• 제목/요약/키워드: Cost Classification

검색결과 767건 처리시간 0.024초

의료기관 인공신장실의 원가계산에 의한 적정수가에 관한 연구 (Study on optimal treatment payment by cost accounting in the artificiality kidney center in medical institutions)

  • 문승권;이윤석
    • 한국병원경영학회지
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    • 제18권2호
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    • pp.81-103
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    • 2013
  • This study is to research cost accounting practice and to analyze propriety of patients' medical payment in artificiality kidney center. The researched cost datum of the year 2012 are as follows. - Hemodialysis medical treatment was reimbursed as much as 158,001 won in case of health insured patients, but payed-off as much as 135,810 won. - The average figure of the total hospitals and clinic center is 1,603,303 won, and one time cost of hemodialysis treatment is 154,487 won. Optimal treatment pay are suggested as follows. First, Regardless of the notified classification from MOHW(Ministry of Health and Welfare), 136,000 won of fixed price payment classification needs to be reclassified by patients, severity and tobe rearranged by fixed price payment system of hospitals. Second, Fixed payment code notified by the Ministry of Health and Welfare is recommended to be simplifies and to reflect according to contents of the medical treatment rendered to patients. Third, Establishment of artificial kidney center has to be risk managed because of its huge investment. Fourth, Cost analysis model has to be maintained as basis together with appropriate application of conversion index model mixed with SGR model.

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대도시 저소득층 만성질환 노인을 위한 가정.방문간호 원가산정 - 환자 중증도 및 활동기준원가계산법(ABC) 적용 - (Estimation of Home-visiting Care Costs for Low-income Elderly with Chronic Disease in a Metropolitan City Using the Severity Classification and ABC(active-based costing))

  • 강성례
    • 간호행정학회지
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    • 제14권2호
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    • pp.118-130
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    • 2008
  • Purpose: The purpose of this study was to estimate of home-visiting nursing costs for low-income elderly with chronic disease in a metropolitan city using the severity classification and ABC(active-based costing). Methods: First, the HHC activity pool was established. The performance time of each nursing activity were estimated. Second, nursing resources(labor costs, operating costs, and traffic expenses) were analyzed and nursing cost per minute was calculated. And then the cost of each activity was estimated. Third, 202 visiting cases were classified into three group by their severity. And then nursing cost per visit according to their severity was estimated. Results: 59 nursing activities were included in HHC activity pool. The average working time of 59 nursing activity was 6.7minutes and nursing cost per minute was 489 won. According severity, nursing cost per visit were in class I, 54,296 (won), class II 83,124(won), and class III 93,455(won).

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지하도로시설물의 LCC예측 모델 및 시스템 개발 (Development of Life Cycle Cost Model & System of the Road Tunnel)

  • 조효남;선종완;김충완;민대홍
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2004년도 가을 학술발표회 논문집
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    • pp.157-162
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    • 2004
  • Recently, Life Cycle Cost (LCC) for civil infrastructures, such as pavements, bridges, and dams, has been emphasized. However there are few cost models for road tunnel especially for maintenance phase. The road network is composed of highways, bridges, and road tunnels. Thus it is as important as for road tunnels to keep safe for traffic. The maintenance strategies for road tunnels can be achieved based on the minimization of LCC in maintenance phase. For this purpose, in this paper, cost model and cost classification for road tunnel in maintenance phase are suggested.

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구간 신경망에 의한 구간 벡터의 식별 (Classification of Interval Vectors by Interval Neural Networks)

  • 권기택
    • 한국산업정보학회논문지
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    • 제6권2호
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    • pp.1-6
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    • 2001
  • 본 논문에서는 구간 데이터 식별을 위한 구간 신경망의 학습 알고리즘을 제안한다. 제안된 기법은 각 데이터의 속성치가 구간으로 주어져 있는 경우의 패턴 식별 문제에 적용된다. 먼저, 구간 입력 벡터를 다루기 위한 구간 신경망의 구조를 제안하고, 평가 함수를 이용하여 학습 알고리즘을 도출한다. 평가 함수는 구간 신경 망으로부터의 구간 출력과 대응하는 목표 출력을 이용하여 정의된다. 마지막으로 컴퓨터 시뮬레이션에 의해 제안 기법의 구간 데이터 식별 능력을 나타내고, 통상의 역전파 신경망을 이용 기법과 비교한다.

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Classification of Grid Connected Transformerless PV Inverters with a Focus on the Leakage Current Characteristics and Extension of Topology Families

  • Ozkan, Ziya;Hava, Ahmet M.
    • Journal of Power Electronics
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    • 제15권1호
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    • pp.256-267
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    • 2015
  • Grid-connected transformerless photovoltaic (PV) inverters (TPVIs) are increasingly dominating the market due to their higher efficiency, lower cost, lighter weight, and reduced size when compared to their transformer based counterparts. However, due to the lack of galvanic isolation in the low voltage grid interconnections of these inverters, the PV systems become vulnerable to leakage currents flowing through the grounded star point of the distribution transformer, the earth, and the distributed parasitic capacitance of the PV modules. These leakage currents are prohibitive, since they constitute an issue for safety, reliability, protection coordination, electromagnetic compatibility, and module lifetime. This paper investigates a wide range of multi-kW range power rating TPVI topologies and classifies them in terms of their leakage current attributes. This systematic classification places most topologies under a small number of classes with basic leakage current attributes. Thus, understanding and evaluating these topologies becomes an easy task. In addition, based on these observations, new topologies with reduced leakage current characteristics are proposed in this paper. Furthermore, the important efficiency and cost determining characteristics of converters are studied to allow design engineers to include cost and efficiency as deciding factors in selecting a converter topology for PV applications.

소프트웨어 비용산정을 위한 SVM의 파라미터 선정과 응용에 관한 연구 (A Study on the Selection of Parameters and Application of SVM for Software Cost Estimation)

  • 권기태;이준길
    • 한국컴퓨터정보학회논문지
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    • 제14권3호
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    • pp.209-216
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    • 2009
  • 소프트웨어 개발 초기 단계에서 소프트웨어 개발비용을 정확하게 예측하는 것은 프로젝트의 성패를 결정짓는 중요한 요소이다. 본 논문에서는 서포트 벡터 머신을 이용하여 소프트웨어 개발비용을 추정하고자 한다. 서포트 벡터 머신은 벡터 공간에서 선형 및 비선형의 경계면을 찾아 입력 데이터를 분류하는 방법으로서 분류 문제에 효과적이다. 하지만 사용자정의에 의한 파라미터에 의존적이어서 최적의 파라미터를 선택하는 어려움이 있다. 본 연구에서는 서포트 벡터 머신에서 사용하는 파라미터 선택을 위한 개선된 방법을 제안하고, 이러한 최적의 파라미터를 가진 서포트 벡터 머신을 이용하여 소프트웨어 개발비용을 추정하였다. 본 연구의 결과 기존 소프트웨어 비용산정 기법에 비해 향상된 결과를 나타내었다.

Classification of Human Papillomavirus (HPV) Risk Type via Text Mining

  • Park, Seong-Bae;Hwang, Sohyun;Zhang, Byoung-Tak
    • Genomics & Informatics
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    • 제1권2호
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    • pp.80-86
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    • 2003
  • Human Papillomavirus (HPV) infection is known as the main factor for cervical cancer which is a leading cause of cancer deaths in women worldwide. Because there are more than 100 types in HPV, it is critical to discriminate the HPVs related with cervical cancer from those not related with it. In this paper, the risk type of HPVs using their textual explanation. The important issue in this problem is to distinguish false negatives from false positives. That is, we must find high-risk HPVs as many as possible though we may miss some low-risk HPVs. For this purpose, the AdaCost, a cost-sensitive learner is adopted to consider different costs between training examples. The experimental results on the HPV sequence database show that the consideration of costs gives higher performance. The improvement in F-score is higher than that of the accuracy, which implies that the number of high-risk HPVs found is increased.

헬스케어 환경에서 복잡도를 고려한 R파 검출과 이진 부호화 기반의 부정맥 분류방법 (R Wave Detection Considering Complexity and Arrhythmia Classification based on Binary Coding in Healthcare Environments)

  • 조익성;윤정오
    • 디지털산업정보학회논문지
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    • 제12권4호
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    • pp.33-40
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    • 2016
  • Previous works for detecting arrhythmia have mostly used nonlinear method to increase classification accuracy. Most methods require accurate detection of ECG signal, higher computational cost and larger processing time. But it is difficult to analyze the ECG signal because of various noise types. Also in the healthcare system based IOT that must continuously monitor people's situation, it is necessary to process ECG signal in realtime. Therefore it is necessary to design efficient algorithm that classifies different arrhythmia in realtime and decreases computational cost by extrating minimal feature. In this paper, we propose R wave detection considering complexity and arrhythmia classification based on binary coding. For this purpose, we detected R wave through SOM and then RR interval from noise-free ECG signal through the preprocessing method. Also, we classified arrhythmia in realtime by converting threshold variability of feature to binary code. R wave detection and PVC, PAC, Normal classification is evaluated by using 39 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.41%, 97.18%, 94.14%, 99.83% in R wave, PVC, PAC, Normal.

분류 및 코딩시스템을 이용한 디지털 가상공장 객체의 효율적 관리 (The Efficient Management of Digital Virtual Factory Objects Using Classification and Coding System)

  • 김유석;강형석;노상도
    • 한국CDE학회논문집
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    • 제12권5호
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    • pp.382-394
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    • 2007
  • Nowadays, manufacturing industries undergo constantly growing pressures for global competitions, and they must shorten time and cost in product development and production to response varied customers' requirements. Digital virtual manufacturing is a technology that can facilitate effective product development and agile production by using digital models representing the physical and logical schema and the behavior of real manufacturing systems including products, processes, manufacturing resources and plants. For successful applications of this technology, a digital virtual factory as a well-designed and integrated environment is essential. In this paper, we developed a new classification and coding system for effective managements of digital virtual factory objects, and implement a supporting application to verify and apply it. Furthermore, a digital virtual factory layout management system based on the classification and coding system has developed using XML, Visual Basic.NET and FactoryCAD. By some case studies for automotive general assembly shops of a Korean automotive company, efficient management of factory objects and reduction of time and cost in digital virtual factory constructions are possible.

Indirect structural health monitoring of a simplified laboratory-scale bridge model

  • Cerda, Fernando;Chen, Siheng;Bielak, Jacobo;Garrett, James H.;Rizzo, Piervincenzo;Kovacevic, Jelena
    • Smart Structures and Systems
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    • 제13권5호
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    • pp.849-868
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    • 2014
  • An indirect approach is explored for structural health bridge monitoring allowing for wide, yet cost-effective, bridge stock coverage. The detection capability of the approach is tested in a laboratory setting for three different reversible proxy types of damage scenarios: changes in the support conditions (rotational restraint), additional damping, and an added mass at the midspan. A set of frequency features is used in conjunction with a support vector machine classifier on data measured from a passing vehicle at the wheel and suspension levels, and directly from the bridge structure for comparison. For each type of damage, four levels of severity were explored. The results show that for each damage type, the classification accuracy based on data measured from the passing vehicle is, on average, as good as or better than the classification accuracy based on data measured from the bridge. Classification accuracy showed a steady trend for low (1-1.75 m/s) and high vehicle speeds (2-2.75 m/s), with a decrease of about 7% for the latter. These results show promise towards a highly mobile structural health bridge monitoring system for wide and cost-effective bridge stock coverage.