SGX securely that involves multiple IoT devices, and a real-time anomaly detection in the streaming data from IoT devices using Spark.
{"title":"Big Data Driven Secure IoT Analytics with Trusted Execution Environments","authors":"Md Shihabul Islam, L. Khan","doi":"10.1109/AECT47998.2020.9194185","DOIUrl":"https://doi.org/10.1109/AECT47998.2020.9194185","url":null,"abstract":"The growing adoption of IoT devices in our daily life engendered a need for secure systems to safely store or analyze sensitive data, as well as a decentralized data processing system to handle vast amount of streaming data. The cloud services used to store data and process sensitive data are often come out to be vulnerable to outside threats. Moreover, to analyze enormous streaming data swiftly, they are in need of a fast and efficient system. In this paper we propose a framework to maintain confidentiality and integrity of IoT data, which is of paramount importance, and manage large-scale data anaytics. We design the framework to preserve data privacy utilizing Trusted Execution Environment (TEE) such as Intel SGX, and end-to-end data encryption mechanism. In addition, we utilize Apache Spark for fast real-time streaming data processing from many IoT devices. We evaluate the framework by performing simple decision making in the SGX securely that involves multiple IoT devices, and a real-time anomaly detection in the streaming data from IoT devices using Spark.","PeriodicalId":331415,"journal":{"name":"2019 International Conference on Advances in the Emerging Computing Technologies (AECT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128524363","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 : 2020-02-01DOI: 10.1109/AECT47998.2020.9194195
Noura El Shabasy, M. Abdellatif
Nowadays, technology has become more reliable that allowed human interaction to decrease while the machines have started to take over in many fields of interest. The Internet of things (IoT) represents the idea of machines ability to control entire systems without any human interactions. This paper proposes an IoT system that takes a picture of parked cars in a garage, extract the plate number and the location of the car, and places these information in a database. At the garage entrance, a terminal linked to the system allows the user to locate the parked car using the license plate no.. The system is tested for reading license plates several times, and is shown to perform with a low probability of error. The proposed IoT parking system is an integrated system combining the RPi operating system Motion Eye, with MATLAB segmentation code for character recognition, database tools, as well as web services all in order to make the user interface as friendly as possible.
{"title":"IoT for Smart Parking","authors":"Noura El Shabasy, M. Abdellatif","doi":"10.1109/AECT47998.2020.9194195","DOIUrl":"https://doi.org/10.1109/AECT47998.2020.9194195","url":null,"abstract":"Nowadays, technology has become more reliable that allowed human interaction to decrease while the machines have started to take over in many fields of interest. The Internet of things (IoT) represents the idea of machines ability to control entire systems without any human interactions. This paper proposes an IoT system that takes a picture of parked cars in a garage, extract the plate number and the location of the car, and places these information in a database. At the garage entrance, a terminal linked to the system allows the user to locate the parked car using the license plate no.. The system is tested for reading license plates several times, and is shown to perform with a low probability of error. The proposed IoT parking system is an integrated system combining the RPi operating system Motion Eye, with MATLAB segmentation code for character recognition, database tools, as well as web services all in order to make the user interface as friendly as possible.","PeriodicalId":331415,"journal":{"name":"2019 International Conference on Advances in the Emerging Computing Technologies (AECT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115166357","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 : 2020-02-01DOI: 10.1109/AECT47998.2020.9194182
N. N. Hussaini, Syed Muhammad Jamil Shah, M. A. Shaikh, S. Faizullah
Evolution of multicast routing protocols for MANET are becoming the center of attraction for scholars of these days. This is due to varying applications areas, which in turn requires appropriate routing schemes for them. In the environment of mobile ad hoc networks, multicast communication efficiently saves the network resources. Adapting MANET as local area social networks allows new nodes to keep arriving and existing nodes departing the network as and when they like. Multicast routing protocols need to be readdressed to introduce the openness of the node set in such environments. The research paper focuses on evaluating the performance of routing scheme used by SLIM+in multicast of live video or audio streaming to the freely interested devices or nodes, coming in the antenna rage. Performance metric used is Packet Delivery Ratio and End-to-End-Delay; by comparing it with its competitive and most commonly used tree based and mesh based multicast routing protocols. It then observed that SLIM+ remained successful in utmost delivery of data packets to the destinations thus took a little bit increased but insignificant time to advertise for live streaming. Whereas its counterpart MAODV failed in successful delivery of the data packets to the desired destinations and become free in less time. Whereas SLIM+ with its tree based structure competed with mesh based structured PUMA.
{"title":"Live multimedia streaming multicast in local area social networking environment of MANETs using SLIM+ Protocol","authors":"N. N. Hussaini, Syed Muhammad Jamil Shah, M. A. Shaikh, S. Faizullah","doi":"10.1109/AECT47998.2020.9194182","DOIUrl":"https://doi.org/10.1109/AECT47998.2020.9194182","url":null,"abstract":"Evolution of multicast routing protocols for MANET are becoming the center of attraction for scholars of these days. This is due to varying applications areas, which in turn requires appropriate routing schemes for them. In the environment of mobile ad hoc networks, multicast communication efficiently saves the network resources. Adapting MANET as local area social networks allows new nodes to keep arriving and existing nodes departing the network as and when they like. Multicast routing protocols need to be readdressed to introduce the openness of the node set in such environments. The research paper focuses on evaluating the performance of routing scheme used by SLIM+in multicast of live video or audio streaming to the freely interested devices or nodes, coming in the antenna rage. Performance metric used is Packet Delivery Ratio and End-to-End-Delay; by comparing it with its competitive and most commonly used tree based and mesh based multicast routing protocols. It then observed that SLIM+ remained successful in utmost delivery of data packets to the destinations thus took a little bit increased but insignificant time to advertise for live streaming. Whereas its counterpart MAODV failed in successful delivery of the data packets to the desired destinations and become free in less time. Whereas SLIM+ with its tree based structure competed with mesh based structured PUMA.","PeriodicalId":331415,"journal":{"name":"2019 International Conference on Advances in the Emerging Computing Technologies (AECT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116855803","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 : 2020-02-01DOI: 10.1109/AECT47998.2020.9194202
Ahsen Tahir, Jawad Ahmad, Syed Aziz Shah, Q. Abbasi
Big data graph analytics is the future of high performance computing and key to many current and future applications. There is a growing demand for high performance graph computing for real-world social network graphs. Real-world graph algorithms are memory-intensive and generate a high percentage of accesses to the memory subsystem due to low cache locality. Near memory or 3D die-stacked memory, known for its low latency, high bandwidth communication has the potential to improve the performance of big data graph analytics.In this paper, we analyse, evaluate and compare the performance of a near memory system for big data graph analytics. Real-world graphs associated with social networks and the web are processed with graph analytics algorithms in a simulated near memory system. The performance advantage of near memory with a large number of simple in-order processor cores for graph analysis is presented.The proposed system provides a performance per Watt improvement of $3.55 - 8.55 times$ for Breadth-First Search algorithm for big data graphs over computing systems with fat cores and traditional Double Data Rate (DDR) memory. The proposed near memory computing system provides a considerable improvement in computational performance of graph analytics algorithms with an average improvement in Instructions Per Cycle (IPC) of $5 times$ and in performance per Watt of $7 times$.
{"title":"High Performance Big Data Graph Analytics Leveraging Near Memory System","authors":"Ahsen Tahir, Jawad Ahmad, Syed Aziz Shah, Q. Abbasi","doi":"10.1109/AECT47998.2020.9194202","DOIUrl":"https://doi.org/10.1109/AECT47998.2020.9194202","url":null,"abstract":"Big data graph analytics is the future of high performance computing and key to many current and future applications. There is a growing demand for high performance graph computing for real-world social network graphs. Real-world graph algorithms are memory-intensive and generate a high percentage of accesses to the memory subsystem due to low cache locality. Near memory or 3D die-stacked memory, known for its low latency, high bandwidth communication has the potential to improve the performance of big data graph analytics.In this paper, we analyse, evaluate and compare the performance of a near memory system for big data graph analytics. Real-world graphs associated with social networks and the web are processed with graph analytics algorithms in a simulated near memory system. The performance advantage of near memory with a large number of simple in-order processor cores for graph analysis is presented.The proposed system provides a performance per Watt improvement of $3.55 - 8.55 times$ for Breadth-First Search algorithm for big data graphs over computing systems with fat cores and traditional Double Data Rate (DDR) memory. The proposed near memory computing system provides a considerable improvement in computational performance of graph analytics algorithms with an average improvement in Instructions Per Cycle (IPC) of $5 times$ and in performance per Watt of $7 times$.","PeriodicalId":331415,"journal":{"name":"2019 International Conference on Advances in the Emerging Computing Technologies (AECT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133340507","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 : 2019-12-27DOI: 10.1109/AECT47998.2020.9194186
M. Shakeel, Turki Alghamidi, S. Faizullah, Imdadullah Khan
Social media platforms and online forums generate a rapid and increasing amount of textual data. Businesses, government agencies, and media organizations seek to perform sentiment analysis on this rich text data. The results of these analytics are used for adapting marketing strategies, customizing products, security, and various other decision makings. Sentiment analysis has been extensively studied and various methods have been developed for it with great success. These methods, however, apply to texts written in a specific language. This limits the applicability to a particular demographic and geographic region. In this paper, we propose a general approach for sentiment analysis on data containing texts from multiple languages. This enables all the applications to utilize the results of sentiment analysis in a language oblivious or language-independent fashion.
{"title":"Language Independent Sentiment Analysis","authors":"M. Shakeel, Turki Alghamidi, S. Faizullah, Imdadullah Khan","doi":"10.1109/AECT47998.2020.9194186","DOIUrl":"https://doi.org/10.1109/AECT47998.2020.9194186","url":null,"abstract":"Social media platforms and online forums generate a rapid and increasing amount of textual data. Businesses, government agencies, and media organizations seek to perform sentiment analysis on this rich text data. The results of these analytics are used for adapting marketing strategies, customizing products, security, and various other decision makings. Sentiment analysis has been extensively studied and various methods have been developed for it with great success. These methods, however, apply to texts written in a specific language. This limits the applicability to a particular demographic and geographic region. In this paper, we propose a general approach for sentiment analysis on data containing texts from multiple languages. This enables all the applications to utilize the results of sentiment analysis in a language oblivious or language-independent fashion.","PeriodicalId":331415,"journal":{"name":"2019 International Conference on Advances in the Emerging Computing Technologies (AECT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113983278","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 : 2019-12-27DOI: 10.1109/AECT47998.2020.9194211
Abdullah M. Alshanqiti, S. Faizullah, Sarwan Ali, Maria K. Alvi, Muhammad Asad Khan, Imdadullah Khan
Software Defined Networking (SDN) is a network paradigm shift that facilitates comprehensive network programmability to cope with emerging new technologies such as cloud computing and big data. SDN facilitates simplified and centralized network management enabling it to operate in dynamic scenarios. Further, SDN uses the OpenFlow protocol for communication between the controller and its switches. The OpenFlow creates vulnerabilities for network attacks especially Distributed Denial of Service (DDoS). DDoS attacks are launched from the compromised hosts connected to the SDN switches. In this paper, we introduce a timeand space-efficient solution for the identification of these compromised hosts. Our solution consumes less computational resources and space and does not require any special equipment.
{"title":"Detecting DDoS Attack on SDN Due to Vulnerabilities in OpenFlow","authors":"Abdullah M. Alshanqiti, S. Faizullah, Sarwan Ali, Maria K. Alvi, Muhammad Asad Khan, Imdadullah Khan","doi":"10.1109/AECT47998.2020.9194211","DOIUrl":"https://doi.org/10.1109/AECT47998.2020.9194211","url":null,"abstract":"Software Defined Networking (SDN) is a network paradigm shift that facilitates comprehensive network programmability to cope with emerging new technologies such as cloud computing and big data. SDN facilitates simplified and centralized network management enabling it to operate in dynamic scenarios. Further, SDN uses the OpenFlow protocol for communication between the controller and its switches. The OpenFlow creates vulnerabilities for network attacks especially Distributed Denial of Service (DDoS). DDoS attacks are launched from the compromised hosts connected to the SDN switches. In this paper, we introduce a timeand space-efficient solution for the identification of these compromised hosts. Our solution consumes less computational resources and space and does not require any special equipment.","PeriodicalId":331415,"journal":{"name":"2019 International Conference on Advances in the Emerging Computing Technologies (AECT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114416772","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 : 2019-10-20DOI: 10.1109/AECT47998.2020.9194188
Metin Ozturk, J. Nadas, P. V. Klaine, S. Hussain, M. Imran
Unmanned aerial vehicles (UAVs) are expected to be deployed in a variety of applications in future mobile networks due to several advantages they bring over the deployment of ground base stations. However, despite the recent interest in UAVs in mobile networks, some issues still remain, such as determining the placement of multiple UAVs in different scenarios. In this paper we propose a solution to determine the optimal 3D position of multiple UAVs in a capacity enhancement use-case, or in other words, when the ground network cannot cope with the user traffic demand. For this scenario, real data from the city of Milan, provided by Telecom Italia is utilized to simulate an event. Based on that, a solution based on k-means, a machine learning technique, to position multiple UAVs is proposed and it is compared with two other baseline methods. Results demonstrate that the proposed solution is able to significantly outperform other methods in terms of users covered and quality of service.
{"title":"Clustering Based UAV Base Station Positioning for Enhanced Network Capacity","authors":"Metin Ozturk, J. Nadas, P. V. Klaine, S. Hussain, M. Imran","doi":"10.1109/AECT47998.2020.9194188","DOIUrl":"https://doi.org/10.1109/AECT47998.2020.9194188","url":null,"abstract":"Unmanned aerial vehicles (UAVs) are expected to be deployed in a variety of applications in future mobile networks due to several advantages they bring over the deployment of ground base stations. However, despite the recent interest in UAVs in mobile networks, some issues still remain, such as determining the placement of multiple UAVs in different scenarios. In this paper we propose a solution to determine the optimal 3D position of multiple UAVs in a capacity enhancement use-case, or in other words, when the ground network cannot cope with the user traffic demand. For this scenario, real data from the city of Milan, provided by Telecom Italia is utilized to simulate an event. Based on that, a solution based on k-means, a machine learning technique, to position multiple UAVs is proposed and it is compared with two other baseline methods. Results demonstrate that the proposed solution is able to significantly outperform other methods in terms of users covered and quality of service.","PeriodicalId":331415,"journal":{"name":"2019 International Conference on Advances in the Emerging Computing Technologies (AECT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127795578","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 : 2019-10-14DOI: 10.1109/AECT47998.2020.9194165
Muhammad Ilyas, O. Bayat, O. Ucan, M. Imran, Q. Abbasi
This paper presents an impact on an in-vivo channel with respect to the position of ex-vivo antenna placement and its location. The paper also shows how the location of the antenna is impacting the channel. Three different parts are considered for the simulations using measured data for 500 MHz bandwidth. The results in the paper present the high location dependent characteristics of the in-vivo channel in the context of changing the position of the ex-vivo antenna. These findings can help in the system design for the future of the implantable devices design to be placed inside the human body.
{"title":"Location Dependent Channel Characteristics for Implantable Devices","authors":"Muhammad Ilyas, O. Bayat, O. Ucan, M. Imran, Q. Abbasi","doi":"10.1109/AECT47998.2020.9194165","DOIUrl":"https://doi.org/10.1109/AECT47998.2020.9194165","url":null,"abstract":"This paper presents an impact on an in-vivo channel with respect to the position of ex-vivo antenna placement and its location. The paper also shows how the location of the antenna is impacting the channel. Three different parts are considered for the simulations using measured data for 500 MHz bandwidth. The results in the paper present the high location dependent characteristics of the in-vivo channel in the context of changing the position of the ex-vivo antenna. These findings can help in the system design for the future of the implantable devices design to be placed inside the human body.","PeriodicalId":331415,"journal":{"name":"2019 International Conference on Advances in the Emerging Computing Technologies (AECT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127640750","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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