• The Journal of Advanced Prosthodontics
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• v.8 no.1
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• pp.37-42
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• 2016

PURPOSE. This study investigated the effect of amount of thickness reduction on color and translucency of dental monolithic zirconia ceramics. MATERIALS AND METHODS. One-hundred sixty-five monolithic zirconia specimens ($16.3mm{\times}16.3mm{\times}2.0mm$) were divided into 5 groups (Group I to V) according to the number of A2-coloring liquid applications. Each group was then divided into 11 subgroups by reducing the thickness up to 1.0 mm in 0.1-mm increments (Subgroup 0 to 10, n=3). Colors and spectral distributions were measured according to CIELAB on a reflection spectrophotometer. All measurements were performed on five different areas of each specimen. Color difference (${\Delta}E^*{^_{ab}}$) and translucency parameter (TP) were calculated. Data were analyzed using one-way ANOVA and multiple comparison $Scheff{\acute{e}}$ test (${\alpha}=.05$). RESULTS. There were significant differences in CIE $L^*$ between Subgroup 0 and other subgroups in all groups. CIE $a^*$ increased (0.52<$R^2$<0.73), while CIE $b^*$ decreased (0.00<$R^2$<0.74) in all groups with increasing thickness reduction. Perceptible color differences (${\Delta}E^*{^_{ab}}$>3.7) were obtained between Subgroup 0 and other subgroups. TP values generally increased as the thickness reduction increased in all groups ($R^2$>0.89, P<.001). CONCLUSION. Increasing thickness reduction reduces lightness and increases a reddish, bluish appearance, and translucency of monolithic zirconia ceramics.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1926-1933
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• 2022

Parameterized multichannel Wiener filter (PMWF) is a linear filter that can control the trade-off between residual noise and signal distortion using the embedded parameter. To apply the PMWF to noisy inputs, accurate noise estimation is important and multichannel minima-controlled recursive averaging (MMCRA) is widely used. However, in the case of the MMCRA, the accuracy of noise estimation decreases when a directional interference is involved into the array inputs. Consequently, the performance of the PMWF is degraded. Therefore, we propose a noise power spectral density (PSD) estimation method for the PMWF in this paper. The proposed method is based on a consecutive process of eigenvalue decomposition on noisy input PSD, estimation of the target component contribution using directional information, and exponential weighting for improved estimation of the target contribution. For evaluation, four objective measures were compared with the MMCRA and we verify that the PMWF with the proposed noise estimation method can improve performance in environments where directional interfereces exist.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.93-101
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• 2024

Accurate field crop classification is essential for various agricultural applications, yet existing methods face challenges due to diverse crop types and complex field conditions. This study aimed to address these issues by combining support vector machine (SVM) models with multi-seasonal unmanned aerial vehicle (UAV) images, texture information extracted from Gray Level Co-occurrence Matrix (GLCM), and RGB spectral data. Twelve high-resolution UAV image captures spanned March-October 2021, while field surveys on three dates provided ground truth data. We focused on data from August (-A), September (-S), and October (-O) images and trained four support vector classifier (SVC) models (SVC-A, SVC-S, SVC-O, SVC-AS) using visual bands and eight GLCM features. Farm maps provided by the Ministry of Agriculture, Food and Rural Affairs proved efficient for open-field crop identification and served as a reference for accuracy comparison. Our analysis showcased the significant impact of hyperparameter tuning (C and gamma) on SVM model performance, requiring careful optimization for each scenario. Importantly, we identified models exhibiting distinct high-accuracy zones, with SVC-O trained on October data achieving the highest overall and individual crop classification accuracy. This success likely stems from its ability to capture distinct texture information from mature crops.Incorporating GLCM features proved highly effective for all models,significantly boosting classification accuracy.Among these features, homogeneity, entropy, and correlation consistently demonstrated the most impactful contribution. However, balancing accuracy with computational efficiency and feature selection remains crucial for practical application. Performance analysis revealed that SVC-O achieved exceptional results in overall and individual crop classification, while soybeans and rice were consistently classified well by all models. Challenges were encountered with cabbage due to its early growth stage and low field cover density. The study demonstrates the potential of utilizing farm maps and GLCM features in conjunction with SVM models for accurate field crop classification. Careful parameter tuning and model selection based on specific scenarios are key for optimizing performance in real-world applications.

• The Journal of the Acoustical Society of Korea
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• v.27 no.5
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• pp.256-261
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• 2008

In this paper, we propose a novel approach to improve the performance of minima controlled recursive averaging (MCRA) which is based on the conditional maximum a posteriori criterion. A crucial component of a practical speech enhancement system is the estimation of the noise power spectrum. One state-of-the-art approach is the minima controlled recursive averaging (MCRA) technique. The noise estimate in the MCRA technique is obtained by averaging past spectral power values based on a smoothing parameter that is adjusted by the signal presence probability in frequency subbands. We improve the MCRA using the speech presence probability which is the a posteriori probability conditioned on both the current observation the speech presence or absence of the previous frame. With the performance criteria of the ITU-T P.862 perceptual evaluation of speech quality (PESQ) and subjective evaluation of speech quality, we show that the proposed algorithm yields better results compared to the conventional MCRA-based scheme.

• Journal of Animal Environmental Science
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• v.18 no.3
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• pp.257-266
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• 2012

Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid, accurate method of evaluating some chemical constituents in cereal and dired animal forages. Analysis of forage quality by NIRS usually involves dry grinding samples. Costs might be reduced if samples could be analyzed without drying or grinding. The objective of this study was to investigate effect of sample preparations on prediction ability of chemical composition and fermentation parameter for Italian ryegrass silages by NIRS. A population of 147 Italian ryegrass silages representing a wide range in chemical parameters were used in this investigation. Samples were scanned at 1nm intervals over the wavelength range 680-2500 nm and the optical data recorded as log 1/Reflectance (log 1/R) and scanned in oven-dried grinding and fresh ungrinding condition. The spectral data were regressed against a range of chemical parameters using partial least squares (PLS) multivariate analysis in conjunction with four spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected on the basis of minimizing the standard error of cross validation (SECV) and maximizing the correlation coefficient of cross validation (${R^2}_{CV}$). The results of this study show that NIRS predicted the chemical parameters with high degree of accuracy in oven-dried grinding treatment except for moisture contents. Prediction accuracy of the moisture contents was better for fresh ungrinding treatment (SECV 1.37%, $R^2$ 0.96) than for oven-dried grinding treatments (SECV 4.31%, $R^2$ 0.68). Although the statistical indexes for accuracy of the prediction were the lower in fresh ungrinding treatment, fresh treatment may be acceptable when processing is costly or when some changes in component due to the processing are expected. Results of this experiment showed the possibility of NIRS method to predict the chemical composition and fermentation parameter of Italian ryegrass silages as routine analysis method in feeding value evaluation and for farmer advice.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.61-73
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• 2014

This study reviewed an application of water quality estimation using an Airborne Hyperspectral Imagery (A-HSI) and tested a part of Han River water quality (especially suspended solid) estimation with available in-situ data. The estimation of water quality was processed two methods. One is using observation data as downwelling radiance to water surface and as scattering and reflectance into water body. Other is linear regression analysis with water quality in-situ measurement and upwelling data as at-sensor radiance (or reflectance). Both methods drive meaningful results of RS estimation. However it has more effects on the auxiliary dataset as water quality in-situ measurement and water body scattering measurement. The test processed a part of Han River located Paldang-dam downstream. We applied linear regression analysis with AISA eagle hyperspectral sensor data and water quality measurement in-situ data. The result of linear regression for a meaningful band combination shows $-24.847+0.013L_{560}$ as 560 nm in radiance (L) with 0.985 R-square. To comparison with Multispectral Imagery (MSI) case, we make simulated Landsat TM by spectral resampling. The regression using MSI shows -55.932 + 33.881 (TM1/TM3) as radiance with 0.968 R-square. Suspended Solid (SS) concentration was about 3.75 mg/l at in-situ data and estimated SS concentration by A-HIS was about 3.65 mg/l, and about 5.85mg/l with MSI with same location. It shows overestimation trends case of estimating using MSI. In order to upgrade value for practical use and to estimate more precisely, it needs that minimizing sun glint effect into whole image, constructing elaborate flight plan considering solar altitude angle, and making good pre-processing and calibration system. We found some limitations and restrictions such as precise atmospheric correction, sample count of water quality measurement, retrieve spectral bands into A-HSI, adequate linear regression model selection, and quantitative calibration/validation method through the literature review and test adopted general methods.

• Progress in Medical Physics
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• v.25 no.4
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• pp.271-280
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• 2014

Recently, digital breast tomosynthesis (DBT) has been investigated to overcome the limitation of conventional mammography for overlapping anatomical structures and high patient dose with cone-beam computed tomography (CBCT). However incomplete sampling due to limited angle leads to interference on the neighboring slices. Many studies have investigated to reduce artifacts such as interference. Moreover, appropriate filters for tomosynthesis have been researched to solve artifacts resulted from incomplete sampling. The primary purpose of this study is finding appropriate filter scheme with FBP reconstruction for DBT system to reduce artifacts. In this study, we investigated characteristics of various filter schemes with simulation and prototype digital breast tomosynthesis under same acquisition parameters and conditions. We evaluated artifacts and noise with profiles and COV (coefficinet of variation) to study characteristic of filter. As a result, the noise with parameter 0.25 of Spectral filter reduced by 10% in comparison to that with only Ramp-lak filter. Because unbalance of information reduced with decreasing B of Slice thickness filter, artifacts caused by incomplete sampling reduced. In conclusion, we confirmed basic characteristics of filter operations and improvement of image quality by appropriate filter scheme. The results of this study can be utilized as base in research and development of DBT system by providing information that is about noise and artifacts depend on various filter schemes.

• Journal of the Korean Chemical Society
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• v.55 no.3
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• pp.418-429
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• 2011

Novel chromium(III), manganese(II), iron(III), cobalt(II), nickel(II), copper(II), ruthenium(III), and zirconyl(II) complexes of $N^1,N^2$-bis(3-((3-hydroxynaphthalen-2-yl)methylene-amino)propyl)phthalamide ($H_4L$, 1) have been synthesized and characterized by elemental, physical, and spectral analyses. The spectral data showed that the ligand behaves as either neutral tridentate ligand as in complexes 2-5 with the general formula $[H_4LMX_2(H_2O)]{\cdot}nH_2O$ (M=Cu(II), Ni(II), Co(II), X = Cl or $NO_3$), neutral hexadentate ligand as in complexes 10-12 with the general formula $[H_4LM_2Cl_6]{\cdot}nH_2O$ (M=Fe(III), Cr(III) or Ru(III)), or dibasic hexadentate ligand as in complexes 6-9 with the general formula $[H_2LM_2Cl_2(H_2O)_4]{\cdot}nH_2O$ (M = Cu(II), Ni(II), Co(II) or Mn(II), and 13 with general formula $[H_4L(ZrO)_2Cl_2]{\cdot}8H_2O$. Molar conductance in DMF solution indicated the non-ionic nature of the complexes. The ESR spectra of solid copper(II) complexes 2, 5, and 6 showed $g_{\parallel}$ >g> $g_e$, indicating distorted octahedral structure and the presence of the unpaired electron in the $N^1,N^2$ orbital with significant covalent bond character. For the dimeric copper(II) complex $[H_2LCu_2Cl_2(H_2O)_4]{\cdot}3H_2O$ (6), the distance between the two copper centers was calculated using field zero splitting parameter for the parallel component that was estimated from the ESR spectrum. The antibacterial and antifungal activities of the compounds showed that, some of metal complexes exhibited a greater inhibitory effect than standard drug as tetracycline (bacteria) and Amphotricene B (fungi).

• Progress in Medical Physics
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• v.19 no.4
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• pp.256-262
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• 2008

To evaluate the metabolic changes in normal adult brains due to alterations SENSE and NEX (number of excitation) by multi voxel MR Spectroscopy at 3.0 Tesla. The study group was composed of normal volunteers (5 men and 8 women) with a mean ($\pm$ standard deviation) age of 41 (${\pm}11.65$). Their ages ranged from 28 to 61 years. MR Spectroscopy was performed with a 3.0T Achieva Release Version 2.0 (Philips Medical System-Netherlands). The 8 channel head coil was employed for MRS acquisition. The 13 volunteers underwent multi voxel spectroscopy (MVS) and single voxel spectroscopy (SVS) on the thalamus area with normally gray matter. Spectral parameters were as follows: 15 mm of thickness; 230 mm of FOV (field of view); 2000 msecs of repetition time (TR); 288 msecs of echo time (TE); $110{\times}110$ mm of VOI (view of interest); $15{\times}15{\times}15$ mm of voxel size. Multi voxel spectral parameters were made using specially in alteration of SENSE factor (1~3) and 1~2 of NEX. All MRS data were processed by the jMRUI 3.0 Version. There was no significant difference in NAA/Cr and Cho/Cr ratio between MVS and SVS likewise the previous results by Ross and coworkers in 1994. In addition, despite the alterations of SENSE factor and NEX in MVS, the metabolite ratios were not changed (F-value : 1.37, D.F : 3, P-value : 0.262). However, line-width of NAA peak in MVS was 3 times bigger than that in SVS. In the present study, we demonstrated that the alterations of SENSE factor and NEX were not critically affective to the result of metabolic ratios in the normal brain tissue.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.17 no.3
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• pp.178-187
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• 2005

A reliability analysis model f3r studying the influence of joint distribution of wave heights and periods on wave un-up is presented in this paper. From the definition of failure mode related to wave run-up, a reliability function may be formulated which can be considered uncertainties of water level. In particular, the reliability analysis model can be directly taken into account statistical properties and distributions of wave periods by considering wave period in the reliability function to be a random variable. Also, variations of wave height distribution conditioned to mean wave periods can be taken into account correctly. By comparison of results of additional reliability analysis using extreme distributions with those resulted from joint distribution of wave height and periods, it is found that probabilities of failure evaluated by the latter is larger than those by the former. Although the freeboard of sloped-breakwater structures can be determined by extreme distribution based on the long-term measurements, it may be necessary to investigate additionally into wave run-up by using the present reliability analysis model formulated to consider joint distribution of a single storm event. In addition, it may be found that the effect of spectral bandwidth parameter on reliability index may be little, but the effect of wave height distribution conditioned to mean wave periods is straightforward. Therefore, it may be confirmed that effects of wave periods on the probability of failure of wave run-up may be taken into account through the conditional distribution of wave heights. Finally, the probabilities of failure with respect to freeboard of sloped-breakwater structures can be estimated by which the rational determination of crest level of sloped-breakwater structures may be possible.