• Journal of Korea Society of Industrial Information Systems
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• v.29 no.4
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• pp.123-138
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• 2024

This study aimed to examine the effects of leisure activities on leisure satisfaction and job satisfaction among airline cabin crew, as well as the mediating effect of leisure satisfaction. The context for this research was the sudden increase in air travel demand in 2022 following the COVID-19 economic recovery, which led to cabin crew members experiencing severe stress and fatigue due to excessive scheduling. To achieve this research objective, a self-administered online survey was conducted with 251 cabin crew members from domestic and international airlines, resulting in a total of 224 valid leisure satisfaction and job satisfaction, as well as the mediating effect of leisure satisfaction on the relationship between leisure activity types and job satisfaction. The hypothesis testing results revealed that all types of leisure activities, including family-oriented, friend-oriented, and work-related activities, had a significant positive effect on leisure satisfaction. Family-oriented and work-related leisure activities had a significant positive effect on job satisfaction, and leisure satisfaction had a significant positive effect on job satisfaction. Additionally, the mediation analysis confirmed that leisure satisfaction partially mediated the relationship between family-oriented and work-related leisure activities and job satisfaction, while it fully mediated the relationship between friend-oriented leisure activities and job satisfaction. Therefore, the study offers academic implications based on these findings and proposes strategies for utilizing various types of leisure activities to enhance leisure satisfaction and job satisfaction among airline cabin crew. It also suggests that future research should further validate these findings through methods such as the Delphi technique or Analytic Hierarchy Process (AHP) analysis to assess the importance and prioritization of these factors among relevant industry stakeholders.

• Journal of Animal Science and Technology
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• v.55 no.5
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• pp.359-365
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• 2013

Estimate breeding value can be used as single trait animal model was developed directly using the Fortran language program. The program is based on data computed by using the indirect method repeatedly. The program develops a common algorithm and imprves efficiency. Algorithm efficiency was compared between the two programs. Estimated using the solution is easy to farm and brand the service, pedigree data base was associated with the development of an improved system. The existing program that uses the single trait animal model and the comparative analysis of efficiency is weak because the estimation of the solution and the conventional algorithm programmed through regular formulation involve many repetition; therefore, the newly developed algorithm was conducted to improve speed by reducing the repetition. Single trait animal model was used to analyze Gauss-Seidel iteration method, and the aforesaid two algorithms were compared thorough the mixed model equation which is used the most commonly in estimating the current breeding value by applying the procedures such as the preparation of information necessary for modelling, removal of duplicative data, verifying the parent information of based population in the pedigree data, and assigning sequential numbers, etc. The existing conventional algorithm is the method for reading and recording the data by utilizing the successive repetitive sentences, while new algorithm is the method for directly generating the left hand side for estimation based on effect. Two programs were developed to ensure the accurate evaluation. BLUPF90 and MTDFREML were compared using the estimated solution. In relation to the pearson and spearman correlation, the estimated breeding value correlation coefficients were highest among all traits over 99.5%. Depending on the breeding value of the high correlation in Model I and Model II, accurate evaluation can be found. The number of iteration to convergence was 2,568 in Model I and 1,038 in Model II. The speed of solving was 256.008 seconds in Model I and 235.729 seconds in Model II. Model II had a speed of approximately 10% more than Model I. Therefore, it is considered to be much more effective to analyze large data through the improved algorithm than the existing method. If the corresponding program is systemized and utilized for the consulting of farm and industrial services, it would make contribution to the early selection of individual, shorten the generation, and cultivation of superior groups, and help develop the Hanwoo industry further through the improvement of breeding value based enhancement, ultimately paving the way for the country to evolve into an advanced livestock country.

• 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.

• Analytical Science and Technology
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• v.28 no.3
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• pp.160-167
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• 2015

This study aims to develop a new analytical method to detect zinc pyrithione, the ingredient of cosmetics appointed as restricted ingredients and used as preservatives.. The analytical method was based on data gathered from the relevant literature. Information about the amounts of these ingredients was researched in order to select the base-matrix materials used to validate the analytical method. After selecting and preparing the base-matrix materials, the analytical method was validated by method validation procedures. The analytical method was verified first by inter-laboratory validation and then through analyzing the cosmetics sold in the market. Based on the results of this study, guidelines are proposed for the analysis of restricted ingredients in cosmetics, which will provide a method to test the cosmetics circulating in the Korean market. The use of the proposed guidelines will increase the quality of the cosmetics as well as the safety of human health, which will enhance the competitiveness of the Korean cosmetics industry and lead to an increase in the exportation of cosmetics.

• Journal of Korea Water Resources Association
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• v.45 no.4
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• pp.373-381
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• 2012

The information on the economic value of industrial water use is widely demanded in policy analysis area as well as academic research area. Therefore, this study attempts to obtain more accurate economic value of industrial water use using the economic theory. To this end, we conducted a survey of 1,017 manufacturing firms and estimated the economic value of industrial water use based on the concept of value of marginal product (VMP). Moreover, this study tried to estimate the VMP of three industrial water types, river water, precipitated water, and purified water. The results show that the VMPs of river water, precipitated water and purified water are estimated to be 769.24 won/$m^3$, 896.76 won/$m^3$ and 1,861.95 won/$m^3$, respectively. The value for the precipitated water found in this study is not significantly different from that (885.1 won/$m^3$) used in the pre-feasibility test implemented by Korea Development Institute (KDI). These imply that the latter is appropriate for evaluating the economic benefit of supplying industrial water, though it is based on 2003 Industry Survey.

• Journal of the Korea Institute of Building Construction
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• v.18 no.2
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• pp.151-159
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• 2018

Accident rate in the construction industry of South Korea is increasing every year, and it represents the highest percentage among industries. This shows that activities performed to prevent safety accidents in the country are not efficient when it comes to reduce the accident rate. In order to resolve this issue, a model for the prediction of human accidents should be established. In addition, it is required a quantification study based on pattern of human accidents. Therefore, the objective of this study is to quantify uncertainty of human accidents risk and predict how to change in various circumstances by using Monte Carlo Simulation. To achieve the objective, first, pattern of human accidents was defined. Second, insurance claim payout and information of human accidents during 14 years in construction site were collected. Third, descriptive analysis is conducted to determine the characteristics of the accident pattern. Fourth, to quantitatively analyze the pattern of the human accidents, the population of each accident occurrence and payout were estimated. Finally, estimated populations was analyzed according to characteristics of distribution by using Monte carlo simulation. In the future, this study can be used as a reference for developing the safety management checklist in construction site and development of prediction models of human accident.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8940-8947
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• 2015

Mixed-model assembly line has been widely used in automotive assembly industry to quickly respond the diverse product demands. But, this model can lead to part confusion, which is a source for assembly errors when parts are physically interchangeable in a mixed-model assembly line. With the recent application of new technologies such as radio frequency identification (RFID) and ZigBee wireless sensor network (WSN) to the assembly process, real-time information has become available in this manufacturing systems through IT infrastructures. At first, this paper presents an RFID application for assembly processes, specifically, for a mixed-model assembly line. Thus, to ensure that parts be picked accurately, each cockpit module on the assembly line is attached with a RFID tag and the tag is scanned using a RFID reader and recognizes the vehicle, and each part of the cockpit module is attached with a barcode and the barcode is scanned by a barcode reader and each part is identified correctly for the vehicle. Second, this paper presents a ZigBee wireless sensor network (WSN) protocol-based application for a reconfigurable mixed-model assembly line of cockpit module to reduce the assembly errors and the cost of the change/reconfiguration on the assembly lines due to the various orders and new models from the motor company, avoiding the wiring efforts and inconvenience by wiring between the several RFID devices and the IT server system. Finally, we presents the operation results for several years using this RFID/ZigBee wireless sensor network (WSN) protocol-based cockpit module assembly line.

• Journal of Korea Port Economic Association
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• v.31 no.4
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• pp.91-106
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• 2015

This study aims to analyze the effects of service quality offered by automotive Ro-Ro terminal operators on customer satisfaction and loyalty. The results of the research can be used to understand how to enhance the service level in order to manage competitiveness of the terminal operators, finally resulting in global competitiveness of the automobile industry of Korea in both exports and imports. We carried out a survey on two groups: shippers (customers) and providers (related terminal operators and stakeholders). To identify and classify the factors into groups, we conducted Exploratory Factors Analysis (EFA) and Confirmatory Factor Analysis (CFA), which showed construct validity and convergent validity. We also calculated Cronbach's alpha for reliability. Five factor groups were identified: tangibles, reliability, responsiveness, assurance, and empathy. We found that empathy is the most influential factor group among the five groups, and that the other groups too exhibited similar effects. Based on the results of the survey and analyses, we can conclude that empathy is most important in automotive Ro-Ro terminals. In particular, specialties, training, experiences, and loyalty of employees are crucial factors because automotive Ro-Ro terminals significantly rely on work forces, differently from other bulk terminals and container terminals. Flexible working hours and fringe benefits for work forces can increase empathy, finally resulting in productivity and efficiency. Next, well-designed work schedules are followed, based on visibility through logistics and SCM activities in automobile export and import processes with information and communication networks.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1522-1522
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• 2001

Beverages based on fruit juices are among the most popular commercially available drinks. There is an ever-increasing demand for these juices in the market. Orange juice is one of the most common as well as most favorite flavor. The fruit processing industries have a tremendous responsibility of quality control. For quality evaluation estimation of various components of the juice is necessary. Sucrose, glucose, fructose, citric acid and malic acid are the prime components of orange juice. Little information is available on analysis of orange juice. However, conventional and general wet chemistry procedures are currently being used which are no longer desired by the industry owing to the time involved, labor input and harmful chemicals required for each analysis. Need to replace these techniques with new, highly specific and automated sophisticated techniques viz. HPLC and spectroscopy has been realized since long time. Potential of Near Infrared Spectroscopy in quantitative analysis of different components of food samples has also been well established. A rapid, non-destructive and accurate technique based on Near Infrared Spectroscopy for determination of sugars and organic acids in orange juice will be highly useful. The current study is an investigation into the potential of Near Infrared Diffuse Reflectance Spectroscopy for rapid quantitative analysis of sucrose, glucose, fructose citric acid and malic acid in orange juice. All the Near Infrared measurements were peformed on a dispersive NIR spectrophotometer (ELICO 153) in diffuse reflectance mode. The spectral region from 1100 to 2500nm has been explored. The calibration has been performed on synthetic samples that are mixtures of sucrose, glucose, fructose, citric acid and malic acid in different concentration ranges typically encountered real orange juice. These synthetic samples are therefore considered to be representatives of natural juices. All the Near Infrared spectra of synthetic samples were subjected to mathematical analysis using Partial Least Square (PLS) algorithm. After the validation, calibration was applied to commercially available real samples and freshly squeezed natural juice samples. The actual concentrations were compared with those predicted from calibration curve. A good correlation is obtained between actual and predicted values as indicated by correlation coefficient ($R^2$) value, which is close to unity, showing the feasibility of the technique.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.10
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• pp.3885-3892
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• 2010

Safety-Critical systems, such as Plant Protection Systems in nuclear power plant, plays a key role that the facilities can be operated without undue risk to the health and safety of public and environment, and those systems shall be designed, fabricated, installed, and tested to quality standards commensurate with the importance of the functions to be performed. Computer-based Instrumentation and Control Systems to perform the safety-critical function have Real Time Operating Systems to control and monitoring the sub-system and executing the application software. The safety-critical Real Time Operating Systems shall be designed, analyzed, tested and evaluated to have capability to maintain a high integrity and quality. However, local nuclear power plants have applied the real time operating systems on safety critical systems through Commercial Grade Item Dedication method, and this is the reason of lack of detailed methodology on assessing the safety of real time operating systems, expecially to the new developed one. This paper presents the methodology and experiences of safety evaluation on safety-critical Real Time Operating Systems based upon design requirements. This paper may useful to develop and evaluate the safety-critical Real Time Operating Systems in other industry to ensure the safety of public and environment.