• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.6-8
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• 2022

Many systems that use images through object recognition using deep learning have provided various solutions beyond the existing methods. Many studies have proven its usability, and the actual control system shows the possibility of using it to make people's work more convenient. Many studies have proven its usability, and actual control systems make human tasks more convenient and show possible. However, with hardware-intensive performance, the development of models is facing some limitations, and the ease with the use and additional utilization of many unupdated models is falling. In this paper, we propose how to increase utilization and accuracy by providing additional information on the emotional regions of colors and objects by utilizing learning and weights from HSV color histograms of local image data recognized after conventional stereotyped object recognition results.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.439-441
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• 2023

National park is one of the important types of protected area management systems established by IUCN and a management model for effective conservation and sustainable use of natural and cultural heritage in countries around the world, and it assumes important roles in conservation, scientific research, education, recreation and driving community development. This study takes Liaohe National Park in China, a typical representative of global coastal wetlands, as a case study, and uses python technology to collect travelogues and reviews of visitors from Mafengwo.com, Ctrip.com, Go.com, Meituan.com and Dianping.com as a source, and the text spans from 2015 to 2022. The results show that wildlife resources, natural landscape with river and sea, wetland ecology and fishing and hunting culture of northern China are fully reflected in the perceptions of visitors to Liaohe National Park. However, there is still much room for improvement in terms of supporting services and facilities, public education and tourists' experience and participation in Liaohe National Park. In this paper, we use python data visualization technology to study the public perception of wetland wildlife as the theme, and grasp the satisfaction, spatial distribution, activity content and emotional tendency of the public in the process of wetland wildlife as the theme, so as to better promote the Liaohe National Park to better carry out the public experience while strictly adhering to ecological protection, and to provide the Liaohe National Park with a better opportunity to This will provide scientific basis for the Liaohe National Park to play a better role in ecological civilization construction and education of ecological civilization awareness.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.33-39
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• 2023

Although COVID-19 has transitioned to a level 4 infectious disease in 2023 and has entered a stable trend, in special education settings, the importance of supporting the academic and social development gaps of students with disabilities caused by non-face-to-face learning situations such as remote classes during the COVID-19 period is emerging. there is. Accordingly, in this study, in order to identify and support the educational status and academic deficits of students with disabilities after COVID-19, we conducted a survey targeting 2,214 special education teachers in 17 cities and analyzed the results. As a result of the study, due to COVID-19, the developmental delay and educational gap in students with disabilities in terms of academics, emotions, and behavior deepened, and there was a high demand for manpower support, psychological counseling, and medical support for emotional behavior as a way to support this. Based on the results of this study, follow-up results were proposed.

• Journal of Korean Academy of Nursing
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• v.53 no.5
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• pp.500-513
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• 2023

Purpose: Women are more vulnerable to post-traumatic stress (PTS) than men, causing several health problems. Nurses should understand and work with women who have experienced trauma and provide interventions to promote their physical, social, and mental health. Methods: This quasi-experimental pilot study used a one-group pre-test/post-test design. Data were collected from 14 women recruited between December 2019 and May 2020 from a self-sufficiency support center in South Korea for sexually-exploited women who had experienced trauma. The program consisted of six one-on-one intervention sessions per week for six weeks. Each session averaged 60~120 minutes. Participants were assessed at pre-test, post-test, and one-month follow-up. Changes in outcome variables over time were analyzed using the Wilcoxon signed-rank and Friedman tests. Results: The caring program for health promotion was divided into six sessions: understanding the self, sharing traumatic events and negative emotions, reframing the meaning of traumatic events, identifying thoughts and physical and emotional responses, developing health promotion activities, and maintaining a positive attitude during the process of change. As a result of the caring program, PTS (F = 36.33, p < .001), depression (F = 24.45, p < .001), health-promoting behaviors (F = 7.06, p = .004), and self-esteem (F = 19.74, p < .001) among the participants differed significantly at pre-test, post-test, and follow-up. Conclusion: This study provides foundational information for the implementation of a theory-driven program by nurses in clinical and community settings to provide comprehensive care for women who have experienced trauma.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.300-305
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• 2023

This thesis is a study of content development utilizing media outlets to date through digital humans. The trend of global content is that the video content industry, including the character business, is growing. Lil Michela, who was selected as one of the 25 most influential people on the Internet by Time magazine in 2018, Nasua, who appeared in a SK Telecom commercial, and Rosie, who appeared in a Shinhan Bank commercial, are representative. Digital humans, which are driving new content, are computer-generated human characters with various characteristics and are referred to as virtual humans, metahumans, and cyber humans. With the rise of the metaverse after COVID-19, digital humans are being utilized in various forms such as media and marketing as an element of visual content. In the form of media, we can see that the boundaries between the offline and digital worlds are converging, and in the form of marketing, we can see that digital humans connect consumers and products more naturally. In the form of interaction, it is possible to achieve two-way communication through various methods of operation, and through these factors, it is possible to go beyond behavioral communication in the form of memorialization to emotional communication through AI technology. What can be seen through these processes is that through the currently developing digital human production methods and AI functions, not only experts but also non-experts can create quality contents, and new directions of contents will appear, and contents that can provide immediate feedback by bringing consumers and creators closer together have been studied.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3218-3241
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• 2023

Financial fraud undermines the sustainable development of financial markets. Financial statements can be regarded as the key source of information to obtain the operating conditions of listed companies. Current research focuses more on mining financial digital data instead of looking into text data. However, text data can reveal emotional information, which is an important basis for detecting financial fraud. The audit opinion of the financial statement is especially the fair opinion of a certified public accountant on the quality of enterprise financial reports. Therefore, this research was carried out by using the data features of 4,153 listed companies' financial annual reports and audits of text opinions in the past six years, and the paper puts forward a financial fraud detection model integrating audit opinions. First, the financial data index database and audit opinion text database were built. Second, digitized audit opinions with deep learning Bert model was employed. Finally, both the extracted audit numerical characteristics and the financial numerical indicators were used as the training data of the LightGBM model. What is worth paying attention to is that the imbalanced distribution of sample labels is also one of the focuses of financial fraud research. To solve this problem, data enhancement and Focal Loss feature learning functions were used in data processing and model training respectively. The experimental results show that compared with the conventional financial fraud detection model, the performance of the proposed model is improved greatly, with Area Under the Curve (AUC) and Accuracy reaching 81.42% and 78.15%, respectively.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.427-436
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• 2024

Recently, the importance of information security (IS) has been socially recognized, leading organizations to adopt IS policies, secure specialized personnel, and demand IS compliance from employees. However, the implementation of these policies can disrupt existing work processes, causing resistance among employees. This study aims to elucidate the mechanism linking work stress, caused by IS policies that do not consider the work system, to individual job burnout and IS policy resistance. We established a research model and hypotheses based on previous studies and utilized structural equation modeling with data collected from organization members of companies that have implemented IS policies. The results of the structural equation modeling confirmed that work ambiguity and work impediment are linked to IS policy resistance through job burnout, characterized by emotional exhaustion and disengagement. Our findings suggest that the swift implementation of IS policies can provoke a backlash from employees, with stress being the primary cause. This paradoxically indicates the need for the development of organization-specific IS policies.

• Human Ecology Research
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• v.62 no.2
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• pp.369-383
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• 2024

The aim of this study was to develop and implement a program based on Cognitive Behavior Therapy (CBT) for female college students experiencing body dissatisfaction. To systematize the program development process, we adopted the service design method. First, we conducted In-Depth Interviews (IDIs) to identify the difficulties faced by six female college students who experience body dissatisfaction, and to determine what kind of help they needed. Second, content analysis of the findings revealed that female college students were experiencing emotional-behavior problems which derived from the discrepancy between their ideal body image and the reality. Third, a prototype of a cognitive reconstruction program was developed to help transform their perceived 'body distortion' to a rational cognitive concept and thus reduce maladaptive consequences of 'body dissatisfaction'. The overall program consisted of three therapeutic components and seven steps. Fourth, to assess the effectiveness of the program, survey and IDIs were conducted. The results revealed that it is appropriate to use a cognitive model to solve problems caused by body dissatisfaction, and that understanding and reconstructing one's own cognitive processes can be effective in reducing body dissatisfaction. However, based on feedback from participants, a number of revisions were proposed, such as including sufficient induction regarding the behavioral change.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.105-112
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• 2024

In contemporary society, the expression of emotions and self-reflection are considered pivotal factors with a positive impact on stress management and mental well-being, thereby highlighting the significance of journaling. However, traditional journaling methods have posed challenges for many individuals due to constraints in terms of time and space. Recent rapid advancements in chatbot and emotion analysis technologies have garnered significant attention as essential tools to address these issues. This paper introduces an artificial intelligence chatbot that integrates the GPT-3 model and emotion analysis technology, detailing the development process of a system that automatically generates journals based on users' chat data. Through this system, users can engage in journaling more conveniently and efficiently, fostering a deeper understanding of their emotions and promoting positive emotional experiences.

• Journal of Korean Society for Quality Management
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• v.52 no.1
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• pp.95-113
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• 2024

Purpose: This study focused on the societal changes associated with the entry into an ultra-aged society and the increase in single-person households. The core objective of this research is to investigate how social intelligent robots can bring about positive changes in the lives of individuals in single-person households and how such changes influence user satisfaction and the intention to use these robots. Methods: The study employed a cross-sectional analysis using a structural equation model. A survey designed to assess the impact of social intelligent robots' characteristics, such as perceived encouragement, empathy, presence, appearance, and attachment, on user satisfaction and usage intentions was conducted. Data were collected from a total of 335 users and analyzed using the structural equation model. Results: In the characteristics of social intelligent robots for single-person households, it was found that empathy, presence, and attachment significantly influenced satisfaction, while perceived encouragement, empathy, and attachment significantly influenced usage intentions. The research results indicate differences between enhancing user satisfaction and increasing the intention to use social intelligent robots. The findings suggest the essential need for a user-centric approach in the design and development of social intelligent robots. Additionally, it was observed that emotional support plays a crucial role in users' experiences with social intelligent robots. Conclusion: This study verified the impact of social intelligent robots on satisfaction and usage intentions based on users' experiences. It examined the influence of linguistic, visual, and personal characteristics of robots on user experiences, providing insights into how technological and human aspects of social intelligent robots interact to shape user satisfaction and usage intentions. Consequently, the study confirmed that social intelligent robots can bring positive changes to human life, emphasizing the necessity for the advancement of robot technology in a human-centric direction.