• Journal of Nutrition and Health
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• v.55 no.1
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• pp.21-35
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• 2022

The recommended meal composition allows the general people to organize meals using the number of intakes of foods from each of six food groups (grains, meat·fish·eggs·beans, vegetables, fruits, milk·dairy products and oils·sugars) to meet Dietary Reference Intakes for Koreans (KDRIs) without calculating complex nutritional values. Through an integrated analysis of data from the 6th to 7th Korean National Health and Nutrition Examination Surveys (2013-2018), representative foods for each food group were selected, and the amounts of representative foods per person were derived based on energy. Based on the EER by age and gender from the KDRIs, a total of 12 kinds of diets were suggested by differentiating meal compositions by age (aged 1-2, 3-5, 6-11, 12-18, 19-64, 65-74 and ≥ 75 years) and gender. The 2020 Food Balance Wheel included the 6th food group of oils and sugars to raise public awareness and avoid confusion in the practical utilization of the model by industries or individuals in reducing the consistent increasing intakes of oils and sugars. To promote the everyday use of the Food Balance Wheel and recommended meal compositions among the general public, the poster of the Food Balance Wheel was created in five languages (Korean, English, Japanese, Vietnamese and Chinese) along with card news. A survey was conducted to provide a basis for categorizing nutritional problems by life cycles and developing customized web-based messages to the public. Based on survey results two types of card news were produced for the general public and youth. Additionally, the educational program was developed through a series of processes, such as prioritization of educational topics, setting educational goals for each stage, creation of a detailed educational system chart and teaching-learning plans for the development of educational materials and media.

• Journal of The Korean Association For Science Education
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• v.40 no.5
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• pp.515-529
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• 2020

'Scientific inquiry experiments', which was newly created subjects in the 2015 revised curriculum, was expected in the aspect of learning science and developing core competences through science practices. Based on changed view of evaluation, assessments of a practice-centered subject 'Scientific inquiry experiments' should be try to conducted in various ways, but many challenges were reported. In this study, through analysis of current status of assessment of the subject, we intended to find the way of conducting and supporting 'Scientific inquiry experiments'. We collected assessment materials and explanatory description about them from 25 teachers who taught 'Scientific inquiry experiments' in 2018 and 2019. And we analyzed the cases with framework which were consisted with three main categories: elements, standards, methods of assessments. Also, we investigated how the results of assessment were utilized. For the validity, we requested verification of the results of our data analysis to experts of science education and science teachers. From them, we also collected their opinions about our analysis. As a result of the study, teachers assessed some elements of inquiry skills such as 'analysis and interpreting the data', 'conducting inquiry' more than others which were closely related to what subject-matter the teachers used to organized inquiry program with. In the aspect of domain of assessments, though cognitive domain and affective domain as well as skills were evaluated, we also found that the assessment of those domains had some limitation. In terms of standard of assessment, the goals of assessment were presented in most cases, but there were relatively few cases which had the specific criteria and the stepwise statements of expected performance of students. The time and subject of the assessment were mainly post-class and teachers, and others such as in-class assessments, peer-assessments were used only in specific contexts. In all cases, the results of assessments used for calculating students' grade, but in some cases, we could observe that the results used for improving teaching and feedback for students. Based on these results, we discussed how to support the assessments of 'Scientific inquiry experiments'.

• Journal of Nutrition and Health
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• v.9 no.4
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• pp.4-8
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• 1976

영양지도원(營養指導員)은 자신(自身)이 알고 있는 기술(技術)을 다른 사람에게 전달(傳達)하여 그 사람으로 하여금 지도원(指導員)이 원하는 방향(方向)으로 행동(行動)을 하도록 해야 한다. 따라서 다른 사람을 지도(指導)하려면은 우선 지도원 자신(指導員自身)의 우수한 자질(資質)"이 필요(必要) 하며 이를 위(爲)하여 기술자(技術者)로서의 연마(硏磨)와 겸(兼)하여 인간(人間)의 지도자(指導者)로서의 수양(修養)을 쌓아야 한다. 그리하여 영양개선(營養改善) 의 선도적(先導的) 점화자(點火者)로 "뒤에서 계속 미는" 지원자(支援者)로서의 역할(役割)을 수행(遂行)하여야 한다. (1) 현직능별(現職能別) 영양지도원(營養指導員)의 범위(範圍)를 보건소(保健所)의 보건지도원(保健指導員), 농촌지도소(農村指導所)의 생활지도요원(生活指導要員), 군면(郡面)의 행정지도요원(行政指導要員), 농협(農協)의 부여지도요원(婦女指導要員), 의료계(醫療界)의 의사(醫師), 간호원(看護員), 조산원(助産員), 학교(學校) 교육기관(敎育機關)의 교사(敎師), 영양사(營養士), 영리회사(營利會社)의 사원(社員) 등을 들 수 있다. (2) 지도대상(指導對象)과 그 장소(場所)는 공장(工場), 학교(學校), 훈련장(訓練場), 병원(病院), 복지시설(福祉施設)과 공동취사(共同炊事) 재해시등(災害時等)의 집단급식장(集團給食場)과 이를 이용(利用)하는 對象者(대상자) 도시(都市) 농촌(農村)의 일반가정(一般家庭)의 주민(住民), 그리고 교실(敎室)에서 학교교과목(學校敎科目)을 통(通)한 학생(學生)의 학습(學習) 새마을운동(運動) 공보시설(公報施設)을 통(通)하여 대중(大衆)에게 "지도(指導)를 지도원(指導員)이" 전개(展開)할 수 있다. (3) 지도방법(指導方法)은 일반적(一般的) 학교교육과정(學校敎育過程)의 교육방법(敎育方法)을 적용(適用)하되 교외교육(校外敎育)이라는 점(點)을 잊어서는 안된다. 현실적(現實的)으로 이론(理論)과 경험(經驗)을 병행활용(倂行活用)하며 영양학(營養學)의 연구결과(硏究結果)가 반드시 또 는 곧 가정생활(家庭生活) 개인생활(個人生活)에 적응(適應)되는 것이 아니며, 행동화(行動化)되지 않는 지식(知識)과 기술(技術)은 무용(無用)하게 되므로 "다고 말 할 수 있다. 따라서 영양개선(營養改善)을 지도(指導)하는 지도원(指導員)은 받아들이는 가정(家庭)이나 개인(個人)의 입장(立場)에서 여러 가지 여건을 파악 최대공약수(最大公約數)의 가능치(可能値)를 알아내서 지도(指導)해야 된다. (4) 영양지도(營養指導)는 기술(技術)이 ,포함(包含)되어 있기 때문에 기술(技術)의 전달과정(傳達過程)을 분석(分析)해야 되고 (5) 지도원(指導員) 자신의 무장(武裝)을 위(爲)하여 자신(自身)의 기술지도(技術指導) 방법(方法), 인간지도자(人間指導者)로서의 능력향상(能力向上)을 독서(讀書), 교육(敎育), 훈련(訓練) 을 통(通)하여 배워 기술자(技術者)로서 인간지도자(人間指導者)로서 전달자(傳達者)로 서의 교양(敎養)을 가져야 한다. (6) 지도원(指導員)의 활동성과(活動成果)는 지도원(指導員) 자신의 열의(熱意)와 받아들이는 사람의 열의(熱意)에 의(依)하여 좌우(左右)된다. 즉(卽) 지도원(指導員)의 열의(熱意)${\times}$피지도자(被指導者)의 열의(熱意)=지도성과(指導成果) $[L{\times}P=f(L{\cdot}P)]$로 나타난다. 결론적(結論的)으로 지도원(指導員)은 영양개선(營養改善)의 전문적(專門的) 각 요소(各要素)를 깊이 알고 이것을 다시 종합(綜合)하고 체계화(體系化)할 줄 알며 직능별(職能別) 각 지도원(各指導員)과의 상호(相互) 협조(協助)로 서로 보완(補完)하고 새마을 운동(運動)과 그 직장(職場) 또는 환경(環境)여건에 결부(結付)되고 현실적(現實的)으로 행동화(行動化)할 수 있는 단계적(的) 장단기계획(長短期計劃)과 평가방법(評價方法)을 숙지(熟知)하여 또 지도방법(指導方法)에 필요(必要)한 교재(敎材)를 충실(充實)히 준비하여 자신(自身)의 실력(實力)을 충분(充分)히 발휘할 수 있도록 하여 자기 열의(熱意)를 다하고" 영양개선(營養改善)의 선도적(先導的) 점화자(點火者)로서 "계속 뒤에서 미는" 지원자(支援者)로서 사명(使命)을 다할 때 그 역할(役割)을 다하는 것이다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.3
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• pp.273-283
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• 2020

Because of climate change, the occurrence of localized and heavy rainfall is increasing. It is important to predict floods in urban areas that have suffered inundation in the past. For flood prediction, not only numerical analysis models but also machine learning-based models can be applied. The LSTM (Long Short-Term Memory) neural network used in this study is appropriate for sequence data, but it demands a lot of data. However, rainfall that causes flooding does not appear every year in a single urban basin, meaning it is difficult to collect enough data for deep learning. Therefore, in addition to the rainfall observed in the study area, the observed rainfall in another urban basin was applied in the predictive model. The LSTM neural network was used for predicting the total overflow, and the result of the SWMM (Storm Water Management Model) was applied as target data. The prediction of the inundation map was performed by using logistic regression; the independent variable was the total overflow and the dependent variable was the presence or absence of flooding in each grid. The dependent variable of logistic regression was collected through the simulation results of a two-dimensional flood model. The input data of the two-dimensional flood model were the overflow at each manhole calculated by the SWMM. According to the LSTM neural network parameters, the prediction results of total overflow were compared. Four predictive models were used in this study depending on the parameter of the LSTM. The average RMSE (Root Mean Square Error) for verification and testing was 1.4279 ㎥/s, 1.0079 ㎥/s for the four LSTM models. The minimum RMSE of the verification and testing was calculated as 1.1655 ㎥/s and 0.8797 ㎥/s. It was confirmed that the total overflow can be predicted similarly to the SWMM simulation results. The prediction of inundation extent was performed by linking the logistic regression with the results of the LSTM neural network, and the maximum area fitness was 97.33 % when more than 0.5 m depth was considered. The methodology presented in this study would be helpful in improving urban flood response based on deep learning methodology.

• Archives of design research
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• v.11 no.1
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• pp.185-197
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• 1998

The domestic publishing market has heen ranked at No.7 in the word publishing market(stastics material in Cultu re and Gymnastics m inistrv )Es pe cia Ill'. publishing quantity of children'book is about to reacb No.3. Such a publishing condition i." showing that Korean publishing world has limit,llion of kind and genre despite of its quant.iative improvement On the ot.her hand. t',reign juvenile publi."hing has multi-publishing form, which is a simultaneous publishing with dolls, audio stuff, game programs and CD-ROM t.itles. Even the animation is considered as of the publication at the planning s tsge. However, when we take a look at domestic condition we come to know that Korean juvenile publishing has been occupied mostly by the studying book. Also, the cautious book selection by the well educated parents in l990's has brought up the change of juvenile publishing world. Such a presen t condition bears of juvenlie publi.,;hing world. Such a present condition bears problem, which is the checking 190 translat.ions among the published picture- books of the last ye ar children's book Nevertheless, there was a sucessful domestic planned creative picture book last year. That is "Puppy s shit", which was sold out 15 000 copies and be st se ller of children's book. Whe n we take a look at the commercial success of "Puppy s shit", it is possible that domestic work holds a position in the publishing market. "Puppy s shit" is the story about valuable nature with Korean styled illustration, which tells the prefemece of Korean book in do mestic pu blis hin f.i market. With the motto "Finding prospect of the Korean creative children's book", this paper was went throu gh. By searchinf.i for creative com ponent.s of picture-book planning such as theme, story, illustration, and edit design through the foreign picture-book "What 1 want. to know from the little mole is who made it on top of his head"-and domestic creative picture/book 'Puppy's shit", this study tried to tell a couple of things like followings publication of Korean creative picture book in t.he world. professional and more artistic inner fabric and originality(the relatio nship be tween stort and illu,tration), improvement of illustration through new formative language with well expressed con ten t, planning improvem ent of Korean creative pictive picture book including literary, artistic and educative component and finally examples of planning, artict and educative component and finally example, of planning the good book with a story and illu,;tration which can in the long run improve the value of life for the children.h can in the long run improve the value of life for the children.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.5
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• pp.431-449
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• 2022

As many tunnels generally have been constructed, various experiences and techniques have been accumulated for tunnel design as well as tunnel construction. Hence, there are not a few cases that, for some usual tunnel design works, it is sufficient to perform the design by only modifying or supplementing previous similar design cases unless a tunnel has a unique structure or in geological conditions. In particular, for a tunnel blast design, it is reasonable to refer to previous similar design cases because the blast design in the stage of design is a preliminary design, considering that it is general to perform additional blast design through test blasts prior to the start of tunnel excavation. Meanwhile, entering the industry 4.0 era, artificial intelligence (AI) of which availability is surging across whole industry sector is broadly utilized to tunnel and blasting. For a drill and blast tunnel, AI is mainly applied for the estimation of blast vibration and rock mass classification, etc. however, there are few cases where it is applied to blast pattern design. Thus, this study attempts to automate tunnel blast design by means of machine learning, a branch of artificial intelligence. For this, the data related to a blast design was collected from 25 tunnel design reports for learning as well as 2 additional reports for the test, and from which 4 design parameters, i.e., rock mass class, road type and cross sectional area of upper section as well as bench section as input data as well as16 design elements, i.e., blast cut type, specific charge, the number of drill holes, and spacing and burden for each blast hole group, etc. as output. Based on this design data, three machine learning models, i.e., XGBoost, ANN, SVM, were tested and XGBoost was chosen as the best model and the results show a generally similar trend to an actual design when assumed design parameters were input. It is not enough yet to perform the whole blast design using the results from this study, however, it is planned that additional studies will be carried out to make it possible to put it to practical use after collecting more sufficient blast design data and supplementing detailed machine learning processes.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.695-713
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• 2023

In coastal waters, phytoplankton,suspended particulate matter, and dissolved organic matter intricately and nonlinearly alter the reflectivity of seawater. Neural network technology, which has been rapidly advancing recently, offers the advantage of effectively representing complex nonlinear relationships. In previous studies, a three-stage neural network was constructed to extract the inherent optical properties of each component. However, this study proposes an algorithm that directly employs a deep neural network. The dataset used in this study consists of synthetic data provided by the International Ocean Color Coordination Group, with the input data comprising above-surface remote-sensing reflectance at nine different wavelengths. We derived inherent optical properties using this dataset based on a deep neural network. To evaluate performance, we compared it with a quasi-analytical algorithm and analyzed the impact of log transformation on the performance of the deep neural network algorithm in relation to data distribution. As a result, we found that the deep neural network algorithm accurately estimated the inherent optical properties except for the absorption coefficient of suspended particulate matter (R² greater than or equal to 0.9) and successfully separated the sum of the absorption coefficient of suspended particulate matter and dissolved organic matter into the absorption coefficient of suspended particulate matter and dissolved organic matter, respectively. We also observed that the algorithm, when directly applied without log transformation of the data, showed little difference in performance. To effectively apply the findings of this study to ocean color data processing, further research is needed to perform learning using field data and additional datasets from various marine regions, compare and analyze empirical and semi-analytical methods, and appropriately assess the strengths and weaknesses of each algorithm.