• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.155-166
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• 2002

Since 1990s. there has been an increasing number of traffic accidents at intersection. which requires more urgent measures to insure safety on intersection. This study set out to analyze the road conditions, traffic conditions and traffic operation conditions on signalized intersection. to identify the elements that would impose obstructions in safety, and to develop a traffic accident prediction model to evaluate the safety of an intersection using the cop relation between the elements and an accident. In addition, the focus was made on suggesting appropriate traffic safety policies by dealing with the danger elements in advance and on enhancing the safety on the intersection in developing a traffic accident prediction model fir a signalized intersection. The data for the study was collected at an intersection located in Wonju city from January to December 2001. It consisted of the number of accidents, the road conditions, the traffic conditions, and the traffic operation conditions at the intersection. The collected data was first statistically analyzed and then the results identified the elements that had close correlations with accidents. They included the area pattern, the use of land, the bus stopping activities, the parking and stopping activities on the road, the total volume, the turning volume, the number of lanes, the width of the road, the intersection area, the cycle, the sight distance, and the turning radius. These elements were used in the second correlation analysis. The significant level was 95% or higher in all of them. There were few correlations between independent variables. The variables that affected the accident rate were the number of lanes, the turning radius, the sight distance and the cycle, which were used to develop a traffic accident prediction model formula considering their distribution. The model formula was compared with a general linear regression model in accuracy. In addition, the statistics of domestic accidents were investigated to analyze the distribution of the accidents and to classify intersections according to the risk level. Finally, the results were applied to the Spearman-rank correlation coefficient to see if the model was appropriate. As a result, the coefficient of determination was highly significant with the value of 0.985 and the ranks among the intersections according to the risk level were appropriate too. The actual number of accidents and the predicted ones were compared in terms of the risk level and they were about the same in the risk level for 80% of the intersections.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.67-83
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• 2018

The Korean film industry with significant increase every year exceeded the number of cumulative audiences of 200 million people in 2013 finally. However, starting from 2015 the Korean film industry entered a period of low growth and experienced a negative growth after all in 2016. To overcome such difficulty, stakeholders like production company, distribution company, multiplex have attempted to maximize the market returns using strategies of predicting change of market and of responding to such market change immediately. Since a film is classified as one of experiential products, it is not easy to predict a box office record and the initial number of audiences before the film is released. And also, the number of audiences fluctuates with a variety of factors after the film is released. So, the production company and distribution company try to be guaranteed the number of screens at the opining time of a newly released by multiplex chains. However, the multiplex chains tend to open the screening schedule during only a week and then determine the number of screening of the forthcoming week based on the box office record and the evaluation of audiences. Many previous researches have conducted to deal with the prediction of box office records of films. In the early stage, the researches attempted to identify factors affecting the box office record. And nowadays, many studies have tried to apply various analytic techniques to the factors identified previously in order to improve the accuracy of prediction and to explain the effect of each factor instead of identifying new factors affecting the box office record. However, most of previous researches have limitations in that they used the total number of audiences from the opening to the end as a target variable, and this makes it difficult to predict and respond to the demand of market which changes dynamically. Therefore, the purpose of this study is to predict the weekly number of audiences of a newly released film so that the stakeholder can flexibly and elastically respond to the change of the number of audiences in the film. To that end, we considered the factors used in the previous studies affecting box office and developed new factors not used in previous studies such as the order of opening of movies, dynamics of sales. Along with the comprehensive factors, we used the machine learning method such as Random Forest, Multi Layer Perception, Support Vector Machine, and Naive Bays, to predict the number of cumulative visitors from the first week after a film release to the third week. At the point of the first and the second week, we predicted the cumulative number of visitors of the forthcoming week for a released film. And at the point of the third week, we predict the total number of visitors of the film. In addition, we predicted the total number of cumulative visitors also at the point of the both first week and second week using the same factors. As a result, we found the accuracy of predicting the number of visitors at the forthcoming week was higher than that of predicting the total number of them in all of three weeks, and also the accuracy of the Random Forest was the highest among the machine learning methods we used. This study has implications in that this study 1) considered various factors comprehensively which affect the box office record and merely addressed by other previous researches such as the weekly rating of audiences after release, the weekly rank of the film after release, and the weekly sales share after release, and 2) tried to predict and respond to the demand of market which changes dynamically by suggesting models which predicts the weekly number of audiences of newly released films so that the stakeholders can flexibly and elastically respond to the change of the number of audiences in the film.

• Journal of Energy Engineering
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• v.23 no.1
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• pp.58-66
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• 2014

Catalytic gasification of a low rank coal- Inner Mongolian lignite has been carried out with carbon dioxide. The gasification reactions were performed in a thermogravimetric analyzer at temperatures of $600^{\circ}C$ to $900^{\circ}C$. The kinetic parameters were evaluated using three different gas-solids reaction models and the prediction ability of each model were compared. Among the models evaluated, the modified volumetric model was found to correlate best both the non-catalytic and catalytic gasification reactions. The theoretical models, homogeneous and shrinking-core models, were found to satisfactorily correlate gasification reactions for the non-catalytic and $FeSO_4$-catalyzed reactions. In case of alkali metal catalysts, the catalytic activity was mostly pronounced at a low temperature of $600^{\circ}C$ and observed to decrease by 50% as the temperature was increased to $700^{\circ}C$, and it remained nearly constant at temperature over $800^{\circ}C$. The order of catalytic activity was found to be: $K_2CO_3$ > $Na_2CO_3$ > $K_2SO_4$ > $FeSO_4$.

• Journal of Korea Water Resources Association
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• v.43 no.1
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• pp.81-94
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• 2010

Input variable selection is one of the various techniques for improving the performance of artificial neural network. In this study, mutual information is applied for input variable selection technique instead of correlation coefficient that is widely used. Among 152 variables of RDAPS (Regional Data Assimilation and Prediction System) output results, input variables for artificial neural network are chosen by computing mutual information between rainfall records and RDAPS' variables. At first the rainfall forecast variable of RDAPS result, namely APCP, is included as input variable and the other input variables are selected according to the rank of mutual information and correlation coefficient. The input variables using mutual information are usually those variables about wind velocity such as D300, U925, etc. Several statistical error estimates show that the result from mutual information is generally more accurate than those from the previous research and correlation coefficient. In addition, the artificial neural network using input variables computed by mutual information can effectively reduce the relative errors corresponding to the high rainfall events.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1161-1161
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• 2001

Rapid cost-effective methods of measuring wood quality are extremely important to tree improvement programs where it is necessary to test large numbers of trees. Non-destructive sampling of a forest can be achieved by using increment cores generally removed at breast height. At CSIRO Forestry and Forest Products methods for the rapid, non-destructive measurement of wood properties and wood chemistry based on increment core samples have been developed. In this paper the application of near infrared (NIR) spectroscopy to the prediction of a range solid wood properties, including density, longitudinal modulus of elasticity (E$\sub$L/) and microfibril angle (MFA), is described. Experiments conducted on individual species (Eucalyptus delegatensis and Pinus radiata), the two species combined and a number of mixed species from several genera are reported. NIR spectra were obtained from the radial/longitudinal face of each sample and used to develop calibrations for the measured physical properties. When the individual species were used the relationships between laboratory determined data and NIR fitted data were good in all cases. Coefficients of determination (R$^2$) ranging from 0.77 for MFA to 0.93 for stick density were obtained for E. delegatensis and R$^2$ ranging from 0.68 for MFA to 0.94 for strip density were obtained for P. radiata. The calibration statistics for the combined E. delegatensis and P. radiata samples were similar to those found for the individual species. As these results indicated that it might be possible to produce general calibrations based on samples from a number of species of a single genus or samples from a number of different genera, a wide range of species was subsequently tested. Good relationships were obtained for both density and E$\sub$L/. These calibrations had R$^2$ that were slightly lower than those determined using individual species and standard errors that were higher. The mixed species calibrations, when applied to the E. delegatensis and P. radiata sample sets, provided good estimates of density (stick and strip) and E$\sub$L/. The results demonstrated that a mixed species calibration, that encompasses wide variation in terms of, wood anatomy, chemistry and physical properties, could be used to rank trees. Experiments reported in this paper demonstrate that solid wood properties can be estimated by NIR spectroscopy. The method offers a rapid and non-destructive alternative to traditional methods of analysis and is applicable to large-scale non-destructive forest resource assessment, and to tree breeding and silvicultural programs.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.7
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• pp.4157-4160
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• 2013

Objectives: Understanding the situation of cancer awareness which doctors give to patients might lead to prognostic prediction in cases of of colorectal cancer (CRC). Methods: Subsets of 10,779 CRC patients were used to screen the risk factors from the Cancer Registry in Pudong New Area in cancer awareness, age, TNM stage, and gender. Survival of the patients was calculated by the Kaplan-Meier method and assessed by Cox regression analysis. The views of cancer awareness in doctors and patients were surveyed by telephone or household. Results: After a median observation time of 1,616 days (ranging from 0 to 4,083 days) of 10,779 available patients, 2,596 of the 4,561 patients with cancer awareness survived, whereas 2,258 of the 5,469 patients without cancer awareness and 406 of the 749 patients without information on cancer awareness died of the disease. All-cause and cancer-specific survival were poorer for the patients without cancer awareness than those with (P < 0.001 for each, log-rank test). Cox multivariate regression analysis showed that cancer concealment cases had significantly lower cancer-specific survival (hazard ratio (HR) = 1.299; 95 % confidence interval (CI): 1.200-1.407)and all-cause survival (HR = 1.324; 95 % CI: 1.227-1.428). Furthermore, attitudes of cancer awareness between doctors and patients were significantly different (P < 0.001). Conclusion: Cancer concealment, not only late-stage tumor and age, is associated with a poor survival of CRC patients.

• Journal of Digital Contents Society
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• v.15 no.1
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• pp.19-27
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• 2014

In order to estimate the life of 2,5 inch HDD which is adopted by PC environment, make the test plan which reflect the failure mode of market, make the test model of accelerated life test which reflect the stress of temperature. after an analysis of the environment of PC using, test procedure was decided that operation was write 50 % and read 50 %, and then access method was sequential 50 % and random 50%. The acceleration life test was executed on condition that temperature was $50^{\circ}C$ and $60^{\circ}C$, performance was 95 % in max performance, test time was 1000 hours. by the test of goodness of fit of anderson-darling of the failure data during test, it was confirmed that the distribution of failure fellow weibull. test for shape and scale was equal, and shape parameter was 0.7177, characteristic life was 429434 hours at normal user condition($30^{\circ}C$) by the analysis of weibull-arrhenius modeling. It made no difference about the statistics when equality test was executed. The activation energy was 0.2775eV. In analyzing between the failure samples of acceleration test and the samples of market return even though there is detail difference about the share of failure mode, the rank of share was almost same. This study suggest the test procedure of acceleration test of 2.5 inch HDD in PC using environment, and help the life estimation at manufacture and user.

• Korean Journal of Radiology
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• v.21 no.6
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• pp.707-716
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• 2020

Objective: To evaluate pharmacokinetic variables from contrast-enhancing lesions (CELs) and non-enhancing T2 high signal intensity lesions (NE-T2HSILs) on dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging for predicting progression-free survival (PFS) in glioblastoma (GBM) patients. Materials and Methods: Sixty-four GBM patients who had undergone preoperative DCE MR imaging and received standard treatment were retrospectively included. We analyzed the pharmacokinetic variables of the volume transfer constant (Ktrans) and volume fraction of extravascular extracellular space within the CEL and NE-T2HSIL of the entire tumor. Univariate and multivariate Cox regression analyses were performed using preoperative clinical characteristics, pharmacokinetic variables of DCE MR imaging, and postoperative molecular biomarkers to predict PFS. Results: The increased mean Ktrans of the CEL, increased 95th percentile Ktrans of the CELs, and absence of methylated O⁶-methylguanine-DNA methyltransferase promoter were relevant adverse variables for PFS in the univariate analysis (p = 0.041, p = 0.032, and p = 0.083, respectively). The Kaplan-Meier survival curves demonstrated that PFS was significantly shorter in patients with a mean Ktrans of the CEL > 0.068 and 95th percentile Ktrans of the CEL > 0.223 (log-rank p = 0.038 and p = 0.041, respectively). However, only mean Ktrans of the CEL was significantly associated with PFS (p = 0.024; hazard ratio, 553.08; 95% confidence interval, 2.27-134756.74) in the multivariate Cox proportional hazard analysis. None of the pharmacokinetic variables from NE-T2HSILs were significantly related to PFS. Conclusion: Among the pharmacokinetic variables extracted from CELs and NE-T2HSILs on preoperative DCE MR imaging, the mean Ktrans of CELs exhibits potential as a useful imaging predictor of PFS in GBM patients.

• The Journal of Bigdata
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• v.8 no.2
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• pp.125-131
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• 2023

Globally, drug side effects rank among the top causes of death. To effectively respond to these adverse drug reactions, a shift towards an active real-time monitoring system, along with the standardization and quality improvement of data, is necessary. Integrating individual institutional data and utilizing large-scale data to enhance the accuracy of drug side effect predictions is critical. However, data sharing between institutions poses privacy concerns and involves varying data standards. To address this issue, our research adopts a federated learning approach, where data is not shared directly in compliance with privacy regulations, but rather the results of the model's learning are shared. We employ the Common Data Model (CDM) to standardize different data formats, ensuring accuracy and consistency of data. Additionally, we propose a drug monitoring system that enhances security and scalability management through a cloud-based federated learning environment. This system allows for effective monitoring and prediction of drug side effects while protecting the privacy of data shared between hospitals. The goal is to reduce mortality due to drug side effects and cut medical costs, exploring various technical approaches and methodologies to achieve this.

• Journal of Korean Society of Disaster and Security
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• v.6 no.1
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• pp.65-72
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• 2013

In this study, the early suicide prevention program was applied to the elementary school students and compared the prior & post effect of the program, and verified the status of psychology change like emotional status, or temptation to take a suicide, and presented the possibility as a suicide prevention program. The period of adolescence is the very unstable period in the process of growth being cognitively immature, emotionally impulsive period. It is the period emotionally unstable and unpredictable possible to select the method of suicide as an extreme method to escape the reality, or impulsive problem solving against small conflict or dispute situation. Many stress of the student such as recent nuclear family, expectation of parents to their children, education problem, socio-environmental elements, individual psychological factor lead students to the extreme activity of suicide in recent days. In this study, the scope of stress experienced in the elementary school as well as idea and degree of temptation regarding suicide by the suicide prevention program were identified, and through prevention program such as meditation training, breath training and through experience of anger control, emotion-expression, self overcome and establish positive self-identity and make understanding Self-control, Self-esteem & preciousness of life based on which the effect to suicide prevention was analyzed. The study was made targeting 51 students of 2 classes of 6th grade of elementary school of Goyang-si and processed 30 minutes every morning focused on through experience & activity of the principle & method of brain science. The data was collected for 20 times before starting morning class by using Suicide Probability Scale(herein SPS-A) designed to predict effectively suicide Probability, suicide risk prediction scale, surveyed by 7 areas such as Positive outlook, Within the family closeness, Impulsivity, Interpersonal hostility, Hopelessness, Hopelessness syndrome, suicide accident. Analytical methods and validation was used the Wilcoxon's signed rank test using SPSS Program. Though the process of program in short period, but there was a effective and positive results in the 7 areas in the average comparison. But in the t-test result, there was a different outcome. It indicated changes in the 3 questionnaires (No.7, No.14, No.19) out of 31 SPS-A questionnaires, and there was a no change to the rest item. It also indicated more changes of the students in the class A than class B. And in case of the class A students, psychological changes were verified in the areas of Hopelessness syndrome, suicide accident among 7 areas after the program was processed. Through this study, it could be verified that different results could be derived depending on the Student tendency, program professional(teacher in charge, processing lecturer). The suicide prevention program presented in this article can be a help in learning and suicide prevention with consistent systematization, activation through emotion and impulse control based on emotional stress relief and positive self-identity recovery, stabilization of brain waves, and let the short period program not to be died out but to be continued connecting from childhood to adolescence capable to make surrounding environment for spiritual, physical healthy growth for which this could be an effective program for suicide prevention of the social problem.