• ETRI Journal
• /
• v.40 no.5
• /
• pp.653-663
• /
• 2018

Patients with spinal cord injuries cannot move their limbs using their intact muscles. A suitable controller can be used to move their arms by employing the functional electrical stimulation method. In this article, a fuzzy exponential sliding-mode controller is designed to move a musculoskeletal human arm model to track an optimal trajectory in the sagittal plane. This optimal arm trajectory is obtained by developing a policy for the central nervous system. In order to specify the optimal trajectory between two points, two dynamic and static optimal criteria are applied simultaneously. The first dynamic objective function is defined to minimize the joint torques, and the second static optimization is offered to minimize the muscle forces at each moment. In addition, fuzzy logic is used to tune the sliding-surface parameter to enable an appropriate tracking performance. Simulation results are evaluated and compared with experimental data for upward and downward movements of the human arm.

• Journal of the Ergonomics Society of Korea
• /
• v.12 no.1
• /
• pp.17-24
• /
• 1993

Today, rapid development and timeliness of introducing a new product be- comes a more influencing factor of determing its competitive power due to a shortened product cycle, while rapid improvement of manufacturing technology makes product design and manufacturing fuse together. This implies that prod- uct usability evaluation and improvement starts right from its design phase, resulting in less development time and cost. To make this possible, proper as- sessment of human reach is one of essential functions for ergonomic product us- ability evaluation, specifically in the platform of computer-aided ergonomic evaluation models or any CAD system with a built-in man model. In this study, an analytic reach prediction algorithm ensuring the posture that human naturally takes, is presented by employing the methods developed for robot kinematics. Among robot kinematic methods for solving the multi-link system, the resolved motion method was found to be effective to solve human reach as a redundant manipulator model. Also, the joint range availability was used as a performance fonction to guarantee human naturalness. The result is expected to be directly applicable to product usability evaluations.

• International Journal of Advanced Culture Technology
• /
• v.8 no.3
• /
• pp.216-222
• /
• 2020

The purpose of this study was to predict the performance of female weightlifters using time series analysis. Based on this purpose, a time series analysis was used to calculate the performance prediction model for women(58kg) among the domestic women weightlifters who participated in the Olympics. As a result of creating time series data based on 10 years of record and then evaluating the sequential charts of each athlete group, the female athletes' records did not show any seasonality or difference. In addition, after examining the independence of the data through the creation of a time series model, it was shown that the models produced conformed to the criteria for compliance and that there was no difference in the data, but there was a trend. Accordingly, Holt linear trend analysis of the exponential smoothing model was applied. As a result of deriving the prediction model of the athletes through this process, it was found that the women (58kg) who participated in the Olympics continued to improve within the range of 166.11kg to 184.1kg.

• Proceedings of the Korea Society for Simulation Conference
• /
• 1992.09a
• /
• pp.161-167
• /
• 1992

The spcaker will briefly summarized the current state of the art in commericial simulation tools as limited by soft ware and hardware technology. He will then discuss how recent and near-future advances in software and hardware tenilogy can be applied to the benefit of simulationists. Specifically, the following topics will be ciscussed : Simulation Languages vs Simulations ; Computer hardware platforms ; Performance liminting factors ; Performance assisting techniques ; Software architectures ; Human factors and model interaction.

• International conference on construction engineering and project management
• /
• 2013.01a
• /
• pp.359-366
• /
• 2013

Although many research efforts have been conducted to address the effect of crew members' work skills (e.g., technical and planning skills) on work performance (e.g., work duration and quality) in construction projects, the relationship between skill and performance has generated a great deal of controversy in the field of management (Inkpen and Crossan 1995). This controversy can lead to under- or over-estimations of the overall project schedule, and can make it difficult for project managers to implement appropriate managerial policies for enhancing project performance. To address this issue, the following aspects need to be considered: (a) work performances are determined not only by individual-level work skill but also by the group-level work skill affected by work team members, each member's role, and any working behavior pattern; (b) work planning has significant effects on to what extent work skill enhances performance; and (c) different types of activities in construction require different types of work, skill, and team composition. This research, therefore, develops a system dynamics (SD) model to analyze the effects of both individual-and group-level (i.e., multi-level) skill on performances by utilizing the advantages of SD in capturing a feedback process and state changes, especially in human factors (e.g., attitude, ability, and behavior). The model incorporates: (a) a multi-level skill evolution and relevant behavior development mechanism within a work group; (b) the interaction among work planning, a crew's skill-learning, skill manifestation, and performances; and (c) the different work characteristics of each activity. This model can be utilized to implement appropriate work planning (e.g., work scope and work schedule) and crew management policies (e.g., work team composition and decision of each worker's role) with an awareness of crew's skill and work performance. Understanding the different characteristics of each activity can also support project managers in applying strategic work planning and crew management for a corresponding activity, which may enhance each activity's performance, as well as the overall project performance.

• Journal of Korean Institute of Industrial Engineers
• /
• v.41 no.4
• /
• pp.389-395
• /
• 2015

According to much research on cognitive science, the impact of the scene-context on human visual search in real-world images could be as important as the saliency. Therefore, this study proposed a method of Adaptive Control of Thought-Rational (ACT-R) modeling of visual search in real-world images, based on saliency and scene-context. The modeling method was developed by using the utility system of ACT-R to describe influences of saliency and scene-context in real-world images. Then, the validation of the model was performed, by comparing the data of the model and eye-tracking data from experiments in simple task in which subjects search some targets in indoor bedroom images. Results show that model data was quite well fit with eye-tracking data. In conclusion, the method of modeling human visual search proposed in this study should be used, in order to provide an accurate model of human performance in visual search tasks in real-world images.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.4
• /
• pp.131-143
• /
• 2014

We propose a no-reference perceptual fog density and visibility prediction model in a single foggy scene based on natural scene statistics (NSS) and perceptual "fog aware" statistical features. Unlike previous studies, the proposed model predicts fog density without multiple foggy images, without salient objects in a scene including lane markings or traffic signs, without supplementary geographical information using an onboard camera, and without training on human-rated judgments. The proposed fog density and visibility predictor makes use of only measurable deviations from statistical regularities observed in natural foggy and fog-free images. Perceptual "fog aware" statistical features are derived from a corpus of natural foggy and fog-free images by using a spatial NSS model and observed fog characteristics including low contrast, faint color, and shifted luminance. The proposed model not only predicts perceptual fog density for the entire image but also provides local fog density for each patch size. To evaluate the performance of the proposed model against human judgments regarding fog visibility, we executed a human subjective study using a variety of 100 foggy images. Results show that the predicted fog density of the model correlates well with human judgments. The proposed model is a new fog density assessment work based on human visual perceptions. We hope that the proposed model will provide fertile ground for future research not only to enhance the visibility of foggy scenes but also to accurately evaluate the performance of defog algorithms.

• Journal of Technology Innovation
• /
• v.15 no.2
• /
• pp.177-209
• /
• 2007

This work firstly aims to analyse the balance between tangibles and intangibles as well as among human capital, structural capital and relational capital of evaluation indicators for the research institutes in science and technology sector conducted in 2006, by adopting intellectual capital model. The research question of this work comes from that while the R&D activity can produce both tangibles and intangibles, there have no been methodologies to relevantly measure and rationally judge these, in particular, intangible performance. The result shows that the institute evaluation system in 2006 had given more weight on tangibles and structural capital than intangibles and other intellectual capitals such as human capital and relational capital, in comparison to the past evaluation system, even though, in principle, the current evaluation system has to deal with the intangible research performances as well as tangible ones in economic, social and cultural perspective. Finally, based on these analysis, I will try to suggest some policy directions for overcoming the deficits of indicators in institute evaluation system.

• Nuclear Engineering and Technology
• /
• v.45 no.2
• /
• pp.151-164
• /
• 2013

A key input for the assessment of Human Error Probabilities (HEPs) with Human Reliability Analysis (HRA) methods is the evaluation of the factors influencing the human performance (often referred to as Performance Shaping Factors, PSFs). In general, the definition of these factors and the supporting guidance are such that their evaluation involves significant subjectivity. This affects the repeatability of HRA results as well as the collection of HRA data for model construction and verification. In this context, the present paper considers the TAsk COMplexity (TACOM) measure, developed by one of the authors to quantify the complexity of procedure-guided tasks (by the operating crew of nuclear power plants in emergency situations), and evaluates its use to represent (objectively and quantitatively) task complexity issues relevant to HRA methods. In particular, TACOM scores are calculated for five Human Failure Events (HFEs) for which empirical evidence on the HEPs (albeit with large uncertainty) and influencing factors are available - from the International HRA Empirical Study. The empirical evaluation has shown promising results. The TACOM score increases as the empirical HEP of the selected HFEs increases. Except for one case, TACOM scores are well distinguished if related to different difficulty categories (e.g., "easy" vs. "somewhat difficult"), while values corresponding to tasks within the same category are very close. Despite some important limitations related to the small number of HFEs investigated and the large uncertainty in their HEPs, this paper presents one of few attempts to empirically study the effect of a performance shaping factor on the human error probability. This type of study is important to enhance the empirical basis of HRA methods, to make sure that 1) the definitions of the PSFs cover the influences important for HRA (i.e., influencing the error probability), and 2) the quantitative relationships among PSFs and error probability are adequately represented.

• Journal of the Korean Society of Safety
• /
• v.13 no.1
• /
• pp.112-118
• /
• 1998

Human errors performed during the operations have a dominant portion of the accidents. But the systematic human error evaluation methodology universally accepted is not developed yet. One of the difficulties in performing human reliability analysis is to evaluate the performance shaping factors which represent the characteristics and the circumstances in the discriminate manner. For assessing a specific human action more exactly, it is necessary to consider all of the PSFs at the same time which make an effect on the human action. In this paper, dynamic influence diagrams are introduced to model simultaneously their effects on the specific human action. And the human actions and their subsequent PSFs are categorized and classified as the complementary works. A new human error evaluation methodology using influence diagrams is developed. This methodology involves the categorization of PSFs and the PSFs quantification. The applied analysis results for the example task are shown for representative purposes. It is shown that this approach is very flexible in that it can be applied to any kind of actions.