• Asian Pacific Journal of Cancer Prevention
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• 제15권10호
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• pp.4143-4145
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• 2014

Background: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) Ewing sarcoma (ES) outcome data. The aim of this study was to identify and optimize ES-specific survival prediction models and sources of survival disparities. Materials and Methods: This study analyzed socio-economic, staging and treatment factors available in the SEER database for ES. 1844 patients diagnosed between 1973-2009 were used for this study. For the risk modeling, each factor was fitted by a Generalized Linear Model to predict the outcome (bone and joint specific death, yes/no). The area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. Results: The mean follow up time (S.D.) was 74.48 (89.66) months. 36% of the patients were female. The mean (S.D.) age was 18.7 (12) years. The SEER staging has the highest ROC (S.D.) area of 0.616 (0.032) among the factors tested. We simplified the 4-layered risk levels (local, regional, distant, un-staged) to a simpler non-metastatic (I and II) versus metastatic (III) versus un-staged model. The ROC area (S.D.) of the 3-tiered model was 0.612 (0.008). Several other biologic factors were also predictive of ES-specific survival, but not the socio-economic factors tested here. Conclusions: ROC analysis measured and optimized the performance of ES survival prediction models. Optimized models will provide a more efficient way to stratify patients for clinical trials.

• 음성과학
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• 제10권2호
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• pp.99-109
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• 2003

The purpose of this study was to analyze and compare head register with chest register of singers acoustically. Fifteen healthy tenor major students were participated. Fifteen healthy untrained adults were chosen as the control group for this study. Long term average (LTA) power spectrum using the Fast Fourier transform (FFT) algorithm and Linear predictive coding (LPC) filter response were made with /a/ sustained in both head (G4, 392 Hz) and chest registers (C3, 131 Hz). Statistical analysis was performed using the Mann-Whitney test. In the LTA power spectrum, head register of singers increased in the level of energy gain within the frequency of 2.2-3.4 kHz (p<0.01), and 7.5-8.4 kHz (p<0.01, p<0.05). Chest register of singers increased in the frequency of 2.2-3.1 kHz (p<0.01), 7.8-8.4 kHz (p<0.05) and around 9.6 kHz (p<0.01). The LTA power spectrum revealed a peak of acoustic energy around 2,500 Hz, known as the singer's formant and another peak of acoustic energy around 8,000 Hz in the singer's voice.

• 대한전기학회논문지:전력기술부문A
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• 제48권6호
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• pp.789-799
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• 1999

In this paper, the optimization of fuzzy inference systems is proposed for fuzzy model of nonlinear systems. A fuzzy model needs to be identified and optimized by means of the definite and systematic methods, because a fuzzy model is primarily acquired by expert's experience. The proposed rule-based fuzzy model implements system structure and parameter identification using the HCM(Hard C-mean) clustering method, genetic algorithms and fuzzy inference method. Two types of inference methods of a fuzzy model are the simplified inference and linear inference. in this paper, nonlinear systems are expressed using the identification of structure such as input variables and the division of fuzzy input subspaces, and the identification of parameters of a fuzzy model. To identify premise parameters of fuzzy model, the genetic algorithms is used and the standard least square method with the gaussian elimination method is utilized for the identification of optimum consequence parameters of fuzzy model. Also, the performance index with weighting factor is proposed to achieve a balance between the performance results of fuzzy model produced for the training and testing data set, and it leads to enhance approximation and predictive performance of fuzzy system. Time series data for gas furnace and sewage treatment process are used to evaluate the performance of the proposed model.

• 천문학회지
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• 제47권6호
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• pp.209-214
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• 2014

In this study we develop a set of solar proton event (SPE) forecast models with NOAA scales by Multi Layer Perceptron (MLP), one of neural network methods, using GOES solar X-ray flare data from 1976 to 2011. Our MLP models are the first attempt to forecast the SPE scales by the neural network method. The combinations of X-ray flare class, impulsive time, and location are used for input data. For this study we make a number of trials by changing the number of layers and nodes as well as combinations of the input data. To find the best model, we use the summation of F-scores weighted by SPE scales, where F-score is the harmonic mean of PODy (recall) and precision (positive predictive value), in order to minimize both misses and false alarms. We find that the MLP models are much better than the multiple linear regression model and one layer MLP model gives the best result.

• Smart Structures and Systems
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• 제4권4호
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• pp.493-515
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• 2008

Semi-active control systems have attracted a great deal of attention in recent years because these systems can operate on battery power alone, proving advantageous during seismic events when the main power source of the structure may likely fail. The behavior of semi-active devices is often highly non-linear and requires suitable and efficient control algorithm. This paper presents the comparative study and performance of variable semi-active friction dampers by using recently proposed predictive control law with direct output feedback. In this control law, the variable slip force of semi-active variable friction damper is kept slightly lower than the critical friction force, which allows the damper to remain in the slip state during an earthquake, resulting in improved energy dissipation capability. This control algorithm is able to produce a continuous and smooth slip forces for a variable friction damper. The numerical examples include a structure controlled with multiple variable semi-active friction dampers and with multiple passive friction dampers. A parameter, gain multiplier defined as the ratio of damper force to critical damper control force, is investigated under four different real earthquake ground motions, which plays an important role in the present control algorithm of the damper. The numerically evaluated optimum parametric value is considered for the analysis of the structure with dampers. The numerical results of the variable friction dampers show better performance over the passive dampers in reducing the seismic response of structures.

• Asian Pacific Journal of Cancer Prevention
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• 제16권15호
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• pp.6477-6480
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• 2015

Purpose: Given the importance of sun protection in the prevention of skin cancer, this study was designed to determine predictors of sun-protective practices among a sample of Iranian female college students based on protection motivation theory (PMT) variables. Materials and Methods: In this cross-sectional study, a total of 201 female college students in Iran University of Medical Sciences were selected. Demographic and PMT variables were assessed with a 67-item questionnaire. Multiple linear regression was used to identify demographic and PMT variables that were associated with sun-protective practices and intention. Results: one percent of participants always wore a hat with a brim, 3.5% gloves and 15.9% sunglasses while outdoors. Only 10.9% regularly had their skin checked by a doctor. Perceived rewards, response efficacy, fear, self-efficacy and marital status were the five variables which could predict 39% variance of participants intention to perform sun-protective practices. Also, intention and response cost explained 31% of the variance of sun-protective practices. Conclusions: These predictive variables may be used to develop theory-based education interventions to prevent skin cancer among college students.

• Earthquakes and Structures
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• 제14권3호
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• pp.203-214
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• 2018

Predictive demand and collapse fragility functions are two essential components of the probabilistic seismic demand analysis that are commonly developed based on statistics with enormous, costly and time consuming data gathering. Although this approach might be justified for research purposes, it is not appealing for practical applications because of its computational cost. Thus, in this paper, Bayesian regression-based demand and collapse models are proposed to eliminate the need of time-consuming analyses. The demand model developed in the form of linear equation predicts overall maximum inter-story drift of the lowto mid-rise regular steel moment resisting frames (SMRFs), while the collapse model mathematically expressed by lognormal cumulative distribution function provides collapse occurrence probability for a given spectral acceleration at the fundamental period of the structure. Next, as an application, the proposed demand and collapse functions are implemented in a seismic fragility analysis to develop fragility and consequently seismic demand curves of three example buildings. The accuracy provided by utilization of the proposed models, with considering computation reduction, are compared with those directly obtained from Incremental Dynamic analysis, which is a computer-intensive procedure.

• 생물정신의학
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• 제18권1호
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• pp.36-45
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• 2011

Objectives : Though a proportion of Alzheimer's disease(AD) patients treated with donepezil have shown positive response on cognition, but the responders' characteristics are still uncertain. This study attempts to identify whether a single oral dose of donepezil(5mg) can change cognition and the relationship between single dose responder items and long-term responder are examined. Methods : Twenty-three AD patients for single donepezil challenge study group and eleven AD patients for controls were participated in the study. Seven days after baseline study for neuropsychological test and EEG, same studies were rechecked after donepezil medication in study group. In donepezil study groups, 12 weeks after donepezil medication, neuropsychological test and EEG were rechecked. Results : After single donepezil challenge, forward digit span, Rey-Osterrieth Complex Figure Test copy, SVLT delayed recall were significantly improved, and beta spectra power in anterior, theta spectra power in posterior field were significantly decreased. According to linear regression analysis, forward digit span after single donepezil challenge was significantly positive correlated with long-term responders. Conclusions : This study suggests that single donepezil medication can significantly change cognitive functions and EEG in AD patients. Among these responsive items, forward digit span was significantly correlated with long-term responder.

• Asian Pacific Journal of Cancer Prevention
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• 제17권4호
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• pp.2229-2233
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• 2016

Background: Breast cancer is one of the most common cancers among women in the world. Early detection is necessary to improve outcomes and decrease related costs. The aim of this study was to assess the predictive power of health locus of control as a modifying factor in the Health Belief Model (HBM) for prediction of breast self-examination. Materials and Methods: In this cross- sectional study, 400 women selected through the convenience sampling from health centers. Data were collected using part of the Champion's HBM scale (CHBMS), the Health Locus of Control Scale and a self administered questionnaire. For data analysis by SPSS the independent T test, Chi square test, logistic and linear regression modes were appliedl. Results: The results showed that 10.9% of the participants reported performing BSE regularly. Health locus of control did not act as a predictor of BSE as a modifying factor. In this study, perceived self-efficacy was the strongest predictor of BSE performance (Exp (B) =1.863) with direct effect, while awareness had direct and indirect influence. Conclusions: For increasing BSE, improvement of self-efficacy especially in young women and increasing knowledge about cancer is necessary.

• 대한간호학회지
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• 제29권4호
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• pp.829-840
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• 1999

This study was conducted to construct a hypothetical model of depression in Korean adolescent women and validate the fit of the model to the empirical data. The data were collected from 345 high school girls in Seoul, from May 1 to June 30, 1998. The instruments were the Body Mass Index, Physical Satisfaction Scale, Family Adaptatibility and Cohesion Evaluation Scale III, Family Satisfaction Scale, CES-D and School Adptation Scale. The data were analyzed using descriptive statistics with the pc -SAS program. The Linear Structural Relationship(LISREL) modeling process was used to find the best fit model which would predict the causal relationships among the variables. The overall fit of the hypothetical model to the data was moderate ［X$^2$＝69.6(df＝17, p＝.000), GFI ＝0.95, AGFI＝0.90, RMR＝0.087, NNFI＝0.86, NFI＝0.90］. The predictable variables, especially menstrual symptoms, physical symptoms and family function, had a significant direct effect on depression. but school life adaptation did not have a significant direct effect. These variables explained 18.1% of the total variance.