• The Research Journal of the Costume Culture
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• v.31 no.5
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• pp.651-668
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• 2023

This study aims to help companies with efficient investment and marketing strategies by empirically verifying the impact on satisfaction and purchase intention for artificial intelligence-based digital technology supported shopping assistants introduced in e-commerce. Frequency, factor, SEM, and multiple group analysises were conducted using SPSS 26.0 and Amos 26.0. As a result, first, motivated consumer innovativeness elements of AI shopping assistant were derived into a total of four categories: functional, hedonic, rational, and reliable. Second, in the order of hedonic and rational, satisfaction with the AI shopping assistant was significantly affected, and in the order of rational and functional, purchase intention was significantly affected. The satisfaction with the AI shopping assistant did not affect the purchase intention. Third, in the case of hedonic, the AI-preferred group had a more significant effect on satisfaction than the human-preferred group, and in the case of rational, there was no difference by group in purchase intention. Thus, it was found that consumers prefer AI shopping helpers for e-commerce because they can shop reasonably and are functionally convenient. Therefore, when introducing AI shopping assistants, it is essential to include content that can compare and analyze fundamental information, such as product prices, as well as search functions and payment system compatibility that facilitate shopping.

• Journal of the Korean Ceramic Society
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• v.35 no.7
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• pp.726-732
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• 1998

• Journal of Digital Convergence
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• v.14 no.4
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• pp.139-147
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• 2016

The purpose of this study is to identify the relationships between AI education characteristics and psychological capital, psychological capital and flow, AI characteristics and flow through meditating effect of psychological capital in the digital convergence society. There are three AI characteristics: correctness, usefulness, easy of use. This empirical study was examined by 282 questionnaires to the three universities that teach accounting information system. It was performed by three-step method of the hierarchical regression analysis for the multiple regression analysis and parameter using the SPSS 22.0. The results and implications by analysis are as follows. First, AI characteristics and psychological capital have statistically significant positive influence. From AI attribute, correctness was established as the most important element. Second, psychological capital positively(+) influences flow. It allowed for the developed in flow. Third, psychological capital was shown as the major meditative variable between AI characteristics and flow. Through these, this paper suggests to reinforce self-efficacy, hope, resilience, optimism.

• Journal of Information Technology Services
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• v.20 no.5
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• pp.189-207
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• 2021

Voice interaction combined with artificial intelligence is poised to revolutionize human-computer interactions with the advent of virtual assistants. This paper is analyzing interactive elements of AI-based voice recognition services such as sympathy, assurance, intimacy, and trust on intention to use. The questionnaire was carried out for 284 smartphone/smart TV users in Korea. The collected data was analyzed by structural equation model analysis and bootstrapping. The key results are as follows. First, AI-based voice recognition service characteristics such as sympathy, assurance, intimacy, and trust have positive effects on interactivity with the AI-based voice recognition service. Second, the interactivity with the AI-based voice recognition service has positive effects on intention to use. Third, AI-based voice recognition service characteristics such as interactional enjoyment and intimacy have directly positive effects on intention to use. Fourth, AI-based voice recognition service characteristics such as sympathy, assurance, intimacy and trust have indirectly positive effects on intention to use the AI-based voice recognition service by mediating the effect of the interactivity with the AI-based voice recognition service. It is meaningful to investigate factors affecting the interactivity and intention to use voice recognition assistants. It has practical and academic implications.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.203-214
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• 2024

This study seeks to provide implications for domestic-related policies through exploratory analysis research to support AI-based policy decision-making. The following should be considered when establishing an AI-based decision-making model in Korea. First, we need to understand the impact that the use of AI will have on policy and the service sector. The positive and negative impacts of AI use need to be better understood, guided by a public value perspective, and take into account the existence of different levels of governance and interests across public policy and service sectors. Second, reliability is essential for implementing innovative AI systems. In most organizations today, comprehensive AI model frameworks to enable and operationalize trust, accountability, and transparency are often insufficient or absent, with limited access to effective guidance, key practices, or government regulations. Third, the AI system is accountable. The OECD AI Principles set out five value-based principles for responsible management of trustworthy AI: inclusive growth, sustainable development and wellbeing, human-centered values and fairness values and fairness, transparency and explainability, robustness, security and safety, and accountability. Based on this, we need to build an AI-based decision-making system in Korea, and efforts should be made to build a system that can support policies by reflecting this. The limiting factor of this study is that it is an exploratory study of existing research data, and we would like to suggest future research plans by collecting opinions from experts in related fields. The expected effect of this study is analytical research on artificial intelligence-based decision-making systems, which will contribute to policy establishment and research in related fields.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.4
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• pp.743-759
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• 2023

Collaboration between AI and fashion designers is becoming essential. Thus, this study explored (1) 321 consumer responses to fashion designers, comparing their capabilities and product quality across different designer types, (2) the relationship between designer capabilities and perceived product quality, and (3) the moderating role of AI knowledge in the effect of capabilities on perceived product quality. Data were analyzed using EFA, ANOVA, regression, and moderation analysis. The results indicated that subjects perceived human designers as having higher capabilities and perceived product quality than AI designers. All subjects' perceived creativity and empathy significantly impacted the perceived functionality, aesthetics, and symbolism-sociality of clothing. Additionally, the perceived creativity of AI and human+AI designers, and the perceived empathy of human and human+AI designers, significantly influenced the perceived functionality and symbolism-sociality, but the perceived creativity of human designers and empathy of AI designers did not directly impact perceived functionality and symbolism-sociality. Moreover, perceptions of the designers' capabilities significantly aesthetics in all subjects. Furthermore, low levels of perceived consumer AI knowledge enhanced the positive impact of perceived human+AI designers' creativity and empathy on perceived functionality and aesthetics. The study suggests that fashion companies should refrain from revealing AI designers at this time.

• Herbal Formula Science
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• v.32 no.1
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• pp.99-109
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• 2024

Objectives : In this study, we investigated the cytoprotective effect of Eriobotrya japonica L. (EJ) extract against Arachidonic acid (AA)+iron-induced oxidative stress. Methods : To confirm the cytoprotective effect of EJ against AA+iron-induced oxidative stress in HepG2 cells, it was evaluated by MTT assay, immunoblot anaylsis, and Calcein-AM/propidium iodide (PI) staining. Additionally, the mechanism of action of the cytoprotective effect was evaluated through molecular mechanisms. Results : EJ (100 ㎍/mL) inhibited Arachidonic acid (AA)+iron-induced cell death in a concentration-dependent manner. It also inhibited AA+iron-induced mitochondrial dysfunction and ROS production. EJ activated the LKB1-AMPK signaling pathway. Conclusions : In conclusion, EJ has the ability to protect liver cells from oxidative stress, indicating that it is related to AMPK-LKB1 signaling pathways.

• Korean Journal of Agricultural Science
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• v.50 no.2
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• pp.207-218
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• 2023

Duck farming restriction refers to a program in which duck farms suspend their operations for a certain period at times when the risk of avian influenza (AI) is high and receive compensation from the Korean government. This study analyzed the effect of this duck farming restriction on the incidence of AI using data on regional AI incidence rates, the program participation rate, and characteristics of poultry farming in 2016 (before the implementation of the restriction), as well as data from 2020 and 2021 (when new AI outbreaks occurred). In this study, the treatment group was divided into five subgroups according to the policy participation rate and a difference-in-difference (DID) estimation was conducted using certain covariates, in this case the average number of ducks raised, the land area, the number of high-susceptibility farms, the number of low-susceptibility farms, the average number of farms within a 3 km radius, the average distance to the nearest farm, and a year dummy. The results showed that when more than 30% of all duck farms in a region participated in the farming restriction, it had a statistically significant effect on the incidence of AI. Specifically, when more than 30, 40, 50, and 60% of all duck farms participated in the farming restriction, the AI incidence rate decreased by 0.7184, 1.0025, 1.5844, and 1.5843%p, respectively.

• Journal of Embryo Transfer
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• v.28 no.2
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• pp.87-93
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• 2013

The efficiency of artificial insemination (AI) for horses remains unsatisfactory. It is mainly because each process of AI causes a detrimental effect on semen quality. To sustain quality of semen properly, several factors including libido of stallions and sperm damage during sperm processing and preservation should be considered. Stallions with decent libido produce a high ratio of sperm to seminal plasma in their ejaculates, which is the ideal semen composition for maintaining sperm quality. Thus, to maximize the fertility rate upon AI, stallions should be appropriately managed to enhance their libido. Seminal plasma should have a positive effect on horse fertility in the case of natural breeding, whereas the effects of seminal plasma on both sperm viability and quality in the context of AI remain controversial. Centrifugation of semen is performed during semen processing to remove seminal plasma and to isolate fine quality sperm from semen. However, the centrifugation process can also result in sperm loss and damage. To solve this problem, several different centrifugation techniques such as Cushion Fluid along with dual and single Androcoll-E$^{TM}$ were developed to minimize loss of sperm and to damage at the bottom of the pellet. Most recently, a new technique without centrifugation was developed with the purpose of separating sperm from semen. AI techniques have been advanced to deliver sperm to optimal region of female reproductive tract at perfect timing. Recombinant equine luteinizing hormone (reLH) and low dose insemination techniques have been developed to maximize both fertility rate and the efficiency of AI. Horse breeders should consider that the entire AI procedure should be optimized for each stallion due to variation in individual horses for a uniformed AI protocol.

• Journal of radiological science and technology
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• v.46 no.4
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• pp.303-313
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• 2023

This study aimed to investigate the relevance of cardiovascular disease risk factors AI and AIP, divided into three groups, among 300 individuals who underwent health checkups at the hospital. Various variables such as Age, Sex, BMI, WC, TC, TG, HDL-C, LDL-C, FBS, HbA1C, SBP, DBP, HR, AI (TC/HDL-C), and AIP (log(TG/HDL-C)) were analyzed using statistical methods including frequency analysis, cross-tabulation, one-way ANOVA, Pearson's correlation analysis, and multiple linear regression analysis. The cross-analysis based on cardiovascular disease risk criteria revealed that men and individuals in their 50s had higher cardiovascular disease risk based on AI and AIP. Significant differences were observed in TG, TC, HDL-C, LDL-C, SBP, DBP, AI (TC/HDL-C), and AIP (log(TG/HDL-C)) according to AI criteria. For the AIP criteria, TG, TC, HDL-C, FBS, HbA1C, HR, AI (TC/HDL-C), and AIP (log(TG/HDL-C)) were identified as cardiovascular disease risk factors. FBS and HbA1c showed the highest positive correlation In the correlation analysis, followed by TC and LDL-C. The lowest positive correlation was observed between LDL-C and DBP. In terms of negative correlation, HDL-C and AI had the highest negative correlation, while LDL-C and TG showed the lowest negative correlation. Multiple regression analysis indicated that the AI and AIP risk criteria had explanatory powers of 73.6% and 72.5%, respectively. HDL-C had the greatest negative effect on the AI risk criterion, while TG had the most significant influence on the AIP risk criterion. In conclusion, while other serological variables are important, managing HDL-C and TG levels may help reduce the risk of cardiovascular disease.