Pub Date : 2018-07-01DOI: 10.1109/JCSSE.2018.8457377
Sirisilp Kongsilp, Hathaichanok Chawmungkrung, T. Komuro
In this paper, we apply a Fish Tank Virtual Reality technique to a commodity tablet. Our first goal is to develop a tablet-based FTVR system that does not require additional enhancement to a tablet because it would allow tablet user to use the technology quickly and easily. To address this goal, we adopt a FTVR technique based on previous works and use it to develop our tablet FTVR prototype. It uses a camera-based face tracking and the anaglyph 3D display techniques. Our second goal is to determine that whether it is feasible to use tablet-based FTVR for entertainment and other mobile applications in daily life. To address the second goal, we implemented a game for our prototype called “pop-out Tetris Then we assess our prototype and the game using heuristic evaluation technique. We describe the technique that we used to develop our tablet FTVR prototype. The technique is based on previous works; it uses a camera-based face tracking and the anaglyph 3D display techniques. Therefore, it does not require any additional enhancement to a tablet. In addition to the prototype, we also implemented a game for tablet FTVR called “pop-out Tetris we describe our design of the application. Then we assess our prototype and the game using heuristic evaluation technique. In the end, we concluded that the technique is not ready for day-to-day use case scenario. We underline key points that affect the adoption of tablet-based FTVR technology and provide recommendations for future research to consider when developing a mobile FTVR system.
{"title":"Pop-Out Tetris: An Implementation of a Tablet FTVR Game","authors":"Sirisilp Kongsilp, Hathaichanok Chawmungkrung, T. Komuro","doi":"10.1109/JCSSE.2018.8457377","DOIUrl":"https://doi.org/10.1109/JCSSE.2018.8457377","url":null,"abstract":"In this paper, we apply a Fish Tank Virtual Reality technique to a commodity tablet. Our first goal is to develop a tablet-based FTVR system that does not require additional enhancement to a tablet because it would allow tablet user to use the technology quickly and easily. To address this goal, we adopt a FTVR technique based on previous works and use it to develop our tablet FTVR prototype. It uses a camera-based face tracking and the anaglyph 3D display techniques. Our second goal is to determine that whether it is feasible to use tablet-based FTVR for entertainment and other mobile applications in daily life. To address the second goal, we implemented a game for our prototype called “pop-out Tetris Then we assess our prototype and the game using heuristic evaluation technique. We describe the technique that we used to develop our tablet FTVR prototype. The technique is based on previous works; it uses a camera-based face tracking and the anaglyph 3D display techniques. Therefore, it does not require any additional enhancement to a tablet. In addition to the prototype, we also implemented a game for tablet FTVR called “pop-out Tetris we describe our design of the application. Then we assess our prototype and the game using heuristic evaluation technique. In the end, we concluded that the technique is not ready for day-to-day use case scenario. We underline key points that affect the adoption of tablet-based FTVR technology and provide recommendations for future research to consider when developing a mobile FTVR system.","PeriodicalId":338973,"journal":{"name":"2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128471235","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 : 2018-07-01DOI: 10.1109/JCSSE.2018.8457368
Amarin Jettakul, Chavisa Thamjarat, Kawin Liaowongphuthorn, Can Udomcharoenchaikit, P. Vateekul, P. Boonkwan
In Natural Language Processing (NLP), there are three fundamental tasks of NLP which are Tokenization being a part of a lexical level, Part-of-Speech tagging (POS) and Named-Entity-Recognition (NER) being parts of a syntactic level. Recently, there have been many deep learning researches showing their success in many domains. However, there has been no comparative study for Thai NLP to suggest the most suitable technique for each task yet. In this paper, we aim to provide a performance comparison among various deep learning-based techniques on three NLP tasks, and study the effect on synthesized OOV words and the OOV handling algorithm with Levenshtein distance had been provided due to the fact that most existing works relied on a set of vocabularies in the trained model and not being fit for noisy text in the real use case. Our three experiments were conducted on BEST 2010 I2R, a standard Thai NLP corpus on F1 measurement, with the different percentage of noises having been synthesized. Firstly, for Tokenization, the result shows that Synthai, a jointed bidirectional LSTM, has the best performance. Additionally, for POS, bi-directional LSTM with CRF has obtained the best performance. For NER, variational bi-directional LSTM with CRF has outperformed other methods. Finally, the effect of noises reduces the performance of all algorithms on these foundation tasks and the result shows that our OOV handling technique could improve the performance on noisy data.
{"title":"A Comparative Study on Various Deep Learning Techniques for Thai NLP Lexical and Syntactic Tasks on Noisy Data","authors":"Amarin Jettakul, Chavisa Thamjarat, Kawin Liaowongphuthorn, Can Udomcharoenchaikit, P. Vateekul, P. Boonkwan","doi":"10.1109/JCSSE.2018.8457368","DOIUrl":"https://doi.org/10.1109/JCSSE.2018.8457368","url":null,"abstract":"In Natural Language Processing (NLP), there are three fundamental tasks of NLP which are Tokenization being a part of a lexical level, Part-of-Speech tagging (POS) and Named-Entity-Recognition (NER) being parts of a syntactic level. Recently, there have been many deep learning researches showing their success in many domains. However, there has been no comparative study for Thai NLP to suggest the most suitable technique for each task yet. In this paper, we aim to provide a performance comparison among various deep learning-based techniques on three NLP tasks, and study the effect on synthesized OOV words and the OOV handling algorithm with Levenshtein distance had been provided due to the fact that most existing works relied on a set of vocabularies in the trained model and not being fit for noisy text in the real use case. Our three experiments were conducted on BEST 2010 I2R, a standard Thai NLP corpus on F1 measurement, with the different percentage of noises having been synthesized. Firstly, for Tokenization, the result shows that Synthai, a jointed bidirectional LSTM, has the best performance. Additionally, for POS, bi-directional LSTM with CRF has obtained the best performance. For NER, variational bi-directional LSTM with CRF has outperformed other methods. Finally, the effect of noises reduces the performance of all algorithms on these foundation tasks and the result shows that our OOV handling technique could improve the performance on noisy data.","PeriodicalId":338973,"journal":{"name":"2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115278721","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 : 2018-07-01DOI: 10.1109/JCSSE.2018.8457386
Kamonluk Suksen, P. Chongstitvatana
In Evolutionary Computation, good substructures that are combined into good solutions are called building blocks. In this context, building blocks are common structure of high- quality solutions. The compact genetic algorithm is an extension of the genetic algorithm that replaces the latter’s population of chromosomes with a probability distribution from which candidate solutions can be generated. This paper describes an algorithm that exploits building blocks with compact genetic algorithm in order to solve difficult optimization problems under the assumption that we have already known building blocks. The main idea is to update the probability vectors as a group of bits that represents building blocks thus avoiding the disruption of the building blocks. Comparisons of the new algorithm with a conventional compact genetic algorithm on trap-function and traveling salesman problems indicate the utility of the proposed algorithm. It is most effective when the problem instants have common structures that can be identify as building blocks.
{"title":"Exploiting Building Blocks in Hard Problems with Modified Compact Genetic Algorithm","authors":"Kamonluk Suksen, P. Chongstitvatana","doi":"10.1109/JCSSE.2018.8457386","DOIUrl":"https://doi.org/10.1109/JCSSE.2018.8457386","url":null,"abstract":"In Evolutionary Computation, good substructures that are combined into good solutions are called building blocks. In this context, building blocks are common structure of high- quality solutions. The compact genetic algorithm is an extension of the genetic algorithm that replaces the latter’s population of chromosomes with a probability distribution from which candidate solutions can be generated. This paper describes an algorithm that exploits building blocks with compact genetic algorithm in order to solve difficult optimization problems under the assumption that we have already known building blocks. The main idea is to update the probability vectors as a group of bits that represents building blocks thus avoiding the disruption of the building blocks. Comparisons of the new algorithm with a conventional compact genetic algorithm on trap-function and traveling salesman problems indicate the utility of the proposed algorithm. It is most effective when the problem instants have common structures that can be identify as building blocks.","PeriodicalId":338973,"journal":{"name":"2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126921376","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 : 2018-07-01DOI: 10.1109/JCSSE.2018.8457394
Surasak Tangsakul, S. Wongthanavasu
Hazy images are the images acquired under bad weather with low contrast and faint color properties. Several algorithms used dichromatic model to remove the haze in the image. This paper proposed a novel technique using cellular automata for the single image haze removal. It aims to improve the dark channel and the transmission map. We proposed the cellular automata rule to refine the intensity of image pixel in a dark channel. Then, the light source is estimated from the dark channel. Finally, we proposed the cellular automata rule to construct the transmission map and restored the haze-free image. The experimental results show that the proposed method improved intensity, color saturation quality, and avoid halo artifact without any post-processing when compared with the state-of-the-art methods.
{"title":"Improving Single Image Haze Removal Based On Cellular Automata Model","authors":"Surasak Tangsakul, S. Wongthanavasu","doi":"10.1109/JCSSE.2018.8457394","DOIUrl":"https://doi.org/10.1109/JCSSE.2018.8457394","url":null,"abstract":"Hazy images are the images acquired under bad weather with low contrast and faint color properties. Several algorithms used dichromatic model to remove the haze in the image. This paper proposed a novel technique using cellular automata for the single image haze removal. It aims to improve the dark channel and the transmission map. We proposed the cellular automata rule to refine the intensity of image pixel in a dark channel. Then, the light source is estimated from the dark channel. Finally, we proposed the cellular automata rule to construct the transmission map and restored the haze-free image. The experimental results show that the proposed method improved intensity, color saturation quality, and avoid halo artifact without any post-processing when compared with the state-of-the-art methods.","PeriodicalId":338973,"journal":{"name":"2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127502369","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 : 2018-07-01DOI: 10.1109/JCSSE.2018.8457397
Panida Wiriyachaiporn, Kankawee Chanasit, A. Suchato, P. Punyabukkana, E. Chuangsuwanich
This paper presents the application of Machine Learning (ML) algorithm as an algorithmic music composer, compared to a rule-based algorithm. The ML model is based on LSTMs which takes in previous notes and predicts the next set of notes based on a midi format. For the rule-based method, we apply chord progression rules and binary rhythm pattern theory. We used both algorithms to generate music in two different genres, namely rock, and jazz. To evaluate the effectiveness of the algorithms, fifteen raters are asked to identify the genre of the generated songs. The results showed 77.33% of the rulebased algorithms Jazz songs were correctly identified, compared to the 62.67% generated by the LSTM. For the rock genre, only 49.33% percent of rule-based algorithms songs and 44% Machine Learning algorithms songs were correctly identified. In terms of music satisfaction, the rule-based algorithm on average obtains higher scores in both genres, 2.17 for Jazz and 2.42 for Rock while Machine Learning algorithm receives 1.83 for Jazz songs and 1.57 for Rock.
{"title":"Algorithmic Music Composition Comparison","authors":"Panida Wiriyachaiporn, Kankawee Chanasit, A. Suchato, P. Punyabukkana, E. Chuangsuwanich","doi":"10.1109/JCSSE.2018.8457397","DOIUrl":"https://doi.org/10.1109/JCSSE.2018.8457397","url":null,"abstract":"This paper presents the application of Machine Learning (ML) algorithm as an algorithmic music composer, compared to a rule-based algorithm. The ML model is based on LSTMs which takes in previous notes and predicts the next set of notes based on a midi format. For the rule-based method, we apply chord progression rules and binary rhythm pattern theory. We used both algorithms to generate music in two different genres, namely rock, and jazz. To evaluate the effectiveness of the algorithms, fifteen raters are asked to identify the genre of the generated songs. The results showed 77.33% of the rulebased algorithms Jazz songs were correctly identified, compared to the 62.67% generated by the LSTM. For the rock genre, only 49.33% percent of rule-based algorithms songs and 44% Machine Learning algorithms songs were correctly identified. In terms of music satisfaction, the rule-based algorithm on average obtains higher scores in both genres, 2.17 for Jazz and 2.42 for Rock while Machine Learning algorithm receives 1.83 for Jazz songs and 1.57 for Rock.","PeriodicalId":338973,"journal":{"name":"2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121388030","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 : 2018-07-01DOI: 10.1109/JCSSE.2018.8457339
Amirhossein Moravejosharieh, Michael J. Watts, Yu Song
Software-Defined Networking (SDN) is a new networking paradigm designed to resolve traditional IP network shortcomings by breaking the vertical integration of control and data planes. SDN separates the network control logic from underlying routers and switches and introduces the ability to program the network. Bandwidth reservation is an approach offered in SDN-enabled networks to guarantee relatively high Quality of Service for different types of media, e.g., video, audio or data. Although, this approach has been proven to be worthy of considering in SDN, there are still some concerns regarding its applicability in a relatively large networks. In this paper, we have evaluated the performance of bandwidth reservation approach in a relatively large-scaled SDN-enabled network in terms of its suitability when the number of users demanding for reserved bandwidth becomes larger. The obtained results from our simulation study show that bandwidth reservation can be beneficial only when the number of users asking for guaranteed bandwidth is relatively smaller than other users. Moreover, higher end-to-end QoS delivery can be achieved as an immediate outcome of deploying bandwidth reservation approach for a particular type of traffic flow, however, at the cost of incurring negative impact on other types of traffic flow in terms of achievable network throughput.
{"title":"Bandwidth Reservation Approach to Improve Quality of Service in Software-Defined Networking: A Performance Analysis","authors":"Amirhossein Moravejosharieh, Michael J. Watts, Yu Song","doi":"10.1109/JCSSE.2018.8457339","DOIUrl":"https://doi.org/10.1109/JCSSE.2018.8457339","url":null,"abstract":"Software-Defined Networking (SDN) is a new networking paradigm designed to resolve traditional IP network shortcomings by breaking the vertical integration of control and data planes. SDN separates the network control logic from underlying routers and switches and introduces the ability to program the network. Bandwidth reservation is an approach offered in SDN-enabled networks to guarantee relatively high Quality of Service for different types of media, e.g., video, audio or data. Although, this approach has been proven to be worthy of considering in SDN, there are still some concerns regarding its applicability in a relatively large networks. In this paper, we have evaluated the performance of bandwidth reservation approach in a relatively large-scaled SDN-enabled network in terms of its suitability when the number of users demanding for reserved bandwidth becomes larger. The obtained results from our simulation study show that bandwidth reservation can be beneficial only when the number of users asking for guaranteed bandwidth is relatively smaller than other users. Moreover, higher end-to-end QoS delivery can be achieved as an immediate outcome of deploying bandwidth reservation approach for a particular type of traffic flow, however, at the cost of incurring negative impact on other types of traffic flow in terms of achievable network throughput.","PeriodicalId":338973,"journal":{"name":"2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"367 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121730262","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 : 2018-07-01DOI: 10.1109/JCSSE.2018.8457329
Piyapat Charoensawan, P. Sukanya, I. Shimizu
This paper aims to find an effective method for identifying colors of fabrics. We consider the following color naming models: Basic Color terms, ISCC-NBS Color system, Frery’s Color name, and Fractals Lab’s Ultimate color vocabulary. The appropriate color name is assigned for a fabric image by using seven types of minimum distance in RGB and HSV color models. Experiments are performed on S3 plain color fabric images. Results show that in general, the method of identifying fabric color name by using Frery’s color name model with the color similarity measure by Euclidean distance in RGB space gives the better result than the other methods. When we analyze in more details by classifying fabric images into three groups based on color saturation, we found that the effective methods for color naming are as follows: Frery’s color name model with the quadratic distance in HSV space works well for the group of low color saturation (96.23% accuracy). Frery’s color name model with Euclidean distance in RGB space works well for the group of medium color saturation (81.82% accuracy). And Fractals Lab’s Ultimate color vocabulary model with the weighted Euclidean distance in HSV space work good for the group of high color saturation (76.09% accuracy).
{"title":"Comparison of Fabric Color Naming Using RGB and HSV Color Models","authors":"Piyapat Charoensawan, P. Sukanya, I. Shimizu","doi":"10.1109/JCSSE.2018.8457329","DOIUrl":"https://doi.org/10.1109/JCSSE.2018.8457329","url":null,"abstract":"This paper aims to find an effective method for identifying colors of fabrics. We consider the following color naming models: Basic Color terms, ISCC-NBS Color system, Frery’s Color name, and Fractals Lab’s Ultimate color vocabulary. The appropriate color name is assigned for a fabric image by using seven types of minimum distance in RGB and HSV color models. Experiments are performed on S3 plain color fabric images. Results show that in general, the method of identifying fabric color name by using Frery’s color name model with the color similarity measure by Euclidean distance in RGB space gives the better result than the other methods. When we analyze in more details by classifying fabric images into three groups based on color saturation, we found that the effective methods for color naming are as follows: Frery’s color name model with the quadratic distance in HSV space works well for the group of low color saturation (96.23% accuracy). Frery’s color name model with Euclidean distance in RGB space works well for the group of medium color saturation (81.82% accuracy). And Fractals Lab’s Ultimate color vocabulary model with the weighted Euclidean distance in HSV space work good for the group of high color saturation (76.09% accuracy).","PeriodicalId":338973,"journal":{"name":"2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130014064","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 : 2018-07-01DOI: 10.1109/JCSSE.2018.8457181
Yusuke Katoh, Hironari Yoshiuchi, Yoshio Murata, H. Nakajo
We propose the Scalable Hardware Mechanism, which enables the operation of a partitioned circuit to prevent the degradation of clock frequency by minimizing its dependence on the usage and the type of FPGA. Our mechanism provides a reduced delay by the collective signal transmission with the partitioned AES code generation circuit and the character string edit distance calculation circuit as partitioned circuits. The collective signal transmission has attained 1.27 times improvement in the speed for the AES code generation circuit and 3.16 times improvement for the character string edit distance calculation circuit compared with the circuit by the conventional method.
{"title":"Operation in Partitioned Circuits with Scalable Hardware Mechanism","authors":"Yusuke Katoh, Hironari Yoshiuchi, Yoshio Murata, H. Nakajo","doi":"10.1109/JCSSE.2018.8457181","DOIUrl":"https://doi.org/10.1109/JCSSE.2018.8457181","url":null,"abstract":"We propose the Scalable Hardware Mechanism, which enables the operation of a partitioned circuit to prevent the degradation of clock frequency by minimizing its dependence on the usage and the type of FPGA. Our mechanism provides a reduced delay by the collective signal transmission with the partitioned AES code generation circuit and the character string edit distance calculation circuit as partitioned circuits. The collective signal transmission has attained 1.27 times improvement in the speed for the AES code generation circuit and 3.16 times improvement for the character string edit distance calculation circuit compared with the circuit by the conventional method.","PeriodicalId":338973,"journal":{"name":"2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131499426","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 : 2018-07-01DOI: 10.1109/JCSSE.2018.8457341
Narongsak Sukma, R. Chokngamwong
Nowadays, verifying the owner of every phone number is still possible only by showing the phone number on the screen. The telephone networks today do not have a proper validation process. This is a critical vulnerability for attackers to use this vulnerability to fake a phone number to deceive themselves as someone, i.e., a government agency and trick people into believing and eventually transferring money. Based on this problem, the research team has researched and found that many kinds of research have tried to solve the problem using a short message. (SMS), time spent on user response, hardware usage, and digital signature verification. However, the research team presented a new conceptual model as a onetime password authentication model for authentication. This new approach can reduce the need for external hardware, learning time and response time without the use of an external CA or a certification authority. This paper base on our previous paper [1] has a point that needed for improvement in the first time verification process. We propose a model that adds the ability to the first verification called advisory system which uses statistics to assist responsiveness to unknown calls. The testing result has shown the presence of fraud detection at the first call. The performance of the system is satisfied because the mobile phone that has this monitoring system installed still usually operates. Temperature, resources usage, and power consumption are not affected.
{"title":"Increasing the efficiency of One-time key Issuing for The First Verification Caller ID Spoofing Attacks","authors":"Narongsak Sukma, R. Chokngamwong","doi":"10.1109/JCSSE.2018.8457341","DOIUrl":"https://doi.org/10.1109/JCSSE.2018.8457341","url":null,"abstract":"Nowadays, verifying the owner of every phone number is still possible only by showing the phone number on the screen. The telephone networks today do not have a proper validation process. This is a critical vulnerability for attackers to use this vulnerability to fake a phone number to deceive themselves as someone, i.e., a government agency and trick people into believing and eventually transferring money. Based on this problem, the research team has researched and found that many kinds of research have tried to solve the problem using a short message. (SMS), time spent on user response, hardware usage, and digital signature verification. However, the research team presented a new conceptual model as a onetime password authentication model for authentication. This new approach can reduce the need for external hardware, learning time and response time without the use of an external CA or a certification authority. This paper base on our previous paper [1] has a point that needed for improvement in the first time verification process. We propose a model that adds the ability to the first verification called advisory system which uses statistics to assist responsiveness to unknown calls. The testing result has shown the presence of fraud detection at the first call. The performance of the system is satisfied because the mobile phone that has this monitoring system installed still usually operates. Temperature, resources usage, and power consumption are not affected.","PeriodicalId":338973,"journal":{"name":"2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131637267","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 : 2018-07-01DOI: 10.1109/JCSSE.2018.8457349
Ekapop Verasakulvong, P. Vateekul, Apivadee Piyatumrong, Chatchawal Sangkeettrakarn
Social media is one of the most impactful and fastest communication methods. By monitoring Twitter streams, we are able to detect emerging topics and understand events around the world. There are some prior attempts that aim to online detect topics on Twitter. However, they can only detect bursty topics by using user-defined keywords a long with simple rules. In this paper, we propose an algorithm to detect emerging topics on Twitter streams. To detect emerging topics, a clustering technique has been applied to aggregate a set of keywords. Since an emerging topic occurs continuously, the emerging topics are merged with stateful technique to accumulate topics from different time intervals. To detect both high signal topics and small-medium signal topics, we use statistical features based on average, acceleration, and z-score. Moreover, we propose to include the stock indicator features: Relative Strength Index (RSI) and Stochastic Oscillator (STOCH). They are common features in trend (oversold and overbought) detection in stock analysis which is similar to our topic detection in twitter. To capture any event patterns, Random Forest (RF) has been proposed as a classifier to detect emerging keywords by utilizing the stated above five features. To evaluate the performance, we created and published a corpus by collecting Twitter data for 10 days with over 80 million tweets and then labeling possible topics in tota1161 events along with related keywords. The experiment was conducted on our collected data. The Fl-results show that our model outperforms all baselines: TwitterMonitor, SigniTrend, and TopicSketch, in terms of detected keywords and topics.
{"title":"Online Emerging Topic Detection on Twitter Using Random Forest with Stock Indicator Features","authors":"Ekapop Verasakulvong, P. Vateekul, Apivadee Piyatumrong, Chatchawal Sangkeettrakarn","doi":"10.1109/JCSSE.2018.8457349","DOIUrl":"https://doi.org/10.1109/JCSSE.2018.8457349","url":null,"abstract":"Social media is one of the most impactful and fastest communication methods. By monitoring Twitter streams, we are able to detect emerging topics and understand events around the world. There are some prior attempts that aim to online detect topics on Twitter. However, they can only detect bursty topics by using user-defined keywords a long with simple rules. In this paper, we propose an algorithm to detect emerging topics on Twitter streams. To detect emerging topics, a clustering technique has been applied to aggregate a set of keywords. Since an emerging topic occurs continuously, the emerging topics are merged with stateful technique to accumulate topics from different time intervals. To detect both high signal topics and small-medium signal topics, we use statistical features based on average, acceleration, and z-score. Moreover, we propose to include the stock indicator features: Relative Strength Index (RSI) and Stochastic Oscillator (STOCH). They are common features in trend (oversold and overbought) detection in stock analysis which is similar to our topic detection in twitter. To capture any event patterns, Random Forest (RF) has been proposed as a classifier to detect emerging keywords by utilizing the stated above five features. To evaluate the performance, we created and published a corpus by collecting Twitter data for 10 days with over 80 million tweets and then labeling possible topics in tota1161 events along with related keywords. The experiment was conducted on our collected data. The Fl-results show that our model outperforms all baselines: TwitterMonitor, SigniTrend, and TopicSketch, in terms of detected keywords and topics.","PeriodicalId":338973,"journal":{"name":"2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129100449","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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