• Journal of the Korean Society for Heat Treatment
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• v.15 no.2
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• pp.82-92
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• 2002

In the present investigation wear behavior of the 6061AI composites reinforced with 5, 10, 20% SiC particles for dry sliding against a SM45C counterface was studied as a function of load and sliding velocity. Sliding wear tests were conducted at two loads(19.6 and 49N) and three sliding velocities(0.2, 1 and 2 m/sec) at constant sliding distance of 4000 m using pin-on-disk machine under room temperature. Presence of SiC reinforcement particles in the composites has displayed a transition from mild to severe wear at relatively higher applied load and sliding velocity compare to that of the matrix metal. As the volume fraction of SiC particles increased, the transition moved to a more severe wear conditions. Eventually, mild wear prevailed at a most severe wear conditions in this study, that was 49N load and 2 m/sec sliding velocity in 20% SiC particle/6061AI composite.

• The Journal of the Convergence on Culture Technology
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• v.5 no.2
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• pp.177-182
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• 2019

As progress of technology, Artificial Intelligence is applied in various fields of industry such as finance, production, medical treatment, service, art by changing the way they look continuously. As AI is progressive area, We have to know what kind of changing is merged in human society by AI. In this paper, through the investigations of Artificial Intelligence's concept and the way Artificial Intelligence's technology is implemented in modern industry, we studied positive effect and negative effect of AI. By this study, In conclusion, by realizing how close Artificial Intelligence had come to our life, we can prepare to seek a foothold to deal with this Artificial Intelligence.

• Journal of agriculture & life science
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• v.50 no.5
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• pp.183-188
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• 2016

This experiment was conducted to investigate the effects of artificial insemination(AI) frequency on reproductive performance of sows. A total of 48 F1 sows(Yorkshire×Landrace) were allocated to 1 of 4 treatments using completely randomized design(CRD). Four experimental treatments were AI frequency from one to four times(AI1, AI2, AI3, AI4) respectively. Estrus detection was done at approximately 09:00 and 21:00 daily by applying back pressure to females with the presence of a mature boar and the weaning to estrus interval(WEI) of all sows were 5~6 day. Sows detected in estrus were mated at 12 hour after and mating interval was 12 hour by treatments. This experiment demonstrated that the lowest farrowing rate was observed AI3 treatment. Frequency of AI did not influence on reproductive performance when WEI was 5-6 day. No significant differences were observed on litter size, born alive and litter birth weight. Consequently, decreased AI frequency did not have any detrimental effect on reproductive performance when estrus detection was adequate. Decreased AI frequency could reduce cost of production of pigs when sows showed normal reproductive performance.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.297-307
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• 2022

This study examined whether there was a difference in the attitude toward the recommended product and the effect on the choice deferral according to information sources. Experiment 1 examined the relationship between trust in information and product attitude, and between uncertainty and choice deferral according to information sources (AI chatbot vs. human). Experiment 2 examined the impact of social presence, perceived personalization, and choice deferral according to whether anthropomorphism of AI chatbots or not. The research results are as follows. First, consumers were found to have a more positive attitude toward products recommended by AI chatbots (vs. human). Second, consumers were more choice deferral whether to purchase products recommended by AI chatbots (vs. human). Third, it was found that consumers' selection of products recommended by anthropomorphic AI chatbots (vs. impersonated AI chatbots) increased. Also, the implications of this study and future research directions were discussed.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.572-580
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• 2020

Recently released AI speakers show a pattern of interacting with the user by mainly with voice and simultaneously displaying simple and formal visual feedback through status LED light. This is due to the limitations of the product characteristics of the speaker, which makes it difficult to interact variously, and even such visual feedback is not standardized for each product, and thus does not give a consistent user experience. By maximizing the visual elements that can be expressed through color and abstract movement to assist voice feedback, the product can provide the user with an extended experience that includes not only functional satisfaction but also emotional satisfaction. In this study, after analyzing the interaction methods of the existing AI speakers, we examined the theory of color communication in order to expand the visual feedback effect, and examined the meaning and expression technique of Color Field Painting, an art genre that maximizes the emotional experience by using only color. Through this, the AI speaker's visual communication function was expanded by designing a way to feedback communication status using LED light.

• Journal of Creative Information Culture
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• v.7 no.4
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• pp.265-277
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• 2021

Data is the core of AI technology. With the development of technology, AI technology is also accelerating as the amount of data increases explosively than before. However, compared to the interest in AI education, research on data education with AI is still insufficient. According to the case analysis of exsisting AI data education, there were cases of educating the process and part of data science, but it was hard to find studies related to data collection. Cause physical computing tools have a positive effect on AI education for elementary school students, data collection cases using tools were studied, but researches related to data collection were rare. Therefore, in this study, an efficient data collection method using physical tools was designed. A structural diagram of a data collection program was created using COBL S, a modular physical computing teaching tool, and examples of program screens from the service side and the user side were configured. This study has limitations in that the establishment of an AI education platform that can be used in conjunction with future program production and programs should be prioritized as a proposal in terms of design.

• Science of Emotion and Sensibility
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• v.22 no.3
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• pp.35-46
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• 2019

Artificial intelligence (AI) technology has been evolving to recognize and learn the languages, voice tones, and facial expressions of users so that they can respond to users' emotions in various contexts. Many AI-based services of particular importance in communications with users provide emotional interaction. However, research on nonverbal interaction as a means of expressing emotion in the AI system is still insufficient. We studied the effect of lighting on users' emotional interaction with an AI device, focusing on color and flickering motion. The AI device used in this study expresses emotions with six colors of light (red, yellow, green, blue, purple, and white) and with a three-level flickering effect (high, middle, and low velocity). We studied the responses of 50 men and women in their 20s and 30s to the emotions expressed by the light colors and flickering effects of the AI device. We found that each light color represented an emotion that was largely similar to the user's emotional image shown in a previous color-sensibility study. The rate of flickering of the lights produced changes in emotional arousal and balance. The change in arousal patterns produced similar intensities of all colors. On the other hand, changes in balance patterns were somewhat related to the emotional image in the previous color-sensibility study, but the colors were different. As AI systems and devices are becoming more diverse, our findings are expected to contribute to designing the users emotional with AI devices through lighting.

• Korean Journal of Cognitive Science
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• v.32 no.4
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• pp.169-191
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• 2021

With the development of artificial intelligence(AI), the jobs of many human experts are threatened, and this also applies to the legal profession. This study attempted to investigate whether AI can actually replace humans in the legal profession, especially the role of judges making final judgments. For this purpose, from the perspective of uniqueness neglect, this study was conducted to confirm the effect of involvement and the severity on acceptance of the judgment made by the AI judge (Experiment 1) and the AI jury (Experiment 2). The involvement was manipulated as if the subject who was sentenced for committing a crime was his or her family (mother, father) or stranger, and the severity was manipulated by the extent of the damage, the perception of the crime, and the number of applied crimes. In Experiment 1, the interactive effect of involvement and severity was found. Specifically, when the involvement was low, the acceptance of AI judges was higher in high severity (vs. low severity). Conversely, when the involvement was high, the acceptance of AI judges was higher in low severity (vs. high severity). The same interactions as in Experiment 1 occurred in Experiment 2. Specifically, when the involvement was low, a larger number of AI jury members were allocated in high severity (vs. low severity). On the other hand, when the involvement was high, the number of AI juries increased in low severity (vs. high severity). This study has implications in that it is the first experimental study in Korea on artificial intelligence legal judgment and that it presents the prospects for the jobs of legal experts.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.82-104
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• 2023

This study analyzes the effect of users' experiences using AI chatbot services on relationship quality and behavioral intention. For the study, a survey was conducted on users who experienced AI chatbot services, and the research hypothesis was verified by analyzing the final 299 copies of valid data. As a result of the analysis, it was confirmed that satisfaction and trust, which are the relationship quality dimensions of AI chatbot service, were formed in users through the cognitive experience, emotional experience, and relational experience. In addition, it was confirmed that satisfaction and trust have a positive effect on the intention to continue using and recommending AI chatbot services, which correspond to the level of consumers' behavioral intentions, respectively. In addition, in terms of relationship quality, it was significant in all paths of the road of behavior, but in satisfaction, the path coefficient of the road of continuous use of AI chatbot and recommended road was significantly higher than the path coefficient in trust. This study provided a theoretical foundation that the relationship with relationship quality that affects behavioral intention also affects AI chatbot services in the online environment, and it is significant in that it suggests that relationship quality is an important mediating factor in establishing long-term relationships with consumers.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.137-148
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• 2024

The purpose of this study is to determine how the use of retailtech technology affects consumers' purchase intention. Furthermore, this study aims to investigate the mediating effects of technology usefulness and ease of use on this influence relationship and whether experiential marketing moderates consumers' purchase intention. The survey was conducted from August 1, 2023 to September 30, 2023, and a total of 257 people participated in the study. For statistical analysis, hierarchical regression analysis, three-stage mediation regression analysis, and hierarchical three-stage controlled regression analysis were conducted to test the hypothesis. The results of the study are as follows. First, it was confirmed that big data-AI utilization, mobile-SNS utilization, live commerce utilization, and IoT utilization affect purchase intention in retail technology utilization. Second, technology usefulness has a mediating effect on IoT utilization, mobile-SNS utilization, and big data-AI utilization. Third, perceived ease of use of technology mediated the effects of IoT utilization, mobile-SNS utilization, live-commerce utilization, and big data-AI utilization. Fourth, escapist experience has a moderating effect on mobile SNS utilization and live commerce utilization. Fifth, esthetic experience has a moderating effect on mobile-SNS utilization and big data-AI utilization. Through this study, we hope that the domestic distribution industry will contribute to national competitiveness by securing the competitive advantage of companies by utilizing new technologies in entering the global market.