• Journal of Life Science
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• v.31 no.6
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• pp.603-608
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• 2021

The purpose of this perspective research is to discuss the potential role of exercise-interventions in COVID-19, terms of prevention and prognosis in the periods of the COVID-19 vaccine. SARCO-CoV-2. COVID-19 was detected as a new virus causing severe cardiovascular and respiratory complications. It emerged as a global public health emergency and national pandemic. It caused more than 1 million deaths in the first 6 months of the pandemic and resulted in huge social and economic fluctuations internationally. Unprecedented stressful situations, such as COVID-19 blue and COVID-19 red impact on many health problems. In healthy individuals, COVID-19 infection may induced no symptoms (i.e., asymptomatic), whereas others may experience flu-like symptoms, such as ARDS, pneumonia, and death. Poor health status, such as obesity and cardiovascular and respiratory complications, are high risk factors for COVID-19 prevention, occurrence, and prognosis. Several COVID-19 vaccines are currently in human trials. However, the efficacy and safety of COVID-19 vaccines, including potential side effects, such as anaphylaxis (a life-threatening allergic reaction) and rare blood clots, still need to be investigated. On the basis of direct and indirect evidence, it seems that regular and moderate physical exercise can be recommended as a nonpharmacological, efficient, and safe way to cope with COVID-19. Physical inactivity and metabolic abnormalities are directly associated with reduced immune responses, including reduced innate, CMI, and AMI responses. Due to prolonged viral shedding, quarantine in inactive, obese and disease people should likely be longer than physical active people. Multicomponent and systemic exercise should be considered for the obese, disease, and elderly people. More mechanism research is needed in this area.

• Korean Journal of Forensic Psychology
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• v.13 no.1
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• pp.1-22
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• 2022

This study tested the effect of the verdict category of lay-participation trial in Korea on the legal decision of layperson and the role of representation of 'innocent' in the process. Representation of 'innocent' refers to a psychological threshold for deciding someone's innocence (no fault or sin) in a general sense. The functions as a threshold for a legal decision of 'beyond a reasonable doubt (BRD)' and the individual threshold (IT), regarded as a standard for judgment of guilt established by law and an estimate of an individual's threshold, respectively, were compared. This study used a 2×2 complete factorial design in which the verdict category (guilty/innocent vs. guilty/not guilty) and the defendant's likelihood of guilt (low vs. high) were manipulated. Data from 137 lay-people who voluntarily participated in the online experiment was analyzed. The experiment's procedure was in the order of measuring 'representation of innocent' and the likelihood of guilt of an accused, presenting one of four trial vignettes, and obtaining legal decisions (verdict confidence and estimation of the likelihood of guilt for the defendant). As a result, it was found that the verdict category did not significantly affect the legal decision of layperson. However, the guilty verdict rate of the 'guilty/innocent' condition tended to be higher than those of the 'guilty/not guilty' condition. The layperson's representation of 'innocent' and the verdict category had an interaction effect on the difference between BRD and IT (threshold change) at the significance level of .1. In the 'guilty/innocent' condition, the threshold change varying with layperson's representation of 'innocent' was larger than in the 'guilty/not guilty' condition. In comparing the function of BRD and IT, IT significantly predicted the lay person's legal decision at the significance level of .1 by interacting with the likelihood of guilt for the defendant. Therefore, it could be said that IT was a better threshold estimator than BRD. The implication of this study is that it provided experimental evidence for the effect of the verdict category of lay-participation trial in Korea, which is a problem often raised among lawyers, and suggested logical reasoning and empirical grounds for the psychological mechanism of the possible effect.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.165-175
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• 2023

In venture creation research, studying 'entrepreneurial leadership' is important for uncovering and comprehending the underlying causal process in innovative behavior performance. Although previous studies provide that entrepreneurial leadership enhances followers' innovative behavior, there is few research on entrepreneurial leadership and followers' characteristics interaction. The present study's focus is paradoxical effects of entrepreneurial leadership on self-efficacy and innovative behavior. On the basis of individual regulatory focus, this study suggests that interaction effects of entrepreneurial leadership and followers' regulatory focus differed in promotion view and prevention view followers' innovative behavior. To strengthen the casual mechanism, this study conducted in priming experiment method using employees in SMEs. This study used a 2(entrepreneurial leadership vs. control) x 2 (regulatory focus: promotion vs. prevention) between-participants design. The results of this study provide that (1) Individuals in promotion focus especially benefited from entrepreneurial leadership in terms of its effect on their self-efficacy and innovative behavior; (2) whereas entrepreneurial leadership was negatively related to self-efficacy and innovative behavior of followers' prevention focus. In sum, results of the present study supporting evidence for hypotheses, combined effect of entrepreneurial leadership and regulatory focus on innovative behavior through self-efficacy. Experimental results confirmed hypotheses of this study, revealing that promotion focus show more innovative behavior than prevention focus when their leaders' leadership style is entrepreneurial leadership. Also, the paradoxical effect of entrepreneurial leadership and regulatory focus of followers on innovative behavior was mediated by followers' self-efficacy. This study helps explain how leaders' entrepreneurial leadership boost followers' innovative behavior, particularly for those employees who have promotion focus. The current study contributes to the theory of entrepreneurial leadership and regulatory focus and innovation literature. Findings of this study shed light on the organizational processes that shape innovative behavior in venture/startup corporations and provide contributions for venture business field.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.1
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• pp.59-78
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• 2024

In tunnel construction, the stability is evaluated by the settlement of adjacent structures and ground, but the shear strain of the ground is the main factor that determines the failure mechanism of the ground due to the tunnel excavation and the change of the operating load, and can be used to review the stability of the tunnel excavation and to calculate the reinforcement area. In this study, a twin tunnel excavation was simulated on a soft ground in an urban area through a laboratory model test to analyze the behavior of the twin tunnel excavation on the adjacent pile grouped foundation and adjacent ground. Both the displacement and the shear strain of ground were obtained using a close-range photogrammetry during laboratory model test. In addition, two-dimensional finite element numerical analysis was performed based on the model test. The results of a back-analysis showed that the maximum shear strain rate tends to decrease as the horizontal distance between the pillars of the twin tunnel and the vertical distance between the toe of the pile group and the crown of the tunnel were decreased. The impact of the second tunnel on the first tunnel and pile group was decreased as the horizontal distance between the pillars of the twin tunnel was increased. In addition, the vertical distance between the toe of the pile group and the crown of the tunnel had a relatively greater impact on the shear strain results than the horizontal distance of the pillars between the twin tunnels. According to the results of the close-range photogrammetry and numerical analysis, the settlement of adjacent pile group and adjacent ground was measured within the design criteria, but the shear strain of the ground was judged to be outside the range of small strain in all cases and required reinforcement.

• Journal of Korea Water Resources Association
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• v.57 no.7
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• pp.437-449
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• 2024

Rainfall-runoff prediction studies using deep learning while considering catchment attributes have been gaining attention. In this study, we selected two models: the Transformer model, which is suitable for large-scale data training through the self-attention mechanism, and the LSTM-based multi-state-vector sequence-to-sequence (LSTM-MSV-S2S) model with an encoder-decoder structure. These models were constructed to incorporate catchment attributes and predict the inflow of 10 multi-purpose dam watersheds in South Korea. The experimental design consisted of three training methods: Single-basin Training (ST), Pretraining (PT), and Pretraining-Finetuning (PT-FT). The input data for the models included 10 selected watershed attributes along with meteorological data. The inflow prediction performance was compared based on the training methods. The results showed that the Transformer model outperformed the LSTM-MSV-S2S model when using the PT and PT-FT methods, with the PT-FT method yielding the highest performance. The LSTM-MSV-S2S model showed better performance than the Transformer when using the ST method; however, it showed lower performance when using the PT and PT-FT methods. Additionally, the embedding layer activation vectors and raw catchment attributes were used to cluster watersheds and analyze whether the models learned the similarities between them. The Transformer model demonstrated improved performance among watersheds with similar activation vectors, proving that utilizing information from other pre-trained watersheds enhances the prediction performance. This study compared the suitable models and training methods for each multi-purpose dam and highlighted the necessity of constructing deep learning models using PT and PT-FT methods for domestic watersheds. Furthermore, the results confirmed that the Transformer model outperforms the LSTM-MSV-S2S model when applying PT and PT-FT methods.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.227-252
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• 2018

The evolution of instant communication has mirrored the development of the Internet and messenger applications are among the most representative manifestations of instant communication technologies. In messenger applications, senders use emoticons to supplement the emotions conveyed in the text of their messages. The fact that communication via messenger applications is not face-to-face makes it difficult for senders to communicate their emotions to message recipients. Emoticons have long been used as symbols that indicate the moods of speakers. However, at present, emoticon-use is evolving into a means of conveying the psychological states of consumers who want to express individual characteristics and personality quirks while communicating their emotions to others. The fact that companies like KakaoTalk, Line, Apple, etc. have begun conducting emoticon business and sales of related content are expected to gradually increase testifies to the significance of this phenomenon. Nevertheless, despite the development of emoticons themselves and the growth of the emoticon market, no suitable emoticon recommendation system has yet been developed. Even KakaoTalk, a messenger application that commands more than 90% of domestic market share in South Korea, just grouped in to popularity, most recent, or brief category. This means consumers face the inconvenience of constantly scrolling around to locate the emoticons they want. The creation of an emoticon recommendation system would improve consumer convenience and satisfaction and increase the sales revenue of companies the sell emoticons. To recommend appropriate emoticons, it is necessary to quantify the emotions that the consumer sees and emotions. Such quantification will enable us to analyze the characteristics and emotions felt by consumers who used similar emoticons, which, in turn, will facilitate our emoticon recommendations for consumers. One way to quantify emoticons use is metadata-ization. Metadata-ization is a means of structuring or organizing unstructured and semi-structured data to extract meaning. By structuring unstructured emoticon data through metadata-ization, we can easily classify emoticons based on the emotions consumers want to express. To determine emoticons' precise emotions, we had to consider sub-detail expressions-not only the seven common emotional adjectives but also the metaphorical expressions that appear only in South Korean proved by previous studies related to emotion focusing on the emoticon's characteristics. We therefore collected the sub-detail expressions of emotion based on the "Shape", "Color" and "Adumbration". Moreover, to design a highly accurate recommendation system, we considered both emotion-technical indexes and emoticon-emotional indexes. We then identified 14 features of emoticon-technical indexes and selected 36 emotional adjectives. The 36 emotional adjectives consisted of contrasting adjectives, which we reduced to 18, and we measured the 18 emotional adjectives using 40 emoticon sets randomly selected from the top-ranked emoticons in the KakaoTalk shop. We surveyed 277 consumers in their mid-twenties who had experience purchasing emoticons; we recruited them online and asked them to evaluate five different emoticon sets. After data acquisition, we conducted a factor analysis of emoticon-emotional factors. We extracted four factors that we named "Comic", Softness", "Modernity" and "Transparency". We analyzed both the relationship between indexes and consumer attitude and the relationship between emoticon-technical indexes and emoticon-emotional factors. Through this process, we confirmed that the emoticon-technical indexes did not directly affect consumer attitudes but had a mediating effect on consumer attitudes through emoticon-emotional factors. The results of the analysis revealed the mechanism consumers use to evaluate emoticons; the results also showed that consumers' emoticon-technical indexes affected emoticon-emotional factors and that the emoticon-emotional factors affected consumer satisfaction. We therefore designed the emoticon recommendation system using only four emoticon-emotional factors; we created a recommendation method to calculate the Euclidean distance from each factors' emotion. In an attempt to increase the accuracy of the emoticon recommendation system, we compared the emotional patterns of selected emoticons with the recommended emoticons. The emotional patterns corresponded in principle. We verified the emoticon recommendation system by testing prediction accuracy; the predictions were 81.02% accurate in the first result, 76.64% accurate in the second, and 81.63% accurate in the third. This study developed a methodology that can be used in various fields academically and practically. We expect that the novel emoticon recommendation system we designed will increase emoticon sales for companies who conduct business in this domain and make consumer experiences more convenient. In addition, this study served as an important first step in the development of an intelligent emoticon recommendation system. The emotional factors proposed in this study could be collected in an emotional library that could serve as an emotion index for evaluation when new emoticons are released. Moreover, by combining the accumulated emotional library with company sales data, sales information, and consumer data, companies could develop hybrid recommendation systems that would bolster convenience for consumers and serve as intellectual assets that companies could strategically deploy.