• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup1
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• pp.49-53
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• 2016

Evidence shows that tobacco advertising and promotion activities may increase tobacco consumption and usage, especially in youth. Despite the regulation on prohibiting advertisement of any tobacco product, tobacco advertisement and promotion activities are still common in Vietnam. This article presents current exposure to tobacco advertising and promotion (TAP) among school children aged 13 to 15 years in Vietnam in 2014 and potential influencing factors. Data from the Global Youth Tobacco Survey 2014 in Vietnam covering 3,430 school aged children were used. Both descriptive and analytical statistics were carried out with Stata 13 statistical software. Binary logistic regression was applied to explain the exposure to TAP among youth and examine relationships with individual factors. A significance level of p<0.05 and sampling weights were used in all of the computations. In the past 30 days, 48.6% of the students experienced exposure to at least 1 type of tobacco advertising or promotion. Wearing or otherwise using products related to tobacco was the most exposure TAP type reported by students (22.3%). The internet (22.1), points of sales (19.2) and social events (11.5) were three places that students aged 13-15 frequently were exposed to TAP. Binary logistic results showed that gender (female vs male) (OR = 0.61, 95%CI: 0.52 - 0.71), susceptibility to smoking (OR = 2.12, 95%CI: 1.53 - 2.92), closest friends' smoked (OR = 1.43, 95%CI: 1.2 - 1.7) and parents smoking status (OR = 2.83, 95%CI: 1.6 - 5.01) were significantly associated with TAP exposure among school-aged children. The research findings should contribute to effective implementation of measures for preventing and controlling tobacco use among students aged 13-15 in Viet Nam.

• Journal of the Korean Recycled Construction Resources Institute
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• v.5 no.1
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• pp.103-110
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• 2010

Recently, reducing usage of cement and using by-product of industry such as blast furnace slag and fly-ash have been increased to reduce $CO_2$ gas emission. That apply to construction. As a result, reduction of environmental stress and recycling of resources are expected. In this study, as basic study to the reuse of resources and reduce Environmental Load, comparing and analyzing hardening characteristics and durability as using the blast furnace slag and fly-ash, examining concrete characteristics substituted the three elements for the blast furnace slag and fly-ash and evaluating the relationship as binder. Through this, it want to provide the basic data for mass utilization. Blast furnace slag powder and replaced at fly-ash compressive strength of concrete in the strength of the initial seven days material age lower level of expression significantly compared to the concrete, but, 28 days after the similar or higher compressive strength than the concrete expression of the was. In addition, the reserves replacement of blast furnace slag powder salt injury increasing resistance are seen improvements, according to the conventional blast furnace slag powder study by the chloride ions on the surface of the concrete are improved being fixation salt injury resistance is considered.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.7
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• pp.1075-1081
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• 2013

Twitter, Facebook, and KakaoStory are the major SNS in Korea. Social knowledge production is being produced by those services from numerous collaboration and co-participation in those SNS. Wikipedia or Naver JishikIN service was regarded as the representative product of collective knowledge production during the wired internet era. However now at the wireless internet era centered with smart phones, various forms of collective knowledge production would be achieved by connecting to SNS in real-time. In this thesis, the survey data of collective knowledge production for users of three SNS have been compared and analyzed. The difference of the collective knowledge production mechanism among Twitter, Facebook and KakaoStory has been studied and compared through three variables: the motivation of collective knowledge production, the preference of collective knowledge production model, and collective knowledge production cultural perception. As a result of the analysis of the discriminant factors for three SNS user groups, it turns out that the diversity-toward usage motivation, personal contribution motivation, and collective knowledge production tendency perception are the most influential variables. This thesis is of significance in that it unites the value of social science such as social capital and collective knowledge production from the viewpoint of computer science and opens the new chapter of collective knowledge production with the real-time SNS of wireless internet from the wired internet.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.125-131
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• 2022

Recently, the prevalence of remotely managed patient care systems in medical institutions is increasing due to COVID-19. In particular, in the case of fluid monitoring, hospitals are considering introducing it as a system that can reduce patient safety and nurses' work. There are two products under development: a load cell method that measures weight and a method that detects drops of sap by infrared sensing. Although each product has differences in operation principle, sensor type, size, usage, and price, medical institutions are highly interested in the accuracy of the data obtained.In this study, two prototypes with different sensor methods were manufactured and the total amount of infusion per hour was measured to test the accuracy, which is the core of the infusion monitoring device. In addition, when there was an external movement, the change in the measured value of the sap was tested to evaluate the accuracy according to the measurement method. As a result of the experiment, there was a difference of less than 5% in the measurement value error of the two devices, and the load cell method showed a difference in the low-capacity measurement value and the infrared method in the high-capacity measurement value. As a result of this experiment, there was little difference in accuracy according to the sensor method of the infusion monitoring device, and it is considered that there is no problem in accuracy when used in a medical institution.

• Journal of Food Hygiene and Safety
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• v.38 no.5
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• pp.311-318
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• 2023

This study was performed to determine the contents of propionic, benzoic, and sorbic acids in dried seasoned seafood products (n=27) sold in Korea. Propionic acid was determined using a gas chromatogramphy-flame ionization detector. Benzoic and sorbic acid were analyzed by using a high-performance liquid chromatography-diode array detector. Benzoic acid was not detected in the dried seasoned seafood products; however, propionic and sorbic acid were detected in some samples. The concentrations of propionic acid and sorbic acid were up to 125.10 mg/kg and 658.18 mg/kg in dried seasoned seafood products, respectively. Of eight samples labeled with potassium sorbate, sorbic acid was detected in seven of them. The detected sorbic acid levels in these samples met the regulations for sorbic acid usage in Korea. The propionic, benzoic, and sorbic acid contents of dried seasoned seafood products determined in this study can provide basic data for safety management of dried seasoned seafood products in future.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.173-198
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• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.609-625
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• 2022

Validation of satellite data products is critical for subsequent analysis that is based on the data. Particularly, performance of ocean color products in turbid and shallow near-land ocean areas has been questioned for long time for its difficulty that stems from the complex optical environment with varying distribution of water constituents. Furthermore, validation with ship-based or station-based measurements has also exhibited clear limitation in its spatial scale that is not compatible with that of satellite data. This study firstly performed validation of major GOCI-II products such as remote sensing reflectance, chlorophyll-a concentration, suspended particulate matter, and colored dissolved organic matter, using the in-situ measurements collected from ship-based field campaign. Secondly, this study also presents preliminary analysis on the use of drone images for product validation. Multispectral images were acquired from a MicaSense RedEdge camera onboard a UAV to compensate for the significant scale difference between the ship-based measurements and the satellite data. Variation of water radiance in terms of camera altitude was analyzed for future application of drone images for validation. Validation conducted with a limited number of samples showed that GOCI-II remote sensing reflectance at 555 nm is overestimated more than 30%, and chlorophyll-a and colored dissolved organic matter products exhibited little correlation with in-situ measurements. Suspended particulate matter showed moderate correlation with in-situ measurements (R²~0.6), with approximately 20% uncertainty.

• Culinary science and hospitality research
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• v.21 no.3
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• pp.168-180
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• 2015

This study set out to make sponge cake a product of confectionery and bakery to expand the uses of rice bran and conducted a preliminary experiment to revise and supplement the addition of rice bran. The study sought to determine the level of added rice bran, 0~20%, by taking into account the taste, color, and marketability of rice bran in order to provide basic data for the possibilities of new product development and increase the usage of rice bran. As for the general composition, moisture, protein, fat, carbohydrate, and ash content comprised 9.50%, 15.51%, 18.12%, 48.17%, and 8.70% of the rice bran powder respectively. The pH of the dough decreased significantly with increased levels of rice bran. The specific gravity of the dough tended to rise significantly with the addition of rice bran. The group of 0% rice bran powder recorded the highest score of brightness, whereas the group of 20% rice bran powder scored lowest in terms of brightness. While there were significant differences between the control and experiment groups, no significant differences were found among the addition groups. Hardness also showed a tendency to significantly increase. The sensory evaluation results indicate that the group of 0% rice bran powder recorded the highest overall preference score at 5.00 and that the group of 20% rice bran powder had the lowest overall preference score at 2.87. The results also suggest that 10% rice bran powder sponge cake could be helpful in improving physical quality.

• Asia pacific journal of information systems
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• v.18 no.4
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• pp.105-130
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• 2008

Consumers of e-learning market differ from those of other markets in that they are replaced in a specific time scale. For example, e-learning contents aimed at highschool senior students cannot be consumed by a specific consumer over the designated period of time. Hence e-learning service providers need to attract new groups of students every year. Due to lack of information on products designed for continuously emerging consumers, the consumers face difficulties in making rational decisions in a short time period. Increased uncertainty of product purchase leads customers to herding behaviors to obtain information of the product from others and imitate them. Taking into consideration of these features of e-learning market, this study will focus on the online herding behavior in purchasing e-learning contents. There is no definite concept for e-learning. However, it is being discussed in a wide range of perspectives from educational engineering to management to e-business etc. Based upon the existing studies, we identify two main view-points regarding e-learning. The first defines e-learning as a concept that includes existing terminologies, such as CBT (Computer Based Training), WBT (Web Based Training), and IBT (Internet Based Training). In this view, e-learning utilizes IT in order to support professors and a part of or entire education systems. In the second perspective, e-learning is defined as the usage of Internet technology to deliver diverse intelligence and achievement enhancing solutions. In other words, only the educations that are done through the Internet and network can be classified as e-learning. We take the second definition of e-learning for our working definition. The main goal of this study is to investigate what factors affect consumer intention to purchase e-learning contents and to identify the differential impact of the factors between consumers with purchase experience and those without the experience. To accomplish the goal of this study, it focuses on herding behavior and perceived usefulness as antecedents to behavioral intention. The proposed research model in the study extends the Technology Acceptance Model by adding herding behavior and usability to take into account the unique characteristics of e-learning content market and e-learning systems use, respectively. The current study also includes consumer experience with e-learning content purchase because the previous experience is believed to affect purchasing intention when consumers buy experience goods or services. Previous studies on e-learning did not consider the characteristics of e-learning contents market and the differential impact of consumer experience on the relationship between the antecedents and behavioral intention, which is the target of this study. This study employs a survey method to empirically test the proposed research model. A survey questionnaire was developed and distributed to 629 informants. 528 responses were collected, which consist of potential customer group (n = 133) and experienced customer group (n = 395). The data were analyzed using PLS method, a structural equation modeling method. Overall, both herding behavior and perceived usefulness influence consumer intention to purchase e-learning contents. In detail, in the case of potential customer group, herding behavior has stronger effect on purchase intention than does perceived usefulness. However, in the case of shopping-experienced customer group, perceived usefulness has stronger effect than does herding behavior. In sum, the results of the analysis show that with regard to purchasing experience, perceived usefulness and herding behavior had differential effects upon the purchase of e-learning contents. As a follow-up analysis, the interaction effects of the number of purchase transaction and herding behavior/perceived usefulness on purchase intention were investigated. The results show that there are no interaction effects. This study contributes to the literature in a couple of ways. From a theoretical perspective, this study examined and showed evidence that the characteristics of e-learning market such as continuous renewal of consumers and thus high uncertainty and individual experiences are important factors to be considered when the purchase intention of e-learning content is studied. This study can be used as a basis for future studies on e-learning success. From a practical perspective, this study provides several important implications on what types of marketing strategies e-learning companies need to build. The bottom lines of these strategies include target group attraction, word-of-mouth management, enhancement of web site usability quality, etc. The limitations of this study are also discussed for future studies.

• The Journal of Society for e-Business Studies
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• v.25 no.4
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• pp.33-60
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• 2020

Along with the rapid advance in internet technologies, ubiquitous mobile device usage has enabled consumers to access real-time information and increased interaction with others through various social media. Consumers can now get information more easily when making purchase decisions, and these changes are affecting the brand landscape. In a digitally connected world, brand image is not communicated to the consumers one-sidedly. Rather, with consumers' growing influence, it is a result of co-creation where consumers have an active role in building brand image. This explains a reality where people no longer purchase products just because they know the brand or because it is a famous brand. However, there has been little discussion on the matter, and many practitioners still rely on the traditional measures of brand indicators. The goal of this research is to present the limitations of traditional definition and measurement of brand and brand image, and propose a more direct and adequate measure that reflects the nature of a connected world. Inspired by the proverb, "A man is known by the company he keeps," the proposed measurement offers insight to the position of brand (or brand image) through co-purchased product networks. This paper suggests a framework of network analysis that clusters brands of cosmetics by the frequency of other products purchased together. This is done by analyzing product networks of a brand extracted from actual purchase data on Amazon.com. This is a more direct approach, compared to past measures where consumers' intention or cognitive aspects are examined through survey. The practical implication is that our research attempts to close the gap between brand indicators and actual purchase behavior. From a theoretical standpoint, this paper extends the traditional conceptualization of brand image to a network perspective that reflects the nature of a digitally connected society.