• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1376-1384
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• 2013

In this paper, we propose an automaticdetection method of foreign bodies through template matching in industrial CT volume data. Our method is composed of three main steps. First,Indown-sampling data, the product region is separated from background after noise reduction and initial foreign-body candidates are extracted using mean and standard deviation of the product region. Then foreign-body candidates are extracted using K-means clustering. Second, the foreign body with different intensity of product region is detected using template matching. At this time, the template matching is performed by evaluating SSD orjoint entropy according to the size of detected foreign-body candidates. Third, to improve thedetection rate of foreign body in original volume data, final foreign bodiesare detected using percolation method. For the performance evaluation of our method, industrial CT volume data and simulation data are used. Then visual inspection and accuracy assessment are performed and processing time is measured. For accuracy assessment, density-based detection method is used as comparative method and Dice's coefficient is measured.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.2
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• pp.184-193
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• 2015

This paper proposes a cost-efficient and automatic method for large data acquisition from a test chip without expensive equipment to characterize random process variation in an integrated circuit. Our method requires only a test chip, a personal computer, a cheap digital-to-analog converter, a controller and multimeters, and thus large volume measurement can be performed on an office desk at low cost. To demonstrate the proposed method, we designed a test chip with a current model logic driver and an array of 128 current mirrors that mimic the random process variation of the driver's tail current mirror. Using our method, we characterized the random process variation of the driver's voltage due to the random process variation on the driver's tail current mirror from large volume measurement data. The statistical characteristics of the driver's output voltage calculated from the measured data are compared with Monte Carlo simulation. The difference between the measured and the simulated averages and standard deviations are less than 20% showing that we can easily characterize the random process variation at low cost by using our cost-efficient automatic large data acquisition method.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.201-205
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• 1997

With the recent advance of Web and its associated technologies, information sharing on distribute computing environments has gained a great amount of attention from many researchers in many application areas, such as medicine, engineering, and business. One basic requirement of distributed medical consultation systems is that geographically dispersed, disparate participants are allowed to exchange information readily with each other. Such software also needs to be supported on a broad range of computer platforms to increase the software's accessibility. In this paper, the development of world-wide-web based medical consultation system or radiology imaging is addressed to provide the platform independence and great accessibility. The system supports sharing of 3-dimensional objects. We use VRML (Virtual Reality Modeling Language), which is the de-facto standard in 3-D modeling on the Web. 3-D objects are reconstructed from CT or MRI volume data using a VRML format, which can be viewed and manipulated easily in Web-browsers with a VRML plug-in. A Marching cubes method is used in the transformation of scanned volume data set to polygonal surfaces of VRML. A decimation algorithm is adopted to reduce the number of meshes in the resulting VRML file. 3-D volume data are often very large-sized, and hence loading the data on PC level computers requires a significant reduction of the size of the data, while minimizing the loss of the original shape information. This is also important to decrease network delays. A prototype system has been implemented (http://netopia.snu.ac.kr/-cyber/). and several sessions of experiments are carried out.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.5
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• pp.693-701
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• 2018

Transfer types at the Seoul Metropolitan Urban Railway Stations can be classified into transfer between lines and station transfer. Station transfer is defined as occurring when either 1) the operating line that operates the tag-in card-reader and that operating the first train boarded by the passenger are different; or 2) the line operating the final alighted train and that operating the tag-out card-reader are different. In existing research, transportation card data is used to estimate transfer volume between lines, but excludes station transfer volume which leads to underestimation of volume through transfer passages. This research applies transportation card data to a method for station transfer volume estimation. To achieve this, the passenger path choice model is made appropriate for station transfer estimation using a modified big-node based network construction and data structure method. Case study analysis is performed using about 8 million daily data inputs from the metropolitan urban railway.

• Journal of the Korean Geosynthetics Society
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• v.18 no.4
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• pp.87-95
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• 2019

Earth-work calculation is the important data for estimating the optimal construction cost at the construction site. Earth-work calculations require the accurate terrain data and precise soil volume calculations. Drone surveying technology provides accurate topography in a short time and economic advantages. In this paper, a drone surveying technique was used to derive a high precision soil volume calculation system. Field demonstration were performed to verify the accuracy of the volume measurement system. The results of earth-work calculation using drone survey were compared with those of GPS surveying. In addition, the developed earth-work volume calculation algorithm is compared with the existing aerial survey software (Pix4D) to verify the accuracy.

• Journal of Korea Water Resources Association
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• v.45 no.5
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• pp.473-480
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• 2012

A two-dimensional depth-integrated hydrodynamic and a depth-averaged passive scalar transport models were developed by using a Compact Finite Volume Method (CFVM) which can assure a higher order accuracy. A typical wave current interaction experimental data set was compared with the computed results by the proposed CFVM model, and resonable agreements were observed from the comparisons. One and two dimensional scalar advection tests were conducted, and very close agreements were observed with very little numerical diffusion. Finally, a turbulent mixing simulation was done in an open channel flow, and a reasonable similarity with LES data was observed.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.1 s.39
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• pp.55-59
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• 2007

This study is aimed to acquire the depth information and measure the water volume of reservoir using the robot-ship equipped with GPS and echosounder. Robot-ship is an automatic system for measuring exact depth and bed topography. According to field experiment results, measured water volume by the robot-ship data was not much exceeding 6.8% in comparison with existing water volume data, and it was guessed because of sediments of reservoir bottom. The robot-ship could be used to acquire economically and exactly the water depth and bed topography of reservoirs, dams, rivers and so on.

• Nuclear Engineering and Technology
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• v.29 no.3
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• pp.218-228
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• 1997

Correlations between the amount of DAW (Dry Active Waste) generated from present Korean PWRs and their operating parameters were analyzed. As the result of multi-variable linear regressions, a model predicting the volume of DAW using the number of shutdowns ( $f_{FS}$ ) and total personnel exposure ( $P_{\varepsilon}$) was derived. Considering one standard error bound, the model could successfully simulate about 8575 of the real data. In order to predict the amount of DAW to be generated from a KNGR another model was derived by taking into account the additional volume reduction by supercompaction system. In addition, the volume of WAW (Wet Active Waste) to be generated from KNGR (Korean Next Generation Reactor) was calculated by considering conceptual design data and replacement effect of radwaste evaporator with selective ion exchangers. Finally, total volume of SRW (Solid Radioactive Waste) to be generated from KNGR was predicted by inserting design goal values of $f_{FS}$ and $P_{\varepsilon}$ into the model. The result showed that the expected amount of SRW to be generated from KNGR would be in the range of 33~44㎥. $y^{-1}$ . It was proved that the value would meet the operational target of KNGR proposed by KEPCO, that is, 50㎥. $y^{-1}$ .

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7672-7676
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• 2015

This study examines the dynamic relations between housing price and trading volume in a set of apartment markets in Republic of Korea to explore the informational role of trading volume in predicting the price volatility. Using monthly index data, EGARCH model is utilized to test for volume effect. To estimate the EGARCH-based volatility, two different sets of region are applied for the monthly return. Strong evidence has been found towards housing turnover leading price volatility, this supports previous studies on financial sector(s). These findings also support that trading volume in the housing market contains information on investor sentiment which, in turn, has a valuation effect on the price.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.5
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• pp.868-889
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• 2022

Fashion companies are using a big data approach as a key strategic analysis to predict and forecast sales. This study investigated the effectiveness of the past sales, web search volume, information amount, brand promotion, and the advertising endorser on the sales forecasting model. The study conducted the autoregressive distributed lag (ARDL) time series model using the internal and external social big data of a national fashion brand. Results indicated that the brand's past sales, search volume, promotion, and amount of advertising endorser information amount significantly affected the sales forecast, whereas the brand's advertising endorser search volume and information amount did not significantly influence the sales forecast. Moreover, the brand's promotion had the highest correlation with sales forecasting. This study adds to information-searching behavior theory by measuring consumers' brand involvement. Last, this study provides digital marketers with implications for developing profitable marketing strategies on the basis of consumers' interest in the brand and advertising endorser.