• 산업공학
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• 제16권spc호
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• pp.87-92
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• 2003

Progressive mesh representation and generation have become one of the most important issues in network-based computer graphics. However, current researches are mostly focused on triangular mesh models. On the other hand, solid models are widely used in industry and are applied to advanced applications such as product design and virtual assembly. Moreover, as the demand to share and transmit these solid models over the network is emerging, the generation and the transmission of progressive solid models depending on specific engineering needs and purpose are essential. In this paper, we present a Cellular Topology-based approach to generating and transmitting progressive solid models from a feature-based solid model for internet-based design and collaboration. The proposed approach introduces a new scheme for storing and transmitting solid models over the network. The Cellular Topology (CT) approach makes it possible to effectively generate progressive solid models and to efficiently transmit the models over the network with compact model size.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.377-377
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• 2000

Current software cost estimation models, such as the 1951 COCOMO, its 1987 Ada COCOMO update, is composed of nonlinear models, such as product attributes, computer attributes, personnel attributes, project attributes, effort-multiplier cost drivers, and have been experiencing increasing difficulties in estimating the costs of software developed to new lift cycle processes and capabilities. The COCOMO II is developed fur new forms against the current software cost estimation models. This paper provides a case-based analysis result of the cost driver in the software cost models, such as COCOMO and COCOMO 2.0 by fuzzy and neural network.

• 한국경영과학회지
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• 제16권2호
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• pp.128-147
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• 1991

We propose a dynamic incidence matrix (DIM) for reflecting states and time conditions of a timed Petri net (TPN) explicitly. Since a DIM consists of a conventional incidence matrix, two time-related vectors and two state-related vectors, we can get the advantages inherent in the conventional incidence matrix of describing a static structure of a system as well as another advantage of expressing time dependent state transitions. We introduce an algorithm providing the DIM with a state transition mechanism. Because the algorithm is, in fact, an algorithmic model for discrete event simulation of TPN models, we provide a theoretical basis of model transformation of a TPN model into a DEVS(Discrete Event system Specification) model. By executing the algorithm we can carry out performance analysis of computer communication protocols which are represented TPN models.

• 대한기계학회논문집A
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• 제28권7호
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• pp.885-895
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• 2004

Generally, automatic design is carried out with computer simulation and the simulation models are established by investigating the correlations between the simulation and real experiments. Therefore, the experiment results are utilized as complimentary data although they are considered to be precise. Orthogonal arrays have been adopted for discrete design. A method is proposed to directly exploit the experiment results in the design process with orthogonal arrays. Experiments are allocated to some rows of an orthogonal array and computer simulations are allocated to the others. A rule for the allocation is found to keep the orthogonality. Error analysis of the design results is performed. Mathematical examples are made to verify the validity of the proposed method. Error models are defined with the examples and the design solutions from the examples are discussed.

• 한국문헌정보학회지
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• 제35권1호
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• pp.101-122
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• 2001

오늘날 대부분의 도서관은 컴퓨터 중심의 워크스테이션 환경을 조성하고 있다. 이에 따른 문제점과 병리 현상이 심각함에도 불구하고 국내 도서관계에서는 컴퓨터 워크스테이션에 대한 기초연구나 조사분석이 전무한 실정이다. 따라서 본 연구에서는 국내 성인의 표준체위에 근거하여 도서관의 컴퓨터 워크스테이션(테이블과 의자, 모니터와 키보드, 자세와 동작, VDT 조명, 기타 환경요소)을 분석하고 인간공학적 모형을 제시하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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• pp.234-238
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• 1996

In this paper, Plasma-Enhanced Chemical Vapor Deposition (PECVD) modeling using Polynomial Neural Networks (PNN) has been introduced. The deposition of SiO2 was characterized via a 25-1 fractional factorial experiment, was used to train PNNs using predicted squared error (PSE). The optimal neural network structure and learning parameters were determined by means of a second fractional factorial experiment. The optimized networks minimized both learning and prediction error. From these PNN process models, the effect of deposition conditions on film properties has been studied. The deposition experiments were carried out in a Plasma Therm 700 series PECVD system. The models obtained will ultimately be used for several other manufacturing applications, including recipe synthesis and process control.

• 한국컴퓨터그래픽스학회논문지
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• 제9권2호
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• pp.1-9
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• 2003

Information assurance(IA) refers to methodologies to protect engineering information by ensuring its availability, confidentiality, integrity, non-repudiation, authentication, access control, etc. In collaborative design, IA techniques are needed to protect intellectual property, establish security privileges and create "need to know" protections on critical features. Aside from 3D watermarking, research on how to provide IA to distributed collaborative engineering teams is largely non-existent. This paper provides a framework for information assurance within collaborative design, based on a technique we call role-based viewing. Such role-based viewing is achieved through integration of multi-resolution geometry and security models. 3D models are geometrically partitioned, and the partitioning is used to create multi-resolution mesh hierarchies. Extracting an appropriately simplified model suitable for access rights for individual designers within a collaborative design environment is driven by an elaborate access control mechanism.

• 한국자동차공학회논문집
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• 제12권1호
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• pp.145-152
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• 2004

This paper compares seat vibrations of a small passenger car and a SUV. The results also include the comparison of the human body accelerations and the ride values, such as the component ride values, and SEAT values of 12 axis accelerations obtained at the human body and seat track. The ride comfort evaluation is usually carried out by experiments of real cars which are expensive and sometimes may contain errors by passenger's postures. Simulations by computer, on the other hand, enable to solve these problems when the accuracy is proven. This paper, thus, also shows the correlation of human body vibration between experiments and computer simulations. For the computer simulation, korean dummy models are developed from the Hybrid III models by scaling the body data of Hybrid III to those of Korean men and women. From the comparison between the test data and simulation data, a nice correlation in trends was shown.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2005년도 추계 학술대회 발표논문집
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• pp.159-162
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• 2005

Identification is the process automatically identify who is speaking on the basis of information obtained from speech waves. In training phase, each speaker models are trained using each speaker's speech data. GMMs (Gaussian Mixture Models), which have been successfully applied to speaker modeling in text-independent speaker identification, are not efficient in insufficient training data environment. This paper proposes speaker modeling method using MLLR (Maximum Likelihood Linear Regression) method which is used for speaker adaptation in speech recognition. We make SD-like model using MLLR adaptation method instead of speaker dependent model (SD). Proposed system outperforms the GMMs in small training data environment.

• 한국멀티미디어학회논문지
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• 제22권6호
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• pp.665-675
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• 2019

In this paper, we compare and analyze the classification performance of deep learning algorithm Convolutional Neural Network(CNN) ac cording to ensemble generation and combining techniques. We used several CNN models(VGG16, VGG19, DenseNet121, DenseNet169, DenseNet201, ResNet18, ResNet34, ResNet50, ResNet101, ResNet152, GoogLeNet) to create 10 ensemble generation combinations and applied 6 combine techniques(average, weighted average, maximum, minimum, median, product) to the optimal combination. Experimental results, DenseNet169-VGG16-GoogLeNet combination in ensemble generation, and the product rule in ensemble combination showed the best performance. Based on this, it was concluded that ensemble in different models of high benchmarking scores is another way to get good results.