• Journal of Distribution Science
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• v.22 no.3
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• pp.105-112
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• 2024

Purpose: This study analyzed the relationship between corporate capacity and management performance in the Korean distribution industry during the COVID-19 pandemic. Research design, data and methodology: The data for this study used the 2021 KOTRA GCL Test Data, and multiple regression analysis was performed using SPSS 26. As corporate competency, human capital and related capital of intellectual capital theory were utilized, and the global network level of social network theory was also utilized. As an additional analysis, corporate characteristics factors were used. Results: First, the level of global mindset of human capital acted as a positive factor in management performance, and the level of professional manpower did not achieve significant results. Second, related capital acted as a positive factor in corporate performance. Third, from the perspective of social network theory, the global network level of companies acted as a positive factor in management performance. Finally, the relationship between corporate characteristics and management performance was marginally significant. Conclusions: In order to improve the business performance of a company in a market shock such as the COVID-19 pandemic, it is required to strengthen the level of network construction with customers and increase the level of intellectual capital that a company has.

• Journal of Pharmacopuncture
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• v.22 no.3
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• pp.166-170
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• 2019

Objectives: Attentional and memory functions are important aspects of neural plasticity that, theoretically, should be amenable to pharmacopuncture treatments. A previous study from our laboratory suggested that quantitative electroencephalographic (qEEG) measurements of theta/beta ratio (TBR), an index of attentional control, may be indicative of academic performance in a first-semester medical school course. The present study expands our prior report by extracting and analyzing data on frontal theta and beta asymmetries. We test the hypothesis that the amount of frontal theta and beta asymmetries (fTA, fBA), are correlated with TBR and academic performance, thereby providing novel targets for pharmacopuncture treatments to improve cognitive performance. Methods: Ten healthy male volunteers were subjected to 5-10 min of qEEG measurements under eyes-closed conditions. The qEEG measurements were performed 3 days before each of first two block examinations in anatomy-physiology, separated by five weeks. Amplitudes of the theta and beta waveforms, expressed in ${\mu}V$, were used to compute TBR, fTA and fBA. Significance of changes in theta and beta EEG wave amplitude was assessed by ANOVA with post-hoc t-testing. Correlations between TBR, fTA, fBA and the raw examination scores were evaluated by Pearson's product-moment coefficients and linear regression analysis. Results: fTA and fBA were found to be negatively correlated with TBR (P<0.03, P<0.05, respectively) and were positively correlated with the second examination score (P<0.03, P=0.1, respectively). Conclusion: Smaller fTA and fBA were associated with lower academic performance in the second of two first-semester medical school anatomy-physiology block examination. Future studies should determine whether these qEEG metrics are useful for monitoring changes associated with the brain's cognitive adaptations to academic challenges, for predicting academic performance and for targeting phamacopuncture treatments to improve cognitive performance.

• The Journal of the Korea Contents Association
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• v.19 no.6
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• pp.311-324
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• 2019

The purpose of this study is to analyze the mediating effects of employee outcomes on the relationship between quality of employment and organizational performance and to understand the specific mechanism of the impact of employment quality on organizational performance. Although there has been a widespread debate on the merits of the quality of employment, there have been few studies dealing with how the quality of employment contributes to organizational performance. For the empirical analysis, we analyzed the mediating effect of employee outcomes on the relationship between employment quality and employee outcomes (human capital competence and collective organizational commitment) and employment quality and organizational performance for 501 Korean companies. The results showed that the higher the quality of employment, the higher the employee's human capital competence and collective organizational commitment, and the employee outcomes mediate the relationship between the quality of employment and organizational performance.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.393-404
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• 2022

This study attempted to examine the effect of education and training on organizational performance based on HCCP research through the systematic review of previous studies. For this, 29 papers used HCCP data were selected and analyzed, and the research results are as follows. First, the research results showed that education and training had a positive effect on non-financial performance such as organizational commitment and job satisfaction, and financial performance such as sales and operating profit. Second, in order for education and training to affect organizational performance, job satisfaction, organizational culture, and education transfer were found to be important factors. Third, for effective transfer of education and training, it is necessary to establish a system that can be applied to the field after education and training, finally, it suggested the need for research to be conducted to reveal the practical effectiveness of education and training by measuring the degree to which education and training contributed to financial performance more closely.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.1
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• pp.109-120
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• 2004

In large scale complex system such as a nuclear power plant, it is important to select guidelines and/or checklist to evaluate the system performance, especially human performance for visual information while the number of evaluation items of the guidelines and checklist is voluminous. This paper presents the methodology and experiment for the relative weights or priority selection of evaluation items on the advanced information display of main control room in a nuclear power plant. To summarize this, 1) many human factors guidelines of Visual Display Terminal(VDT) displays are collected, 2) the collected guidelines are integrated and unified based on some rules in a way to avoid confusion or errors about work performances of operator groups, 3) using the unified guidelines, the more important items are defined when the advanced information indexes are applied by using the Analytic Hierarchy Process(AHP). For employing the AHP, the decisions and response of many human factors evaluation specialists in this field are collected to get the priority order of the evaluation items of VDT. The result of this paper will be applied for the evaluation of the usability of next generation of nuclear power plant which is focused on the visual information display on VDT.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.3
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• pp.202-208
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• 2011

Recently the technologies that control the computer system through human computer interaction(HCI) have been widely studied. Their applications usually involve the methods that locate user's positions via face detection and recognize user's gestures, but face detection performance is not good enough. In case that the applications do not locate user's position stably, user interface performance, such as gesture recognition, is significantly decreased. In this paper we propose a new stable face detection algorithm using skin color detection and cumulative distribution of face detection results, whose effectiveness was verified by experiments. The propsed algorithm can be applicable in the area of human tracking that uses correspondence matrix analysis.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.29-40
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• 2012

A challenging research issue that has been one of growing importance to those working in human-computer interaction are to endow a machine with an emotional intelligence. Thus, emotion recognition technology plays an important role in the research area of human-computer interaction, and it allows a more natural and more human-like communication between human and computer. In this paper, we propose the multimodal emotion recognition system using face and speech to improve recognition performance. The distance measurement of the face-based emotion recognition is calculated by 2D-PCA of MCS-LBP image and nearest neighbor classifier, and also the likelihood measurement is obtained by Gaussian mixture model algorithm based on pitch and mel-frequency cepstral coefficient features in speech-based emotion recognition. The individual matching scores obtained from face and speech are combined using a weighted-summation operation, and the fused-score is utilized to classify the human emotion. Through experimental results, the proposed method exhibits improved recognition accuracy of about 11.25% to 19.75% when compared to the most uni-modal approach. From these results, we confirmed that the proposed approach achieved a significant performance improvement and the proposed method was very effective.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1264-1274
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• 2015

Human action recognition received many interest in the computer vision community. Most of the existing methods focus on either construct robust descriptor from the temporal domain, or computational method to exploit the discriminative power of the descriptor. In this paper we explore the idea of using local action attributes to form an action descriptor, where an action is no longer characterized with the motion changes in the temporal domain but the local semantic description of the action. We propose an novel framework where introduces local action attributes to represent an action for the final human action categorization. The local action attributes are defined for each body part which are independent from the global action. The resulting attribute descriptor is used to jointly model human action to achieve robust performance. In addition, we conduct some study on the impact of using body local and global low-level feature for the aforementioned attributes. Experiments on the KTH dataset and the MV-TJU dataset show that our local action attribute based descriptor improve action recognition performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.8
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• pp.5263-5268
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• 2014

This paper suggests a fast human detection algorithm that can be applied to a high-resolution CCTV camera. Human detection algorithms, which used a HOG detector show high performance in the region of image processing. On the other hand, it is difficult to apply to real-time high resolution imaging because of its slow processing speed in the extracting figures of HOG. To resolve this problems, we suggest how to detect humans into two stages. First, candidates of a human region are found using background subtraction, and humans and non-humans are distinguished using a HOG detector only. This process increases the detection speed by approximately 2.5 times without any degradation in performance.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.2
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• pp.21-30
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• 2007

A practical method to design the input shaping which generates control command is proposed in this paper, We suggest an experimental technique considering human operator's target tracking error to improve aiming accuracy which significantly affects hit probability. It is known that stabilization performance is one of the most important factors for ground combat vehicle system. In particular, stabilization error of the manual target tracking system mounted on moving vehicle directly affects hit probability. To reduce this error, we applied input command shaping method using preprocessing filtering and functional curve fitting. First of all, we construct the human operator model to consider effects of human operator on our system. Input shaping curve is divided into several regions to get rid of the above problems and to improve the system performance. At example design part, we chose three steps of functional command curve and determine the parameters of the function by the proposed design method. In order to verify the proposed design method, we carried out the experiments with real plant of a fighting vehicle.