• Journal of KIISE:Computer Systems and Theory
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• v.26 no.11
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• pp.1285-1295
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• 1999

본 논문은 방대한 크기의 볼륨 데이타를 효율적으로 렌더링하기 위한 셀 기반 웨이브릿 압축 방법을 제시한다. 이 방법은 볼륨을 작은 크기의 셀로 나누고, 셀 단위로 웨이브릿 변환을 한 다음 복원 순서에 따른 런-길이(run-length) 인코딩을 수행하여 높은 압축율과 빠른 복원을 제공한다. 또한 최근 복원 정보를 캐쉬 자료 구조에 효율적으로 저장하여 복원 시간을 단축시키고, 에러 임계치의 정규화로 비정규화된 웨이브릿 압축보다 빠른 속도로 정규화된 압축과 같은 고화질의 이미지를 생성하였다. 본 연구의 성능을 평가하기 위하여 {{}} 해상도의 볼륨 데이타를 압축하여 쉬어-？ 분해(shear-warp factorization) 알고리즘에 적용한 결과, 손상이 거의 없는 상태로 약 27:1의 압축율이 얻어졌고, 약 3초의 렌더링 시간이 걸렸다.Abstract This paper presents an efficient cell-based wavelet compression method of large volume data. Volume data is divided into individual cell of {{}} voxels, and then wavelet transform is applied to each cell. The transformed cell is run-length encoded according to the reconstruction order resulting in a fairly good compression ratio and fast reconstruction. A cache structure is used to speed up the process of reconstruction and a threshold normalization scheme is presented to produce a higher quality rendered image. We have combined our compression method with shear-warp factorization, which is an accelerated volume rendering algorithm. Experimental results show the space requirement to be about 27:1 and the rendering time to be about 3 seconds for {{}} data sets while preserving the quality of an image as like as using original data.

• Transactions on Electrical and Electronic Materials
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• v.13 no.3
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• pp.139-143
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• 2012

Optical emission spectroscopy (OES) is often used for real-time analysis of the plasma processes. OES has been suggested as a primary plasma process monitoring tool. It has the advantage of non-invasive in-situ monitoring capability but selecting the proper wavelengths for the analysis of OES data generally relies on empirically established methods. In this paper, we propose a practical method for the selection of OES wavelength peaks for the analysis of plasma etch process and this is done by investigating reactants and by-product gas species that reside in the plasma etch chamber. Wavelength selection criteria are based on the standard deviation and correlation coefficients. Moreover, chemical actinometry is employed for the normalization of the selected wavelengths. We also present the importance of chemical actinometry of OES data for quantitative analysis of plasma. Then, the suggested OES peak selection method is employed.. This method is used to find out the reason behind abnormal etching of PR erosion during a series of $SiO_2$ etch processes using the same recipe. From the experimental verification, we convinced that OES is not only capable for real-time detection of abnormal plasma process but it is also useful for the analysis of suspicious plasma behavior.

• Korean Journal of Metals and Materials
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• v.48 no.7
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• pp.598-604
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• 2010

Tensile tests are widely used for evaluating mechanical properties of materials including flow curves as well as Young's modulus, yield strength, tensile strength, and yield point elongation. This research aims at analyzing the plastic flow behavior of high strength steels for automotive bodies using the finite element method in conjunction with the viscoplastic model considering the yield point elongation phenomenon. The plastic flow behavior of the high strength steel was successfully predicted, by considering an operating deformation mechanism, in terms of normalization dislocation density, and strain hardening and accumulative damage of high strength steel using the modified constitutive model. In addition, the finite element method is employed to track the properties of the high strength steel pertaining to the deformation histories in a skin pass mill process.

• Journal of the Semiconductor & Display Technology
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• v.21 no.2
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• pp.133-137
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• 2022

In the smart industry where data plays an important role, cloud computing is being used in a complex and advanced way as a convergence technology because it has and fits well with its strengths. Accordingly, in order to utilize artificial intelligence rather than human beings for quality management of cloud computing services, a consistent standardization method of data collected from various nodes in various areas is required. Therefore, this study analyzed technologies and cases for incorporating artificial intelligence into specific services through previous studies, suggested a plan to use artificial intelligence to comprehensively standardize data in quality management of cloud computing services, and then verified it through case studies. It can also be applied to the artificial intelligence learning model that analyzes the risks arising from the data formalization method presented in this study and predicts the quality risks that are likely to occur. However, there is also a limitation that separate policy development for service quality management needs to be supplemented.

• Smart Structures and Systems
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• v.32 no.6
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• pp.393-402
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• 2023

Recently, hybrid and electric vehicles have been actively developed to replace internal combustion engine (ICE) vehicles. However, their vibrations and noise with complex spectra cause discomfort to drivers. To reduce the vibrations transmitted through primary excitation sources such as powertrains, structural changes have been introduced. However, the interference among different parts is a limitation. Thus, active mounting systems based on smart materials have been actively investigated to overcome these limitations. This study focuses on diminishing the source movement when a structure with two active mounting systems is excited to a single sinusoidal and a multi-frequency signal, which were investigated for source movement reduction. The overall structure was modeled based on the lumped parameter method. Active vibration control was implemented based on the modeled structure, and a multi-normalization least mean square (NLMS) algorithm was used to obtain the control input for the active mounting system. Furthermore, the performance of the NLMS algorithm was compared with that of the quantification method to demonstrate the performance of active vibration control. The results demonstrate that the vibration attenuation performance of the source component was improved.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.75-80
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• 2017

In this paper, we describe the effect of the regularization method and the network with identity mapping on the performance of the activation functions in deep convolutional neural networks. The activation functions act as nonlinear transformation. In early convolutional neural networks, a sigmoid function was used. To overcome the problem of the existing activation functions such as gradient vanishing, various activation functions were developed such as ReLU, Leaky ReLU, parametric ReLU, and ELU. To solve the overfitting problem, regularization methods such as dropout and batch normalization were developed on the sidelines of the activation functions. Additionally, data augmentation is usually applied to deep learning to avoid overfitting. The activation functions mentioned above have different characteristics, but the new regularization method and the network with identity mapping were validated only using ReLU. Therefore, we have experimentally shown the effect of the regularization method and the network with identity mapping on the performance of the activation functions. Through this analysis, we have presented the tendency of the performance of activation functions according to regularization and identity mapping. These results will reduce the number of training trials to find the best activation function.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.73-82
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• 2017

In Korea, previous certification of water supply infrastructure was mainly focused on economical and physical aspects. Recently, hygienic safety of water supply service has become a sensitive and important issue to our people for evaluating the water quality with growth of economy and education system. According on water quality in 497 Korean water supply facilities, pH values in the supplied water have ranged between 5.8-8.5. However, little is known about metal leachability at the pH conditions observed in the real water supply systems because a fixed pH condition (pH 7.0) has been used in the current standard method, 'Hygienic Safety Testing Method', in water supply. In this work, we examined the effects on heavy metal leachability with pH differences in the water supply pipes which are typically used in Korea. As a result, the amounts of metal leachability were tended to increase when pH levels were decreased. Especially at pH 5.8, Cu leachability from Cu pipes was found to exceed the public health standard level even after applying a normalization factor (NF) given by the current Korea standard method. The Cr and Cu leached from stainless steel pipes, Cd, Pb, Cu, and Zn from Cu-based pipe fittings, and Zn from Zn-based pipe fittings were exceeded the Korean hygienic safety standards while, after applying the NF, concentrations of the leached metals were satisfied with the current Korean standard. The findings from this work provide implications on the needs of reforming the current hygienic safety standard methodology.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.250-258
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• 2019

Due to the problems associated with the aging of industrial complexes, research on the decline of industrial complexes is being conducted. In the case of decline, it is necessary to not respond immediately, but with a crisis, it is necessary to minimize the impact on the industrial complex through preemptive responses to the external environment and internal changes. Therefore, it is necessary to develop a crisis index that can systematically predict and evaluate changes in the industrial complex. In this research, a method for extracting the crisis index of an industrial complex is developed. We derive performance measures for developing the crisis index, deriving the relative importance of performance measures based on the analytical hierarchy process. Because units of performance measurement are different, a normalization method is developed to sensitively reflect change. Based on the relative importance and normalized values of the performance measures, the crisis index of the industrial complex is developed and applied to a national industrial complex in order to verify its applicability.

• Smart Media Journal
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• v.12 no.2
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• pp.56-65
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• 2023

In broadcasts such as news and coverage programs, voice is modulated to protect the identity of the informant. Adjusting the pitch is commonly used voice modulation method, which allows easy voice restoration to the original voice by adjusting the pitch. Therefore, since broadcast voice modulation methods cannot properly protect the identity of the speaker and are vulnerable to security, a new voice modulation method is needed to replace them. In this paper, using the Lightweight speech de-identification model as the evaluation target model, we compare speech de-identification performance with broadcast voice modulation method using pitch modulation. Among the six modulation methods in the Lightweight speech de-identification model, we experimented on the de-identification performance of Korean speech as a human test and EER(Equal Error Rate) test compared with broadcast voice modulation using three modulation methods: McAdams, Resampling, and Vocal Tract Length Normalization(VTLN). Experimental results show VTLN modulation methods performed higher de-identification performance in both human tests and EER tests. As a result, the modulation methods of the Lightweight model for Korean speech has sufficient de-identification performance and will be able to replace the security-weak broadcast voice modulation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.153-159
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• 2010

This article presents a method that improve the drive-license test system, especially the course-driving by using the image processing. Decision(pass or not) is recorded and informed to test-driver after the image processing such as image capture, grayscaling, normalization, Hough transform and decision. That result system enables us to manage much more economically and effectively.