• Journal of KIISE:Computing Practices and Letters
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• v.11 no.2
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• pp.180-191
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• 2005

The rapid growth of mobile communication technology has provided the expansion of mobile internet services, particularly mobile commerce takes much weight among them. Even though current mobile commerce service has serious problems which check its development, such as limited contents, expensive charge system and hardware restriction of mobile device, it is strongly expected as one of the next generation Internet services. In this paper, we summarize the problems like above and provide some total solution to meet them as follows: a function for automatic gathering of product information on online Internet and automatic translation it to data for mobile commerce, a middlelet application which provides functions for product search and order on the mobile device through off-line processing, and a function of user adaptive recommendation. We have actually designed and implemented the proposed system and verified the functions and effectiveness of the system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.710-726
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• 2018

This paper presents an extended particle filter to increase the accuracy and decrease the computation load of vehicle tracking. Particle filter has been the subject of extensive interest in video-based tracking which is capable of solving nonlinear and non-Gaussian problems. However, there still exist problems such as preventing unnecessary particle consumption, reducing the computational burden, and increasing the accuracy. We aim to increase the accuracy without an increase in computation load. In proposed method, we calculate the direction angle of the target vehicle. The angular difference between the direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted, based on their angular difference. Particles with angular difference greater than a threshold is eliminated and the remaining are stored with greater weights in order to increase their probability for state estimation. Threshold value is very critical for performance. Thus, instead of having a constant threshold value, proposed algorithm updates it online. The first advantage of our algorithm is that it prevents the system from failures caused by insufficient amount of particles. Second advantage is to reduce the risk of using unnecessary number of particles in tracking which causes computation load. Proposed algorithm is compared against camshift, direction-based particle filter and condensation algorithms. Results show that the proposed algorithm outperforms the other methods in terms of accuracy, tracking duration and particle consumption.

• Journal of Korea Multimedia Society
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• v.13 no.3
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• pp.467-474
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• 2010

The market of Internet-based fashion/coordination shopping malls have been growing rapidly year by year. In accordance with this growth, Internet fashion shopping malls are also making a lot of efforts to increase their revenue by displaying new fashion products on a high spot or by having professional models wear them to make them more attractive to the customers. If online shopping malls have the functionality of automatically calculating the matching degree of lower and upper clothes, it could play a role of off-line shop assistants and provide a more convenient way of purchasing fashion products for customers. In this paper, we present a learning system adopting the content-based filtering method for online shopping malls, which automatically calculates the matching degree of lower and upper clothes and recommends the most well-matched pair.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.443-451
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• 2021

The classification standards for hotels in Vietnam are different from many other hotel classification standards in the world. This study aims to analyze customer reviews on the TripAdvisor website to develop a new algorithm for hotel rating that is independent of Vietnam's hotel classification standards. This method can be applied to individual hotels, or hotels of a region or the whole country, while online booking sites only rate individual hotels. Data was crawled from TripAdvisor with 22,287 reviews of 5 cities in Vietnam. This study used a statistical model to analyze the review dataset and build an algorithm to rate hotels according to aspects or hotel overall. The results have less rating deviation when compared to the TripAdvisor system. This study also supports hotel managers to regularly update the status of their hotels using data from customer reviews, from which, managers can strategize long-term solutions to improve the quality of the hotel in all aspects and attract more travelers to Vietnam. Moreover, this method can be developed into an automatic system to rate hotels and update the status of service quality more quickly, thus, saving time and costs.

• Journal of Information Management
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• v.33 no.2
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• pp.19-32
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• 2002

With the growth of the digital library and the use of Internet, the amount of online text information has increased rapidly. The need for efficient data management and retrieval techniques has also become greater. An automatic text categorization system assigns text documents to predefined categories. The system allows to reduce the manual labor for text categorization. In order to classify text documents, the good features from the documents should be selected and the documents are indexed with the features. In this paper, each steps of text categorization and several techniques used in each step are introduced.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.295-298
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• 2010

There are three types of survey research system, telephone surveys, online surveys, interviews and so on. Currently most of the survey data have been verified by hand-collecting state in korea. Semi-automated research systems, some companies are using imported from abroad. This paper is the study on the design and implementation of linked research system for global standardization. The system is optimized through customizing for local conditions, as well as professionals for telephone surveys, online surveys, interviews even a normal user can enter the questionnaire easily and quickly. The result data is passed to the customer quickly and accurately. In particular, this system is based on automatic data input and collected provides best efficient analysis and statistics. Office programs and advanced statistical program SPSS is compatible with the maximum benefits for proposed system. Additionally, to achieve the import substitution effect through localization and to propose a global standard the proposed system is designed and implemented.

• Journal of Korean Society for Atmospheric Environment
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• v.25 no.6
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• pp.523-538
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• 2009

Recently, there has been a keen demand for real-time automatic monitoring of VOCs not only in Korea but other developed countries. We carried out this study to evaluate and to optimize the performance of a continuous automatic monitoring system for hazardous VOCs (HVOCs) in the ambient atmosphere, using an on-line GC system. The online system normally consisted of a Nafion dryer prior to a cold trap of an automatic thermal desorption apparatus and a GC system equipped with two detectors, i.e. PID and ECD. Preliminary tests conducted to check out any contamination of the system revealed an evidence of significant artifact formation of benzene, and it was found that the Nafion dryer (even brand new one) is the source of the benzene artifact. Thus, all the subsequent experiments in this study was carried out inevitably by removing the Nafion dryer. The on-line GC method was investigated with a variety of QC/QA performance criteria such as repeatability, linearity, lower detection limits, and accuracy. In order to find out the best operating condition for the on-line GC system, three different types (in terms of adsorption strength) of cold trap combinations were tested, i.e. (i) Tenax-TA and Carbopack-B combination (weak and hydrophobic); (ii) Tenax-TA, Carbopack-X and Carboxen-1000 combination (strong and hydrophilic); and (iii) Tenax-TA and Carbopack-X combination (medium and hydrophobic/hydrophilic). The USEPA TO-17 manual method was selected as a reference method to evaluate the performance of the on-line method. A series of experiments revealed that the system performance was superior to others when a cold trap packed with hydrophilic adsorbents (Tenax-TA/Carbopack-X/Carboxen-1000 combination) was used and operated at $25^{\circ}C$. However, the system with a cold trap packed with a combination of Tenax-TA and Carbopack-X is more recommended for field applications since the carboxen-1000 adsorbent is too sensitive to water vapor, and hence the performance of the system might be very unstable to humid samples or during rainy days. Furthermore, the precision and accuracy criteria of the Tenax-TA/ Carbopack-X combination were generally compatible with the triple adsorbents cold trap. The continuous automatic monitoring method is, thus, considered very useful to real-time monitoring to understand the variations of VOCs concentrations in ambient air, as it adopts much simpler procedures in sampling, analysis, and data integration steps than manual monitoring methods. However, it should be noted that there is a high possibility of benzene artifacts formation through the Nafion dryer, which is often installed to remove water vapor in air samples before being adsorbed onto the cold trap. Therefore, if a Nafion dryer is used in any studies of monitoring VOCs, the benzene contamination should be carefully examined before carrying out obtaining the data.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.3
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• pp.129-134
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• 2015

Since automatic social engineering based spam attacks induce for users to click or receive the short message service (SMS), e-mail, site address and make a relationship with an unknown friend, it is very easy for them to active in online social networks. The previous spam detection schemes only apply manual filtering of the system managers or labeling classifications regardless of the features of social networks. In this paper, we propose the spam detection metric after reflecting on a couple of features of social networks followed by analysis of real social network data set, Twitter spam. In addition, we provide the online social networks based unsupervised scheme for automated social engineering spam with self organizing map (SOM). Through the performance evaluation, we show the detection accuracy up to 90% and the possibility of real time training for the spam detection without the manager.

• Journal of Korea Game Society
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• v.18 no.5
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• pp.83-92
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• 2018

Many studies in deep learning show results as good as human's decision in various fields. And importance of activation of online-community and SNS grows up in game industry. Even it decides whether a game can be successful or not. The purpose of this study is to construct a system which can read texts and create comments according to schedule in online-community and SNS using deep learning. Using recurrent neural network, we constructed models generating a comment and a schedule of writing comments, and made program choosing a news title and uploading the comment at twitter in calculated time automatically. This study can be applied to activating an online game community, a Q&A service, etc.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.258-268
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• 2021

Online learning systems are becoming an effective educational medium for many universities. The accessibility of online learning system in universities means that every student, including the visually impaired, is able use all the site's services. This research focuses on investigating the accessibility of online learning systems for visually impaired users. The paper purpose is to understand the perception of visually impaired undergraduate students towards Blackboard's accessibility and to make recommendations for a new Blackboard design with accessible features that support their needs. Impact of a new Blackboard design with accessible features on visually impaired students, using Taif University students as a case study is evaluated in this paper, as it is similar to most learning systems used by Saudi universities. A study on Taif University's utilization of Blackboard was conducted using mixed method approaches (an automatic tool and a user study). In the first phase, Taif's use of Blackboard was evaluated by the web accessibility tool called AChecker. In the second phase, we conducted a user study to verify previously discovered accessibility challenges to fully assess them according to the accessibility and usability guidelines. In this study, the accessibility of Taif University's Blackboard was evaluated by thirteen visually impaired undergraduate students. The results of the study show that Blackboard has accessibility issues, which are confusing navigation, incompatibility with assistive technologies, untitled pages or parts, unclear identification for visual elements, and inaccessible PDF files. This paper also introduces a set of recommendations that aim to improve the accessibility of Blackboard and other educational websites developed for this population. It also highlights the serious need for universities to enhance web accessibility for online learning systems for students with disabilities.