• Korean Management Science Review
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• v.32 no.4
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• pp.57-67
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• 2015

It is a familiar Wall Street adage that "It takes volume to make prices move." Numerous researches have found the positive correlation between trading volume and price changes. Recent studies have documented that informed traders have strong influences on stock market prices through their trading with distinctive information power. Ever since 1992 capital market liberalization in Korea, it is said that foreign investors make consistent profits with their superior information and analytical skills. This study aims at whether we can make a profitable trading strategy by using the foreign investors' trading information. We analyse the relation between the KOSPI index returns and the foreign investors trading volume using GARCH models and VAR models. This study suggests the profitable trading strategies based on the documented relation between the foreign investors' trading volume and KOSPI index returns. We simulate the trading system with the real stock market data. The data include the daily KOSPI index returns and foreign investors' trading volume for 2001~2013. We estimate the GARCH and VAR models using 2001~2011 data and simulate the suggested trading system with the remaining out-of-sample data. Empirical results are as follows. First, we found the significant positive relation between the KOSPI index returns and contemporaneous foreign investors' trading volume. Second, we also found the positive relation between the KOSPI index returns and lagged foreign investors' trading volume. But the relation showed no statistical significance. Third, our suggested trading system showed better trading performance than B&H strategy, especially trading system 2. Our results provide good information for uninformed traders in the Korean stock market.

• Journal of Korea Game Society
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• v.13 no.2
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• pp.99-110
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• 2013

As volume rendering has been applied for computer game, the visualization of volume data with surface data in one scene has been required. Though a hybrid rendering of volume and surface data have been developed using the GPGPU functionality, computer games which run on low-level hardware are difficult to perform the hybrid rendering. In this paper, we propose a new hybrid rendering based on DirectX 9.0 and general hardware. We generate the layered depth images from surface data using a new method to reduce the depth complexity and generation time. Then, we perform the hybrid rendering using the layered depth images. In the rendering process, we suggest a new method to transform the coordinate system from a surface coordinate to a volume coorinate and propose an accelerated rendering technique. As the result, we can perform volume-surface hybrid rendering in an efficient way.

• Korean Journal of Radiology
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• v.22 no.3
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• pp.435-441
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• 2021

Objective: To evaluate the usefulness of the ventricular volume percentage quantified using three-dimensional (3D) brain computed tomography (CT) data for interpreting serial changes in hydrocephalus. Materials and Methods: Intracranial and ventricular volumes were quantified using the semiautomatic 3D threshold-based segmentation approach for 113 brain CT examinations (age at brain CT examination ≤ 18 years) in 38 patients with hydrocephalus. Changes in ventricular volume percentage were calculated using 75 serial brain CT pairs (time interval 173.6 ± 234.9 days) and compared with the conventional assessment of changes in hydrocephalus (increased, unchanged, or decreased). A cut-off value for the diagnosis of no change in hydrocephalus was calculated using receiver operating characteristic curve analysis. The reproducibility of the volumetric measurements was assessed using the intraclass correlation coefficient on a subset of 20 brain CT examinations. Results: Mean intracranial volume, ventricular volume, and ventricular volume percentage were 1284.6 ± 297.1 cm³, 249.0 ± 150.8 cm³, and 19.9 ± 12.8%, respectively. The volumetric measurements were highly reproducible (intraclass correlation coefficient = 1.0). Serial changes (0.8 ± 0.6%) in ventricular volume percentage in the unchanged group (n = 28) were significantly smaller than those in the increased and decreased groups (6.8 ± 4.3% and 5.6 ± 4.2%, respectively; p = 0.001 and p < 0.001, respectively; n = 11 and n = 36, respectively). The ventricular volume percentage was an excellent parameter for evaluating the degree of hydrocephalus (area under the receiver operating characteristic curve = 0.975; 95% confidence interval, 0.948-1.000; p < 0.001). With a cut-off value of 2.4%, the diagnosis of unchanged hydrocephalus could be made with 83.0% sensitivity and 100.0% specificity. Conclusion: The ventricular volume percentage quantified using 3D brain CT data is useful for interpreting serial changes in hydrocephalus.

• Journal of Forest and Environmental Science
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• v.34 no.4
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• pp.313-320
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• 2018

Tectona grandis (teak) is one of the most important timber species worldwide and India is one of the major teak growing countries. Though some volume equations were developed for teak in India but the models developed were neither evaluated using robust statistical criteria nor validated. Hence, the objective of this study was to develop statistically tested appropriate volume equation to predict total wood volume (over- and under-bark) for teak trees in Gujarat. A total of 41 trees with age varying from 15 to 33 years and diameter at breast height (dbh) from 7.3 to 30.8 cm were felled for the purpose. Linear and non-linear equations were used to model the relationship of the total wood volume with respect to dbh and total height. The equations tested mostly fitted well to the data. Model evaluation and validation indicated that models should be calibrated with local data for greater accuracy in the prediction.

• Journal of Korea Multimedia Society
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• v.25 no.4
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• pp.559-567
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• 2022

The optimal shipping location is determined by measuring the volume and weights of cargo shipped to non-standard cargo carriers. Currently, workers manually measure cargo volume, but automate it to improve work inefficiency. In this paper, we proposed the method of a real-time volume calculation using LiDar sensor for automating cargo measurement of non-standard cargo. For this purpose, we utilized the statistical techniques for data preprocessing and volume calculation, also used Voxel Grid filter to light weighted of data which are appropriate in real-time calculation. We implemented the function of Normal vectors and Triangle Mesh to generate surfaces and Alpha Shapes algorithms to process 3D modeling.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.6
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• pp.705-716
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• 2002

This paper proposes a method which visualizes MRI head data in 3 dimensions with direct volume rendering. Though surface rendering is usually used for MRI data visualization, it has some limits of displaying little speckles because it loses the information of the speckles in the surfaces while acquiring the information. Direct volume rendering has ability of displaying little speckles, but it doesn't treat MRI data because of the data features of MRI. In this paper, we try to visualize MRI head data in 3 dimensions as follows. First, we separate the brain region from the head region of MRI head data, next increase the pixel level of the brain region, then combine the brain region with the increased pixel level and the head region without brain region, last visualizes the combined MRI head data with direct volume rendering. We segment the brain region from head region based on histogram threshold, morphology operations and snakes algorithm. The proposed segmentation method shows 91~95% similarity with a hand segmentation. The method rather clearly visualizes the organs of the head in 3 dimensions.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.85-93
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• 2007

This paper describes a compression scheme for volumetric video data(3D space X 1D time) there each frame of the volume is decompressed and rendered in real-time. Since even one frame size of volume is very large, runtime decompression can be a bottleneck for real-time playback of time-varying volume data. To increase the run-time decompression speed and compression ratio, we decompose the volume into small blocks and only update significantly changing blocks. The results show that our compression scheme compromises decompression speed and image quality well enough for interactive time-varying visualization.

• Asian Journal of Business Environment
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• v.4 no.2
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• pp.17-21
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• 2014

Purpose - The paper analyzes basic indicators characterizing the volume of energy sector activity in the Russian Federation, Privolzhsky Federal district, Republic of Tatarstan. Research design, data, and methodology - The study analyzed data from the Privolzhsky Federal district, specifically, industrial production volume, electricity production, energy consumption, energy-balance data, capital investments, and capital investment structure. An array of data has been investigated in recent years. The dataset's dynamics were analyzed in 1998. Fixed capital investment dynamics were studied in 1946 the figures were converted to a comparable form using the index method. Trends were analyzed using multivariate statistics methods and the Statgraphics software package. Results - Hypothesis 1. There are sectoral disproportions in energy flows,taking into account the volume of electricity production and consumption. Trends in electricity production in general coincide with industrial production volume trends. Energy flows have disparities in individual territorial units, and in general. Hypothesis 2. The degree of sectoral economic stability decreases with insufficient levels of investment in fixed capital energy organizations. Conclusions - Because totalelectricity production is largely determined by fixed capital investments, the study of their trends and patterns will coordinate efforts on investment operations in this area.

• Archives of Plastic Surgery
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• v.40 no.3
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• pp.203-208
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• 2013

Background Preoperative volume assessment is useful in breast reconstruction. Magnetic resonance imaging (MRI) and mammography are commonly available to reconstructive surgeons in the care of a patient with breast cancer. This study aimed to verify the accuracy of breast volume measured by MRI, and to identify any factor affecting the relationship between measured breast volume and actual breast weight to derive a new model for accurate breast volume estimation. Methods From January 2012 to January 2013, a retrospective review was performed on a total of 101 breasts from 99 patients who had undergone total mastectomy. The mastectomy specimen weight was obtained for each breast. Mammographic and MRI data were used to estimate the volume and density. A standard statistical analysis was performed. Results The mean mastectomy specimen weight was 340.8 g (range, 95 to 795 g). The mean MRI-estimated volume was $322.2mL^3$. When divided into three groups by the "difference percentage value", the underestimated group showed a significantly higher fibroglandular volume, higher percent density, and included significantly more Breast Imaging, Reporting and Data System mammographic density grade 4 breasts than the other groups. We derived a new model considering both fibroglandular tissue volume and fat tissue volume for accurate breast volume estimation. Conclusions MRI-based breast volume assessment showed a significant correlation with actual breast weight; however, in the case of dense breasts, the reconstructive surgeon should note that the mastectomy specimen weight tends to overestimate the volume. We suggested a new model for accurate breast volume assessment considering fibroglandular and fat tissue volume.

• The Journal of Bigdata
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• v.4 no.2
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• pp.85-91
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• 2019

Since online shopping has become common, people can easily buy fashion goods anytime, anywhere. Therefore, consumers quickly respond to various environmental variables such as weather and sales prices. Thus, utilizing big data for efficient inventory management has become very important in the fashion industry. In this paper, the changes in sales volume of fashion goods due to changes in temperature is analyzed via the proposed big data analysis algorithm by utilizing actual big data from Korean fashion company 'B'. According to the analytic results, the proposed big data analysis algorithm found both expected and unexpected changes in sales volume depending on the characteristics of the fashion goods.