• Journal of Convergence for Information Technology
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• v.11 no.7
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• pp.31-38
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• 2021

In this paper, in order to obtain the optimization of the RNN model used for sentiment analysis, the correlation of each model was studied by observing the trend of loss and accuracy according to hyperparameter tuning. As a research method, after configuring the hidden layer with LSTM and the embedding layer that are most optimized to process sequential data, the loss and accuracy of each model were measured by tuning the unit, batch-size, and embedding size of the LSTM. As a result of the measurement, the loss was 41.9% and the accuracy was 11.4%, and the trend of the optimization model showed a consistently stable graph, confirming that the tuning of the hyperparameter had a profound effect on the model. In addition, it was confirmed that the decision of the embedding size among the three hyperparameters had the greatest influence on the model. In the future, this research will be continued, and research on an algorithm that allows the model to directly find the optimal hyperparameter will continue.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.465-472
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• 2021

In this paper, we present an approach for detection of adverse drug reactions from drug reviews to compensate limitations of the spontaneous adverse drug reactions reporting system. Considering negative reviews usually contain adverse drug reactions, sentiment analysis on drug reviews was performed and extracted negative reviews. After then, MedDRA dictionary and named entity recognition were applied to the negative reviews to detect adverse drug reactions. For the experiment, drug reviews of Celecoxib, Naproxen, and Ibuprofen from 5 drug review sites, and analyzed. Our results showed that detection of adverse drug reactions is able to compensate to limitation of under-reporting in the spontaneous adverse drugs reactions reporting system.

• Trans-
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• v.13
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• pp.141-169
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• 2022

Analysis of narrative texts has been regarded as academically and practically important, and has been made from various perspectives and methods. In this paper, the computational narrative analysis methodology from the perspective of information processing was examined. From the point of view of information processing, the creation and acceptance of narrative is a bidirectional coding process mediated by narrative text, and narrative text can be said to be a multi-layered structured code. In this paper, four methodologies that share this point of view - character network analysis, text mining and sentiment analysis, continuity analysis of event composition, and knowledge analysis of narrative agents - were examined together with cases. Through this, the mechanism and possibility of computational methodology in narrative analysis were confirmed. In conclusion, the significance and side effects of computational narrative analysis were examined, and the necessity of designing a human-computer collaboration model based on the consilience of the humanities and science/technology was discussed. Based on this model, it was argued that aesthetically creative, ethically good, politically progressive, and cognitively sophisticated narratives could be made more effectively.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.269-275
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• 2022

As artificial intelligence services targeting humans increase, social demands are increasing that artificial intelligence should also be made on an ethical basis. Following this trend, the government and businesses are preparing policies and norms related to artificial intelligence ethics. In order to establish reasonable policies and norms, the first step is to understand the public's perceptions. In this paper, social data and news comments were collected and analyzed to understand the public's perception related to artificial intelligence and ethics. Interest analysis, emotional analysis, and discourse analysis were performed and visualized on the collected datasets. As a result of the analysis, interest in "artificial intelligence ethics" and "artificial intelligence" favorability showed an inversely proportional correlation. As a result of discourse analysis, the biggest issue was "personal information leakage," and it also showed a discourse on contamination and deflection of learning data and whether computer-made artificial intelligence should be given a legal personality. This study can be used as data to grasp the public's perception when preparing artificial intelligence ethical norms and policies.

• Journal of the Korea Society of Computer and Information
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• v.16 no.6
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• pp.79-88
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• 2011

In this paper, We propose real-time sound editing and playback systems which is based on Augmented Reality. The proposed system are composed with music maker which is based on AR maker and music board. By using music marker's contents, the proposed system selects the kinds of musical instruments and pre-defined midi track and by calculating the relative location of music marker on 2-dimensional plane, we set the spatial relative parameter in midi track. For performance evaluation, we check the jitter value of in various resolutions by using CAM which supports $1600{\pm}1200$ as the maximum resolution. As a result, when we set the configuration value of CAM as $860{\pm}600$ pixels and process two frames per minute, the success ratio of recognizing music markers and jitter values are accegnable. It can be utilized in the fields of alternative cmacine which is based on music and also be utilized in the educational aspects because child or elderly who don't know enough musical theory can easily handle it.

• Design Convergence Study
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• v.15 no.6
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• pp.229-241
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• 2016

In generative design computer automatically and quickly generates many alternative design solutions, and the computer algorithms which perform the design tasks are important. The main purpose of this study is to propose a computer algorithm which generates three-dimensional shapes from a two-dimensional digital image such as a photograph or a painting. The base geometry of the final shape is a cylinder or sphere. A surface of the cylinder or sphere is deformed depending on the used image. The proposed algorithm was implemented as a computer program, and the program tested with several famous paintings. The algorithm and results presented in this study implicate the possibilities of the generative design which generates three-dimensional shapes from two-dimensional images. It is necessary to find and measure the values of the generated shape, and it will be a future research to find the relations of emotional and cognitive aspects between the input images and the generated shapes. Those studies are expected to expand the possibilities of generative design.

• Science of Emotion and Sensibility
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• v.23 no.2
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• pp.23-34
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• 2020

Loneliness is an unpleasant experience due to the human need for social connection. Anthropomorphism is the attribution of human traits, emotions, and intentions to nonhuman entities. The inverse process of anthropomorphism is dehumanization in which individuals treat humans like animals or objects. Two studies were conducted to investigate whether relationships exist among loneliness, anthropomorphism, and dehumanization. In Study 1, loneliness was measured via self-reports, and an anthropomorphism task was introduced to examine the extent to which subjective experiences of loneliness related to the tendency to describe nonhuman agents with humanlike characteristics. According to the results, lonelier participants attributed more humanlike capacities to computers and cats. Study 2 examined whether significant differences emerged in anthropomorphism and dehumanization between the experimental condition of loneliness and the control condition. After having been induced to the emotion of loneliness using an experimental writing task, the participants tended to perceive nonhuman agents to be more humanlike in the condition of loneliness than in the control condition. Moreover, there was a stronger tendency of dehumanization toward other humans in the condition of loneliness than in the control condition. There was also higher levels of negatively biased perceptions of neighborhood characteristics. This scenario implies that anthropomorphism is related to sociality motivation, which is the need for social connection through establishing bonds with nonhumans, and may result in the dehumanization and emotional experiences of other humans.

• Science of Emotion and Sensibility
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• v.16 no.1
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• pp.95-106
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• 2013

The study compares accuracies between humans and computer algorithms in the discrimination of spontaneous smiles from posed smiles. For this purpose, subjects performed two tasks, one was judgment with single pictures and the other was judgment with pair comparison. At the task of judgment with single pictures, in which pictures of smiling facial expression were presented one by one, subjects were required to judge whether smiles in the pictures were spontaneous or posed. In the task for judgment with pair comparison, in which two kinds of smiles from one person were presented simultaneously, subjects were to select spontaneous smile. To calculate the discrimination algorithm accuracy, 8 kinds of facial features were used. To calculate the discriminant function, stepwise linear discriminant analysis (SLDA) was performed by using approximately 50 % of pictures, and the rest of pictures were classified by using the calculated discriminant function. In the task of single pictures, the accuracy rate of SLDA was higher than that of humans. In the analysis of accuracy on pair comparison, the accuracy rate of SLDA was also higher than that of humans. Among the 20 subjects, none of them showed the above accuracy rate of SLDA. The facial feature contributed to SLDA effectively was angle of inner eye corner, which was the degree of the openness of the eyes. According to Ekman's FACS system, this feature corresponds to AU 6. The reason why the humans had low accuracy while classifying two kinds of smiles, it appears that they didn't use the information coming from the eyes enough.

• Science of Emotion and Sensibility
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• v.14 no.1
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• pp.101-116
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• 2011

Current researches on emotion detection classify emotions by using the information from facial, vocal, and bodily expressions, or physiological responses. This study was to review three representative emotion recognition methods, which were based on psychological theory of emotion. Firstly, literature review on the emotion recognition methods based on facial expressions was done. These studies were supported by Darwin's theory. Secondly, review on the emotion recognition methods based on changes in physiology was conducted. These researches were relied on James' theory. Lastly, a review on the emotion recognition was conducted on the basis of multimodality(i.e., combination of signals from face, dialogue, posture, or peripheral nervous system). These studies were supported by both Darwin's and James' theories. In each part, research findings was examined as well as theoretical backgrounds which each method was relied on. This review proposed a need for an integrated model of emotion recognition methods to evolve the way of emotion recognition. The integrated model suggests that emotion recognition methods are needed to include other physiological signals such as brain responses or face temperature. Also, the integrated model proposed that emotion recognition methods are needed to be based on multidimensional model and take consideration of cognitive appraisal factors during emotional experience.

• Science of Emotion and Sensibility
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• v.25 no.3
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• pp.15-32
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• 2022

This study seeks to clarify the mechanisms of anthropomorphism and positive user experience. This study adopts the "computers are social actors" (CASA) paradigm to verify the causal relationship between social response and anthropomorphism and correctly explicate this paradigm. The intimacy-forming and anthropomorphizing effects of deep self-disclosure in interpersonal relationships were replicated in relationships between humans and conversational agents to induce both social response and anthropomorphism. Then, the mediating effect of intimacy on the anthropomorphizing effect of deep self-disclosure was explored with psychological models that revealed the causal relationships between social connections, including intimacy and anthropomorphism. Furthermore, we explored how intimacy and anthropomorphism trigger positive user experiences. The results demonstrated that the deeper the self-disclosure depth was, the more intimate and humanly the agent was perceived and the more positive the user experience was. In addition, the effect of self-disclosure depth on anthropomorphism and positive user experience was completely mediated by intimacy. This means that when using a computer with interpersonal characteristics, people anthropomorphize it and have a positive experience because people react socially to objects with social cues. This study bridges the gap between the CASA paradigm and anthropomorphism research, suggesting the possibility of psychological explanations for the principle of human-computer interactions. In addition, it explicates the mechanism of anthropomorphism and positive user experience, emphasizing the importance of social response-that is, intimacy.