• Journal of the Korea Society for Simulation
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• v.23 no.3
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• pp.19-25
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• 2014

Demand forecasting is the basis of management activities including marketing strategy. Especially, the demand of a part is remarkably important in supply chain management (SCM). In the fields of various industries, the part demand usually has the intermittent characteristic. The intermittent characteristic implies a phenomenon that there frequently occurs zero demands. In the intermittent demands, non-zero demands have large variance and their appearances also have stochastic nature. Accordingly, in the intermittent demand forecasting, it is inappropriate to apply the traditional time series models and/or cause-effect methods such as linear regression; they cannot describe the behaviors of intermittent demand. Markov bootstrap method was developed to forecast the intermittent demand. It assumes that first-order autocorrelation and independence of lead time demands. To release the assumption of independent lead time demands, this paper proposes a modified bootstrap method. The method produces the pseudo data having the characteristics of historical data approximately. A numerical example for real data will be provided as a case study.

• Journal of the Korea Organic Resources Recycling Association
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• v.32 no.3
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• pp.19-29
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• 2024

Total organic carbon (TOC) represents the total amount of organic carbon contained in water and is a key water quality parameter used, along with biochemical oxygen demand (BOD) and chemical oxygen demand (COD), to quantify the amount of organic matter in water. In this study, a model to predict TOC was developed using XGBoost (XGB), a representative ensemble machine learning algorithm. Independent variables for model construction included water temperature, pH, electrical conductivity, dissolved oxygen concentration, BOD, COD, suspended solids, total nitrogen, total phosphorus, and discharge. To quantitatively analyze the impact of various water quality parameters used in model construction, the feature importance of input variables was calculated. Based on the results of feature importance analysis, items with low importance were sequentially excluded to observe changes in model performance. When built by sequentially excluding items with low importance, the performance of the model showed a root mean squared error-observation standard deviation ratio (RSR) range of 0.53 to 0.55. The model that applied all input variables showed the best performance with an RSR value of 0.53. To enhance the model's field applicability, models using relatively easily measurable parameters were also built, and the performance changes were analyzed. The results showed that a model constructed using only the relatively easily measurable parameters of water temperature, electrical conductivity, pH, dissolved oxygen concentration, and suspended solids had an RSR of 0.72. This indicates that stable performance can be achieved using relatively easily measurable field water quality parameters.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.343-343
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• 2021

최근 국내외적으로 발생되는 대규모의 가뭄에 대하여 여러 과학자들은 자연적인 현상의 가뭄이 아니라 인간의 영향으로 변형된 유역 상황으로 증발산과 토양수분량 그리고 하천유량 등이 자연적인 상태와 다르게 변화되면서 지속된 가뭄으로 평가하고 있다. 우리나라는 대부분의 지역에서 댐과 저류지를 중심으로 수자원 관리가 이루어지고 있으며, 자연적인 수문과정에 의한 유출에 따른 수문학적 가뭄과는 차이가 존재한다. 사회경제적 인자(인구밀도, 농업 및 산업 경제규모 등)는 댐 및 저수지의 용수사용에 큰 영향을 미치며, 저류지의 저류량을 활용하여 판단한 인위적 용수사용이 고려된 수문학적 가뭄(인위적 수문학적 가뭄)과 자연 상태로의 수문학적 가뭄의 특성은 크게 다를 수 있다. 하지만, 사회경제적 인자들이 수문학적 가뭄에 미치는 영향에 대하여 비교한 연구는 상관성 분석을 토대로한 연구가 대부분이다. 본 연구에서는 인자들이 인위적 수문학적 가뭄에 미치는 정도를 정량적으로 비교하기 위하여 베이지안 네크워크 모형을 활용하여 사회경제적 인자와 인위적 수문학적 가뭄과의 관계를 분석하였다. 해당 관계를 바탕으로 코플라 함수를 활용함으로써 베이지안 네트워크 내의 결합확률을 산정하였다. 다양한 사회경제적 인자들에 중에서 인과지도를 바탕으로 활용 가능한 인자로 농업용수 사용량, 생공용수 사용량 자료를 구축하였으며, 기상학적 가뭄지수를 추가적으로 고려하여 한강유역 충주댐 유역에 적용하였다. 그 결과 기상학적 가뭄과 농업용수 사용량과 생공용수 사용량은 값이 증가함에 따라 인위적 수문학적 가뭄의 발생확률이 증가하였다. 사회경제적 인자 중에서는 생공용수 사용량(0.39~0.49)이 전반적으로 농업용수 사용량(0.36~0.48)보다 인위적 수문학적 가뭄에 보다 큰 영향을 미치고 있으며, 값이 적을수록 생공용수 사용량의 영향이 보다 더 크다는 것이 확인되었다. 이를 바탕으로 인위적 수문학적 가뭄의 대응을 위해서는 농업용수 사용량보다 생공용수 사용량의 감축이 우선적으로 이루어져야 그 효과가 클 것으로 판단된다. 본 연구에서 제시한 모형은 베이지안 네트워크를 기반으로 하므로, 둘 이상의 인자에 대하여 복합적으로 가뭄에 영향을 미치는 영향에 대한 추가적인 연구가 가능하다.

• Journal of the Korean Society for information Management
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• v.22 no.1 s.55
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• pp.65-85
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• 2005

This study proposes a new site selection model which reflects integrated opinions of several groups and identifies sites through objectivity of selection procedure. The proposed model consists of two parts, Analytic Hierarchy Process(AHP) and Geographic Information(GIS). This model was applied to Seocho-gu in Seoul. First, library site selection criteria were determined through literature study. Hierarchical relationship based on the questionnaire was determined and refined to be suited to Seocho-gu case. A survey was conducted with three groups, namely, library users, librarians, and public worker. A few inconsistent answers to the survey questionnaire were excluded and the relative importance of each criterion was measured. Next, an overlay method was used and the relative importance was used as a weight for selecting candidates. This process excluded the areas where a library was unable to be built, for example, rivers, military areas, other restricted areas by law, etc. and resulted in seventy-five sites. Five groups of candidates were identified according to the similarity of criteria. Finally, four groups, after eliminating one lowly fitted group, were determined.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.102-116
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• 2006

Electronic catalogs (or e-catalogs) hold information about the goods and services offered or requested by the participants, and consequently, form the basis of an e-commerce transaction. Catalog management is complicated by a number of factors and product classification is at the core of these issues. Classification hierarchy is used for spend analysis, custom3 regulation, and product identification. Classification is the foundation on which product databases are designed, and plays a central role in almost all aspects of management and use of product information. However, product classification has received little formal treatment in terms of underlying model, operations, and semantics. We believe that the lack of a logical model for classification Introduces a number of problems not only for the classification itself but also for the product database in general. It needs to meet diverse user views to support efficient and convenient use of product information. It needs to be changed and evolved very often without breaking consistency in the cases of introduction of new products, extinction of existing products, class reorganization, and class specialization. It also needs to be merged and mapped with other classification schemes without information loss when B2B transactions occur. For these requirements, a classification scheme should be so dynamic that it takes in them within right time and cost. The existing classification schemes widely used today such as UNSPSC and eClass, however, have a lot of limitations to meet these requirements for dynamic features of classification. In this paper, we try to understand what it means to classify products and present how best to represent classification schemes so as to capture the semantics behind the classifications and facilitate mappings between them. Product information implies a plenty of semantics such as class attributes like material, time, place, etc., and integrity constraints. In this paper, we analyze the dynamic features of product databases and the limitation of existing code based classification schemes. And describe the semantic classification model, which satisfies the requirements for dynamic features oi product databases. It provides a means to explicitly and formally express more semantics for product classes and organizes class relationships into a graph. We believe the model proposed in this paper satisfies the requirements and challenges that have been raised by previous works.

• Fashion & Textile Research Journal
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• v.6 no.3
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• pp.399-403
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• 2004

Education of clothing and textiles in the university is various according to the purposes. Among that clothing construction and practice is what is needed the most in understanding the process of apparel producing, and is the basic subject of areas from apparel designs to quality management. Producing apparel starts from planning the bodice pattern according to the human body shape. Basic bodice pattern should be highly practical so that production of all items of apparel patterns can be possible. Also, a basic bodice pattern needs to be planned in the way that even beginners can use it by classifying sizes according to each body measurements. Thus in this study. bodice patterns will be produced in way of draping method subjecting university students in early 20s. standardized and classified sizes will be calculated from it and bodice pattern made by studied flat pattern method will be examined and compared so that finally suitability will be compared. As a result of examining and comparing bodice patterns made by draping method and studied flat pattern method on the model of the human body produced by plaster method, sizes were classified into 5 levels. As a result of evaluation of creation. satisfying consequence from various body shape was acquired and it is expected of the beginners who are stating from clothing construction and practice to be educated by using the result of this study.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.143-143
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• 2012

최근 우리나라 주요하천에 걸쳐 수행된 '4대강 살리기 사업'에서는 하천에서 발생하는 홍수 및 가뭄재해의 방지를 위한 다양한 사업이 추진되었다. 특히 안정적인 용수공급과 재해방지를 위한 수위확보를 목적으로 4대강 16 개 구간에 걸쳐서 일반적 형태의 고정보와 함께 다양한 형상과 운영방식이 적용된 가동보로 이루어진 다목적보가 설치되었다. 본 연구에서는 4대강 유역(한강, 낙동강, 영산강, 금강)에 설치된 16 개 가동보의 형식 중 4곳(강정고령보, 강천보, 합천창녕보, 창녕함안보)에 적용된 라이징 섹터 게이트(rising sector gate)의 수리학적 특성을 분석하고자 가동보의 수리실험 모형을 개수로에 설치하여 보 주변에서의 흐름 및 난류 특성을 분석하고자 하였다. 4대강 유역에 설치된 라이징 섹터 게이트의 설치목적은 일반적인 고정보의 문제점으로 대두되고 있는 보 상류부의 퇴적토를 신속하게 배사(sediment flushing)하는 데 있다. 이를 위해서는 우선 배사 시에 보 하단부에서 최대유속을 발생시키면서 동시에 최적의 상하류 수위조건을 만족시키는 것이 매우 중요하다. 본 연구에서는 개수로에 설치된 가동보의 수문개방도에 따른 유속분포를 측정하였다. 보 주변에서의 보다 정밀한 유속장의 측정을 위해서 비접촉식 유속측정 방법인 PIV 측정방법을 이용하였다. PIV 측정방법은 일정한 입경과 밀도를 가지며 레이저 반사율이 높은 입자를 흐름에 투입하고 laser 발생장치로 laser sheet를 생성하여 레이저가 반사되어 나타나는 입자 각각의 시간변화에 따른 변위를 CCD 카메라로 가시화한 뒤 유속벡터값을 추출할 수 있게 한다. PIV 측정방법으로 유체의 흐름을 파악하고 시간평균된 유속결과를 바탕으로 난류 특성을 분석하였다. 수로전체 구간에 대하여 3차원 수치해석 프로그램인 FLOW-3D 모의결과와 비교하여 분석하였다. 실험을 통한 유속결과와 수치해석결과는 실험을 통한 유속결과와 비교 분석하였으며, 적용성을 검증한 후 다양한 조건에 대한 설계방안 및 유지관리에 활용하고자 한다.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.31 no.4
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• pp.62-69
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• 2013

The origin of natural planting, which is getting the spotlight in modern time facing natural and environmental problems, can be found from wild gardens. They were started by William Robinson and concretely embodied by Gertrude Jekyll. It is worth shedding new light on wild gardens, as they served as a pathbreaker for ecological design and an important foundation for the specialization of naturalism, which are part of the most important topics in modern gardens. This study aimed to infer the conceptual model of wild gardens and identify their historic significance by comparatively analyzing Robinson's Gravetye Manor and Jekyll's Munstead Wood. The results are: Firstly, they inherited inspirations for spatial organization from basic cottage gardens and introduced informal forms. Secondly, in terms of the use of materials, they had observed various climates in their journeys so that they could use both native and naturalized plants based on their understanding of the plants' hardiness and exotic species. They also displayed interests in plants in the woodlands and forests. Thirdly, in terms of design techniques, they investigated the colors and textures of individual plants and their relationships to produce a variety of views that resembled nature in microcosm. Fourthly, in terms of maintenance, their basic orientation was the minimum maintenance to allow plants to live according to their nature.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.101-108
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• 2024

The total number of railroad stations managed in Korea is 322 (including general and wide-area railways), and a considerable number of stations are aging. In terms of the size of the existing railway station and the number of entrances, it has not been possible to secure adequate service capacity, and the demand for station improvement is increasing due to changes in surrounding conditions such as urban development. In the past, railroad stations were focused on the simple function of a connection passage in terms of maintenance or management, but in recent years, railroad stations are also changing to an atmosphere that they should be reborn as a user-centered comfortable, convenient, and safe service provision space. In this study, a case study related to the improvement of the old railway station was conducted to derive an improvement plan that meets the improvement standard of the old station, and the service level evaluation standard was developed. By introducing the concept of service level (LOS) in the development model, station congestion, station movement convenience, and station safety were selected as evaluation indicators. In addition, this development model applied an analytical stratification technique to divide various evaluation elements of each indicator into major and detailed elements and derive the relative importance of the elements by class. Priority for improvement was derived using the ratio of the number of E and F on the LOS for each facility. Based on this study, it is expected to be helpful in using it as an evaluation criterion for improving objective and equitable railway station.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.10
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• pp.391-398
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• 2021

Since the leased line is a structure that exclusively uses two connected areas for data transmission, a stable quality level and security are ensured, and despite the rapid increase in the number of switched lines, it is a line method that is continuously used a lot in companies. However, because the cost is relatively high, one of the important roles of the network operator in the enterprise is to maintain the optimal state by properly arranging and utilizing the resources of the network leased line. In other words, in order to properly support business service requirements, it is essential to properly manage bandwidth resources of leased lines from the viewpoint of data transmission, and properly predicting and managing leased line usage becomes a key factor. Therefore, in this study, various prediction models were applied and performance was evaluated based on the actual usage rate data of leased lines used in corporate networks. In general, the performance of each prediction was measured and compared by applying the smoothing model and ARIMA model, which are widely used as statistical methods, and the representative models of deep learning based on artificial neural networks, which are being studied a lot these days. In addition, based on the experimental results, we proposed the items to be considered in order for each model to achieve good performance for prediction from the viewpoint of effective operation of leased line resources.