• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.4
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• pp.1-10
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• 2023

In the seismic design of structures, seismic forces are calculated based on structural models and analysis. In order to accurately address the dynamic characteristics of the actual structure in the structural model, calibration based on actual measurements is required. In this study, a 4-story frame test specimen was manufactured to simulate frame building, accelerometers were attached at each floor, and 1-axis shaking table test was performed. The natural period of the specimen was similar to that of the actual 4 story frame building, and the columns were designed to behave with double-curvature having the infinite stiffness of the horizontal members. To investigate the effects seismic waves characteristics, historical and artificial excitations with various frequencies and acceleration magnitudes were applied. The natural frequencies, damping ratios, and mode shapes were obtained using frequency response functions obtained from dynamic response signals, and the mode vector deviations according to the input seismic waves were verified using the Mode assurance criterion (MAC). In addition, the damping ratios obtained from the vibration tests were applied to the structural model, and the method with refined dynamic characteristics was validated by comparing the analysis results with the experimental data.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.103-112
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• 2009

In a nuclear power plant (NPP), periodic sensor calibrations are required to assure sensors are operating correctly. However, only a few faulty sensors are found to be calibrated. For the safe operation of an NPP and the reduction of unnecessary calibration, on-line calibration monitoring is needed. In this paper, principal component-based Auto-Associative support vector regression (PCSVR) was proposed for the sensor signal validation of the NPP. It utilizes the attractive merits of principal component analysis (PCA) for extracting predominant feature vectors and AASVR because it easily represents complicated processes that are difficult to model with analytical and mechanistic models. With the use of real plant startup data from the Kori Nuclear Power Plant Unit 3, SVR hyperparameters were optimized by the response surface methodology (RSM). Moreover the statistical techniques are integrated with PCSVR for the failure detection. The residuals between the estimated signals and the measured signals are tested by the Shewhart Control Chart, Exponentially Weighted Moving Average (EWMA), Cumulative Sum (CUSUM) and generalized likelihood ratio test (GLRT) to detect whether the sensors are failed or not. This study shows the GLRT can be a candidate for the detection of sensor drift.

• Parasites, Hosts and Diseases
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• v.61 no.3
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• pp.317-324
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• 2023

Standard- and large-sized eggs of Trichuris trichiura were found in the feces of schoolchildren in Yangon, Myanmar during epidemiological surveys and mass deworming with albendazole in 2017-2019. The standard-sized eggs were identified as those of T. trichiura, but it was necessary to exclude the possibility of the large-sized eggs belonging to Trichuris vulpis, a dog whipworm. We conducted morphological and molecular studies to determine the species of the 2 types of Trichuris eggs. Individual eggs of both sizes were isolated from Kato-Katz fecal smears (n=20) and mechanically destroyed using a 23G injection needle. Nuclear DNA was extracted, and the 18S rRNA region was sequenced in 15 standard-sized eggs and 15 large-sized eggs. The average size of standard-sized eggs (T. trichiura) was 55.2×26.1 ㎛ (range: 51.7-57.6×21.3-28.0 ㎛; n=97), whereas the size of large-sized eggs was 69.3×32.0 ㎛ (range: 65.1-76.4×30.1-34.5 ㎛; n=20), slightly smaller than the known size of T. vulpis. Regarding standard-sized eggs, the 18S rRNA nucleotide sequences exhibited 100% homology with T. trichiura deposited in GenBank and 88.6-90.5% homology with T. vulpis. Regarding large-sized eggs, the nucleotide sequences showed 99.8-100% homology with T. trichiura in GenBank and 89.6-90.7% homology with T. vulpis. Both standard- and large-sized eggs of Trichuris spp. found in Myanmar schoolchildren during 2017-2019 were morphologically and molecularly confirmed to belong to T. trichiura. The conversion of eggs from smaller to large sizes might be due to anthelmintic treatments with albendazole.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.3
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• pp.141-148
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• 2023

Accurate overlay metrology is essential to achieve high yields of semiconductor products. Overlay metrology performance is greatly affected by overlay target design and measurement method. Therefore, in order to improve the performance of the overlay target, measurement methods applicable to various targets are required. In this study, we propose a new algorithm that can measure image-based overlay. The proposed measurement algorithm can estimate the sub-pixel position by using a motion vector. The motion vector may estimate the position of the sub-pixel unit by applying a quadratic equation model through polynomial expansion using pixels in the selected region. The measurement method using the motion vector can calculate the stacking error in all directions at once, unlike the existing correlation coefficient-based measurement method that calculates the stacking error on the X-axis and the Y-axis, respectively. Therefore, more accurate overlay measurement is possible by reflecting the relationship between the X-axis and the Y-axis. However, since the amount of computation is increased compared to the existing correlation coefficient-based algorithm, more computation time may be required. The purpose of this study is not to present an algorithm improved over the existing method, but to suggest a direction for a new measurement method. Through the experimental results, it was confirmed that measurement results similar to those of the existing method could be obtained.

• Journal of the Korean Geotechnical Society
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• v.24 no.2
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• pp.67-75
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• 2008

It is interesting to note that distinct element method has been used extensively to model the response of micro and discontinuous behavior in geomechanics. Impressive advances related to response of distinct particles have been conducted and there were difficulties in considering fluid effect simultaneously. Current distinct element methods are progressively developed to solve particle-fluid coupling focused on fluid flow through soil, rock or porous medium. In this research, numerical simulations of fluid injection into particulate materials were conducted to observe cavity initiation and propagation using distinct element method. After generation of initial particles and wall elements, confining stress was applied by servo-control method. The fluid scheme solves the continuity and Navior-Stokes equations numerically, then derives pressure and velocity vectors for fixed grid by considering the existence of particles within the fluid cell. Fluid was injected as 7-step into the assembly in the x-direction from the inlet located at the center of the left boundary under confining stress condition, $0.1MP{\alpha}\;and\;0.5MP{\alpha}$, respectively. For each simulation, movement of particles, flow rate, fluid velocity, pressure history, wall stress including cavity initiation and propagation by interaction of flulid-paricles were analyzed.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.56-68
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• 2022

In this paper, we propose a compression method for multi-resolution feature maps for VCM. The proposed compression method removes the redundancy between the channels and resolution levels of the multi-resolution feature map through PCA-based transformation. According to each characteristic, the basis vectors and mean vector used for transformation, and the transformation coefficient obtained through the transformation are compressed using a VVC-based coder and DeepCABAC. In order to evaluate performance of the proposed method, the object detection performance was measured for the OpenImageV6 and COCO 2017 validation set, and the BD-rate of MPEG-VCM anchor and feature map compression anchor proposed in this paper was compared using bpp and mAP. As a result of the experiment, the proposed method shows a 25.71% BD-rate performance improvement compared to feature map compression anchor in OpenImageV6. Furthermore, for large objects of the COCO 2017 validation set, the BD-rate performance is improved by up to 43.72% compared to the MPEG-VCM anchor.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.3
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• pp.15-25
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• 2017

As the value and importance of softwares are growing up, software theft and piracy become a much larger problem. To tackle this problem, it is highly required to provide an accurate method for detecting software theft and piracy. Especially, while software theft is relatively easy in the case of Android applications (apps), screening illegal apps has not been properly performed in Android markets. In this paper, we propose a method to effectively measure the similarity between Android apps for detecting software theft at the executable file level. Our proposed method extracts method reference frequency and manifest information through static analysis of executable Android apps as the main features for similarity measurement. Each app is represented as an n-dimensional vectors with the features, and then cosine similarity is utilized as the similarity measure. We demonstrate the effectiveness of our proposed method by evaluating its accuracy in comparison with typical source code-based similarity measurement methods. As a result of the experiments for the Android apps whose source file and executable file are available side by side, we found that our similarity degree measured at the executable file level is almost equivalent to the existing well-known similarity degree measured at the source file level.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.67-69
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• 2021

Weather radar images can be used in a variety of ways because of their high visibility in terms of visuals. In other words it has the advantage of being able to grasp the flow of weather phenomena using not only the raw data of the weather radar, but also the change characteristics between consecutive images. In particular image processing techniques are gradually expanding in the field of meteorological research, and in the case of image data having high resolution such as weather radar images it is expected to produce useful information through a new approach called image processing techniques. In this study the weather phenomena flow was calculated as a vector from the change of the weather radar image according to time interval with the optical flow method, one of the image processing techniques. The characteristics of the weather phenomena to be analyzed were derived through vector analysis resolution suitable for the scale of weather, vector interpolation in regions where no radar echo exists, and the removal of relative flow vectors to distinguish the flow of specific weather and the entire atmosphere. Through this study, it is expected that not only the use of raw data of weather radar, but also the widening of the application area of weather radar, such as the use of unique characteristics of image data, and the active use of image processing techniques in the field of meteorology in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2B
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• pp.141-153
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• 2009

The occurrence causes of the extreme rainfall to happen in Korea can be distinguished with the typhoons and local downpours. The typhoon events attacked irregularly to induce the heavy rainfall, and the local downpour events mean a seasonal rain front and a local rainfall. Almost every year, the typhoons and local downpours that induced a heavy precipitation be generated extreme disasters like a flooding. Consequently, in this research, There were distinguished the causes of heavy rainfall events with the typhoons and the local downpours at Korea. Also, probability precipitation was computed according to the causes of the local downpour events. An evaluation of local downpours can be used for analysis of heavy rainfall event in short period like a flash flood. The methods of calculation of probability precipitation used the parametric frequency analysis and the Empirical Simulation Technique (EST). The correlation analysis was computed between annual maximum precipitation by local downpour events and sea surface temperature, moisture index for composition of input vectors. At the results of correlation analysis, there were revealed that the relations closely between annual maximum precipitation and sea surface temperature. Also, probability precipitation using EST are bigger than probability precipitation of frequency analysis on west-middle areas in Korea. Therefore, region of west-middle in Korea should prepare the extreme precipitation by local downpour events.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.279-289
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• 2006

The reconstruction of low dimension nonlinear behavior from the hydrologic time series has been an active area of research in the last decade. In this study, we present the applications of a powerful state space reconstruction methodology using the method of Support Vector Machines (SVM) to the Great Salt Lake (GSL) volume. SVMs are machine learning systems that use a hypothesis space of linear functions in a Kernel induced higher dimensional feature space. SVMs are optimized by minimizing a bound on a generalized error (risk) measure, rather than just the mean square error over a training set. The utility of this SVM regression approach is demonstrated through applications to the short term forecasts of the biweekly GSL volume. The SVM based reconstruction is used to develop time series forecasts for multiple lead times ranging from the period of two weeks to several months. The reliability of the algorithm in learning and forecasting the dynamics is tested using split sample sensitivity analyses, with a particular interest in forecasting extreme states. Unlike previously reported methodologies, SVMs are able to extract the dynamics using only a few past observed data points (Support Vectors, SV) out of the training examples. Considering statistical measures, the prediction model based on SVM demonstrated encouraging and promising results in a short-term prediction. Thus, the SVM method presented in this study suggests a competitive methodology for the forecast of hydrologic time series.