• Asia pacific journal of information systems
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• 제6권1호
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• pp.223-240
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• 1996

The paper proposes an approach, called OPNets, for modeling and validating manufacturing systems that is based on object-oriented high-level Petri nets. In OPNets, modeling components of Petri net are constructed into hierarchical objects that communicate with each other by passing messages. To enhance the reusability and maintainability, OPNets organizes a system into hierarchical objects that inherit attributes and behavioral properties from the object of super class and object-interaction relations are separated from the internal structure of object. The modeling scheme of OPNets tries to resolve the complexity problems of Petri net. To illustrate the modeling schemes of OPNets, a storage/retrieval example has been proposed.

• Communications for Statistical Applications and Methods
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• 제24권6호
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• pp.561-581
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• 2017

Bayesian statistics can play a key role in the design and analysis of clinical trials and this has been demonstrated for medical device trials. By 1995 Bayesian statistics had been well developed and the revolution in computing powers and Markov chain Monte Carlo development made calculation of posterior distributions within computational reach. The Food and Drug Administration (FDA) initiative of Bayesian statistics in medical device clinical trials, which began almost 20 years ago, is reviewed in detail along with some of the key decisions that were made along the way. Both Bayesian hierarchical modeling using data from previous studies and Bayesian adaptive designs, usually with a non-informative prior, are discussed. The leveraging of prior study data has been accomplished through Bayesian hierarchical modeling. An enormous advantage of Bayesian adaptive designs is achieved when it is accompanied by modeling of the primary endpoint to produce the predictive posterior distribution. Simulations are crucial to providing the operating characteristics of the Bayesian design, especially for a complex adaptive design. The 2010 FDA Bayesian guidance for medical device trials addressed both approaches as well as exchangeability, Type I error, and sample size. Treatment response adaptive randomization using the famous extracorporeal membrane oxygenation example is discussed. An interesting real example of a Bayesian analysis using a failed trial with an interesting subgroup as prior information is presented. The implications of the likelihood principle are considered. A recent exciting area using Bayesian hierarchical modeling has been the pediatric extrapolation using adult data in clinical trials. Historical control information from previous trials is an underused area that lends itself easily to Bayesian methods. The future including recent trends, decision theoretic trials, Bayesian benefit-risk, virtual patients, and the appalling lack of penetration of Bayesian clinical trials in the medical literature are discussed.

• 한국사회복지학
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• 제62권4호
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• pp.171-192
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• 2010

본 연구는 장애인의 직업재활성과에 영향을 미치는 개인적, 조직적 특성을 밝힘으로써 장애인 직업재활사업의 발전을 위한 실천적 함의를 제공하는데 목적이 있다. 분석을 위해 2009년 서울시에서 운영비를 지원하고 있는 장애인 직업재활시설 내 장애인과 시설에 대한 조사결과를 활용하였으며, 임금수준을 장애인의 직업재활성과로 간주하여 분석하였다. 분석방법으로는 직업재활성과의 개인효과와 조직효과를 구분하기 위해 위계선형모형(Hierarchical Linear Model)을 사용하였다. 분석결과, 장애인 직업재활시설 간 차이가 장애인의 임금수준을 설명하는 비중이 유의하게 높았으며, 개인특성과 조직특성의 상호작용효과를 분석한 결과 장애유형과 조직특성 변수 간의 상호작용효과가 유의한 것으로 나타났다. 정책적으로 장애인 직업재활사업의 성과를 높이기 위해 직업재활시설 간 격차를 줄이기 위한 노력이 필요하며, 장애유형 및 특성에 따라 시설운영에 있어 각별한 관심이 요구된다.

• 한국지능시스템학회논문지
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• 제12권5호
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• pp.405-410
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• 2002

본 논문은 수학적으로 모델링하기 어려운 비선형 시스템을 위한 새로운 계층적 규칙 기반 퍼지 시스템 모델링 기법을 제안한다. 제안된 기법은 퍼지 규칙 기반 구조를 상위 규칙 기반과 하위 규칙 기반으로 나누어 계층화시키는 새로운 모델링 방법이다. 본 논문에서 제안한 계층적 퍼지 규칙을 적용함으로써 퍼지 규칙을 효율적이고 논리적으로 이용할 수 있음은 물론, 퍼지 규칙의 효율적, 논리적 사용은 퍼지 시스템의 정확성을 높일 수 있고 구조를 명료화시킬 수 있음을 보인다. 유전알고리즘은 제안된 퍼지 규칙의 파라미터 최적화 과정에 이용된다. 마지막으로, 복잡한 비선형 시스템에 대한 퍼지 모델링 결과를 통해서 제안된 기법의 타당성 및 효용성을 검증하고 타 기법의 결과와 비교한다.

• 로봇학회논문지
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• 제2권3호
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• pp.262-269
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• 2007

Hierarchical Planning based on Abstraction of World Elements and Operators(HiPAWO) is proposed for mobile robots task planning, where abstraction of world elements is used for hierarchical planning and abstraction of operators is used for hierarchical decomposition of abstracted actions. Especially, a hierarchical domain theory based on JAH(Joint of Action Hierarchy)-graph is proposed to improve efficiency of planning, where a number of same actions are included in both adjacent hierarchical levels of domain theories to provide relationships between adjacent hierarchical levels. To show the validities of our proposed HiPAWO, experimental results are illustrated and will be compared with two other classical planning methods.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.176-176
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• 2018

This study presents a regional, probabilistic framework for estimating streamflow via spatial scaling in the Great Lakes basin, which is the largest lake system in the world. The framework follows a two-fold strategy including (1) a quadratic-programming based optimization model a priori to explore the model structure, and (2) a time-varying hierarchical Bayesian model based on insights found in the optimization model. The proposed model is developed to explore three innovations in hierarchical modeling for reconstructing historical streamflow at ungaged sites: (1) information of physical characteristics is utilized in spatial scaling, (2) a time-varying approach is introduced based on climate information, and (3) heteroscedasticity in residual errors is considered to improve streamflow predictive distributions. The proposed model is developed and calibrated in a hierarchical Bayesian framework to pool regional information across sites and enhance regionalization skill. The model is validated in a cross-validation framework along with four simpler nested formulations and the optimization model to confirm specific hypotheses embedded in the full model structure. The nested models assume a similar hierarchical Bayesian structure to our proposed model with their own set of simplifications and omissions. Results suggest that each of three innovations improve historical out-of-sample streamflow reconstructions although these improvements vary corrsponding to each innovation. Finally, we conclude with a discussion of possible model improvements considered by additional model structure and covariates.

• 정보처리학회논문지C
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• 제8C권1호
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• pp.97-104
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• 2001

본 논문에서는 무선망에서 채널할당을 받은 호가 무선 패킷 데이터를 서비스하는 경우의 성능분석 수행을 위한 계층 모델을 제안한다. 제안된 계층 모델로는 상위계층으로 무선자원 관리를 위한 채널할당 모델을, 하위계층으로 에러발생을 고려한 패킷 재전송 프로토콜 모델을 고려하였으며 이들 모델은 모델링 도구인 SRN을 이용하여 각각 개발한다. 추계적 페트리 네트의 확장형인 SRN은 시스템 성능분석을 위한 간결한 모델링 기능을 제공해 주며 모델에 적절한 보상률(reward) 기능을 부여함으로써 원하는 성능지표를 구할 수 있다. 이들 두 계층간의 상호 연관된 매개변수의 값인 서비스 시간과 패킷 발생률은 고정점 반복순환(fixed-point iteration) 기법을 사용하여 구한다. 즉 상위계층의 호 서비스 시간은 한 호당 K개의 패킷전송을 완료할때 까지 소요되는 시간인 하위계층 모델의 지연시간으로 구할 수 있고, 하위계층 모델의 패킷 발사율은 상위계층의 새로운 호와 핸드오프 호의 발생률로부터 구할 수 있다.

• 아동학회지
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• 제30권4호
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• pp.87-97
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• 2009

This study used Hierarchical Linear Modeling analysis to investigate the effects of individual self-regulated cognitive strategies and public education on middle school students' academic achievement. Participants were 6389 (boys 3287, girls 3102) middle school students from the 2005 data of the Korea Education Longitudinal Study. Results were as follows : (1) there were significant differences among different schools in middle school students' academic achievement, i.e. 20% of variance in English achievement and 15% of variance in mathematics achievement were explained by school differences. (2) Students' elaboration and meta-cognitive strategy influenced academic achievement positively. (3) Predictor variables by ability grouping, supplementary class, and/or self-learning class had no significant effects on students' academic achievement.

• Coupled systems mechanics
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• 제7권5호
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• pp.509-524
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• 2018

A hierarchical multi-scale modeling strategy devoted to the study of a Bitumen-Bound Gravel (BBG) is presented in this paper. More precisely, the paper investigates the temperature-dependent linear viscoelastic of the material when submitted to low deformations levels and moderate number of cycles. In such a hierarchical approach, 3D digital Representative Elementary Volumes are built and the outcomes at a scale (here, the sub-mesoscale) are used as input data at the next higher scale (here, the mesoscale). The viscoelastic behavior of the bituminous phases at each scale is taken into account by means of a generalized Maxwell model: the bulk part of the behavior is separated from the deviatoric one and bulk and shear moduli are expanded into Prony series. Furthermore, the viscoelastic phases are considered to be thermorheologically simple: time and temperature are not independent. This behavior is reproduced by the Williams-Landel-Ferry law. By means of the FE simulations of stress relaxation tests, the parameters of the various features of this temperature-dependent viscoelastic behavior are identified.

• 제어로봇시스템학회논문지
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• 제11권10호
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• pp.843-850
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• 2005

FBA(flux balance analysis) with Boolean rules for representing regulatory events has correctly predicted cellular behaviors, such as optimal flux distribution, maximal growth rate, metabolic by-product, and substrate concentration changes, with various environmental conditions. However, until now, since FBA has not taken into account a hierarchical regulatory network, it has limited the representation of the whole transcriptional regulation mechanism and interactions between specific regulatory proteins and genes. In this paper, in order to solve these problems, we describe the construction of hierarchical regulatory network with defined symbols and the introduction of a weight for representing interactions between symbols. Finally, the whole cellular behaviors with time were simulated through the linkage of a hierarchical regulatory network module and dynamic simulation module including FBA. The central metabolic network of E. coli was chosen as the basic model to identify our suggested modeling method.