• Journal of Information Technology Applications and Management
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• v.11 no.1
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• pp.117-135
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• 2004

Since human decision making behavior is likely to follow nonlinear strategy, it is conjectured that the human decision making behavior can be modeled better by nonlinear models than by linear models. All that linear models can do is to approximate rather than model the decision behavior. This study attempts to test this conjecture by analyzing human decision making behavior and combining the results of the analysis with predictive performance of both linear models and nonlinear models. In this way, this study can examine the relationship between the predictive performance of models and the existence of valid nonlinear strategy in decision making behavior. This study finds that the existence of nonlinear strategy in decision making behavior is highly correlated with the validity of the decision (or the human experts). The second finding concerns the significant correlations between the model performance and the existence of valid nonlinear strategy which is detected by Lens Model. The third finding is that as stronger the valid nonlinear strategy becomes, the better nonlinear models predict significantly than linear models. The results of this study bring an important concept, validity of nonlinear strategy, to modeling human experts. The inclusion of the concept indicates that the prior analysis of human judgement may lead to the selection of proper modeling algorithm. In addition, lens Model Analysis is proved to be useful in examining the valid nonlinearity in human decision behavior.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1225-1227
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• 2004

The robotic shoe testing system that mechanically simulates human motion was proposed to overcome the problems associated with human subject tests. The objective of this study is to predict new motion trajectory for robot that will produce similar force and moment of particular human motion. In order to solve this problem, it is imperative to understand the dynamics of robot for shoe testing. The methodology using parameter estimation technique was proposed for this problem. Since the dynamics of robot is certainly different from that of human, it is necessary to adapt/modify the robot's trajectory for future analysis, which is currently under investigation.

• 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 Korea Safety Management & Science
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• v.21 no.4
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• pp.67-74
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• 2019

Visual inspection is regarded as one of the critical activities for quality control in a manufacturing company. it is thus important to improve the performance of detecting a defective part or product. There are three probable working modes for visual inspection: fully automatic (by automatic machines), fully manual (by human operators), and semi-automatic (by collaboration between human operators and automatic machines). Most of the current studies on visual inspection have been focused on the improvement of automatic detection performance by developing a better automatic machine using computer vision technologies. However, there are still a range of situations where human operators should conduct visual inspection with/without automatic machines. In this situation, human operators'performance of visual inspection is significant to the successful quality control. However, visual inspection of components assembled into a mobile camera module belongs to those situations. This study aims to investigate human performance issues in visual inspection of the components, paying more attention to human errors. For this, Abstraction Hierarchy-based work domain modeling method was applied to examine a range of direct or indirect factors related to human errors and their relationships in the visual inspection of the components. Although this study was conducted in the context of manufacturing mobile camera modules, the proposed method would be easily generalized into other industries.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.2
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• pp.85-93
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• 2009

GOMS model is a cognitive modeling method of human performance based on Goal, Operators, Methods, Selection rules. GOMS model was originally designed for desktop environment so that it is difficult for GOMS model to be implemented into the mobile environment. In addition, GOMS model would be inaccurate because the original GOMS model was based on serial processing, excluding one of most important human information processing characteristics, parallel processing. Therefore this study was designed to propose a modified GOMS model including mobile computing and parallel processing. In order to encompass mobile environment, an operator of 'look for' was divided into 'visual move to' and 'recognize' whereas 'point to' and 'click' were combined into 'tab.' The results showed that newly introduced operators were necessary to estimate more accurate mobile computing behaviors. In conclusion, modified-GOMS model could predict human performance more accurately than the original GOMS model in the mobile computing environment.

• Korean Journal of Computational Design and Engineering
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• v.18 no.3
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• pp.155-166
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• 2013

We present recent human-vehicle interaction (HVI) research conducted in the area of defense and military application. Research topics discussed in this paper include: training simulation for overland navigation tasks; expertise effects in overland navigation performance and scan patterns; pilot's perception and confidence on an overland navigation task; effects of UAV (Unmanned Aerial Vehicle) supervisory control on F-18 formation flight performance in a simulator environment; autonomy balancing in a manned-unmanned teaming (MUT) swarm attack, enabling visual detection of IED (Improvised Explosive Device) indicators through Perceptual Learning Assessment and Training; usability test on DaViTo (Data Visualization Tool); and modeling peripheral vision for moving target search and detection. Diverse and leading HVI study in the defense domain suggests future research direction in other HVI emerging areas such as automotive industry and aviation domain.

• Korean Journal of Labor Studies
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• v.19 no.1
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• pp.65-104
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• 2013

This study aims to examine the intermediary roles of employee performance between high performance work system (HPWS) and its operational performance on the resource based view. Taking into account the unit of analysis, this study used a hierarchical linear modeling analysis in order to test rigorously the association between HPWS at the organisational level and employee performance at the individual level. For this empirical test, Human Capital Corporate Panel (HCCP) data including 316 firms and 7,872 respondents (including 923 team leaders) were used. To meet the unit of analysis and test the mediation effect, data at the individual and team level were aggregated into the organisational level. The empirical results show that HPWS have a positive impact on operational performance as well as employee performance such as job satisfaction, organisational commitment and organisational trust. Regarding the mediation effect, job satisfaction and organisational trust mediate between HPWS and operational performance. Theoretical implications are discussed in conclusion.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.593-602
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• 2020

The purpose of this study is to examine and analyze the effect of human capital supply chain on the firm performance mediated by innovation culture and innovation process on small- and medium-sized construction enterprises (SMEs) in Indonesia. A survey has been distributed to all construction SMEs that have direct involvement in construction work (contractors and subcontractors). The construction SMEs including medium- and small-scale construction services in three Provinces, namely, the special region of Yogyakarta, East Java, and Central Java. Through purposive sampling technique, primary data is collected by giving a questionnaire to the owner/manager of construction SMEs. The target sample in this study was 200 respondents who have been operating for a minimum of two years. 154 valid questionnaires could be processed. Data analysis uses structural equation modeling with AMOS 24. The results of the study conclude that there is a positive effect on human capital supply chain on firm performance mediated by innovation culture and innovation process, while innovation culture does not affect firm performance. In sum, the innovation culture mediates the relationship between human capital supply chain and firm performance, and the innovation process mediates the relationship between human capital supply chain and firm 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.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.3
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• pp.51-57
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• 2007

Without human dynamics effects, the manually operated target tracking system has poor performance or instability in real environments. The tracking system is invalid when a human is added to the control loop as a real time delay, because input signals are generated by human operator to reduce the errors between target and gun. In this paper, we consider the human operator as a part of controller and modeling the human operator as a first-order model to generate the intentional force. But it is known that human modeling is not easy because of disturbance or noise of the vehicle while moving for the target. We performed a variety of experiments with real plant to identify the model's parameters and verify the proposed operator model's efficiency.