• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1347-1348
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• 2015

본 논문에서는 기상레이더 데이터에서 섞여있는 강수에코 및 비강수에코를 분류하기 위하여 Interval Type-2 FCM based RBFNN의 도움으로 사례 및 에코 분류기의 설계를 제안한다. 학습과 테스트 데이터는 현재 기상청에서 사용하는 UF radar data를 사용하였으며, 사례 분류기와 에코패턴 분류기의 데이터를 각각 생성한다. 전처리 과정인 사례 분류를 통하여 강수사례 혹은 비강수사례를 분류하여 강수사례일 경우 에코패턴분류를 진행하며, 비강수사례일 경우 데이터에 관측된 모든 반사도 값을 제거한다. 사례 및 에코 분류기는 Interval Type-2 FCM based RBFNN을 통하여 패턴분류를 진행하며, 패턴분류 성능을 확인한다. 또한 후반부 파라미터의 동정 시, 각 규칙에 파라미터를 전역적으로 구하는 LSE와 각 규칙에 대한 파라미터를 독립적으로 구하는 WSLE의 비교연구를 수행한다. 분류기의 성능을 확인하기 위하여 사례 분류 후 에코패턴분류의 결과는 현재 기상청에서 사용하고는 품질검사(QC) 데이터와 비교하여 평가하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.536-541
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• 2014

Data through meteorological radar includes ground echo, sea-clutter echo, anomalous propagation echo, clear echo and so on. Each echo is a kind of non-precipitation echoes and the characteristic of individual echoes is analyzed in order to identify with non-precipitation. Meteorological radar data is analyzed through pre-processing procedure because the data is given as big data. In this study, echo pattern classifier is designed to distinguish non-precipitation echoes from precipitation echo in meteorological radar data using RBFNNs and echo judgement module. Output performance is compared and analyzed by using both HCM clustering-based RBFNNs and FCM clustering-based RBFNNs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.957-960
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• 2013

Eco driving comprises the use of feedback information that informs the driver of vehicle performance. This paper evaluated the performance of feedback device that reported instantaneous fuel economy to drivers while driving. We took the measurement by getting data through OBD port from commercial vehicle covered 67 km on road. The changes observed in fuel efficiency were established 10.6 % improvement in fuel economy.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.242-247
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• 2015

In this study, we propose the design of Radial Basis Function Neural Network(RBFNN) classifier in order to classify between precipitation and non-precipitation echo. The characteristics of meteorological radar data is analyzed for classifying precipitation and non-precipitation echo. Input variables is selected as DZ, SDZ, VGZ, SPN, DZ_FR, VR by performing pre-processing of UF data based on the characteristics analysis and these are composed of training and test data. Finally, QC data being used in Korea Meteorological Administration is applied to compare with the performance results of proposed classifier.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.545-550
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• 2013

In pattern recognition field, data classification is an essential process for extracting meaningful information from data. Adaptive boosting algorithm, known as AdaBoost algorithm, is a kind of improved boosting algorithm for applying to real data analysis. It consists of weak classifiers, such as random guessing or random forest, which performance is slightly more than 50% and weights for combining the classifiers. And a strong classifier is created with the weak classifiers and the weights. In this paper, a research is performed using AdaBoost algorithm for detecting chaff echo which has similar characteristics to precipitation echo and interrupts weather forecasting. The entire process for implementing chaff echo classifier starts spatial and temporal clustering based on similarity with weather radar data. With them, learning data set is prepared that separated chaff echo and non-chaff echo, and the AdaBoost classifier is generated as a result. For verifying the classifier, actual chaff echo appearance case is applied, and it is confirmed that the classifier can distinguish chaff echo efficiently.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.12
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• pp.6114-6118
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• 2013

This study examined the ultrasonic pulse reflection method(UPRM) for testing each ultrasonic pulse waveform model(UPWM) based on weld defects. The sharp crack of a clear signal was generated. The echo height of the defective probes changed according to the location. In a long crack in a circle around the defective probes, the Swivel scanning echo height when using the particle was reduced drastically. The peaks in the echo were thin because the needle was pointed. The porosity defects arising from a single echo was sharp and crisp, but a number of pores of the collective reflection overlapped and ajagged echo was observed. Slag, slag inclusions, cracks, and defects at the Swivel scan of each particle using the echo shape showed difference in the degree. Cracks were revealed as sudden changes in the echo height of the slag inclusions: increase ${\rightarrow}$ decrease ${\rightarrow}$ increase ${\rightarrow}$ decrease. In addition, the location of a number of defects in the dense pore geometry, such as a typical echo sundry, revealed the shape in the slag. Poor penetration of the defect echo, revealed the cracks to have a sharp-edged, crack-like shape with an echo.

• Journal of the Korean Society of Radiology
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• v.15 no.6
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• pp.883-889
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• 2021

This study was conducted on 101 patients who visited hospital for abdominal ultrasonography from May 2020 to December 2020. The purpose of this study was to find out the elasticity according to the ultrasound images (echo pattern, splenomegaly, hepatitis) during the ultrasound examination using the shear wave elastography. The shear wave elastography value of the normal group of the echo pattern was 5.75±1.58 kPa, and the group with the abnormal echo pattern was 8.84±4.94 kPa, and the shear wave elastography value of the abnormal group was high (p<0.05). In normal spleen size, hepatic elasticity value was 6.33±2.54 kPa, and hepatic elasticity value of splenomegaly was 13.73±5.48 kPa. In the case of splenomegaly, the liver elasticity value was high, and there was a statistically significant difference (p<0.05). As the spleen size increased, the liver elasticity value increased by 1.485 times, and as hepatitis progressed, the liver elasticity value increased by 1.573 times (p<0.05). As a result of analysis of concordance between ultrasound imaging findings and shear wave elastography, the Kappa value was found to be as high as 0.922 (p<0.05), which showed high concordance between the two test methods. Additional comparisons of liver elasticity values in shearwave elastography tests along with liver ultrasound findings are thought to be of great help in diagnosing liver fibrosis.

• Korean Journal of Clinical Laboratory Science
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• v.56 no.3
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• pp.273-276
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• 2024

Spontaneous echo contrast is a swirling, smoke-like echographic pattern observed in B-mode ultrasound imaging, typically arising in areas of blood stasis or low-flow states. This hemodynamic disturbance generates low shear stress due to sluggish flow, leading to endothelial dysfunction and facilitating the activation of fibrinogen, a coagulation factor. Consequently, blood cells, including erythrocytes, readily aggregate, forming a spontaneous echo contrast, a precursor to thrombus formation. Spontaneous echo contrast is primarily found in the left atrium of patients with left atrial enlargement or the left atrial appendage of patients with atrial fibrillation. While less common, it can also be observed in the carotid arteries. This case report presents the imaging findings of spontaneous echo contrast detected during carotid duplex ultrasonography in a patient with metastatic cancer and discusses its clinical implications.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.969-972
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• 2013

In this paper, we presented high-pass OBU device to support eco driving for commercial vehicles such as heavy trucks. The proposed OBU is convergence OBU (On Board Units) platform with high-pass toll functions and eco driving functions. In order to verity performance of proposed OBU device, we conducted test drives on road.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.217-222
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• 2015

Clustering is one of important data mining techniques known as exploratory data analysis and is being applied in various engineering and scientific fields such as pattern recognition, remote sensing, and so on. The method organizes data by abstracting underlying structure either as a grouping of individuals or as a hierarchy of groups. Weather radar observes atmospheric objects by utilizing reflected signals and stores observed data in corresponding coordinate. To analyze the radar data, it is needed to be separately organized precipitation and non-precipitation echo based on similarities. Thus, this paper studies to apply clustering method to radar data. In addition, in order to solve the problem when precipitation echo locates close to non-precipitation echo, fuzzy logic based clustering method which can consider both distance and other properties such as reflectivity and Doppler velocity is suggested in this paper. By using actual cases, the suggested clustering method derives better results than previous method in near-located precipitation and non-precipitation echo case.