• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.871-882
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• 2010

In animal tumorigenicity data, the occurrence time of tumor is not observed because the existence of a tumor is examined only at either time of natural death or time of sacrifice for the animal. A three-state model (Health-Tumor onset-Death) is widely used to model the incomplete data. In this paper, we employed a frailty effect into the three-state model to incorporate the dependency of death on tumor occurrence when the time of natural death works as an informative censoring against the tumor onset time. For the inference of parameters, then the EM algorithm is considered in order to deal with missing quantities of tumor onset time and random frailty. The proposed method is applied to the bladder tumor data taken from Lindsey and Ryan (1993, 1994) and a simulation study is performed to show the behavior of the proposed estimators.

• Polymer(Korea)
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• v.32 no.2
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• pp.125-130
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• 2008

A commercial cyclic diphosphonate ester (TPMP) and melamine (MA) was combined and added to polyamide 6 (PA6) to prepare the fire retardant PA6. An increase of the oxygen index to 28.6 as well as an improvement of the UL-94 classification to V-0 rating was observed. Cone measurements explained the rate of heat release (RHR) decreased and TGA showed the early decomposition and high solid residue due to co-addition of TPMP and MA, suggesting the occurrence of synergistic effect of TPMP and MA on fire resistance of PA6. The morphology of the char developed during combust ion showed the appearance of thick, intumescent cells on the surface of retardant PA6, which protects the underlying material from the action of the heat flux or flame and limits the diffusion of combustible volatile products towards the flame and oxygen.

• Structural Monitoring and Maintenance
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• v.2 no.4
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• pp.383-397
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• 2015

This article identifies and addresses current limitations on the use of numerical models for validation and/or calibration of damage detection methodologies that are based on the analysis of the high frequency response of the structure to identify the occurrence of abrupt anomalies. Distributed-plasticity non-linear fiber-based models in combination with experimental data from a full-scale reinforced concrete column test are used to point out current modeling techniques limitations. It was found that the numerical model was capable of reproducing the global and local response of the structure at a wide range of inelastic demands, including the occurrences of rebar ruptures. However, when abrupt sudden damage occurs, like rebar fracture, a high frequency pulse is detected in the accelerations recorded in the structure that the numerical model is incapable of reproducing. Since the occurrence of such pulse is fundamental on the detection of damage, it is proposed to add this effect to the simulated response before it is used for validation purposes.

• Journal of Power Electronics
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• v.17 no.5
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• pp.1327-1337
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• 2017

Photovoltaic (PV) systems are influenced by disproportionate impacts on energy production caused by frequent mismatch cases. The occurrence of multiple maximum power points (MPPs) adds complexity to the tracking process in various PV systems. However, current maximum-power point tracking (MPPT) techniques exhibit limited performance. This paper introduces an enhanced simulated annealing (ESA)-based GMPPT technique against multiple MPP issues in P-V curve with different PV system structures. The proposed technique not only distinguishes global and local MPPs but also performs rapid convergence speed and high tracking accuracy of irradiance changing and restart capability detection. Moreover, the proposed global maximum power tracking algorithm can be applied in the central converter of DMPPT and hybrid PV system to meet various application scenarios. Its effectiveness is verified by simulation and test results.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2001.11a
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• pp.77-82
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• 2001

This paper is contents that measure the ventilation rates and temperature by driving condition of exhaust fan, vapor, contaminant occurrence amount of carbon dioxide etc. In kitchen of apartment house. The ventilation rates in the apartment kitchen measured by Tracer Gas Method. And, temperature of when cook by gas table hood lower part 10cm and floor upside 10cm of kitchen central part, 120cm, 210cm heights measure. As ventilation rates measurement result, ventilation number of times was 0.7(number of times/hour) when did not to operate exhaust fan. but we were measured by 2.3(number of times/hour) when drove strongly. As temperature measurement result at cooking by gas table, temperature showed highest in hood lower part 10cm of case that do not operate exhaust fan. Temperature at kitchen central was most low in 10cm height in talc floor, and 210cm were measured highest. Concentration of carbon dioxide is very high by 4,350ppm after measurement time 10 minutes in state who do not operate exhaust fan at cooking by gas table.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.5
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• pp.242-250
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• 2005

This paper proposes a new protective relaying algorithm using Neuro-Fuzzy and wavelet transform. To organize advanced nuero-fuzzy algorithm, it is important to select target data reflecting various transformer transient states. These data are made of changing-rates of Dl coefficient and RSM value within half cycle after fault occurrence. Subsequently, advanced neuro-fuzzy algorithm is obtained by converging the target data. As a result of applying the advanced neuro-fuzzy algorithm, discrimination between internal fault and inrush is correctly distinguished within 1/2 after fault occurrence. Accordingly, it is evaluated that the proposed algorithm can effectively protect a transformer by correcting discrimination between winding fault and inrushing state.

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.293-296
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• 2004

This paper proposes a new protective relaying algorithm using ACI(Advanced Computational Intelligence) and wavelet transform. To organize the advanced neuro-fuzzy algorithm, it is important to select target data reflecting various transformer transient states. These data are made of changing-rates of D1 coefficient and RSM value within half cycle after fault occurrence. Subsequently, the advanced neuro-fuzzy algorithm is obtained by converging the target data. As a result of applying the advanced neuro-fuzzy algorithm, discrimination between internal fault and inrush is correctly distinguished within half cycle after fault occurrence. Accordingly, it is evaluated that the proposed algorithm can effectively protect a transformer by correcting discrimination between winding fault and inrushing state.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.9
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• pp.4109-4115
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• 2014

Background: Accurate assessment of disease progression requires proper understanding of natural disease process which is often hidden and unobservable. For this purpose, disease status should be clearly detected. But in most diseases it is not possible to detect such status. This study, therefore, aims to present a model which both investigates the unobservable disease process and considers the error probability in diagnosis of disease states. Materials and Methods: Data from 330 patients with gastric cancer undergoing surgery at the Iran Cancer Institute from 1995 to 1999 were analyzed. Moreover, to estimate and assess the effect of demographic, diagnostic and clinical factors as well as medical and post-surgical variables on transition rates and the probability of misdiagnosis of relapse, a hidden Markov multi-state model was employed. Results: Classification errors of patients in alive state without a relapse ($e_{21}$) and with a relapse ($e_{12}$) were 0.22 (95% CI: 0.04-0.63) and 0.02 (95% CI: 0.00-0.09), respectively. Only variables of age and number of renewed treatments affected misdiagnosis of relapse. In addition, patient age and distant metastasis were among factors affecting the occurrence of relapse (state1${\rightarrow}$state2) while the number of renewed treatments and the type and extent of surgery had a significant effect on death hazard without relapse (state2${\rightarrow}$state3)and death hazard with relapse (state2${\rightarrow}$state3). Conclusions: A hidden Markov multi-state model provides the possibility of estimating classification error between different states of disease. Moreover, based on this model, factors affecting the probability of this error can be identified and researchers can be helped with understanding the mechanisms of classification error.

• 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.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.14 no.3
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• pp.71-84
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• 2011

The purpose of this study is to suggest sustainable management of rooftop greening areas. This research is conducted to analyze birth-and-breeding state of planted plants set in extensive rooftop greening, and to examine occurrence aspect of invasive plants and its changes, some features of invasive plants on which can make a basic material for management program of planted plants as a whole. The experimental site is on the rooftop green area of Seoul Women's University which was constructed in 2007. The using method was monitoring rooftop greening areas and analyzing occurrence aspect of invasive plants and its changes by planted plants. Invasive plants were investigated six times overall in April, June, September, November of 2008, and April & June of 2009. As a result, 26 families and 66 species were found invaded. Of which 14 species of Gramineae were invaded the most remarkably. Through these study, it could be inferred some features of invasive plants and major region for it. After the analysis get done about feature of invasive plants, it shows that some invasive plants of all 66 species in total came out, otherwise occurred in a certain time of season. Within the researches eriod showed a higher incidence was found in Artemisia princeps, Conyza canadensis, Coreopsis anceolata, Equisetum arvense, Erigeron annuus, Oxalis corniculata, invasive plant have a lower incidence of plants were identified as Aster koraiensis, Dendranthema zawadsbum. So, when the plan to set a management device regarding occurrence aspect of invasive plants in accordance with planted plants on extensive rooftop greening, it was found that a sustainable & rational management device is desperately needed there for invasive & planted plants of the target area.