• Journal of Korean Institute of Industrial Engineers
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• v.25 no.1
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• pp.56-66
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• 1999

Shoulder joint is the most movable joint in human body with, at least, three degrees of freedom, since there are at least three bones and five joints involved in shoulder movement. Due to the complexity of the shoulder joint and the lack of appropriate anatomical data, modeling of the shoulder joint has been known to be extremely difficult. In many biomechanical models being used, shoulder joint is considered as a fixed point and it is also assumed that the shoulder joint does not noticeably move during the shoulder movement. However, such an assumption is not valid in real applications and causes inaccuracy, especially, in the area of workspace evaluation. The reachable area generated by a human becomes somewhat different from that of current models for those models fail to appropriately reflect the movement of shoulder joint's center of rotation. In this study, the location of the shoulder joint's center of rotation was obtained in relation to the location of humerus, on which a new model for reach envelope generation was developed for workspace evaluation. From the experiments conducted for three subjects, the initial location of the center of rotation was determined for each subject and subsequent changes in the instantaneous center of rotation were drawn as a function of flexion and abduction of the shoulder. Based on the regression analysis, the study suggested a new method for the generation of reach envelope. Comparisons were also made among real reach envelopes obtained from the experiment, the ones from the model, and the ones from the new method suggested in the study. As a result, the prediction errors incurred from the new method were significantly reduced when compared to the ones from the current approach.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.347-373
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• 2023

As the significance of ESG (Environmental, Social, and Governance) management amplifies in driving sustainable growth, this study delves into and compares ESG trends and interrelationships from both corporate and societal viewpoints. Employing a combination of Latent Dirichlet Allocation Topic Modeling (LDA) and Semantic Network Analysis, we analyzed sustainability reports alongside corresponding social media datasets. Additionally, an in-depth examination of social media content was conducted using Joint Sentiment Topic Modeling (JST), further enriched by Semantic Network Analysis (SNA). Complementing text mining analysis with the assistance of ChatGPT, this study identified 25 different ESG topics. It highlighted differences between companies aiming to avoid risks and build trust, and the general public's diverse concerns like investment options and working conditions. Key terms like 'greenwashing,' 'serious accidents,' and 'boycotts' show that many people doubt how companies handle ESG issues. The findings from this study set the foundation for a plan that serves key ESG groups, including businesses, government agencies, customers, and investors. This study also provide to guide the creation of more trustworthy and effective ESG strategies, helping to direct the discussion on ESG effectiveness.

• Composites Research
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• v.23 no.6
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• pp.19-25
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• 2010

This paper describes the optimum design of bolt locations for metal joint parts of railway bogie frame made of glass fiber/epoxy 4-harness satin woven laminate composite and PVC foam core. The optimum design analysis was done by sub-problem approximation method using Ansys Parameter Design Language(APDL). The sub-modeling method was introduced to conduct the detailed recalculation for the only target parts and reduce calculating time. The structural analysis for composite bogie frame was performed according to JIS E 4207. The results showed that the optimum design analysis using sub-modeling method was able to obtain faster and more precise results than that of the entire model by the control of mesh size for the target parts, and the maximum Von-Mises stress has been reduced in comparison with its original dimensions due to the optimum design of bolt locations.

• Structural Engineering and Mechanics
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• v.74 no.1
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• pp.55-67
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• 2020

The common practice to predict the characteristic structural load effects (LEs) in long reference periods is to employ the extreme value theory (EVT) for building limit distributions. However, most applications ignore that LEs are driven by multiple loading events and thus do not have the identical distribution, a prerequisite for EVT. In this study, we propose the composite extreme value modeling approach using clustering to (a) cluster initial blended samples into finite identical distributed subsamples using the finite mixture model, expectation-maximization algorithm, and the Akaike information criterion; (b) combine limit distributions of subsamples into a composite prediction equation using the generalized Pareto distribution based on a joint threshold. The proposed approach was validated both through numerical examples with known solutions and engineering applications of bridge traffic LEs on a long-span bridge. The results indicate that a joint threshold largely benefits the composite extreme value modeling, many appropriate tail approaching models can be used, and the equation form is simply the sum of the weighted models. In numerical examples, the proposed approach using clustering generated accurate extrema prediction of any reference period compared with the known solutions, whereas the common practice of employing EVT without clustering on the mixture data showed large deviations. Real-world bridge traffic LEs are driven by multi-events and present multipeak distributions, and the proposed approach is more capable of capturing the tendency of tailed LEs than the conventional approach. The proposed approach is expected to have wide applications to general problems such as samples that are driven by multiple events and that do not have the identical distribution.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.32-41
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• 2017

Accidents on offshore oil and gas platforms (OOGPs) usually cause serious fatalities and financial losses considering demanding environment platforms locate and complex topsides structure platforms own. Evacuation planning on platforms is usually challenging. The computational tool is a good choice to plan evacuation by emergency simulation. However, the complex structure of platforms and varied evacuation behaviors usually weaken the advantages of computational simulation. Therefore, this study developed a simulation model for OOGPs to evaluate different evacuation plans to improve evacuation performance by integrating building information modeling (BIM) and agent-based model (ABM). The developed model consists of four parts: evacuation model input, simulation environment modeling, agent definition, and simulation and comparison. Necessary platform information is extracted from BIM and then used to model simulation environment by integrating matrix model and network model. During agent definition, in addition to basic characteristics, environment sensing and dynamic escape path planning functions are also developed to improve simulation performance. An example OOGP BIM topsides with different emergent scenarios is used to illustrate the developed model. The results showed that the developed model can well simulate evacuation on OOGPs and improve evacuation performance. The developed model was also suggested to be applied to other industries such as the architecture, engineering, and construction industry.

• Journal of the Korean Statistical Society
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• v.35 no.4
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• pp.453-458
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• 2006

It is well known fact for the iid data that the limiting standard errors of sample autocorrelations are all unity for all time lags and they are asymptotically independent for different lags (Brockwell and Davis, 1991). It is also usual practice in time series modeling that this fact continues to be valid for white noise series which is a sequence of uncorrelated random variables. This paper contradicts this usual practice for white noise. We consider a sequence of martingale differences which belongs to white noise time series and derive exact joint asymptotic distributions of sample autocorrelations. Some implications of the result are illustrated for conditionally heteroscedastic time series.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.12
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• pp.3073-3082
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• 1993

A magnetically suspended robot joint is developed, which is free of dust and oil generation. Two radial bearings consisting of cone-shaped magnet cores control the rotor motion in the axial and radial directions. A linearized dynamic model is developed for active control of the magnetic bearing system. The control algorithm is constructed such that the axial displacement of the joint is controlled by radial control current to the pairs of facing radial bearings. The stability and control performance is tested through numerical simulation based on the nonlinear model. Experiments are also performed to verify the theoretical development.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.666-671
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• 1993

A new robust control law is proposed for uncertain rigid robots and two composite robust control laws for flexible-joint manipulators which contain uncertainties. The uncertainty, is nonlinear and (possibly fast) time-varying. Therefore, the uncertain factors such as imperfect modeling, function, payload change, and external disturbances are all addressed. Based only on the possible bound of the uncertainty, a robust controller is constructed for the rigid counterpart of the flexible-joint robot Some feedback control terms are then added to the robust control law to stabilize the elastic vibrations at the joints. To show that the proposed composite robust control laws are indeed applicable to flexible-joint robots, a singular perturbation approach and the stability study based on Lyapunov function are proposed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.12
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• pp.2110-2117
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• 2003

A physics-based material removal model in various scales is described and a feature scale simulation for a chemical mechanical polishing (CMP) process is performed in this work. Three different scales are considered in this model, i.e., abrasive particle scale, asperity scale and wafer scale. The abrasive particle and the asperity scales are combined together and then homogenized to result in force balance conditions to be satisfied in the wafer scale using an extended Greenwood-Williamson and Whitehouse-Archard statistical model that takes into consideration the joint distribution of asperity heights and asperity tip radii. The final computation is made to evaluate the material removal rate in wafer scale and a computer simulation is performed for detailed surface profile variations on a representative feature. The results show the dependence of the material removal rate on the joint distribution, applied external pressure, relative velocity, and other operating conditions and design parameters.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.959-964
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• 1992

This study treats the method for kinematic modeling of the biped walking robot, for synthesizing various gait trajectories, and for calculating adequate values of the joint torque inside the stable region. To synthesize various and anthropomorphic walking easily, the gait trajectory is specified by a set of ten walking prameters, and the trunk motion equation is derived by the zero moment point and the gait trajectory. By distributing ground reaction force and moment reduced at the zero moment point to the both feet, the joint torque equation can be derived readily, and according to this equation, the joint torque to stable walking can be computed.