• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.881-887
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• 2015

The hardware-in-the-loop simulation (HILS) of a railway vehicle is crucial for overcoming the limitation of field tests of a railway vehicle. A brake HILS system for a railway vehicle was previously not able to test the performance of a speed-sensing system of a railway vehicle, since wheelset speeds were generated only by computer simulations. In this paper, we present a novel wheelset speed implementation of a brake HILS system for a railway vehicle. Four wheelset speeds of a brake HILS system for a car of a railway vehicle are implemented using four small-sized servomotors, whereas the speed sensors and pole wheels used in the brake HILS system are the actual ones of the railway vehicle. According to the simulated speeds of four wheelsets in the dynamic equations of motion, four servomotors generate wheel speeds in real time, and then the measured wheelset speeds are fed back to the computer simulation model. Moreover, in this paper, we improve the performance of wheelset speed measurement via the T method instead of the M method presently used in the field. The performances of wheelset speed implementation and speed-sensor operation are demonstrated by experimental works using a HILS system.

• Proceedings of the Korean Association for Survey Research Conference
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• 2006.06a
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• pp.131-159
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• 2006

This paper consider multinomial group testing which is concerned with classification each of N given units into one of k disjoint categories. In this paper, we propose exact Bayesian, approximate Bayesian, bootstrap methods for estimating individual category proportions using the multinomial group testing model proposed by Bar-Lev et al (2005). By the comparison of Mcan Squre Error (MSE), it is shown that the exact Bayesian method has a bettor efficiency and consistency than maximum likelihood method. We suggest an approximate Bayesian approach using Markov Chain Monte Carlo (MCMC) for posterior computation. We derive exact credible intervals based on the exact Bayesian estimators and present confidence intervals using the bootstrap and MCMC. These intervals arc shown to often have better coverage properties and similar mean lengths to maximum likelihood method already available. Furthermore the proposed models are illustrated using data from a HIV blooding test study throughout California, 2000.

• Journal of Industrial Convergence
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• v.13 no.2
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• pp.25-37
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• 2015

The purpose of this study is about the influence of the Service quality on the customer loyalty depending on the customer value(social and psychological value, functional value) because of the dynamic business environment is react quickly and flexibly, many of today's companies are required to consult an expert. According to the circumstances, Service Firms(Hotel) should be provide a differentiated service for each customer. And this paper attempt to theoretical organize and take advantage of practical in Service industry. The questionaries of 154 from the companies which have received Service in 3 years in the metropolis and small and medium-sized cities were used to test hierarchical regression model with mediating effects of customer value between Service quality and Customer loyalty by SPSS(PASW) 18.0 version. From these analyses, the following results were obtained: First, social-psychological value have partially mediated effect on the tangibility, responsibility, assurance and customer loyalty. Second, functional value have partially mediated effects on the between tangibles, reliability and customer loyalty. The result suggests that 'tangibility', 'reliability', 'responsibility', 'assurance', 'empathy' are the most important factors to affect customer loyalty, and there are partially mediated effects of customer intention between Service quality and Customer loyalty. In conclusion, to improve the specific and actual meaning and value about the Hotel service quality and to give the suggestions on the Hotel's marketing communication by understanding the customer action.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.1041-1050
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• 2021

Employee engagement plays an important role in the development as well as the success of a company. The manner in which employees are committed to their work and be more innovative seems to drive people's curiosity. This study aims to analyze the impacts of job demands-resources, personal resources, and coworker support on work engagement. Also, whether there is a relationship between work engagement and creativity of employees is tested through this research. The data served for the research was collected in the context of Vietnamese small- and medium-sized enterprises (SMEs). The authors used structural equation modeling (SEM) (software Smart PLS), to test the proposed hypotheses by using the data of 602 employees. Results of the study point out that proposed antecedents influence work engagement and creativity. Such findings have shed light on both theory and practice implications. In theory, it supports the social exchange theory and the job demands and resources model. In practice, leaders should assist subordinates in various aspects and build and promote a corporate culture where employees help others with great enthusiasm to increase the level of work engagement and spirit of innovation of employees.

• Korea Trade Review
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• v.47 no.5
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• pp.161-179
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• 2022

This paper aims to examine the role of government's support in facilitating small and medium sized enterprises (SMEs)' green dynamic capabilities and green SCM practices in a global market. It also investigates whether government support, green dynamic capabilities, and green SCM practices affect export competitiveness. To develop those hypotheses, prior studies and in-depth interviews were conducted and data was collected from Korean manufacturing companies that export abroad and then developed the structural equation model. The hypotheses test results revealed that green dynamic capabilities through government support positively affect export competitiveness and green SCM practices through green dynamic capabilities have positive effects on export competitiveness. Finally, this study is valuable in that it directly and indirectly confirmed the effect of eco-friendly government support on export competitiveness.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.2
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• pp.11-16
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• 2015

A lot of factor effects on the enterprise's innovation and business performance, for instance CEO and members intention etc.. Niehoff et al. says, The success factors of innovation enterprise's management lead to members of vision, innovation, innovation activities and support for an aggressive attitude of the enterprise members. However, today's products consumers wanted diverse and complex needs. CEO and members of the enterprise has been the diversity effort. The increase cost savings as well as in the profit improve factors that enterprise's participated a education and training, Subgroup activities, process quality, eliminate waste, improve yields, lead time reduction, process capability increasing, ets. This paper is a report of an empirical survey performed to 277 small and medium-sized enterprise in the korea. Cronbach's alpha coefficient is employed to analyze the reliability of the data. The effect analysis of each group is performed by the SEM(structural equation model). We use the SPSS' Amos program to analyze the equation modeling and test the hypotheses of the model.

• Journal of Korea Water Resources Association
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• v.30 no.3
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• pp.279-291
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• 1997

This study is to evaluate the accuracy and practicality of the existing four conceptual models, two linear models of Clark and Nash model and two nonlinear models of Laruenson and WBN model, and to select an appropriate model to simulate the rainfall-runoff process in a given catchment. The variability of parameters for linear models is generally larger than that of nonlinear models. The errors in peak discharge are similar among the four conceptual models buy the errors in time to peak are quite different. Nonlinear models produce better results for time distribution than linear models. A comparison of the conceptual models to predict overall hydrograph using Friedman two-way analysis of variance by rank test indicates that nonlinear models are slightly better than linear models.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.23-32
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• 2020

Many small and medium-sized manufacturing companies process various product types to respond different customer orders in a single production line. To improve their productivity, they often apply batch processing while considering various product types, constraints on batch sizes and setups, and due date of each order. This study introduces a batch scheduling heuristic for a production line with multiple product types and different due dates of each order. As the process times vary due to the different batch sizes and product types, a recursive equation is developed based on a flow line model to obtain the upper bound on the completion times with less computational complexity than full computation. The batch scheduling algorithm combines and schedules the orders with same product types into a batch to improve productivity, but within the constraints to match the due dates of the orders. The algorithm incorporates simple and intuitive principles for the purpose of being applied to small and medium companies. To test the algorithm, two case studies are introduced; a high pressure coolant (HPC) manufacturing line and a press process at a plate-type heat exchanger manufacturer. From the case studies, the developed algorithm provides significant improvements in setup frequency and thus convenience of workers and productivity, without violating due dates of each order.

• Korean Journal of Construction Engineering and Management
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• v.17 no.5
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• pp.78-88
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• 2016

Recently BIM technology has been expanded for using in construction project. However its spread has been delayed than the initial expectations, due to the high-cost of BIM infrastructure development, the lack of regulations, the lack of process and so forth. In design phase, especially, collaboration based on BIM system has being a key factor for successful next generation building project. Through the analysis of current research trend about IT technologies, virtualization and BIM service, data exchange such as drawing, 3D model, object data, properties using cloud computing and virtual server system is defined as a most successful solution. In various industrial fields, cloud computing technology is utilized as a promising solution which can reduce time and cost of hardware infrastructure. Among the cloud computing technology, VDI is receiving a great deal of attention from it market as an essential part cloud computing. VDI enables to host multiple individual virtual machines by using hypervisor. It has an advantage to easy main device management. Therefore, this study implements a step-by-step user's DaaS by analyzing the desktop resource data of the workers from Pre-design phase to Schematic design, Design develop and Construction design phase. It also develops BIM environment based on test of BIM modeler and designers in architectural design firm. The goal of the study is to enable the cloud computing BIM server. It provides cost saving, high-performance quality of working environment and cooperation's convenience and high security when doing BIM work in small and medium sized architectural design firm.

• Smart Structures and Systems
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• v.29 no.4
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• pp.625-640
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• 2022

Maglev rail joints are vital components serving as connections between the adjacent F-type rail sections in maglev guideway. Damage to maglev rail joints such as bolt looseness may result in rough suspension gap fluctuation, failure of suspension control, and even sudden clash between the electromagnets and F-type rail. The condition monitoring of maglev rail joints is therefore highly desirable to maintain safe operation of maglev. In this connection, an online damage detection approach based on three-dimensional (3D) convolutional neural network (CNN) and time-frequency characterization is developed for simultaneous detection of multiple damage of maglev rail joints in this paper. The training and testing data used for condition evaluation of maglev rail joints consist of two months of acceleration recordings, which were acquired in-situ from different rail joints by an integrated online monitoring system during a maglev train running on a test line. Short-time Fourier transform (STFT) method is applied to transform the raw monitoring data into time-frequency spectrograms (TFS). Three CNN architectures, i.e., small-sized CNN (S-CNN), middle-sized CNN (M-CNN), and large-sized CNN (L-CNN), are configured for trial calculation and the M-CNN model with excellent prediction accuracy and high computational efficiency is finally optioned for multiple damage detection of maglev rail joints. Results show that the rail joints in three different conditions (bolt-looseness-caused rail step, misalignment-caused lateral dislocation, and normal condition) are successfully identified by the proposed approach, even when using data collected from rail joints from which no data were used in the CNN training. The capability of the proposed method is further examined by using the data collected after the loosed bolts have been replaced. In addition, by comparison with the results of CNN using frequency spectrum and traditional neural network using TFS, the proposed TFS-CNN framework is proven more accurate and robust for multiple damage detection of maglev rail joints.