• Journal of Science Education
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• v.45 no.3
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• pp.292-303
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• 2021

This study identifies the terms frequently used together with energy in online science news articles and topics of the news reports to find out how the term energy is used in everyday life and to draw implications for science curriculum and instruction about energy. A total of 2,171 online news articles in science category published by 11 major newspaper companies in Korea for one year from March 1, 2018 were selected by using energy as a search term. As a result of natural language processing, a total of 51,224 sentences consisting of 507,901 words were compiled for analysis. Using the R program, term frequency analysis, semantic network analysis, and structural topic modeling were performed. The results show that the terms with exceptionally high frequencies were technology, research, and development, which reflected the characteristics of news articles that report new findings. On the other hand, terms used more than once per two articles were industry-related terms (industry, product, system, production, market) and terms that were sufficiently expected as energy-related terms such as 'electricity' and 'environment.' Meanwhile, 'sun', 'heat', 'temperature', and 'power generation', which are frequently used in energy-related science classes, also appeared as terms belonging to the highest frequency. From a network analysis, two clusters were found including terms related to industry and technology and terms related to basic science and research. From the analysis of terms paired with energy, it was also found that terms related to the use of energy such as 'energy efficiency,' 'energy saving,' and 'energy consumption' were the most frequently used. Out of 16 topics found, four contexts of energy were drawn including 'high-tech industry,' 'industry,' 'basic science,' and 'environment and health.' The results suggest that the introduction of the concept of energy degradation as a starting point for energy classes can be effective. It also shows the need to introduce high-tech industries or the context of environment and health into energy learning.

• Journal of Biosystems Engineering
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• v.16 no.4
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• pp.384-398
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• 1991

A computer program was developed to select the optimum size of farm machine and analyze its operation costs according to various farming conditions. It was written in FORTRAN 77 and BASIC languages and can be run on any personal computer having Korean Standard Complete Type and Korean Language Code. The program was developed as a user-friendly type so that users can carry out easily the costs analysis for the whole farm work or respective operation in rice production, and for plowing, rotarying and pest controlling in upland. The program can analyze simultaneously three different machines in plowing & rotarying and two machines in transplanting, pest controlling and harvesting operations. The input data are the sizes of arable lands, possible working days and number of laborers during the opimum working period, and custom rates varying depending on regions and individual farming conditions. We can find out the results such as the selected optimum combination farm machines, the overs and shorts of working days relative to the planned working period, capacities of the machines, break-even points by custom rate, fixed costs for a month, and utilization costs in a hectare.

• Clinical and Experimental Pediatrics
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• v.49 no.10
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• pp.1056-1060
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• 2006

Purpose : As hearing ability affects language and cognitive development, early detection and intervention of congenital hearing defects is very important. We analyzed the result of newborn hearing screening using automated auditory brainstem response and estimated the incidence of congenital hearing defects in newborn infants in Korea. Methods : Hearing screening tests were done on 7,218 newborn infants who were delivered at Cheil General Hospital from July 1, 2004 to June 30, 2005. The first screening test was done on the second day of life with automated auditory brainstem response(AABR) using $ALGO{\bigcirc}^{(3)}$ Newborn hearing screener($Natus^{(R)}$ Medical Incorporated, San Carlos, USA) with 35 dB sound level. The newborn infants who did not pass the initial screening test took the second screening AABR test before discharge from the nursery. Infants who did not pass these screenings at the nursery were followed up at the Department of Otorhinolaryngology, Samsung Seoul Hospital. Results : Total 7,218 infants(83.3 percent of total 8,664 live births of the Cheil General Hospital) were screened in the nursery, and 55 of them failed to pass the newborn screening. Among 55 infants who were referred, six were lost during follow-up, and 14 were confirmed as hearing impaired. Six of them(42.8 percent) do not have any risk factors for hearing impairment. We can estimate that the incidence of hearing defects is about 1.9-2.8 per 1,000 live births. Conclusion : Automated auditory brainstem response is an effective tool to screen the hearing of newborn infants. Congenital hearing loss is more frequent than metabolic diseases on which screening tests are available in the newborn period. About 40 percent of infants who have hearing defects do not have any risk factors for hearing impairment. Therefore, universal newborn hearing screening must be recommended to all neonates.

• Asia pacific journal of information systems
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• v.19 no.1
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• pp.113-145
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• 2009

Recently, due to the globalization of the IT(Information Technology) market, devices and systems designed in one country are used in other countries as well. This phenomenon is becoming the key factor for increased interest on cross-cultural, or cross-national, research within the IT area. However, as the IT market is becoming bigger and more globalized, a great number of IT practitioners are having difficulty in designing and developing devices or systems which can provide optimal experience. This is because not only tangible factors such as language and a country's economic or industrial power affect the user experience of a certain device or system but also invisible and intangible factors as well. Among such invisible and intangible factors, the cultural characteristics of users from different countries may affect the user experience of certain devices or systems because cultural characteristics affect how they understand and interpret the devices or systems. In other words, when users evaluate the quality of overall user experience, the cultural characteristics of each user act as a perceptual lens that leads the user to focus on a certain elements of experience. Therefore, there is a need within the IT field to consider cultural characteristics when designing or developing certain devices or systems and plan a strategy for localization. In such an environment, existing IS studies identify the culture with the country, emphasize the importance of culture in a national level perspective, and hypothesize that users within the same country have same cultural characteristics. Under such assumptions, these studies focus on the moderating effects of cultural characteristics on a national level within a certain theoretical framework. This has already been suggested by cross-cultural studies conducted by scholars such as Hofstede(1980) in providing numerical research results and measurement items for cultural characteristics and using such results or items as they increase the efficiency of studies. However, such national level culture has its limitations in forecasting and explaining individual-level behaviors such as voluntary device or system usage. This is because individual cultural characteristics are the outcome of not only the national culture but also the culture of a race, company, local area, family, and other groups that are formulated through interaction within the group. Therefore, national or nationally dominant cultural characteristics may have its limitations in forecasting and explaining the cultural characteristics of an individual. Moreover, past studies in psychology suggest a possibility that there exist different cultural characteristics within a single individual depending on the subject being measured or its context. For example, in relation to individual vs. collective characteristics, which is one of the major cultural characteristics, an individual may show collectivistic characteristics when he or she is with family or friends but show individualistic characteristics in his or her workplace. Therefore, this study acknowledged such limitations of past studies and conducted a research within the framework of 'theoretically integrated model of user satisfaction and emotional attachment', which was developed through a former study, on how the effects of different experience elements on emotional attachment or user satisfaction are differentiated depending on the individual cultural characteristics related to a system or device usage. In order to do this, this study hypothesized the moderating effects of four cultural dimensions (uncertainty avoidance, individualism vs, collectivism, masculinity vs. femininity, and power distance) as suggested by Hofstede(1980) within the theoretically integrated model of emotional attachment and user satisfaction. Statistical tests were then implemented on these moderating effects through conducting surveys with users of four digital devices (mobile phone, MP3 player, LCD TV, and refrigerator) in three countries (US, Germany, and Russia). In order to explain and forecast the behavior of personal device or system users, individual cultural characteristics must be measured, and depending on the target device or system, measurements must be measured independently. Through this suggestion, this study hopes to provide new and useful perspectives for future IS research.

• The Journal of Korean Academic Society of Nursing Education
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• v.3
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• pp.99-116
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• 1997

In response of the increasing demand for professional degree in nursing, some university in Korea offers RN-BSN program for R. N. from diploma in nursing. However, RN-BSN program in Korea is in formative period. Therefore, the purpose of this survey study is for the comparative analysis of RN-BSN curriculum in Korea and U.S.A. In this study, subjects consisted of 18 department of nursing in university and 5 RN-BSN programs in Korea and 18 department of nursing in university and 12 RN-BSN programs in U.S.A. For earn the degree of Bachelor of Science in Nursing, the student earns 134 of mean credits in U.S.A., whereas 150.3 of mean credits in Korea. The mean credit for clinical pratice is 30.1 in U.S.A., whereas 23.9 in Korea. Students are assigned to individually planned clinical experiences under the direction of a preceptor in U.S.A. In RN-BSN program, total mean credits through lecture and clinical practice for earn the degree of BSN is 35.5(lecture : 27.7, practice ; 7.8)in U.S.A., whereas,48.1 (lecture;42.1, practice;6.0) in Korea. RN-BSN program can be taken on a full-or-part time basis in U.S.A., whereas didn't in Korea. Especially, emphasis is place on the advanced nursing practicum that focus on the role of the professional nurse in providing health care to individuals, families, and groups in community setting in U.S.A. 27.7 of mean credits was earned through lecture in U.S.A., whereas 42.1 of mean credits in Korea. It means that RN-BSN program in Korea is the lesser development in teaching method and appraisal method than in U.S.A. Students of RN-BSN program in U.S.A. can earns credit through CLEP, NLN achievement test, portfolio review session etc as well as lecture. Therefore, the authors suggests some recommendations for the development of curriculum of RN-BSN program in Korea based on comparative analysis of RN-BSN curricula in U.S.A. and Korea. 1. The curriculum of RN-BSN Program in nursing was required to do some alterations. Nursing care, today, is complex and ever changing. According to change of public need, RN-BSN curriculum intensified primary care program in community setting, geriatric nursing, marketing skill, computer language. 2. The various and new methods of earning credit should be developed. That is, the students will earn credits through the transfer of previous nursing college credits, accredited examination of university, advanced placement examination, portfolio review session, case study, report, self-directed learning and so on. Flexible teaching place should ile offered. 3. Flexible teaching place should be offered. The RN-BSN curriculum should accommodate each RN student's geographical needs and school/work schedule. Therefore, the university should search a variety of teaching places and the RN students can obtain their degrees comfortably throughout the teaching place such as lecture room inside the health care agency and establishment of the branch school in each student's residence area. 4. The RN-BSN program should offer a long distance education to place-bound RN student in many parts of Korea. That is, from the main office of university, the RN-BSN courses are delivered to many areas by Internet, EdNet (satellite telecommunication) and other non-traditional methods. 5. For allowing RN student to take nursing courses, program length should be various, depending upon the student's study/work schedule. That is, the various term systems such as semester, three terms, quarter systems and the student's status like full time or part time should be considered. Therefore, the student can take advantage of the many other educational and professional opportunities, making them available during the school year.

• Restorative Dentistry and Endodontics
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• v.27 no.2
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• pp.183-195
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• 2002

흑색 색소를 형성하는 그람음성 혐기성 세균은 급성 임상 증상을 가진 환자의 근관에서 자주 발견되는 세균으로서 세균 및 세균의 성분과 산물이 치근단 병소의 생성과 밀접하게 연관된 것으로 알려져 있다. 본 연구는 흑색 색소를 형성하는 그람음성 혐기성 세균 중 가장 발현율이 높은 Prevotella nigrescens가 배양된 세포에 미치는 세포 독성을 연구하고자 하였다. 두 가지 세포주 및 사람의 치은섬유모세포를 일차배양하여 사용하였으며, 세포주에 따른 독성 발현에 차이가 있는지를 비교하였다. P. nigrescens ATCC 33563 표준 균주 및 임상 균주로는 환자의 감염된 근관으로부터 165 rRNA primer를 사용한 중합효소 연쇄반응으로 P. nigrescens 6 균주를 동정하여 사용하였다. 세균배양액, 세균의 초음파 추출단백질 및 lipopolysaccharide (LPS)를 MC3T3-El 조골세포, NIH3T3 섬유모세포 및 치은섬유모세포에 첨가한 후 MTT분석법으로 세포의 활성을 측정하였으며, 세포의 형태학적 변화를 도립현미경으로 관찰하였다. 세균배양액을 100$\mu\textrm{l}$ 첨가한 경우는 세가지 세포주 모두에서 통계적으로 유의하게 세포의 활성을 억제하였다. 세균의 초음파 추출단백질 12.5$\mu\textrm{g}$/ml 와 25$\mu\textrm{g}$/ml 는 NIH3T3세포에 통계적으로 유의한 세포독성을 보였다. 세 가지 세포주에 대한 LPS의 세포 독성 효과는 첨가된 LPS의 농도 및 균주에 따라 다양하게 나타났다. 심하게 손상된 세포는 세포의 단일층이 수축되고 세포가 응집되었으며 세포가 배양용기의 바닥에서 떨어지는 양상이 도립 현미경하에서 관찰되었다. 본 연구의 결과 P. nigrescens가 숙주 반응을 조절하여 치수 및 치근단 병소의 유발 및 악화에 기여하는 세균으로 작용할 수 있음을 시사한다. 조직과 함께 제거하고 포르말린에서 48시간 고정시킨 후 파라핀에 포매한 다음에 micro-tome을 사용하여 6$\mu\textrm{m}$로 serial section을 시행하였다. 정중선 부위의 시편에 Hematoxylin-Eosin staining을 시행한 후 Olsson, Orstavik 그리고 Mjor 등의 방법에 따라 조직학적 변화를 관찰한 후 slight(1), moderate(2), severe inflammation(3)의 단계로 분류하였다. 얻어진 결과를 통계처리 프로그램인 Jandel사의 Sigmastat을 이용하여 Kruskal Wallis Test로 통계처리를 하였다. 결과 : (Table omitted) 결론 : 1) Pulp Canal Sealer를 제외한 모든 군에서 시간이 지남에 따라 유의성 있게 염증이 감소되는 양상을 보였다(p<0.05). 2) Pulp Canal Sealer는 1주, 2주, 12주에서 강한 염증반응을 보였다. 3) AH 26과 AH Plus에서는 1주, 2주에서 강한 염증반응을 보였으나 12주에서는 염증반응이 감소하였다. 4) 새로 개발된 봉함제 Adseal-1,2는 1주, 2주에서는 가장 약한 염증반응을 보이나 4주, 12주 후에는 AH Plus와 비슷한 수준의 염증 반응을 보였다. 5) Pulp Canal Sealer를 제외한 모든 군에서 인정할 만한 생체친화성을 보였다. 6) Adseal-2가 Adseal-1에 비하여 전반적으로 낮은 염증반응을 보였다. 7) 각 군간 결과의 차이에 통계적 유의성은 없었다(p>0.05).mmunity. Then, a hierarchical language is to defeat its own purpose.중 행정부가 북한에 대해 실시한 포용정책이 어떠한 성과를 거두고 어떠한 문제점을 간과하고 있는가에 대해 논의하고, 대북 정책의 새로운 지평을 논의하는 것을 목적으로 하고 있다. 1) 포용 정책은 세계의

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.63-79
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• 2024

The startup ecosystem is experiencing a paradigm shift in founding due to the acceleration of digital transformation, online platform companies have grown significantly into unicorns, but the lack of differentiated approaches and strategic support for deep tech startups has led to the inactivity of the startup ecosystem. is lacking. Therefore, in this study, we proposed ways to develop domestic startup development policies, focusing on the US system, which is an advanced example overseas. Focusing on the definition and characteristics of deep tech startups, current investment status, success stories, support policies, etc., we comprehensively analyzed domestic and international literature and derived suggestions. In particular, he proposed specific ways to improve support policies for domestic deep tech startups and presented milestones for their development. Currently, the United States is significantly strengthening the role of the government in supporting deep tech startups. The US government provides direct financial support to deep tech startups, including detergent support and infrastructure support. It has also established policies to foster deep tech startups, established related institutions, and systematized support. It is worth noting that US universities play a core role in nurturing deep tech startups. Leading universities in the United States operate deep tech startup discovery and development programs, providing research and development infrastructure and technology. It also works with companies to provide co-investment and commercialization support for deep tech startups. As a result, the growth of domestic deep tech startups requires the cooperation of diverse entities such as the government, universities, companies, and private investors. The government should strengthen policy support, and universities and businesses should work together to support R&D and commercialization capabilities. Furthermore, private investors must stimulate investment in deep tech startups. Through such efforts, deep tech startups are expected to grow and Korea's innovation ecosystem will be revitalized.

• The Mathematical Education
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• v.63 no.2
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• pp.123-138
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• 2024

This study described the utilization of ChatGPT in teaching and students' learning processes for the course "Introductory Mathematics for Artificial Intelligence (Math4AI)" at 'S' University. We developed a customized ChatGPT and presented a learning model in which students supplement their knowledge of the topic at hand by utilizing this model. More specifically, first, students learn the concepts and questions of the course textbook by themselves. Then, for any question they are unsure of, students may submit any questions (keywords or open problem numbers from the textbook) to our own ChatGPT at https://math4ai.solgitmath.com/ to get help. Notably, we optimized ChatGPT and minimized inaccurate information by fully utilizing various types of data related to the subject, such as textbooks, labs, discussion records, and codes at http://matrix.skku.ac.kr/Math4AI-ChatGPT/. In this model, when students have questions while studying the textbook by themselves, they can ask mathematical concepts, keywords, theorems, examples, and problems in natural language through the ChatGPT interface. Our customized ChatGPT then provides the relevant terms, concepts, and sample answers based on previous students' discussions and/or samples of Python or R code that have been used in the discussion. Furthermore, by providing students with real-time, optimized advice based on their level, we can provide personalized education not only for the Math4AI course, but also for any other courses in college math education. The present study, which incorporates our ChatGPT model into the teaching and learning process in the course, shows promising applicability of AI technology to other college math courses (for instance, calculus, linear algebra, discrete mathematics, engineering mathematics, and basic statistics) and in K-12 math education as well as the Lifespan Learning and Continuing Education.

• Journal of The Korean Association For Science Education
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• v.29 no.8
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• pp.990-1010
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• 2009

To derive brain-based evolutionary educational principles, this study examined the studies on the structural and functional characteristics of human brain, the biological evolution occurring between- and within-organism, and the evolutionary attributes embedded in science itself and individual scientist's scientific activities. On the basis of the core characteristics of human brain and the framework of universal Darwinism or universal selectionism consisted of generation-test-retention (g-t-r) processes, a Model of Brain-based Evolutionary Scientific Teaching for Learning (BEST-L) was developed. The model consists of three components, three steps, and assessment part. The three components are the affective (A), behavioral (B), and cognitive (C) components. Each component consists of three steps of Diversifying $\rightarrow$ Emulating (Executing, Estimating, Evaluating) $\rightarrow$ Furthering (ABC-DEF). The model is 'brain-based' in the aspect of consecutive incorporation of the affective component which is based on limbic system of human brain associated with emotions, the behavioral component which is associated with the occipital lobes performing visual processing, temporal lobes performing functions of language generation and understanding, and parietal lobes, which receive and process sensory information and execute motor activities of the body, and the cognitive component which is based on the prefrontal lobes involved in thinking, planning, judging, and problem solving. On the other hand, the model is 'evolutionary' in the aspect of proceeding according to the processes of the diversifying step to generate variants in each component, the emulating step to test and select useful or valuable things among the variants, and the furthering step to extend or apply the selected things. For three components of ABC, to reflect the importance of emotional factors as a starting point in scientific activity as well as the dominant role of limbic system relative to cortex of brain, the model emphasizes the DARWIN (Driving Affective Realm for Whole Intellectual Network) approach.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.