Pub Date : 2019-03-01DOI: 10.1109/INFOCT.2019.8711432
Angelu Bianca C. Abrigo, M. R. Estuar
The increasing use of social media platform like Twitter provides opportunity for information dissemination to the public. The Dengvaxia controversy in the Philippines negatively affected the public’s perception towards vaccination. It has been noted that due to this incident, many parents have decided not to have their children vaccinated due to fear of endangering them [2]. This resulted to children contracting other diseases like measles due to the lack of immunization [1] [2]. The preference to not have newborns undergo vaccination program remains a threat to public health. Using publicly accessible tweets, this study aims to understand health perceptions of the public in relation to Dengvaxia. A deep neural network approach using n-gram vectorization is used in comparison to the Doc2Vec neural network classifier to identify tweets containing personal perception on health. It was discovered that not only does the bigram model perform better in classifying than the Doc2Vec model with a performance measure of 86.25% accuracy, 0.85 precision, 0.86 ROC and 0.85 F1 score, but also it is able to identify clearer and more diverse topic using LDA topic modeling in comparison with unigram and trigram model. This method allows the monitoring of public perception and acceptance towards the implementation of a new medication or vaccination especially after the Dengvaxia scandal that the Philippines experienced.
{"title":"A Comparative Analysis of N-Gram Deep Neural Network Approach to Classifying Human Perception on Dengvaxia","authors":"Angelu Bianca C. Abrigo, M. R. Estuar","doi":"10.1109/INFOCT.2019.8711432","DOIUrl":"https://doi.org/10.1109/INFOCT.2019.8711432","url":null,"abstract":"The increasing use of social media platform like Twitter provides opportunity for information dissemination to the public. The Dengvaxia controversy in the Philippines negatively affected the public’s perception towards vaccination. It has been noted that due to this incident, many parents have decided not to have their children vaccinated due to fear of endangering them [2]. This resulted to children contracting other diseases like measles due to the lack of immunization [1] [2]. The preference to not have newborns undergo vaccination program remains a threat to public health. Using publicly accessible tweets, this study aims to understand health perceptions of the public in relation to Dengvaxia. A deep neural network approach using n-gram vectorization is used in comparison to the Doc2Vec neural network classifier to identify tweets containing personal perception on health. It was discovered that not only does the bigram model perform better in classifying than the Doc2Vec model with a performance measure of 86.25% accuracy, 0.85 precision, 0.86 ROC and 0.85 F1 score, but also it is able to identify clearer and more diverse topic using LDA topic modeling in comparison with unigram and trigram model. This method allows the monitoring of public perception and acceptance towards the implementation of a new medication or vaccination especially after the Dengvaxia scandal that the Philippines experienced.","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129065602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1109/INFOCT.2019.8710881
E. Asa, Y. Yamamoto, T. Benjanarasuth
This research presents the controller design for aircraft altitude control based on Coefficient Diagram Method (CDM). The controller, which is designed by CDM, guarantees a good balance of stability, response and robustness. The simulation results of the proposed control system show that the controller is able to control the aircraft altitude as desired and has a disturbance rejection behavior and the response speed can be easily adjusted by specification of the equivalent time constant. As the result, the controller design processes are less complex than other methods and the controller is still effective.
{"title":"Aircraft Altitude Control Based on CDM","authors":"E. Asa, Y. Yamamoto, T. Benjanarasuth","doi":"10.1109/INFOCT.2019.8710881","DOIUrl":"https://doi.org/10.1109/INFOCT.2019.8710881","url":null,"abstract":"This research presents the controller design for aircraft altitude control based on Coefficient Diagram Method (CDM). The controller, which is designed by CDM, guarantees a good balance of stability, response and robustness. The simulation results of the proposed control system show that the controller is able to control the aircraft altitude as desired and has a disturbance rejection behavior and the response speed can be easily adjusted by specification of the equivalent time constant. As the result, the controller design processes are less complex than other methods and the controller is still effective.","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132259000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1109/INFOCT.2019.8711254
M. Petrovskiy, M. Chikunov
The activity of extremist organizations on the Internet is continuously growing with the increase of Web’s usage for means of communication. Therefore analysis of radical members in social networks provides important information on how to prevent them propagate ideology and recruiting new members in the future. But nowadays terrorists often use confidential chats and private threads to communicate, thus it’s quite hard to detect them using only the public messages they generate. In fact, it is usually known that some users of social networks are dangerous, another are innocent, and no information is available about the remaining users. In this paper, we propose an approach for detecting radical users of social network among unknown ones by analyzing their relationships and features as of vertices of social graph without usage of any information about text content they generate. We find that the proposed method is very promising and may be efficiently used for real-time monitoring systems and future terrorism and extremism research.
{"title":"Online Extremism Discovering through Social Network Structure Analysis","authors":"M. Petrovskiy, M. Chikunov","doi":"10.1109/INFOCT.2019.8711254","DOIUrl":"https://doi.org/10.1109/INFOCT.2019.8711254","url":null,"abstract":"The activity of extremist organizations on the Internet is continuously growing with the increase of Web’s usage for means of communication. Therefore analysis of radical members in social networks provides important information on how to prevent them propagate ideology and recruiting new members in the future. But nowadays terrorists often use confidential chats and private threads to communicate, thus it’s quite hard to detect them using only the public messages they generate. In fact, it is usually known that some users of social networks are dangerous, another are innocent, and no information is available about the remaining users. In this paper, we propose an approach for detecting radical users of social network among unknown ones by analyzing their relationships and features as of vertices of social graph without usage of any information about text content they generate. We find that the proposed method is very promising and may be efficiently used for real-time monitoring systems and future terrorism and extremism research.","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120973843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1109/INFOCT.2019.8711073
L. He, Zhifeng Ge, Zhongjie Zhu, Chongchong Jin
The article introduces a novel scheme of express sheet design and realization based on portrait storage with QR code. For a given portrait image, it is first preprocessed then compressed and embedded into a QR code. The aim of the proposed scheme is mainly to address the problems of storing high quality images within limited memory space and preserving good visual quality of reconstructed images. Experiments are conducted and the results show the proposed scheme is both feasible and effective.
{"title":"Novel Scheme for Express Sheet Design and Realization Based on Portrait Storage with QR Code","authors":"L. He, Zhifeng Ge, Zhongjie Zhu, Chongchong Jin","doi":"10.1109/INFOCT.2019.8711073","DOIUrl":"https://doi.org/10.1109/INFOCT.2019.8711073","url":null,"abstract":"The article introduces a novel scheme of express sheet design and realization based on portrait storage with QR code. For a given portrait image, it is first preprocessed then compressed and embedded into a QR code. The aim of the proposed scheme is mainly to address the problems of storing high quality images within limited memory space and preserving good visual quality of reconstructed images. Experiments are conducted and the results show the proposed scheme is both feasible and effective.","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128332818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1109/INFOCT.2019.8710963
Masanori Takagi, Ryu Hirano
We have developed a field monitoring system (http://kansatu.net) using network-connected cameras and sensors installed in apple trees to support the hands-on agriculture curriculum of an elementary school. The system enables to collects and stores a variety of images taken by network-connected cameras equipped with infrared motion sensors. Agricultural works and animals are photographed in these images. The system has been in place seven years since 2011, during which time, there have been years in which more than approximately 50,000 images were collected. However, these data have not been used effectively to learn agricultural works. On the other side, in recent years, damage to agricultural crops by wild animals has been increasing. From these backgrounds, our ultimate goal is to utilize the images captured by motion sensor-equipped network cameras to develop countermeasures to prevent wild animals from damaging agricultural crops and to educate and cultivate future farmers. In this study, we proposed a method that employs image analysis technology and the date and time of image capture to automatically classify images acquired by the motion sensor network cameras by type of agricultural work and animal. We also developed a method for automatically classifying the type of agricultural work. We evaluated the accuracy of the developed method by comparing the results of automated classification with the results of manual classification. The recall of the proposed method exceeded 90% for all three types of agricultural work tested, which was equal to or greater than the classification accuracy achieved with manual classification.
{"title":"Proposal and Evaluation of A Method for Automatically Classifying Images of Agricultural Work and Animals Acquired with Motion Sensor Cameras","authors":"Masanori Takagi, Ryu Hirano","doi":"10.1109/INFOCT.2019.8710963","DOIUrl":"https://doi.org/10.1109/INFOCT.2019.8710963","url":null,"abstract":"We have developed a field monitoring system (http://kansatu.net) using network-connected cameras and sensors installed in apple trees to support the hands-on agriculture curriculum of an elementary school. The system enables to collects and stores a variety of images taken by network-connected cameras equipped with infrared motion sensors. Agricultural works and animals are photographed in these images. The system has been in place seven years since 2011, during which time, there have been years in which more than approximately 50,000 images were collected. However, these data have not been used effectively to learn agricultural works. On the other side, in recent years, damage to agricultural crops by wild animals has been increasing. From these backgrounds, our ultimate goal is to utilize the images captured by motion sensor-equipped network cameras to develop countermeasures to prevent wild animals from damaging agricultural crops and to educate and cultivate future farmers. In this study, we proposed a method that employs image analysis technology and the date and time of image capture to automatically classify images acquired by the motion sensor network cameras by type of agricultural work and animal. We also developed a method for automatically classifying the type of agricultural work. We evaluated the accuracy of the developed method by comparing the results of automated classification with the results of manual classification. The recall of the proposed method exceeded 90% for all three types of agricultural work tested, which was equal to or greater than the classification accuracy achieved with manual classification.","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122909027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1109/infoct.2019.8711129
T. Saraç
{"title":"Certification Aspects of Model Based Development for Airborne Software","authors":"T. Saraç","doi":"10.1109/infoct.2019.8711129","DOIUrl":"https://doi.org/10.1109/infoct.2019.8711129","url":null,"abstract":"","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131901918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1109/infoct.2019.8711279
{"title":"ICICT 2019 Cover Page","authors":"","doi":"10.1109/infoct.2019.8711279","DOIUrl":"https://doi.org/10.1109/infoct.2019.8711279","url":null,"abstract":"","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130371262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1109/INFOCT.2019.8711400
Lv Pengfei, Wang Chunning
Based on the characteristics of geoscience literature, this paper designs a knowledge discovery technology framework, which consists of data preprocessing, relationship extraction and visual presentation. The main technical features are the use of dictionary-based maximum reverse matching word segmentation algorithm and the selection of the statistical language model based relationship extraction method. Finally, a distributed computing environment was built in the experiment, and the Mapping knowledge domain of the goldfield was constructed so that the feasibility of the technical framework was verified by experiments.
{"title":"Research and Application on Geoscience Literature Knowledge Discovery Technology","authors":"Lv Pengfei, Wang Chunning","doi":"10.1109/INFOCT.2019.8711400","DOIUrl":"https://doi.org/10.1109/INFOCT.2019.8711400","url":null,"abstract":"Based on the characteristics of geoscience literature, this paper designs a knowledge discovery technology framework, which consists of data preprocessing, relationship extraction and visual presentation. The main technical features are the use of dictionary-based maximum reverse matching word segmentation algorithm and the selection of the statistical language model based relationship extraction method. Finally, a distributed computing environment was built in the experiment, and the Mapping knowledge domain of the goldfield was constructed so that the feasibility of the technical framework was verified by experiments.","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"700 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133522942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1109/INFOCT.2019.8711416
Ala'a N. Alslaity, T. Tran
The primary objective of recommender systems, in a general sense, is to recommend items to users rather than to persuade users to get those items. Hence, a recommender system is not a persuasive technology by itself. In recent years, however, there has been increasing attention in the literature towards augmenting persuasiveness features into recommender systems. Several researchers have discussed the feasibility of enriching recommendations with persuasive messages. Nonetheless, there is a lack of works that discuss how to incorporate personalized and dynamic persuasive capabilities to recommender systems. To mitigate this issue, we propose the Personalized Persuasive RS (PerPer) framework. The PerPer adopts learning automata concepts to dynamically choose a suitable persuasive strategy for users in a personalized manner. PerPer is general enough to be plugged into different recommenders and to consider several persuasive strategies. PerPer aims to provide a simple and straightforward way to incorporate persuasive features to recommenders. By this, it would have the potential of increasing users’ perceived acceptance of recommendations
{"title":"Towards Persuasive Recommender Systems","authors":"Ala'a N. Alslaity, T. Tran","doi":"10.1109/INFOCT.2019.8711416","DOIUrl":"https://doi.org/10.1109/INFOCT.2019.8711416","url":null,"abstract":"The primary objective of recommender systems, in a general sense, is to recommend items to users rather than to persuade users to get those items. Hence, a recommender system is not a persuasive technology by itself. In recent years, however, there has been increasing attention in the literature towards augmenting persuasiveness features into recommender systems. Several researchers have discussed the feasibility of enriching recommendations with persuasive messages. Nonetheless, there is a lack of works that discuss how to incorporate personalized and dynamic persuasive capabilities to recommender systems. To mitigate this issue, we propose the Personalized Persuasive RS (PerPer) framework. The PerPer adopts learning automata concepts to dynamically choose a suitable persuasive strategy for users in a personalized manner. PerPer is general enough to be plugged into different recommenders and to consider several persuasive strategies. PerPer aims to provide a simple and straightforward way to incorporate persuasive features to recommenders. By this, it would have the potential of increasing users’ perceived acceptance of recommendations","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122264961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1109/INFOCT.2019.8711051
P. Jayawardhana, A. Aponso, Naomi Krishnarajah, A. Rathnayake
This paper attempts to investigate novel Text-to-Speech algorithm based on Deep voice which is an attention based, fully convolutional mechanism. The procedure of producing speech synthesis involves with learning statistical model of the human vocal production mechanism which is eligible of taking some text and vocalize that as speech. This paper would reveal the route of the attempt where there is the destination of accuracy and realism. Serenity and fluency are the most important qualities which expect from a TTS. The idea is to give an outline of discourse amalgamation in the Sinhala language, compresses and replicates about the characteristics of different blend procedures utilized. The proposed TTS synthesizing with the neural network based approach to perform phonetic-to-acoustic mapping has described by the purpose of applying for multilingual synthesizers.
{"title":"An Intelligent Approach of Text-To-Speech Synthesizers for English and Sinhala Languages","authors":"P. Jayawardhana, A. Aponso, Naomi Krishnarajah, A. Rathnayake","doi":"10.1109/INFOCT.2019.8711051","DOIUrl":"https://doi.org/10.1109/INFOCT.2019.8711051","url":null,"abstract":"This paper attempts to investigate novel Text-to-Speech algorithm based on Deep voice which is an attention based, fully convolutional mechanism. The procedure of producing speech synthesis involves with learning statistical model of the human vocal production mechanism which is eligible of taking some text and vocalize that as speech. This paper would reveal the route of the attempt where there is the destination of accuracy and realism. Serenity and fluency are the most important qualities which expect from a TTS. The idea is to give an outline of discourse amalgamation in the Sinhala language, compresses and replicates about the characteristics of different blend procedures utilized. The proposed TTS synthesizing with the neural network based approach to perform phonetic-to-acoustic mapping has described by the purpose of applying for multilingual synthesizers.","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131558067","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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