Pub Date : 2018-11-01DOI: 10.1109/GWS.2018.8686560
Hou Xiao-lan, W. Muqing
Software-defined networks(SDNs) can effectively solve the problem of scalability of current network system. The deployment of multi-controllers in the control plane is a very important task that can directly affect the network performance. In this paper, we research the controller deployment problem based on density clustering algorithm. The clustering by fast search and find of density peaks (CFSFDP) is a clustering algorithm by finding tall density peaks. In this paper, we put forward a controller deployment algorithm based on the CFSFDP algorithm in SDN to decrease propagation delay and communication consumption between switches and between switch and its controller. The delay density is calculated by introducing the k-nearest neighbors and the nearest neighbor with lower density. And the number of controllers is obtained automatically through the number of side lobes of $gamma$ density curve by the kernel density estimation(KDE). Extensive simulations are conducted on Internet2 OS3E network topology. Compared to other methods, the results certify that our proposed algorithm has better performance considering communication consumption and propagation delay.
{"title":"An Effective Clustering Algorithm for Controller Deployment in SDN","authors":"Hou Xiao-lan, W. Muqing","doi":"10.1109/GWS.2018.8686560","DOIUrl":"https://doi.org/10.1109/GWS.2018.8686560","url":null,"abstract":"Software-defined networks(SDNs) can effectively solve the problem of scalability of current network system. The deployment of multi-controllers in the control plane is a very important task that can directly affect the network performance. In this paper, we research the controller deployment problem based on density clustering algorithm. The clustering by fast search and find of density peaks (CFSFDP) is a clustering algorithm by finding tall density peaks. In this paper, we put forward a controller deployment algorithm based on the CFSFDP algorithm in SDN to decrease propagation delay and communication consumption between switches and between switch and its controller. The delay density is calculated by introducing the k-nearest neighbors and the nearest neighbor with lower density. And the number of controllers is obtained automatically through the number of side lobes of $gamma$ density curve by the kernel density estimation(KDE). Extensive simulations are conducted on Internet2 OS3E network topology. Compared to other methods, the results certify that our proposed algorithm has better performance considering communication consumption and propagation delay.","PeriodicalId":256742,"journal":{"name":"2018 Global Wireless Summit (GWS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114439569","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 : 2018-11-01DOI: 10.1109/GWS.2018.8686547
Faruk Lawal Ibrahim Dutsinma, Supansa Chaising, Wanus Srimaharaj, R. Chaisricharoen, P. Temdee
Theoretically, learning style is the most preferred way in which a student engages, processes, understand and hold information. Every child understands and learns differently, which make the child learning style in the classroom to be influential on the overall success of the learning process. Many children lost interest and zeal when they struggle hard to understand what is being taught in the classroom, which is why it is of paramount importance for this problem to be addressed, in other to make learning fair for every child. Numerous theoretical studies on identifying learning styles have been carried out lately, but the implementation in real life have been so few and vague. This study proposes an approach for identifying children learning style using their physiological response which including blood pressure and heart pulse rate. Following the VARK model, four different types of learning styles are obtained, including visual, aural, tactile (read and write) and tactile. The decision tree is used as the classifier. The experiment is conducted with 21 primary school students within the age of 12–13. The classification result shows that the proposed method provides 81%accuracy of the study physiological response correlate with the VARK model categorization of learning.
{"title":"Identifying Child Learning Style by Using Human Physiological Response and VARK Model","authors":"Faruk Lawal Ibrahim Dutsinma, Supansa Chaising, Wanus Srimaharaj, R. Chaisricharoen, P. Temdee","doi":"10.1109/GWS.2018.8686547","DOIUrl":"https://doi.org/10.1109/GWS.2018.8686547","url":null,"abstract":"Theoretically, learning style is the most preferred way in which a student engages, processes, understand and hold information. Every child understands and learns differently, which make the child learning style in the classroom to be influential on the overall success of the learning process. Many children lost interest and zeal when they struggle hard to understand what is being taught in the classroom, which is why it is of paramount importance for this problem to be addressed, in other to make learning fair for every child. Numerous theoretical studies on identifying learning styles have been carried out lately, but the implementation in real life have been so few and vague. This study proposes an approach for identifying children learning style using their physiological response which including blood pressure and heart pulse rate. Following the VARK model, four different types of learning styles are obtained, including visual, aural, tactile (read and write) and tactile. The decision tree is used as the classifier. The experiment is conducted with 21 primary school students within the age of 12–13. The classification result shows that the proposed method provides 81%accuracy of the study physiological response correlate with the VARK model categorization of learning.","PeriodicalId":256742,"journal":{"name":"2018 Global Wireless Summit (GWS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116318440","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 : 2018-11-01DOI: 10.1109/GWS.2018.8686591
P. Clausen, J. Mathiasen, J. Nielsen
This paper aims at revealing the current distribution of digitized boards at the shop floor and to explore barriers and enablers for improving the application of digitized boards to accomplish shop floor meetings. This paper suggests a close relation between Human Bond Communication (HBC) and Shop Floor Management (SFM) because HBC aims at evolving communication into advanced levels by using digital opportunities. Furthermore, it is believed that digitized SFM boards facilitates communication and affect the managerial approach wherefrom new business opportunities can be developed. Based on a survey and subsequent a workshop with practitioners this paper shows that digitized boards have not yet been adapted at the SFM level. The research indicates that the managerial approach in SFM meetings are stuck in an old industrial mindset, which obstructs the digital transformation of SFM meetings.
{"title":"Barriers and Enablers for Digitizing Shop Floor Management Boards","authors":"P. Clausen, J. Mathiasen, J. Nielsen","doi":"10.1109/GWS.2018.8686591","DOIUrl":"https://doi.org/10.1109/GWS.2018.8686591","url":null,"abstract":"This paper aims at revealing the current distribution of digitized boards at the shop floor and to explore barriers and enablers for improving the application of digitized boards to accomplish shop floor meetings. This paper suggests a close relation between Human Bond Communication (HBC) and Shop Floor Management (SFM) because HBC aims at evolving communication into advanced levels by using digital opportunities. Furthermore, it is believed that digitized SFM boards facilitates communication and affect the managerial approach wherefrom new business opportunities can be developed. Based on a survey and subsequent a workshop with practitioners this paper shows that digitized boards have not yet been adapted at the SFM level. The research indicates that the managerial approach in SFM meetings are stuck in an old industrial mindset, which obstructs the digital transformation of SFM meetings.","PeriodicalId":256742,"journal":{"name":"2018 Global Wireless Summit (GWS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127252483","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 : 2018-11-01DOI: 10.1109/GWS.2018.8686507
T. Tran, Rougsan Chaisricharoen, H. Yahoui, V. Khieovongphachanh, D. Genon-Catalot
The protection is one of the major technical challenge to increase the extension of DC power networks. Our research proposes a new concept of three-layer self-protection module for DC micro grid nodes. This module allows the node to react when a problem happens by promptly sensing the line, using sensor and receiving an emergency signal from other nodes. A prototype has been build using a common MOSFET as the switch and testing with resistor as load on low voltage DC micro grid system.
{"title":"Self-Protection Module for Power Line Communication Node in DC Micro Grid System","authors":"T. Tran, Rougsan Chaisricharoen, H. Yahoui, V. Khieovongphachanh, D. Genon-Catalot","doi":"10.1109/GWS.2018.8686507","DOIUrl":"https://doi.org/10.1109/GWS.2018.8686507","url":null,"abstract":"The protection is one of the major technical challenge to increase the extension of DC power networks. Our research proposes a new concept of three-layer self-protection module for DC micro grid nodes. This module allows the node to react when a problem happens by promptly sensing the line, using sensor and receiving an emergency signal from other nodes. A prototype has been build using a common MOSFET as the switch and testing with resistor as load on low voltage DC micro grid system.","PeriodicalId":256742,"journal":{"name":"2018 Global Wireless Summit (GWS)","volume":"53 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120839394","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 : 2018-11-01DOI: 10.1109/GWS.2018.8686580
C. Wongwatkit, Pakpoom Prommool
Interactive learning environments have widely been accepted in enhancing students' learning performance. Students can have interaction with different learning modules, materials, and activities. However, the ongoing learning data is not well utilized for further analysis. Educational data mining has played an increasing role in considering such essential data in order to improve students' ongoing learning and teachers' ongoing instructions. Therefore, this study proposes several model frameworks in analyzing the students' ongoing learning experience by integrating with data mining techniques for interactive learning systems, which can be applied on different learning platforms. Three models have been proposed for updating learning activities to match with ongoing learning performance, for identifying students' learning problems for teachers to adjust the instructions, and for presenting the students' preferred learning materials format. The results of this study can be further implemented by learning system developers to help improve their interactive learning platforms for more significant benefits for students and teachers.
{"title":"Analysing Ongoing Learning Experience with Educational Data Mining for Interactive Learning Environments","authors":"C. Wongwatkit, Pakpoom Prommool","doi":"10.1109/GWS.2018.8686580","DOIUrl":"https://doi.org/10.1109/GWS.2018.8686580","url":null,"abstract":"Interactive learning environments have widely been accepted in enhancing students' learning performance. Students can have interaction with different learning modules, materials, and activities. However, the ongoing learning data is not well utilized for further analysis. Educational data mining has played an increasing role in considering such essential data in order to improve students' ongoing learning and teachers' ongoing instructions. Therefore, this study proposes several model frameworks in analyzing the students' ongoing learning experience by integrating with data mining techniques for interactive learning systems, which can be applied on different learning platforms. Three models have been proposed for updating learning activities to match with ongoing learning performance, for identifying students' learning problems for teachers to adjust the instructions, and for presenting the students' preferred learning materials format. The results of this study can be further implemented by learning system developers to help improve their interactive learning platforms for more significant benefits for students and teachers.","PeriodicalId":256742,"journal":{"name":"2018 Global Wireless Summit (GWS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125352556","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}
In this paper, we present the implementation of Dynamic model averaging (DMA) algorithm where the posterior inclusion probability is crucial estimated to deliver the results from the model questions of what actually drive specific Stock Exchange Thailand (SET) indexes. The predictors we use in this work are the fundamental economic variables: Borrowing Rates, Policy Rate, Minimum Overdraft Rates and Lending Rates. These factors are ones of the most important monetary tools from Bank of Thailand. The empirical results demonstrate that each SET index sectors response to those economic variables differently. Some of them are not actually correlated in some specific periods of time. For the others periods of time, however, they do affect to SET indexes.
{"title":"Which Crucial Economic Variables Do Drive Specific Sector in Stock Exchange of Thailand Indexes? Evidences from Bayesian Perspective","authors":"Paponpat Taveeapiradeecharoen, Sujitra Arwatchananukul, Nattapol Aunsri","doi":"10.1109/GWS.2018.8686502","DOIUrl":"https://doi.org/10.1109/GWS.2018.8686502","url":null,"abstract":"In this paper, we present the implementation of Dynamic model averaging (DMA) algorithm where the posterior inclusion probability is crucial estimated to deliver the results from the model questions of what actually drive specific Stock Exchange Thailand (SET) indexes. The predictors we use in this work are the fundamental economic variables: Borrowing Rates, Policy Rate, Minimum Overdraft Rates and Lending Rates. These factors are ones of the most important monetary tools from Bank of Thailand. The empirical results demonstrate that each SET index sectors response to those economic variables differently. Some of them are not actually correlated in some specific periods of time. For the others periods of time, however, they do affect to SET indexes.","PeriodicalId":256742,"journal":{"name":"2018 Global Wireless Summit (GWS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123408780","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 : 2018-11-01DOI: 10.1109/GWS.2018.8686653
Arun Kumar Chattonadhvav, Debalina Ghosh, R. Pati, A. Nag, Sanchita Ghosh
The world has become very much dependent on electronic devices and internet with the advancement of new technologies. So, security is also becoming a very vital issue as we share all our details through different electronic mediums to internet. Cryptography is a well known technique of hiding secret data. Visual Cryptography (VC) is a special type of cryptography where we can securely transmit secret data over different transmission mediums. Various visual cryptography schemes have been formulated to carry out the secure transmission of images efficiently. Visual Cryptography provides techniques to share an image efficiently over various internet services. In visual cryptography an image is broken into a number of share images which are later stacked upon to generate the original image. Out of various schemes some have shown very promising results with or without a small increase in the final image dimension which is also referred as pixel expansion. The proper alignment of the distributed shares reveals the original secret image. In this paper we provide a state-of-the-art review and analysis of the several existing schemes of Visual Cryptography.
{"title":"Visual Cryptography: Review and Analysis of Existing Methods","authors":"Arun Kumar Chattonadhvav, Debalina Ghosh, R. Pati, A. Nag, Sanchita Ghosh","doi":"10.1109/GWS.2018.8686653","DOIUrl":"https://doi.org/10.1109/GWS.2018.8686653","url":null,"abstract":"The world has become very much dependent on electronic devices and internet with the advancement of new technologies. So, security is also becoming a very vital issue as we share all our details through different electronic mediums to internet. Cryptography is a well known technique of hiding secret data. Visual Cryptography (VC) is a special type of cryptography where we can securely transmit secret data over different transmission mediums. Various visual cryptography schemes have been formulated to carry out the secure transmission of images efficiently. Visual Cryptography provides techniques to share an image efficiently over various internet services. In visual cryptography an image is broken into a number of share images which are later stacked upon to generate the original image. Out of various schemes some have shown very promising results with or without a small increase in the final image dimension which is also referred as pixel expansion. The proper alignment of the distributed shares reveals the original secret image. In this paper we provide a state-of-the-art review and analysis of the several existing schemes of Visual Cryptography.","PeriodicalId":256742,"journal":{"name":"2018 Global Wireless Summit (GWS)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116814814","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：