• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.14 no.4
• /
• pp.887-896
• /
• 1994

It is common practice in the case of optimum reservoir operation model that the reservoir inflow series are generated by stochastic model with keeping other variable such as water demands from the reservoir constant. However, when the input and output of the water distribution system have close relationship the output variables can be stochastically generated in relation with the input variables. In the present study the reservoir inflow series, the input of the system, is generated by periodic autoregressive model with constant parameter, and the agricultural water demand series, the output, is generated using periodic multivariate autoregressive model with constant parameter. The time period of the data series generated is taken as 10-day which is the common period used for agricultural water uses. The results of data generation by two different models showed that the periodic stochastic models well represent the characteristics of the historical time series, and that in the case of generating model for agricultural demand series it has closer relation with reservoir inflow than with the series itself.

• Asian Pacific Journal of Cancer Prevention
• /
• v.17 no.12
• /
• pp.5133-5138
• /
• 2016

Background: Breast cancer is one of the most common cancers and a major public health problem in developing countries. However, early detection and treatment may be achieved by breast self-examination (BSE). Despite the importance of BSE in reducing the incidence of breast cancer and esultant deaths, the disease continues to be the most common cause of cancer death among women in Iran.This study aimed to determine the effects of self-care education on performance of BSE among women referring to health centers in our country. Materials and Methods: This quasi-experimental interventional study with pretest/posttest control group design was conducted on 168 women referred to health centers. The data were collected using a validated researcher-made questionnaire including demographic variables and trans-theoretical model constructs as well as a checklist assessing BSE behavior. The instruments were administered to groups with and without self-care education before, a week after, and 10 weeks after the intervention. Then, the data were entered into the SPSS statistical software (version 19) and analyzed using independent sample t-tests, paired sample t-test, repeated measures ANOVA, Chi-square, and Friedman tests (p<0.05). Results: The results showed an increase in the intervention group's mean scores of trans-theoretical model constructs (stages of change, self-efficacy, decisional balance, and processes of change) and BSE behavior compared to the control group (p<0.001). Conclusion: The study confirmed the effectiveness of aneducational intervention based ona trans-theoretical model in performing BSE. Therefore, designing educational interventions based on this model is recommended to improve women's health and reduce deaths due to breast cancer.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.17 no.11
• /
• pp.965-973
• /
• 2005

This paper proposes a mathematical model for predicting the frosting performance on a fin-tube heat exchanger. The model consists of empirical correlations of average heat transfer coefficients for the plate and tube surfaces and a diffusion equation inside the frost layer. The numerical results are compared with experimental data for the frost thickness, the frosting rate and the heat transfer rate to validate the proposed model. The results are in good agreement with the experimental data, and show that this model can be applied to predict frosting performance of common fin-tube heat exchanger.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2002.05a
• /
• pp.551-554
• /
• 2002

The paper discusses new approach for machining operation simulation using enhanced Z map algorithm. To extract the required geometric information from NC code, suggested algorithm uses supersampling method to enhance the efficiency of a simulation process. By executing redundant Boolean operations in a grid cell and averaging down calculated data, presented algorithm can accurately represent material removal volume though tool swept volume is negligibly small. Supersampling method is the most common form of antialiasing and usually used with polygon mesh rendering in computer graphics. The key advantage of enhanced Z map model is that the data structure is same with conventional Z map model, though it can acquire higher accuracy and reliability with same or lower computation time. By simulating machining operation efficiently, this system can be used to improve the reliability and efficiency of NC machining process as well as the quality of the final product.

• Journal of ILASS-Korea
• /
• v.17 no.2
• /
• pp.77-85
• /
• 2012

The CFD simulation of diesel spray tip penetrations were compared with 0-D simulation for experimental data obtained with common rail injection system. The simulated four injection patterns include single, pilot and split injections. The CFD simulation of the spray penetration over these injection patterns was performed using the KIVA-3V code, which was implemented with both the standard KIVA spray and original gas jet sub-models. 0-D simulation of the spray tip penetration with time-varying injection profiles was formulated based on the effective injection velocity concept as an extension of steady gas jet theory. Both the CFD simulation of the spray tip penetration with the standard KIVA spray model and 0-D simulation matched better with the experimental data than the results of the gas jet model for the entire fuel injection patterns.

• Proceedings of the Korea Society of Information Technology Applications Conference
• /
• 2002.11a
• /
• pp.363-370
• /
• 2002

A substrate network model characterizing substrate effect of submicron MOS transistors for RF operation and its parameter extraction with physically meaningful values are presented. The proposed substrate network model includes a single resistance and inductance originated from ring-type substrate contacts around active devices. Model parameters are extracted from S-parameter data measured from common-bulk configured MOS transistors with floating gate and use where needed with out any optimization. The proposed modeling technique has been applied to various-sized MOS transistors. Excellent agreement the measurement data and the simulation results using extracted substrate network model up to 30GHz.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 2002.11a
• /
• pp.363-370
• /
• 2002

A substrate network model characterizing substrate effect of submicron MOS transistors for RF operation and its parameter extraction with physically meaningful values are presented. The proposed substrate network model includes a single resistance and inductance originated from ring-type substrate contacts around active devices. Model parameters are extracted from S-parameter data measured from common-bulk configured MOS transistors with floating gate and use where needed with out any optimization. The proposed modeling technique has been applied to various-sized MOS transistors. Excellent agreement the measurement data and the simulation results using extracted substrate network model up to 30㎓

• Journal of Yeungnam Medical Science
• /
• v.41 no.2
• /
• pp.86-95
• /
• 2024

Background: This study aimed to investigate the impact of coronavirus disease 2019 (COVID-19) on the development of major mental disorders in patients visiting a university hospital. Methods: The study participants were patients with COVID-19 (n=5,006) and those without COVID-19 (n=367,162) registered in the database of Keimyung University Dongsan Hospital and standardized with the Observational Medical Outcomes Partnership Common Data Model. Data on major mental disorders that developed in both groups over the 5-year follow-up period were extracted using the FeederNet computer program. A multivariate Cox proportional hazards model was used to estimate the hazard ratio (HR) and 95% confidence interval (CI) for the incidence of major mental disorders. Results: The incidences of dementia and sleep, anxiety, and depressive disorders were significantly higher in the COVID-19 group than in the control group. The incidence rates per 1,000 patient years in the COVID-19 group vs. the control group were 12.71 vs. 3.76 for dementia, 17.42 vs. 7.91 for sleep disorders, 6.15 vs. 3.41 for anxiety disorders, and 8.30 vs. 5.78 for depressive disorders. There was no significant difference in the incidence of schizophrenia or bipolar disorder between the two groups. COVID-19 infection increased the risk of mental disorders in the following order: dementia (HR, 3.49; 95% CI, 2.45-4.98), sleep disorders (HR, 2.27; 95% CI, 1.76-2.91), anxiety disorders (HR, 1.90; 95% CI, 1.25-2.84), and depressive disorders (HR, 1.54; 95% CI, 1.09-2.15). Conclusion: This study showed that the major mental disorders associated with COVID-19 were dementia and sleep, anxiety, and depressive disorders.

• Clean Technology
• /
• v.29 no.2
• /
• pp.151-159
• /
• 2023

The realization of carbon neutrality requires cooperation from various stakeholders and the utilization of a governance system. The criteria for participating members are crucial for the successful operation of governance, and it is especially necessary for experts who can provide scientific advice for policy implementation to share a framework for successful consensus. In this study, governance model theory and model structure, governance common success factors by case, and the application of governance cases in the climate and environmental sector of Seoul, were investigated and analyzed to derive common success factors in order to present the activity standards of the science and technology experts participating in governance. The study of the model theory suggested that the model structure is commonly composed of a basic condition-process-result structure, and it was confirmed that common success factors can be derived at the process stage which is the activity period of members. Through the case study of common success factors, overlapping factors were found to be reliability, accountability, transparency, networks, and related factors. The validity of the common success factors was verified using the analysis results of satisfaction survey data from Seoul Governance Committee participants. The results confirmed that reliability was the most valuable factor followed by networks, transparency, and responsibility, and it was found that the related factors were appropriately derived. The findings of this study are expected to be used as an activity factor for science and technology experts to increase the acceptability and effectiveness of carbon-neutral policies in the future.

• Journal of Korean Society for Quality Management
• /
• v.34 no.2
• /
• pp.129-135
• /
• 2006

In the advance of computer technology, it is possible to keep all the related informations for monitoring equipments in control and huge amount of real time manufacturing data in a data base. Thus, the statistical analysis of large data sets with hundreds of thousands observations and hundred of independent variables whose some of values are missing at many observations is needed even though it is a formidable computational task. A tree structured approach to classification is capable of screening important independent variables and their interactions. In a Six Sigma project handling large amount of manufacturing data, one of the goals is to screen vital few variables among trivial many variables. In this paper we have reviewed and summarized CART, C4.5 and CHAID algorithms and proposed a simple method of screening vital few variables by selecting common variables screened by all the three algorithms. Also how to develop a logistics regression model on a large data set is discussed and illustrated through a large finance data set collected by a credit bureau for th purpose of predicting the bankruptcy of the company.