• The Journal of the Korea Contents Association
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• v.15 no.11
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• pp.635-657
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• 2015

The current society characterized by knowledge-based information technology and multiculturalism put more emphasis on problem-solving skills, creative thinking, and communication skills than any other periods did. In response to the demand of the current times, multidisciplinary, or convergence courses and majors are being created and conducted in college education, yet, with the lack of specific teaching and learning model for the convergence courses. In this context, this study aimed to examine PBL as an instructional model for the convergent approaches in classroom, since PBL has been regarded as a model for fostering the 21st century learning capabilities for student coupled with the learning principles of authentic tasks, learner-centeredness, collaborative learning. This study, after conducted a PBL course for the general art education during the summer semester of 2014, analyzed the result using data collected from students' reflective journals, in-depth interviews, and SNS posts among the students. The result presented students' enhanced self-respect, increased interest in their learning and communication skills, and their recognition of the value on diversity and empathetic attitudes toward each others. In conclusion, PBL showed its potential as an alternative instructional model for the multidisciplinary and convergent learning in college education.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.366-373
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• 2020

This study explored the factors associated with dependence among smartphone-dependent adults in their 20s. The data was derived from the 2017 survey on smartphone over-dependence conducted by the Ministry of Science and ICT and the National Information Society Agency. The participants were 879 adults in their 20s. The data was analyzed by frequencies, percentages, means, standard deviations, independent t-tests, Pearson's correlation coefficients, and multiple regression analysis. The results revealed instant messengers as the most used application by participants. Participants in the high risk category of dependence also used SNS (Social Networking Services), music, and games more than those in the potential risk category. The more serious the dependence, the greater the frequency of smartphone use (β=.16, p=.000), and use of games (β=.10, p=.028), webtoons (β=.14, p=.004), SNS (β=.09, p=.047), and financial transactions (β=.17, p=.000). They did not recognize their smartphone dependence when it was relatively low. However, when this became serious, they then realized that they depended on the smartphone more than others. That means that it is not easy for adults to recognize their smartphone dependence on their own. However, recognition of the problem is the first step for adults to solve their problems. A program that evaluates their problematic smartphone use should be installed and used on all smartphones.

• The Journal of the Convergence on Culture Technology
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• v.1 no.2
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• pp.71-75
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• 2015

Smart City for establishing mutual communication for next-generation digital signage technology attracting attention in the tele screen service is being spread. In recent years, the state of the surrounding circumstances of the user-to-user information such as situation-based, bi-directional communication by collecting and analyzing the possible interactive tele-screen services. This study suggests the value of smart city services platform, standardization trends, domestic, and international marketability analysis information. Tele-screen service technology is able to be a high-level administrative services, and further domestic e-government technology can be spread all over the world.

• Journal of Korea Society of Digital Industry and Information Management
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• v.20 no.2
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• pp.37-47
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• 2024

The food tech market, which uses artificial intelligence robots for the restaurant industry, is gradually expanding. Among them, the robot barista, a representative food tech case for the restaurant industry, is characterized by increasing the efficiency of operators and providing things for visitors to see and enjoy through a 24-hour unmanned operation. This research was conducted through text mining analysis to examine trends related to robot baristas in the restaurant industry. The research results are as follows. First, keywords such as coffee, cafe, certification, ordering, taste, interest, people, robot cafe, coffee barista expert, free, course, unmanned, and wine sommelier were highly frequent. Second, time, variety, possibility, people, process, operation, service, and thought showed high closeness centrality. Third, as a result of CONCOR analysis, a total of 5 keyword clusters with high relevance to the restaurant industry were formed. In order to activate robot barista in the future, it is necessary to pay more attention to functional development that can strengthen its functions and features, as well as online promotion through various events and SNS in the robot barista cafe.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.619-626
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• 2012

The purpose of this study is to compare and analyze the utilization state of smart devices and the recognition level of educational application development of the general high school and the specialized high school. Specialized high school students preferred the utilization of smart devices more and daily spent on the devices more time than general high school students. As for the learning field, language for the general high school and the certificate of qualification for the specialized high school were shown high. The merit of smart device utilization is the use of spare time and its infrastructure was most required. The most expected content is a video lecture for the general high school and cooperative learning for the specialized high school and the most satisfied point was mobility. The specialized high school students feel more necessity about the application development for culinary education and had a plan to utilize it more and more preferred practice videos. As for the food development areas, the general high school students hoped simple food and the specialized high school students did cooking technician food and they both hoped the application to be uploaded in portal sites and the department homepage. The application development for culinary education is required to focus simulation learning including practice videos and cooking recipes and add an evaluation function to check the academic achievement levels. It is required to provide the subject goals of each course and concrete information on solving problems. Contents including video, music, texts need to be attached to improve learning immersion. There should be the beginning and development of a lesson and the flow of arrangement and communication between main bodies of learning should be improved by utilization of SNS cooperative learning services.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.8
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• pp.601-605
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• 2009

Recently, photo sharing and publishing based Social Network Sites(SNSs) are increasingly attracting the attention of academic and industry researches. Millions of users have integrated these sites into their daily practices to communicate with online people. In this paper, we propose an efficient face annotation and retrieval system under SNS. Since the system needs to deal with a huge database which consists of an increasing users and images, both effectiveness and efficiency are required, In order to deal with this problem, we propose a face annotation classifier which adopts an online learning and social decomposition approach. The proposed method is shown to have comparable accuracy and better efficiency than that of the widely used Support Vector Machine. Consequently, the proposed framework can reduce the user's tedious efforts to annotate face images and provides a fast response to millions of users.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.289-301
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• 2023

Due to the development and dissemination of modern technology, anyone can easily communicate using services such as social network service (SNS) through a personal computer (PC) or smartphone. The development of these technologies has caused many beneficial effects. At the same time, bad effects also occurred, one of which was the spam problem. Spam refers to unwanted or rejected information received by unspecified users. The continuous exposure of such information to service users creates inconvenience in the user's use of the service, and if filtering is not performed correctly, the quality of service deteriorates. Recently, spammers are creating more malicious spam by distorting the image of spam text so that optical character recognition (OCR)-based spam filters cannot easily detect it. Fortunately, the level of transformation of image spam circulated on social media is not serious yet. However, in the mail system, spammers (the person who sends spam) showed various modifications to the spam image for neutralizing OCR, and therefore, the same situation can happen with spam images on social media. Spammers have been shown to interfere with OCR reading through geometric transformations such as image distortion, noise addition, and blurring. Various techniques have been studied to filter image spam, but at the same time, methods of interfering with image spam identification using obfuscated images are also continuously developing. In this paper, we propose a deep learning-based spam image detection model to improve the existing OCR-based spam image detection performance and compensate for vulnerabilities. The proposed model extracts text features and image features from the image using four sub-models. First, the OCR-based text model extracts the text-related features, whether the image contains spam words, and the word embedding vector from the input image. Then, the convolution neural network-based image model extracts image obfuscation and image feature vectors from the input image. The extracted feature is determined whether it is a spam image by the final spam image classifier. As a result of evaluating the F1-score of the proposed model, the performance was about 14 points higher than the OCR-based spam image detection performance.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.3
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• pp.11-21
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• 2010

To aim at improving performance and reflecting user's needs of retrieval, the number of researches has been actively conducted in recent year as the quantity of information and generation of the web pages exceedingly increase. One of alternative approaches can be a tagging system. It makes users be able to provide a representation of metadata including writings, pictures, and movies etc. called tag and be convenient in use of retrieval of internet resources. Tags similar to keywords play a critical role in maintaining target pages. However, they still needs time consuming labors to annotate tags, which sometimes are found to be a hinderance caused by overuse of tagging. In this paper, we present an automatic tagging scheme for a solution of current tagging system conveying drawbacks and inconveniences. To realize the approach, face recognition-based tagging system on SNS is proposed by building a face area detection procedure, linear-based classification and boosting algorithm. The proposed novel approach of tagging service can increase possibilities that utilized SNS more efficiently. Experimental results and performance analysis are shown as well.

• Human Ecology Research
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• v.56 no.6
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• pp.555-571
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• 2018

This study identified the characteristics of fashion rental service users as well as analyzed their purchase decision-making processes. A qualitative investigation was conducted through in-depth interviews with 13 women in their 20s-30s who have experienced renting fashion items due to a high interest in fashion. The results of the study are summarized as follows. The need recognition stage analyzed ventilation by mass media, SNS impact, curiosity, saving shopping time and money, awareness of situational necessity, and creation of various styles. The information search stage analyzed how users obtained information from 2 different sources of nonmarketer-dominated sources and marketer-dominated sources. The pre-purchase stage analyzed the evaluation of alternatives in which study participants used 2 evaluation criteria for fashion rental services and fashion rental items. The purchase stage analyzed how participants wait and select desired items (when receiving the notification of rentable items) or select alternative products. The consumption stage examined the usage frequency and usage method. The study divided the post-consumption evaluation stage into 2 categories for evaluation: personal feelings and service. The post-consumption behavior stage analyzed how participants displayed WOM, eWOM and purchase rental product behavior. Clothing shopping orientation of study participants is displayed in 5 dimensions of brand-seeking propensity, individuality-seeking propensity, economic efficiency-seeking propensity, rationality-seeking propensity, and pleasure-seeking propensity. This study identified three main characteristics in the study participants: interest in the fashion, favorable attitude toward used fashion items, consciousness of others.

• Smart Media Journal
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• v.10 no.4
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• pp.71-79
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• 2021

One of the social aspects that changes as the use of the Internet becomes widespread is communication in online space. In the past, only one-on-one conversations were possible remotely, except when they were physically in the same space, but nowadays, technology has been developed to enable communication with a large number of people remotely through bulletin boards, communities, and social network services. Due to the development of such information and communication networks, life becomes more convenient, and at the same time, the damage caused by rapid information exchange is also constantly increasing. Recently, cyber crimes such as sending sexual messages or personal attacks to certain people with recognition on the Internet, such as not only entertainers but also influencers, have occurred, and some of those exposed to these cybercrime have committed suicide. In this paper, in order to reduce the damage caused by malicious comments, research a method for improving the performance of discriminate malicious comments through feature extraction based on parts-of-speech.