• 한국지진공학회논문집
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• 제22권4호
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• pp.253-259
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• 2018

Structure behaviors resulting from an earthquake are experimentally simulated mainly through a shaking table test. As for large-scale structures, however, size effects over a miniature may make it difficult to assess actual behaviors properly. To address this problem, research on the hybrid simulation is being conducted actively. This method is to implement numerical analysis on framework members that affect the general behavior of the structure dominantly through an actual scale experiment and on the rest parts by applying the substructuring technique. However, existing studies on hybrid simulation focus mainly on Slow experimental methods, which are disadvantageous in that it is unable to assess behaviors close to the actual level if material properties change depending on the speed or the influence of inertial force is significant. The present study aims to establish a Real-time hybrid simulation system capable of excitation based on the actual time history and to verify its performance and applicability. The hybrid simulation system built up in this study utilizes the ATS Compensator system, CR integrator, etc. in order to make the target displacement the same with the measured displacement on the basis of MATLAB/Simulink. The target structure was a 2-span bridge and an RC pier to support it was produced as an experimental model in order for the shaking table test and Slow and Real-time hybrid simulations. Behaviors that result from the earthquake of El Centro were examined, and the results were analyzed comparatively. In comparison with the results of the shaking table test, the Real-time hybrid simulation produced more similar maximum displacement and vibration behaviors than the Slow hybrid simulation. Hence, it is thought that the Real-time hybrid simulation proposed in this study can be utilized usefully in seismic capacity assessment of structural systems such as RC pier that are highly non-linear and time-dependent.

• 한국산학기술학회논문지
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• 제8권3호
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• pp.563-568
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• 2007

본 논문에서는 EVRC 시스템에 사용되어지는 실근 방식의 계산량 감소 알고리즘을 치안한다. 실근 방법에서는 다항식에서의 근을 구하여 LSP로 변환하는 과정이 필요하다. 그러나, 근을 구하는 과정에서 주파수 대역을 순차적으로 검색하므로 계산시간이 많이 소요된다. LSP 파라미터의 중요한 특징은 대부분의 계수가 특정 주파수 대역에 주로 분포한다는 것이다. 그러므로, 본 논문에서는 실근 방식에서의 계산시간을 줄이기 위하여 1KHz 대역까지는 선형적이고 1KHz 대역 이상에서는 로그 스케일인 멜 스케일을 사용하였다. 실근 방식과 제안한 방법을 비교하기 위하여 두 가지를 측정하였다. 첫째, 제안한 방법에서의 LSP 파라미터의 값과 실근방식에서의 LSP 파라미터 값을 비교하였다. 둘째, 계산 시간 감소율을 측정하였다. 실험결과, LSP 파라미터의 값은 변화하지 않았으며 계산량은 약 48% 정도 감소하였다.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.1243-1244
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• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.

• 신재생에너지
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• 제4권2호
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• pp.87-93
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• 2008

Wind tunnel test for the 12% scaled model of NREL Phase VI wind turbine was conducted in KARI low speed wind tunnel for $2006{\sim}2007$. The 1st and 2nd test was designed to find out the wind tunnel test method for the blade manufacturing accuracy and surface treatment method by using the composite and aluminum blades. And the 3rd test was designed to study the scale effect. The chord extension method which was used for Bo-105 40% scaled model was adapted for scale effect correction. Test results shows that the chord extension method works well for the torque slope but the maximum torque for scaled model is about 8% below than the real scale model. New correction method to correct this offset was proposed.

• 대한수학회논문집
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• 제22권1호
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• pp.91-109
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• 2007

In this paper, we derive a change of scale formula for conditional Wiener integrals, as integral transforms, of possibly unbounded functions over Wiener paths in abstract Wiener space. In fact, we derive the change of scale formula for the product of the functions in a Banach algebra which is equivalent to both the Fresnel class and the space of measures of bounded variation over a real separable Hilbert space, and the $L_p-type$cylinder functions over Wiener paths in abstract Wiener space. As an application of the result, we obtain a change of scale formula for the conditional analytic Fourier-Feynman transform of the product of the functions.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2010년도 춘계 학술발표회
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• pp.1094-1103
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• 2010

The safety of pile foundation is getting declined when the pile foundation acting on lateral load is exposed by dredging. So appropriate reinforcement is needed for stability secure. Thus, in this study, the stability variation and reinforcement range caused by dredging is estimated on the basis of down scale test. The scale effect is determined by real scale numerical analysis. the behavior of pile by dredging stages is estimated by load control type. The credibility is verified through the comparison between down scale model test and numerical analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권4호
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• pp.1846-1863
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• 2016

High dynamic range (HDR) images can present the perfect real scene and rich color information. A commonly encountered problem in practical applications is how to well visualize HDR images on standard display devices. In this paper, we propose a multi-scale decomposition method using guided filtering for HDR image tone mapping. In our algorithm, HDR images are directly decomposed into three layers：base layer, coarse scale detail layer and fine detail layer. We propose an effective function to compress the base layer and the coarse scale detail layer. An adaptive function is also proposed for detail adjustment. Experimental results show that the proposed algorithm effectively accomplishes dynamic range compression and maintains good global contrast as well as local contrast. It also presents more image details and keeps high color saturation.

• 조명전기설비학회논문지
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• 제26권10호
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• pp.72-80
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• 2012

In general, electronic conveyor scales are installed in a relatively distributed manner on the crushed rock and sand production site. It is one of the time-consuming and difficult engineering works to monitor and control the plant operation status such as the management of measuring data, malfunction of belt conveyor, and fault of electronic conveyor scale. Therefore, to alleviate the inefficient problems and to monitor the operating plant in the online and remote control room, a remote calibration and real-time monitoring system, which is practically applied to the electronic conveyor scale system and verified by onsite experiment, is developed based on the LabVIEW.

• Communications for Statistical Applications and Methods
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• 제27권4호
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• pp.397-412
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• 2020

In this paper, a notion of data depth is used to propose nonparametric multivariate two sample tests for difference between scale parameters. Data depth can be used to measure the centrality or outlying-ness of the multivariate data point relative to data cloud. A difference in the scale parameters indicates the difference in the depth values of a multivariate data point. By observing this fact on a depth vs depth plot (DD-plot), we propose nonparametric multivariate two sample tests for scale parameters of multivariate distributions. The p-values of these proposed tests are obtained by using Fisher's permutation approach. The power performance of these proposed tests has been reported for few symmetric and skewed multivariate distributions with the existing tests. Illustration with real-life data is also provided.

• 한국농림기상학회:학술대회논문집
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• 한국농림기상학회 2014년도 추계 학술발표논문집
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• pp.74-85
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• 2014

This study is a part of "Early Warning Service for Weather Risk Management in Climate-smart Agriculture", describes the delivery techniques from 840 catchment scale weather warning information using 150 counties unit special weather report(alarm, warning) released from KMA(Korea Meteorological Administration) and chronic weather warning information based on daily weather data from 76 synoptic stations. Catchment weather hazard warning service express a sequential risk index map generated by countries report occurs and report grade(alarm, warning) convert to catchment scale using zonal summarizing method. Additional services were chronic weather warning service at crop growth and accumulated more than 4 weeks, based on an unsuitable weather conditions, representing a relative risk compared to its catchment climatological normal conditions (normal distribution ) in addition to special weather report. Service provided by a real-time catchment scale map overlaid with VWORLD open platform operated by Ministry of Land, Infrastructure and Transport. Also provide a foundation for weather risk information to inform individual farmers to farm located within the catchment zone warning occur.