• Journal of Korean Society of Water and Wastewater
• /
• v.35 no.1
• /
• pp.93-100
• /
• 2021

Forward osmosis (FO) process is a chemical potential driven process, where highly concentrated draw solution (DS) is used to take water through semi-permeable membrane from feed solution (FS) with lower concentration. Recently, commercial FO membrane modules have been developed so that full-scale FO process can be applied to seawater desalination or water reuse. In order to design a real-scale FO plant, the performance prediction of FO membrane modules installed in the plant is essential. Especially, the flux prediction is the most important task because the amount of diluted draw solution and concentrate solution flowing out of FO modules can be expected from the flux. Through a previous study, a theoretical based FO module model to predict flux was developed. However it needs an intensive numerical calculation work and a fitting process to reflect a complex module geometry. The idea of this work is to introduce deep learning to predict flux of FO membrane modules using 116 experimental data set, which include six input variables (flow rate, pressure, and ion concentration of DS and FS) and one output variable (flux). The procedure of optimizing a deep learning model to minimize prediction error and overfitting problem was developed and tested. The optimized deep learning model (error of 3.87%) was found to predict flux better than the theoretical based FO module model (error of 10.13%) in the data set which were not used in machine learning.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.7
• /
• pp.55-66
• /
• 2021

The purpose of this study is to analyze the relationship and effects of variables both directly and indirectly (e.g., investment (INV), government expenditure (GE), unemployment rate (UR), economic growth (EG), and income inequality). The analytical phases consist, first, to transform the data using the Log Natural (Ln) method. Second, to check normality and multicollinearity of data. Third, to test direct effects of variables (government expenditure and investment effect on the unemployment rate and economic growth; investment on government expenditure; economic growth on unemployment rate; economic growth and unemployment rate on income inequality). Fourth, to test indirect effects using Sobel test, which involves UR and EG as intervening variable. Fifth, to test hypotheses with p-value < 0.05. The results of the study reveal that, of the 12 relationships, statistics show that 11 variations of the association have significant positive and negative effects. Theoretically, the different characters and goals of GE and INV in each country will have a different impact on EG and UR goals. The study provides an input, especially for the government. To create optimal EG through GE and INV, it is necessary to allocate budgets to industrial sectors that can absorb a massive labor force and to new economic growth sectors.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.44 no.2
• /
• pp.78-84
• /
• 2021

In addition to physical risks such as electrical, chemical, and mechanic ones in the workplace, psychosocial risks are also raising as an important issue in recent years in connection with human rights and work-life balance policies. The purpose of this study is to confirm the degree of effect of the psychosocial risk management plan at the workplace on workers through logistic regression analysis. Input data for logistic regression analysis is the results of a survey of 4,558 people conducted by the Institute for Occupational Safety and Health were used. There are 9 independent variables, including the change a workplace and confidential counseling, and the dependent variable is whether the worker feels the effect on the psychosocial risk management plan. As a result of this study, changes in work organization, dispute resolution procedures, provision of education program, notification of the impact of psychosocial risks on safety and health, and the persons in charge of solving psychosocial problems are shown effective in reducing worker's psychosocial risks. This study drives which of the management plans implemented to reduce the psychosocial risk of workers in the workplace are effective, so it can contribute to the development of psychosocial risk management plans in the future.

• Journal of the Korea Convergence Society
• /
• v.12 no.8
• /
• pp.39-45
• /
• 2021

This paper discusses how to handle incomplete data including missing values. Optimally processing the missing value means obtaining an estimate that is the closest to the original value from the information contained in the training data, and replacing the missing value with this value. The way to achieve this is to use a decision tree that is completed in the process of classifying information by the classifier. In other words, this decision tree is obtained in the process of learning by inputting only complete information that does not include loss values among all training data into the C4.5 classifier. The nodes of this decision tree have classification variable information, and the higher node closer to the root contains more information, and the leaf node forms a classification region through a path from the root. In addition, the average of classified data events is recorded in each region. Events including the missing value are input to this decision tree, and the region closest to the event is searched through a traversal process according to the information of each node. The average value recorded in this area is regarded as an estimate of the missing value, and the compensation process is completed.

• Journal of the Korean Society of Industry Convergence
• /
• v.25 no.1
• /
• pp.121-129
• /
• 2022

With the recent increase in international trade volume the trade volume through ships is also continuously increasing. The treatment of ballast water goes through the following five steps, samples are taken and analyzed at each step, and samples are obtained using a suction pump. These suction pumps have low efficiency and thus need to be improved. In this study, it is to optimize the form of the impeller which affects directly improvements of performance to determine the capacity of suction pump and to fulfill the purpose of this research. To do it, we have carried out parametric design as an input variable, geometric form for the impeller. By conducting the flow analysis for the optimum form, it has confirmed the value of improved results and achieved the purpose to study in this paper. It has selected the necessary parameter for optimizing the form of the pump impeller and analyzed the property using experiment design. And it can reduce the factor of parameter for local optimization from findings to analyze the property of form parameter. To perform MOGA(Multi-Objective Genetic Algorithm) it has generated response surface using parameters for local optimization and conducts the optimization using multi-objective genetic algorithm. with created experiment cases, it has performed the computational fluid dynamics with model applying the optimized impeller form and checked that the capacity of the pump was improved. It could verify the validity concerning the improvement of pump efficiency, via optimization of pump impeller form which is suggested in this study.

• Journal of IKEEE
• /
• v.25 no.4
• /
• pp.762-765
• /
• 2021

In this paper, an automotive ECU (electronic control unit) with Kalman filter accelerator is designed and implemented. RISC-V is exploited as a processor core. Accelerator for Kalman filter matrix operation, CAN (controller area network) controller for in-vehicle network, and LIN (local interconnect network) controller are designed and embedded. Kalman filter operation consists of time update process and measurement update process. Current state variable and its error covariance are estimated in time update process. Final values are corrected from input measurement data and Kalman gain in measurement update process. Usually floating-point multiplication is exploited in software implementation, but fixed-point multiplier considering accuracy analysis is exploited in this paper to reduce hardware area. In 28nm silicon fabrication, its operating frequency, area, and gate counts are 100MHz, 0.37mm², and 760k gates, respectively.

• The Journal of the Korea Contents Association
• /
• v.22 no.7
• /
• pp.663-669
• /
• 2022

The content of fluoride in toothpaste commercially available in Korea has been increased to less than 1500 ppm. The purpose is to provide these results to consumers and to suggest alternatives to the safe use of toothpaste. This study was conducted on 1,300 people for 2 weeks from March 2021. As a research tool, general characteristics and oral health behaviors were surveyed. ConsExpo Web 1.0.2. It was used as an input variable for exposure evaluation. As a result of the study, when a toothpaste containing 1500 ppm of fluoride was used, the external dose on day of exposure was 2.3×10-2 mg/kg/day for males, 2.9×10-2 mg/kg/day for females, and children aged 2-3 years was estimated to be 7.3×10 -2 mg/kg/day. As a result of this study, it is thought that as the fluoride content of toothpaste distributed in the market increases, it will be used as a basic data to present standards for safe use by consumers.

• Physical Therapy Rehabilitation Science
• /
• v.11 no.3
• /
• pp.285-295
• /
• 2022

Objective: The purpose of this study is to use logistic regression and decision tree analysis to identify the factors that affect the success or failurein the national physical therapy examination; and to build and compare predictive models. Design: Secondary data analysis study Methods: We analyzed 76,727 subjects from the physical therapy national examination data provided by the Korea Health Personnel Licensing Examination Institute. The target variable was pass or fail, and the input variables were gender, age, graduation status, and examination area. Frequency analysis, chi-square test, binary logistic regression, and decision tree analysis were performed on the data. Results: In the logistic regression analysis, subjects in their 20s (Odds ratio, OR=1, reference), expected to graduate (OR=13.616, p<0.001) and from the examination area of Jeju-do (OR=3.135, p<0.001), had a high probability of passing. In the decision tree, the predictive factors for passing result had the greatest influence in the order of graduation status (x²=12366.843, p<0.001) and examination area (x²=312.446, p<0.001). Logistic regression analysis showed a specificity of 39.6% and sensitivity of 95.5%; while decision tree analysis showed a specificity of 45.8% and sensitivity of 94.7%. In classification accuracy, logistic regression and decision tree analysis showed 87.6% and 88.0% prediction, respectively. Conclusions: Both logistic regression and decision tree analysis were adequate to explain the predictive model. Additionally, whether actual test takers passed the national physical therapy examination could be determined, by applying the constructed prediction model and prediction rate.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.20 no.7
• /
• pp.105-112
• /
• 2021

Reduction of weld distortions and increase in productivity are some of the major goals of the shipbuilding industry. To address these issues, many researchers have attempted to apply new welding processes. In the shipbuilding industry, steel is the candidate material of choice owing to its good weldability. However, conventional welding techniques are not feasible for avoiding welding problems. Tip-rotating arc welding is one of the high-efficiency welding process that has several advantages, such as high welding speed, high melting rate, low heat input, and less distortion. The present study investigates the influence of the welding variables on the weld characteristics of tip-rotating arc welding. Welding was performed using EH36 as the base metal and SM-70s as the filler metal, which are widely used in shipbuilding. Basic experiments were conducted to understand the effects of the major welding variables, such as welding and tip-rotating speeds. The distortion and mechanical properties of the optimal welding conditions were used to evaluate the tip-rotating arc welding performance. Consequently, the feasibility of the tip-rotating arc welding process for joining steel components was investigated, so that the optimized welding conditions could be applied directly to ship body welding to enhance the quality of the welded joints.

• Journal of The Korean Society of Integrative Medicine
• /
• v.10 no.3
• /
• pp.107-117
• /
• 2022

Purpose : The purpose of this study was to establish a model of the predictive factors for success or failure of examinees undertaking the Korean physical therapist licensing examination (KPTLE). Additionally, we assessed the pass/fail cut-off point. Methods : We analyzed the results of 10,881 examinees who undertook the KPTLE, using data provided by the Korea Health Personnel Licensing Examination Institute. The target variable was the test result (pass or fail), and the input variables were: sex, age, test subject, and total score. Frequency analysis, chi-square test, descriptive statistics, independent t-test, correlation analysis, binary logistic regression, and receiver operating characteristic (ROC) curve analyses were performed on the data. Results : Sex and age were not significant predictors of attaining a pass (p>.05). The test subjects with the highest probability of passing were, in order, medical regulation (MR) (Odds ratio (OR)=2.91, p<.001), foundations of physical therapy (FPT) (OR=2.86, p<.001), diagnosis and evaluation for physical therapy (DEPT) (OR=2.74, p<.001), physical therapy intervention (PTI) (OR=2.66, p<.001), and practical examination (PE) (OR=1.24, p<.001). The cut-off points for each subject were: FPT, 32.50; DEPT, 29.50; PTI, 44.50; MR, 14.50; and PE, 50.50. The total score (TS) was 164.50. The sensitivity, specificity, and the classification accuracy of the prediction model was 99 %, 98 %, and 99 %, respectively, indicating high accuracy. Area under the curve (AUC) values for each subject were: FPT, .958; DEPT, .968; PTI, .984; MR, .885; PE, .962; and TS, .998, indicating a high degree of fit. Conclusion : In our study, the predictive factors for passing KPTLE were identified, and the optimal cut-off point was calculated for each subject. Logistic regression was adequate to explain the predictive model. These results will provide universities and examinees with useful information for predicting their success or failure in the KPTLE.