• Nutritional Sciences
• /
• v.7 no.4
• /
• pp.241-246
• /
• 2004

This study investigated the influence of weight perception on weight management strategies including diet and exercise in Korean female adolescents. Junior (J) and senior (S) high school girls were divided in two groups; those who had $\leq$100% (BI) and > 100% (AI) of ideal weight (J-BI, n=376, 14.8 yr, 46.1 kg; J-AI, 11=128, 15.0 yr, 57.4 kg; S-BI, n=325, 17.4 yr, 50.1 kg; and S-AI, n=133, 17.5 yr, 58.2 kg, mean values). Questionnaires to assess weight perception, desire to lose weight, body image, eating behavior, weight control strategies and physical activity (PPA) were administered J-AI(9.4 kg) and S-AI(9.8 kg) desired to lose weight more than J-BI(2.5 kg) and S-BI(3.6 kg), respectively (p < 0.001). 85% of J-AI and 93% of S-AI perceived their weight being above average and 23% of J-BI and 34% of S-BI responded similarly (p < 0.001). Body dissatisfaction index (BDI) and eating attitude (EAT26) scores were lower in J-BI(9.7, 12.0) vs. J-AI(16.4, 14.7) and S-BI(12.4, 12.4) vs. S-AI(19.5, 15.4) (p < 0.001). However, PPA was not different for J-BI vs. J-AI, and S-BI vs. S-AL Only 17, 18, 9, and 15% of J.BI, J.AI, S-BI, and S-AI, respectively, exercised regularly. PPA and BDI were only slightly correlated in J-BI(r=0.194, p < 0.005) and S-BI(r=0.220, p < 0.005). Even that the majority of Korean female adolescents perceived they were heavy and desired to lose weight, appropriate exercise and physical activities were not practiced.

• Food Science and Biotechnology
• /
• v.18 no.5
• /
• pp.1071-1075
• /
• 2009

Allyl isothiocyanate (AI), a volatile compound of mustard, has excellent antimicrobial effects, but its volatility hinders its wide usage as an ingredient of food products. Microencapsulation technique, therefore, was applied for delaying the release time of AI. For delaying the release time of AI, the mustard powder, which contained AI, was microencapsulated with 5% modified starch by using fluidized bed processing. The efficiency of the controlled release of AI at various pH was analyzed by the head space (HS) analysis and solid phase microextraction (SPME) method using gas chromatography (GC). Also, modified starch encapsulated powder was added into kimchi for applying in food industry. As the result, the release time of AI was delayed by microencapsulation with modified starch and the higher pH could be the faster release of AI. Also, the period until the pH values and total acidity of kimchi reached up to 4.5 and 0.6%, which give its malsour taste, was extended by microencapsulation. These results showed that modified starch encapsulated powder could prolong the preservation in food system.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.8
• /
• pp.2241-2258
• /
• 2023

This study developed digital literacy instruments and tested their effectiveness on college students' perceptions of AI technologies. In creating a new digital literacy test tool, we reviewed the concept and scale of digital literacy based on previous studies that identified the characteristics and measurement of AI literacy. We developed 23 preliminary questions for our research instrument and used a quantitative approach to survey 318 undergraduates. After conducting exploratory and confirmatory factor analysis, we found that digital literacy in the age of AI had four ability sub-factors: critical understanding, artificial intelligence social impact recognition, artificial intelligence technology utilization, and ethical behavior. Then we tested the sub-factors' predictive powers on the perception of AI's usefulness and ease of use. The regression result shows that the most common powerful predictor of the usefulness and ease of use of AI technology was the ability to use AI technology. This finding implies that for college students, the ability to use various tools based on AI technology is an essential competency in the AI era.

• Journal of Engineering Education Research
• /
• v.26 no.3
• /
• pp.12-19
• /
• 2023

The purpose of this study is to develop the Artificial Intelligence thinking-based education program for improving AI literacy and verify its effectiveness for beginner. This program consists of 17 sessions, was designed according to the "ABCDE" model and is a project-based program. This program was conducted on 51 first-year middle school students and 36 respondents excluding missing values were analyzed in R language. The effect of this program on ethics, understanding, social competency, execution plan, data literacy, and problem solving of AI literacy is statistically significant and has very large practical significance. According to the result of this study, this program provided learners experiencing Artificial Intelligence education for the first time with Artificial Intelligence concepts and principles, collection and analysis of information, and problem-solving processes through application in real life, and served as an opportunity to enhance AI literacy. In addition, education program to enhance AI literacy should be designed based on AI thinking.

• Reproductive and Developmental Biology
• /
• v.37 no.2
• /
• pp.75-77
• /
• 2013

This study was conducted to investigate optimal time of artificial insemination (AI) to Hanwoo female after natural estrus. AI was occurred 12 and 24 hours after natural estrus in both heifer and multiparous recipient then pregnancy and parturition rates were estimated. Results indicated that AI performed at 24 hours after natural estrus showed significant (p<0.05) higher pregnancy rate in both heifer and multiparous recipient groups with significantly (p<0.05) higher abortion rate. However, there are no significant differences of parturition rate, twin birth and sex ratio in both heifer and multiparous recipient groups. Therefore, our results may suggest that performance of AI at 24 hours after natural estrus promise higher pregnancy rate than AI at 12 hours after natural estrus in both heifer and multiparous recipient.

• Korean Journal of Microbiology
• /
• v.48 no.3
• /
• pp.207-211
• /
• 2012

Autoinduction is mediated by signaling molecules known as autoinducers (AIs) that are produced, released and detected by bacterium itself. We recently reported that Corynebacterium glutamicum possesses an autoinduction system which secretes autoinducers during the stationary-phase of growth, triggering the expression of acyltransferase gene. However, it is still not clear what may act as autoinducers for the autoinduction in C. glutamicum. In this study, we compared the inducing effects of cell-free culture fluids obtained from a number of microbes including Agrobacterium tumefaciens, Vibrio harveyi, and Escherichia coli. Fluids from A. tumefaciens did not increase the expression of acyltransferase, whereas fluids from V. harveyi BB120 ($AI-1^+$, $AI-2^+$) did. Interestingly, the expression was increased by the fluids obtained from the early exponential-phase culture of BB120. Furthermore, this induction was not observed by the fluids from autoinducer mutants of V. harveyi MM77 ($AI-1^-$, $AI-2^-$) and BB152 ($AI-1^-$, $AI-2^+$). Unlike the effect shown by BB152, fluids from E. coli ($AI-1^-$, $AI-2^+$) still induced the acyltransferase expression. Taken together, these results suggest that C. glutamicum autoinducers seem to be unidentified molecules which do not belong to AI-1 or AI-2.

• Korean Journal of Radiology
• /
• v.22 no.3
• /
• pp.442-453
• /
• 2021

Artificial intelligence (AI) will likely affect various fields of medicine. This article aims to explain the fundamental principles of clinical validation, device approval, and insurance coverage decisions of AI algorithms for medical diagnosis and prediction. Discrimination accuracy of AI algorithms is often evaluated with the Dice similarity coefficient, sensitivity, specificity, and traditional or free-response receiver operating characteristic curves. Calibration accuracy should also be assessed, especially for algorithms that provide probabilities to users. As current AI algorithms have limited generalizability to real-world practice, clinical validation of AI should put it to proper external testing and assisting roles. External testing could adopt diagnostic case-control or diagnostic cohort designs. A diagnostic case-control study evaluates the technical validity/accuracy of AI while the latter tests the clinical validity/accuracy of AI in samples representing target patients in real-world clinical scenarios. Ultimate clinical validation of AI requires evaluations of its impact on patient outcomes, referred to as clinical utility, and for which randomized clinical trials are ideal. Device approval of AI is typically granted with proof of technical validity/accuracy and thus does not intend to directly indicate if AI is beneficial for patient care or if it improves patient outcomes. Neither can it categorically address the issue of limited generalizability of AI. After achieving device approval, it is up to medical professionals to determine if the approved AI algorithms are beneficial for real-world patient care. Insurance coverage decisions generally require a demonstration of clinical utility that the use of AI has improved patient outcomes.

• Journal of Internet Computing and Services
• /
• v.24 no.5
• /
• pp.121-130
• /
• 2023

In the school field, AI convergence education is recommended, which utilizes AI in education to change the paradigm of society. This study was conducted to define the terms of AI and AI convergence education to minimize the confusion of terms and to analyze the educational needs of teachers from the perspective of conducting AI convergence education. To achieve the purpose, 19 experts' opinions were collected, and a self-administered questionnaire was administered to 125 secondary school teachers enrolled in the AI convergence major at the Graduate School of Education. As a result of the analysis, the experts defined AI convergence education as a methodology for problem solving, not AI-based or utilization education. In the analysis of teachers' educational needs, "AI and big data" was ranked first, followed by "AI convergence education methodology" and "learning practice using AI". The significance of this study is that it defined the terminology by collecting the opinions of experts amidst the confusion of various terms related to AI, and presented the educational direction of AI convergence education for in-service teachers.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.6
• /
• pp.1518-1539
• /
• 2024

Artificial intelligence-enabled business models aim to improve decision-making, operational efficiency, innovation, and productivity. The presented systematic literature review is conducted to highlight elucidating the utilization of artificial intelligence (AI) methods and techniques within AI-enabled businesses, the significance and functions of AI-enabled organizational models and frameworks, and the design parameters employed in academic research studies within the AI-enabled business domain. We reviewed 39 empirical studies that were published between 2010 and 2023. The studies that were chosen are classified based on the artificial intelligence business technique, empirical research design, and SLR search protocol criteria. According to the findings, machine learning and artificial intelligence were reported as popular methods used for business process modelling in 19% of the studies. Healthcare was the most experimented business domain used for empirical evaluation in 28% of the primary research. The most common reason for using artificial intelligence in businesses was to improve business intelligence. 51% of main studies claimed to have been carried out as experiments. 53% of the research followed experimental guidelines and were repeatable. For the design of business process modelling, eighteen AI mythology were discovered, as well as seven types of AI modelling goals and principles for organisations. For AI-enabled business models, safety, security, and privacy are key concerns in society. The growth of AI is influencing novel forms of business.

• Journal of Practical Engineering Education
• /
• v.16 no.1_spc
• /
• pp.41-49
• /
• 2024

The advancement of artificial intelligence on a global scale is significantly transforming life. In the field of education, there is a strong emphasis on actively utilizing AI and fostering creatively integrated talents with diverse knowledge. In alignment with this trend, there is a paradigm shift in AI education across primary, middle, high school, as well as university and graduate education. Leading AI schools and specialized high schools are dedicated to enhancing students' AI capabilities, while universities integrate AI into software courses or establish new AI departments to nurture talent. In AI-integrated education graduate programs, national efforts are underway to educate instructors from various disciplines on applying AI technology to the curriculum. In this context, specialized high schools are also restructuring their departments to cultivate technological talent in AI, tailored to students' characteristics and career paths. While the current education focuses primarily on the fundamental concepts and technologies of AI, there is a need to address the aspect of developing practical problem-solving skills. Therefore, this research aims to compare and analyze essential educational courses in AI-leading schools, AI-integrated high schools, AI high schools, university AI departments, and AI-integrated education graduate programs. The goal is to propose the necessary educational courses for AI education in specialized high schools, with the expectation that a more advanced curriculum in AI education can be established in specialized high schools through this effort.