Pub Date : 2020-03-01DOI: 10.1109/ICICT50521.2020.00037
Toshiro Minami, Y. Ohura
The main aim of this paper is to investigate the social relationship among students using their seat position data. Together with the lecturer's intuitive recognition, we are able to know more about student's attitude and style to learning, which helps the lecturers to provide the students with more effective lectures. In this paper, we use the distance of seat positions of students as the index for their friendship relation and find student groups. By combining our findings in our previous studies, we are convinced that data analysis is a very useful tool for understanding students' behavior, which will help the lectures to have useful tips for delivering better lectures.
{"title":"An Investigation on Social Relations between University Students from Seat Position Data","authors":"Toshiro Minami, Y. Ohura","doi":"10.1109/ICICT50521.2020.00037","DOIUrl":"https://doi.org/10.1109/ICICT50521.2020.00037","url":null,"abstract":"The main aim of this paper is to investigate the social relationship among students using their seat position data. Together with the lecturer's intuitive recognition, we are able to know more about student's attitude and style to learning, which helps the lecturers to provide the students with more effective lectures. In this paper, we use the distance of seat positions of students as the index for their friendship relation and find student groups. By combining our findings in our previous studies, we are convinced that data analysis is a very useful tool for understanding students' behavior, which will help the lectures to have useful tips for delivering better lectures.","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124099064","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 : 2020-03-01DOI: 10.1109/icict50521.2020.00001
{"title":"[Title page i]","authors":"","doi":"10.1109/icict50521.2020.00001","DOIUrl":"https://doi.org/10.1109/icict50521.2020.00001","url":null,"abstract":"","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"577 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123405777","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 : 2020-03-01DOI: 10.1109/ICICT50521.2020.00079
A. Abdelaziz, Mahmoud Mandour, A. Elbayoumy, G. Abdel-Hamid
Prioritizing handover calls is an important process in cellular networks. The blocking/dropping calls occurred when there is no free channel is assigned for the subscriber. So, we are going to devise a new scheme for handling the calls among the network. In this paper, the main idea is to maintain an acceptable blocking/dropping trade-off probability for the indoor cells. The proposed solution will show how to change dynamically the number of reserved channels and optimizing it based on the incoming offered traffic type (new or handover calls). The Guard Channel and Non-Prioritized schemes are considered. Finally, the results reveal that call blocking and dropping probabilities performs better while compared with the other existing scheme.
{"title":"Dynamic Channel Allocation Scheme for Handover Calls in Cellular Networks","authors":"A. Abdelaziz, Mahmoud Mandour, A. Elbayoumy, G. Abdel-Hamid","doi":"10.1109/ICICT50521.2020.00079","DOIUrl":"https://doi.org/10.1109/ICICT50521.2020.00079","url":null,"abstract":"Prioritizing handover calls is an important process in cellular networks. The blocking/dropping calls occurred when there is no free channel is assigned for the subscriber. So, we are going to devise a new scheme for handling the calls among the network. In this paper, the main idea is to maintain an acceptable blocking/dropping trade-off probability for the indoor cells. The proposed solution will show how to change dynamically the number of reserved channels and optimizing it based on the incoming offered traffic type (new or handover calls). The Guard Channel and Non-Prioritized schemes are considered. Finally, the results reveal that call blocking and dropping probabilities performs better while compared with the other existing scheme.","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125756954","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 : 2020-03-01DOI: 10.1109/icict50521.2020.00003
{"title":"[Copyright notice]","authors":"","doi":"10.1109/icict50521.2020.00003","DOIUrl":"https://doi.org/10.1109/icict50521.2020.00003","url":null,"abstract":"","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126753799","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 : 2020-03-01DOI: 10.1109/ICICT50521.2020.00025
Rebecca Miao, Zhenyi Yang, V. Gavrishchaka
Identification of rare states and training models with limited data is fundamentally challenging for mainstream machine learning. Alternative approaches include one-shot learning using similarities to reference classes, meta-learning training on many related tasks and transfer learning using relevant pre-trained model. However, their performance quickly deteriorates with decreasing number of available reference classes and related tasks or lack of relevant problem for transfer learning. Previously, we proposed ensemble decomposition learning (EDL) where boosting-ensemble components trained on just two broad classes provide large number of implicit reference classes. Domain-expert knowledge such as complexity measures can be directly incorporated within EDL to reduce dependence on training data. However, success of EDL and similar approaches requires variety of complexity measures sufficiently flexible for further tuning given enough data which is not always available. Therefore, addition of complementary measures not requiring fine-tuning is important. Persistent homology (PH), one of computational topology tools, offers noise-tolerant topological summary of data set. Direct application of PH to high-dimensional data is often prohibitive and requires domain-specific dimensionality reduction. Here we suggest that PH computed on complexity measures rather than raw data could provide robust complementary metrics for enhancement of rare state representation as illustrated in the context of personalized medicine application using data from www.physionet.org.
{"title":"Topological Representation of Rare States Using Combination of Persistent Homology and Complexity Measures","authors":"Rebecca Miao, Zhenyi Yang, V. Gavrishchaka","doi":"10.1109/ICICT50521.2020.00025","DOIUrl":"https://doi.org/10.1109/ICICT50521.2020.00025","url":null,"abstract":"Identification of rare states and training models with limited data is fundamentally challenging for mainstream machine learning. Alternative approaches include one-shot learning using similarities to reference classes, meta-learning training on many related tasks and transfer learning using relevant pre-trained model. However, their performance quickly deteriorates with decreasing number of available reference classes and related tasks or lack of relevant problem for transfer learning. Previously, we proposed ensemble decomposition learning (EDL) where boosting-ensemble components trained on just two broad classes provide large number of implicit reference classes. Domain-expert knowledge such as complexity measures can be directly incorporated within EDL to reduce dependence on training data. However, success of EDL and similar approaches requires variety of complexity measures sufficiently flexible for further tuning given enough data which is not always available. Therefore, addition of complementary measures not requiring fine-tuning is important. Persistent homology (PH), one of computational topology tools, offers noise-tolerant topological summary of data set. Direct application of PH to high-dimensional data is often prohibitive and requires domain-specific dimensionality reduction. Here we suggest that PH computed on complexity measures rather than raw data could provide robust complementary metrics for enhancement of rare state representation as illustrated in the context of personalized medicine application using data from www.physionet.org.","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128020880","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 : 2020-03-01DOI: 10.1109/ICICT50521.2020.00096
S. Girija, R. Rao
Impulse noise is a major performance degrading factor, as it impairs the communication systems, such as mobile radio system, digital subscriber line system, and power line. Various Constant Modulus algorithms (CMA) were introduced to reduce the average of constant modulus error between the constant modulus and the equalizer output power in the impulsive noise environment. However, the existing blind learning methods generate large mis-adjustment and slow convergence rate in the impulse noise of Multiple Input Multiple Output (MIMO) system. To solve the impulse noise problem, the blind equalization method named Robust Adaptive Autoregressive weighted constant modulus algorithm (RAAWCMA) is introduced in this research work for MIMO system. Due to the feasibility and simplicity of stable convergence property, the proposed Robust Adaptive Autoregressive weighted constant modulus algorithm for blind equalization is utilized to solve the complexity of impulse noise in MIMO system. The proposed blind equalization method increases the performance of equalization by adjusting the weight vector based on the samples of output error. Moreover, the maximum average value obtained by the proposed algorithm is revealed based on the evaluation metrics, like Bit Error Rate, Symbol Error Rate, and Mean Square Error which acquire the values of 0.0005, 0.0005, and 0.0001 with the Rayleigh channel, and 0.0004, 0.0004, and 0.0001 with the Rician channel using six antennas.
{"title":"Robust Adaptive AutoRegressive Weighted Constant Modulus Algorithm for Blind Equalization in MIMO-OFDM System","authors":"S. Girija, R. Rao","doi":"10.1109/ICICT50521.2020.00096","DOIUrl":"https://doi.org/10.1109/ICICT50521.2020.00096","url":null,"abstract":"Impulse noise is a major performance degrading factor, as it impairs the communication systems, such as mobile radio system, digital subscriber line system, and power line. Various Constant Modulus algorithms (CMA) were introduced to reduce the average of constant modulus error between the constant modulus and the equalizer output power in the impulsive noise environment. However, the existing blind learning methods generate large mis-adjustment and slow convergence rate in the impulse noise of Multiple Input Multiple Output (MIMO) system. To solve the impulse noise problem, the blind equalization method named Robust Adaptive Autoregressive weighted constant modulus algorithm (RAAWCMA) is introduced in this research work for MIMO system. Due to the feasibility and simplicity of stable convergence property, the proposed Robust Adaptive Autoregressive weighted constant modulus algorithm for blind equalization is utilized to solve the complexity of impulse noise in MIMO system. The proposed blind equalization method increases the performance of equalization by adjusting the weight vector based on the samples of output error. Moreover, the maximum average value obtained by the proposed algorithm is revealed based on the evaluation metrics, like Bit Error Rate, Symbol Error Rate, and Mean Square Error which acquire the values of 0.0005, 0.0005, and 0.0001 with the Rayleigh channel, and 0.0004, 0.0004, and 0.0001 with the Rician channel using six antennas.","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131633537","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 : 2020-03-01DOI: 10.1109/ICICT50521.2020.00085
Kimo Bumanglag, H. Kettani
The Domain Name System (DNS) protocol has been in use for over thirty years. As the primary method of resolving domain names to Internet Protocol (IP) addresses, it is a fundamental component of the Internet. Despite its position of importance, the protocol lacks built-in security mechanisms to address confidentiality, integrity, or availability. Malware can use DNS to fulfill attacker objectives, such as establishing command and control (C2) or exfiltrating data. Various enhancements have been implemented in an attempt to address security after-the-fact. The latest such enhancement is DNS over HTTPS. Methods have also been developed to detect malware's use of DNS. In this paper, we review the weaknesses of the DNS protocol and how malware has abused those weaknesses, enhancements to DNS security, and how malware uses DNS and how that use is detected, with a special emphasis on the effects that DNS over HTTPS may have on an organization's security.
{"title":"On the Impact of DNS Over HTTPS Paradigm on Cyber Systems","authors":"Kimo Bumanglag, H. Kettani","doi":"10.1109/ICICT50521.2020.00085","DOIUrl":"https://doi.org/10.1109/ICICT50521.2020.00085","url":null,"abstract":"The Domain Name System (DNS) protocol has been in use for over thirty years. As the primary method of resolving domain names to Internet Protocol (IP) addresses, it is a fundamental component of the Internet. Despite its position of importance, the protocol lacks built-in security mechanisms to address confidentiality, integrity, or availability. Malware can use DNS to fulfill attacker objectives, such as establishing command and control (C2) or exfiltrating data. Various enhancements have been implemented in an attempt to address security after-the-fact. The latest such enhancement is DNS over HTTPS. Methods have also been developed to detect malware's use of DNS. In this paper, we review the weaknesses of the DNS protocol and how malware has abused those weaknesses, enhancements to DNS security, and how malware uses DNS and how that use is detected, with a special emphasis on the effects that DNS over HTTPS may have on an organization's security.","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"196 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130307503","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 : 2020-03-01DOI: 10.1109/ICICT50521.2020.00089
Chandrasekar Vuppalapati, Anitha Ilapakurti, Sharat Kedari, Rajasekar Vuppalapati, J. Vuppalapati, S. Kedari
Big Data surrounds us. Every minute, our smartphone collects huge amount of data from geolocations to next clickable item on the ecommerce site. Data has become one of the most important commodities for the individuals and companies. Nevertheless, this data revolution has not touched every economic sector, especially rural economies, e.g., small farmers have largely passed over the data revolution, in the developing countries due to infrastructure and compute constrained environments. Not only this is a huge missed opportunity for the big data companies, it is one of the significant obstacle in the path towards sustainable food and a huge inhibitor closing economic disparities. The purpose of the paper is to develop a framework to deploy artificial intelligence models in constrained compute environments that enable remote rural areas and small farmers to join the data revolution and start contribution to the digital economy and empowers the world through the data to create a sustainable food for our collective future.
{"title":"Democratization of AI, Albeit Constrained IoT Devices & Tiny ML, for Creating a Sustainable Food Future","authors":"Chandrasekar Vuppalapati, Anitha Ilapakurti, Sharat Kedari, Rajasekar Vuppalapati, J. Vuppalapati, S. Kedari","doi":"10.1109/ICICT50521.2020.00089","DOIUrl":"https://doi.org/10.1109/ICICT50521.2020.00089","url":null,"abstract":"Big Data surrounds us. Every minute, our smartphone collects huge amount of data from geolocations to next clickable item on the ecommerce site. Data has become one of the most important commodities for the individuals and companies. Nevertheless, this data revolution has not touched every economic sector, especially rural economies, e.g., small farmers have largely passed over the data revolution, in the developing countries due to infrastructure and compute constrained environments. Not only this is a huge missed opportunity for the big data companies, it is one of the significant obstacle in the path towards sustainable food and a huge inhibitor closing economic disparities. The purpose of the paper is to develop a framework to deploy artificial intelligence models in constrained compute environments that enable remote rural areas and small farmers to join the data revolution and start contribution to the digital economy and empowers the world through the data to create a sustainable food for our collective future.","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128286426","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 : 2020-03-01DOI: 10.1109/ICICT50521.2020.00097
C. Yoon
In the 4th industrial revolution, enterprise business environment has sharply been altered with advancing diverse smart technologies. The application of smart business for a firm is very crucial for the efficient execution of its management activities and for improving the performance of its business tasks. The analysis and management for firm smart business ability is required to reasonably build and advance the smart business environment appropriate for its management activities and business fields. A rational analysis framework needs to efficiently analyze an enterprise smart business ability to manage and upgrade its smart business ability. This research verified the validity and reliability of the developed 16-item scale based on previous studies. This study presents a structural framework that can properly analyze an enterprise smart business capability in a smart business ability perspective. The developed framework can be utilized for reasonably analyzing an enterprise smart business capability in a smart business environment.
{"title":"Analyzing Enterprise Smart Business Capability in a Smart Technology Environment","authors":"C. Yoon","doi":"10.1109/ICICT50521.2020.00097","DOIUrl":"https://doi.org/10.1109/ICICT50521.2020.00097","url":null,"abstract":"In the 4th industrial revolution, enterprise business environment has sharply been altered with advancing diverse smart technologies. The application of smart business for a firm is very crucial for the efficient execution of its management activities and for improving the performance of its business tasks. The analysis and management for firm smart business ability is required to reasonably build and advance the smart business environment appropriate for its management activities and business fields. A rational analysis framework needs to efficiently analyze an enterprise smart business ability to manage and upgrade its smart business ability. This research verified the validity and reliability of the developed 16-item scale based on previous studies. This study presents a structural framework that can properly analyze an enterprise smart business capability in a smart business ability perspective. The developed framework can be utilized for reasonably analyzing an enterprise smart business capability in a smart business environment.","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131099672","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 : 2020-03-01DOI: 10.1109/ICICT50521.2020.00076
Kevin Matthe Caramancion
Disinformation or "fake news" has continuously proven to be a pervasive threat in the digital space. The spread and persistence of disinformation especially in the social networking media sites currently factors as one of the most challenging threat for users and content administrators alike. Its ecosystem encompasses several attributing factors including but not limited to humans as information users and source, social communication model as its channel, current trust models in place as defense and guards against it, and finally the archival correction that may halt its persistence in the social space. In this paper, the author aims to explore the dynamics of the several interacting fields i.e. Psychology and Computer Science, their influence on its phenomenon, which provides an ideal interdisciplinary and holistic approach to its reduction and management. Another equally important section in this paper is its attempt to advocate to formally recognize disinformation as a cybersecurity threat for its prospective future categorization. The possible application of discourse analysis as a potential technological tool for its detection as solution is also discussed.
{"title":"An Exploration of Disinformation as a Cybersecurity Threat","authors":"Kevin Matthe Caramancion","doi":"10.1109/ICICT50521.2020.00076","DOIUrl":"https://doi.org/10.1109/ICICT50521.2020.00076","url":null,"abstract":"Disinformation or \"fake news\" has continuously proven to be a pervasive threat in the digital space. The spread and persistence of disinformation especially in the social networking media sites currently factors as one of the most challenging threat for users and content administrators alike. Its ecosystem encompasses several attributing factors including but not limited to humans as information users and source, social communication model as its channel, current trust models in place as defense and guards against it, and finally the archival correction that may halt its persistence in the social space. In this paper, the author aims to explore the dynamics of the several interacting fields i.e. Psychology and Computer Science, their influence on its phenomenon, which provides an ideal interdisciplinary and holistic approach to its reduction and management. Another equally important section in this paper is its attempt to advocate to formally recognize disinformation as a cybersecurity threat for its prospective future categorization. The possible application of discourse analysis as a potential technological tool for its detection as solution is also discussed.","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124441724","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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