• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.11 no.1
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• pp.124-143
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• 2000

Objectives：The primary purpose of this study is to understand the psychopathology of the victims of school violence in terms of early psychosis. By doing this, the early detection of psychosis among the victims is possible, and early detection may lead to early intervention. Methods：Two-thousand and nine-hundred seventy two students from 16 middle schools in Seoul were asked to fill out questionnaire comprised of popularity and intellectual and school status of Piers-Harris Children's Self Concept Inventory, Symptom Check List-90-Revised, and Ostracism Scale. The subjects whose scores upon Ostracism Scale were higher than average by two standard deviation were labeled as ‘Repelled and Isolated group', and subjects whose scores on popularity were significantly lower than average and whose scores on psychoticism of SCL-90-R were higher than average were defined as 'tentative early psychosis group'. Odds ratios were calculated from the numbers of subjects with and without high psychoticism scores and high ostracism scores. On the subjects of 'tentative early psychotic group', we examined every clinical characteristic and conducted correlation analysis and regression analysis in order to find out the risk factors and to construct theoretical model that explains the psychoticism scores. Results：The results were as follows：1) Total 157(5.3%) subjects were rated significantly higher on ostracism scale, and among them, 47 subjects(29.9%) were rated significantly higher than average on psychoticism scale, while only 50 subjects among 2,135 students who were rated within normal range showed significantly higher score on psychoticism scale. Odds ratio for psychotic group of isolated group were 17.82 and it was statistically significant. 2) Forty-seven subjects(31 boys, 16 girls) who were rated as they were unpopular and rejected from peers had significantly higher psychoticism scores. They were not significantly different from simply high psychoticism subjects in anxiety, social anhedonia scale, magical thinking, obsessivecompulsive symptoms, phobic anxiety, psychoticism, somatization, but showed higher ostracism scores and paranoid tendencies. Among school violence victims, who rated themselves unpopular and showed higher psychoticism scores, the psychoticism scores were mainly explained by anxiety, depression, hostility, interpersonal sensitivity, obsessive-compulsive symptoms, paranoid tendency, somatization scales($r^2=0.93$). Conclusion：Thus, it can be concluded that the subjects with higher ostracism score have the substantially high risk for psychosis development. By these results, we propose that school violence victims with anxiety, depression, hostility, interpersonal sensitivity, obsessive-compulsive symptoms, paranoid tendency, somatization should be tested individually considering school adjustment, attentional deficit, concept formation problems.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.5
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• pp.64-72
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• 2014

This study quantified the storage and annual uptake of carbon by apple trees in orchards as a production-type greenspace, and computed the annual carbon emissions from apple cultivation. Tree individuals in the study orchards were sampled to include the range of stem diameter sizes. The study measured biomass for each part including the roots of sample trees through a direct harvesting method to compute total carbon storage per tree. Annual carbon uptake per tree was quantified by analyzing the radial growth rates of stem samples at ground level. Annual carbon emissions from management practices such as pruning, mowing, irrigation, fertilization, and use of pesticides and fungicides were estimated based on maintenance data, interviews with managers, and actual measurements. Regression models were developed using stem diameter at ground level (D) as an independent variable to easily estimate storage and annual uptake of the carbon. Storage and annual uptake of carbon per tree increased as D sizes got larger. Apple trees with D sizes of 10 and 15 cm stored 9.1 and 21.0 kg of carbon and annually sequestered 1.0 and 1.6 kg, respectively. Storage and annual uptake of carbon per unit area in study orchards were 3.81 t/ha and 0.42 t/ha/yr, respectively, and annual carbon emissions were 1.30 t/ha/yr. Thus, the carbon emissions were about 3 times greater than the annual carbon uptake. The study identified management practices to reduce the carbon footprint of production-type greenspace, including efficient uses of water, pesticides, fungicides, and fertilizers. It breaks new ground by including measured biomass of roots and a detailed inventory of carbon emissions.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.2
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• pp.103-119
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• 2023

Since the Korean government has decided to apply the policy of BIM (Building Information Modeling) to the entire construction industry, it has experienced a positive trend in adoption and utilization. BIM can reduce workloads by building model objects into libraries that conform to standards and enable consistent quality, data integrity, and compatibility. In the domestic architecture, civil engineering, and the overseas landscape architecture sectors, many BIM library standardization studies have been conducted, and guidelines have been established based on them. Currently, basic research and attempts to introduce BIM are being made in Korean landscape architecture field, but the diffusion has been delayed due to difficulties in application. This can be addressed by enhancing the efficiency of BIM work using standardized libraries. Therefore, this study aims to provide a starting point for discussions and present a classification system for objects and attribute information that can be referred to when creating landscape libraries in practice. The standardization of landscape BIM library was explored from two directions: object classification and attribute information items. First, the Korean construction information classification system, product inventory classification system, landscape design and construction standards, and BIM object classification of the NLA (Norwegian Association of Landscape Architects) were referred to classify landscape objects. As a result, the objects were divided into 12 subcategories, including 'trees', 'shrubs', 'ground cover and others', 'outdoor installation', 'outdoor lighting facility', 'stairs and ramp', 'outdoor wall', 'outdoor structure', 'pavement', 'curb', 'irrigation', and 'drainage' under five major categories: 'landscape plant', 'landscape facility', 'landscape structure', 'landscape pavement', and 'irrigation and drainage'. Next, the attribute information for the objects was extracted and structured. To do this, the common attribute information items of the KBIMS (Korean BIM Standard) were included, and the object attribute information items that vary according to the type of objects were included by referring to the PDT (Product Data Template) of the LI (UK Landscape Institute). As a result, the common attributes included information on 'identification', 'distribution', 'classification', and 'manufacture and supply' information, while the object attributes included information on 'naming', 'specifications', 'installation or construction', 'performance', 'sustainability', and 'operations and maintenance'. The significance of this study lies in establishing the foundation for the introduction of landscape BIM through the standardization of library objects, which will enhance the efficiency of modeling tasks and improve the data consistency of BIM models across various disciplines in the construction industry.

• Korean Journal of School Psychology
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• v.16 no.3
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• pp.433-451
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• 2019

This study aimed to develop and validate the Classroom Problem Behavior Scale - Elementary School Version (CPBS-E) measure which is unique to classroom problem behavior exhibited by Korean elementary school students. The focus was on developing a universal screening instrument designed to identify and provide intervention to students who are at-risk for severe social-emotional and behavioral problems. Items were initially drawn from the literature, interviews with elementary school teachers, common office discipline referral measures used in U.S. elementary schools, penalty point systems used in Korean schools, 'Green Mileage', and the Inventory of Emotional and Behavioral Traits. The content validity of the initially developed items was assessed by six classroom and subject teachers, which resulted in the development of a preliminary scale consisting of 63 two-dimensional items (i.e., Within Classroom Problem Behavior and Outside of Classroom Problem Behavior), each of which consisted of 3 to 4 factors. The Within Classroom Problem Behavior dimension consisted of 4 subscales (not being prepared for class, class disruption, aggression, and withdrawn) and the Outside of Classroom Problem Behavior dimension consisted of 3 subscales (rule-violation, aggression, and withdrawn). The CPBS-E was pilot tested on a sample of 154 elementary school students, which resulted in reducing the scale to 23 items. Following the scale revision, the CPBS-E was validated on a sample population of 209 elementary school students. The validation results indicated that the two-dimensional CPBS-E scale of classroom problem behavior was a reliable and valid measure. The test-retest reliability was stable at above .80 in most of the subscales. The CPBS-E measure demonstrated high internal consistency of .76-.94. In examining the criterion validity, the scale's correlation with the Teacher Observation of Classroom Adaptation-Checklist (TOCA-C) was high and the aggression and withdrawn subscales of the CPBS-E demonstrated high correlations with externalization and internalization, respectively, of the Child Behavior Checklist - Teacher Report Form CBCL-TRF). In addition, the factor structure of the CPBS-E scale was examined using the structural equation model and found to be acceptable. The results are discussed in relation to implications, contributions to the field, and limitations.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.426-441
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• 2023

This study investigated the predictive accuracy of a model of landslide displacement in Jecheon-si, where a great number of landslides were triggered by heavy rain on both natural (non-clear-cut) and clear-cut slopes during August 2020. This was accomplished by applying three flow direction methods (single flow direction, SFD; multiple flow direction, MFD; infinite flow direction, IFD) and the degree of root cohesion to an infinite slope stability equation. The application assumed that the soil saturation and any changes in root cohesion occurred following the timber harvest (clear-cutting). In the study area, 830 landslide locations were identified via landslide inventory mapping from satellite images and 25 cm resolution aerial photographs. The results of the landslide modeling comparison showed the accuracy of the models that considered changes in the root cohesion following clear-cutting to be improved by 1.3% to 2.6% when compared with those not considered in the area under the receiver operating characteristics (AUROC) analysis. Furthermore, the accuracy of the models that used the MFD algorithm improved by up to 1.3% when compared with the models that used the other algorithms in the AUROC analysis. These results suggest that the discriminatory application of the root cohesion, which considers changes in the vegetation condition, and the selection of the flow direction method may influence the accuracy of landslide predictive modeling. In the future, the results of this study should be verified by examining the root cohesion and its dynamic changes according to the tree species using the field hydrological monitoring technique.

• Korean Journal of Agricultural Science
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• v.4 no.2
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• pp.344-390
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• 1977

The purpose of this paper was to schedule optimum cutting strategy which could maximize the total yield under certain restrictions on periodic timber removals and harvest areas from an industrial forest, based on a linear programming technique. Sensitivity of the regulation model to variations in restrictions has also been analyzed to get information on the changes of total yield in the planning period. The regulation procedure has been made on the experimental forest of the Agricultural College of Seoul National University. The forest is composed of 219 cutting units, and characterized by younger age group which is very common in Korea. The planning period is devided into 10 cutting periods of five years each, and cutting is permissible only on the stands of age groups 5-9. It is also assumed in the study that the subsequent forests are established immediately after cutting existing forests, non-stocked forest lands are planted in first cutting period, and established forests are fully stocked until next harvest. All feasible cutting regimes have been defined to each unit depending on their age groups. Total yield (Vi, k) of each regime expected in the planning period has been projected using stand yield tables and forest inventory data, and the regime which gives highest Vi, k has been selected as a optimum cutting regime. After calculating periodic yields and cutting areas, and total yield from the optimum regimes selected without any restrictions, the upper and lower limits of periodic yields(Vj-max, Vj-min) and those of periodic cutting areas (Aj-max, Aj-min) have been decided. The optimum regimes under such restrictions have been selected by linear programming. The results of the study may be summarized as follows:- 1. The fluctuations of periodic harvest yields and areas under cutting regimes selected without restrictions were very great, because of irregular composition of age classes and growing stocks of existing stands. About 68.8 percent of total yield is expected in period 10, while none of yield in periods 6 and 7. 2. After inspection of the above solution, restricted optimum cutting regimes were obtained under the restrictions of Amin=150 ha, Amax=400ha, $Vmin=5,000m^3$ and $Vmax=50,000m^3$, using LP regulation model. As a result, about $50,000m^3$ of stable harvest yield per period and a relatively balanced age group distribution is expected from period 5. In this case, the loss in total yield was about 29 percent of that of unrestricted regimes. 3. Thinning schedule could be easily treated by the model presented in the study, and the thinnings made it possible to select optimum regimes which might be effective for smoothing the wood flows, not to speak of increasing total yield in the planning period. 4. It was known that the stronger the restrictions becomes in the optimum solution the earlier the period comes in which balanced harvest yields and age group distribution can be formed. There was also a tendency in this particular case that the periodic yields were strongly affected by constraints, and the fluctuations of harvest areas depended upon the amount of periodic yields. 5. Because the total yield was decreased at the increasing rate with imposing stronger restrictions, the Joss would be very great where strict sustained yield and normal age group distribution are required in the earlier periods. 6. Total yield under the same restrictions in a period was increased by lowering the felling age and extending the range of cutting age groups. Therefore, it seemed to be advantageous for producing maximum timber yield to adopt wider range of cutting age groups with the lower limit at which the smallest utilization size of timber could be produced. 7. The LP regulation model presented in the study seemed to be useful in the Korean situation from the following point of view: (1) The model can provide forest managers with the solution of where, when, and how much to cut in order to best fulfill the owners objective. (2) Planning is visualized as a continuous process where new strateges are automatically evolved as changes in the forest environment are recognized. (3) The cost (measured as decrease in total yield) of imposing restrictions can be easily evaluated. (4) Thinning schedule can be treated without difficulty. (5) The model can be applied to irregular forests. (6) Traditional regulation methods can be rainforced by the model.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.77-110
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• 2017

Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.