• The Journal of the Convergence on Culture Technology
• /
• v.10 no.2
• /
• pp.565-574
• /
• 2024

ChatGPT is causing significant reverberations across all sectors of our society, and this holds true for the field of education as well. However, scholarly and societal discussions regarding ChatGPT in academic settings have primarily focused on issues such as plagiarism, with relatively limited research on the positive effects of utilizing generative AI. Additionally, amidst the educational crisis of the post-COVID era, there is a growing recognition of the need to enhance academic engagement. In light of these concerns, we investigated how academic engagement varies based on students' levels of ChatGPT literacy and examined whether students' academic confidence and perceived academic competence serve as mediators between ChatGPT literacy and academic engagement. An analysis using SPSS was conducted on the data collected from 406 college students. The results showed that ChatGPT literacy had a positive effect on academic engagement, and academic confidence mediated the relationship between ChatGPT literacy and academic engagement. Also, when the mediating effect of perceived academic competence was significant only when it was serially mediated. Based on these findings, we discussed the theoretical contributions of identifying the theoretical mechanism between ChatGPT literacy and academic engagement. In addition, practical implications regarding the importance of ChatGPT literacy education were described.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.2
• /
• pp.537-545
• /
• 2024

The importance of University Archives Management is increasing. In this study, we researched cases of collecting and managing educational archival contents in universities. Developed archival contents for software practical education, and implemented it to the Capstone Design course and overseas program. The effect of applying the model was analyzed through surveys and interviews. The Capstone Design Survey, involving 349 participants, indicated the highest satisfaction with the University-Industry Cooperation type. The experience of dissemination and enhancement was aggregated as the second highest satisfaction. In the second survey, 62 students who had participated in the overseas program over the span of two years took part. All nine Likert-type questions showed high satisfaction scores of more than 4 points. The top three satisfaction factors-content, program type, and advanced experience-showed high satisfaction scores of 4.85, 4.74, and 4.71, respectively. Through interviews with professors, mentors, and students, it was also confirmed that instructional methods utilizing archival contents are effective. And the model we developed is applicable for convergence education.

• International Journal of Advanced Culture Technology
• /
• v.12 no.3
• /
• pp.21-28
• /
• 2024

The public can access movies more easily than any other cultural genre. The film's costumes convey the social, political, and cultural climate of that time period. Additionally, it subtly conveys the message of the movie, including the intentions of the director and the characters. Filmmakers can now use fact-based materials to plan their films, and audiences can now watch costume in movies with objective standards, particularly in period dramas, thanks to the advancements in over-the-top (OTT) services. The 77th British Academy costume Award went to the movie Napoleon because of how much emphasis it placed on the outfit. Ninety-five percent of the costume was made by experts in military uniforms and costumery. In contrast to the previous aristocratic and exaggerated Rococo costume, Napoleonic clothing had a natural and common-class character. A natural-shaped Chemise dress composed of light, reflective material first appeared in the Directoire era, just after the French Revolution. Chemise dresses made of a variety of materials gained popularity during the Empire era. With Napoleon taking the throne and Josephine becoming the empress, the vibrant court culture resurfaced during the Empire era. The silk was embellished with gold thread and embroidery, train dangling forms, and different types of sleeves appeared in Empire styles. They wore Pellisse and shawls under the coat. The hair style had long, ancient hair and was adorned with fillets. They also wore straw hats, bonnets, and caps. Long gloves and parasols were also popular accessories, as were pearl or colored jewelry necklaces, earrings, bracelets, and rings. During the Empire era, tiaras were fashionable. Shoes were either low-heeled pumps or sandals. The movie uses Chemise and Empire costumes, which are versatile enough to be used in a range of settings and eras. When it came to details, the type of sleeve was employed without regard to time, such as when using those from an earlier or later period. Since jewelry was worn more often than not in that era, practically every character has earrings on their necklaces. Nearly exact replicas of the coronation costume can be found in paintings by Jacques-Louis David. The red trains, Josephine's Empire dress, the crown, the Tiara, and the costumes of every character in attendance were all clearly identifiable in terms of form and color. To further aid viewers in understanding and enhancing the film's overall coherence, a scene featuring David drawing the coronation was added. Overall, there were differences in that the historical costumes were accurately recreated, the materials and details were utilized without restriction, and some of the costumes were designed with modern materials or accessories that were used more than the historical costumes. This section appears to have been written to highlight the beauty of the characters' personalities or settings. There is a limitation to this study in that it only looked at aristocratic clothing, which includes Josephine's. We will concentrate on male clothing in future research.

• International Journal of Advanced Culture Technology
• /
• v.12 no.3
• /
• pp.29-36
• /
• 2024

The public can now access movies faster and more easily thanks to over-the-top (OTT) services. The audience may be impacted by period dramas, where accurate costume reproduction is crucial. For filmmakers, it is critical to replicate period costumes using precise historical information. The goal of this study is to act as a reference so that, when it comes to period dramas, viewers can evaluate them using impartial criteria and movie producers can use data based on fact to plan their costumes. The film Napoleon won the British Academy Award for Costume after hiring costume experts to create 95% of the entire costume, according to data from the Napoleon I Museum. Following the French Revolution, the ostentatious and ornate men's attire vanished, to be replaced by a more modest and functional outfit. For tops, vests were cut to waist length, shirts, cravats, and carrick were worn, and tailcoats were the norm. The pants were swapped out for loose-fitting ones. The glitzy hues and embellishments from the bygone era progressively vanished and formed the foundation of the contemporary men's costume, which is dominated by black. The hats worn were tricorn, bicorn, top hat, and bowler, and the hairstyle changed from long to short gradually. The civil class wore short tops called carmagnoles. Napoleon wore a high-collared Napoleon collar and a tailcoat with a bicorn, which became his emblem. Green, navy, and white were the colors of the uniform, and a gray woolen coat was worn outside. The elaborately decorated costumes were worn to court and to banquets; the Napoleonic coronation costume was embellished with gold embroidery on silk, red velvet, and martyred hair; the post-revolutionary costumes gradually became more colorful. In the movie Napoleon, period clothing items were well represented, with the aristocracies wearing dark tailcoats, vests, shirts, and cravats. Based on the data from the men's costume, Napoleon's outfit in the movie was made more similarly. This study's limitation is that not every character in the movie could have their costume examined, and the material matter could not be precisely determined by examining the images displayed on the screen. Given that portraits typically feature a great deal of noble imagery, the clothing worn by common people is also associated with data limitations when it comes to movie costume design.

• Journal of the Korea Society for Simulation
• /
• v.33 no.3
• /
• pp.13-26
• /
• 2024

The CBRN(Chemical, Biological, Radiological, and Nuclear) hazard prediction model is a system that supports commanders in making better decisions by creating contamination distribution and damage prediction areas based on the weapons used, terrain, and weather information in the events of biochemical and radiological accidents. NBC_RAMS(Nuclear, Biological and Chemical Reporting And Modeling S/W System) developed by ADD (Agency for Defense Development) is used not only supporting for decision making plan for various military operations and exercises but also for post analyzing CBRN related events. With the NBC_RAMS's core engine, we introduced a CBR hazard assessment scenario analysis system that can generate contaminant distribution prediction results reflecting various CBR scenarios, and described how to apply it in specific purposes in terms of input information, meteorological data, land data with land coverage and DEM, and building data with pologon form. As a practical use case, a technology development case is addressed that tracks the origin location of contaminant source with artificial intelligence and a technology that selects the optimal location of a CBR detection sensor with score data by analyzing large amounts of data generated using the CBRN scenario analysis system. Through this system, it is possible to generate AI-specialized CBRN related to training and analysis data and support planning of operation and exercise by predicting battle field.

• Asian-Australasian Journal of Animal Sciences
• /
• v.28 no.5
• /
• pp.605-611
• /
• 2015

A synthetic strain of ducks (Anas platyrhynchos) was developed by introducing genes for long duration of fertility to be used as mother of mule ducklings and a seven-generation selection experiment was conducted to increase the number of fertile eggs after a single artificial insemination (AI) with pooled Muscovy semen. Reciprocal crossbreeding between Brown Tsaiya LRI-2 (with long duration of fertility) and Pekin L-201 (with white plumage mule ducklings) ducks produced the G0. Then G1 were intercrossed to produce G2 and so on for the following generations. Each female duck was inseminated 3 times, at 26, 29, and 32 weeks of age. The eggs were collected for 14 days from day 2 after AI. Individual data regarding the number of incubated eggs (Ie), the number of fertile eggs at candling at day 7 of incubation (F), the total number of dead embryos (M), the maximum duration of fertility (Dm) and the number of hatched mule ducklings (H) with plumage colour were recorded. The selection criterion was the breeding values of the best linear unbiased prediction animal model for F. The results show high percentage of exhibited heterosis in G2 for traits to improve (19.1% for F and 12.9% for H); F with a value of 5.92 (vs 3.74 in the Pekin L-201) was improved in the G2. Heritabilities were found to be low for Ie ($h^2=0.07{\pm}0.03$) and M ($h^2=0.07{\pm}0.01$), moderately low for Dm ($h^2=0.13{\pm}0.02$), of medium values for H ($h^2=0.20{\pm}0.03$) and F ($h^2=0.23{\pm}0.03$). High and favourable genetic correlations existed between F and Dm ($r_g=0.93$), between F and H ($r_g=0.97$) and between Dm and H ($r_g=0.90$). The selection experiment showed a positive trend for phenotypic values of F (6.38 fertile eggs in G10 of synthetic strain vs 5.59 eggs in G4, and 3.74 eggs in Pekin L-201), with correlated response for increasing H (5.73 ducklings in G10 vs 4.86 in G4, and 3.09 ducklings in Pekin L-201) and maximum duration of the fertile period without increasing the embryo mortality rate. The average predicted genetic response for F was 40% of genetic standard deviation per generation of selection. The mule ducklings' feather colour also was improved. It was concluded that this study provided results for a better understanding of the genetics of the duration of fertility traits in the common female duck bred for mule and that the selection of a synthetic strain was effective method of improvement.

• Development and Reproduction
• /
• v.5 no.1
• /
• pp.47-52
• /
• 2001

Predetermination of sex in livestock of offpring is in great demand and is of critical importance to providing for the most efficient production of the animal ariculture. Such a sexing techlology would also enhance the economy of conventional artificial insemination(AI) and aid the porcine industry. The purpose of this study was to evaluate the efficiency of enriching X-bearing porcine sperm using discontinuous percoll gradients and PCR mefhod. Semen was collected from mature boars of proven fertility center (AI center KimHae). Sperm was leaded on the isotonic discontinuous percoll gradient and then it was centrifuged at 120 ${\times}$ g for 20 minutes. After centrifugation, sperm included in each fraction were recovered (7${\times}$10$^6$ sperms/ml) and then sperm genomic DNA was extractedfor the PCR. SRY gene was used to evaluate the ratio between X and Y sperm in the separated fractions. Ju viro ffrtilization wascarried out by adding the unseparated sperm (control) or separated (experimental poop) to the matured oocytes in TCM-199. Embryos for sex determination were obtained at 2 cell stage and then was used for SRY gene amplification. After centrifugation of discontinuous percoll gradient, the most motile sperm was obtained at 95% fiaction (94.4% ${\pm}$ 5.1%, p < 0.01). The PCR analysis evaluated that 30%, 50% and 65% fractions were Y sperm rich, whereas 80% and 95% fractions were X sperm rich. PCR analysis with each porcineembryo showed that 33.3% of control and 66.7% of experimental group were determined as female embryos. In conclusion, in vitro matured oocytes inseminated with sperms (95% fraction) prepared by percoll gradient centrifugation showed high fertilization rates and female embryos than control sperms.

• Journal of Korean Home Economics Education Association
• /
• v.20 no.2
• /
• pp.75-94
• /
• 2008

The purposes of this paper are to describe the newly established reference values of nutrient intakes: to apply the changed dietary reference intakes to the new text book based on the revised curriculum: and to contrive substantial contents in the domain of dietary life(foods & nutrition) of new text book. Dietary Reference Intakes for Koreans(KDRIs) is newly established reference values of nutrient intakes that are considered necessary to maintain the health of Koreans at the optimal state and to prevent chronic diseases and overnutrition. Unlike previously used Recommended Dietary Allowances for Koreas(KRDA), which presented a single reference value for intake of each nutrient, multiple values are set at levels for nutrients to reduce risk of chronic diseases and toxicity as well as prevention of nutrient deficiency. The new KDRIs include the Estimated Average Requirement(EAR), Recommended Intake(RI), Adequate Intake(AI), and Tolerable Upper Intake Level(UL). The EAR is the daily nutrient intake estimated to meet the requirement of the half of the apparently healthy individuals in a target group and thus is set at the median of the distribution of requirements. The RI is set at two standard deviations above the EAR. The AI is established for nutrients for which existing body of knowledge are inadequate to establish the EAR and RI. The UL is the highest level of daily nutrient intake which is not likely to cause adverse effects for the human health. Age and gender subgroups are established in consideration of physiological characteristics and developmental stages: infancy, toddler, childhood, adolescence, adulthood and old age. Pregnancy and lactation periods were considered separately and gender is divided after early childhood. Reference heights and weights are from the Korean Agency for Technology and Standards, Ministry of Commerce, Industry and Energy. The practical application of DRIs to the new books based on the revision in the 7th curriculum is to assess the dietary and nutrient intake as well as to plan a meal. It can be utilized to set an appropriate nutrient goal for the diet as usually eaten and to develop a plan that the individual will consume using a nutrient based food guidance system in the new books based on the revision in the 7th curriculum.

• Journal of Intelligence and Information Systems
• /
• v.24 no.4
• /
• pp.51-66
• /
• 2018

As AI (Artificial Intelligence) technologies have been swiftly evolved, a lot of products and services are under development in various fields for better users' experience. On this technology advance, negative effects of AI technologies also have been discussed actively while there exists positive expectation on them at the same time. For instance, many social issues such as trolley dilemma and system security issues are being debated, whereas autonomous vehicles based on artificial intelligence have had attention in terms of stability increase. Therefore, it needs to check and analyse major social issues on artificial intelligence for their development and societal acceptance. In this paper, multi-categorical sentiment analysis is conducted over online public opinion on artificial intelligence after identifying the trending topics related to artificial intelligence for two years from January 2016 to December 2017, which include the event, match between Lee Sedol and AlphaGo. Using the largest web portal in South Korea, online news, news headlines and news comments were crawled. Considering the importance of trending topics, online public opinion was analysed into seven multiple sentimental categories comprised of anger, dislike, fear, happiness, neutrality, sadness, and surprise by topics, not only two simple positive or negative sentiment. As a result, it was found that the top sentiment is "happiness" in most events and yet sentiments on each keyword are different. In addition, when the research period was divided into four periods, the first half of 2016, the second half of the year, the first half of 2017, and the second half of the year, it is confirmed that the sentiment of 'anger' decreases as goes by time. Based on the results of this analysis, it is possible to grasp various topics and trends currently discussed on artificial intelligence, and it can be used to prepare countermeasures. We hope that we can improve to measure public opinion more precisely in the future by integrating empathy level of news comments.

• Journal of Intelligence and Information Systems
• /
• v.25 no.3
• /
• pp.1-17
• /
• 2019

Because stock price forecasting is an important issue both academically and practically, research in stock price prediction has been actively conducted. The stock price forecasting research is classified into using structured data and using unstructured data. With structured data such as historical stock price and financial statements, past studies usually used technical analysis approach and fundamental analysis. In the big data era, the amount of information has rapidly increased, and the artificial intelligence methodology that can find meaning by quantifying string information, which is an unstructured data that takes up a large amount of information, has developed rapidly. With these developments, many attempts with unstructured data are being made to predict stock prices through online news by applying text mining to stock price forecasts. The stock price prediction methodology adopted in many papers is to forecast stock prices with the news of the target companies to be forecasted. However, according to previous research, not only news of a target company affects its stock price, but news of companies that are related to the company can also affect the stock price. However, finding a highly relevant company is not easy because of the market-wide impact and random signs. Thus, existing studies have found highly relevant companies based primarily on pre-determined international industry classification standards. However, according to recent research, global industry classification standard has different homogeneity within the sectors, and it leads to a limitation that forecasting stock prices by taking them all together without considering only relevant companies can adversely affect predictive performance. To overcome the limitation, we first used random matrix theory with text mining for stock prediction. Wherever the dimension of data is large, the classical limit theorems are no longer suitable, because the statistical efficiency will be reduced. Therefore, a simple correlation analysis in the financial market does not mean the true correlation. To solve the issue, we adopt random matrix theory, which is mainly used in econophysics, to remove market-wide effects and random signals and find a true correlation between companies. With the true correlation, we perform cluster analysis to find relevant companies. Also, based on the clustering analysis, we used multiple kernel learning algorithm, which is an ensemble of support vector machine to incorporate the effects of the target firm and its relevant firms simultaneously. Each kernel was assigned to predict stock prices with features of financial news of the target firm and its relevant firms. The results of this study are as follows. The results of this paper are as follows. (1) Following the existing research flow, we confirmed that it is an effective way to forecast stock prices using news from relevant companies. (2) When looking for a relevant company, looking for it in the wrong way can lower AI prediction performance. (3) The proposed approach with random matrix theory shows better performance than previous studies if cluster analysis is performed based on the true correlation by removing market-wide effects and random signals. The contribution of this study is as follows. First, this study shows that random matrix theory, which is used mainly in economic physics, can be combined with artificial intelligence to produce good methodologies. This suggests that it is important not only to develop AI algorithms but also to adopt physics theory. This extends the existing research that presented the methodology by integrating artificial intelligence with complex system theory through transfer entropy. Second, this study stressed that finding the right companies in the stock market is an important issue. This suggests that it is not only important to study artificial intelligence algorithms, but how to theoretically adjust the input values. Third, we confirmed that firms classified as Global Industrial Classification Standard (GICS) might have low relevance and suggested it is necessary to theoretically define the relevance rather than simply finding it in the GICS.