• Journal of the Ergonomics Society of Korea
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• v.22 no.4
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• pp.59-78
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• 2003

Most regression models of anthropometric variables use stature and/or weight as regressors; however, these 'flat' regression models result in large errors for anthropometric variables having low correlations with the regressors. To develop more accurate regression models for anthropometric variables, this study proposed a method to estimate anthropometric variables in a hierarchical manner based on the relationships among the variables and a process to develop and improve corresponding regression models. By applying the proposed approach, a hierarchical estimation structure was constructed for 59 anthropometric variables selected for the occupant package design of a passenger car and corresponding regression models were developed with the 1988 US Army anthropometric survey data. The hierarchical regression models were compared with the corresponding flat regression models in terms of accuracy. As results, the standard errors of the hierarchical regression models decreased by 28% (4.3mm) on average compared with those of the flat models.

• JSTS:Journal of Semiconductor Technology and Science
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• v.11 no.3
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• pp.135-145
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• 2011

Accurate process characterization and optimization are the first step for a successful advanced process control (APC), and they should be followed by continuous monitoring and control in order to run manufacturing processes most efficiently. In this paper, process characterization and recipe optimization methods with multiple outputs are presented in high density plasma-chemical vapor deposition (HDP-CVD) silicon dioxide deposition process. Five controllable process variables of Top $SiH_4$, Bottom $SiH_4$, $O_2$, Top RF Power, and Bottom RF Power, and two responses of interest, such as deposition rate and uniformity, are simultaneously considered employing both statistical response surface methodology (RSM) and neural networks (NNs) based genetic algorithm (GA). Statistically, two phases of experimental design was performed, and the established statistical models were optimized using performance index (PI). Artificial intelligently, NN process model with two outputs were established, and recipe synthesis was performed employing GA. Statistical RSM offers minimum numbers of experiment to build regression models and response surface models, but the analysis of the data need to satisfy underlying assumption and statistical data analysis capability. NN based-GA does not require any underlying assumption for data modeling; however, the selection of the input data for the model establishment is important for accurate model construction. Both statistical and artificial intelligent methods suggest competitive characterization and optimization results in HDP-CVD $SiO_2$ deposition process, and the NN based-GA method showed 26% uniformity improvement with 36% less $SiH_4$ gas usage yielding 20.8 ${\AA}/sec$ deposition rate.

• Korean Institute of Interior Design Journal
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• v.22 no.1
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• pp.105-114
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• 2013

This study investigated the application and the change of various architectural models by analyzing expression viewpoint media, which were applied to the visual information of digitalized 3D contemporary architectural models. The purpose of this study was to specify how modern architects have changed 3D architectural models to conceptual, logical, and formational visual information in the process of design. This study discovered a framework of analyses by theoretically investigating a relationship between expression media and expression change in the process of visualizing architectural models. Using the framework of analyses, this study analyzed how the expression viewpoints of architectural model information have been changed and applied. The transformation media of the visual information of digitalized 3D architectural models can be classified into conceptual, analytical, and formational information: 1) Contemporary architects used author-centered subjective viewpoints to express architectural concepts, which were generated in the process of their design. They selected a perspective viewpoint and a bird's eye view in order to present their architectural concepts and to depict them with one architectural model by expanding the visual scope of conceptual information. 2) Contemporary architects adopted observer-centered objective bird's eye view expression media to effectively present their architectural information to building owners and viewers. They used transformal media, which integrate architectural information into 3D and change it to different scales, in order to express their architecture logically. 3) Contemporary architects delivered model information about the generation and change of forms by expressing the image of a project from an author-centered viewpoint, instead of objectively defining formational information. They explained the generation principle of architectural forms via transformal media which develop and rotate an architectural model.

• Korean Journal of Construction Engineering and Management
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• v.14 no.1
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• pp.133-143
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• 2013

BIM can be utilized variously in construction management(CM) in the respect that it helps to manage comprehensively the construction information and make reliable decisions, but the adoption of BIM is insufficient in the CM area. The purpose of this study is to develop work process models and their guides in order to utilize BIM effectively in CM work at construction stage. This study defined BIM functions as 'BIM converting design', 'Model review', 'Data extraction', 'Automatic estimate', '4D simulation', 'Drawing creation', 'Engineering sector linkage analysis' through literature search, and generated CM works applicable to BIM by analyzing the CM work and process. This study developed BIM-based CM work process models by reconstructing the existing work process in connection with BIM function through an analysis on the relationship between BIM function and CM work, and reconstructing the role of each project participants. In order to improve the usefulness of the developed models, guides that described the BIM works of project participants were prepared through interviews and case studies. To validate the utilization of the models, a comparative analysis on the BIM process of precedent studies was also made and a survey was conducted on experts. This study can contribute to increasing the utilization of BIM in the CM area and can be helpful for CM companies to develop an in-house BIM guide. In the future, it will be necessary to make an assessment on the models from a business perspective through case applications and constantly update BIM-based CM work process model in consideration of the expansion of CM work due to the application of BIM.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3330-3344
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• 2023

This paper proposes an antenna performance prediction model in the autonomous driving radar manufacturing process. Our research work is based upon a challenge dataset, Driving Radar Manufacturing Process Dataset, and a typical AutoML machine learning workflow engine, Pycaret open-source Python library. Note that the dataset contains the total 70 data-items, out of which 54 used as input features and 16 used as output features, and the dataset is properly built into resolving the multi-output regression problem. During the data regression analysis and preprocessing phase, we identified several input features having similar correlations and so detached some of those input features, which may become a serious cause of the multicollinearity problem that affect the overall model performance. In the training phase, we train each of output-feature regression models by using the AutoML approach. Next, we selected the top 5 models showing the higher performances in the AutoML result reports and applied the ensemble method so as for the selected models' performances to be improved. In performing the experimental performance evaluation of the regression prediction model, we particularly used two metrics, MAE and RMSE, and the results of which were 0.6928 and 1.2065, respectively. Additionally, we carried out a series of experiments to verify the proposed model's performance by comparing with other existing models' performances. In conclusion, we enhance accuracy for safer autonomous vehicles, reduces manufacturing costs through AutoML-Pycaret and machine learning ensembled model, and prevents the production of faulty radar systems, conserving resources. Ultimately, the proposed model holds significant promise not only for antenna performance but also for improving manufacturing quality and advancing radar systems in autonomous vehicles.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1428-1431
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• 1997

This paper presents an efficient fault diagnosis methodology for lare chemical processes. The methodology is based on a two-tier strategy, When a falt occurs in a process, a top tier identifies the sector (process part or unit) that may contain the fault(s). Afterwards, a bottom tier or lower level evaluates the suspicious sector. The process modeling methodology based on functionality-behavior relations of process units, is proposed and utilized in the top-tier. This methodology models a target process as sequences of functions and variables and their relations. In the bottom tier, each sector has a dedicated diagostic module, which is tailored to the available information or models of the sector. For the sectors selected in the top-tier diagnosis, each diagnostic module is executed to identify the actual faults within the sector. Teh utility of the methodology is illustrated in the diagnosis of the CSTR with heat exchanger.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.39-45
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• 2003

Ghosh and Ramamoorthi (1996) studied the posterior consistency for survival models and showed that the posterior was consistent, when the prior on the distribution of survival times was the Dirichlet process prior. In this paper, we study the posterior consistency of survival models with neutral to the right process priors which include Dirichlet process priors. A set of sufficient conditions for the posterior consistency with neutral to the right process priors are given. Interestingly, not all the neutral to the right process priors have consistent posteriors, but most of the popular priors such as Dirichlet processes, beta processes and gamma processes have consistent posteriors. For extended beta processes, a necessary and sufficient condition for the consistency is also established.

• International Journal of Reliability and Applications
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• v.12 no.1
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• pp.49-60
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• 2011

The geometric process (GP) has been widely used for modeling failure and repair time sequences of repairable systems. The GP is mathematically tractable but restrictive in reliability applications since it actually assumes that the mean function of inter-failure times sequence asymptotically decreases to zero; and the mean function of successive repair times sequence asymptotically increases to infinity. This is generally unrealistic from an engineering perspective. This paper presents three extended GP models for modeling reliability deterioration and improvement (or growth) process. The extensions maintain the advantage of mathematical tractability of GP model. Their usefulness and appropriateness are illustrated with three real-world examples.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1997.10a
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• pp.47-53
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• 1997

Dynamic models have been developed for the coal gasification process by using a modular approach method. The complete unit is divided, for the convenience of the analysis, into several sections, viz. the coal feeding system, the gasifier, the gas cooler, the valves, the pumps, etc. The dynamic behaviour of each section is described in mathematical terms and each term is modulized into several submodels consisting of the complete process. To represent the behaviour of the fluid flow, the hydraulic network is proposed. Results for the more important system variables are presented and discussed. There dynamic models enable process and control engineers to quickly review a wide range of alternative operating and control strategies and help operators to easily understand the process dynamics and eventually can be applied to the design of commercial scale IGCC plants.

• Journal of Korean Society for Quality Management
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• v.40 no.3
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• pp.394-405
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• 2012

Purpose: In this study, we suggest the systematic and comprehensive model to develop PI(Performance Indicators) of the organization or the process. Methods: The model is developed theoretically by using SIPOC(Supplier, Input, Process, Output, Customer) approach which is a tool to analyze the process and is compared with existing models to develop PI or KPI(key performance indicators); financial indicators, BSC, IPOO(input, process, output, outcome), traditional QCD (quality, cost, delivery), and IOS(input, output system). Results: The model provides more systematic method to develop PI and more comprehensive set of PI pools for all kinds of hierarchical levels of process than any other models to develop PI or KPI. Conclusion: This model will provide useful tools for the managers and the organizations who wish to develop PI.