• Title/Summary/Keyword: Compensatory models

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Consumer Choice Model in No-frills Airline Industry

  • Ha, Hong Youl
    • Asia-Pacific Journal of Business
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    • v.1 no.2
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    • pp.23-46
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    • 2010
  • Despite the explosive growth of no-frill airline industry, very little is known about how consumers make purchase decision in such settings. Today's airline industry requires choice models consistent with consumers' true preference sets. This study used conjoint analysis to identify these ideal choice models. 38 percent of the subjects were found to use compensatory and 62 percent non-compensatory models. Our findings suggest a need to base choice-making promotions on ideal choice models if the promotion is to lead consumers to decisions consistent with true preferences.

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On the Optimal Decision Making in the Compensatory Models (보정모형에서의 최적 의사결정에 관한 연구)

  • Chung, Soon-Suk
    • Journal of the Korea Safety Management & Science
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    • v.8 no.4
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    • pp.205-218
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    • 2006
  • Multi-criteria decision making is deducing the relative importance in the criterion of decision making and each alternative which is able to making a variety of choices measures the preferred degree in the series of town ranking criterions. Moreover, this is possible by synthesizing them systematically. In general, a fundamental problem decision maker solve for multi-criteria decision making is evaluating a set of activities which an considered as the target logically, and this kind of work is evaluated and synthesized by various criterions of the value which a chain of activities usually hold in common. In this paper, we use the compensatory models for the optimal decision making. For the purpose of optimal decision making, the data of five different car models are used in Europe.

Hemodynamic Stress Changes due to Compensatory Remodelling of Stenosed Coronary Artery (협착이 발생된 관상동맥의 보상적 재형성에 따른 혈류역학적 응력변화)

  • Cho, Min-Tae;Suh, Sang-Ho;Lee, Byoung-Kwon;Kwon, Hyuck-Moon;Yoo, Sang-Sin
    • Proceedings of the KSME Conference
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    • 2001.11b
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    • pp.529-532
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    • 2001
  • The purposes of the present study are to investigate hemodynamic characteristics and to define shear-sensitive remodeling in the stenosed coronary models. Two models for the compensatory remodelling used for this research are a pre-stenotic dilation and a post-stenotic dilation models for the computer simulation. The peak wall shear stress on the post-stenotic model is higher than that of the pre-stenotic model. Two recirculation zones are generated in the pre-stenotic model, and the zones in the pre-stenotic model are smaller than those in the post-stenotic model. Variation of the wall shear stress in the pre-stenotic model is lower than that in the post-stenotic model. In computer simulation with the post-stenotic model, higher temporal and spatial shear fluctuation and stress suggested shear-sensitive remodeling. Shear-sensitive remodeling may be associated with the increased risk of plaque rupture, the underlying cause of acute coronary syndromes, and sudden cardiac death.

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A Study on Survey and Applicability of Evaluation and Selection Models for Software Products (소프트웨어 제품을 위한 평가 선정 모형의 조사 및 적용성에 관한 연구)

  • Park, Ho-In;Jung, Ho-Won
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.7
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    • pp.1706-1718
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    • 1997
  • The rapid increase in the use of many commercial software products has necessitated a systematic and objective method of their evaluation and selection. Our study focuses on the assignment of weights and choice of proper models. First, the weights of attributes are assigned consistently by using the analytic hierarchy process. Second, many models, which can be suitable for the structure of evaluation and selection for software product, are collected, categorized into two types of model, and compared in terms of their strength and weakness. The models involved are four compensatory models and seven noncompensatory models. Finally, they are analyzed through the application of specific software products(database data modelers) in terms of their attributes. Our study enhances the applicability of models to a variety of user requirement utilizing the evaluating procedure and applications.

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Determination of Forest Road Construction Priority Order Using Multiple Criteria Decision Making Methods (다기준의사결정법(多基準意思決定法)에 의한 임도개설순위(林道開設順位)의 결정(決定))

  • Cha, Du Song;Cho, Koo Hyun;Kim, Jong Yoon
    • Journal of Korean Society of Forest Science
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    • v.85 no.2
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    • pp.149-157
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    • 1996
  • The applications of multiple criteria decision making(MCDM) methods were investigated to determine the priority order in forest road construction for timber harvesting and silvicultrual activities in 22 regions. In this paper, MCDM methods have five methods from two kinds of models. The one is non-compensatory preference model including maximin and maximax method; the other is compensatory preference model including simple additive weighting method(SAW), hierarchical additive weighting method(HAW) and technique for order preference by similarity to ideal solution(TOPSIS), SAW and TOPSIS methods turned out to be the most adequate for forest road construction priority order among the five methods tested in this study.

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On the Multi-attribute Decision Making by Entropy Methods (엔트로피 방법에 의한 다 요소 의사결정에 관한 연구)

  • 정순석
    • Journal of the Korea Safety Management & Science
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    • v.6 no.2
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    • pp.177-186
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    • 2004
  • Decision analysis has becomes an important technique for decision making in the face of uncertainty. It is characterized by enumerating all the available courses of action, identifying the payoffs for all possible outcomes, and quantifying the subjective probabilities for the all possible random events. When the data are available, decision analysis becomes a powerful tool for determining an optimal course of action. We study the multi-attribute decision making in a compensatory models. In this paper, we use the entropy methods in weights calculating. For the purpose of making optimal decision, the data of five different car models are used. For computing, we used Visual Numerica Version 1.0 software package.

Application and Evaluation of An Attitudinal Model for Travel Mode Choice Behavior Analysis (교통수단 선택행태 분석을 위한 태도모형의 적용 및 평가)

  • 신동호
    • Journal of Korean Society of Transportation
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    • v.11 no.2
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    • pp.5-26
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    • 1993
  • In order to analyze travel mode choice behavior, behavioral models including logit model, based on revealed preference theory, have been using easily measurable variables such as individual socioeconomic characteristics and physical attributes of travel modes. But some recent attitudinal models of travel choice behavior have implied that the negligence of individual psychological variables and individual choice constraints in travel mode choice might preclude better prediction of individual travel mode choice behavior. In this context, this study was attempted to reconstruct an attitudinal model(AM), especially focused on the decision rules in travel mode choice decision making process, consistent with the conceptual framework relating individual attitude and choice constraints to choice behavior. And to evaluate the strengths of the AM to other comparative models(logit, linear-additive, conjunctive, lexicographic model) in predicting travel mode choice bebavior, an empirical study of the mode choice in work-trip to CBD in Seoul was performed. According to the results the percent of correct prediction(PCP) derived from the AM was higher than those derived from comparative models by at least 7 to 20% in predicting travel mode choice. But each model produced a different prediction accuracy depending on market segmentation by travel modal users, individual socioeconomic characteristics, transportation system characteristics, and satisfaction levels. The finding that different groups divided by a certain criterion employ different decision rules supports the necessity of developing a choice model such as the AM combining compensatory and noncompensatory decision rules, and suggests that a proposed transportation system management plan or policy may have different effects on each group.

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Induced Mutant Animal Models for Studying the Genetics of Hypertension and Atherosclerosis

  • Oh, Goo-Taeg
    • Toxicological Research
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    • v.17
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    • pp.289-292
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    • 2001
  • Gene targeting allows precise, predetermined changes to be made in a chosen gene in the mouse genome. To date, targeting has been used most often for generation of animals completely lacking the product of a gene of interest. Models of essential hypertension have been produced by mutated genes relating renin angiotensin system. The most significant contribution to understanding the genetic etiology of essential hypertension is probably the demonstration that discrete alterations in the expression of a variety of different genes can individually cause changes in the blood pressures of mice, even when the mice have all their compensatory mechanisms intact. These effects are readily detected in animals having moderate decreases in gene function due to heterozygosity for gene disruptions or modest increases due to gene duplication. As a species the mouse is highly resistant to atherosclerosis. However. through induced mutations it has been possible to develop lines oj mice that are deficient in apolipoprotein E, a ligand important in lipoprotein clearance, develop atherosclerotic lesions resembling those observed in humans. The atherosclerotic lesions in apoE-deficient mice have been well characterized, and they resemble human lesions in their sites of predilection and progression to the fibroproliferative stage. Other promising models are mice that are deficient in the low-density lipoprotein receptor. Considerable work still remains to be done in dissecting out in a rigorous manner the effects of alterations in single genes on the induction or progression of atherosclerosis and on the control of blood pressures. Perhaps even more exciting is the opportunity now becoming available to breed animals in which the effects oj precise differences in more than one gene can be studied in combination.

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How Through-Process Optimization (TPO) Assists to Meet Product Quality

  • Klaus Jax;Yuyou Zhai;Wolfgang Oberaigner
    • Corrosion Science and Technology
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    • v.23 no.2
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    • pp.131-138
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    • 2024
  • This paper introduces Primetals Technologies' Through-Process Optimization (TPO) Services and Through-Process Quality Control (TPQC) System, which integrate domain knowledge, software, and automation expertise to assist steel producers in achieving operational excellence. TPQC collects high-resolution process and product data from the entire production route, providing visualizations and facilitating quality assurance. It also enables the application of artificial intelligence techniques to optimize processes, accelerate steel grade development, and enhance product quality. The main objective of TPO is to grow and digitize operational know-how, increase profitability, and better meet customer needs. The paper describes the contribution of these systems to achieving operational excellence, with a focus on quality assurance. Transparent and traceable production data is used for manual and automatic quality evaluation, resulting in product quality status and guiding the product disposition process. Deviation management is supported by rule-based and AI-based assistants, along with monitoring, alarming, and reporting functions ensuring early recognition of deviations. Embedded root cause proposals and their corrective and compensatory actions facilitate decision support to maintain product quality. Quality indicators and predictive quality models further enhance the efficiency of the quality assurance process. Utilizing the quality assurance software package, TPQC acts as a "one-truth" platform for product quality key players.

A Survival Prediction Model of Rats in Uncontrolled Acute Hemorrhagic Shock Using the Random Forest Classifier (랜덤 포리스트를 이용한 비제어 급성 출혈성 쇼크의 흰쥐에서의 생존 예측)

  • Choi, J.Y.;Kim, S.K.;Koo, J.M.;Kim, D.W.
    • Journal of Biomedical Engineering Research
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    • v.33 no.3
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    • pp.148-154
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    • 2012
  • Hemorrhagic shock is a primary cause of deaths resulting from injury in the world. Although many studies have tried to diagnose accurately hemorrhagic shock in the early stage, such attempts were not successful due to compensatory mechanisms of humans. The objective of this study was to construct a survival prediction model of rats in acute hemorrhagic shock using a random forest (RF) model. Heart rate (HR), mean arterial pressure (MAP), respiration rate (RR), lactate concentration (LC), and peripheral perfusion (PP) measured in rats were used as input variables for the RF model and its performance was compared with that of a logistic regression (LR) model. Before constructing the models, we performed 5-fold cross validation for RF variable selection, and forward stepwise variable selection for the LR model to examine which variables were important for the models. For the LR model, sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (ROC-AUC) were 0.83, 0.95, 0.88, and 0.96, respectively. For the RF models, sensitivity, specificity, accuracy, and AUC were 0.97, 0.95, 0.96, and 0.99, respectively. In conclusion, the RF model was superior to the LR model for survival prediction in the rat model.