• Journal of Korean Academy of Nursing
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• v.34 no.3
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• pp.515-524
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• 2004

Purpose: The purpose of this study was to develop and test a model to explain the transition state for Korean middle-aged women focusing on the transition concept. Method: A hypothetical model was constructed based on the transition model of Schumacher & Meleis(1994) and tested. Thehypothetical model consisted of 5 latent variables and 11 observed variables. Exogenous variables were demographic characteristics, obstetric characteristics, and health behavior. Endogenous variables were transition state and quality of life with 6 paths. The data from 221 middle-aged women selected by convenience was analyzed using covariance structure analysis. Result: The final model which was modified from the hypotheticalmodel improved to GFI=0.97, AGFI=0.94, NFI=0.94, and NNFI=0.95. The transition state was influenced directly by demographic characteristics, quality of life, and also indirectly by health behaviors. However, the influence of obstetric characteristics was not significant. The transition state was accountable for 68% of the variance by these factors. Conclusion: These results suggest that enhancing health behaviors of the women are necessary to increase quality of life and it consequently contributes toimproving the transition state. This model could be used to explain the health related vulnerability in these ages and to diagnosis individual women.

• Journal of the Korea Society for Simulation
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• v.13 no.4
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• pp.1-16
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• 2004

The modelling and simulation of the activation process for the heart system is meaningful to understand special excitatory and conductive system in the heart and to study cardiac functions because the heart activation conducts through this system. This thesis proposes two dimensional cellular automaton(CA) model for the activation process of the myocardium and conducted simulation by means of discrete time and discrete event algorithm. In the model, cells are classified into anatomically similar characteristic parts of the heart and each of cells has a set of cells with preassigned properties. Each cell in this model has state variables to represent the state of the cell and has some state transition rules to change values of state variables executed by state transition function. The state transition rule is simple as follows. First, the myocardium cell at rest stay in passive state. Second, if any one of neighborhood cell in the myocardium cell is active state then the state is change from passive to active state. Third, if cell's state is an active then automatically go to the refractory state after activation phase. Four, if cell's state is refractory then automatically go to the passive state after refractory phase. These state transition is processed repeatedly in all cells through the termination of simulation.

• Bulletin of the Korean Chemical Society
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• v.34 no.11
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• pp.3425-3428
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• 2013

We solve the Klein-Gordon equation with the Morse empirical potential energy model. The bound state energy equation has been obtained in terms of the supersymmetric shape invariance approach. The relativistic vibrational transition frequencies for the $X^1{\sum}^+$ state of ScI molecule have been computed by using the Morse potential model. The calculated relativistic vibrational transition frequencies are in good agreement with the experimental RKR values.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6751-6755
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• 2013

Background: Research on cancers with a high rate of mortality such as those occurring in the stomach requires using models which can provide a closer examination of disease processes and provide researchers with more accurate data. Various models have been designed based on this issue and the present study aimed at evaluating such models. Materials and Methods: Data from 330 patients with gastric cancer undergoing surgery at Iran Cancer Institute from 1995 to 1999 were analyzed. Cox-Snell Residuals and Akaike Information Criterion were used to compare parametric and semi-parametric Cox models in modeling transition rates among different states of a multi-state model. R 2.15.1 software was used for all data analyses. Results: Analysis of Cox-Snell Residuals and Akaike Information Criterion for all probable transitions among different states revealed that parametric models represented a better fitness. Log-logistic, Gompertz and Log-normal models were good choices for modeling transition rate for relapse hazard (state $1{\rightarrow}state$ 2), death hazard without a relapse (state $1{\rightarrow}state$ 3) and death hazard with a relapse (state $2{\rightarrow}state$ 3), respectively. Conclusions: Although the semi-parametric Cox model is often used by most cancer researchers in modeling transition rates of multistate models, parametric models in similar situations- as they do not need proportional hazards assumption and consider a specific statistical distribution for time to occurrence of next state in case this assumption is not made - are more credible alternatives.

• BMB Reports
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• v.37 no.5
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• pp.533-537
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• 2004

Previously published kinetic data on the interactions of seventeen different enzymes with their physiological substrates are re-examined in order to understand the connection between ground state binding energy and transition state stabilization of the enzyme-catalyzed reactions. When the substrate ground state binding energies are normalized by the substrate molar volumes, binding of the substrate to the enzyme active site may be thought of as an energy concentration interaction; that is, binding of the substrate ground state brings in a certain concentration of energy. When kinetic data of the enzyme/substrate interactions are analyzed from this point of view, the following relationships are discovered: 1) smaller substrates possess more binding energy concentrations than do larger substrates with the effect dropping off exponentially, 2) larger enzymes (relative to substrate size) bind both the ground and transition states more tightly than smaller enzymes, and 3) high substrate ground state binding energy concentration is associated with greater reaction transition state stabilization. It is proposed that these observations are inconsistent with the conventional (Haldane) view of enzyme catalysis and are better reconciled with the shifting specificity model for enzyme catalysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.5
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• pp.1010-1019
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• 2004

In this paper, we represent Nakagami-m fading channel as finite-State Markov Channel (FSMC) and analyze the performance of wireless communication system with varying the fading channel condition. In FSMC model, the received signal's SNR is divided into finite intervals and these intervals are formed into Markov chain states. Each state is modeled by a BSC and the transition probability is dependent upon the physical characterization of the channel. The steady state probability and average symbol error rate of each state and transition probability are derived by numerical analysis and FSMC model is formed with these values. We found that various fading channels can be represented with FSMC by changing state transition index. In fast fading environment in which state transition index is large, the channel can be viewed as i.i.d. channel and on the contrary, in slow fading channel where state transition index is small, the channel can be represented by simple FSMC model in which transitions occur between just adjacent states. And we applied the proposed FSMC model to analyze the coding gain of random error correcting code on various fading channels via computer simulation.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.1
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• pp.441-447
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• 2014

Background: Multi-state models are appropriate for cancer studies such as gastrectomy which have high mortality statistics. These models can be used to better describe the natural disease process. But reaching that goal requires making assumptions like Markov and homogeneity with time. The present study aims to investigate these hypotheses. Materials and Methods: Data from 330 patients with gastric cancer undergoing surgery at Iran Cancer Institute from 1995 to 1999 were analyzed. To assess Markov assumption and time homogeneity in modeling transition rates among states of multi-state model, Cox-Snell residuals, Akaikie information criteria and Schoenfeld residuals were used, respectively. Results: The assessment of Markov assumption based on Cox-Snell residuals and Akaikie information criterion showed that Markov assumption was not held just for transition rate of relapse (state 1 ${\rightarrow}$ state 2) and for other transition rates - death hazard without relapse (state 1 ${\rightarrow}$ state 3) and death hazard with relapse (state 2 ${\rightarrow}$ state 3) - this assumption could also be made. Moreover, the assessment of time homogeneity assumption based on Schoenfeld residuals revealed that this assumption - regarding the general test and each of the variables in the model- was held just for relapse (state 1 ${\rightarrow}$ state 2) and death hazard with a relapse (state 2 ${\rightarrow}$ state 3). Conclusions: Most researchers take account of assumptions such as Markov and time homogeneity in modeling transition rates. These assumptions can make the multi-state model simpler but if these assumptions are not made, they will lead to incorrect inferences and improper fitting.

• Bulletin of the Korean Chemical Society
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• v.35 no.9
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• pp.2699-2703
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• 2014

We solve the Klein-Gordon equation with the modified Rosen-Morse potential energy model. The bound state energy equation has been obtained by using the supersymmetric shape invariance approach. The relativistic vibrational transition frequencies for the $6^1{\Pi}_u$ state of the $^7Li_2$ molecule have been computed by using the modified Rosen-Morse potential model. The calculated relativistic vibrational transition frequencies are in good agreement with the experimental RKR values.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.18-23
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• 1993

In this paper, we attempt to estimate the state of a finite state system. In such system, we can observe time series data which has some significant behaviors corresponding to its system states. The behavior is characterized by feature parameters extracted from time series. Our thought is that the system output time series data is expressed as a sequence of behavior patterns which are represented by clusters in feature parameters space. An algorithm jointing fuzzy clustering to fuzzy finite state transition model is suggested.

• The Journal of the Korea Contents Association
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• v.11 no.10
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• pp.49-58
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• 2011

Fault Tree Analysis(FTA) builds fault trees to perform safety analysis of systems. However, building fault trees depends on domain knowledge and expertize on target systems and consumes lots of time and efforts. In this paper, we propose a technique that builds fault trees systematically based on state-transition models which are software design artifacts. For the end, this paper identifies conditions that should be satisfied to guarantee safety of state-transition models and develop templates for fault tree construction. This paper also describes the results of appling the proposed method to railway crossing control system.