• Journal of Broadcast Engineering
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• v.19 no.5
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• pp.578-589
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• 2014

Window image is displayed through a monitor screen when we execute the application programs on the computer. This includes webpage, video player and a number of applications. The webpage delivers a variety of information by various types in comparison with other application. Unlike a natural image captured from a camera, the window image like a webpage includes diverse components such as text, logo, icon, subimage and so on. Each component delivers various types of information to users. However, the components with different characteristic need to be divided locally, because text and image are served by various type. In this paper, we divide window images into many sub blocks, and classify each divided region into background, text and subimage. The detected subimages can be applied into 2D-to-3D conversion, image retrieval, image browsing and so forth. There are many subimage classification methods. In this paper, we utilize AdaBoost for verifying that the machine learning-based algorithm can be efficient for subimage detection. In the experiment, we showed that the subimage detection ratio is 93.4 % and false alarm is 13 %.

• Journal of the Korea Society for Simulation
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• v.26 no.4
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• pp.35-41
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• 2017

With the advances in Internet over Things, the demand in diverse electronic devices such as mobile phones and sensors has been rapidly increasing and boosting up the researches on those products. Semiconductor materials, devices, and fabrication processes are becoming more diverse and complicated, which accompanies finding parameters for an optimal fabrication process. In order to find the parameters, a process simulation before fabrication or a real-time process control system during fabrication can be used, but they lack incorporating the feedback from post-fabrication data and compatibility with older equipment. In this research, we have developed an artificial intelligence based simulator, which finds parameters for an optimal process and controls process equipment. In order to apply the control concept to all the equipment in a fabrication sequence, we have developed a prototype for a manipulator which can be installed over an existing buttons and knobs in the equipment and controls the equipment communicating with the AI over the Internet. The AI is based on the deep learning to find process parameters that will produce a device having target electrical characteristics. The proposed simulator can control existing equipment via the Internet to fabricate devices with desired performance and, therefore, it will help engineers to develop new devices efficiently and effectively.

• Journal of The Korean Association of Information Education
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• v.19 no.1
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• pp.45-56
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• 2015

This article examines the effects of a long term robot based instruction on the creativity of elementary students. To explain these effects, we conducted similar creativity test twice to 237 students of schools which had been designated as a robot based instruction model from 2011 to 2012. From these test results, the following three conclusions may be drawn: (1) The creativity of students who had participated in long term robot based instruction increased significantly, especially after the first test. (2) The fluency and originality as two of the sub-creativity factors are also accelerated significantly, especially after the first test. (3) The creativity of male and female students are all improved significantly but the test period factor and the interaction factor between male and female are not significant. (4) All elementary students of the lower grades(1st and 2nd grades), middle grades(3rd and 4th grades) and higher grades(5th and 6th grades) increased significantly but the test period factor and the interaction factor between the grades were not significant. On the other hand, the creativity improvement between lower-middle grades and higher grades is significant.

• Journal of The Korean Association For Science Education
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• v.21 no.3
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• pp.473-486
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• 2001

The study aimed to evaluate an activity-oriented extracurricular science program as informal science education through the assessment of opinions of student participants and lead-students and lead-teachers who organized the program. An 'Exciting Science Fair' was designed by science teachers and students and provided for 857 students for two days in early 1998. Students chose a course of science activities designed by different levels of student knowledge and interests. During their own science activity courses, the participating students were grouped as pair of two students and guided and facilitated by lead-students. A survey instrument was developed by researchers and asked respondents' opinions of 121 participating students, 72 lead-students, and 19 lead-teachers to the significance of program goals, degree of goal achievement, and program planning and management system before and after the program. It was found that most student participants, lead-students and lead-teachers satisfied with the efficiency of the program. However, it was recommended that the program should place more emphases on engaging student participants in science activities, strengthening scientific inquiry through activities, and increasing science content related to student daily life. It was also suggested that advertizement of the program be publicized in advance through media, an effect teaching-learning strategy for lead-students be developed, and collaboration among lead-students and lead-teachers be improved.

• Culinary science and hospitality research
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• v.19 no.1
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• pp.230-243
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• 2013

The purpose of this study is to offer the basic materials for the development of nutrition education programs for youth and help domestic science teachers in schools implement effective dietary education by examining youth's purchase behavior of processed foods. As a result of figuring out youth's purchasing behavior of processed food and the difference in accordance with social, demographic variables, they considered taste and price mainly when choosing foods. The results showed that what they consider important when checking food display information was shelf life and price. It was observed that 56% of them check additives display information in food when purchasing processed food. In terms of demographic factors, the more likely they are a girl student, the lower grader they are, and the lower price they purchase processed food at, the better they used the nutritional knowledge learned in school. Based upon these results, it is necessary to offer the consumer's level of education and training for their demands by accurately figuring out youth's purchasing behavior of processed foods. For this, home economics education must allow youth to lead healthy diet by implementing a systematic and professional training on food additives on a basis of the research and utilization of a variety of educational media and teaching and learning methods.

• Korean Journal of Community Nutrition
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• v.15 no.1
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• pp.50-60
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• 2010

The purpose of this study was to conduct nutrition education using animations for the establishment of proper eating habits among elementary school students and to evaluate its effectiveness. The subjects of this study were two classes of fourth grade students in an elementary school located in Daegu-city. There were 29 students in each class. One class, the "nutrition-education" group, received nutrition education; the other class, the "no-education" group, did not receive the education. After completing the eight nutrition lessons, the effectiveness of the education was analyzed by measuring changes in the nutrition knowledge, eating habits and food preferences of the nutrition-education group vs. the no-education group. Before nutrition education, there was no significant difference between the two groups in terms of nutrition knowledge. However, after the nutrition education, the nutrition-education group's nutrition knowledge was significantly improved, compared to that of the no-education group (p < 0.001). Following education, the nutrition-education group's responses to the "eating habit" item, "I eat fruits every day," were significantly more positive, compared to the responses of the no-education group (p < 0.01). However, for the ten food groups listed as food preferences, except for fish and shellfish (p < 0.05), there was no significant difference in the responses of the two groups. Following the education, the nutrition-education group showed significantly increased preferences for 12 food items (red beans, mackerels, yellow corvinas, dried laver, kelps, radish, lettuce, pears, kiwi fruits, plums, grapes and sweet drinks made from fermented rice) out of 112 items, compared to the selected preferences of the no-education group. After education, 75.9% of the students in the nutrition-education group indicated changes in their eating habits, and 89.6% of them answered that the nutrition education helped them change their eating habits. The most helpful medium for changing their eating habits was animations (31.0%), followed by songs (20.7%) and lectures (17.2%). As a result of this study, after completing the nutrition education, students in the nutrition-education group showed significant changes in food preferences, and their level of nutrition knowledge was significantly increased. However, their eating habits did not actively change. Therefore, in order to establish proper eating habits, a longer period of consistent education is required, using various educational media and learning methods such as extracurricular activities and discretionary activity programs.

• Journal of Fashion Business
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• v.19 no.6
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• pp.82-100
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• 2015

Mobile fashion apps present much opportunity for marketers to engage consumers, however not all apps provide enough functions for their targeted audience. This study aims to determine how mobile fashion apps can be used to build brand community with consumer engagement. Qualitative data on fashion mobile apps were collected from the Apple app store and Android market during the spring and summer of 2015. A total of 110 fashion mobile apps were collected;, 50 apps were identified as apparel brands that either manufacture or sell apparel to consumers, which we categorized as "brand" fashion apps, and the remaining 60 were categorized as "non-brand" fashion apps. The result of the study can be summarized as below. The 60 non-brand fashion apps were grouped into 5 app types: shopping, searching, sharing, organizational, and informational. The main functions are for informational use and shopping needs, since at least half (31 apps) are used for either retrieving information or for shopping. However, in contrast, social networking and location were infrequent and not commonly utilized by these apps. The most common type of non-brand fashion apps available were shopping apps;, many shopping apps enable users to shop from several different websites and save their items into one universal shopping cart so that they only check out once. Most of these apps are informational and help consumers make more informed decisions on purchases;, in addition many offer location services to help consumers find these items in store. While these apps perform several functions, they do not link to social media. The 50 brand apps were grouped into 5 brand types: athletic, casual, fast fashion, luxury, and retailer. These apps were also checked for attributes to determine their functionality. The result shows that the main functions of brand fashion apps are for information (82% of the 50 apps) as well as location searching (72% of 50 apps). Conversely, these apps do not offer any photo sharing, and very few have organizational or community functions. Fashion mobile apps and m-marketing elements: To build brand community, mobile apps can be designed to motivate consumer's engagement with brands. The motivations of fashion mobile apps are useful in developing fashion mobile apps. Entertainment motives can be fulfilled with multimedia attributes, functionality motives are satisfied with organizational and location-based features, information motives with informational service, socialization with community and social network, learning and intellectual stimulation from informational attributes, and trend following through photo sharing. The 8 key attributes of mobile apps can correspond to the 4 m-marketing elements (i.e., Informative content, multimedia, interactions, and product promotions) that are further intertwined with m-branding elements. App Attributes and M-Marketing aim to Build Brand Community;, the eight key attributes can impact on 4 m-branding elements, which further contribute to building brand community by affecting consumers' perceptions of brands preference and advocacy, and their likelihood to be loyal.

• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.270-283
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• 2012

With the advent of multi-channel TV, IPTV and smart TV services, excessive amounts of TV program contents become available at users' sides, which makes it very difficult for TV viewers to easily find and consume their preferred TV programs. Therefore, the service of automatic TV recommendation is an important issue for TV users for future intelligent TV services, which allows to improve access to their preferred TV contents. In this paper, we present a recommendation model based on statistical machine learning using a collaborative filtering concept by taking in account both public and personal preferences on TV program contents. For this, users' preference on TV programs is modeled as a latent topic variable using LDA (Latent Dirichlet Allocation) which is recently applied in various application domains. To apply LDA for TV recommendation appropriately, TV viewers's interested topics is regarded as latent topics in LDA, and asymmetric Dirichlet distribution is applied on the LDA which can reveal the diversity of the TV viewers' interests on topics based on the analysis of the real TV usage history data. The experimental results show that the proposed LDA based TV recommendation method yields average 66.5% with top 5 ranked TV programs in weekly recommendation, average 77.9% precision in bimonthly recommendation with top 5 ranked TV programs for the TV usage history data of similar taste user groups.

• 대한공업교육학회지
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• v.37 no.1
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• pp.125-143
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• 2012

This study aimed to identify the effect of the instruction applied with a project method for the 'Making Model by Architecture' unit in vocational High schools on the improvement of the Key competences. With this aim, the study selected as an experimental group, control group third graders in two classroom in G vocational High Schools in Goyang, Gyeonggi-do. Aiming at the selected students in the experimental group and the control group, the study conducted a pre-test of their Key competences; thus, the study confirmed that there was no statistically significant difference. Then, the study offered a class applied with a project method to the experimental group, while offering a traditional instruction to the control group. After offering the class, the study undertook a post-test, and verified the effect. In order to prove the test result, the study carried out a Hest using the SPSSWIN 12.0 statistical program, while the significance level being ${\alpha}$<.05. The conclusions obtained from this study include the following. All the six selected areas including 'problem-solving skills', 'communication skills', 'resource utilization competence', 'mathematical competence', 'interpersonal management competence' and 'self-management competence', which were supposed to be appropriate for this study among the sub-areas of Key competences, were found to show significant differences between the experimental group applied with a project method and the control group as a result of the post-test of the two groups. In summarizing the above research results, the class using a project method for the 'Making Model by Architecture' unit was discovered to be effective for improving Key competences. In particular, it may be more effective learning method for enhancing six areas greatly relevant to the project method among various sub-areas of Key competences.

• Journal of Broadcast Engineering
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• v.11 no.2 s.31
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• pp.207-221
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• 2006

A fully automatic and computationally efficient method is proposed for intelligent display of soccer video on small multimedia mobile devices. The rapid progress of the multimedia signal processing has contributed to the extensive use of multimedia devices with a small LCD panel. With these emerging small mobile devices, the video sequences captured for standard- or HDTV broadcasting may give the small-display-viewers uncomfortable experiences in understanding what is happening in a scene. For instance, in a soccer video sequence taken by a long-shot camera technique, the tiny objects (e.g., soccer ball and players) may not be clearly viewed on the small LCD panel. Thus, an intelligent display technique is needed for small-display-viewers. To this end, one of the key technologies is to determine region of interest (ROI), which is a part of the scene that viewers pay more attention to than other regions. In this paper, the focus is on soccer video display for mobile devices. Instead of taking visual saliency into account, we take domain-specific approach to exploit the characteristics of the soccer video. The proposed scheme includes three modules; ground color learning, shot classification, and ROI determination. The experimental results show the propose scheme is capable of intelligent video display on mobile devices.