• The Journal of the Convergence on Culture Technology
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• v.5 no.1
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• pp.13-20
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• 2019

This study aims to study the codes that can code the Sijo's emotional codes into AI and use them in literature therapy. In this study, we conducted emotional coding of the Sijo Crying Cuckoo at the Empty Mountain. As a result, the Emotion Codon was able to indicate the state of sadness catharsis. This implanting of the Sijo's emotional codes into Emotion Codon is like implanting human emotions into AI. If the basic emotion codes are implanted in the Emotion Codon and induced of AI's self-learning, We think AI can combine various emotions that occur in the human body. AI can then replace human emotions, which can be useful in treating of human emotions. It is believed that continuing this study will induce human emotions to heal the mind and spirit.

• International Journal of Advanced Culture Technology
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• v.7 no.1
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• pp.199-208
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• 2019

Today, mankind is falling in serious stress. So there are various way that heal men as human psychology, philosophy, medical science etc. And in recent years, interest in literature therapy has been focused to heal the human sense of spirit. In the future, we will be able to treat our spirit sense with AI Emotion. The treatment process can be induced by the system of emotion coding which AI Emotion deliver Emotion signals to Human body. For this study, we used the Ahn Min-young's Sijo. The reason is that his Sijo is useful this study of the Emotion Coding. As the result, Ahn Min-young's emotion coding created the codes as if amino acid codes. We must continue this research. Then our literature therapy could grow and contribute to human well-being.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.57-66
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• 2023

In this study, we propose a novel research framework for the recommendation system that can estimate the user's emotional state and reflect it in the recommendation process by applying deep learning techniques and emotion AI (artificial intelligence). To this end, we build an emotion classification model that classifies each of the seven emotions of angry, disgust, fear, happy, sad, surprise, and neutral, respectively, and propose a model that can reflect this result in the recommendation process. However, in the general emotion classification data, the difference in distribution ratio between each label is large, so it may be difficult to expect generalized classification results. In this study, since the number of emotion data such as disgust in emotion image data is often insufficient, correction is made through augmentation. Lastly, we propose a method to reflect the emotion prediction model based on data through image augmentation in the recommendation systems.

• Science of Emotion and Sensibility
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• v.24 no.2
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• pp.75-80
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• 2021

Do happy applicants achieve more? Although it is well established that happiness predicts desirable work-related outcomes, previous findings were primarily obtained in social settings. In this study, we extended the scope of the "happiness premium" effect to the artificial intelligence (AI) context. Specifically, we examined whether an applicant's happiness signal captured using an AI system effectively predicts his/her objective performance. Data from 3,609 job applicants showed that verbally expressed happiness (frequency of positive words) during an AI interview predicts cognitive task scores, and this tendency was more pronounced among women than men. However, facially expressed happiness (frequency of smiling) recorded using AI could not predict the performance. Thus, when AI is involved in a hiring process, verbal rather than the facial cues of happiness provide a more valid marker for applicants' hiring chances.

• International Journal of Advanced Culture Technology
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• v.7 no.2
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• pp.188-194
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• 2019

Always, emotion is mutant. This is principle of literary treatment. In the literature, sadness is not sadness, and 'loving emotion' is not 'loving emotion.' Despite loving of our, loving is sadness. Also loving is to cry. This crying becomes love. This study is to show the mutant emotion which is to be able to code Deep Learning AI. We explored the Sijo "Streams that cried last night", because this Sijo was useful to study mutant emotion. The result was that this Sijo was coding the mutant emotion. Almost continuously, the sadness codes were spawning and concentrating. So this Sijo was making the emotion of love with the sadness. If this study is continued, It is believed that our lives will be much happier. And the method of literary therapy will be able to more upgrade.

• Science of Emotion and Sensibility
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• v.26 no.4
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• pp.115-124
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• 2023

This study explores the intersection of literary studies and artificial intelligence (AI), focusing on the common theme of human emotions to foster complementary advancements in both fields. By adopting a comparative perspective, the paper investigates emotion as a shared focal point, analyzing various emotion-related concepts from both literary and AI perspectives. Despite the scarcity of research on the fusion of AI and literary studies, this study pioneers an interdisciplinary approach within the humanities, anticipating future developments in AI. It proposes that literary sensibility can contribute to AI by formalizing subjective literary emotions, thereby enhancing AI's understanding of complex human emotions. This paper's methodology involves the terminology-centered extraction of emotions, aiming to blend subjective imagination with objective technology. This fusion is expected to not only deepen AI's comprehension of human complexities but also broaden literary research by rapidly analyzing diverse human data. The study emphasizes the need for a collaborative dialogue between literature and engineering, recognizing each field's limitations while pursuing a convergent enhancement that transcends these boundaries.

• The Journal of the Convergence on Culture Technology
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• v.5 no.2
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• pp.299-303
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• 2019

This study is one of the preparatory tasks for this researcher to do Emotion Coding on AI. This time, we're doing an Emotion Coding for Sijo "Blue Mountain is My Meaning" by Hwang Jin-yi. Huang Jin-yi is doing Emotion Coding on Blue Mountain and Green Stream in this Sijo. These Emotions code, as seen in Emotion Codon, as in UUU. This phenomenon can be described in the form in which this researcher hypothesized. In other words, this Emotion Coding acts as a catalyst for the formation of an amino acid called phenylalanine. If we continue this research, it is thought that the function of literature, which is more healing, will be utilized in the future of mankind.

• Smart Media Journal
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• v.13 no.7
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• pp.18-26
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• 2024

One of the newest trends in AI is emotion recognition utilizing keystroke dynamics, which leverages biometric data to identify users and assess emotional states. This work offers a comparison of four datasets that are frequently used to research keystroke dynamics: BB-MAS, Buffalo, Clarkson II, and CMU. The datasets contain different types of data, both behavioral and physiological biometric data that was gathered in a range of environments, from controlled labs to real work environments. Considering the benefits and drawbacks of each dataset, paying particular attention to how well it can be used for tasks like emotion recognition and behavioral analysis. Our findings demonstrate how user attributes, task circumstances, and ambient elements affect typing behavior. This comparative analysis aims to guide future research and development of applications for emotion detection and biometrics, emphasizing the importance of collecting diverse data and the possibility of integrating keystroke dynamics with other biometric measurements.

• Science of Emotion and Sensibility
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• v.27 no.2
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• pp.91-104
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• 2024

The increase in the use of artificial intelligence (AI) in the workplace has introduced changes to traditional working environments. However, these are changes not only to employee productivity but also to how employees feel and think about their work. Based on prior research that has suggested connections between employees' perceptions of AI and their emotions and thoughts at work, the present study tested a moderated mediation model in which the perception of AI opportunity is indirectly related to job insecurity via employee hope, with tenure as a moderator. Data obtained from 290 Korean full-time employees illustrated that the perception of AI opportunity was negatively related to job insecurity through hope acting as a mediator. In addition, this indirect relationship was found to be dependent on the moderating role of tenure. Specifically, at lower levels of tenure, the aforementioned indirect relationship was statistically significant, but at higher levels of tenure, this indirect relationship was no longer found to be statistically significant. The implications, limitations, and future research directions of this study are discussed.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.95-100
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• 2019

In this paper, autonomous vehicles of service with existing vehicle accident for the prevention of the vehicle communication technology, self-driving techniques, brakes automatic control technology, artificial intelligence technologies such as well and developed the vehicle accident this occur to death or has been techniques, can prepare various safety cases intended to minimize the injury. In this paper, it is a study to secure safety in autonomous vehicles. This is determined according to spatial factors such as chip signals for general low-power short-range wireless communication and micro road AI. On the other hand, in this paper, the safety of boarding is improved by checking the signal from the electronic chip, up to "recognition of the emotion from residence time in the sensing area" to the biological electronic chip. As a result of demonstrating the reliability of the world countries the world, inducing safety autonomous system of all passengers in terms of safety. Unmanned autonomous vehicle riding and commercialization will lead to AI systems and biochips (Verification), linked IoT on the road in the near future, and the safety technology reliability of the world will be highlighted.