• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.45-61
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• 2024

This study looked in-depth at the importance of cultivating and manifesting entrepreneurship, which is emphasized for companies to gain a competitive advantage and promote innovation in the uncertain environment that organizations face and in the development of technology due to recent industrial advancement, the following innovative performance, and the mechanisms in the performance process. Entrepreneurship is emphasized as a key factor in inducing creative work performance, creation and application of new ideas, and innovative performance at various levels within the organization in various global companies. In particular, this study examined the influence of the CEO's cultivation and expression of entrepreneurship as an organizational leader on the innovative behavior of organizational members, which is a leading factor in the organization's innovative performance, and the role of creative self-efficacy as a mechanism. Through this, the study was to verify the importance of creativity and cultivating a sense of self-efficacy for demonstrating innovative performance within an organization. Additionally, it was to confirm the role of organizational commitment of organizational members as a situational factor. For the empirical analysis, a total of 247 office workers were surveyed, sampled from 10 venture companies engaged in the manufacturing industry in industrial complexes in Daejeon, Korea. As the result of empirical analysis showed, it was confirmed that each sub-factor of the CEO's entrepreneurship had a positive effect on the innovative behavior of organizational members. And in the process, the importance of the creative self-efficacy of members to demonstrate innovative performance was verified by confirming positively significant mediating effect of creative self-efficacy. Furthermore, in the case of organizational commitment, it was found that the innovativeness and proactiveness of the CEO strengthened the positive influence on the creative efficacy of the organization members. Based on the results of empirical analysis, theoretical and practical implications were provided to improve the importance of cultivating and manifesting the CEO's entrepreneurship to demonstrate innovation within the organization.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.50 no.2
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• pp.179-192
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• 2024

In this study, six types of natural products, Prunus tomentosa (P. tomentosa), Akebia quinata (A. quinata), Prunus armeniaca (P. armeniaca), Smallanthus sonchifolius (S. sonchifolius), Citrus japonica (C. japonica), and Citrus australasica (C. australasica), were used to verify the effect of improving sleep and skin barriers by stress relief. As a result of the experiment, the production of cortisol, a stress hormone, was significantly inhibited by the P. tomentosa, C. australasica, A. quinata, and C. japonica among the six natural products. In addition, the expression of GAD67, a GABA-producing enzyme involved in sleep regulation, showed a significant increase in P. tomentosa purified water extract and C. australasica 50% ethanol extract, and the extract by each P. tomentosa solvent was found to have the highest total polyphenol content. Based on the results, the P. tomentosa extract with the highest activity was finally selected, and subsequent experiments were conducted. Among each P. tomentosa solvent extract, the DPPH radical scavenging activity was the highest in the 30% ethanol extract, and purified water extract increased GABA production and skin barrier factors filaggrin and claudin-1 expression the highest. HPLC analysis confirmed quercitrin as the main component of P. tomentosa extract, and quercitrin content by extraction solvent was high in the order of 30% ethanol > purified water > 70% ethanol > 50% ethanol. Quercitrin inhibited the production of cortisol in a concentration-dependent manner, significantly increasing GAD67 expression and GABA production, which had been reduced by cortisol. From the results of this study, it has been demonstrated that P. tomentosa can be used as a cosmetic material to help improve sleep and strengthen skin barriers by relieving stress.

• Journal of Marine Life Science
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• v.9 no.1
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• pp.9-21
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• 2024

Paralytic shellfish poisoning (PSP) including Saxitoxin (STX) is caused by harmful algae, and poisoning occurs when the contaminated seafood is consumed. The mouse bioassay (MBA), a standard test method for detecting PSP, is being sanctioned in many countries due to its low detection limit and the animal concerns. An alternative to the MBA is the Neuro-2a cell-based assay. This study aimed to establish various test conditions for Neuro-2a assay, including cell density, culture conditions, and STX treatment conditions, to suit the domestic laboratory environment. As a result, the initial cell density was set to 40,000 cells/well and the incubation time to 24 hours. Additionally, the concentration of Ouabain and Veratridine (O/V) was set to 500/50 μM, at which most cells died. In this study, we identified eight concentrations of STX, ranging from 368 to 47,056 fg/μl, which produced an S-shaped dose-response curve when treated with O/V. Through inter-laboratory variability comparison of the Neuro-2a assay, we established five Quality Control Criteria to verify the appropriateness of the experiments and six Data Criteria (Top and Bottom OD, EC₅₀, EC₂₀, Hill slop, and R² of graph) to determine the reliability of the experimental data. The Neuro-2a assay conducted under the established conditions showed an EC₅₀ value of approximately 1,800~3,500 fg/μl. The intra- & inter-lab variability comparison results showed that the coefficients of variation (CVs) for the Quality Control and Data values ranged from 1.98% to 29.15%, confirming the reproducibility of the experiments. This study presented Quality Control Criteria and Data Criteria to assess the appropriateness of the experiments and confirmed the excellent repeatability and reproducibility of the Neuro-2a assay. To apply the Neuro-2a assay as an alternative method for detecting PSP in domestic seafood, it is essential to establish a toxin extraction method from seafood and toxin quantification methods, and perform correlation analysis with MBA and instrumental analysis methods.

• Information Systems Review
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• v.18 no.3
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• pp.209-233
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• 2016

Internet companies that utilize social network have increased in number. The introduction of diverse social media services facilitated innovative changes in e-business. Social network service (SNS), which is a domain of social media, is a web-based service designed to strengthen human relations in the Internet and build new social relations. The remarkable growth of social network services and the profit generation and perception of this service are the new growth engines of this digital age. Given this development, many global IT companies views SNS as the most powerful form of social media. Thus, they invest efforts to develop business models using SNS.2) This study verifies the impact of privacy exposure in SNS as a result of privacy invasion. This study examines the purpose of using the SNS and user's awareness of the significance of personal information, which are key factors that affect self-disclosure of personal information. This study utilizes theory of reasoned action (TRA) to provide a theoretical platform that describes the specific behavior and emotional response of individuals. This study presents a research model that considers negative attitude (negatude). In this model, self-disclosure in SNS is considered a TRA. TRA is a subjective norm, a behavioral intention, and a key variable of exposure behavior. A survey was conducted on college students at Y university in Seoul to empirically verify the research model. The students have experiences in using SNS. A total of 198 samples were collected. Path analysis was applied to analyze the relations of factors. The results of path analysis show the statistically insignificant impact of privacy invasion on negatude, subjective norm, behavioral intention, and exposure behavior. The impact of unrecognized privacy invasion was also considered insignificant. The impacts of intention to use SNS on negatude, subjective norm, behavioral intention, and exposure behavior was significant. A significant impact was also found for the significance of personal information on subjective norm, behavioral intention, and exposure behavior, whereas the impact on negatude was insignificant. The impact of subjective norm on behavioral intention was significant. Lastly, the impact of behavioral intention on exposure behavior was insignificant. These findings are significant because the study examined the process of self-disclosure by integrating psychological and social factors based on theoretical discussion.

• Journal of Korean Dental Hygiene Science
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• v.6 no.2
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• pp.129-139
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• 2023

Background: The elderly population aged 65 or older in Korea is expected to continue to increase to 18.4% in 2023, and to enter a super-aged society at 20.6% in 2025. In clinical practice, the elderly discrimination of dental hygienists may experience difficulties during dental hygiene treatment due to an increase in the number of elderly patients due to aging, which can lead to maladjustment to work and turnover, so education on the understanding of the elderly is essential for students in the Department of Dentistry, who are prospective dental hygienists. Accordingly, a study was conducted to prepare for a super-aged society by studying the relationship between elderly discrimination and the knowledge and attitudes of the elderly, and to change the curriculum of universities and develop programs related to the elderly. Method: 204 students enrolled in the Department of Dentistry in D area were analyzed using the SPSS/WIN 25.0 program. The subject's geriatric discrimination, knowledge about the elderly, and attitude toward the elderly were calculated as the mean and standard deviation. T-test and one-way ANOVA were performed to verify the difference in geriatric discrimination according to the general characteristics of the subject, with a Scheffe' test applied for post-hoc analysis. Correlation analysis was conducted on the subject's geriatric discrimination, knowledge about the elderly, and attitudes toward the elderly. Results: Geriatrics scored 2.03±0.36 out of 4. Knowledge about the elderly was categorized as follows: physical domain 0.57±0.15; social domain 0.36±0.17; and psychological domain 0.35±0.20. The attitude toward the elderly was 3.86±0.27. Knowledge of the elderly averaged 11.27±3.30 points out of 25. The question with the highest percentage of correct answers to knowledge about the elderly was 'physical strength tends to decrease with age', which was 93.1%. The attitude toward the elderly according to the general characteristics of the study subjects showed significant differences in gender (p=0.040), age (p=0.026), and life experience with grandparents (p=0.001). The elderly discrimination of the study subjects showed a negative correlation in both attitude and knowledge toward the elderly, and among the elderly discrimination, there was a high positive correlation with regard to emotional avoidance (r=.892, p<0.001). Conclusion: College students are the leading players in caring for the elderly and are directly affected by aging social problems. Therefore, it is considered necessary to apply various programs in the state, society, and educational institutions to avoid negative prejudices that lead to positive thinking and discrimination against the elderly.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.44-62
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• 2024

The development of online funeral services and social issues of eco-friendly funeral culture have raised awareness of the new need for online funeral culture. There have been several attempts to revitalize online funeral services in domestic institutions and companies, but the effect is weak. The purpose of this study is to propose a design that can improve the accessibility and usability of online memorial services by analyzing the usability problem factors through a First Time User Experience analysis of the online memorial platform. Therefore, in this study, in order to identify the problem factors of the online memorial platform, a literature review on the UX, OOBE, and FTUE theories was conducted. The subject of the study was the app 'Memorial'. Before analyzing the First-Time User-Experience, IA was compared and analyzed with other similar services to understand the characteristics of the UX service of the app 'Memorial', which is the subject of the study. In addition, tasks corresponding to the Unpack-Setup/Configure-First Use stage were performed on 10 subjects who had no experience using the online memorial platform. The experimental process was expressed as the UX Curve to identify factors that caused negative experiences. As a result, the major problem factors included unnecessary UI elements, the need for sensitive personal information at the membership stage, and lack of immersion in the service. The improvements included strengthening community functions to facilitate the sharing of emotions and promote smooth communication between users. We proposed UI/UX service developments that enhanced the app by incorporating these insights. In order to verify the effectiveness, serviceability, and value of the developed prototype, an interview with a expert was conducted. The interviewes consisted of three service design experts. This study was conducted to contribute to the quality improvement and activation of the recently emerging online funeral services. The study is significant as it aims to understand the current status of these services and identify the factors necessary to improve service accessibility and usability. Subsequent studies require in-depth user verification of how much the proposed improvement plan affects the actual user experience.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.13-26
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• 2024

Multi-modal generation is the process of generating results based on a variety of information, such as text, images, and audio. With the rapid development of AI technology, there is a growing number of multi-modal based systems that synthesize different types of data to produce results. In this paper, we present an AI system that uses speech and text recognition to describe a person and generate a montage image. While the existing montage generation technology is based on the appearance of Westerners, the montage generation system developed in this paper learns a model based on Korean facial features. Therefore, it is possible to create more accurate and effective Korean montage images based on multi-modal voice and text specific to Korean. Since the developed montage generation app can be utilized as a draft montage, it can dramatically reduce the manual labor of existing montage production personnel. For this purpose, we utilized persona-based virtual person montage data provided by the AI-Hub of the National Information Society Agency. AI-Hub is an AI integration platform aimed at providing a one-stop service by building artificial intelligence learning data necessary for the development of AI technology and services. The image generation system was implemented using VQGAN, a deep learning model used to generate high-resolution images, and the KoDALLE model, a Korean-based image generation model. It can be confirmed that the learned AI model creates a montage image of a face that is very similar to what was described using voice and text. To verify the practicality of the developed montage generation app, 10 testers used it and more than 70% responded that they were satisfied. The montage generator can be used in various fields, such as criminal detection, to describe and image facial features.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.91-107
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• 2024

This study attempted to empirically verify the possibility of K-content for Chinese people who have recently slowed down due to restriction of movement and political and diplomatic conflicts, although it is a very meaningful market for Korea's content industry and tourism industry. As a result of the study, each item of K-content experience, national image, tourism attitude, and visit intention was derived as one factor, and only the national image factor was derived as two factors: 'functional image' and 'cultural image'. As a result of examining the influence relationship between them established based on previous studies focusing on the derived factors, all five research hypotheses were adopted. K-content experience was found to have a significant influence on both factors of the national image. It was found that it had a greater influence on cultural image factors than functional image factors, cultural image factors were found to have a greater influence on tourism attitudes, K-content experiences had a significant effect on tourism attitudes, and tourism attitudes had a significant effect on visit intentions. Based on the results of this study, it was once again confirmed that the national image even comtually bees an important factor for linking to practical tourism behavior, and in this respect, "culture" is an important key factor that can lead to practical tourism and visits. Previous national images indicate that if the functional aspect of the country was more emphasized, it is now necessary to focus more on the importance of culture than on the functional aspect. As the K-content experience has a significant effect on tourism attitude, it can have a positive effect on the formation of a positive tourism attitude that can lead to actual tourism behavior, so various efforts will be needed to form an active tourism attitude using K-content in the future. As the content and target scope of K-content are expanded and diversified, specific strategies for each sub-market using cultural contents in various fields should be established and implemented.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.2
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• pp.129-152
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• 2024

In the application of deep learning object detection via CCTV in tunnels, a large number of false positive detections occur due to the poor environmental conditions of tunnels, such as low illumination and severe perspective effect. This problem directly impacts the reliability of the tunnel CCTV-based accident detection system reliant on object detection performance. Hence, it is necessary to reduce the number of false positive detections while also enhancing the number of true positive detections. Based on a deep learning object detection model, this paper proposes a false positive data training method that not only reduces false positives but also improves true positive detection performance through retraining of false positive data. This paper's false positive data training method is based on the following steps: initial training of a training dataset - inference of a validation dataset - correction of false positive data and dataset composition - addition to the training dataset and retraining. In this paper, experiments were conducted to verify the performance of this method. First, the optimal hyperparameters of the deep learning object detection model to be applied in this experiment were determined through previous experiments. Then, in this experiment, training image format was determined, and experiments were conducted sequentially to check the long-term performance improvement through retraining of repeated false detection datasets. As a result, in the first experiment, it was found that the inclusion of the background in the inferred image was more advantageous for object detection performance than the removal of the background excluding the object. In the second experiment, it was found that retraining by accumulating false positives from each level of retraining was more advantageous than retraining independently for each level of retraining in terms of continuous improvement of object detection performance. After retraining the false positive data with the method determined in the two experiments, the car object class showed excellent inference performance with an AP value of 0.95 or higher after the first retraining, and by the fifth retraining, the inference performance was improved by about 1.06 times compared to the initial inference. And the person object class continued to improve its inference performance as retraining progressed, and by the 18th retraining, it showed that it could self-improve its inference performance by more than 2.3 times compared to the initial inference.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.9-18
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• 2024

The importance of active sonar systems is emerging due to the quietness of underwater targets and the increase in ambient noise due to the increase in maritime traffic. However, the low signal-to-noise ratio of the echo signal due to multipath propagation of the signal, various clutter, ambient noise and reverberation makes it difficult to identify underwater targets using active sonar. Attempts have been made to apply data-based methods such as machine learning or deep learning to improve the performance of underwater target recognition systems, but it is difficult to collect enough data for training due to the nature of sonar datasets. Methods based on mathematical modeling have been mainly used to compensate for insufficient active sonar data. However, methodologies based on mathematical modeling have limitations in accurately simulating complex underwater phenomena. Therefore, in this paper, we propose a sonar signal synthesis method based on a deep neural network. In order to apply the neural network model to the field of sonar signal synthesis, the proposed method appropriately corrects the attention-based encoder and decoder to the sonar signal, which is the main module of the Tacotron model mainly used in the field of speech synthesis. It is possible to synthesize a signal more similar to the actual signal by training the proposed model using the dataset collected by arranging a simulated target in an actual marine environment. In order to verify the performance of the proposed method, Perceptual evaluation of audio quality test was conducted and within score difference -2.3 was shown compared to actual signal in a total of four different environments. These results prove that the active sonar signal generated by the proposed method approximates the actual signal.