• Journal of the Korean Geotechnical Society
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• v.32 no.11
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• pp.51-60
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• 2016

In determining a shear wave velocity (Vs) profile model based on field tests for dams, the uncertainties always exist. These uncertainties are caused by spatial variations of material properties in each dam and between dams and should be considered in determining Vs profile model for dams. In this paper, these uncertainties are evaluated and Vs profile model for core zone of fill dam in Korea is proposed using the shear wave velocity profiles determined in seven fill dams. The proposed Vs profile model is compared with Kim's model and Sawada-Takahashi model widely used for evaluation of Vs profile of core zone of fill dam.

• The Journal of Information Systems
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• v.31 no.3
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• pp.1-18
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• 2022

Purpose The purpose of this study is to analize a psychological and behavioral mechanism for using profile picture management in digital service such as social network service. Profile picture management falls under metadata management and is performed only by those who want it. This means that it, is one of the typical makeup-type digital shadow works (DSWs) which have not been studied yet. Design/methodology/approach This study adopts ground theory method(GTM) as research methodology. GTM, which is one of qualitative methodologies, is for developing theories while most survey based methodologies, which are well adopted in much research for information systems, are for validation of theories. By interviewing ten users, the data are collected and analyzed by open coding, axis coding with paradigm model, and selective coding. Findings In result, 39 codes are found and classified into 29 sub classes and 15 classes. These 15 classes are organized by paradigm model which derives core code of profile picture management as 'voluntary management tasks to experience small pleasures with intermittent attention'. Finally, based on the paradigm model and the core code, the story line, which can explain profile picture management, is suggested.

• International Journal of Control, Automation, and Systems
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• v.2 no.2
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• pp.256-262
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• 2004

Conventionally, profile non-uniformity has been characterized by relying on approximated profile with angle or anisotropy. In this study, a new non-uniformity model for etch profile is presented by applying a discrete wavelet to the image obtained from a scanning electron microscopy (SEM). Prediction models for wavelet-transformed data are then constructed using a back-propagation neural network. The proposed method was applied to the data collected from the etching of tungsten material. Additionally, 7 experiments were conducted to obtain test data. Model performance was evaluated in terms of the average prediction accuracy (APA) and the best prediction accuracy (BPA). To take into account randomness in initial weights, two hundred models were generated for a given set of training factors. Behaviors of the APA and BPA were investigated as a function of training factors, including training tolerance, hidden neuron, initial weight distribution, and two slopes for bipolar sig-moid and linear function. For all variations in training factors, the APA was not consistent with the BPA. The prediction accuracy was optimized using three approaches, the best model based approach, the average model based approach and the combined model based approach. Despite the largest APA of the first approach, its BPA was smallest compared to the other two approaches.

• Journal of Internet Computing and Services
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• v.20 no.2
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• pp.69-76
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• 2019

Recent Enterprise System has component driven real-time distributed architecture (RDA) and this kind of architecture should performed with satisfying strict constraints on life cycle of object and response time such as synchronization, transaction and so on. Microsoft's .NET platform supports RDA and is able to implement services including before mentioned time restriction and security service by only specifying attribute code and maximizing advantages of OMG's Model Driven Architecture (MDA). In this study, a method to automatically generate an extended model of essential elements in an enterprise-system-based RDA as well as the platform specific model (PSM) for Microsoft's .NET platform are proposed. To realize these ideas, the functionalities that should be considered in enterprise system development are specified and defined in a meta-model and an extended UML profile. In addition, after defining the UML profile for .NET specification, these are developed and applied as plug-ins of the open source MDA tool, and extended models are automatically generated using this tool. Accordingly, by using the proposed specification technology, the profile and tools can easily and quickly generate a reusable extended model even without detailed coding-level information about the functionalities considered in the .NET platform and RDA.

• Transactions of Materials Processing
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• v.21 no.7
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• pp.426-431
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• 2012

The work roll of a Sendzimir mill has a small diameter in comparison to its length, so it is easily deformed by the rolling pressure. It also has a complex back up roll system, so it is difficult to analyze the roll deformation. For this reason in Part I we have developed a model which predicts the radial displacement of the roll. In this paper, we apply the model to a Sendzimir mill and propose a new model for the prediction of the deformed roll profile in a Sendzimir mill. The prediction accuracy of the new model is demonstrated through comparison of the predictions from the FE model.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.96-98
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• 2006

A new ex-situ model to diagnose a plasma processing equipment was presented. The model was constructed by combining wavelet, scanning electron microscope, ex-situ measurement of etching profile, and neural network. The diagnosis technique was applied to a tungsten etching process, conducted in a $SF_6$ helicon plasma. The wavelet was used to characterize detailed variations of plasma-etched surface. The diagnosis model was constructed with the vertical wavelet component. For comparison, a conventional model was built by using the estimated profile data. Compared to the conventional model, the wavelet-based model, demonstrated a much improved diagnosis.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.488-491
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• 2005

Abrasive Jet Micromachining (AJM) is a process that uses high pressure air with micron-sized particles to erode a substrate. It has been considered as the most economic and appropriate technique to pattern glass surfaces for the flat panel applications. To accelerate the industrialization of AJM, it is necessary to understand the erosion mechanisms thoroughly. Thus, this paper introduces a new method to model the erosion mechanism in AJM. The model is developed by using the concept of the accumulation of the microdeformation caused by each particle. And this paper proposes the model added the effects of second impact. The developed model is used to simulate the erosion profile, and is compared with the model considered only first impact. It can be concluded that the proposed model predicts the erosion profile more accurately.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.2
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• pp.209-216
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• 1992

Deafs train articulation by observing mouth of a tutor, sensing tactually the motions of the vocal organs, or using speech training aids. Present speech training aids for deafs can measure only single speech parameter, or display only frequency spectra in histogram of pseudo-color. In this study, a speech training aids that can display subject's articulation in the form of a cross section of the vocal organs and other speech parameters together in a single system is to be developed and this system makes a subject know where to correct. For our objective, first, speech production mechanism is assumed to be AR model in order to estimate articulatory motions of the vocal organs from speech signal. Next, a vocal tract profile model using LP analysis is made up. And using this model, articulatory motions for Korean vowels are estimated and displayed in the vocal tract profile graphics.

• Journal of Korea Multimedia Society
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• v.20 no.11
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• pp.1720-1728
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• 2017

Active shape model is widely used in the field of image processing especially on arbitrary meaningful shape extraction from single gray level image. Cootes et. al. showed efficient detection of variable shape from image by using covariance and mean shape from learning. There are two stages of learning and testing. Hahn applied enhanced shape alignment method rather than using Cootes's rotation and scale scheme. Hahn did not modified the profile itself. In this paper, the method using directional one dimensional profile is proposed to enhance Cootes's one dimensional profile and the shape alignment algorithm of Hahn is combined. The performance of the proposed method was superior to Cootes's and Hahn's. Average landmark estimation error for each image was 27.72 pixels and 39.46 for Cootes's and 33.73 for Hahn's each.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.611-613
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• 1998

A structure of musculotendon model with a fatigue profile is investigated. The Hill-type musculotendon model can predicts the decline in muscle force for a given fatigue profile. It consists of nonlinear activation and contraction dynamics based on the physiological concepts. It is normalized for generalization to deal with the various muscles. Muscle force generated by continuous tetanic electrical monophasic pulsewidth modulation stimulation is decreased in time. A fatigue profile is expressed by a function of intramuscular acidification and applied to the relationship between muscle force and shortening velocity in contraction dynamics. The results of computer simulation are well matched with data in a literature which are isometrically performed for knee extension muscles. Also change in optimal fiber length has an effect only on muscle time, constant not on the steady-state tetanic force.