• Korean Journal of Human Ecology
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• v.16 no.1
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• pp.159-171
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• 2007

The purpose of this research is to analyze the difference of Structural Equation Model which shows the path between BRQ and its performance variables according to purchase product types-fashion brand types, clothing item groups. The subjects were women in their 20s to 40s living in Seoul and Metropolitan areas, and 482 copies of questionnaire were analyzed. Multi-Group Analysis of AMOS 5.0 Package was used to investigate structural equation model according to fashion brand types and clothing item groups. The results of this study were as follows. As for fashion brand types, there appeared to be significant differences between high price brand type and medium-low price brand type for three paths, namely brand satisfaction to brand loyalty, BRQ to brand attitude, and brand attitude to brand loyalty. However the verification of structural equation model according to clothing item groups showed no significant differences between formal wear and informal wear. Consequently, BRQ was proved to affect brand satisfaction and brand loyalty, and brand satisfaction was the important intermediate variable between BRQ and brand loyalty. As consumers were likely to show the difference of structural equation model according to the price of purchase goods, differencial marketing strategy would be suggested.

• Journal of the Ergonomics Society of Korea
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• v.30 no.2
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• pp.365-373
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• 2011

The existing GOMS model overestimates the performance time of mouse activities because it describes them in a serial sequence. However, parallel movements of eye and hand(eye-hand coordination) have been dominant in mouse activities and this eye-hand coordination is the main factor for the overestimation of performance time. In this study, therefore, the revised CGOMSL model was developed to implement eye-hand coordination to the mouse activity to overcome one of the limitations of GOMS model, the lack of capability for parallel processing. The suggested revised CGOMSL model for drag activity, as an example for one of mouse activities in this study, begins visual search processing before a hand movement but ends the visual search processing with the hand movement in the same time. The results show that the revised CGOMSL model made the prediction of human performance more accurately than the existing GOMS model. In other words, one of the limitations of GOMS model, the incapability of parallel processing, could be overcome with the revised CGOMSL model so that the performance time should be more accurately predicted.

• Asian Journal for Public Opinion Research
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• v.10 no.2
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• pp.123-146
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• 2022

This study aims to identify the effect of the relationship between human resources management (HRM) and total quality management (TQM) on improving employee performance. Several previous qualitative studies have stated that TQM and HRM are separate methods. This article describes a new method using a quantitative approach. This research is needed to fill the gap in the literature by empirically analyzing the relationship between HRM, TQM practices, and organizational performance. Data was collected quantitatively from 100 employees in Indonesia through questionnaires and online survey methods. The data collected were analyzed using structural equation modeling (SEM) with the Lisrel 8.5 system. TQM-oriented HRM is operationalized as a second-order latent variable measured by four factors (training, empowerment, teamwork, compensation). The findings support the validity of the TQM-oriented HRM model as a hierarchical, second-order latent construct and show a strong relationship with employee performance. The results of this study are different from previous studies, which showed that TQM and HRM are separate methods. The results of our research provide an academic and practical overview that TQM-oriented HRM can be used to help organizations build platforms for human resources policies aimed at improving employee performance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.836-842
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• 2016

When an accident occurs in the nuclear power plant, the faulted information might mislead to the high possibility of aggravating the accident. At the Fukushima accident, the operators misunderstood that there was no core exposure despite in the processing of core damage, because the instrument information of the reactor water level was provided to the operators optimistically other than the actual situation. Thus, this misunderstanding actually caused to much confusions on the rapid countermeasure on the accident, and then resulted in multiplying the accident propagation. It is necessary to be equipped with the function that informs operators the status of instrument integrity in real time. If plant operators verify that the instruments are working properly during accident conditions, they are able to make a decision more safely. In this study, we have performed various tests for the fault detection sensitivity of an data-driven empirical model to review the usability of the model in the accident conditions. The test was performed by using simulation data from the compact nuclear simulator that is numerically simulated to PWR type nuclear power plant. As a result of the test, the proposed model has shown good performance for detecting the specified instrument faults during normal plant conditions. Although the instrument fault detection sensitivity during plant accident conditions is lower than that during normal condition, the data-drive empirical model can be detected an instrument fault during early stage of plant accidents.

• The Journal of Korea Robotics Society
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• v.8 no.2
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• pp.104-115
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• 2013

For natural human-robot interaction, we need to know location and shape of facial feature in real environment. In order to track facial feature robustly, we can use the method combining particle filter and active appearance model. However, processing speed of this method is too slow. In this paper, we propose two ideas to improve efficiency of this method. The first idea is changing the number of particles situationally. And the second idea is switching the prediction model situationally. Experimental results is presented to show that the proposed method is about three times faster than the method combining particle filter and active appearance model, whereas the performance of the proposed method is maintained.

• Journal of Korean Academy of Nursing Administration
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• v.8 no.2
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• pp.335-346
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• 2002

Purpose: This study is to analyze the relationship between leadership, empowerment, organizational commitment, and nursing performance. Method: The method of the study is the establishment of the analytical framework of the theoretical model and the hypotheses for the empirical survey, analysis of the data collected by the empirical survey, and the provision of a revised model explaining more clearly the causal relationship between variables. Result: Transformational leadership has greater influence on empowerment and nursing performance than transactional leadership. Self determination and impact of empowerment factors greatly influence on organizational commitment, competence and impact significantly influence on nursing performance, and organizational commitment is closely related to the general nursing affair, the human relationship, and the job as an organizational member. Transactional and transformational leadership, in provision of the revised model by verification of goodness-of-fit of the hypothetical model, affects all parts of nursing performance by intervening competence and self determination of empowerment factors. Especially, transactional leadership directly influences on nursing performance without intervening the empowerment factor. Conclusion: The conclusion of the study is transformational leadership exerts a more positive influence on empowerment, organizational commitment, and nursing performance than transactional leadership.

• Journal of Korean Society for Quality Management
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• v.39 no.4
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• pp.464-479
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• 2011

The purpose of this study is that analyzing the causal relationship between Infra, Process and Performance of companies which are executing the Supply Chain Quality Management(SCQM) with their subcontractors and partners. Korean Standards Association(KSA) provides the Supply Chain Quality Management Model and Quality Collaboration Index for 4 years, but a few study has investigated the critical variables and their causal relationship to organizational performance. Therefore we examine the SCQM model and related index and choose the quality, human resource and risk management processes for identifying the path to organizational performance. In addition, exploratory factor analysis is conducted for figuring out the major factors among the 3 processes. Structural Equation Model are successively used for determining which characteristics of the infra and processes are the most critical variables to performance. The data was collected from KSA and composed of 52 companies and 346 their partners. The result shows that risk management process has no significant effect on the organizational performance and pre-production process collaboration.

• ETRI Journal
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• v.36 no.4
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• pp.662-672
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• 2014

Human action recognition is used in areas such as surveillance, entertainment, and healthcare. This paper proposes a system to recognize both single and continuous human actions from monocular video sequences, based on 3D human modeling and cyclic hidden Markov models (CHMMs). First, for each frame in a monocular video sequence, the 3D coordinates of joints belonging to a human object, through actions of multiple cycles, are extracted using 3D human modeling techniques. The 3D coordinates are then converted into a set of geometrical relational features (GRFs) for dimensionality reduction and discrimination increase. For further dimensionality reduction, k-means clustering is applied to the GRFs to generate clustered feature vectors. These vectors are used to train CHMMs separately for different types of actions, based on the Baum-Welch re-estimation algorithm. For recognition of continuous actions that are concatenated from several distinct types of actions, a designed graphical model is used to systematically concatenate different separately trained CHMMs. The experimental results show the effective performance of our proposed system in both single and continuous action recognition problems.

• Journal of the Ergonomics Society of Korea
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• v.18 no.3
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• pp.153-169
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• 1999

The design of nuclear control room is advancing toward totally computer based human system interfaces (HSI). Computer based interfaces offer the opportunity to provide improved support of operator performance, but if not properly deployed, can introduce new challenges. This paper reviews the Westinghouse AP-600 Human Factors Verification and Validation Plan selected for HSI evaluation model of Korea next generation nuclear control rooms. The AP-600 HSI evaluation model addressed 15 evaluation issues considering major activity class of operator and task complexity factors. This paper also describes the test procedures experimenters should follow to evaluate the addressed issues.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.961-968
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• 2018

Recently, researches on automatic recognition of human activities have been actively carried out with the emergence of various intelligent systems. Since a large amount of visual data can be secured through Closed Circuit Television, it is required to recognize human behavior in a dynamic situation rather than a static situation. In this paper, we propose new intelligent human activity recognition model using the trajectory information extracted from the video sequence. The proposed model consists of three steps: segmentation and partitioning of trajectory step, feature extraction step, and behavioral learning step. First, the entire trajectory is fuzzy partitioned according to the motion characteristics, and then temporal features and spatial features are extracted. Using the extracted features, four pedestrian behaviors were modeled by decision tree learning algorithm and performance evaluation was performed. The experiments in this paper were conducted using Caviar data sets. Experimental results show that trajectory provides good activity recognition accuracy by extracting instantaneous property and distinctive regional property.