• 제목/요약/키워드: Cost Classification

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Study on 3D Printer Suitable for Character Merchandise Production Training (캐릭터 상품 제작 교육에 적합한 3D프린터 연구)

  • Kwon, Dong-Hyun
    • Cartoon and Animation Studies
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    • s.41
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    • pp.455-486
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    • 2015
  • The 3D printing technology, which started from the patent registration in 1986, was a technology that did not attract attention other than from some companies, due to the lack of awareness at the time. However, today, as expiring patents are appearing after the passage of 20 years, the price of 3D printers have decreased to the level of allowing purchase by individuals and the technology is attracting attention from industries, in addition to the general public, such as by naturally accepting 3D and to share 3D data, based on the generalization of online information exchange and improvement of computer performance. The production capability of 3D printers, which is based on digital data enabling digital transmission and revision and supplementation or production manufacturing not requiring molding, may provide a groundbreaking change to the process of manufacturing, and may attain the same effect in the character merchandise sector. Using a 3D printer is becoming a necessity in various figure merchandise productions which are in the forefront of the kidult culture that is recently gaining attention, and when predicting the demand by the industrial sites related to such character merchandise and when considering the more inexpensive price due to the expiration of patents and sharing of technology, expanding opportunities and sectors of employment and cultivating manpower that are able to engage in further creative work seems as a must, by introducing education courses cultivating manpower that can utilize 3D printers at the education field. However, there are limits in the information that can be obtained when seeking to introduce 3D printers in school education. Because the press or information media only mentions general information, such as the growth of the industrial size or prosperous future value of 3D printers, the research level of the academic world also remains at the level of organizing contents in an introductory level, such as by analyzing data on industrial size, analyzing the applicable scope in the industry, or introducing the printing technology. Such lack of information gives rise to problems at the education site. There would be no choice but to incur temporal and opportunity expenses, since the technology would only be able to be used after going through trials and errors, by first introducing the technology without examining the actual information, such as through comparing the strengths and weaknesses. In particular, if an expensive equipment introduced does not suit the features of school education, the loss costs would be significant. This research targeted general users without a technology-related basis, instead of specialists. By comparing the strengths and weaknesses and analyzing the problems and matters requiring notice upon use, pursuant to the representative technologies, instead of merely introducing the 3D printer technology as had been done previously, this research sought to explain the types of features that a 3D printer should have, in particular, when required in education relating to the development of figure merchandise as an optional cultural contents at cartoon-related departments, and sought to provide information that can be of practical help when seeking to provide education using 3D printers in the future. In the main body, the technologies were explained by making a classification based on a new perspective, such as the buttress method, types of materials, two-dimensional printing method, and three-dimensional printing method. The reason for selecting such different classification method was to easily allow mutual comparison of the practical problems upon use. In conclusion, the most suitable 3D printer was selected as the printer in the FDM method, which is comparatively cheap and requires low repair and maintenance cost and low materials expenses, although rather insufficient in the quality of outputs, and a recommendation was made, in addition, to select an entity that is supportive in providing technical support.

Trends of Study and Classification of Reference on Occupational Health Management in Korea after Liberation (해방 이후 우리나라 산업보건관리에 관한 문헌분류 및 연구동향)

  • Ha, Eun-Hee;Park, Hye-Sook;Kim, Young-Bok;Song, Hyun-Jong
    • Journal of Preventive Medicine and Public Health
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    • v.28 no.4 s.51
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    • pp.809-844
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    • 1995
  • The purposes of this study are to define the scope of occupational health management and to classify occupational management by review of related journals from 1945 to 1994 in Korea. The steps of this study were as follows: (1) Search of secondary reference; (2) Collection and review of primary reference; (3) Survey; and (4) Analysis and discussion. The results were as follows ; 1. Most of the respondents majored in occupational health(71.6%), and were working in university (68.3%), males and over the age 40. Seventy percent of the respondents agreed with the idea that classification of occupational health management is necessary, and 10% disagreed. 2. After integration of the idea of respondents, we reclassified the scope of occupational health management. It was defined 3 parts, that is , occupational health system, occupational health service and others (such as assessment, epidemiology, cost-effectiveness analysis and so on). 3. The number of journals on occupational health management was 510. It was sightly increased from 1986 and abruptly increased after 1991. The kinds of journals related to occupational health management were The Korean Journal of Occupational Medicine(18.2%), Several Kinds of Medical Colloge Journal(17.0%), The Korean Journal Occupational Health(15.1%), The Korean Journal of Preventive Medicine(15.1%) and others(34.6%). As for the contents, the number of journals on occupational health management systems was 33(6.5%) and occupational health services 477(93.5%). Of the journals on occupational health management systems, the number of journals on the occupational health resource system was 15(45.5%), occupational finance system 8(24.2%), occupational health management system 6(18.2%), occupational organization 3(9.1%) and occupational health delivery system 1 (3.0%). Of the journals on occupational health services, the number of journals on disease management was 269(57.2%), health management 116(24.7%), working environmental management 85(18.1%). As for the subjects, the number of journals on general workers was 185(71.1%), followed by women worker, white coiler workers and so on. 4. Respondents made occupational health service(such as health management, working environmental management and health education) the first priority of occupational health management. Tied for the second are quality analysis(such as education, training and job contents of occupational health manager) and occupational health systems(such as the recommendation of systems of occupational and general disease and occupational health organization). 5. Thirty seven respondents suggested 48 ideas about the future research of occupational health management. The results were as follows: (1) Study of occupational health service 40.5%; (2) Study of organization system 27.1%; (3) Study of occupational health system (e.g. information network) 8.3%; (4) Study of working condition 6.2%; and (5) Study of occupational health service analysis 4.2%.

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Self-optimizing feature selection algorithm for enhancing campaign effectiveness (캠페인 효과 제고를 위한 자기 최적화 변수 선택 알고리즘)

  • Seo, Jeoung-soo;Ahn, Hyunchul
    • Journal of Intelligence and Information Systems
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    • v.26 no.4
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    • pp.173-198
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    • 2020
  • For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.

A Methodology of Customer Churn Prediction based on Two-Dimensional Loyalty Segmentation (이차원 고객충성도 세그먼트 기반의 고객이탈예측 방법론)

  • Kim, Hyung Su;Hong, Seung Woo
    • Journal of Intelligence and Information Systems
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    • v.26 no.4
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    • pp.111-126
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    • 2020
  • Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

PM2.5 Simulations for the Seoul Metropolitan Area: (II) Estimation of Self-Contributions and Emission-to-PM2.5 Conversion Rates for Each Source Category (수도권 초미세먼지 농도모사 : (II) 오염원별, 배출물질별 자체 기여도 및 전환율 산정)

  • Kim, Soontae;Bae, Changhan;Yoo, Chul;Kim, Byeong-Uk;Kim, Hyun Cheol;Moon, Nankyoung
    • Journal of Korean Society for Atmospheric Environment
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    • v.33 no.4
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    • pp.377-392
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    • 2017
  • A set of BFM (Brute Force Method) simulations with the CMAQ (Community Multiscale Air Quality) model were conducted in order to estimate self-contributions and conversion rates of PPM (Primary $PM_{2.5}$), $NO_x$, $SO_2$, $NH_3$, and VOC emissions to $PM_{2.5}$ concentrations over the SMA (Seoul Metropolitan Area). CAPSS (Clean Air Policy Support System) 2013 EI (emissions inventory) from the NIER (National Institute of Environmental Research) was used for the base and sensitivity simulations. SCCs (Source Classification Codes) in the EI were utilized to group the emissions into area, mobile, and point source categories. PPM and $PM_{2.5}$ precursor emissions from each source category were reduced by 50%. In turn, air quality was simulated with CMAQ during January, April, July, and October in 2014 for the BFM runs. In this study, seasonal variations of SMA $PM_{2.5}$ self-sensitivities to PPM, $SO_2$, and $NH_3$ emissions can be observed even when the seasonal emission rates are almost identical. For example, when the mobile PPM emissions from the SMA were 634 TPM (Tons Per Month) and 603 TPM in January and July, self-contributions of the emissions to monthly mean $PM_{2.5}$ were $2.7{\mu}g/m^3$ and $1.3{\mu}g/m^3$ for the months, respectively. Similarly, while $NH_3$ emissions from area sources were 4,169 TPM and 3,951 TPM in January and July, the self-contributions to monthly mean $PM_{2.5}$ for the months were $2.0{\mu}g/m^3$ and $4.4{\mu}g/m^3$, respectively. Meanwhile, emission-to-$PM_{2.5}$ conversion rates of precursors vary among source categories. For instance, the annual mean conversion rates of the SMA mobile, area, and point sources were 19.3, 10.8, and $6.6{\mu}g/m^3/10^6TPY$ for $SO_2$ emissions while those rates for PPM emissions were 268.6, 207.7, and 181.5 (${\mu}g/m^3/10^6TPY$), respectively, over the region. The results demonstrate that SMA $PM_{2.5}$ responses to the same amount of reduction in precursor emissions differ for source categories and in time (e.g. seasons), which is important when the cost-benefit analysis is conducted during air quality improvement planning. On the other hand, annual mean $PM_{2.5}$ sensitivities to the SMA $NO_x$ emissions remains still negative even after a 50% reduction in emission category which implies that more aggressive $NO_x$ reductions are required for the SMA to overcome '$NO_x$ disbenefit' under the base condition.

A basic research for evaluation of a Home Care Nursing Delivery System (가정간호 서비스 질 평가를 위한 도구개발연구)

  • Kim, Mo-Im;Cho, Won-Jung;Kim, Eui-Sook;Kim, Sung-Kyu;Chang, Soon-Bok;Ryu, Ho-Sihn
    • Journal of Home Health Care Nursing
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    • v.6
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    • pp.33-45
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    • 1999
  • The purpose of this study was to develop a basic framework and criteria for evaluation of quality care provided to patients with the attributes of disease in the home care nursing field, and to provide measurement tools for home health care in the future. The study design was a developmental study for evaluation of hospital-based HCN(home care nursing) in Korea. The study process was as follows: a home care nursing study team of College of Nursing. Yonsei University reviewed the nursing records of 47 patients who were enrolled at Yonsei University Medical Center Home Care Center in March, 1995. Twenty-five patients were insured at that time, were selected from 47 patients receiving home care service for study feasibility with six disease groups; Caesarean Section (C/S), simple nephrectomy, Liver cirrhosis(LC), chronic obstructive pulmonary disease(COPD), Lung cancer or cerebrovascular accident(CVA). In this study, the following items were selected : First step : Preliminary study 1. Criteria and items were selected on the basis of related literature on each disease area. 2. Items were identified by home care nurses. 3. A physician in charge reviewed the criteria and content of selected items. 4. Items were revised through preliminary study offered to both HCN patients and discharged patients from the home care center. Second step : Pretest 1. To verify the content of the items, a pretest was conducted with 18 patients of which there were three patients in each of the six selected disease groups. Third step : Test of reliability and validity of tools 1. Using the collected data from 25 patients with either cis, Simple nephrectomy, LC, COPD, Lung cancer, or CVA. the final items were revised through a panel discussion among experts in medical care who were researchers, doctors, or nurses. 2. Reliability and validity of the completed tool were verified with both inpatients and HCN patients in each of field for researches. The study results are as follows: 1. Standard for discharge with HCN referral The referral standard for home care, which included criteria for discharge with HCN referral and criteria leaving the hospital were established. These were developed through content analysis from the results of an open-ended questionnaire to related doctors concerning characteristic for discharge with HCN referral for each of the disease groups. The final criteria was decided by discussion among the researchers. 2. Instrument for measurement of health statusPatient health status was measured pre and post home care by direct observation and interview with an open-ended questionnaire which consisted of 61 items based on Gorden's nursing diagnosis classification. These included seven items on health knowledge and health management, eight items on nutrition and metabolism, three items on elimination, five items on activity and exercise, seven items on perception and cognition, three items on sleep and rest, three items on self-perception, three items on role and interpersonal relations, five items on sexuality and reproduction, five items on coping and stress, four items on value and religion, three items on family. and three items on facilities and environment. 3. Instrument for measurement of self-care The instrument for self-care measurement was classified with scales according to the attributes of the disease. Each scale measured understanding level and practice level by a Yes or No scale. Understanding level was measured by interview but practice level was measured by both observation and interview. Items for self-care measurement included 14 for patients with a CVA, five for women who had a cis, ten for patients with lung cancer, 12 for patients with COPD, five for patients with a simple nephrectomy, and 11 for patients with LC. 4. Record for follow-up management This included (1) OPD visit sheet, (2) ER visit form, (3) complications problem form, (4) readmission sheet. and (5) visit note for others medical centers which included visit date, reason for visit, patient name, caregivers, sex, age, time and cost required for visit, and traffic expenses, that is, there were open-end items that investigated OPD visits, emergency room visits, the problem and solution of complications, readmissions and visits to other medical institution to measure health problems and expenditures during the follow up period. 5. Instrument to measure patients satisfaction The satisfaction measurement instrument by Reisseer(1975) was referred to for the development of a tool to measure patient home care satisfaction. The instrument was an open-ended questionnaire which consisted of 11 domains; treatment, nursing care, information, time consumption, accessibility, rapidity, treatment skill, service relevance, attitude, satisfaction factors, dissatisfaction factors, overall satisfaction about nursing care, and others. In conclusion, Five evaluation instruments were developed for home care nursing. These were (1)standard for discharge with HCN referral. (2)instrument for measurement of health status, (3)instrument for measurement of self-care. (4)record for follow-up management, and (5)instrument to measure patient satisfaction. Also, the five instruments can be used to evaluate the effectiveness of the service to assure quality. Further research is needed to increase the reliability and validity of instrument through a community-based HCN evaluation.

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Improvement on Management of Non-point Source Pollution for Reasonable Implementation of TMDL - Focusing on Selection of Non-point Source Pollution Management Region and Management of Non-point Source Pollutant - (수질오염총량관리제의 합리적인 시행을 위한 비점오염원관리 개선방안 - 비점오염원 관리지역 선정 및 비점오염물질 관리를 중심으로 -)

  • Yi, Sang-Jin;Kim, Young-Il
    • Journal of Korean Society of Environmental Engineers
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    • v.36 no.10
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    • pp.719-723
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    • 2014
  • For effective implementation of total maximum daily load (TMDL), this study presented the improving plans of non-point source pollution management including the classification of non-point source pollution, calculation of non-point source pollution load (generated, discharged), selection of non-point source pollution management regions and management of non-point source pollutant. First of all, the definition of point source pollution and non-point source pollution based on the legal and scientific viewpoint should be precisely classified and managed. Especially, the forest, grassland and river without occurrence of environmental damage by activity of business and human should be separately classified natural background pollutants. The unit for generated and discharged non-point source pollution should be preferentially changed according to actual condition of watershed. The calculation methods of generated and discharged non-point source pollution should be corrected consideration on the amount and duration of rainfall. While the TMDL is implemented, non-point source pollution management regions should be selected in the watersheds exceed the targeted water quality standards by the rainfall. The non-point source pollution management regions should be selected in the minimal regions where have high values of discharged non-point source pollution density in the urban area, farmland and site area except forest, grassland in the whole watershed. The non-point source pollutant treatment facilities, which take into consideration non-point source pollution load per unit area, duration of the excess concentration, realizable possibility of treatment, effectiveness of treatment cost versus point source pollutant, should be established in the regions with a large generated non-point source pollution load and a high concentration of water quality exceed the targeted water quality standards by the rainfall.

A Study on the Traditional Geographic System Recognition and Environmental Value Estimate of Hannamkeumbuk-Keumbuk Mountains for the Establishment of a Management Plan (관리계획 수립을 위한 한남금북.금북정맥의 전통적 지리체계인식과 환경가치 추정 연구)

  • Kang, Kee-Rae;Kim, Dong-Pil
    • Journal of the Korean Institute of Landscape Architecture
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    • v.40 no.1
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    • pp.23-33
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    • 2012
  • In this study, how much users of Hannamkeumbuk Keumbuk Mountains are aware of Baekdaegan and its attached mountain chains, a traditional geographic system, according to Sangyungpyo and basic data like the degree of awareness and use-behaviors, etc. have been studied. In addition, the environmental value of Hannamkeumbuk Keumbuk Mountains separating the central and the southern part of Korea among attached mountain ranges, secondary mountain chains, which act as an ecosystem buffer in the Baekdudaegan Range, has been estimated at the current amount of currency. In the questions of the perception of the traditional classification standard of mountain chains and Baekdudaegan, more than 70% of respondents answered that they had heard of or known them but 66.8% werenot aware of Hannamkeumbuk Keumbuk Mountains. While the awareness for Baekdudaegan is high, the perception of its attached mountain chains was very poor. DBDC responder system and CVM, which is used widely for the value estimate method of environment goods, were used. As the result, an additional benefit got when a person visits Hannamkeumbuk Keumbuk mountains was estimated as 5,813 won. It could find out that this amount was very low compared with 51,984 won, average visit cost. It judged that the reason was that damage of environmental conditions, the monotony of the trails and progress of indiscriminate environmental destruction, etc. The results of this study will offer a new perspective on public relations activities and resource conservation of Baekdudaegan and its attached mountain chains and estimate perceptions and efficient services for visitors to HannamKeumbuk Keumbuk Mountains. This study will act as data for basic planning and management to increase the mountains' value and to preserve them. Further studies are needed to make a frame of work division and management with various organizations so that the management of Hannamkeumbuk-Keumbuk Mountains may be properly established and their value may been hanced.

An Analysis of the Cognition of Professionals Regarding the Validity of Planting Design Change that Occurred in the Landscape Construction of a Major Private Company (민간기업 조경공사에서 나타나는 식재설계 변경 타당성에 대한 전문가 인식 분석)

  • Park, Jae-Young;Cho, Se-Hwan
    • Journal of the Korean Institute of Landscape Architecture
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    • v.42 no.6
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    • pp.101-110
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    • 2014
  • This study analyzes the validity of the type classification of the type and design changes of apartment landscaping planting construction design changes that were completed in the private sector, efficiently manages the design changes that are displayed over landscaping planting work in general in the future, and performs research by placing the object underlying the presentation. The results are as follows. First, the percentage that occurred in the planting construction of design changes that have occurred in the apartment landscaping construction was carried out in the private sector and accounted for 61.8%. This indicates that part of the planting is a major design change. Second, as the cause of such a design change to be those associated with the field conditions such as lack of main construction period. In particular, due to a change in oral, appeared 7-48 times design changes of one review design change approval is complex, design changes of planting construction had shown a feature that occurs in multiple simultaneous. Third, the 7 types of Design Changes in planting design were delineated as 'design changes for consideration of the user', 'design changes for image improvement', 'design changes for ease of maintenance', 'design changes due to the mismatch of design statement', 'design changes due to the relationship with the engineering species of other', 'design changes due to lack of field study', and 'design changes due to the consideration of feasibility.' Fourth, 'design changes for consideration of the user' and 'design changes for image improvement' were found in more than half of the frequency of the overall changes. This differed from the results shown in public corporations. Fifth, if planting construction design change process, private companies, it was found that is showing the approval of the practice after the previous construction of the construction cost savings due to construction time. However, in the case of a public corporation, these exhibited a different aspect from the private sector and show a design change procedure that reflects the changes after the design change events in the field have occurred. The above results, the type of landscaping works in planting design change of public enterprises, regardless of the private sector, is the same in the seven types, the main reason of and procedures for design changes, indicating that there are other respects. In design change, it may be desirable to apply becomes liquidity rationality and efficiency of the dimension, depending on the nature of the landscape construction.

Estimation and Mapping of Soil Organic Matter using Visible-Near Infrared Spectroscopy (분광학을 이용한 토양 유기물 추정 및 분포도 작성)

  • Choe, Eun-Young;Hong, Suk-Young;Kim, Yi-Hyun;Zhang, Yong-Seon
    • Korean Journal of Soil Science and Fertilizer
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    • v.43 no.6
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    • pp.968-974
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    • 2010
  • We assessed the feasibility of discrete wavelet transform (DWT) applied for the spectral processing to enhance the estimation performance quality of soil organic matters using visible-near infrared spectra and mapped their distribution via block Kriging model. Continuum-removal and $1^{st}$ derivative transform as well as Haar and Daubechies DWT were used to enhance spectral variation in terms of soil organic matter contents and those spectra were put into the PLSR (Partial Least Squares Regression) model. Estimation results using raw reflectance and transformed spectra showed similar quality with $R^2$ > 0.6 and RPD> 1.5. These values mean the approximation prediction on soil organic matter contents. The poor performance of estimation using DWT spectra might be caused by coarser approximation of DWT which not enough to express spectral variation based on soil organic matter contents. The distribution maps of soil organic matter were drawn via a spatial information model, Kriging. Organic contents of soil samples made Gaussian distribution centered at around 20 g $kg^{-1}$ and the values in the map were distributed with similar patterns. The estimated organic matter contents had similar distribution to the measured values even though some parts of estimated value map showed slightly higher. If the estimation quality is improved more, estimation model and mapping using spectroscopy may be applied in global soil mapping, soil classification, and remote sensing data analysis as a rapid and cost-effective method.