• Korean Association of Arts Management
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• no.56
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• pp.145-188
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• 2020

This study starts from an experience-oriented perspective that raises the need to examine the individual's cultural consumption experience with qualitative approach. In particular, this study aims to analyze in-depth the journey of the performance experience by connecting with offline-based social relationships as well as online-based informative and communicative behaviors. For this, in-depth interviews were conducted with 15 teams (30 people) by setting up two people as research units, and self-recorded data using the mobile application were collected. Results showed that social media and online communication play an important role before and after the performance in amplifying the performance experience and the consumer's taste developments. This study also found that relational aspects of the performance experience by identifying the significance of the partners and the existence of the cultural taste leader. For each result, there was a difference among audience proficiency: enthusiastic, interested, and indifferent audiences. Based on these results, we suggest that the performance experience should not be limited to the performance itself, but should be understood in a comprehensive manner before and after the performance, and that the consumption of the performance takes place in a social relationship, not in an individual's own experience only.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.4
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• pp.283-290
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• 2022

In this study, an IoT inspection system that can be linked with a server was developed using a gas timer and ESP-01 Wi-Fi module installed on a gas valve in the home. The server environment of the gas leak IoT inspection system was installed with APM (Apache, PHP, MySQL) to collect gas pressure data by generation so that leakage checks could be performed. In order to control the gas leak IoT inspection system, the app inventory was used to manage the gas leak check value in real time. In addition, user convenience has been enhanced so that membership management, WiFi settings, and leakage check values can be checked through mobile apps. In order to manage subscribers by region, the user list was checked by logging in in in the administrator mode so that the information on whether or not the leak test was conducted and the results could be provided. In addition, when the user presses the gas leak check button, the pressure is automatically checked, and the measured value is stored in the server, and when a gas leak occurs, the leakage check is performed after alarm and repair so that it can be used if normal. In addition, in order to prevent overlapping membership, membership management can be performed based on MAC addresses.

• Therapeutic Science for Rehabilitation
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• v.12 no.3
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• pp.7-18
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• 2023

Objective : This study aimed to confirm the research characteristics by analyzing the literature that applied the school readiness programs for children with disabilities. Methods : Studies were collected from the PubMed, Embase, Web of Science, and Research Information Sharing Service databases. The key terms were "School readiness" AND ("Occupational Therapy" OR "Rehabilitation") in English and Korean. Total eight articles were selected through the selection and exclusion criteria. Results : The programs included multi-type training, motor skill training, parent training, and mobile application training. The providers were psychologists, occupational therapists, physical therapists, speech pathologists, community workers, educators, and the psychologists who conducted most of the research. The program factors can be classified into academic function, motor function, social function, parental training, and others. Academic and social functions accounted for the largest proportion of the respondents. The intervention improved multiple skills, literacy, parenting skills, and gross fine motor function. Conclusion : This study aimed to provide basic data for school-based occupational therapy by analyzing school readiness programs for children with disabilities. Recently, interest in and research on school readiness has increased. Occupational therapists should also establish their roles in the field of school-related rehabilitation and provide various school-based occupational therapies.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.125-144
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• 2023

Recently, the use of Large Language Models (LLMs) such as ChatGPT has been increasing in various fields such as interactive commerce and mobile financial services. However, LMMs, which are mainly created by learning existing documents, can also learn various human biases inherent in documents. Nevertheless, there have been few comparative studies on the aspects of bias and discrimination in LLMs. The purpose of this study is to examine the existence and extent of nine types of discrimination (Age, Disability status, Gender identity, Nationality, Physical appearance, Race ethnicity, Religion, Socio-economic status, Sexual orientation) in LLMs and suggest ways to improve them. For this purpose, we utilized BBQ (Bias Benchmark for QA), a tool for identifying discrimination, to compare three large-scale language models including ChatGPT, GPT-3, and Bing Chat. As a result of the evaluation, a large number of discriminatory responses were observed in the mega-language models, and the patterns differed depending on the mega-language model. In particular, problems were exposed in elder discrimination and disability discrimination, which are not traditional AI ethics issues such as sexism, racism, and economic inequality, and a new perspective on AI ethics was found. Based on the results of the comparison, this paper describes how to improve and develop large-scale language models in the future.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.21-30
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• 2023

The study proposes a model that utilizes Python-based deep learning text classification techniques to detect the legality of illegal financial advertising posts on the internet. These posts aim to promote unlawful financial activities, including the trading of bank accounts, credit card fraud, cashing out through mobile payments, and the sale of personal credit information. Despite the efforts of financial regulatory authorities, the prevalence of illegal financial activities persists. By applying this proposed model, the intention is to aid in identifying and detecting illicit content in internet-based illegal financial advertisining, thus contributing to the ongoing efforts to combat such activities. The study utilizes convolutional neural networks(CNN) and recurrent neural networks(RNN, LSTM, GRU), which are commonly used text classification techniques. The raw data for the model is based on manually confirmed regulatory judgments. By adjusting the hyperparameters of the Korean natural language processing and deep learning models, the study has achieved an optimized model with the best performance. This research holds significant meaning as it presents a deep learning model for discerning internet illegal financial advertising, which has not been previously explored. Additionally, with an accuracy range of 91.3% to 93.4% in a deep learning model, there is a hopeful anticipation for the practical application of this model in the task of detecting illicit financial advertisements, ultimately contributing to the eradication of such unlawful financial advertisements.

• Journal of Korea Entertainment Industry Association
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• v.13 no.1
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• pp.25-34
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• 2019

The purpose of this study is to develop a mobile app for mental health self care of university student. User centered design is a research design that applies the subject's needs assessment, analysis, design, development, evaluation, modification and supplement to suit the subjects. In order to manage the mental health of university students, they consisted of four main areas of mental health problems: drinking, sleeping, depression, and stress. It is designed to enable self test content, analysis and notification of inspection results, and management plan for current status of each area. Based on this, I developed an Android based mental health self-care Application. The subject can enter his or her mental health status data to explain the normal or risk level for each result, and the subject can then select the appropriate intervention method that he or she can perform. In addition, we developed a mental health self care calendar that can display the present status of each of the four areas on a day by day basis, and the current status can be expressed in an integrated manner through animations and status bars. The purpose of this study was to develop a mental health self-care app that can be improved by continuous and improved programs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.141-143
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• 2022

This paper presented a new technology to identify traffic violations of motorbike riders by detecting the traffic signal using You Only Look Once (YOLO) object detection. The hardware module that is mounted on the front of the motorbike consists of Raspberry Pi with a camera to run the YOLO object detection, a GPS module to acquire the motorcycle's coordinate, and a LoRa communication module to send the data to a cloud DB. The main goal of the software is to determine whether a motorbike has violated a traffic signal. This paper proposes a function to recognize the red traffic signal colour with its movement inside the camera angle and determine that the traffic signal violation happens if the traffic signal is moving to the right direction (the rider turns left) or moving to the top direction (the riders goes straight). Furthermore, if a motorbike rider is violated the signal, the rider's personal information (name, mobile phone number, etc), the snapshot of the violation situation, rider's location, and date/time will be sent to a cloud DB. The violation information will be delivered to the driver's smartphone as a push notification and the local police station to be used for issuing violation tickets, which is expected to prevent motorbike riders from violating traffic signals.

• The Korean Journal of Coaching Psychology
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• v.5 no.2
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• pp.101-125
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• 2021

This study tried to identify the psychological mechanisms that middle and high school students can adaptively solve various problems, and to identify differences according to gender and school level. To this end, the growth mindset was set as an independent variable predicting the problem-solving ability of middle and high school students, and ego-resilience and emotional intelligence were set as the mediating variables. As for the research data, responses of 94 middle school students(40 males, 54 females) and 134 high school students(63 males, 71 females) who participated through mobile and off-line were analyzed using SPSS 24.0 and AMOS 18.0. The results are as follows. First, differences according to gender and school level were significant only in emotional intelligence. Second, ego-resilience and emotional intelligence mediated the relationship between growth mindset and problem-solving ability respectively. Third, the dual mediation effect of ego-resilience and emotional intelligence was significant in the relationship between growth mindset and problem-solving ability. Based on these results, theoretical and practical discussions and implications for improving problem-solving ability of middle and high school students are presented.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.197-216
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• 2022

With the development of Internet and mobile technology and the spread of social media, a large amount of information is being generated and distributed online. Some of them are useful information for the public, but others are misleading information. The misleading information, so-called 'fake news', has been causing great harm to our society in recent years. Since the global spread of COVID-19 in 2020, much of fake news has been distributed online. Unlike other fake news, fake news related to COVID-19 can threaten people's health and even their lives. Therefore, intelligent technology that automatically detects and prevents fake news related to COVID-19 is a meaningful research topic to improve social health. Fake news related to COVID-19 has spread rapidly through social media, however, there have been few studies in Korea that proposed intelligent fake news detection using the information about how the fake news spreads through social media. Under this background, we propose a novel model that uses Graph2vec, one of the graph embedding methods, to effectively detect fake news related to COVID-19. The mainstream approaches of fake news detection have focused on news content, i.e., characteristics of the text, but the proposed model in this study can exploit information transmission relationships in social engagement networks when detecting fake news related to COVID-19. Experiments using a real-world data set have shown that our proposed model outperforms traditional models from the perspectives of prediction accuracy.

• Design Convergence Study
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• v.16 no.6
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• pp.123-135
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• 2017

In recent mobile health care service, health management using number of steps is becoming popular. In addition, a variety of activity trackers have made it possible to measure the number of steps more accurately and easily. Nevertheless, the activity tracker is not popularized, and it is a trend to use the pedometer sensor of the smartphone as an alternative. In this study, we tried to find out how much the number of steps collected by the smartphone versus the actual number of steps in actual situations, and what factors make the difference. We conducted an experiment to collect number of steps data of 21 people using the smartphone and wearable device simultaneously for 7 days. As a result, we found that the average number of steps of the smartphone is 62% compared to the actual number of steps, and that there is a large variation among users. We derived a regression model in which the accuracy of smartphone increases with the degree of awareness of smartphone. We expect that this can be used as a factor to correct the difference from the actual number of steps in the smartphone alone healthcare service.