• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup1
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• pp.1-9
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• 2016

In Vietnam, the WHO Framework Convention on Tobacco Control (WHO FCTC) took effect in March 2005 while MPOWER has been implemented since 2008. This paper describes the progress and challenges of implementation of the MPOWER package in Vietnam. We can report that, in term of monitoring, Vietnam is very active in the Global Tobacco Surveillance System, completing two rounds of the Global Adult Tobacco Survey (GATS) and three rounds of the Global Youth Tobacco Survey (GYTS). To protect people from tobacco smoke, Vietnam has issued and enforced a law requiring comprehensive smoking bans at workplaces and public places since 2013. Tobacco advertising and promotion are also prohibited with the exception of points of sale displays of tobacco products. Violations come in the form of promotion girls, corporate social responsibility activities from tobacco manufacturers and packages displayed by retail vendors. Vietnam is one of the 77 countries that require pictorial health warnings to be printed on cigarette packages to warn about the danger of tobacco and the warnings have been implemented effectively. Cigarette tax is 70% of factory price which is equal to less than 45% of retail price and much lower than the recommendation of WHO. However, Vietnam is one of the very few countries that require manufacturers and importers to make "compulsory contributions" at 1-2% of the factory price of cigarettes sold in Vietnam for the establishment of a Tobacco Control Fund (TCF). The TCF is being operated well. In 2015, 67 units of 63 provinces/cities, 22 ministries and political-social organizations and 6 hospitals received funding from TCF to implement a wide range of tobacco control activities. Cessation services have been starting with a a toll-free quit-line but need to be further strengthened. In conclusion, Vietnam has constantly put efforts into the tobacco control field with high commitment from the government, scientists and activists. Though several remarkable achievements have been gained, many challenges remain. To overcome those challenges, implementation strategies that take into account the contextual factors and social determinants of tobacco use in Vietnam are needed.

• Journal of the Earthquake Engineering Society of Korea
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• v.15 no.5
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• pp.11-24
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• 2011

A real-time hybrid test of a 3 story-3 bay reinforced concrete frame which is divided into numerical and physical substructure models under uniaxial earthquake excitation was run using a fixed iteration implicit HHT time integration method. The first story inner non-ductile column was selected as the physical substructure model, and uniaxial earthquake excitation was applied to the numerical model until the specimen failed due to severe damage. A finite-element analysis program, Mercury, was newly developed and optimized for a real-time hybrid test. The drift ratio based on the top horizontal displacement of the physical substructure model was compared with the result of a numerical simulation by OpenSees and the result of a shaking table test. The experiment in this paper is one of the most complex real-time hybrid tests, and the description of the hardware, algorithm and models is presented in detail. If there is an improvement in the numerical model, the evaluation of the tangent stiffness matrix of the physical substructure model in the finite element analysis program and better software to reduce the computational time of the element state determination for the force-based beam-column element, then the comparison with the results of the real-time hybrid test and the shaking table test deserves to make a recommendation. In addition, for the goal of a "Numerical simulation of the complex structures under dynamic loading", the real time hybrid test has enough merit as an alternative to dynamic experiments of large and complex structures.

• The Journal of Society for e-Business Studies
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• v.23 no.2
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• pp.83-96
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• 2018

Extracting keywords representing documents is very important because it can be used for automated services such as document search, classification, recommendation system as well as quickly transmitting document information. However, when extracting keywords based on the frequency of words appearing in a web site documents and graph algorithms based on the co-occurrence of words, the problem of containing various words that are not related to the topic potentially in the web page structure, There is a difficulty in extracting the semantic keyword due to the limit of the performance of the Korean tokenizer. In this paper, we propose a method to select candidate keywords based on semantic similarity, and solve the problem that semantic keyword can not be extracted and the accuracy of Korean tokenizer analysis is poor. Finally, we use the technique of extracting final semantic keywords through filtering process to remove inconsistent keywords. Experimental results through real web pages of small business show that the performance of the proposed method is improved by 34.52% over the statistical similarity based keyword selection technique. Therefore, it is confirmed that the performance of extracting keywords from documents is improved by considering semantic similarity between words and removing inconsistent keywords.

• Journal of IKEEE
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• v.11 no.4
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• pp.348-357
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• 2007

Due to the improved performance and cost of personal mobile devices and rapid progress of wireless communication technology, the number of users who utilize these devices is increasing. This trend requires various types of services be available to users. So far, there have been many solutions provided for the shortest path problem. But, technologies which can offer various recommendation services to user depending on user’s current location are focused on Euclidean spaces rather than road network. Thus, in this paper, we extend the previous work to satisfy this requirement on road network database. Our proposed scheme requires pre-computation for the efficient query processing. In the preprocessing step, we first partition the input road network into a fixed number of Voronoi polygons and then pre-compute routing information for each polygon. In the meantime, we select the number of Voronoi polygons in proposition to the scale of road network. Through this selection, the required size of pre-computation is linearly increasing to the size of road network. Using this pre-computated information, we can process queries more quickly. Through experiments, we have shown that our proposed scheme can achieve excellent performance in terms of scheduling time and the number of visited nodes.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.83-91
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• 2011

Much research has been conducted on the e-learning systems for recommending a learning content to a student based on the difficulty of it. The difficulty is one of the most important factors for selecting a learning content. In the existing learning content recommendation systems, the difficulty of a learning content is determined by the creator. Therefore, it is not easy to apply a standard rule to the difficulty as it is determined by a subjective method. In this paper, we propose an ontology-based method for determining the difficulty of a learning content in order to provide an objective measurement. Previously, ontologies and knowledge maps have been used to recommend a learning content. However, their methods have the same problem because the difficulty is also determined by the creator. In this research, we use an ontology representing the IS-A relationships between words. The difficulty of a learning content is the sum of the weighted path lengths of the words in the learning content. By using this kind of difficulty, we can provide an objective measurement and recommend the proper learning content most suitable for the student's current level.

• The Journal of Society for e-Business Studies
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• v.18 no.2
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• pp.153-173
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• 2013

The ontology has been gaining increasing interests by recent arise of the semantic web and related technologies. The focus is mostly on inference query processing that requires high-level techniques for storage and searching ontologies efficiently, and it has been actively studied in the area of semantic-based searching. W3C's recommendation is to use RDFS and OWL for representing ontologies. However memory-based editors, inference engines, and triple storages all store ontology as a simple set of triplets. Naturally the performance is limited, especially when a large-scale ontology needs to be processed. A variety of researches on proposing algorithms for efficient inference query processing has been conducted, and many of them are based on using proven relational database technology. However, none of them had been successful in obtaining the complete set of inference results which reflects the five characteristics of the ontology properties. In this paper, we propose a new index structure called hyper cube index to efficiently process inference queries. Our approach is based on an intuition that an index can speed up the query processing when extensive inferencing is required.

• The Journal of Information Systems
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• v.27 no.2
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• pp.157-173
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• 2018

Purpose Product characteristics and price value in website have strongly effects on customer satisfaction. Especially, in the online shopping site, the scarcity limits the customer's opportunity to purchase the product. Thus scarcity has been proposed as a important factor that makes the customer highly aware of the merchantability of the product. The scarcity in the web store is used as an important variable to make purchasing decisions of users easier by psychological pressure. In the case of scarce products with price discounts in online commerce, advertising formats that highlight scarcity value in the web commerce market are very effective in enhancing purchase intentions of consumers. Unlike offline stores, the importance of scarcity becomes more important when reflecting the characteristics of online commerce. Therefore, this study intends to confirm the influence of the degree of price discounts and scarcity information presented by Web sites on consumer purchase behavior in Web purchase behavior. Design/methodology/approach This study conducted a web-based experimental study on price sensitivity and price discount. Therefore, we created experimental web-sites that offer two stimuli according to the discount rate. The 200 respondents were randomly assigned. The stimuli were fictitious based on tourism products. The first stimulus presented the price discount(15% discount) with basic explanation about the package of the tourist package. The stimuli assigned to the second group were used for groups with high price discount intensity(65% discount). In this way, the two stimuli clearly distinguished the level of price discount intensity. This paper conducted t-test analysis and structural equation to analyze the experiemental results after confirming the reliability and validity. Findings The results of this study are as follows. The difference in price discount intensity (15% vs 65%) with scarcity showed the mean difference among all the variables. Therefore, this study concluded that there is a significant difference between the price discount of 15% and 65% for the acquisition value and transaction value of users. In particular, consumers' purchase intention is greater and product recommendation intensity is stronger when the price discount is 65%. As a result, the high degree of the price discount intensity with scarcity exerts a greater influence on consumers' purchase intentions. Product scarcity also have a significant impact on perceived value of users. Therefore, purchase intention of customers increases when perceived value increases their profit and pleasure feeling.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.101-108
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• 2015

This paper presents the implementation of a system that recommends empirical best routes based on classification of large trajectory data. As many location-based services are used, we expect the amount of location and trajectory data to become big data. Then, we believe we can extract the best empirical routes from the large trajectory repositories. Large trajectory data is clustered into similar route groups using Hadoop MapReduce framework. Clustered route groups are stored and managed by a DBMS, and thus it supports rapid response to the end-users' request. We aim to find the best routes based on collected real data, not the ideal shortest path on maps. We have implemented 1) an Android application that collects trajectories from users, 2) Apache Hadoop MapReduce program that can cluster large trajectory data, 3) a service application to query start-destination from a web server and to display the recommended routes on mobile phones. We validated our approach using real data we collected for five days and have compared the results with commercial navigation systems. Experimental results show that the empirical best route is better than routes recommended by commercial navigation systems.

• Journal of Distribution Science
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• v.16 no.8
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• pp.79-89
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• 2018

Purpose - This research aims to investigate the factors that influence consumer's overseas online shopping behavior. Consumers adopt overseas online shopping as a new buying way and more and more consumers prefer overseas online shopping than traditional shopping ways. Consumers' behaviors in this shopping experience can be different from other shopping experiences. With the increase of overseas online shopping, we need to find antecedents and results of overseas online shopping. Especially there would be positive or negative factors which influence overseas online shopping motivation. To find the relationship, this study examines self-efficacy and impulsivity as major factors which influence overseas online shopping. We also suggest that several attitude factors increase self-efficacy and it is positively related to customer satisfaction. On the other hand, we assume that overseas online shopping factors influence impulsivity of buying and it will decrease customer satisfaction. Research design, data, and methodology - This empirical study data were collected from Korean people who experience overseas online shopping. The subjects for this study were confined to shoppers who used overseas online shopping within the past six months. A total of 267 responses were gathered. SPSS 23.0, PLS 2.0 software were used in the data analysis. Descriptive statistics were used to show sample characteristics. We examined reliability, validity test for constructs. All measurement items used seven-point scales(1= very strong disagree, 7 = very strongly agree) drawn from previously published papers. Partial Least Square method was applied to find the relationship between antecedent factors and dependent factors and hypotheses were estimated. Results - Results show that perceived superiority, perceived ease of use, perceived transaction safety, perceived behavioral control positively affect self-efficacy. Self-efficacy influences positively to consumer's post purchase satisfaction. Perceived monetary benefit and perceived uniqueness motivated impulse buying. This can make consumer's post purchase dissatisfaction. Conclusions - This paper attempted to confirm the existence of both the positive and negative faces of overseas online shopping. The result reveals that self-efficacy is a major factor which may increase satisfaction in the overseas online shopping. Usually, we can think monetary benefit and uniqueness of products motivate overseas online shopping. But it can also intrigue impulse buying and negatively affect customer relationship. Therefore companies should provide enough products information to their potential customers and they might apply adequate processes such as recommendation, comparing systems to build long term relationship with their customers.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.407-419
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• 2017

In this paper, we aim to evaluate the effect of simulation training with a focus on the application of SBAR for the improvement of communication skills of nursing students with physician. The results of the analysis of 25 videos recorded pre/post-simulation were as follows: In terms of the SBAR score, "the most recently measured vital signs" in stage B increased significantly (Z = -2.448, p =.014); the frequency of step-by-step progress in SBAR did not advance to the SBA or SBAR stage in the pre-simulation stage, but increased to 48% post-simulation. The frequencies of SBAR evaluation items mentioned in the post-simulation were the following order: the name of the patient (96%), nurse's name (80%), most recently measured oxygen saturation (76%), and main symptoms (60%). The results of the nurse's judgment (A), request for additional prescription or request for the doctor's direct patient visit (R) were not mentioned. Therefore, it is necessary to consider the application of SBAR in simulation training, which requires problem solving through cooperation with physicians, because it has a positive effect on education in nurse-physician communication.