• PNF and Movement
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• v.20 no.3
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• pp.399-408
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• 2022

Purpose: This study investigated the differences in winged scapula between the symptomatic side and asymptomatic side, the reliability of the winged scapula test, and the correlation between winged scapula and the stability of the scapula in patients with subacromial impingement syndrome. Methods: Twenty-four patients with unilateral subacromial impingement syndrome participated in this study. Winged scapula was compared between the symptomatic and asymptomatic sides using a scapulometer. The reliability of the scapulometer was assessed by calculating the intraclass correlation coefficient (ICC), standard error of measurement (SEM), and minimal clinically important difference (MCID). The correlation between winged scapula and the results of the upper quarter Y-balance test were also obtained. Conclusion: Winged scapula was significantly greater on the symptomatic side compared with the asymptomatic side (p < 0.05). High to excellent ICCs were obtained for the winged scapula test, and SEM and MCID values were obtained for winged scapula (SEM: 0.2-0.3 cm, MCID: 0.6-0.8 cm); however, winged scapula and the results of the upper quarter Y-balance test were not correlated. Conclusion: The scapulometer is useful for measuring winged scapula in patients with subacromial impingement syndrome.

• Steel and Composite Structures
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• v.44 no.5
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• pp.603-617
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• 2022

Structural design, in general, is developed through trial and error technique which is guided by standards criteria and based on the intuition and experience of the engineer, a context that leads to structural over-dimensioning, with uneconomic solutions. Aiming to find the optimal design, structural optimization methods have been developed to find a balance between cost, structural safety, and material performance. These methods have become a great opportunity in the steel structural engineering domain since they have as their main purpose is weight minimization, a factor directly correlated to the real cost of the structure. Assuming an objective function of minimum weight with stress and displacement constraints provided by Brazilian standards, the present research proposes the sizing optimization and combined approach of sizing and shape optimization, through a software developed to implement the Simulated Annealing metaheuristic algorithm. Therefore, two steel plane frame layouts, each admitting four typical truss geometries, were proposed in order to expose the difference between the optimal solutions. The assessment of the optimal solutions indicates a notable weight reduction, especially in sizing and shape optimization combination, in which the quantity of design variables is increased along with the search space, improving the efficiency of the optimal solutions achieved.

• Asia Marketing Journal
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• v.11 no.1
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• pp.29-38
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• 2009

Estimating the Bass diffusion model often creates a time-interval bias, which leads the OLS approach to overestimate sales at early stages and underestimate sales after the peak. Further, a specification error from omitted variables might raise serial correlations among residuals when marketing actions are not incorporated into the diffusion model. Autocorrelated disturbances may yield unbiased but inefficient estimation, and therefore invalid inference results. This phenomenon warrants a modified approach to estimating the Bass diffusion model. In this paper, the authors propose a modified Bass diffusion model handling autocorrelated disturbances. To validate the new approach, authors applied the method on two different data-sets: CT Scanners in the U.S, and FPD TV sales in Korea. The results showed improved model fit and the validity of the proposed model.

• The Korean Journal of Applied Statistics
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• v.36 no.6
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• pp.573-589
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• 2023

In a piecewise linear trend model, the change points coincide with the mean change points of the first differenced time series. Therefore, by detecting the mean change points of the first differenced time series, one can estimate the change points of the piecewise linear trend model. In this paper, based on this fact, a method is proposed for detecting change points of the piecewise linear trend model using the simple moving average of the first differenced time series rather than estimates of the slope or residuals. Our Monte Carlo simulation experiments show that the proposed method performs well in estimating the number of change points not only when the error terms in the piecewise linear trend model are independent but also when they are serially correlated.

• Safety and Health at Work
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• v.14 no.4
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• pp.431-437
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• 2023

Background: Depressive symptoms (DS) can erode physical and mental health; social support (SS) is considered a buffer for DS and a promoter for improving coping and recovery abilities. However, there is almost no research on the mediating role of negative coping (NC) in SS and DS, especially among firefighters. Methods: A cross-sectional survey was conducted among firefighters in Chongqing, China, and the valid data of 407 firefighters were collected through questionnaires distributed on the WeChat platform in 2020. Statistical Product and Service Solutions (SPSS) 26.0 is used for descriptive statistics and correlation analysis. Structural equation modeling was adopted to analyze the association among SS, NC, and DS. The mediation effect is also evaluated. Results: Firefighters' detection rate of DS is 23.3%, and when they receive more SS were less likely to develop DS. NC was positively correlated with DS (β = 0.54, p < 0.001) after controlling for SS. Besides, the results of structural equation modeling showed that NC partially mediates the relationship between SS and DS (standard error = 0.039, indirect effects = 0.109, 95% confidence interval: 0.047-0.200 p < 0.001). Conclusion: NC has a partial indirect effect between SS and DS among firefighters. SS could not only affect DS directly but also indirect work on it by affecting NC. This discovery will be a novel and meaningful part of the research on the firefighter population.

• Progress in Medical Physics
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• v.17 no.3
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• pp.136-143
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• 2006

The respiratory gating radiation therapy which Irradiates only in the stable respiratory period with analyzing the periodic motion of a reflective marker on the patient's abdomen has been applied to the precise radiation treatment in order to minimize the effect of organ motion induced by the respiration. This respiratory gating system establishes irradiation region using the amplitude-based or phase-based method. Although phase-based method Is preferred because of the stability in the real treatment conditions, it has some limits to explain the exact correlation between the marker motion and organ motion. Even when the variation of amplitude which can introduce target motion considered as an error is produced, the phase-based method has the possibility to irradiate including the error positions. In this study, the error analysis program was developed for the verification of the tumor position's variation correlated with the variation of marker's amplitude which can be occurred during a phase-based respiratory sating treatment. The analysis program was tested with a virtual treatment record file and with a record file using moving phantom which were modified considering the irregular amplitude's variation simulating the real clinical situations. In both cases, accurate discrimination of error points and error calculation were produced. When the treatment record files of a real patient were analyzed with the program, the accurate recognition and calculation of the error points were also verified. The analysis program developed in this study will be applied as a useful tool for the analysis of errors due to the irregular variation of patients' respiration during the phase-base respiratory gating radiation treatment.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.157-168
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• 2016

In image processing and computer vision fields, mean squared error (MSE) has popularly been used as an objective metric in image quality optimization problems due to its desirable mathematical properties such as metricability, differentiability and convexity. However, as known that MSE is not highly correlated with perceived visual quality, much effort has been made to develop new image quality assessment (IQA) metrics having both the desirable mathematical properties aforementioned and high prediction performances for subjective visual quality scores. Although recent IQA metrics having the desirable mathematical properties have shown to give some promising results in prediction performance for visual quality scores, they also have high computation complexities. In order to alleviate this problem, we propose a new fast IQA metric using a simple Laplace operator. Since the Laplace operator used in our IQA metric can not only effectively mimic operations of receptive fields in retina for luminance stimulus but also be simply computed, our IQA metric can yield both very fast processing speed and high prediction performance. In order to verify the effectiveness of the proposed IQA metric, our method is compared to some state-of-the-art IQA metrics. The experimental results showed that the proposed IQA metric has the fastest running speed compared the IQA methods except MSE under comparison. Moreover, our IQA metric achieves the best prediction performance for subjective image quality scores among the state-of-the-art IQA metrics under test.

• Geophysics and Geophysical Exploration
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• v.10 no.4
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• pp.241-251
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• 2007

The observed spectra from Odaesan earthquake were fitted to a point-source spectral model to evaluate the source spectrum and spatial features of the modelling error. The source spectrum was calculated by removing from the observed spectra the path and site dependent responses (Yun, 2007) that were previously revealed through an inversion process applied to a large accumulated spectral dataset. The stress drop parameter of one-corner Brune's ${\omega}^2$ source model fitted to the estimated source spectrum was well predicted by the scaling relation between magnitude and stress drop developed by Yun et al. (2006). In particular, the estimated spectrum was quite comparable to the two-corner source model that was empirically developed for recent moderate earthquakes occurring around the Korean Peninsula, which indicates that Odaesan earthquake is one of typical moderate earthquakes representative of Korean Peninsula. Other features of the observed spectra from Odaesan earthquake were also evaluated based on the commonly treated random error between the observed data and the estimated point-source spectral model. Radiation pattern of the error according to azimuth angle was found to be similar to the theoretical estimate. It was also observed that the spatial distribution of the errors was correlated with the geological map and the $Q_0$ map which are indicatives of seismic boundaries.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.95-101
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• 2008

Modeling of stock prices forecast has been considered as one of the most difficult problem to develop accurately since stock prices are highly correlated with various environmental conditions including economics and political situation. In this paper, we propose a agent system approach to predict Korea Composite Stock Price Index (KOSPI) using neural network and statistical methods. To minimize mean of prediction error and variation of prediction error, agent system includes sub-agent modules for feature extraction, variables selection, forecast engine selection, and forecasting results analysis. As a first step to develop agent system for KOSPI forecasting, twelve economic indices are selected from twenty two basic standard economic indices using principal component analysis. From selected twelve economic indices, prediction model input variables are chosen again using best-subsets regression method. Two different types data are tested for KOSPI forecasting and the Prediction results showed 11.92 points of root mean squared error for consecutive thirty days of prediction. Also, it is shown that proposed agent system approach for KOSPI forecast is effective since required types and numbers of prediction variables are time-varying, so adaptable selection of modeling inputs and prediction engine are essential for reliable and accurate forecast model.

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.35-51
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• 2008

Comparative studies in Phase III clinical trials quite often involve two or more equally important endpoints, and one cannot select primary endpoint from them. O'Brien(1984) proposed for continuous endpoints the OLS and GLS statistics as milti-variate test statistics. Pocock et al. (1987) mentioned the possibility of analyzing a mixture of data types, such as quantitative, binary and survival data types, with the OLS and GLS statistics, but the authors did not explore problems in combining several endpoints of different types. Furthermore, they did not perform a simulation study to assess the efficiencies of the OLS and GLS statistics for endpoints of a mixture of data types. In this paper, we propose the combining methods of correlated P-values for the analysis of multiple endpoints, and compare the efficiencies of this method with those of OLS and GLS statistics for a mixture of data types with a simulation study. Among the several methods of combining P-values that are more advantageous than combining of OLS and GLS statistics, method B maintains nominal significance levels and is more efficient, while method F and G have type I error rates that are larger than the specified significance levels, which might occasionally lead to a wrong conclusion.