• Pediatric Infection and Vaccine
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• v.30 no.3
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• pp.139-144
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• 2023

Purpose: Children with incomplete Kawasaki disease (KD) and pyuria may be misdiagnosed with urinary tract infection (UTI) during the early phase of the prodrome. We investigated the percentage of UTI diagnoses preceding a KD diagnosis. Methods: Using the National Health Insurance data of South Korea, we assessed differences in UTI diagnoses made during the week preceding a KD diagnosis, according to demographic and geographic factors from November 2007-October 2019. Results: A total of 53,822 KD cases were identified, including 304 patients (0.56%) diagnosed with a UTI during the week preceding a KD diagnosis. The younger age group (0-11 months) showed the highest percentage of preceding UTI diagnoses (0.95%), with higher odds than 4-year-old children (3.12; 95% confidence interval, 2.05-4.77). Conclusions: These findings suggest a potentially misleading presentation of incomplete KD, a clinical conundrum requiring further investigation and validation, particularly in infants.

• Korean Journal of Cognitive Science
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• v.35 no.1
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• pp.23-48
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• 2024

Building human-aligned artificial intelligence (AI) for social support remains challenging despite the advancement of Large Language Models. We present a novel method, the Chain of Empathy (CoE) prompting, that utilizes insights from psychotherapy to induce LLMs to reason about human emotional states. This method is inspired by various psychotherapy approaches-Cognitive-Behavioral Therapy (CBT), Dialectical Behavior Therapy (DBT), Person-Centered Therapy (PCT), and Reality Therapy (RT)-each leading to different patterns of interpreting clients' mental states. LLMs without CoE reasoning generated predominantly exploratory responses. However, when LLMs used CoE reasoning, we found a more comprehensive range of empathic responses aligned with each psychotherapy model's different reasoning patterns. For empathic expression classification, the CBT-based CoE resulted in the most balanced classification of empathic expression labels and the text generation of empathic responses. However, regarding emotion reasoning, other approaches like DBT and PCT showed higher performance in emotion reaction classification. We further conducted qualitative analysis and alignment scoring of each prompt-generated output. The findings underscore the importance of understanding the emotional context and how it affects human-AI communication. Our research contributes to understanding how psychotherapy models can be incorporated into LLMs, facilitating the development of context-aware, safe, and empathically responsive AI.

• Journal of Korean Elementary Science Education
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• v.43 no.1
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• pp.185-200
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• 2024

This study explored the changes in the elementary science teaching expertise of teachers who participated in an in-school professional learning community for elementary science instructional research. Six elementary school teachers from grades 4, 5, and 6 at an 18-class S elementary school in a medium-sized city in Chungcheongbuk-do conducted collaborative instructional research on elementary science lessons as part of an in-school professional learning community, which was held 26 times over 7 months in 2020. During the professional learning community, video and audio recordings of the activities, research lessons, course materials, and professional learning community reflection activities were collected for analysis. The collected data were analyzed using qualitative research methods; data processing, reading, note-taking, description, classification, interpretation, reporting, and visualization; and the instructional professionalism elements were extracted based on the instructional professionalism framework. In the early professional learning community activity stages, the participating teachers first discussed their teaching perspectives, their experiences, and their goals for teaching science, which resulted in a selection of research questions. The teachers then collaboratively designed and implemented research lessons for each grade level, after which lesson reflections were conducted. The teachers' abilities to engage in qualitative reflection on the research questions improved after each reflection iteration. It was found that this professional learning community collaborative lesson study experience positively contributed to teaching expertise development. Based on the study findings, the implications for using professional learning communities to improve elementary teachers' science teaching expertise are given.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.1363-1373
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• 2009

본 연구는 두 집단지성의 가장 대표적인 서비스인 네이버 지식iN과 위키피디아의 구조적, 경험적 차이를 바탕으로 생산의 차원에서 생산 주기, 생산 참여자, 생산물의 모델을 설정하고, 새롭게 탄생하는 지식을 중심으로 검증함으로써 최종 지식 소비 행위를 반영한 각각의 종합모델을 도출하였다. 우리는 웹에서 집단지성의 일상화를 확인할 수 있다. 지식 획득 매체가 매스미디어에서 인터넷으로 변화하는 과정에서 등장한 포털 및 검색사이트는 지식의 생산이 전문가패러다임에서 소비자 중심으로 재편될 수 있는 가능성을 열어주었다. 그리고 이러한 생산 방식의 변화는 '지식'의 개념 역시 변화시키고 있다. 즉, 집단지성이라는 새로운 웹2.0의 현상이 지식생산방식을 변화시키고 변화된 지식생산방식은 '지식'자체를 변화시킨다는 이론적 가설을 도출할 수 있는 것이다. 본 연구는 이러한 새로운 현상들을 분석하기 위해서는 먼저 보다 엄밀하게 집단지성의 개념을 규정할 필요성에 출발하였다. 현재 집단지성이라는 이름으로 불리면서 급격히 성장하고 있는 위키 방식의 인터넷 서비스와 지식검색 방식의 인터넷 서비스를 비교함으로써 보다 정교한 집단지성의 모델을 구축하고자 하였다. 위키형 집단지성과 지식검색형 집단지성의 차이점은 경험적으로도 뚜렷하게 확인할 수 있다. 본 연구는 이러한 경험적 차이와 기존의 문헌에서 밝혀진 사실들을 바탕으로 두 서비스의 지식생산 방식을 생산플로우, 생산참여자 성향, 생산물(지식)의 성향과 같이 세 영역으로 나누어 각각의 가설 모델을 설정하고 이 모델을 선정된 질의어를 바탕으로 검증한 뒤에 최종적인 모델을 도출하는 방식으로 진행되었다. 지식검색형 집단지성은 '질문-답변-채택'의 구조이고, 그 구조 속에서 '질문기-답변기-순서화기'를 거쳐 하나의 지식 덩어리인 'K-let'을 생산한다. 생산된 'K-let'들은 지식검색서비스의 데이터베이스에 축적되고, 이는 공통된 질의어를 기준으로 소비자들에 의해서 검색되어 소비된다. 하나의 질문에 대해 여러 개의 답변들이 존재하고, 답변자의 성향은 크게 전문성과 체계성을 바탕으로 한 전문가형 답변자와 경험적이고 의견지향적인 대화형 답변자로 나눠진다. 다수의 네티즌들의 참여에 의해서 지식의 생산이 진행되므로 질문의 성향 역시 사실, 의견, 경험 등 다양한 스펙트럼을 가지는 모델로 설정하였다. 반면에 위키형 집단지성은 개방형 플랫폼을 바탕으로 한 백과사전의 형식이며, 이러한 형식 속에서 최초의 개념어 등록과 다수의 편집활동을 거치면서 완성되지 않는 하나의 아티클인 'W-let'을 생산한다. 이러한 'W-let'은 생성 초기에 소수에 의한 활발한 내용 입력 활동으로 어느 정도의 안정화를 거친 후에는 꾸준한 다수의 수정활동을 통해서 'W-let'의 생명력을 유지함으로써 지식의 실제적인 변화를 반영한다. 생산된 'W-let'들은 위키형 집단지성 서비스의 데이터베이스에 축적되고, 이것들은 내부링크를 통해서 모두 연결되어 있다. 백과사전 형식으로 하나의 개념어를 설명하는 하나의 아티클은 오로지 사실적인 지식들로만 구성되나 내부링크와 외부링크를 통해서 다양한 스펙트럼을 가지는 모델로 설정하였다. 위와 같이 설정된 모델을 바탕으로 공통된 질의어 및 개념어를 선정하여 각각의 서비스에 노출시켰다. 이를 통해서 얻어진 각 서비스의 데이터베이스에 축적된 모든 데이터들 중에서 일정한 기간을 기준으로 각각의 모델 검증에 필요한 데이터를 추출하여 분석하는 방식으로 진행되었다. 그 결과 지식검색형 집단지성에서는 '질문-답변-채택'의 생산 구조 속에 다수가 참여하여 질문-채택답변-기타답변으로 배열되어 있는 완성된 형태의 K-let들을 지속적으로 생산하며 비슷한 성향을 가진 K-let들이 반복적으로 생산되어 지식검색 데이터베이스에 누적된다. 지식 소비자들은 질의어 검색을 통해서 다양한 K-let들을 선택하여 비교, 검토한 후에 선택된 K-let들의 배열은 해체되어 소비자들에 의해서 재배열됨을 발견할 수 있었다. 이에 지식검색형 집단지성이란 다수의 의해서 생산되고 누적된 지식들이 소비자의 검색과 선택에 의해 해체되어 재배열되는 지식의 맞춤화 과정이라고 정의내릴 수 있었다. 반면에 위키형 집단지성에서는 '내용입력-미세수정' 구조 속에서 생명력 있는 W-let을 생성한다. W-let은 백과사전처럼 정리되어 내부링크를 통해서 서로 연결되고, 외부링크를 통해 확장되고, 지식소비자들은 검색을 통해 최초의 W-let에 도달한 후에 링크를 선택함으로써 지식을 확장시킴을 검증할 수 있었다. 따라서 위키형 집단지성이란 다수의 의해서 생산되고 정리된 지식들이 소비자의 검색과 링크에 의해 무한히 확장되는 지식의 확대 재생산되는 과정이라고 정의 내릴 수 있다. 결국, 현재의 집단지성이란 지식이 다수의 참여로 생산됨으로써 개인에게 맞춤화되고, 끊임없이 확대 재생산되는 과정을 의미한다. 그리고 이러한 집단지성의 방식은 지식이라는 현재의 차원을 넘어서 정치, 경제를 비롯한 사회의 전 영역으로 점차적으로 확대되어갈 것이다. 앞으로 연구들은 두 가지 모델이 혼재되어 있는 현재의 집단지성이 어떠한 새로운 모델을 만들면서 다른 영역으로 확장되어갈 것인지에 대해서 초점을 맞춰 나가야할 것이다.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.175-190
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• 2018

Recently, policy of the marine advanced countries were switched from the preemption using ocean to post-project development. In this study, we suggest improvement and the pending issues when are deducted to the database of the marine spatial information is constructed over the GIS system for the Korean Marine Spatial Planning (KMSP). More than 250 spatial information in the seas of Korea were processed in order of data collection, GIS transformation, data analysis and processing, data grouping, and space mapping. It's process had some problem occurred to error of coordinate system, digitizing process for lack of the spatial information, performed by overlapping for the original marine spatial information, and so on. Moreover, solution is needed to data processing methods excluding personal information which is necessary when produce the spatial data for analysis of the used marine status and minimized method for different between the spatial information based GIS system and the based real information. Therefore, collection and securing system of lacking marine spatial information is enhanced for marine spatial planning. it is necessary to link and expand marine fisheries survey system. It is needed to the marine spatial planning. The marine spatial planning is required to the evaluation index of marine spatial and detailed marine spatial map. In addition, Marine spatial planning is needed to standard guideline and system of quality management. This standard guideline generate to phase for production, processing, analysis, and utilization. Also, the quality management system improve for the information quality of marine spatial information. Finally, we suggest necessity need for the depths study which is considered as opening extension of the marine spatial information and deduction on application model.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.6
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• pp.16-24
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• 2020

The purpose of this study is to analyze the usage behavior of Seoullo 7017, the first public garden in Korea, to understand the usage status by analyzing blogs, and to present usage behavior and improvement plans for Seoullo 7017. From June 2017 to May 2020, after Seoullo 7017 was open to citizens, character data containing 'Seoullo 7017' in the title and contents of NAVER and·DAUM blogs were converted to text mining and socialization, a Big Data technique. The analysis was conducted using social network analysis. The summary of the research results is as follows. First of all, the ratio of men and women searching for Seoullo 7017 online is similar, and the regions that searched most are in the order of Seoul and Gyeonggi, and those in their 40s and 50s were the most interested. In other words, it can be seen that there is a lack of interest in regions other than Seoul and Gyeonggi and among those in their 10s, 20s, and 30s. The main behaviors of Seoullo 7017 are' night view' and 'walking', and the factors that affect culture and art are elements related to culture and art. If various programs and festivals are opened and actively promoted, the main behavior will be more varied. On the other hand, the main behavior that the users of Seoullo 7017 want is 'sit', which is a static behavior, but the physical conditions are not sufficient for the behavior to occur. Therefore, facilities that can cause sitting behavior, such as shades and benches must be improved to meet the needs of visitors. The peculiarity of the change in the behavior of Seoullo 7017 is that it is recognized as a good place to travel alone and a good place to walk alone as a public multi-use facility and group activities are restricted due to COVID-19. Accordingly, in a situation like the COVD-19 pandemic, more diverse behaviors can be derived in facilities where people can take a walk, etc., and the increase of various attractions and the satisfaction of users can be increased. Seoullo 7017, as Korea's first public pedestrian area, was created for urban regeneration and the efficient use of urban resources in areas beyond the meaning of public spaces and is a place with various values such as history, nature, welfare, culture, and tourism. However, as a result of the use behavior analysis, various behaviors did not occur in Seoullo 7017 as expected, and elements that hinder those major behaviors were derived. Based on these research results, it is necessary to understand the usage behavior of Seoullo 7017 and to establish a plan for spatial system and facility improvement, so that Seoullo 7017 can be an important place for urban residents and a driving force to revitalize the city.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1159-1172
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• 2020

This study applied deep convolution neural network based on U-Net and SegNet using long period weather radar data to very short-term rainfall prediction. And the results were compared and evaluated with the translation model. For training and validation of deep neural network, Mt. Gwanak and Mt. Gwangdeoksan radar data were collected from 2010 to 2016 and converted to a gray-scale image file in an HDF5 format with a 1km spatial resolution. The deep neural network model was trained to predict precipitation after 10 minutes by using the four consecutive radar image data, and the recursive method of repeating forecasts was applied to carry out lead time 60 minutes with the pretrained deep neural network model. To evaluate the performance of deep neural network prediction model, 24 rain cases in 2017 were forecast for rainfall up to 60 minutes in advance. As a result of evaluating the predicted performance by calculating the mean absolute error (MAE) and critical success index (CSI) at the threshold of 0.1, 1, and 5 mm/hr, the deep neural network model showed better performance in the case of rainfall threshold of 0.1, 1 mm/hr in terms of MAE, and showed better performance than the translation model for lead time 50 minutes in terms of CSI. In particular, although the deep neural network prediction model performed generally better than the translation model for weak rainfall of 5 mm/hr or less, the deep neural network prediction model had limitations in predicting distinct precipitation characteristics of high intensity as a result of the evaluation of threshold of 5 mm/hr. The longer lead time, the spatial smoothness increase with lead time thereby reducing the accuracy of rainfall prediction The translation model turned out to be superior in predicting the exceedance of higher intensity thresholds (> 5 mm/hr) because it preserves distinct precipitation characteristics, but the rainfall position tends to shift incorrectly. This study are expected to be helpful for the improvement of radar rainfall prediction model using deep neural networks in the future. In addition, the massive weather radar data established in this study will be provided through open repositories for future use in subsequent studies.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.5
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• pp.69-79
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• 2022

This study aims to assess the current understanding of the landscape of wind power facilities as renewable energy sources that supply sightseeing, tourism, and other opportunities. Therefore, social media data related to the landscape of wind power facilities experienced by visitors from different regions was analyzed. The analysis results showed that the common characteristics of the landscape of wind power facilities are based on the scale of wind power facilities, the distance between overlook points of wind power facilities, the visual openness of the wind power facilities from the overlook points, and the terrain where the wind power facilities are located. In addition, the preference for wind power facilities is higher in places where the shape of wind power facilities and the surrounding landscape can be clearly seen- flat ground or the sea are considered better landscapes. Negative keywords about the landscape appear on Gade Mountain in Taibai, Meifeng Mountain in Taibai, Taiqi Mountain, and Gyeongju Wind Power Generation Facilities on Gyeongshang Road in Gangwon. The keyword 'negation' occurs when looking at wind power facilities at close range. Because of the high angle of the view, viewers can feel overwhelmed seeing the size of the facility and the ridge simultaneously, feeling psychological pressure. On the contrary, positive landscape adjectives are obtained from wind power facilities on flat ground or the sea. Visitors think that the visual volume of the landscape is fully ensured on flat ground or the sea, and it is a symbolic element that can represent the site. This study analyzes landscape awareness based on the opinions of visitors who have experienced wind power facilities. However, wind power facilities are built in different areas. Therefore, landscape characteristics are different, and there are many variables, such as viewpoints and observers, so the research results are difficult to popularize and have limitations. In recent years, landscape damage due to the construction of wind power facilities has become a hot issue, and the domestic methods of landscape evaluation of wind power facilities are unsatisfactory. Therefore, when evaluating the landscape of wind power facilities, the scale of wind power facilities, the inherent natural characteristics of the area where wind power facilities are set up, and the distance between wind power facilities and overlook points are important elements to consider. In addition, wind power facilities are set in the natural environment, which needs to be protected. Therefore, from the landscape perspective, it is necessary to study the landscape of wind power facilities and the surrounding environment.

• Journal of Practical Agriculture & Fisheries Research
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• v.4 no.1
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• pp.128-137
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• 2002

This study was conducted to develop the heat exchanger by utilizing the heat energy of underground water(15℃), which might be used for cooling and heating system of the agricultural facilities. We developed the heat exchanger by using the parallel type plat fin tube made of Aluminum(Al 6063), which was named Aloo-Heat(No. 0247164, offered by Korean Intellectual property Office). The trial manufactures were made from Aloo-heat which was 600mm, 700mm length respectively, and It were welded to the end "U" type in order to direct flow of the underground water. The performance test was carried out under the condition of open space and room temperature with the change of flow rate of the underground water and air. The results are as follows. 1. The trial manufactures had convection heat value from 33 to 156 W/m²℃, and It was coincided with design assumption. 2. The amount of energy transfer was increased with the increment of the area of heat transfer, the air flow, the gap of temperature inlet & outlet the underground water and the air. 3. The heat value was 6,825W when the air flow was 6,000m³/h and the gap of temperature between inlet and outlet of the underground water was 6℃, and It dropped from 25.8℃ to 23.2℃(-2.6℃ difference). The convection heat value was 88.5W/m²℃. 4. The heat value was 2.625W when the air flow was 4,000m³/h and the gap of temperature between inlet and outlet the underground water was 2℃, and It dropped from 27℃ to 22.5℃(-4.5℃ difference). The convection heat value was 33.6W/m²℃. 5. Correlation values(R²) of the testing heat values of the trial manufacture type I, II, and III were 0.9141, 0.8935, and 0.9323 respectively, and correlation values(R²) of the amount of the air flow 6,000m³/h, 5,000m³/h, 4,000m³/h were 0.9513, 0.9414, and 0.9003 respectively.

• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.1
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• pp.11-21
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• 2023

This study was conducted to estimate the damage of Whole Crop Corn (WCC; Zea Mays L.) according to abnormal climate using machine learning as the Representative Concentration Pathway (RCP) 4.5 and present the damage through mapping. The collected WCC data was 3,232. The climate data was collected from the Korea Meteorological Administration's meteorological data open portal. The machine learning model used DeepCrossing. The damage was calculated using climate data from the automated synoptic observing system (ASOS, 95 sites) by machine learning. The calculation of damage was the difference between the dry matter yield (DMY)_normal and DMY_abnormal. The normal climate was set as the 40-year of climate data according to the year of WCC data (1978-2017). The level of abnormal climate by temperature and precipitation was set as RCP 4.5 standard. The DMY_normal ranged from 13,845-19,347 kg/ha. The damage of WCC which was differed depending on the region and level of abnormal climate where abnormal temperature and precipitation occurred. The damage of abnormal temperature in 2050 and 2100 ranged from -263 to 360 and -1,023 to 92 kg/ha, respectively. The damage of abnormal precipitation in 2050 and 2100 was ranged from -17 to 2 and -12 to 2 kg/ha, respectively. The maximum damage was 360 kg/ha that the abnormal temperature in 2050. As the average monthly temperature increases, the DMY of WCC tends to increase. The damage calculated through the RCP 4.5 standard was presented as a mapping using QGIS. Although this study applied the scenario in which greenhouse gas reduction was carried out, additional research needs to be conducted applying an RCP scenario in which greenhouse gas reduction is not performed.