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Revision of Nutrition Quotient for Elderly in assessment of dietary quality and behavior (식사의 질과 식행동 평가를 위한 노인영양지수 개정 연구)

  • Lim, Young-Suk;Lee, Jung-Sug;Hwang, Ji-Yun;Kim, Ki-Nam;Hwang, Hyo-Jeong;Kwon, Sehyug;Kim, Hye-Young
    • Journal of Nutrition and Health
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    • v.55 no.1
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    • pp.155-173
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    • 2022
  • Purpose: This study was undertaken to update the Nutrition Quotient for Elderly (NQ-E), which reflects dietary quality and behavior among Korean older adults. Methods: The first 29 items of the measurable food behavior checklist were obtained from a previous NQ-E checklist, recent literature reviews, and national nutrition policies and recommendations. One-hundred subjects (50 men and 50 women) aged ≥ 65 years living in the Seoul Metropolitan Area, including Gyeonggi Province, completed a pilot survey from March to April 2021. Based on the results of the pilot study, we conducted factor analysis and frequency analysis to determine whether the items of the survey were properly organized and whether the distribution of answers for each evaluation item was properly distributed. As a result, we reduced the number of items on the food behavior checklist and used 23 items for the national survey. Nationwide, 1,000 subjects (472 men and 528 women) aged > 65 years, completed the checklist survey, which was applied using a face-to-face survey method from May to August 2021. The construct validity of the NQ-E 2021 was assessed using confirmatory factor analysis, LISREL. Results: Seventeen food behavior checklist items were selected for the final NQ-E 2021. Checklist items addressed three factors: balance (8 items), moderation (2 items), and practice (7 items). Standardized path coefficients were used as the weights of items to determine nutrition quotients. NQ-E and three-factor scores were calculated according to the weights of questionnaire items. Conclusion: The updated NQ-E 2021 produced by structural equation modelling provides a suitable tool for assessing the dietary quality and behavior of Korean older adults.

Comparison and evaluation of treatment plans using Abdominal compression and Continuous Positive Air Pressure for lung cancer SABR (폐암의 SABR(Stereotactic Ablative Radiotherapy)시 복부압박(Abdominal compression)과 CPAP(Continuous Positive Air Pressure)를 이용한 치료계획의 비교 및 평가)

  • Kim, Dae Ho;Son, Sang Jun;Mun, Jun Ki;Park, Jang Pil;Lee, Je Hee
    • The Journal of Korean Society for Radiation Therapy
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    • v.33
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    • pp.35-46
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    • 2021
  • Purpose : By comparing and analyzing treatment plans using abdominal compression and The Continuous Positive Air Pressure(CPAP) during SABR of lung cancer, we try to contribute to the improvement of radiotherapy effect. Materials & Methods : In two of the lung SABR patients(A, B patient), we developed a SABR plan using abdominal compression device(the Body Pro-Lok, BPL) and CPAP and analyze the treatment plan through homogeneity, conformity and the parameters proposed in RTOG 0813. Furthermore, for each phase, the X, Y, and Z axis movements centered on PTV are analyzed in all 4D CTs and compared by obtaining the volume and average dose of PTV and OAR. Four cone beam computed tomography(CBCT) were used to measure the directions from the center of the PTV to the intrathoracic contacts in three directions out of 0°, 90°, 180° and 270°, and compare the differences from the average distance values in each direction. Result : Both treatment plans obtained using BPL and CPAP followed recommendations from RTOG, and there was no significant difference in homogeneity and conformity. The X-axis, Y-axis, and Z-axis movements centered on PTV in patient A were 0.49 cm, 0.37 cm, 1.66 cm with BPL and 0.16 cm, 0.12 cm, and 0.19 cm with CPAP, in patient B were 0.22 cm, 0.18 cm, 1.03 cm with BPL and 0.14 cm, 0.11 cm, and 0.4 cm with CPAP. In A patient, when using CPAP compared to BPL, ITV decreased by 46.27% and left lung volume increased by 41.94%, and average dose decreased by 52.81% in the heart. In B patient, volume increased by 106.89% in the left lung and 87.32% in the right lung, with an average dose decreased by 44.30% in the stomach. The maximum difference of A patient between the straight distance value and the mean distance value in each direction was 0.05 cm in the a-direction, 0.05 cm in the b-direction, and 0.41 cm in the c-direction. In B patient, there was a difference of 0.19 cm in the d-direction, 0.49 cm in the e-direction, and 0.06 cm in the f-direction. Conclusion : We confirm that increased lung volume with CPAP can reduce doses of OAR near the target more effectively than with BPL, and also contribute more effectively to restriction of tumor movement with respiration. It is considered that radiation therapy effects can be improved through the application of various sites of CPAP and the combination with CPAP and other treatment machines.

A Study on the Influence of Workers' Aspiration for Academic Needs on Participation in University Education (근로자의 학업욕구 열망이 대학교육 참여에 미치는 영향에 관한 연구)

  • Lee, Ji-Hun;Mun, Bok-Hyun
    • Journal of Korea Entertainment Industry Association
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    • v.15 no.3
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    • pp.231-241
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    • 2021
  • This study intended to present strategies and implications for attracting new students and customized education to university officials through research on the participation of workers' academic aspirations in university education. Thus, variables were derived by analyzing prior data, and causal settings between variables and questionnaires were developed. Subject to the survey, 331 workers interested in participating in university education were collected through interpersonal interviews. The collected data were dataized, and reliability and feasibility verification and frequency analysis were conducted. Finally, we validate the fit of the structural equation model and the causal relationship for each concept. Therefore, the results of the validation show the following implications. First, university officials should be motivated by a mentor and mentee system with experienced people who have switched to a suitable vocational group through university education. It will also be necessary to develop and disseminate programs so that they can continue to develop themselves for the future. To this end, it will be necessary to help them understand their aptitude and strengths through consultation with experts. Second, university officials should strengthen public relations so that prospective students can know the cases and information of the job transformation of the admitted workers through recommendations. It will also be necessary to develop university education programs that can self-develop, accept various ideas through "public contest", and provide accurate information about university education to workers through re-processing. Third, university officials should provide workers with a program that allows them to catch two rabbits: job transformation and self-improvement through university education. In other words, it is necessary to stimulate the motivation of workers by providing various information such as visiting advanced overseas companies, obtaining various certificates, moving between departments of blue-collar and white-collar, and transfer opportunities. Fourth, university officials should actively promote university education programs related to this by participating in university education and receiving systematic education and the flow of social environment. Finally, university officials will need to consult and promote workers so that they can self-develop when they participate in college education, and they will have to figure out what they need for self-development through demand surveys and analysis.

Revision of Nutrition Quotient for Korean adults: NQ-2021 (한국 성인을 위한 영양지수 개정: NQ-2021)

  • Yook, Sung-Min;Lim, Young-Suk;Lee, Jung-Sug;Kim, Ki-Nam;Hwang, Hyo-Jeong;Kwon, Sehyug;Hwang, Ji-Yun;Kim, Hye-Young
    • Journal of Nutrition and Health
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    • v.55 no.2
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    • pp.278-295
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    • 2022
  • Purpose: This study was undertaken to revise and update the Nutrition Quotient (NQ) for Korean adults, a tool used to evaluate dietary quality and behavior. Methods: The first 31 items of the measurable food behavior checklist were adopted based on considerations of the previous NQ checklist, recent literature reviews, national nutrition policies, and recommendations. A pilot survey was conducted on 100 adults aged 19 to 64 residing in Seoul and Gyeonggi Province from March to April 2021 using a provisional 26- item checklist. Pilot survey data were analyzed using factor analysis and frequency analysis to determine whether checklist items were well organized and responses to questions were well distributed, respectively. As a result, the number of items on the food behavior checklist was reduced to 23 for the nationwide survey, which was administered to 1,000 adults (470 men and 530 women) aged 19 to 64 from May to August 2021. The construct validity of the developed NQ (NQ-2021) was assessed using confirmatory factor analysis, linear structural relations. Results: Eighteen items in 3 categories, that is, balance (8 items), moderation (6 items), and practice (4 items), were finally included in NQ-2021 food behavior checklist. 'Balance' items addressed the intake frequencies of essential foods, 'moderation' items the frequencies of unhealthy food intakes or behaviors, and 'practice' items addressed eating behaviors. Items and categories were weighted using standardized path coefficients to calculate NQ-2021 scores. Conclusion: The updated NQ-2021 appears to be suitable for easily and quickly assessing the diet qualities and behaviors of Korean adults.

Non-invasive Brain Stimulation and its Legal Regulation - Devices using Techniques of TMS and tDCS - (비침습적 뇌자극기술과 법적 규제 - TMS와 tDCS기술을 이용한 기기를 중심으로 -)

  • Choi, Min-Young
    • The Korean Society of Law and Medicine
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    • v.21 no.2
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    • pp.209-244
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    • 2020
  • TMS and tDCS are non-invasive devices that treat the diseases of patients or individual users, and manage or improve their health by applying stimulation to a brain through magnetism and electricity. The effect and safety of these devices have proved to be valid in several diseases, but research in this area is still much going on. Despite increasing cases of their application, legislations directly regulating TMS and tDCS are hard to find. Legal regulation regarding TMS and tDCS in the United States, Germany and Japan reveals that while TMS has been approved as a medical device with a moderate risk, tDCS has not yet earned approval as a medical device. However, the recent FDA guidance, European MDR changes, recalls in the US, and relevant legal provisions of Germany and Japan, as well as recommendations from expert groups all show signs of tDCS growing closer to getting approved as a medical device. Of course, safety and efficacy of tDCS can still be regulated as a general product instead of as a medical device. Considering multiple potential impacts on a human brain, however, the need for independent regulation is urgent. South Korea also lacks legal provisions explicitly regulating TMS and tDCS, but they fall into the category of the grade 3 medical devices according to the notifications of the Korean Ministry of Food and Drug Safety. And safety and efficacy of TMS are to be evaluated in compliance with the US FDA guidance. But no specific guidelines exist for tDCS yet. Given that tDCS devices are used in some hospitals in reality, and also at home by individual buyers, such a regulatory gap must quickly be addressed. In a longer term, legal system needs to be in place capable of independently regulating non-invasive brain stimulating devices.

Exploring the Priority Area of Policy-based Forest Road Construction using Spatial Information (공간정보를 활용한 산림정책 기반 임도시공 우선지역 선정 연구)

  • Sang-Wook, LEE;Chul-Hee, LIM
    • Journal of the Korean Association of Geographic Information Studies
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    • v.25 no.4
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    • pp.94-106
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    • 2022
  • In order to increase timber self-sufficiency, Korea's 6th Basic Forest Plan aims to increase the density of forest roads to 12.8 m ha-1 by 2037. However, due to rapid re-forestation, current management infrastructure is insufficient, with just 4.8 m ha-1 of forest roads in 2017. This is partly due to time and cost limitations on the process of forest road feasibility evaluation, which considers factors such as topography and forest conditions. To solve this problem, we propose an eco-friendly and efficient forest road network planning method using a geographic information system (GIS), which can evaluate a potential road site remotely based on spatial information. To facilitate such planning, this study identifies forest road construction priorities that can be evaluated using spatial information, such as topography, forest type and forest disasters. A method of predicting the optimal route to connect a forest road with existing roads is also derived. Overlapping analysis was performed using GIS-MCE (which combines GIS with multi-criteria evaluation), targeting the areas of Cheongsong-gun and Buk-gu, Pohang-si, which have a low forest-road density. Each factor affecting the suitability of a proposed new forest road site was assigned a cost, creating a cost surface that facilitates prioritization for each forest type. The forest path's optimal route was then derived using least-cost path analysis. The results of this process were 30 forestry site recommendations in Cheongsong-gun and one in Buk-gu, Pohang-si; this would increase forest road density for the managed forest sites in Cheongsong-gun from 1.58 m ha-1 to 2.55 m ha-1. This evaluation method can contribute to the policy of increasing timber self-sufficiency by providing clear guidelines for selecting forest road construction sites and predicting optimal connections to the existing road network.

Estimation of Monthly Dissolved Inorganic Carbon Inventory in the Southeastern Yellow Sea (황해 남동부 해역의 월별 용존무기탄소 재고 추정)

  • KIM, SO-YUN;LEE, TONGSUP
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.27 no.4
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    • pp.194-210
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    • 2022
  • The monthly inventory of dissolved inorganic carbon (CT) and its fluxes were simulated using a box-model for the southeastern Yellow Sea, bordering the northern East China Sea. The monthly CT data was constructed by combining the observed data representing four seasons with the data adopted from the recent publications. A 2-box-model of the surface and deep layers was used, assuming that the annual CT inventory was at the steady state and its fluctuations due to the advection in the surface box were negligible. Results of the simulation point out that the monthly CT inventory variation between the surface and deep box was driven primarily by the mixing flux due to the variation of the mixed layer depth, on the scale of -40~35 mol C m-2 month-1. The air to sea CO2 flux was about 2 mol C m-2 yr-1 and was lower than 1/100 of the mixing flux. The biological pump flux estimated magnitude, in the range of 4-5 mol C m-2 yr-1, is about half the in situ measurement value reported. The CT inventory of the water column was maximum in April, when mixing by cooling ceases, and decreases slightly throughout the stratified period. Therefore, the total CT inventory is larger in the stratified period than that of the mixing period. In order to maintain a steady state, 18 mol C m-2 yr-1 (= 216 g C m-2 yr-1), the difference between the maximum and minimum monthly CT inventory, should be transported out to the East China Sea. Extrapolating this flux over the entire southern Yellow Sea boundary yields 4 × 109 g C yr-1. Conceptually this flux is equivalent to the proposed continental shelf pump. Since this flux must go through the vast shelf area of the East China Sea before it joins the open Pacific waters the actual contribution as a continental shelf pump would be significantly lower than reported value. Although errors accompanied the simple box model simulation imposed by the paucity of data and assumptions are considerably large, nevertheless it was possible to constrain the relative contribution among the major fluxes and their range that caused the CT inventory variations, and was able to suggest recommendations for the future studies.

A Generalized Adaptive Deep Latent Factor Recommendation Model (일반화 적응 심층 잠재요인 추천모형)

  • Kim, Jeongha;Lee, Jipyeong;Jang, Seonghyun;Cho, Yoonho
    • Journal of Intelligence and Information Systems
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    • v.29 no.1
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    • pp.249-263
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    • 2023
  • Collaborative Filtering, a representative recommendation system methodology, consists of two approaches: neighbor methods and latent factor models. Among these, the latent factor model using matrix factorization decomposes the user-item interaction matrix into two lower-dimensional rectangular matrices, predicting the item's rating through the product of these matrices. Due to the factor vectors inferred from rating patterns capturing user and item characteristics, this method is superior in scalability, accuracy, and flexibility compared to neighbor-based methods. However, it has a fundamental drawback: the need to reflect the diversity of preferences of different individuals for items with no ratings. This limitation leads to repetitive and inaccurate recommendations. The Adaptive Deep Latent Factor Model (ADLFM) was developed to address this issue. This model adaptively learns the preferences for each item by using the item description, which provides a detailed summary and explanation of the item. ADLFM takes in item description as input, calculates latent vectors of the user and item, and presents a method that can reflect personal diversity using an attention score. However, due to the requirement of a dataset that includes item descriptions, the domain that can apply ADLFM is limited, resulting in generalization limitations. This study proposes a Generalized Adaptive Deep Latent Factor Recommendation Model, G-ADLFRM, to improve the limitations of ADLFM. Firstly, we use item ID, commonly used in recommendation systems, as input instead of the item description. Additionally, we apply improved deep learning model structures such as Self-Attention, Multi-head Attention, and Multi-Conv1D. We conducted experiments on various datasets with input and model structure changes. The results showed that when only the input was changed, MAE increased slightly compared to ADLFM due to accompanying information loss, resulting in decreased recommendation performance. However, the average learning speed per epoch significantly improved as the amount of information to be processed decreased. When both the input and the model structure were changed, the best-performing Multi-Conv1d structure showed similar performance to ADLFM, sufficiently counteracting the information loss caused by the input change. We conclude that G-ADLFRM is a new, lightweight, and generalizable model that maintains the performance of the existing ADLFM while enabling fast learning and inference.

Export Prediction Using Separated Learning Method and Recommendation of Potential Export Countries (분리학습 모델을 이용한 수출액 예측 및 수출 유망국가 추천)

  • Jang, Yeongjin;Won, Jongkwan;Lee, Chaerok
    • Journal of Intelligence and Information Systems
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    • v.28 no.1
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    • pp.69-88
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    • 2022
  • One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.

The Change in Participation Patterns in Play Activities of Children with Autism Spectrum Disorder during COVID-19: A Scoping Review (COVID-19로 인한 자폐스펙트럼 장애아동의 놀이 활동 참여 변화: 주제범위 문헌고찰)

  • Kim, Hyang-Won;Song, Ye-Ji;Kang, Seong-Hyeon;Won, Ha-Eun;Jeong, Yun-Wha
    • The Journal of Korean Academy of Sensory Integration
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    • v.21 no.1
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    • pp.59-73
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    • 2023
  • Objective : To examine changes in participation patterns of children with Autism Spectrum Disorder (ASD) in play activities during COVID-19 by reviewing relevant literature. Methods : This scoping review was conducted via five steps. we created a research question and searched for relevant literature published in English through CINAHL, PubMed, ERIC, MEDLINE, Google Scholar and Google search engine. After selecting the literature based on inclusion criteria, data were charted based on 10 items (i.e., author name, journal name, publication year, nation, authors' majors, research method, participant' age and gender as well as quantitative and qualitative results of study). The results were analyzed using descriptive numerical and thematic analyses. Results : After reviewing 437 articles and 152 websites, six articles were included. Theses articles were conducted by experts from various fields and countries. Five themes were highlighted in selected articles: COVID-19 resulted in (1) decreased time of outdoor play, (2) increased play time on screen, (3) increased time spent with family, (4) increased sensory difficulties, and (5) recommendations for services for children with disabilities and during COVID-19. Conclusion : This study suggests telerehabilitation programs about parental behavior strategies in order to solve difficulties in which children with ASD may experience when participating in play activities during disasters. Study results can be used as fundamental evidence to emphasize importance of play activities and to systematize role of occupational therapists and service guidelines for supporting play activities of children with disabilities in disasters.