Pub Date : 2017-07-01DOI: 10.1109/JCSSE.2017.8025952
Charles Allen, A. Harfield
QR codes are increasingly being used as a mechanism to transmit one time passwords (OTPs) between devices for the purpose of authentication due to their convenience, low cost, and the ubiquity of consumer mobile devices. Existing practice typically utilizes a single QR code which is relatively easy to capture and relay to an offsite attacker or collaborator. We propose a mechanism using a stream of rapidly changing QR codes that maintains the convenience, ubiquity, and low cost of the standard approach, while aiming to eliminate the viability of relay attacks. We test this setup using a university class attendance scenario and successfully distinguish between valid physically present users and invalid offsite attackers.
{"title":"Authenticating physical location using QR codes and network latency","authors":"Charles Allen, A. Harfield","doi":"10.1109/JCSSE.2017.8025952","DOIUrl":"https://doi.org/10.1109/JCSSE.2017.8025952","url":null,"abstract":"QR codes are increasingly being used as a mechanism to transmit one time passwords (OTPs) between devices for the purpose of authentication due to their convenience, low cost, and the ubiquity of consumer mobile devices. Existing practice typically utilizes a single QR code which is relatively easy to capture and relay to an offsite attacker or collaborator. We propose a mechanism using a stream of rapidly changing QR codes that maintains the convenience, ubiquity, and low cost of the standard approach, while aiming to eliminate the viability of relay attacks. We test this setup using a university class attendance scenario and successfully distinguish between valid physically present users and invalid offsite attackers.","PeriodicalId":6460,"journal":{"name":"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"52 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79862444","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 : 2017-07-01DOI: 10.1109/JCSSE.2017.8025946
A. Prayote, Watcharet Kuntichod
This paper presents a solution to classifying sentences with multi-labels. This problem is an essential part to a semantic search process. Sentences or keywords with correctly automated labelling can enhance the efficiency and performance of the search. The technique introduces a vector space of relevance for keywords and sentences with necessary operations. Concepts and motivation are explained with mathematical models for the two vectors and their operations. Experiments of multi-role identification of sentences are conducted with abstracts of scientific articles. Procedures of executing models in the experiment are explained step by step. In comparison, nine other techniques of multi-label classification are used on the same data set. The evaluation is done on 4-fold cross validation basis. The study reveals a successful result of multi-role identification of sentences with higher accuracy than other nine techniques.
{"title":"Multi-role identification of sentences using Relevance Vector Space","authors":"A. Prayote, Watcharet Kuntichod","doi":"10.1109/JCSSE.2017.8025946","DOIUrl":"https://doi.org/10.1109/JCSSE.2017.8025946","url":null,"abstract":"This paper presents a solution to classifying sentences with multi-labels. This problem is an essential part to a semantic search process. Sentences or keywords with correctly automated labelling can enhance the efficiency and performance of the search. The technique introduces a vector space of relevance for keywords and sentences with necessary operations. Concepts and motivation are explained with mathematical models for the two vectors and their operations. Experiments of multi-role identification of sentences are conducted with abstracts of scientific articles. Procedures of executing models in the experiment are explained step by step. In comparison, nine other techniques of multi-label classification are used on the same data set. The evaluation is done on 4-fold cross validation basis. The study reveals a successful result of multi-role identification of sentences with higher accuracy than other nine techniques.","PeriodicalId":6460,"journal":{"name":"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"49 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78850596","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 : 2017-07-01DOI: 10.1109/JCSSE.2017.8025917
Shlok Gilda
Programming languages are the primary tools of the software development industry. As of today, the programming language of the vast majority of the published source code is manually specified or programmatically assigned based solely on the respective file extension. This work shows that the identification of the programming language can be done automatically by utilizing an artificial neural network based on supervised learning and intelligent feature extraction from the source code files. We employ a multi-layer neural network - word embedding layers along with a Convolutional Neural Network - to achieve this goal. Our criteria for an automatic source code identification solution include high accuracy, fast performance, and large programming language coverage. The model achieves a 97% accuracy rate while classifying 60 programming languages.
{"title":"Source code classification using Neural Networks","authors":"Shlok Gilda","doi":"10.1109/JCSSE.2017.8025917","DOIUrl":"https://doi.org/10.1109/JCSSE.2017.8025917","url":null,"abstract":"Programming languages are the primary tools of the software development industry. As of today, the programming language of the vast majority of the published source code is manually specified or programmatically assigned based solely on the respective file extension. This work shows that the identification of the programming language can be done automatically by utilizing an artificial neural network based on supervised learning and intelligent feature extraction from the source code files. We employ a multi-layer neural network - word embedding layers along with a Convolutional Neural Network - to achieve this goal. Our criteria for an automatic source code identification solution include high accuracy, fast performance, and large programming language coverage. The model achieves a 97% accuracy rate while classifying 60 programming languages.","PeriodicalId":6460,"journal":{"name":"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"45 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89434314","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 : 2017-07-01DOI: 10.1109/JCSSE.2017.8025944
Peerasak Wangsom, K. Lavangnananda, P. Bouvry
The data locality is significant factor which has a direct impact on the performance of MapReduce framework. Several previous works have proposed alternative scheduling algorithms for improving the performance by increasing data locality. Nevertheless, their studies had focused the data locality on physical MapReduce cluster. As more and more deployment of MapReduce cluster have been on virtual environment, a more suitable evaluation of MapReduce cluster may be necessary. This study adopts a simulation based approach. Five scheduling algorithms were used for the simulation. WorkflowSim is extended by inclusion of three implemented modules to assess the new performance measure called ‘data locality ratio’. Comparison of their results reveals interesting findings. The proposed implementation can be used to assess ‘data locality ratio’ and allows users prior to efficiently select and tune scheduler and system configurations suitable for an environment prior to its actual physical MapReduce deployment.
{"title":"Measuring data locality ratio in virtual MapReduce cluster using WorkflowSim","authors":"Peerasak Wangsom, K. Lavangnananda, P. Bouvry","doi":"10.1109/JCSSE.2017.8025944","DOIUrl":"https://doi.org/10.1109/JCSSE.2017.8025944","url":null,"abstract":"The data locality is significant factor which has a direct impact on the performance of MapReduce framework. Several previous works have proposed alternative scheduling algorithms for improving the performance by increasing data locality. Nevertheless, their studies had focused the data locality on physical MapReduce cluster. As more and more deployment of MapReduce cluster have been on virtual environment, a more suitable evaluation of MapReduce cluster may be necessary. This study adopts a simulation based approach. Five scheduling algorithms were used for the simulation. WorkflowSim is extended by inclusion of three implemented modules to assess the new performance measure called ‘data locality ratio’. Comparison of their results reveals interesting findings. The proposed implementation can be used to assess ‘data locality ratio’ and allows users prior to efficiently select and tune scheduler and system configurations suitable for an environment prior to its actual physical MapReduce deployment.","PeriodicalId":6460,"journal":{"name":"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"41 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76470196","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 : 2017-07-01DOI: 10.1109/JCSSE.2017.8025951
Pavit Noinongyao, U. Watchareeruetai, Puriwat Khantiviriya, Chaiwat Wattanapaiboonsuk, S. Duangsrisai
This paper proposes an image analysis method for separating abnormal regions caused by nutrient deficiencies on plants' leaves. The proposed method analyzes a histogram of normal leaves' colors to identify abnormalities on leaves. It can be divided into three main steps. Firstly, color features of leaf region in an input image are computed. Secondly, for each pixel, its color features are compared to the corresponding bin in the histogram to determine whether the pixel is abnormal. Finally, a post-processing technique is then applied to reduce noises in the result. Experiments have been conducted using black gram (Vigna mungo) leaves with five different nutrient deficiencies. The experimental results show that the proposed method can separate abnormal regions with an accuracy of above 90%.
{"title":"Separation of abnormal regions on black gram leaves using image analysis","authors":"Pavit Noinongyao, U. Watchareeruetai, Puriwat Khantiviriya, Chaiwat Wattanapaiboonsuk, S. Duangsrisai","doi":"10.1109/JCSSE.2017.8025951","DOIUrl":"https://doi.org/10.1109/JCSSE.2017.8025951","url":null,"abstract":"This paper proposes an image analysis method for separating abnormal regions caused by nutrient deficiencies on plants' leaves. The proposed method analyzes a histogram of normal leaves' colors to identify abnormalities on leaves. It can be divided into three main steps. Firstly, color features of leaf region in an input image are computed. Secondly, for each pixel, its color features are compared to the corresponding bin in the histogram to determine whether the pixel is abnormal. Finally, a post-processing technique is then applied to reduce noises in the result. Experiments have been conducted using black gram (Vigna mungo) leaves with five different nutrient deficiencies. The experimental results show that the proposed method can separate abnormal regions with an accuracy of above 90%.","PeriodicalId":6460,"journal":{"name":"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"7 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86123735","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 : 2017-07-01DOI: 10.1109/JCSSE.2017.8025925
Kristsana Seepanomwan
This work demonstrates how generalization ability can be integrated into a neural network model of mental rotation. The model was validated with a physical humanoid robot, the iCub, as simulated participants. The results confirm that the proposed model is capable of solving a mental rotation task consisting of a number of unseen stimuli. Furthermore, characteristic of response time profiles and error rates replicates the same fashion as found in human participants. Mechanisms underlie the successes are forward model training and matching processes, both are independent of objects' identity. This work could benefit robotic applications e.g., planning, decision-making, in which the results of any actions can be seen before really performing them.
{"title":"Generalization of a mental rotation skill in humanoid robots","authors":"Kristsana Seepanomwan","doi":"10.1109/JCSSE.2017.8025925","DOIUrl":"https://doi.org/10.1109/JCSSE.2017.8025925","url":null,"abstract":"This work demonstrates how generalization ability can be integrated into a neural network model of mental rotation. The model was validated with a physical humanoid robot, the iCub, as simulated participants. The results confirm that the proposed model is capable of solving a mental rotation task consisting of a number of unseen stimuli. Furthermore, characteristic of response time profiles and error rates replicates the same fashion as found in human participants. Mechanisms underlie the successes are forward model training and matching processes, both are independent of objects' identity. This work could benefit robotic applications e.g., planning, decision-making, in which the results of any actions can be seen before really performing them.","PeriodicalId":6460,"journal":{"name":"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"602 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77626699","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 : 2017-07-01DOI: 10.1109/JCSSE.2017.8025945
Neung Viriyadamrongkij, T. Senivongse
Online inquiry communities such as Question-Answer Communities (QAC) have captured interest of online users since they can share and search for any information from any place in the world. The number of questions and answers submitted to a popular community can increase rapidly, and that can make it difficult for users who look for the “right” questions to answer. That is, from the view of knowledgeable experienced users, they tend to look for hard challenging questions as an opportunity to share their knowledge and to build respect with the community. Hence it is desirable to distinguish difficult questions from easy ones. Current researches estimate complexity of questions based on the analysis of the features of the QAC without considering the contents of the questions. This paper presents a method to measure question difficulty levels based directly on the question contents. In particular, we analyze the difficulty of terms that appear in a JavaScript-related question, based on the proposed JavaScript concept hierarchy. In an evaluation of the performance of the question difficulty estimation, our concept-based measure gives similar performance to that of the existing measure based on the features of the QAC, but when they are used together, the performance can be enhanced.
{"title":"Measuring difficulty levels of JavaScript questions in Question-Answer Community based on concept hierarchy","authors":"Neung Viriyadamrongkij, T. Senivongse","doi":"10.1109/JCSSE.2017.8025945","DOIUrl":"https://doi.org/10.1109/JCSSE.2017.8025945","url":null,"abstract":"Online inquiry communities such as Question-Answer Communities (QAC) have captured interest of online users since they can share and search for any information from any place in the world. The number of questions and answers submitted to a popular community can increase rapidly, and that can make it difficult for users who look for the “right” questions to answer. That is, from the view of knowledgeable experienced users, they tend to look for hard challenging questions as an opportunity to share their knowledge and to build respect with the community. Hence it is desirable to distinguish difficult questions from easy ones. Current researches estimate complexity of questions based on the analysis of the features of the QAC without considering the contents of the questions. This paper presents a method to measure question difficulty levels based directly on the question contents. In particular, we analyze the difficulty of terms that appear in a JavaScript-related question, based on the proposed JavaScript concept hierarchy. In an evaluation of the performance of the question difficulty estimation, our concept-based measure gives similar performance to that of the existing measure based on the features of the QAC, but when they are used together, the performance can be enhanced.","PeriodicalId":6460,"journal":{"name":"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"1 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85653389","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 : 2017-07-01DOI: 10.1109/JCSSE.2017.8025937
P. Chumcharoen, Kiattikun Kawila, K. N. Nakorn, K. Rojviboonchai
Routing Algorithm is an important mechanism which decides data transferring path in a network. Several existed routing algorithms are derived from a fundamental of graph theory with shortest path approach. A lot of additional network metrics were applied to serve the best quality of service (QoS) to end devices. However, a selected path from the existed algorithms can suffer from additional end-to-end latency for long time periods when the number of traffic flows increases. This situation is called the bufferbloat problem which is caused by excessively large queue in buffer. In this paper, we proposed a novel queuing-aware routing algorithm in software defined networks. The proposed algorithm leverages a capability of centralized system to gather directly the buffering information in real-time to calculate the shortest path with acceptable buffering occupancy level. The simulation result shows that the proposed algorithm outperforms the traditional shortest path approach in term of overall throughput significantly.
{"title":"Queuing-aware Routing Algorithm in Software Defined Networks","authors":"P. Chumcharoen, Kiattikun Kawila, K. N. Nakorn, K. Rojviboonchai","doi":"10.1109/JCSSE.2017.8025937","DOIUrl":"https://doi.org/10.1109/JCSSE.2017.8025937","url":null,"abstract":"Routing Algorithm is an important mechanism which decides data transferring path in a network. Several existed routing algorithms are derived from a fundamental of graph theory with shortest path approach. A lot of additional network metrics were applied to serve the best quality of service (QoS) to end devices. However, a selected path from the existed algorithms can suffer from additional end-to-end latency for long time periods when the number of traffic flows increases. This situation is called the bufferbloat problem which is caused by excessively large queue in buffer. In this paper, we proposed a novel queuing-aware routing algorithm in software defined networks. The proposed algorithm leverages a capability of centralized system to gather directly the buffering information in real-time to calculate the shortest path with acceptable buffering occupancy level. The simulation result shows that the proposed algorithm outperforms the traditional shortest path approach in term of overall throughput significantly.","PeriodicalId":6460,"journal":{"name":"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"25 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85671853","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 : 2017-07-01DOI: 10.1109/JCSSE.2017.8025940
Sasithorn Rattanarungrot, S. Chaisriya, Patibut Preeyawongsakul, Patiwat Ketlertprasert, Nattacha Silakun
This paper presents the process of developing Living Weir 3D animations used for supporting water appreciation and management in local communities. The living weir is an innovative water management system that allows people in the communities to contribute and take responsibility in maintaining and organizing their living weirs and water supply. In addition, the animations have been published on YouTube where they can be easily accessed and shared. The main idea of the Living Weir 3D animations is enhancing the understanding about living weirs and encouraging water management for sustainable use. The animation production starts with data collection that is accomplished by gathering information such as daily routine related to water consumption, ecosystem and the built living weirs from people who live in the community. The next step is analyzing data and storyboarding where the collected data is transformed into stories, scripts and storyboards. The final step is creating 3D aminations from the designed storyboards.
{"title":"Encouraging water management in local communities through Living Weir 3D animations","authors":"Sasithorn Rattanarungrot, S. Chaisriya, Patibut Preeyawongsakul, Patiwat Ketlertprasert, Nattacha Silakun","doi":"10.1109/JCSSE.2017.8025940","DOIUrl":"https://doi.org/10.1109/JCSSE.2017.8025940","url":null,"abstract":"This paper presents the process of developing Living Weir 3D animations used for supporting water appreciation and management in local communities. The living weir is an innovative water management system that allows people in the communities to contribute and take responsibility in maintaining and organizing their living weirs and water supply. In addition, the animations have been published on YouTube where they can be easily accessed and shared. The main idea of the Living Weir 3D animations is enhancing the understanding about living weirs and encouraging water management for sustainable use. The animation production starts with data collection that is accomplished by gathering information such as daily routine related to water consumption, ecosystem and the built living weirs from people who live in the community. The next step is analyzing data and storyboarding where the collected data is transformed into stories, scripts and storyboards. The final step is creating 3D aminations from the designed storyboards.","PeriodicalId":6460,"journal":{"name":"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"6 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89209004","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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