• Transactions of the Korean Society of Mechanical Engineers B
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• v.25 no.8
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• pp.1060-1067
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• 2001

A large-scale bursting event has been analyzed in a turbulent channel flow using a data obtained from a direct numerical simulation (DNS). Large-scale, plume-like structures have been frequently observed in many experimental results, but the origin of those structures is far from being fully understood. It is believed that those large scale events occur occasionally but contribute significantly to the generation of Reynolds shear stress in the outer layer. This paper attempts to give detailed examples of those large-scale motions observed in a turbulent channel flow at relatively low Reynolds number.

• Journal of Distribution Science
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• v.12 no.2
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• pp.73-79
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• 2014

Purpose - The Korean government has revised the distribution industry development law to regulate large-scale retailer operations to protecting medium- and small-scale retailers and traditional markets. According to the revised law, large-scale retailers must follow regulations on operating hours and compulsory store closures two days per month. Based on the revised distribution industry development law, most local governments regulate operation hours and they have adopted compulsory closure programs for large-scale retail stores. However, it is argued that fresh food producers suffer from a decrease in sales based on the compulsory closure of stores operated by large-scale retailers. Large-scale retailers reduce their fresh food orders from agricultural and fishery producers because of the compulsory store closures. Fresh food producers also suffer from a decrease in prices because reduced orders lead to a decrease in auction prices based on the availability of excess goods in wholesale markets. This paper investigates the effects of operation regulations for large-scale retailers on agricultural producers by surveying agricultural and fishery producer organizations. Research design, data, methodology - A survey was conducted on 117 producer organizations of fruits and vegetables, cereals, fisheries, and livestock products from September 10 to October 4, 2012. Survey items are annual sales, shares of sales accounted for by large-scale retailers, reduction of orders and prices from large-scale retailers, methods to deal with the sales reduction, unfair trade practices of large-scale retailers, opinion of the large-scale retailer regulations, and so on. The average sales of the sampled producer organizations are 13.7 billion won and the average share of sales accounted for by large-scale retailers is 35.4%. Results - Survey results show that the sample producer organizations' sales decreased 10.1% because of the compulsory closures of stores operated by large-scale retailers. It is estimated that the total sales of producer organizations decreased 371.2 billion won because of the regulations on the operation of large-scale retailers. In addition to the direct effect of a sales decrease due to order reduction, agricultural and fishery producer organizations suffered from the secondary effect of price reduction in wholesale markets. When orders from large-scale retailers decreased, most agricultural and fishery producer organizations shipped redundant products to wholesale markets, decreasing auction prices. It was estimated that the price received decreased 21.9% when sold in other marketing channels. As producer organization sales decreased, it was reported that the labor force employed by producer organizations also decreased by 15.1%. Therefore, we can conclude that the regulations for large-scale retailer operations resulted in negative impacts on agricultural producers. Conclusions - Although the sales reduction due to the regulations for large-scale retailer operations are not great, the cumulative effects due to the continued compulsory closure of stores operated by large-scale retailers could be great. This paper suggests governmental programs that could help agricultural producer organizations to find new and effective marketing channels such as direct marketing, farmers' markets, exports, Internet shopping, and so on.

• Journal of Ship and Ocean Technology
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• v.5 no.4
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• pp.44-50
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• 2001

Large container carriers are suffering from lack of knowledge on reliable correlation allowances between model tests and full-scale trials, especially at fully loaded condition, Careful full-scale sea trial with a full loading of containers both in holds and on decks was carried out to clarify it. Model test results were analyzed by different methods but with the same measuring data to figure out appropriated correlations factors for each analysis methods, Even if it is no doubt that model test technique is one of the most reliable tool to predict full scale powering performance, its assumptions and simplifications which have been applied on the course of data manipulation and analysis need a feedback from sea trial data for a fine tuning, so called correlation factor. It can be stated that the best correlation allowances at fully loaded condition for both 2-dimensional and 3-dimensional analysis methods are fecund through the careful sea trial results and relevant study on the large size container carriers.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.1
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• pp.83.1-83.1
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• 2010

In the last meeting of KAS, we reported the first statistical study of Faraday rotation measure (RM) in the large-scale structure of the universe using the data of cosmological structure formation simulations. With a turbulence dynamo model for the intergalactic magnetic field (IGMF), we predicted that the root mean square of RM through filaments is \sim 1 rad/m^2. Future radio observatories such as the Square Kilometer Array (SKA) could detect this signal level. However, it is known that the typical foreground galactic RM is a few tens and less than ten rad/m^2 in the low and high galactic latitudes, respectively. So the RM in the large-scale structure could be detected only after the foreground galactic RM is removed. In this talk, we show how we remove the foreground galactic RM and what we obtain from the masked data, by using some noise models and masking techniques. Our results can be used to simulate future RM observations by SKA, and eventually to constrain the origin and evolution of the IGMF in the large-scale structure.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.1
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• pp.58.2-58.2
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• 2011

Park, Gott, & Choi (2008) found that when a galaxy is located within the virial radius from its closest neighbor and the neighbor is an elliptical, the probability of the galaxy to be an elliptical is very sensitive to the large-scale background density over a few Mpc scales. They suggested that the large-scale dependence can be arise if the temperature of a diffuse hot gas held by elliptical galaxies are higher in higher density environment. In this study, to understand the large-scale environment affects the X-ray properties of individual galaxies, we investigated the dependence of the X-ray luminosities of the elliptical galaxies on the large-scale environment using X-ray and optical data which we selected from the ROSAT All-Sky Survey and the Sloan Digital Sky Survey Data Release 7. To exclude galaxies embedded in an intra-group/cluster medium which could enhance their observed X-ray luminosity, we used isolated elliptical galaxies.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.268-273
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• 2021

In this paper, we propose a sentiment analysis model that improves performance on small-scale data. A sentiment analysis model for small-scale data is proposed and verified through experiments. To this end, we propose Bagging-Bi-GRU, which combines Bi-GRU, which learns GRU, which is a variant of LSTM (Long Short-Term Memory) with excellent performance on sequential data, in both directions and the bagging technique, which is one of the ensembles learning methods. In order to verify the performance of the proposed model, it is applied to small-scale data and large-scale data. And by comparing and analyzing it with the existing machine learning algorithm, Bi-GRU, it shows that the performance of the proposed model is improved not only for small data but also for large data.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.63.1-63.1
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• 2018

The modern large-scale surveys and state-of-the-art cosmological simulations produce various kinds of big data composed of millions and billions of galaxies. Inevitably, we need to adopt modern Big Data platforms to properly handle such large-scale data sets. In my talk, I will briefly introduce the de facto standard of modern Big Data platform, Apache Spark, and present some examples to demonstrate how Apache Spark can be utilized for solving data-driven astronomical problems.

• International Journal of CAD/CAM
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• v.9 no.1
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• pp.111-120
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• 2010

In this paper, we propose a volume rendering method using grid computing for large-scale volume data. Grid computing is attractive because medical institutions and research facilities often have a large number of idle computers. A large-scale volume data is divided into sub-volumes and the sub-volumes are rendered using grid computing. When using grid computing, different computers rarely have the same processor speeds. Thus the return order of results rarely matches the sending order. However order is vital when combining results to create a final image. Job-Scheduling is important in grid computing for volume rendering, so we use an obstacle-flag which changes priorities dynamically to manage sub-volume results. Obstacle-Flags manage visibility of each sub-volume when line of sight from the view point is obscured by other subvolumes. The proposed Dynamic Job-Scheduling based on visibility substantially increases efficiency. Our Dynamic Job-Scheduling method was implemented on our university's campus grid and we conducted comparative experiments, which showed that the proposed method provides significant improvements in efficiency for large-scale volume rendering.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5972-5989
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• 2019

With the onset of the big data age, data is growing exponentially, and the issue of how to optimize large-scale data processing is especially significant. Large-scale global optimization (LSGO) is a research topic with great interest in academia and industry. Spark is a popular cloud computing framework that can cluster large-scale data, and it can effectively support the functions of iterative calculation through resilient distributed datasets (RDD). In this paper, we propose a hybrid mechanism of particle swarm optimization (PSO) and differential evolution (DE) algorithms based on Spark (SparkPSODE). The SparkPSODE algorithm is a parallel algorithm, in which the RDD and island models are employed. The island model is used to divide the global population into several subpopulations, which are applied to reduce the computational time by corresponding to RDD's partitions. To preserve population diversity and avoid premature convergence, the evolutionary strategy of DE is integrated into SparkPSODE. Finally, SparkPSODE is conducted on a set of benchmark problems on LSGO and show that, in comparison with several algorithms, the proposed SparkPSODE algorithm obtains better optimization performance through experimental results.

• Korean Journal of Geomatics
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• v.1 no.1
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• pp.7-13
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• 2001

Geospatial Information Systems (GIS) have been employed to systematically manage and design land use in urban areas. This has increased the need for more accurate vector and raster data. In Korea, l/l,000-scale digital maps are used as vector data for the facility management in urban areas. This has increased the need for large scale orthoimages. Orthoimages generated from aerial imagery can provide accurate information, making possible the more effective city management. However, there is a large problem in using the orthoimages, i.e., currently available conventional orthoimages have not been generated based on Digital Elevation Model (DEM) that takes into account the building heights. So this causes the displacements of building image in large scale orthoimages. The present study is an attempt to generate the large scale orthoimages based on building DEM. The semiautomatic building extraction method can detect building outlines by mouse clicking on either building roofs or corners. Building DEM, based on the outline and calculated building height, was used to produce the large scale orthoimages with the corrected building occlusion.