• Title/Summary/Keyword: Classification model

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Net Primary Production Changes over Korea and Climate Factors (위성영상으로 분석한 장기간 남한지역 순 일차생산량 변화: 기후인자의 영향)

  • Hong, Ji-Youn;Shim, Chang-Sub;Lee, Moung-Jin;Baek, Gyoung-Hye;Song, Won-Kyong;Jeon, Seong-Woo;Park, Yong-Ha
    • Korean Journal of Remote Sensing
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    • v.27 no.4
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    • pp.467-480
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    • 2011
  • Spatial and temporal variabilities of NPP(Net Primary Production) retrieved from two satellite instruments, AVHRR(Advanced Very High Resolution Radiometer, 1981-2000) and MODIS(MODerate-resolution Imaging Spectroradiometer, 2000-2006), were investigated. The range of mean NPP from A VHRR and MODIS were estimated to be 894-1068 $g{\cdot}C/m^2$/yr and 610-694.90 $g{\cdot}C/m^2$/yr, respectively. The discrepancy of NPP between the two instruments is about 325 $g{\cdot}C/m^2$/yr, and MODIS product is generally closer to the ground measurement than AVHRR despite the limitation in direct comparison such as spatial resolution and vegetation classification. The higher NPP values over South Korea are related to the regions with higher biomass (e.g., mountains) and higher annual temperature. The interannual NPP trends from the two satellite products were computed, and both mean annual trends show continuous NPP increase; 2.14 $g{\cdot}C/m^2$/yr from AVHRR(1981-2000) and 6.08 $g{\cdot}C/m^2$/yr from MODIS (2000-2006) over South Korea. Specifically, the higher increasing trends over the Southwestern region are likely due to the increasing productivity of crop fields from sufficient irrigation and fertilizer use. The retrieved NPP shows a closer relationship between monthly temperature and precipitation, which results in maximum correlation during summer monsoons. The difference in the detection wavelength and model schemes during the retrieval can make a significant difference in the satellite products, and a better accuracy in the meterological and land use data and modeling applications will be necessary to improve the satellite-based NPP data.

Chilling Requirement for Breaking of Internal Dormancy of Main Apple Cultivars in Korea (국내 사과 주요 품종들의 자발휴면 타파에 필요한 저온요구도)

  • Kweon, Hun-Joong;Sagong, Dong-Hoon;Song, Yang-Yik;Park, Moo-Yong;Kwon, Soon-Il;Kim, Mok-Jong
    • Horticultural Science & Technology
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    • v.31 no.6
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    • pp.666-676
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    • 2013
  • The study was carried out to examine the initial point of dormancy, breaking time of internal dormancy, and to find out the accumulated hours of low temperature (under $7.2^{\circ}C$ from $0.0^{\circ}C$ to $7.2^{\circ}C$) for bud-breaking. Over-all, the chilling requirement for breaking of internal dormancy in the commercial apple cultivars ('Fuji' and 'Tsugaru') and apple cultivars bred in Korea ('Hongro', 'Sunhong', 'Honggeum', 'Hongan', 'Hongso', 'Gamhong', 'Summer dream') at the Gunwi region for 4 years (from 2009 to 2012) was investigated. Also, the breaking time of internal dormancy in the field at the Gunwi region and the breaking time of dormancy if air temperature of Gunwi region rises $4^{\circ}C$ higher than the current one were investigated using the same data. The initial point of dormancy was set at the time when the lateral bud breaking did not occurred (when heading back cutting was done in the middle of terminal shoots). The occurrence of the breaking of internal dormancy was decided if the breaking of the terminal bud of bourse shoot occurred within 15 days or not in growth chamber. About 100 bourse shoots were collected by cultivar classification in early December every year and were stored at $5.0^{\circ}C$, and they were placed in growth chamber at one week interval. The chilling requirement of cultivars was expressed in accumulated hours in the field and in the growth chamber under $7.2^{\circ}C$ and $0.0-7.2^{\circ}C$ from the initial point of dormancy to the breaking time of internal dormancy. The results showed that the initial point of dormancy in selected cultivars could occur at the end of September. The breaking time of internal dormancy could occur from the end of January to the early of February. The accumulated hours under $7.2^{\circ}C$ for breaking of internal dormancy were 1,600-2,000 hours, while those of $0.0-7.2^{\circ}C$ were 1,300-1,800 hours. In comparing the different apple cultivars, the chilling requirement of the early flowering cultivars seemed lower than that of the late-flowering cultivars. Based on these results, if the air temperature of Gunwi region rises about $4.0^{\circ}C$ higher than the current one, the breaking time of internal dormancy will be delayed by 2-4 weeks.

Ecoclimatic Map over North-East Asia Using SPOT/VEGETATION 10-day Synthesis Data (SPOT/VEGETATION NDVI 자료를 이용한 동북아시아의 생태기후지도)

  • Park Youn-Young;Han Kyung-Soo
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.8 no.2
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    • pp.86-96
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    • 2006
  • Ecoclimap-1, a new complete surface parameter global database at a 1-km resolution, was previously presented. It is intended to be used to initialize the soil-vegetation- atmosphere transfer schemes in meteorological and climate models. Surface parameters in the Ecoclimap-1 database are provided in the form of a per-class value by an ecoclimatic base map from a simple merging of land cover and climate maps. The principal objective of this ecoclimatic map is to consider intra-class variability of life cycle that the usual land cover map cannot describe. Although the ecoclimatic map considering land cover and climate is used, the intra-class variability was still too high inside some classes. In this study, a new strategy is defined; the idea is to use the information contained in S10 NDVI SPOT/VEGETATION profiles to split a land cover into more homogeneous sub-classes. This utilizes an intra-class unsupervised sub-clustering methodology instead of simple merging. This study was performed to provide a new ecolimatic map over Northeast Asia in the framework of Ecoclimap-2 global database construction for surface parameters. We used the University of Maryland's 1km Global Land Cover Database (UMD) and a climate map to determine the initial number of clusters for intra-class sub-clustering. An unsupervised classification process using six years of NDVI profiles allows the discrimination of different behavior for each land cover class. We checked the spatial coherence of the classes and, if necessary, carried out an aggregation step of the clusters having a similar NDVI time series profile. From the mapping system, 29 ecosystems resulted for the study area. In terms of climate-related studies, this new ecosystem map may be useful as a base map to construct an Ecoclimap-2 database and to improve the surface climatology quality in the climate model.

Analysis of Utilization Characteristics, Health Behaviors and Health Management Level of Participants in Private Health Examination in a General Hospital (일개 종합병원의 민간 건강검진 수검자의 검진이용 특성, 건강행태 및 건강관리 수준 분석)

  • Kim, Yoo-Mi;Park, Jong-Ho;Kim, Won-Joong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.14 no.1
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    • pp.301-311
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    • 2013
  • This study aims to analyze characteristics, health behaviors and health management level related to private health examination recipients in one general hospital. To achieve this, we analyzed 150,501 cases of private health examination data for 11 years from 2001 to 2011 for 20,696 participants in 2011 in a Dae-Jeon general hospital health examination center. The cluster analysis for classify private health examination group is used z-score standardization of K-means clustering method. The logistic regression analysis, decision tree and neural network analysis are used to periodic/non-periodic private health examination classification model. 1,000 people were selected as a customer management business group that has high probability to be non-periodic private health examination patients in new private health examination. According to results of this study, private health examination group was categorized by new, periodic and non-periodic group. New participants in private health examination were more 30~39 years old person than other age groups and more patients suspected of having renal disease. Periodic participants in private health examination were more male participants and more patients suspected of having hyperlipidemia. Non-periodic participants in private health examination were more smoking and sitting person and more patients suspected of having anemia and diabetes mellitus. As a result of decision tree, variables related to non-periodic participants in private health examination were sex, age, residence, exercise, anemia, hyperlipidemia, diabetes mellitus, obesity and liver disease. In particular, 71.4% of non-periodic participants were female, non-anemic, non-exercise, and suspicious obesity person. To operation of customized customer management business for private health examination will contribute to efficiency in health examination center.

Development of the Korean version of Postconcussional Syndrome Questionnaire (한글판 뇌진탕후증후군 척도의 개발)

  • Yoon, Mi-Ri;Ko, Young-Hoon;Han, Chang-Su;Joe, Sook-Haeng;Jeon, Sang-Won;Han, Chang-Woo
    • Korean Journal of Psychosomatic Medicine
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    • v.23 no.1
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    • pp.26-35
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    • 2015
  • Objectives:The purpose of this study was to evaluate reliability and validity of the Korean version of the Postconcussional Syndrome Questionnaire(KPCSQ) which was originally developed in 1992 by Lees-Haley. Methods:Patients with traumatic brain injury were recruited from April 2009 to December 2011 from the Korean University Ansan Hospital. We selected patients that met the ICD-10 diagnostic criteria of postconcussional syndrome and organic mental disorder including organic mood disorder, organic emotionally labile disorder, organic anxiety disorder and organic personality disorder. The KPCSQ, Trait and State Anxiety Inventory(STAI-I, II), and Center for Epidemiologic Studies Depression Scale(CESD) were administered to all subjects. Factor analysis of the items were performed and test-retest correlation were evaluated. Internal consistency of the KPCSQ and its subscales was assessed with Cronbach's alpha. External validity of the KPCSQ were examined by correlation coefficient with the STAI-I, II, and CESD. Results:The Cronbach's alpha coefficient of the total PCSQ was 0.956. The test-retest reliability coefficient was 0.845. The PCSQ showed significant correlation with STAI-I, II and CESD. The factor analysis of the PCSQ yielded 4 factors model. Factor 1 represented 'affective and cognitive symptoms', factor 2 represented 'somatic symptoms', factor 3 represented 'infrequent symptoms' and factor 4 represented 'exaggeration or inattentive response'. There was no significant difference between the PCS group and the organic mental disorder group in the score on each measure. The scores on KPCSQ and its subscales in the subjects that had scored 5 or more in 'exaggeration or inattentive response' are significantly higher than those in the subjects had scored 4 in 'exaggeration or inattentive response'. Conclusions:This study suggests that the Korean version of PCSQ is a valid and reliable tool for assessing psychiatric symptomatology of patients with traumatic brain injury. Further investigations with greater numbers of subjects are necessary to assess the clinical usefulness of the KPCSQ.

A Study for the establishment environment of the Labor Archives (노동 아카이브(Labor Archives) 설립 환경에 관한 연구)

  • Kwak, Kun-Hong
    • The Korean Journal of Archival Studies
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    • no.20
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    • pp.77-114
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    • 2009
  • The actual conditions of the labor unions are primitive. First, there is no good records management regulation. At this research, I found it that most regulations of the labor unions were all the same. I think they have been copied a kind of one of originality. Second, the definition of records were very narrow, like documentary evidence. Third, the classification, filing, disposal regulations are the below level of the public institution in 1970s. Fourth, there are no standards of the records scheduling for the labor records. What kind of labor records have the historical values? I could not find, only the documentary evidence value. So, I think The actual conditions of the labor unions are primitive. I investigated the collections of the Southern Labor Archives in USA. There were many kind of records. For example, the records of regional labor unions also central labor unions, pamphlets, journals, photos, personal records, oral history, organizational records like protocols article of associations internal rules, minute books etc. Like this the collections of the Southern Labor Archives in USA are very various. But our actual conditions of the labor unions is far from that. Rather, we just have tried collected records for publishing the white papers. But this habitual practice would not be desirable. Because they must manage the records from the producing time. Mostly, 'laborer history HANNAE' were organised, and they are trying the collecting and management of the labor records. Also They are trying the computerizing, compilation. 'HANNAE' has the condition for the transformation of the labor archives. But if they want to be really, they must make the records management infra and so, should normalize the record management firstly. For example, They must be keep the standardized records management regulations, records scheduling redesigned. the developing standard model for the records management. And they have the vision for the hub of the labor archives. When coming to this, it will be realized the labor archives Now the records for the working class are disappearing. The managing the records for the labor is another labor movement. All together should join it. But I think the supporting of the archival science research colleagues will be the essential part.

Development Process and Methods of Audit and Certification Toolkit for Trustworthy Digital Records Management Agency (신뢰성 있는 전자기록관리기관 감사인증도구 개발에 관한 연구)

  • Rieh, Hae-young;Kim, Ik-han;Yim, Jin-Hee;Shim, Sungbo;Jo, YoonSun;Kim, Hyojin;Woo, Hyunmin
    • The Korean Journal of Archival Studies
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    • no.25
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    • pp.3-46
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    • 2010
  • Digital records management is one whole system in which many social and technical elements are interacting. To maintain the trustworthiness, the repository needs periodical audit and certification. Thus, individual electronic records management agency needs toolkit that can be used to self-evaluate their trustworthiness continuously, and self-assess their atmosphere and system to recognize deficiencies. The purpose of this study is development of self-certification toolkit for repositories, which synthesized and analysed such four international standard and best practices as OAIS Reference Model(ISO 14721), TRAC, DRAMBORA, and the assessment report conducted and published by TNA/UKDA, as well as MoRe2 and current national laws and standards. As this paper describes and demonstrate the development process and the framework of this self-certification toolkit, other electronic records management agencies could follow the process and develop their own toolkit reflecting their situation, and utilize the self-assessment results in-house. As a result of this research, 12 areas for assessment were set, which include (organizational) operation management, classification system and master data management, acquisition, registration and description, storage and preservation, disposal, services, providing finding aids, system management, access control and security, monitoring/audit trail/statistics, and risk management. In each 12 area, the process map or functional charts were drawn and business functions were analyzed, and 54 'evaluation criteria', consisted of main business functional unit in each area were drawn. Under each 'evaluation criteria', 208 'specific evaluation criteria', which supposed to be implementable, measurable, and provable for self-evaluation in each area, were drawn. The audit and certification toolkit developed by this research could be used by digital repositories to conduct periodical self-assessment of the organization, which would be used to supplement any found deficiencies and be used to reflect the organizational development strategy.

Deterioration Evaluation Method of Noise Barriers for Managements of Highway (고속도로 방음벽 유지관리를 위한 방음벽 노후도 평가 방안)

  • Kim, Sangtae;Shin, Ilhyoung;Kim, Kyoungsu;Kim, Daae;Kim, Heungrae;Im, Jahae;Lee, Jajun
    • Journal of Environmental Impact Assessment
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    • v.28 no.4
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    • pp.387-399
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    • 2019
  • This research aimed to prepare the classification of the damage types and the damage rating system of noise barriers for expressway noise barriers and to develop deterioration evaluation method of noise barriers by reflecting them. The noise barrier consists of soundproof panels, foundations and posts and the soundproof panels with 10 different types of materials are used in a single or mixed form.In this paper, damage of soundproof panel shows a single or composite damage, and thus a evaluation model of deterioration has been developed for noise barriers that can reflect the characteristic of noise barriers. Materials used mainly for soundproof walls were divided into material types for metal, plastic, timber, transparent and concrete. And damage types for noise barrier were classified into corrosion, discoloration, deformation, spalling and dislocation and damage types were subdivided according to the noise barrier's components and materials. Damage rating was divided into good, minor, normal and severe for each major part of noise barrier to assess damage rating of soundproof panel, foundation and post. The deterioration degree of noise barrier was evaluated comprehensively by using the deterioration evaluation method of whole noise barrier using weighted average. Deterioration evaluation method that can be systematically assessed has been developed for noise barrier using single or mixed soundproof panel and noise barrier with single or complex damage types. Through such an evaluation system, it is deemed that the deterioration status of noise barrier installed can be systematically understood and utilized for efficient maintenance planning and implementation for repair and improvement of noise barriers.

Recommender system using BERT sentiment analysis (BERT 기반 감성분석을 이용한 추천시스템)

  • Park, Ho-yeon;Kim, Kyoung-jae
    • Journal of Intelligence and Information Systems
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    • v.27 no.2
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    • pp.1-15
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    • 2021
  • If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

A prediction model for adolescents' skipping breakfast using the CART algorithm for decision trees: 7th (2016-2018) Korea National Health and Nutrition Examination Survey (의사결정나무 CART 알고리즘을 이용한 청소년 아침결식 예측 모형: 제7기 (2016-2018년) 국민건강영양조사 자료분석)

  • Sun A Choi;Sung Suk Chung;Jeong Ok Rho
    • Journal of Nutrition and Health
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    • v.56 no.3
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    • pp.300-314
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    • 2023
  • Purpose: This study sought to predict the reasons for skipping breakfast by adolescents aged 13-18 years using the 7th Korea National Health and Nutrition Examination Survey (KNHANES). Methods: The participants included 1,024 adolescents. The data were analyzed using a complex-sample t-test, the Rao Scott χ2-test, and the classification and regression tree (CART) algorithm for decision tree analysis with SPSS v. 27.0. The participants were divided into two groups, one regularly eating breakfast and the other skipping it. Results: A total of 579 and 445 study participants were found to be breakfast consumers and breakfast skippers respectively. Breakfast consumers were significantly younger than those who skipped breakfast. In addition, breakfast consumers had a significantly higher frequency of eating dinner, had been taught about nutrition, and had a lower frequency of eating out. The breakfast skippers did so to lose weight. Children who skipped breakfast consumed less energy, carbohydrates, proteins, fats, fiber, cholesterol, vitamin C, vitamin A, calcium, vitamin B1, vitamin B2, phosphorus, sodium, iron, potassium, and niacin than those who consumed breakfast. The best predictor of skipping breakfast was identifying adolescents who sought to control their weight by not eating meals. Other participants who had low and middle-low household incomes, ate dinner 3-4 times a week, were more than 14.5 years old, and ate out once a day showed a higher frequency of skipping breakfast. Conclusion: Based on these results, nutrition education targeted at losing weight correctly and emphasizing the importance of breakfast, especially for adolescents, is required. Moreover, nutrition educators should consider designing and implementing specific action plans to encourage adolescents to improve their breakfast-eating practices by also eating dinner regularly and reducing eating out.