• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.426-429
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• 2004

To reconstruct the 3-D information of a irregular object, this paper proposes a new method applying the composition focus measure to time-series image. A focus measure function is carefully selected because a focus measure is apt to be affected by the working environment and the characteristics of an object. The proposed focus measure function combines the variance measure which is robust to noise and the Laplacian measure which, regardless of an object shape, has a good performance in calculating the focus measure. And the time-series image, which considers the object shape, is proposed in order to efficiently applying the interesting window. This method, first, divides the image frame by the window. Second, the composition focus measure function be applied to the windows, and the time-series image is constructed. Finally, the 3-D information of an object is reconstructed from the time-series images considering the object shape. The experimental results have shown that the proposed method is suitable algorithm to 3-D reconstruction of an irregular object.

• Journal of Technology Innovation
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• v.13 no.2
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• pp.207-222
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• 2005

A prerequisite for making R&D more productive is to able to measure its productivity. Most of the previous studies on this topic have attempted to measure R&D productivity at the firm or industry levels. In this study, however, R&D productivity is measured at the national level to provide R&D policy implications, particularly for Asian countries. Contrary to the previous studies where total factor productivity was adopted, this study employs the data envelopment analysis (DEA) approach to measure R&D productivity. DEA is a multi-factor productivity analysis model for measuring the relative efficiency of each Decision Making Unit (DMU). In addition to the basic DEA model that includes all inputs and outputs, five additional models are constructed by combining single input with all outputs and single output with all inputs in order to measure specialized R&D efficiency. In this study, the twenty-seven countries are classified into four clusters based on the output-specialized R&D efficiency: inventors, merchandisers, academicians, and duds. Then, the characteristics of the Asian countries with respect to R&D efficiency are identified. It is found that Singapore ranks high in total efficiency, and Japan in patent-oriented efficiency. Meanwhile, China, Korea, and Taiwan are found to be relatively inefficient in R&D. We expect that the findings from this study will be able to provide directions for R&D policy-making of the Asian countries.

• The Journal of the Acoustical Society of Korea
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• v.11 no.2
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• pp.73-84
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• 1992

This paper studies noise subtraction methods and distance measures for speech recognition in a noisy environment, and investigates noise robustness of the distance measures applied to the problem of isolated word recognition in white Gaussian and colored noise (vehicle noise) environments. Noise subtraction methods which can be used as a pre-processor for the speech recognition system, such as the spectral subtraction method, autocorrelation subtraction method, adaptive noise cancellation and acoustic beamforming are studied, and distance measures such and Log Likelihood Ratio ($d_{LLR}$), cepstral distance measure ($d_{CEP}$), weighted cepstral distance measure ($d_{WCEP}$), spectral slope distance measure ($d_{RPS}$) and cepstral projection distance measure ($d_{CP},\;d_{BCP},\;d_{WCP},\;d_{BWCP}$) are also investigated. Testing of the distance measures for speaker-dependent isolated word recognition in a noisy environment indicate that $d_{RPS}\;and\;d_{WCEP}$ which weigh higher order cepstral coefficients more heavily give considerable performance improvement over $d_{CEP}and\;d_{LLR}$. In addition, when no pre-emphasis is performed, the recognizer can maintain higher performance under high noise conditions.

• Bulletin of the Korean Mathematical Society
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• v.53 no.3
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• pp.943-957
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• 2016

We introduce a 2-variable weighted shift, denoted by $S_2$(a, b, c, d), which arises naturally from analytic function space theory. We investigate when it is subnormal, and compute the Berger measure of it when it is subnormal. And we apply the results to investigate the relationship among 2-variable subnormal, hyponormal and 2-hyponormal weighted shifts.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.5 no.2
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• pp.128-136
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• 1995

The purpose of this study is to evaluate the difference of noise level according to noise measuring methods in the noisy working environments. Sound pressure level(SPL), equivalence sound level(Leq) and personal noise exposure dose(Dose) in the fifty-nine unit workplaces of the twenty-eight industries were measured and relating factors which were affected noise level were investigated. The results were as follows ; 1. The noise levels were $88.70{\pm}5.68dB(A)$ by SPL, $89.07{\pm}5.41dB(A)$ by Leq and $89.07{\pm}5.69$ by Dose. The differences of noise levels by three measuring methods were statistically significant(P<0.001) by repeated measure ANOV A. 2. Comparing with noise levels by general classes of noise exposure, noise levels of continuous noise were $89.14{\pm}5.19dB(A)$ by SPL, $89.45{\pm}4.65dB(A)$ by Leq and $90.04{\pm}5.09$ by Dose. Noise levels of intermittent noise were $87.90{\pm}6.52dB(A)$ by SPL, $88.40{\pm}6.63dB(A)$ by Leq and $90.10{\pm}6.80$ by Dose. The differences noise level of noise measuring methods by general classese of noise exposure were statistically not significant by repeated measure ANOV A. 3. Interaction between general classese of noise exposure and noise measuring methods for noise level was not statistically significant by repeated measure ANOVA. And the noise level by noise measuring methods were statistically significant by repeated measure ANOV A(P<.001) 4. Comparing with noise levels by unit workplace size, noise levels of large unit workplace were $90.73{\pm}5.87dB(A)$ by SPL, $91.32{\pm}5.50dB(A)$ by Leq and $91.82{\pm}6.06$ by Dose and noise levels of middle unit workplace were $88.31{\pm}5.26dB(A)$ by SPL, $88.41{\pm}4.83dB(A)$ by Leq and $89.69{\pm}5.05$ by Dose. And noise levels of small unit workplace were $94.89{\pm}4.10dB(A)$ by SPL, $85.35{\pm}4.11dB(A)$ by Leq and $86.87{\pm}4.98$ by Dose. The noise level differences of noise measuring methods by unit workplace size were statistically significant by repeated measure ANOV A(P<.05). 5. The noise level by noise measuring methods were statistically significant by repeated measure ANOV A(P<.001). But Interaction between workplace size and noise level measuring methods for noise level was not statistically significant by repeated measure ANOVA. According to the above results, there was a difference of the noise level among the three measuring methods. Therefore we must use the personal noise exposure dose using by noise dose meter, possible, to prvent occupational hearing loss in noisy working environment.

• Journal of the Semiconductor & Display Technology
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• v.13 no.2
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• pp.23-28
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• 2014

For the reconstruction of three-dimensional (3D) shape of microscopic objects through shape from focus (SFF) methods, usually a single focus measure operator is employed. However, it is difficult to compute accurate depth map using a single focus measure due to different textures, light conditions and arbitrary object surfaces. Moreover, real images with diverse types of illuminations and contrasts lead to the erroneous depth map estimation through a single focus measure. In order to get better focus measurements and depth map, we have combined focus measure operators by using genetic algorithm. The resultant focus measure is obtained by weighted sum of the output of various focus measure operators. Optimal weights are obtained using genetic algorithm. Finally, depth map is obtained from the refined focus volume. The performance of the developed method is then evaluated by using both the synthetic and real world image sequences. The experimental results show that the proposed method is more effective in computing accurate depth maps as compared to the existing SFF methods.

• Speech Sciences
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• v.7 no.2
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• pp.85-95
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• 2000

In this paper, the H1*-H2* measure is introduced and exact procedures for obtaining the H1*-H2* value are fully specified, The H1*-H2* measure (a corrected difference in dB between the first and second harmonics) has been devised to provide an acoustic correlate of the phonation mode of a vowel following a consonant. With this measure, we can investigate the phonation mode of a vowel that is free from the F1 amplitude perturbation effect caused by the preceding consonant, which is especially salient at the voicing onset position of the vowel. For identical research purposes, on the other hand, the H1-H2 measure (the observed difference in dB between the first and second harmonic) has been employed in many previous studies. This paper compares these two measures by illustrating experimental results of exploring post-release phonation modes of vowels following the different manner classes of stop consonants in Korean $\square$i.e., the tense, lenis, and aspirated stops.

• Journal of the Semiconductor & Display Technology
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• v.3 no.4
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• pp.19-27
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• 2004

The characteristic evaluation of A/D converter is to measure the linearity of the converter. The evaluation of the linearity is to measure the DNL, INL, gain error and offset error in the various test parameters of A/D converter. Generally, DNL and INL are to be measured by the Histogram Test Algorithm in the DSP-based ATE environment. And gain error and offset error are to be measured by the calculation equation of the measuring algorithm. It is to propose the new Concurrent Histogram Test Algorithm for the test of the housekeeping A/D converter used in the CDMA cellular phone. Using the proposed method, it is to measure the DNL, INL, gain error and offset error concurrently and to show the measured results.

• Journal of Broadcast Engineering
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• v.16 no.2
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• pp.319-330
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• 2011

For objective assessment of stereoscopic 3D image quality, we measure quality of left and right image with 2D image quality measurement method. However, this method is inconvenient because that we have to measure quality of left and right image individually. Therefore we propose a method of stereoscopic 3D image quality assessment using one overlaid image with left and right image. Using this method, One can measure quality of stereoscopic 3D image more easily and quickly.

• Journal of Korea Multimedia Society
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• v.16 no.1
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• pp.11-18
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• 2013

This paper presents a SFF(shape from focus) algorithm using a new focus measure based on higher order statistics for the exact depth estimation. Since conventional SFF-based 3D depth reconstruction algorithms used SML(sum of modified Laplacian) as the focus measure, their performance is strongly depended on the image characteristics. These are efficient only for the rich texture and well focused images. Therefore, this paper adopts a new focus measure using HOS(higher order statistics), in order to extract the focus value for relatively poor texture and focused images. The initial best focus area map is generated by the measure. Thereafter, the area refinement, thinning, and corner detection methods are successively applied for the extraction of the locally best focus points. Finally, a 3D model from the carefully selected points is reconstructed by Delaunay triangulation.