• The Journal of Fisheries Business Administration
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• v.52 no.4
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• pp.13-28
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• 2021

The purpose of this study is to compare short-term price predictive power among ARMA ARMAX and VAR forecasting models based on the MDM test using monthly consumer price data of frozen mackerel. This study also aims to help policymakers and economic actors make reasonable choices in the market on monthly consumer price of frozen mackerel. To analyze this study, the frozen wholesale prices and new consumer prices were used as variables while the price time series data were used from December 2013 to July 2021. Through the unit root test, it was confirmed that the time series variables employed in the models were stable while the level variables were used for analysis. As a result of conducting information standards and Granger causality tests, it was found that the wholesale prices and fresh consumer prices from the previous month have affected the frozen consumer prices. Then, the model with the highest predictive power was selected by RMSE, RMSPE, MAE, MAPE, and Theil's inequality coefficient criteria where the predictive power was compared by the MDM test in order to examine which model is superior. As a result of the analysis, ARMAX(1,1) with the frozen wholesale, ARMAX(1,1) with the fresh consumer model and VAR model were selected. Through the five criteria and MDM tests, the VAR model was selected as the superior model in predicting the monthly consumer price of frozen mackerel.

• Childhood Kidney Diseases
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• v.9 no.2
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• pp.167-174
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• 2005

Purpose : Relapses are a major problem in children with steroid responsive nephrotic syndrome(SRNS). This study has been performed to determine the predictive factors for relapse in children with SRNS. Methods : The study group consisted of 7,3 children with SRNS who had been admitted to the Department of Pediatrics, Kyungpook National University Hospital, over 6 years from 1996 to 2001. The medical records were reviewed retrospectively and analyzed to determine significant relationships between selected variables[age at onset, sex, laboratory data, the rapidity of response(days to remission), interval to first relapse] and the frequency of relapse. Results : The age($mean{\pm}SD$) of patients was $4.53{\pm}2.53$ years old. The male to female ratio was 52:21. In 95$\%$, 39 out of the 41 children had a renal biopsy, and the final diagnosis was minimal change nephrotic syndrome. There was no significant correlation between the frequency of relapse and the following variables age at onset, sex, and presence of hematuria. However, the rapidity of response correlated well with the frequency of relapse, especially during the first year after the onset of the disease(P=0.005). Conclusion : The rapidity of response is expected to be one of the predictive (actors for relapse in children with SRNS. (J Korean Soc Pediatr Nephrol 2005;9:167-174)

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.3
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• pp.1187-1191
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• 2016

Background: The prevalence of prostate cancer (PCa) has been increasing in recent years. Treatment strategies are largely based on the results of bone scan screening. Therefore, our aim was to investigate predictors of positive bone metastasis in newly diagnosed PCa patients. Materials and Methods: After extensive review, 336 consecutive patients newly diagnosed with PCa between April 2010 and November 2013 at our institution were enlisted in the study. Patients were divided into two groups according to bone scan results. Univariate analyses (Chi-square test for discrete variables and independent t-test for continuous variables) were applied to determine the potentially significant risk factors associated with distant bone metastasis. Binary logistic regression analyses were used to further investigate the influence of these factors on bone metastasis. Results: The patient mean age was $71.9{\pm}8.6years$ (range: 48 to 94 years). The mean prostate specific antigen (PSA) level and biopsy Gleason score were $260.2{\pm}1107.8ng/mL$ and $7.4{\pm}1.5$, respectively. The body mass index (BMI) for the series was $24.5{\pm}3.4kg/m^2$. Sixty-four patients (19.0%) had a positive bone scan result. Patients with positive bone scan results had a significantly lower BMI ($23.3{\pm}3.5$ vs. $24.8{\pm}3.3$; p=0.003), a higher Gleason score ($8.5{\pm}1.1$ vs. $7.1{\pm}1.5$; p < 0.001), and a higher PSA level ($1071.3{\pm}2337.1$ vs. $69.4{\pm}235.5$; p < 0.001) than those without bone metastasis. Multivariate logistic regression analysis employing the above independent predictors demonstrated that a Gleason score of ${\geq}7$, clinical stage ${\geq}T3$, $BMI{\leq}22kg/m^2$, and an initial PSA level of ${\geq}20ng/mL$ were all independent predictors of bone metastasis. Conclusions: A bone scan might be necessary in newly diagnosed PCa patients with any of the following criteria: clinical stage T3 or higher, a Gleason score of 7 or higher, BMI equal to or less than 22, and a PSA level of 20 or higher.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.33-49
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• 2018

The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.