• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.42-49
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• 2018

Pilot Aptitude Research Equipment (PARE) is a simulator developed to measure or research pilot aptitude and train for student pilots. Design of an ergonomic PARE operation console is required to operate the equipment effectively. This study carried out five steps : (S1) operator questionnaire survey, (S2) anthropometric design formula development, (S3) usability evaluation, (S4) improvement design, and (S5) validation considering both Physical User Interface (PUI) and Graphic User Interface (GUI) of PARE operation console. The operator questionnaire surveyed needs for each PUI and GUI part of the console from two PARE actual operators. In terms of PUI, the anthropometric design formula was developed by using design variables, body dimensions, target population characteristics, and reference posture related to the PARE console. In terms of GUI, the usability evaluation was conducted by three usability testing experts with a 7-point scale (1 : very low, 4 : neutral, 7 : very high) on GUI of the PARE operation console by seven usability criteria. The improved PARE operation console was designed to reflect the optimal values of design variables calculated from design formula, the results from usability testing, and the operator's needs. The improvement effect was observed by 20 people who had experience with the PARE operation console. As a result of the validation, monitor visibility and cockpit visibility for the improved PUI design and visibility and efficiency for the improved GUI design were significantly increased by more than 90% respectively. The improved design of the PARE operation console in this study can contribute to enhance operation performance of the PARE.

• Fisheries and Aquatic Sciences
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• v.3 no.2
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• pp.156-162
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• 2000

Model experiments for a purse seine were carried out in order to measure the geometry of net shape and to estimate an enclosed volume by using 1177 scale model purse seine of 12.62m float line from an offshore mackerel purse seine. A model purse seine was set from a net box of shooting equipments and then pursing and hauling net by hauling equipment. The 3- D geometry shape of the purse seine net during hauling operation was measured by video image processing and tension of purse line by load cell. The 3-D geometry of the model purse seine during hauling operation could be represented with variables such as a ratio of shooting diameter or maximum net depth and a ratio of hauling operation time. Horizontal shapes of float line and lead line were varied from a circle after shooting to an ellipse with pursing and hauling. Projected lateral shape of purse line was observed and formulated as a shape of a water drop. The cross sectional shapes of curved net from two directions were varied such as sine function or polynomial curves. Therefore, enclosed volume of a purse seine in relation to fish school behaviour can be approximated using two main variables from relevant equations.

• Journal of the Korean Society for Railway
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• v.10 no.6
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• pp.766-771
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• 2007

In this research, we were going to make the function which can forecast the operating cost of metropolitan railroad that is performing a role of assistant highway within the city. In order to do this, based on service records of subway line 1st to 8th in Seoul, we extracted 23 variables which can affect to the operating cost, and we selected the final variable for estimate the function of operating cost from correlation among variables and influence analysis. Then, we performed regression analysis by stages using final variable. 6 independent variables are chosen for presuming the operating cost, and we obtained the final 3 variables (quantity of holding motor cars, peak quantity of possessed motor cars, and quantity of stations) as a result of regression analysis. Through this research, function of operating cost of metropolitan railroad has better applicability than existing preliminary validity, and it is used by further preliminary validity investigation and master plan or validity investigation which is accompanied by operation designing, thus we expect that it could make a great contribution to the priority order of investment for metropolitan railroad or process of policy decision.

• Korean journal of food and cookery science
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• v.14 no.4
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• pp.407-415
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• 1998

The objectives of this study were to analyze the factors that affect the productivity for university food services. In a survey involving four-year university dining centers throughout the country, and correlations among thriteen different variables that affect productivity were determined. Productivity index (PI) was determined by meals per hour, the average score for 38 institutions was found to be 14.2 meals/hour. For serving methods, the fixed ration had a higher PI than the self-serving. When two types of serving trays were considered, the PI of the compartmantalized trays was higher than that of the tray accompanying saparate small dishes. When single (S)-or. multiple(M)-menu was compared with the cafeteria style, a higher PI was obtained by the S-or M-menu. Among the three operation systems, the PI was found to be the highest by direct operation (17.6 meals/hour), followed by contract operation (11.1 meals/hour) and rent operation (7.9 meals/hour). For the factors that affect the productivity of the university food services, the total number sewed (r=0.54, p＜0.001) and the use of convenient food items (r=0.28, P＜0.05) exhibited positive correlations, while food costs and labor costs showed negative correlations. This suggests that the productivity of university food service increases as the total number served and the use of convenient food item increased, but decreases as the food costs and labor costs per meal increased. A regression analysis showed that three variables - total number sewed, labor cost per meal, number of employees-influenced about 73% components of food service showed a negative correlation with PI and a positive correlation with the labor cost per meal.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.4
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• pp.97-110
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• 2022

The purpose of this study is to analyze the level of public data convergence capabilities of administrative organizations and to explore important variables in data-based organizational capabilities. The theoretical background was summarized on public data and use activation, joint use, convergence, administrative organization, and convergence constraints. These contents were explained Public Data Act, the Electronic Government Act, and the Data-Based Administrative Act. The research model was set as the data-based organizational capabilities effect by a data-based administrative capability, public data operation capabilities, and public data operation constraints. It was also set whether there is a capabilities difference data-based on an organizational operation by the level of data convergence capabilities. This study analysis was conducted with hierarchical cluster analysis and multiple regression analysis. As the research result, First, hierarchical cluster analysis was classified into three groups. It was classified into a group that uses only public data and structured data, a group that uses public data on both structured and unstructured data, and a group that uses both public and private data. Second, the critical variables of data-based organizational operation capabilities were found in the data-based administrative planning and administrative technology, the supervisory organizations and technical systems by public data convergence, and the data sharing and market transaction constraints. Finally, the essential independent variables on data-based organizational competencies differ by group. This study contributed. As a theoretical implication, this research is updated on management information systems by explaining the Public Data Act, the Electronic Government Act, and the Data-Based Administrative Act. As a practical implication, the activity reinforcement of public data should be promoting the establishment of data standardization and search convenience and elimination of the lukewarm attitudes and Selfishness behavior for data sharing.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.374-379
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• 1988

We propose a framework for modelling and operation management of robotic assembly cells via knowledge base. In the framework, each component of the cell is considered as a state variable, the relations among the state variables are stored in state transition maps(STMs) and then transformed into the form of knowledge. The assembly job tree(AJT) which includes the precedence relations and the constraints for assembly tasks is also described. Finally, an algorithm is presented to manage the cell operation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.8
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• pp.585-592
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• 1989

This paper presents an efficient algorithm for the reactive planning of transmission network under normal operating conditions. The optimal operation of a power system is a prerequisite to obtain the optimal investment planning. The operation problem is decomposed into a P-optimization module and a Q-optimization module, but both modules use the same objective function of generation cost. In the investment problem, a new variable decomposition technique is adopted which can operate the operation and the investment variables. The optimization problem is solved by using the gradient projection method (GPM).

• Journal of Korean Academy of Nursing
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• v.2 no.1
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• pp.49-61
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• 1971

The purpose of this study is to observe the administering of analgesics and sedatives to cases of surgery, the influence of the patients'situational variables on the use of these drugs, and the required number of recovery days in relation to the patients'situational variables and general conditions. Fifty patients in the age range of 15 through 65 who had undergone general surgery at Seoul national University Hospital. Woo Sok University Hospital and Koryo Hospital between May and August of 1971 were chosen for this study. They were observed with regard to the frequency of postoperative uses of analgesics and sedatives age, the required period of recovery in comparison with the situational variables of patients such as sex, age, marital status, the type and duration of anesthesia, experience of previous operation, history of other diseases, preoperative period of hospitalizations and the general conditions of patients such as sleep, stomach condition, bowel condition, urination, interest in surroundings, strength and energy, self-assistance and appetite. The study results were reviewed in a statistical method to obtain the following findings: 1. There was a significant decrease in the frequency of analgesic uses according to the number of days passed after operation. 2. The mean postoperative recovery days were 5.31 days and mote than half of the patients have never used analgesics until recovery. 3. There was a significant decrease in the frequency of sedative uses according to the number of days passed after operation. 4. The rank-order correlation between the frequency of analgesic use and that of sedative use following surgery observes in relation to the number of postoperative days was a low and negative one. 5. All of the patients except one hate used sedatives only once a day for the whole recovery period. 6. The longer they stayed in the hospital before surgery, the less have they used analgesics after surgery. 7. There were significant differences in use of analgesics after surgery by age groups; the 25-44 age group used more analgesics than the 15-24 and 45-65 age groups. 8. There were no significant differences in use of analgesics after surgery by all situational variables except the number of days of hospitalization and age. 9. The longer they stayed in the hospital before surgery, the earlier have they recovered from the surgery. 10. There were no significant differences in the number of required recovery days by all situational variables except the length of preoperative hospitalization. 11. There were no significant differences in the number of required postoperative recordedly days by the general conditions of patients.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.

• Korea Journal of Hospital Management
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• v.9 no.1
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• pp.66-94
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• 2004

The objective of this study is to examine how to maximize the efficiency of hospital management by minimizing the unit cost of hospital operation. For this purpose, this paper proposes to develop a model of the profit maximization based on the cost minimization dictum using the statistical tools of arriving at the maximum likelihood values. The preliminary survey data are collected from the annual statistics and their analyses published by Korea Health Industry Development Institute and Korean Hospital Association. The maximum likelihood value statistical analyses are conducted from the information on the cost (function) of each of 36 hospitals selected by the random stratified sampling method according to the size and location (urban or rural) of hospitals. We believe that, although the size of sample is relatively small, because of the sampling method used and the high response rate, the power of estimation of the results of the statistical analyses of the sample hospitals is acceptable. The conceptual framework of analyses is adopted from the various models of the determinants of hospital costs used by the previous studies. According to this framework, the study postulates that the unit cost of hospital operation is determined by the size, scope of service, technology (production function) as measured by capacity utilization, labor capital ratio and labor input-mix variables, and by exogeneous variables. The variables to represent the above cost determinants are selected by using the step-wise regression so that only the statistically significant variables may be utilized in analyzing how these variables impact on the hospital unit cost. The results of the analyses show that the models of hospital cost determinants adopted are well chosen. The various models analyzed have the (goodness of fit) overall determination (R2) which all turned out to be significant, regardless of the variables put in to represent the cost determinants. Specifically, the size and scope of service, no matter how it is measured, i. e., number of admissions per bed, number of ambulatory visits per bed, adjusted inpatient days and adjusted outpatients, have overall effects of reducing the hospital unit costs as measured by the cost per admission, per inpatient day, or office visit implying the existence of the economy of scale in the hospital operation. Thirdly, the technology used in operating a hospital has turned out to have its ramifications on the hospital unit cost similar to those postulated in the static theory of the firm. For example, the capacity utilization as represented by the inpatient days per employee tuned out to have statistically significant negative impacts on the unit cost of hospital operation, while payroll expenses per inpatient cost has a positive effect. The input-mix of hospital operation, as represented by the ratio of the number of doctor, nurse or medical staff per general employee, supports the known thesis that the specialized manpower costs more than the general employees. The labor/capital ratio as represented by the employees per 100 beds is shown to have a positive effect on the cost as expected. As for the exogeneous variable's impacts on the cost, when this variable is represented by the percent of urban 100 population at the location where the hospital is located, the regression analysis shows that the hospitals located in the urban area have a higher cost than those in the rural area. Finally, the case study of the sample hospitals offers a specific information to hospital administrators about how they share in terms of the cost they are incurring in comparison to other hospitals. For example, if his/her hospital is of small size and located in a city, he/she can compare the various costs of his/her hospital operation with those of other similar hospitals. Therefore, he/she may be able to find the reasons why the cost of his/her hospital operation has a higher or lower cost than other similar hospitals in what factors of the hospital cost determinants.