• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.2
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• pp.91-99
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• 1998

This paper presents a methodology for identifying the cutter runout geometry in end milling process. Cutter runout is common but undesirable phenomenon in multi-tooth machining because it introduces variable chip loading to insert which results in a accelerated tool wear. amplification of force variation and hence enlargement vibration amplitude From understanding of chip load change kinematics, the analytical cutting force convolution model was formulated as the angular domain convolution model was formulated as the angular domain convolution of three dynamic cutting force component functions. By virtue of the convolution integration property, the frequency domain expression of the local cutting forces and the chip width density of the cutter. Experimental study is presented to validate the analytical model. This study provides the in-process monitoring and compensation of dynamic cutter runout to improve machining tolerance and surface quality for industrial application.

• Journal of Korea Multimedia Society
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• v.21 no.1
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• pp.61-68
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• 2018

In this paper, we present an effective encryption algorithm for 3D printing models in the frequency domain of discrete cosine transform to prevent illegal copying, access in the secured storage and transmission. Facet data of 3D printing model is extracted to construct a three by three matrix that is then transformed to the frequency domain of discrete cosine transform. The proposed algorithm is based on encrypting the DC coefficients of matrixes of facets in the frequency domain of discrete cosine transform in order to generate the encrypted 3D printing model. Experimental results verified that the proposed algorithm is very effective for 3D printing models. The entire 3D printing model is altered after the encryption process. The proposed algorithm is provide a better method and more security than previous methods.

• Journal of Information Technology Services
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• v.1 no.1
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• pp.141-148
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• 2002

As an optimun alternatives for the solution of recent software crisis, we have to develop component technologies so as to develop and propagate business components for various domains to industries. For the sake of development of business components, a conceptual architecture which defines a model for component assembly should be prescribed first, and a systematic specification method based on this model be defined, so we can build a system environments for making specifications and development of each component by the consistent scheme. In this study, we propose a domain architecture model for implementing the pUblic component bank as a project supported by the ministry of information and communication, discuss the conceptual model of specification for developing components of storing component bank, specification steps, specification approach for application of business domains and the development results of them.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.03a
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• pp.232-237
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• 2003

A new displacement-based transmitting boundary is developed for the transient analysis of dynamics interactions between flexible dam body and reservoir impounding compressible water The mechanical model is derived analytically in time domain from the kernel function, Bessel function, appearing in the convolution integral and corresponding mechanical model is developed that consists of mass, damping and stiffness matrices. The resulting system of, equations uses displacement degrees of freedom. Hence it can be coupled directly with the displacement-based solid finite element model of dam body, linear of nonlinear. The method was applied to the rigid and flexible dam models. The results showed very good agreement : with the semi-analytic frequency domain solutions.

• Journal of information and communication convergence engineering
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• v.21 no.2
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• pp.139-144
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• 2023

Engineers prefer deep neural networks (DNNs) for solving computer vision problems. However, DNNs pose two major problems. First, neural networks require large amounts of well-labeled data for training. Second, the covariate shift problem is common in computer vision problems. Domain adaptation has been proposed to mitigate this problem. Recent work on adversarial-learning-based unsupervised domain adaptation (UDA) has explained transferability and enabled the model to learn robust features. Despite this advantage, current methods do not guarantee the distinguishability of the latent space unless they consider class-aware information of the target domain. Furthermore, source and target examples alone cannot efficiently extract domain-invariant features from the encoded spaces. To alleviate the problems of existing UDA methods, we propose the mixup regularization in adversarial discriminative domain adaptation (ADDA) method. We validated the effectiveness and generality of the proposed method by performing experiments under three adaptation scenarios: MNIST to USPS, SVHN to MNIST, and MNIST to MNIST-M.

• Journal of Computing Science and Engineering
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• v.11 no.4
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• pp.152-159
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• 2017

Three-dimensional (3D) printing is applied to many areas of life, but 3D printing models are stolen by pirates and distributed without any permission from the original providers. Moreover, some special models and anti-weapon models in 3D printing must be secured from the unauthorized user. Therefore, 3D printing models must be encrypted before being stored and transmitted to ensure access and to prevent illegal copying. This paper presents a selective encryption algorithm for 3D printing models based on clustering and the frequency domain of discrete cosine transform. All facets are extracted from 3D printing model, divided into groups by the clustering algorithm, and all vertices of facets in each group are transformed to the frequency domain of a discrete cosine transform. The proposed algorithm is based on encrypting the selected coefficients in the frequency domain of discrete cosine transform to generate the encrypted 3D printing model. Experimental results verified that the proposed algorithm is very effective for 3D printing models. The entire 3D printing model is altered after the encryption process. The decrypting error is approximated to be zero. The proposed algorithm provides a better method and more security than previous methods.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1165-1168
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• 2002

Knowledge acquisition is the process that extracts the required knowledge from available sources, such as experts, textbooks and databases, for incorporation into a knowledge-based system. Knowledge acquisition is described as the first step in building expert systems and a major bottleneck in the efficient development and application of effective knowledge based expert systems. One cause of the problem is that the process of human reasoning we need to understand for knowledge-based system development is not available for direct observation. Moreover, the expertise of interest is typically not reportable due to the compilation of knowledge which results from extensive practice in a domain of problem solving activity. This is also a problem of modeling knowledge, which has been described as not a problem of accessing and translating what is known, but the familiar scientific and engineering problem of formalizing models for the first time. And this formalization process is especially difficult for knowledge engineers who are often faced with the difficult task of creating a knowledge model of a domain unfamiliar to them. In this paper, we propose an automated knowledge acquisition tool which is based on an implementation of the Inferential Modeling Technique. The Inferential Modeling Technique is derived from the Inferential Model which is a domain-independent categorization of knowledge types and inferences ［Chan 1992］. The model can serve as a template of the types of knowledge in a knowledge model of any domain.

• Coupled systems mechanics
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• v.12 no.1
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• pp.1-20
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• 2023

On the basis of the explicit time-domain method, an investigation is performed on the influence of the rotational stiffness and rotational damping of the vehicle body and front-rear bogies on the dynamic responses of the vehicle-bridge coupled systems. The equation of motion for the vehicle subsystem is derived employing rigid dynamical theories without considering the rotational stiffness and rotational damping of the vehicle body, as well as the front-rear bogies. The explicit expressions for the dynamic responses of the vehicle and bridge subsystems to contact forces are generated utilizing the explicit time-domain method. Due to the compact wheel-rail model, which reflects the compatibility requirement of the two subsystems, the explicit expression of the evolutionary statistical moment for the contact forces may be performed with relative ease. Then, the evolutionary statistical moments for the respective responses of the two subsystems can be determined. The numerical results indicate that the simplification of vehicle model has little effect on the responses of the bridge subsystem and the vehicle body, except for the responses of the rotational degrees of freedom for the vehicle subsystem, regardless of whether deterministic or random analyses are performed.

• Journal of Electrical Engineering and Technology
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• v.7 no.6
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• pp.932-939
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• 2012

This paper presents an equivalent circuit model of a LIPB (Li-Ion Polymer battery) for Hybrid Electric Vehicles (HEVs). The proposed equivalent circuit can be used to predict the charging/discharging characteristics in time domain as well as the impedance characteristic analysis in frequency domain. Based on these features, a one-cell model is established as a function of Depth of Discharge (DoD), and a 48-cell model for a battery pack was also established. It was confirmed by experiment that the proposed model predict the discharging and impedance (AC) characteristics quite accurately at different constant current levels. To check the usefulness of the proposed circuit, the model was used to simulate a motor driving circuit with an Insulated Gate Bipolar Transistor (IGBT) inverter and Brushless DC (BLDC) motor, and it is confirmed that the model can calculate the battery voltage fluctuation in time domain at different DoDs.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.421-430
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• 2006

In sample survey sample designs are performed by geographically-based domain such as countries, states and metropolitan areas. However mostly statistics of interests are smaller domain than sample designed domain. Then sample sizes are typically small or even zero within the domain of interest. Shin and Lee(2003) mentioned Spatial Autoregressive(SAR) model in small area estimation model-based method and show the effectiveness by MSE. In this study, Bayesian Auto-Poisson Model is applied in model-based small area estimation method and compare the results with SAR model using MSE ME and bias check diagnosis using regression line. In this paper Survey of Disability, Aging and Cares(SDAC) data are used for simulation studies.