• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.21 no.2
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• pp.151-155
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• 2008

KHST(Korean High Speed Train) has been utilized the total measurement system which evaluates the efficiency and a breakdown of the vehicle and it's results effect to secure reliability of the vehicle. Generally KHST has been received pulse signals from the wheel. It calculates the travel distance after counter the signals to confirm location information of the vehicle. However, there is a limit to measure the location of the vehicle due to slip, slide and the wheel attrition. We have developed a new measurement system by using GPS to complement those errors. In general, GPS receivers are composed of an antenna, tuned to the frequencies transmitted by the satellites, receiver-processors, and a highly-stable clock The GPS mounted on the roof of TT4 in KHST receives a signal from the RS232 communication port. It is connected to the network system in TT3 after converting with TCPIP communication. It is able to track the position of vehicle and synchronize the signal from different measurement system simultaneously. Therefore it is able to chase the fault occurrence, track inspection and electrical interruption at real-time situation more accurately. There is not an error coursed by vehicle conditions such as slip and the slide.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.987-1000
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• 2021

The concept of 'Employer branding' (EB) - one effective and sustainable strategy to attract and retain talent - has received a lot of attention from researchers and business managers. This concept becomes more meaningful when the 'war of talent' takes place in an extremely fierce manner in Vietnam as well as around the world. However, this concept is rather new; as a result, many points related to 'EB' scales should be improved, especially in Vietnamese context. Therefore, this study focuses on developing and confirming the EB scale in the context of Vietnam. Based on EB theory, this research applies the mixed research method: qualitative methods (expert interview and group discussion) and quantitative method (questionnaire survey of 937 respondents). EB is demonstrated to be a quadratic concept, consisting of the following 10 dimensions: Corporate social responsibility (CSR), Promotion (PRO), Work-Life Balance Satisfaction (WLSA), Education (EDU), Behavior-based Family interference with work (WLBE), Travel opportunities (TRA), Time-based work interference with family (WLTI), Teamwork (GRO), Supporting (SUP), and Strain-based family interference with work (WLST) with 58 observed variables. Based on the survey towards the employees in enterprises and organizations in Vietnam, the analysis results affirm that this scale ensures efficiency, reliability, unidirectionality and convergent values.

• Journal of Korean Society of Transportation
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• v.23 no.3 s.81
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• pp.7-19
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• 2005

Mode choice Analysis is essential analysis stage in transportation demand forecasting process. Therefore, methods for calibration and forecasting of mode choice model in aspect of practical view need to be discussed in depth. Since 1980s, choice models, especially Logit model, are spread widely and rapidly over academic area, research institutes and consulting firms in Korea like other developed countries in the world. However, the process of calibration and parameter estimation for practical application was not clearly explained in previous papers and reports. This study tried to explain clearly the calibration process of mode choice step by step and suggested a forecasting mode choice model that can be applicable in real policy analysis by using household survey data of Pusan metropolitan are. The study also suggested a way of estimating attributes which was not observed during the household survey commonly such as travel time and cost of unchosen alternative modes. The study summarized the statistical results of model specification for four different Logit models as a process to upgrade model capability of explanation for real traveler's choice behaviors. By using the analysis results, it also calculated the value of travel time and compared them with the values of other previous studies to test reliability of the estimated model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.42-52
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• 2022

Bus Information System (BIS) services are expanding nationwide to small and medium-sized cities, including large cities, and user satisfaction is continuously improving. In addition, technology development related to improving reliability of bus arrival time and improvement research to minimize errors continue, and above all, the importance of information accuracy is emerging. In this study, accuracy performance was evaluated using LSTM, a machine learning method, and compared with existing methodologies such as Kalman filter and neural network. As a result of analyzing the standard error for the actual travel time and predicted values, it was analyzed that the LSTM machine learning method has about 1% higher accuracy and the standard error is about 10 seconds lower than the existing algorithm. On the other hand, 109 out of 162 sections (67.3%) were analyzed to be excellent, indicating that the LSTM method was not entirely excellent. It is judged that further improved accuracy prediction will be possible when algorithms are fused through section characteristic analysis.

• Journal of Korean Public Health Nursing
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• v.17 no.2
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• pp.203-211
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• 2003

The purpose of this study was to investigate the degree of satisfaction in using rehabilitation exercise rooms in public health centers. A total of 100 subjects were participated in the study who were clients of rehabilitation exercise rooms in two public health centers in one city of Kyunggi Do, Korea. Data were collected from March 1 to 30, 2003 using questionnaire. The data were analyzed using SPSS/PC computer program. The result are as follows : 1. The mean age of subjects was 62.6 years old, and men constituted $67.0\%$ of the participants. Most participants $(64\%)$ were in the middle socioeconomic status, and $(65\%)$ of subjects was diagnosed as stroke. 2. Regarding the source of information about rehabilitation exercise room in public health center, $56.0\%$ obtain information from colleagues or neighbors, and for most participants the time required to travel to rehabilitation exercise room was less than 30min on foot. Among rehabilitation services, Taping therapy $(53.0\%)$ was most frequently used among participants, 3. Sum of all satisfaction score was $71.10(\pm6.60,\;range:\;1-90)$ showed higher level of satisfaction. Cost, reliability, and kindness were main factors that affect the degree of satisfaction among participants. 4. Twenty-four percent of the respondents utilized clinic services in the health centers, and $27.4\%$ stoped rehabilitation services from hospitals and/or clinics due to high cost. 5. In the use of rehabilitation exercise room was positively correlated to age (r=.214, p<0.05) and disease duration(r=.241. p<0.05).

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.183-193
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• 2009

Air pollution due to vehicle exhaust gas is considered to be a main contributor to the issues of transportation & environment. Furthermore it is raising concern over life quality and public health and is also perceived as a global issue. This research aims at providing helping hands for both central and local governments to set up and promote efficient atmospheric quality improvement policies, with the help of the travel demand forecasting model and GIS. More specifically, it tries to produce the overall emission level with time and space-based high resolution framework. This research, based on bottom-up approach reflecting vehicular traffic characteristics, suggested an improved approach to estimating emission level, by using a traffic model with a total of vehicular mileage revised by surveyed value and atmosphere model. Summing up, using the method proposed, the improvement of the reliability of the emissions inventory from the mobile pollutions sources is expected by the proposed integrated paradigm of transportation and atmosphere modeling approach as a new alternative.

• International Journal of Highway Engineering
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• v.9 no.3
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• pp.51-62
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• 2007

Recently various low-noise-pavement methods have been developed. Since tire/pavement noise is the major source of traffic noise at high speed condition, the core-technology of low-noise pavement is to produce the road surface texture that can reduce tire/pavement noise. The difficulties in the development of the low-noise pavements are high costs and time to construct test roads, since vehicles have to travel on the test roads to evaluate the noise from a particular condition of pavement surface. Tire/Pavement Noise Simulator were developed to overcome those difficulties and the reliability of developed Tire/Pavement Noise Simulator are investigated based on the simulating and measuring the noise of tire-tined concrete pavement and tire-non tined concrete pavement.

• The Journal of the Korea Contents Association
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• v.10 no.7
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• pp.317-325
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• 2010

This study aims to deduct the extensive improvement types of leisure activities of private security agents using PPA technique and to examine the influence of leisure constraint on the index of participation. Through this process, this study consequently will draw the priority list of investment on the policy for improving the welfare status of private security agents. In this study, judgement sampling was applied to 6 security agencies located in Seoul, 2010, and 267 cases were used in the final analysis. Collected data went through factor analysis, reliability analysis, paired t test, PPA analysis, and regression analysis by using SPSSWIN 17.0. The conclusions were drawn as follows. In regard to the reliability, Cronbach's $\alpha$ was over .768. First, there was a difference between the preference rate and the participation rate which are the participation index of the private security agents' leisure activities. concentrate here in leisure types turned out to be fitness activities, walking/jogging, tourism, a day-long travel, and keep up the cood work in leisure types are movies, domestic tourist attractions, dating, eating out, personal relationship, watching sports, reading, karaoke, TV video watching, drinking etc. low priority in leisure types are water sports, hiking, biking, soccer, photography, ball games, sky sports, playing go/janggi, inline skates, and cooking. Second, the leisure constraint affects the participation index of leisure activities. As the personal constraint, and surrounding conscious constraint which are the subordinate factors of the leisure constraint get bigger, the participation index of favored leisure activities become lower. In contrast, when the difficulties such as structural constraint, time and economical constraint are overcome, participation index of leisure activities go on the rise.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.6
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• pp.74-83
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• 2011

The high-pass transportation information system directly collects section information by using probe cars and therefore can offer more reliable information to drivers. However, because the running condition and features of probe cars and statistical processing methods affect the reliability of the information and particularly because the section travel time is greatly influenced by whether there has been delay by signals on urban roads or not, there can be much deviation among the collected individual probe data. Accordingly, researches in multilateral directions are necessary in order to enhance the credibility of the section information. Yet, the precedent studies related to high-pass information provision have been conducted on the highway sections with the feature of continuous flow, which has a limit to be applied to the urban roads with the transportational feature of an interrupted flow. Therefore, this research aims at analyzing the features of high-pass transportation data on urban roads and finding a proper processing method. When the characteristics of the high-pass data on urban roads collected from RSE were analyzed by using a time-space diagram, the collected data was proved to have a certain pattern according to the arriving cars' waiting for signals with the period of the signaling cycle of the finish node. Moreover, the number of waiting for signals and the time of waiting caused the deviation in the collected data, and it was bigger in traffic jam. The analysis result showed that it was because the increased number of waiting for signals in traffic jam caused the deviation to be offset partially. The analysis result shows that it is appropriate to use the mean of this collected data of high-pass on urban roads as its representative value to reflect the transportational features by waiting for signals, and the standard of judgment of delay and congestion needs to be changed depending on the features of signals and roads. The results of this research are expected to be the foundation stone to improve the reliability of high-pass information on urban roads.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.44-53
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• 2016

The era of Big Data has come and the importance of Big Data has been rapidly growing. The part of transportation, the Four-Step Travel Demand Model(FSTDM), a traditional Trip-Based Model(TBM) reaches its limit. In recent years, a traffic demand forecasting method using the Activity-Based Model(ABM) emerged as a new paradigm. Given that transportation means the spatial movement of people and goods in a certain period of time, transportation could be very closely associated with spatial data. So, I mined Spatial Big Data from SNS. After that, I analyzed the character of these data from SNS and test the reliability of the data through compared with the attributes of TBM. Finally, I built a database from SNS for the operation of ABM and manipulate an ABM simulator, then I consider the result. Through this research, I was successfully able to create a spatial database from SNS and I found possibilities to overcome technical limitations on using Spatial Big Data in the transportation planning process. Moreover, it was an opportunity to seek ways of further research development.