• The Journal of the Korea Contents Association
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• v.9 no.2
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• pp.432-438
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• 2009

In this paper, we evaluated the performance of the automatic classifier applied for the discrimination of acute alcoholic liver injury and chronic liver fibrosis. The classifier uses the discriminant peaks of the preprocessed Raman spectrum as a feature set. In preprocessing step, we subtract baseline and apply Savitzky-Golay smoothing filter which is known to be useful at preserving peaks. After identifying discriminant peaks from the spectra, we carried out the classification experiments using MAP and neural networks. According to the experimental results, the classifier shows the promising results to diagnosis alcoholic liver injury and chronic liver fibrosis. Classification results over 80% means that the peaks used as a feature set is useful for diagnosing liver disease.

• Proceedings of the KSRS Conference
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• v.2
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• pp.981-984
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• 2006

Oil pollution of the ocean is a major environmental problem, especially in its coastal zones. Synthetic aperture radar (SAR) flown on satellites, such as ERS-2 and Envisat, has been proved to be a useful tool in oil spill monitoring due to its wide coverage, day and night, and all-weather capability. The total 120 SAR images containing oil spill over the East China Sea were collected and analyzed, ranging in date from July 23, 2002 to November 11, 2005. After preprocessed, SAR images were segmented by adaptive threshold method. The oil spill images were incorporated into GIS after distinguished from look-like phenomena, finally we presented the oil spills distribution map for the East China Sea. The wide-swath and quick-looks SAR imagery for mapping of oil spill distribution over large marine areas were proved to be useful when full resolution data are not available. After the temporal and spatial distribution of the oil spills were analyzed, we found that most of oil spills were distributed along the main ship routes, which means the illegal discharge by ships, and the occurrence of oil spill detected on SAR images acquired during morning and summer is much higher than during evening and winter.

• Journal of Forest and Environmental Science
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• v.30 no.2
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• pp.233-242
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• 2014

Estimating above-ground biomass is important in establishing an applicable methodology of Measurement, Reporting and Verification (MRV) System for Reducing Emissions from Deforestation and Forest Degradation-Plus (REDD+). We developed an estimation model of diameter at breast height (DBH) from IKONOS-2 image that led to above-ground biomass estimation (AGB). The IKONOS image was preprocessed with dark object subtraction and topographic effect correction prior to watershed segmentation for tree crown delineation. Compared to the field observation, the overall segmentation accuracy was 64%. Crown detection percent had a strong negative correlation to tree density. In addition, satellite-based crown area had the highest correlation with the field measured DBH. We then developed the DBH allometric model that explained 74% of the data variance. In average, the estimated DBH was very similar to the measured DBH as well as for AGB. Overall, this method can potentially be applied to estimate AGB over a relatively large and remote tropical forest in Northern Borneo.

• Korean Journal of Oriental Medicine
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• v.12 no.2 s.17
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• pp.93-101
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• 2006

Pulse feeling is one of the most important diagnosis method in Oriental medicine. But it is not easy to make an objective and standardized diagnosis. In this study, we found how to quantify diagnosis. Specially dally the high practicality in clinic, we search some parameters especially well-related to floating and sinking pulse by statistic analysis. By extension, we find the pulse patterns of the floating and sinking pulse. We choose 15 subjects diagnosed as floating pulse and 15 subjects diagnosed as sinking pulse by oriental doctors. And their pulse signals were acquired by Pulse analyzer which has piezoresistive pressure sensor. For the quantification of the floating and sinking pulse, at first, we examined the parameters which were highly correlated with oriental doctor's diagnosis. And then we derived pulse patterns of the floating-sinking pulse from preprocessed signal and its ensemble average. We also looked trend variation (PH-Curve) between contact and pulse pressure. As a result, statistically there is the biggest difference between contact pressure, the maximum pulse pressure, diastolic area (Ad) and floating and sinking data. Through the PH-Curve, which represented the relationship between contact and pulse pressure, we could divide the floating and sinking pulse clearly. As a basic research of pulse diagnosis algorithm, we can contribute to select essential parameters in diagnosis algorithm And using these diagnosis method, we expect to find typical pulse patterns and some useful parameters about other pulses like slow/rapid, large/fine pulse and so on. We hope that this study will contribute pulse objectification.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.2
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• pp.80-85
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• 2011

Alzheimer's disease and Parkinson's disease are the most common neurodegenerative disorders. In this paper, we proposed a feature extraction method for classification of AD and PD based on micro-Raman spectra from platelet. The first step of the preprocessing is a simple smoothing followed by background elimination to the original spectra to make it easy to measure the intensity of the peaks. The last step of the preprocessing was peak alignment with the reference peak. After the inspection of the preprocessed spectra, we found that proportion of two peak intensity at 743 and $757cm^{-1}$ and peak intensity at 1248 and $1448cm^{-1}$ are the most discriminative features. Then we apply mapstd method for normalization. The method returned data with means to 0 and deviation to 1. With these three features, the classification result involving 263 spectra showed about 95.8% true classification in case of MAP(maximum a posteriori probability).

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.105-112
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• 2006

In this study, we propose a simple preprocessing method for classification of basal cell carcinoma (BCC), which is one of the most common skin cancer. The preprocessing step consists of data clipping with a half Hanning window and dimension reduction with principal components analysis (PCA). The application of the half Hanning window deemphasizes the peak near $1650cm^{-1}$ and improves classification performance by lowering the false negative ratio. Classification results with various classifiers are presented to show the effectiveness of the proposed method. The classifiers include maximum a posteriori probability (MAP), k-nearest neighbor (KNN), probabilistic neural network (PNN), multilayer perceptron(MLP), support vector machine (SVM) and minimum squared error (MSE) classification. Classification results with KNN involving 216 spectra preprocessed with the proposed method gave 97.3% sensitivity, which is very promising results for automatic BCC detection.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.27 no.12
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• pp.609-619
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• 2015

A preprocessing scheme utilizing multi-division of the ROI (region of interest) in a chemiluminescence image during inversion is proposed. The resulting inverted image shows the flame's structure, which can be useful for studying combustion instability. The flame structure is often quantitatively visualized with PLIF (planar laser-induced fluorescence) images as well. The chemiluminescence image, which is a line-integral of the flame, needs to be preprocessed before inversion, mainly due to the inherent noise and the assumption of axisymmetry during the inversion. The feasibility of the multi-division preprocessing technique has been tested with experimentally-obtained OH PLIF and $OH^*$ chemiluminescence images of jet and swirl-stabilized flames burning substitute natural gas (SNG). It turns out that the technique outperforms two conventional methods, specifically, the technique without preprocessing and the one with uni-division, reconstructing the SNG flame structures much better than its two counterparts when compared using corresponding OH PLIF images. The characteristics of the optimum degree of polynomials to be applied for curve-fitting of the flame region data for the multi-division method involving two flames has also been investigated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4C
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• pp.277-282
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• 2012

In this paper, we present a real-time eye contact system for realistic telepresence using a Kinect depth camera. In order to generate the eye contact image, we capture a pair of color and depth video. Then, the foreground single user is separated from the background. Since the raw depth data includes several types of noises, we perform a joint bilateral filtering method. We apply the discontinuity-adaptive depth filter to the filtered depth map to reduce the disocclusion area. From the color image and the preprocessed depth map, we construct a user mesh model at the virtual viewpoint. The entire system is implemented through GPU-based parallel programming for real-time processing. Experimental results have shown that the proposed eye contact system is efficient in realizing eye contact, providing the realistic telepresence.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.6
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• pp.1327-1337
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• 2019

With the growth of the IoT market, malware security threats are steadily increasing for devices that use the linux architecture. However, except for the major malware causing serious security damage such as Mirai, there is no related technology or research of security community about linux malware. In addition, the diversity of devices, vendors, and architectures in the IoT environment is further intensifying, and the difficulty in handling linux malware is also increasing. Therefore, in this paper, we propose an analysis system based on ELF which is the main format of linux architecture, and a binary based analysis system considering IoT environment. The ELF-based analysis system can be pre-classified for a large number of malicious codes at a relatively high speed and a relatively low-speed binary-based analysis system can classify all the data that are not preprocessed. These two processes are supposed to complement each other and effectively classify linux-based malware.

• Journal of Biomedical Engineering Research
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• v.29 no.3
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• pp.212-221
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• 2008

The total hip replacement (THR) has been used as the most effective way to restore the function of damaged hip joint. However, various factors have caused some side effects after the THR. Unfortunately, the success of the THR have been decided only by the proficiency of surgeons so far. Hence, It is necessary to find the way to minimize the side effect caused by those factors. The purpose of this study was to suggest the definite data, which can be used to design and choose the optimal hip implant. Using finite element analysis (FEA), the biomechanical condition of bone cement was evaluated. Stress patterns were analyzed in three conditions: cement mantle, procimal femur and stem-cement contact surface. Additionally, micro-motion was analyzed in the stem-cement contact surface. The 3-D femur model was reconstructed from 2-D computerized tomography (CT) images. Raw CT images were preprocessed by image processing technique (i.e. edge detection). In this study, automated edge detection system was created by MATLAB coding for effective and rapid image processing. The 3-D femur model was reconstructed based on anatomical parameters. The stem shape was designed using that parameters. The analysis of the finite element models was performed with the variation of parameters. The biomechanical influence of each parameter was analyzed and derived optimal parameters. Moreover, the results of FE A using commercial stem model (Zimmer's V erSys) were similar to the results of stem model that was used in this study. Through the study, the improved designs and optimal factors for clinical application were suggested. We expect that the results can suggest solutions to minimize various side effects.