• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.392-400
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• 2009

In this paper, we propose an effective speech reinforcement technique base on ITU-T G.729A CS-ACELP codec under the near-end background noise environments. In general, since the intelligibility of the far-end speech for the near-end listener is significantly reduced under near-end noise environments, we require a far-end speech reinforcement approach to avoid this phenomena. In contrast to the conventional speech reinforcement algorithm, we reinforce the excitation signal of the codec's parameters received from the far-end speech signal based on the G.729A speech codec under various background noise environments. Specifically, we first estimate the excitation signal of ambient noise at the near-end through the encoder of the G.729A speech codec, reinforcing the excitation signal of the far-end speech transmitted from the far-end. we specially propose a novel approach to directly reinforce the excitation signal of far-end speech signal based on the decoder of the G.729A. The performance of the proposed algorithm is evaluated by the CCR (Comparison Category Rating) test of the method for subjective determination of transmission quality in ITU-T P.800 under various noise environments and shows better performances compared with conventional SNR Recovery methods.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.397-418
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• 2024

The Land Surface Temperature (LST) is a crucial parameter in identifying drought. It is essential to identify how LST can increase its accuracy, particularly in mountainous and hill areas. Increasing the LST accuracy can be achieved by applying early data processing in the correction phase, specifically in the context of topographic correction on the Lambertian model. Empirical evidence has demonstrated that this particular stage effectively enhances the process of identifying objects, especially within areas that lack direct illumination. Therefore, this research aims to examine the application of the Lambertian model in estimating LST using the Multi-Channel Method (MCM) across various physiographic regions. Lambertian model is a method that utilizes Lambertian reflectance and specifically addresses the radiance value obtained from Sun-Canopy-Sensor(SCS) and Cosine Correction measurements. Applying topographical adjustment to the LST outcome results in a notable augmentation in the dispersion of LST values. Nevertheless, the area physiography is also significant as the plains terrain tends to have an extreme LST value of ≥ 350 K. In mountainous and hilly terrains, the LST value often falls within the range of 310-325 K. The absence of topographic correction in LST results in varying values: 22 K for the plains area, 12-21 K for hilly and mountainous terrain, and 7-9 K for both plains and mountainous terrains. Furthermore, validation results indicate that employing the Lambertian model with SCS and Cosine Correction methods yields superior outcomes compared to processing without the Lambertian model, particularly in hilly and mountainous terrain. Conversely, in plain areas, the Lambertian model's application proves suboptimal. Additionally, the relationship between physiography and LST derived using the Lambertian model shows a high average R² value of 0.99. The lowest errors(K) and root mean square error values, approximately ±2 K and 0.54, respectively, were achieved using the Lambertian model with the SCS method. Based on the findings, this research concluded that the Lambertian model could increase LST values. These corrected values are often higher than the LST values obtained without the Lambertian model.

• Journal of Biomedical Engineering Research
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• v.25 no.4
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• pp.261-268
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• 2004

Osteoporosis is a clinical condition in which the amount of bone tissue is reduced and the likelihood of fracture is increased. It is known that the electrical property of the bone is related to its density, and, in particular, the electrical resistance of the bone decreases as the bone loss increases. This implies that the electrical property of bone may be an useful parameter to diagnose osteoporosis, provided that it can be readily measured. The study attempted to evaluate the electrical conductivity of bone using a technique of electrical impedance tomography (EIT). It nay not be easy in general to get an EIT for the bone due to the big difference (an order of 2) of electrical properties between the bone and the surrounding soft tissue. In the present study, we took an adaptive mesh regeneration technique originally developed for the detection of two phase boundaries and modified it to be able to reconstruct the electrical conductivity inside the boundary provided that the geometry of the boundary was given. Numerical simulation was carried out for a tibia phantom, circular cylindrical phantom (radius of 40 mm) inside of which there is an ellipsoidal homeogenous tibia bone (short and long radius are 17 mm and 15 mm, respectively) surrounded by the soft tissue. The bone was located in the 15 mm above from the center of the circular cross section of the phantom. The electrical conductivity of the soft tissue was set to be 4 mS/cm and varies from 0.01 to 1 ms/cm for the bone. The simulation considered measurement errors in order to look into its effects. The simulated results showed that, if the measurement error was maintained less than 5 %, the reconstructed electrical conductivity of the bone was within 10 % errors. The accuracy increased with the electrical conductivity of the bone, as expected. This indicates that the present technique provides more accurate information for osteoporotic bones. It should be noted that tile simulation is based on a simple two phase image for the bone and the surrounding soft tissue when its anatomical information is provided. Nevertheless, the study indicates the possibility that the EIT technique may be used as a new means to detect the bone loss leading to osteoporotic fractures.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.13-17
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• 2010

Purpose: Partial volume effect (PVE) is the phenomenon to lower the accuracy of image due to low estimate, which is to occur from PET/CT 3D image acquisition. The more resolution is declined and the lesion is small, the more it causes a big error. So that it can influence the test result. Studied the optimum image reconstruction method by using variation of parameter, which can influence the PVE. Materials and Methods: It acquires the image in each size spheres which is injected $^{18}F$-FDG to hot site and background in the ratio 4:1 for 10 minutes by using NEMA 2001 IEC phantom in GE Discovey STE 16. The iterative reconstruction is used and gives variety to iteration 2-50 times, subset number 1-56. The analysis's fixed region of interest in detail part of image and compute % difference and signal to noise ratio (SNR) using $SUV_{max}$. Results: It's measured that $SUV_{max}$ of 10 mm spheres, which is changed subset number to 2, 5, 8, 20, 56 in fixed iteration to times, SNR is indicated 0.19, 0.30, 0.40, 0.48, 0.45. As well as each sphere's of total SNR is measured 2.73, 3.38, 3.64, 3.63, 3.38. Conclusion: In iteration 6th to 20th, it indicates similar value in % difference and SNR ($3.47{\pm}0.09$). Over 20th, it increases the phenomenon, which is placed low value on $SUV_{max}$ through the influence of noise. In addition, the identical iteration, it indicates that SNR is high value in 8th to 20th in variation of subset number. Therefore, to reduce partial volume effect of small lesion, it can be declined the partial volume effect in iteration 6 times, subset number 8~20 times, considering reconstruction time.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.155-159
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• 2004

Recently, there are many trials about Artificial neural networks : ANNs structure and studying method of researches for forecasting traffic volume. ANNs have a powerful capabilities of recognizing pattern with a flexible non-linear model. However, ANNs have some overfitting problems in dealing with a lot of parameters because of its non-linear problems. This research deals with the application of a variety of model selection criterion for cancellation of the overfitting problems. Especially, this aims at analyzing which the selecting model cancels the overfitting problems and guarantees the transferability from time measure. Results in this study are as follow. First, the model which is selecting in sample does not guarantees the best capabilities of out-of-sample. So to speak, the best model in sample is no relationship with the capabilities of out-of-sample like many existing researches. Second, in stability of model selecting criterion, AIC3, AICC, BIC are available but AIC4 has a large variation comparing with the best model. In time-series analysis and forecasting, we need more quantitable data analysis and another time-series analysis because uncertainty of a model can have an effect on correlation between in-sample and out-of-sample.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.139-155
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• 2009

For the last few decades, many studies have tried to explore and unveil venture companies' success factors and unique features in order to identify the sources of such companies' competitive advantages over their rivals. Such venture companies have shown tendency to give high returns for investors generally making the best use of information technology. For this reason, many venture companies are keen on attracting avid investors' attention. Investors generally make their investment decisions by carefully examining the evaluation criteria of the alternatives. To them, credit rating information provided by international rating agencies, such as Standard and Poor's, Moody's and Fitch is crucial source as to such pivotal concerns as companies stability, growth, and risk status. But these types of information are generated only for the companies issuing corporate bonds, not venture companies. Therefore, this study proposes a method for evaluating venture businesses by presenting our recent empirical results using financial data of Korean venture companies listed on KOSDAQ in Korea exchange. In addition, this paper used multi-class SVM for the prediction of DEA-based efficiency rating for venture businesses, which was derived from our proposed method. Our approach sheds light on ways to locate efficient companies generating high level of profits. Above all, in determining effective ways to evaluate a venture firm's efficiency, it is important to understand the major contributing factors of such efficiency. Therefore, this paper is constructed on the basis of following two ideas to classify which companies are more efficient venture companies: i) making DEA based multi-class rating for sample companies and ii) developing multi-class SVM-based efficiency prediction model for classifying all companies. First, the Data Envelopment Analysis(DEA) is a non-parametric multiple input-output efficiency technique that measures the relative efficiency of decision making units(DMUs) using a linear programming based model. It is non-parametric because it requires no assumption on the shape or parameters of the underlying production function. DEA has been already widely applied for evaluating the relative efficiency of DMUs. Recently, a number of DEA based studies have evaluated the efficiency of various types of companies, such as internet companies and venture companies. It has been also applied to corporate credit ratings. In this study we utilized DEA for sorting venture companies by efficiency based ratings. The Support Vector Machine(SVM), on the other hand, is a popular technique for solving data classification problems. In this paper, we employed SVM to classify the efficiency ratings in IT venture companies according to the results of DEA. The SVM method was first developed by Vapnik (1995). As one of many machine learning techniques, SVM is based on a statistical theory. Thus far, the method has shown good performances especially in generalizing capacity in classification tasks, resulting in numerous applications in many areas of business, SVM is basically the algorithm that finds the maximum margin hyperplane, which is the maximum separation between classes. According to this method, support vectors are the closest to the maximum margin hyperplane. If it is impossible to classify, we can use the kernel function. In the case of nonlinear class boundaries, we can transform the inputs into a high-dimensional feature space, This is the original input space and is mapped into a high-dimensional dot-product space. Many studies applied SVM to the prediction of bankruptcy, the forecast a financial time series, and the problem of estimating credit rating, In this study we employed SVM for developing data mining-based efficiency prediction model. We used the Gaussian radial function as a kernel function of SVM. In multi-class SVM, we adopted one-against-one approach between binary classification method and two all-together methods, proposed by Weston and Watkins(1999) and Crammer and Singer(2000), respectively. In this research, we used corporate information of 154 companies listed on KOSDAQ market in Korea exchange. We obtained companies' financial information of 2005 from the KIS(Korea Information Service, Inc.). Using this data, we made multi-class rating with DEA efficiency and built multi-class prediction model based data mining. Among three manners of multi-classification, the hit ratio of the Weston and Watkins method is the best in the test data set. In multi classification problems as efficiency ratings of venture business, it is very useful for investors to know the class with errors, one class difference, when it is difficult to find out the accurate class in the actual market. So we presented accuracy results within 1-class errors, and the Weston and Watkins method showed 85.7% accuracy in our test samples. We conclude that the DEA based multi-class approach in venture business generates more information than the binary classification problem, notwithstanding its efficiency level. We believe this model can help investors in decision making as it provides a reliably tool to evaluate venture companies in the financial domain. For the future research, we perceive the need to enhance such areas as the variable selection process, the parameter selection of kernel function, the generalization, and the sample size of multi-class.

• Clinical and Experimental Pediatrics
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• v.51 no.8
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• pp.842-847
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• 2008

Purpose : Measurement of forced expiratory volume in 1 second ($FEV_1$) is usually difficult to obtain in children under six years of age because it requires active cooperation. This study evaluates the sensitivity of impulse oscillometry system (IOS) parameters for detecting airway obstruction in comparison with $FEV_1$. Methods : We studied 174 children who performed the lung function and methacholine challenge tests to diagnose asthma by IOS and spirometry. Children were divided into two subgroups according to their $PC_{20}$, which is a parameter for bronchial sensitivity. We compared IOS parameters with $FEV_1$ at the baseline, post-methacholine challenge, and evaluated their correlation. Results : At the baseline, reactance at 5 Hz (X5) and resistance at 5 Hz (R5) significantly differed between the $PC_{20}$ positive ($PC_{20}{\leq}16mg/mL$) group and $PC_{20}$ negative ($PC_{20}$ >16 mg/mL) group; however, $FEV_1$, $FEV_1$ % predicted, $FEV_1_-Zs$ (Z score) did not differ. $FEV_1$ is correlated with X5 (r=0.45, P<0.01) and R5 (r=-0.69, P<0.01). $FEV_1_-Zs$ is also correlated with X5_Zs (r=-0.26, P<0.01) and R5_Zs (r=-0.31, P<0.01). After the methacholine challenge test, dose-response slopes in $FEV_1$ and X5 significantly differed between the two subgroups (P<0.05). Conclusion : IOS parameters were more discriminative than $FEV_1$ for detecting decreased baseline lung function between two subgroups and have a good correlation with $FEV_1$.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.46-46
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• 2011

Severe sediment erosion during floods occur disaster and economic losses, but general sediment erosion is basic mechanism to move sediment from upstream to downstream river. In addition, it is important process to change river form. Check dam, which is constructed in mountain stream, play a vital role such as control of sudden debris flow, but it has negative aspects to river ecosystem. Now a day, check dam of open type is an alternative plan to recover river biological diversity and ecosystem through sediment transport while maintaining the function of disaster control. The purpose of this paper is to verify sediment erosion progress of river bottom and bank as first step for river restoration after dam slit by cross-sectional shear stress and critical shear stress. Study area is upstream reach of slit check dam in mountain stream, named Wasada, in Japan. The check dam was slit with two passages in August, 2010. The transects were surveyed for four upstream cross-sections, 7.4 m, 34 m, 86 m, and 150 m distance from dam in October 2010. Sediment size was surveyed at river bottom and bank. Sediment of cobble size was found at the wetted bottom, and small size particles of sand to medium gravel composed river bank. Discharge was $2.5\;m^3/s$ and bottom slope was 0.027 m/m. Excess shear stress (${\tau}_{ex}$) was calculated for hydraulic erosion by subtracting the values of critical shear stress (${\tau}_{c}$) from the value of shear stress (${\tau}$) at river bottom and bank (${\tau}_{ex}=\tau-{\tau}_c$). Shear stress of river bottom (${\tau}_{bottom}$) was calculated using the cross-sectional shear stress, and bank shear stress (${\tau}_{bank}$) was calculated from the method of Flintham and Carling (1988). $${\tau}_{bank}={\tau}^*SF_{bank}((B+P_{bed})/(2^*P_{bank}))$$ where $SF_{bank}=1.77(P_{bed}/p_{bank}+1.5)^{-1.4}$, B is the water surface width, $P_{bed}$ and $P_{bank}$ are wetted parameter of the bed and bank. Estimated values for ${\tau}_{bottom}$ for a flow of $2.5\;m^3/s$ were lower as 25.0 (7.5 m cross-section), 25.7 (34 m), 21.3 (86 m) and 19.8 (150 m), in N/$m^2$, than critical shear stress (${\tau}_c=62.1\;N/m^2$) with cobble of 64 mm. The values were insufficient to erode cobble sediment. In contrast, even if the values of ${\tau}_{bank}$ were lower than the values for ${\tau}_{bottom}$ as 18.7 (7.5 m), 19.3 (34 m), 16.1 (86 m) and 14.7 (150 m), in N/$m^2$, excess shear stresses were calculated at the three cross-sections of 7.5 m, 34 m, and 86 m distances compare with ${\tau}_c$ is 15.5 N/$m^2$ of 16mm gravel. Bank shear stresses were sufficient for erosion of the medium gravel to sand. Therefore there is potential to erode lateral bank than downward erosion in a flow of $2.5\;m^3/s$. Undercutting of the wetted bank can causes bank scour or collapse, therefore this channel has potential to become wider at the same time. This research is about a potential of sediment erosion, and the result could not verify with real data. Therefore it need next step for verification. In addition an erosion mechanism for river restoration is not simple because discharge distribution is variable by snow-melting or rainy season, and a function for disaster control will recover by big precipitation event. Therefore it needs to consider the relationship between continuous discharge change and sediment erosion.

• Journal of Animal Science and Technology
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• v.49 no.6
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• pp.699-710
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• 2007

This study was conducted to estimate the genetic parameters and their relationships with weight traits of the steers and bulls in the Hanwoo population. The data used were weights and weight gain of performance and progeny test from 6,024 heads of Hanwoo. Data of performance test consisted of total 3,737 heads raised from August, 1989 to September, 2005. The number of the records of progeny test was total 2,287 heads from August, 1996 to June, 2004. The heritabilities and correlations for the body weights at the ages of 6 months, 12 months and 24 months and average daily gain were estimated by DFREML. Overall means and standard deviations of body weights at 6 and 12 months of age and average daily gain(ADG) from the data of performance test were 181.72±30.22kg, 351.48±40.24kg, 998.07±153.84g, respectively. Overall means and standard deviations of body weights at 6, 12, and 24 month of age and ADG from the data of progeny test were 169.18±32.82kg, 229.37±44.57kg, 570.45±64.36kg and 739.41± 172.14g, respectively. The heritability estimates of the body weight at 6, 12 month and ADG from the performance test were 0.54±0.06, 0.60±0.06 and 0.23±0.04, respectively. The heritability estimates of the body weight at 6, 12, 24 month and ADG from the progeny test were 0.80±0.08, 0.50±0.07, 0.46±0.07 and 0.07±0.03, respectively.

• The Korean Journal of Food And Nutrition
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• v.26 no.1
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• pp.66-77
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• 2013

In this study, we investigated the preventive effects of the mulberry leaf tea fermented by Monascus pilosus on high fat-induced obesity, hyperlipidemia, and fatty liver in mice. Non-fermented mulberry leaf tea powder (UM) and fermented mulberry leaf tea powder (FM) were supplemented with high-fat diet at 2% (wt/wt) dosage for 8 weeks. Both UM and FM lowered body weight gain, feed efficiency ratio, epididymal fat, serum triglyceride, total cholesterol and LDL-cholesterol increased markedly with high fat diet (HC) in mice. FM showed more significant effects when it was compared with UM. In addition, Hepatic lipid peroxides and xanthin oxidase activities of the UM and FM were significantly lower than those of HC, despite the lack of a big difference in the amount of hepatic GSH. Activities of ROS scavenging enzymes and serum alanine aminotransferase activity were also examined as a parameter of hepatic damage. The UM and FM groups showed a recovery to NC group from significant changes induced by HC. Finally, histopathological analyses of liver samples revealed a decrease of lipid accumulation in hepatocytes in the UM and FM groups. These results suggest that UM and especially FM can reduce the development of obesity, hyperlipidemia and fatty liver.