• Title/Summary/Keyword: Term Mapping

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Effects of Physical Environment on Quality of Life among Residents with Dementia in Long-Term Care Facilities in Canada and Sweden: A longitudinal study in a large-scale institutional setting versus a small-scale homelike setting

  • Lee, Sook Young;Hung, Lillian;Chaudhury, Habib;Morelli, Agneta
    • Architectural research
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    • v.23 no.2
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    • pp.19-28
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    • 2021
  • Reduction in competence makes older adults with dementia more sensitive to the influence of the physical environment. The aim of the longitudinal study was to examine whether residents with dementia in long-term facilities with variability in physical environmental characteristics in Vancouver (N= 11), Canada and Stockholm (N=13), Sweden had a difference in their quality of life (QoL). QoL was assessed using Dementia Care Mapping tool three times over one year for the reliability of data. The results of the study demonstrated that the residents with dementia living in a homelike and positive stimulating setting showed less withdrawn behaviors and a higher level of well-being compared to those in a large-scale institutional setting. This study also found that the residents living in a large-scale institutional environment spent more monotonous times than the other groups, which may be to provision of fewer structured activity programs or less social interaction with neighbors or staff members. Residents living in a large-scale institutional setting in Canada showed so far as five times more agitated/ distressed behaviors and twice more withdrawal compared to the ones living in a small-scale homelike setting in Sweden. The study supports that the large-scale institutional environment was considerably associated with levels of lower quality of life among the residents with dementia.

A study on Mapping the Unicode based Hangul-Hanja for prescription names in Korean Medicine (처방명 연계를 위한 유니코드 한자 기반의 한글-한자 매핑정보 구축에 관한 연구)

  • Jeon, Byoung-Uk;Kim, An-Na;Kim, Ji-Young;Oh, Yong-Taek;Kim, Chul;Song, Mi-Young;Jang, Hyun-Chul
    • Korean Journal of Oriental Medicine
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    • v.18 no.3
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    • pp.133-139
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    • 2012
  • Objective : UMLS is 'Ontology' which establishes the database for medical terminology by gathering various medical vocabularies representing same fundamental concepts. Method : Although Chinese character are represented in the Chinese part of Korean Unicode system in a computer, writing of Chinese characters is vary depending on Chinese input systems and Chinese writers' levels of knowledge. As the result of this, representation of Chinese writing in a computer will be considerably different from an old Chinese document. Therefore, a meaningful relationship between digital Chinese terminology and translated Korean is necessary in order to build Ontology for Chinese medical terms from Oriental medical prescription in a computer system. Result : This research will present 1:1 mapping information among the Chinese characters used in the Oriental medical prescription with analysis of 'same character different sound' and 'same meaning different shape' in Chinese part of Unicode systems. Conclusions : Furthermore, the research will provide top-down menu of relationship between Chinese term and Korean term in medical prescription with assumption of that the Oriental medical prescription has its own unique meaning.

FIRE PROPAGATION EQUATION FOR THE EXPLICIT IDENTIFICATION OF FIRE SCENARIOS IN A FIRE PSA

  • Lim, Ho-Gon;Han, Sang-Hoon;Moon, Joo-Hyun
    • Nuclear Engineering and Technology
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    • v.43 no.3
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    • pp.271-278
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    • 2011
  • When performing fire PSA in a nuclear power plant, an event mapping method, using an internal event PSA model, is widely used to reduce the resources used by fire PSA model development. Feasible initiating events and component failure events due to fire are identified to transform the fault tree (FT) for an internal event PSA into one for a fire PSA using the event mapping method. A surrogate event or damage term method is used to condition the FT of the internal PSA. The surrogate event or the damage term plays the role of flagging whether the system/component in a fire compartment is damaged or not, depending on the fire being initiated from a specified compartment. These methods usually require explicit states of all compartments to be modeled in a fire area. Fire event scenarios, when using explicit identification, such as surrogate or damage terms, have two problems: (1) there is no consideration of multiple fire propagation beyond a single propagation to an adjacent compartment, and (2) there is no consideration of simultaneous fire propagations in which an initiating fire event is propagated to multiple paths simultaneously. The present paper suggests a fire propagation equation to identify all possible fire event scenarios for an explicitly treated fire event scenario in the fire PSA. Also, a method for separating fire events was developed to make all fire events a set of mutually exclusive events, which can facilitate arithmetic summation in fire risk quantification. A simple example is given to confirm the applicability of the present method for a $2{\times}3$ rectangular fire area. Also, a feasible asymptotic approach is discussed to reduce the computational burden for fire risk quantification.

Semantic-based Keyword Search System over Relational Database (관계형 데이터베이스에서의 시맨틱 기반 키워드 탐색 시스템)

  • Yang, Younghyoo
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.12
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    • pp.91-101
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    • 2013
  • One issue with keyword search in general is its ambiguity which can ultimately impact the effectiveness of the search in terms of the quality of the search results. This ambiguity is primarily due to the ambiguity of the contextual meaning of each term in the query. In addition to the query ambiguity itself, the relationships between the keywords in the search results are crucial for the proper interpretation of the search results by the user and should be clearly presented in the search results. We address the keyword search ambiguity issue by adapting some of the existing approaches for keyword mapping from the query terms to the schema terms/instances. The approaches we have adapted for term mapping capture both the syntactic similarity between the query keywords and the schema terms as well as the semantic similarity of the two and give better mappings and ultimately 50% raised accurate results. Finally, to address the last issue of lacking clear relationships among the terms appearing in the search results, our system has leveraged semantic web technologies in order to enrich the knowledgebase and to discover the relationships between the keywords.

Development and Lessons Learned of Clinical Data Warehouse based on Common Data Model for Drug Surveillance (약물부작용 감시를 위한 공통데이터모델 기반 임상데이터웨어하우스 구축)

  • Mi Jung Rho
    • Korea Journal of Hospital Management
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    • v.28 no.3
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    • pp.1-14
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    • 2023
  • Purposes: It is very important to establish a clinical data warehouse based on a common data model to offset the different data characteristics of each medical institution and for drug surveillance. This study attempted to establish a clinical data warehouse for Dankook university hospital for drug surveillance, and to derive the main items necessary for development. Methodology/Approach: This study extracted the electronic medical record data of Dankook university hospital tracked for 9 years from 2013 (2013.01.01. to 2021.12.31) to build a clinical data warehouse. The extracted data was converted into the Observational Medical Outcomes Partnership Common Data Model (Version 5.4). Data term mapping was performed using the electronic medical record data of Dankook university hospital and the standard term mapping guide. To verify the clinical data warehouse, the use of angiotensin receptor blockers and the incidence of liver toxicity were analyzed, and the results were compared with the analysis of hospital raw data. Findings: This study used a total of 670,933 data from electronic medical records for the Dankook university clinical data warehouse. Excluding the number of overlapping cases among the total number of cases, the target data was mapped into standard terms. Diagnosis (100% of total cases), drug (92.1%), and measurement (94.5%) were standardized. For treatment and surgery, the insurance EDI (electronic data interchange) code was used as it is. Extraction, conversion and loading were completed. R language-based conversion and loading software for the process was developed, and clinical data warehouse construction was completed through data verification. Practical Implications: In this study, a clinical data warehouse for Dankook university hospitals based on a common data model supporting drug surveillance research was established and verified. The results of this study provide guidelines for institutions that want to build a clinical data warehouse in the future by deriving key points necessary for building a clinical data warehouse.

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Mapping the Potential Distribution of Raccoon Dog Habitats: Spatial Statistics and Optimized Deep Learning Approaches

  • Liadira Kusuma Widya;Fatemah Rezaie;Saro Lee
    • Proceedings of the National Institute of Ecology of the Republic of Korea
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    • v.4 no.4
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    • pp.159-176
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    • 2023
  • The conservation of the raccoon dog (Nyctereutes procyonoides) in South Korea requires the protection and preservation of natural habitats while additionally ensuring coexistence with human activities. Applying habitat map modeling techniques provides information regarding the distributional patterns of raccoon dogs and assists in the development of future conservation strategies. The purpose of this study is to generate potential habitat distribution maps for the raccoon dog in South Korea using geospatial technology-based models. These models include the frequency ratio (FR) as a bivariate statistical approach, the group method of data handling (GMDH) as a machine learning algorithm, and convolutional neural network (CNN) and long short-term memory (LSTM) as deep learning algorithms. Moreover, the imperialist competitive algorithm (ICA) is used to fine-tune the hyperparameters of the machine learning and deep learning models. Moreover, there are 14 habitat characteristics used for developing the models: elevation, slope, valley depth, topographic wetness index, terrain roughness index, slope height, surface area, slope length and steepness factor (LS factor), normalized difference vegetation index, normalized difference water index, distance to drainage, distance to roads, drainage density, and morphometric features. The accuracy of prediction is evaluated using the area under the receiver operating characteristic curve. The results indicate comparable performances of all models. However, the CNN demonstrates superior capacity for prediction, achieving accuracies of 76.3% and 75.7% for the training and validation processes, respectively. The maps of potential habitat distribution are generated for five different levels of potentiality: very low, low, moderate, high, and very high.

Evaluation of groundwater recharge rate for land uses at Mandae stream watershed using SWAT HRU Mapping module (SWAT HRU Mapping module을 이용한 해안면 만대천 유역의 토지이용별 지하수 함양량 평가)

  • Ryu, Jichul;Choi, Jae Wan;Kang, Hyunwoo;Kum, Donghyuk;Shin, Dong Suk;Lee, Ki Hwan;Jeong, Gyo-Cheol;Lim, Kyoung Jae
    • Journal of Korean Society on Water Environment
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    • v.28 no.5
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    • pp.743-753
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    • 2012
  • The hydrologic models, capable of simulating groundwater recharge for long-term period and effects on it of crops management in the agricultural areas, have been used to compute groundwater recharge in the agricultural fields. Among these models, the Soil and Water Assessment Tool (SWAT) has been widely used because it could interpret hydrologic conditions for the long time considering effects of weather condition, land uses, and soil. However the SWAT model couldn't represent the spatial information of Hydrologic Response Unit (HRU), the SWAT HRU mapping module was developed in 2010. With this capability, it is possible to assume and analyze spatio-temporal groundwater recharge. In this study, groundwater recharge of rate for various crops in the Mandae stream watershed was estimated using SWAT HRU Mapping module, which can simulate spato-temporal recharge rate. As a result of this study, Coefficient of determination ($R^2$) and Nash-Sutcliffe model efficiency (NSE) for flow calibration were 0.80 and 0.72, respectively, and monthly groundwater recharge of Mandae watershed in Haean-myeon was 381.24 mm/year. It was 28% of total precipitation in 2009. Groundwater recharge rate was 73.54 mm/month and 73.58 mm/month for July and August 2009, which is approximately 18 times of groundwater recharge rate for December 2009. The groundwater recharges for each month through the year were varying. The groundwater recharge was smaller in the spring and winter seasons, relatively. So, it is necessary to enforce proper management of groundwater recharge during droughty season. Also, the SWAT HRU Mapping module could show the result of groundwater recharge as a GIS map and analyze spatio-temporal groundwater recharge. So, this method, proposed in this study, would be quite useful to make groundwater management plans at agriculture-dominant watershed.

Material as a Key Element of Fashion Trend in 2010~2019 - Text Mining Analysis - (패션 트렌트(2010~2019)의 주요 요소로서 소재 - 텍스트마이닝을 통한 분석 -)

  • Jang, Namkyung;Kim, Min-Jeong
    • Fashion & Textile Research Journal
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    • v.22 no.5
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    • pp.551-560
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    • 2020
  • Due to the nature of fashion design that responds quickly and sensitively to changes, accurate forecasting for upcoming fashion trends is an important factor in the performance of fashion product planning. This study analyzed the major phenomena of fashion trends by introducing text mining and a big data analysis method. The research questions were as follows. What is the key term of the 2010SS~2019FW fashion trend? What are the terms that are highly relevant to the key trend term by year? Which terms relevant to the key trend term has shown high frequency in news articles during the same period? Data were collected through the 2010SS~2019FW Pre-Trend data from the leading trend information company in Korea and 45,038 articles searched by "fashion+material" from the News Big Data System. Frequency, correlation coefficient, coefficient of variation and mapping were performed using R-3.5.1. Results showed that the fashion trend information were reflected in the consumer market. The term with the highest frequency in 2010SS~2019FW fashion trend information was material. In trend information, the terms most relevant to material were comfort, compact, look, casual, blend, functional, cotton, processing, metal and functional by year. In the news article, functional, comfort, sports, leather, casual, eco-friendly, classic, padding, culture, and high-quality showed the high frequency. Functional was the only fashion material term derived every year for 10 years. This study helps expand the scope and methods of fashion design research as well as improves the information analysis and forecasting capabilities of the fashion industry.

Forecasting Ecosystem Changes in Virtual Reality Game Industry using Scenario Network Mapping (가상현실게임 산업의 생태계 변화 예측 및 대응 전략)

  • Rhee, Chang Seop;Rhee, Hyunjung
    • Journal of Korea Game Society
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    • v.18 no.2
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    • pp.15-26
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    • 2018
  • Virtual Reality(VR) is one of the most remarkable technologies in the current game industry. Nevertheless, it is difficult for the game industry to actively invest in the VR technology because of the technical problems to overcome and the uncertainty about the market possibility. Therefore, this study attempts to estimate the future possibilities of the VR game market in various angles. For the purpose, we explore the domestic game market from the past to the present, and forecast the game industry ecosystem using the Scenario Network Mapping. Based on the result, we propose a short and long term future prospect and suggest the possible strategies for each stakeholder of the VR game market.

Advances in Functional Connectomics in Neuroscience : A Focus on Post-Traumatic Stress Disorder (뇌과학 분야 기능적 연결체학의 발전 : 외상후스트레스장애를 중심으로)

  • Park, Shinwon;Jeong, Hyeonseok S.;Lyoo, In Kyoon
    • Korean Journal of Biological Psychiatry
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    • v.22 no.3
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    • pp.101-108
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    • 2015
  • Recent breakthroughs in functional neuroimaging techniques have launched the quest of mapping the connections of the human brain, otherwise known as the human connectome. Imaging connectomics is an umbrella term that refers to the neuroimaging techniques used to generate these maps, which recently has enabled comprehensive brain mapping of network connectivity combined with graph theoretic methods. In this review, we present an overview of the key concepts in functional connectomics. Furthermore, we discuss articles that applied task-based and/or resting-state functional magnetic resonance imaging to examine network deficits in post-traumatic stress disorder (PTSD). These studies have provided important insights regarding the etiology of PTSD, as well as the overall organization of the brain network. Advances in functional connectomics are expected to provide insight into the pathophysiology and the development of biomarkers for diagnosis and treatment of PTSD.