• Title/Summary/Keyword: Large Data Set

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Catch fluctuation of the rectangular set net according to the tide age in the coastal waters of Jeju (제주연안 각망의 조석에 의한 어획량 변동)

  • Lee, Chang-Heon;Choi, Chan-Moon
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.44 no.2
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    • pp.112-119
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    • 2008
  • The fundamental data on the catch fluctuation in the rectangular set net according to the tide age were developed based on the catches recorded from the year 1986 to 2004 in the coastal waters of Hamdeok, Jeju. Total catch by the rectangular set net had a deep connection with the tide age. In particular, during increasing tide, total catch were reduced gradually from the neap tide to the high tide. As it turned out, the slope of total catch declined by degree and showed a correlation coefficient of determination of 0.76. On the contrary, in the case of decreasing tide, there was little sign of rise in total catch. In particular, large catch seemed to occur at the next tide to the neap tide. In the relation between the catch and the tide age, the level of the correlation coefficient chosen at $p{\leq}0.05$ decreased in the order rabbitfish(-0.84) and horse mackerel(-0.71), while the significance of other dominant species were not selected.

QSO Selections Using Time Variability and Machine Learning

  • Kim, Dae-Won;Protopapas, Pavlos;Byun, Yong-Ik;Alcock, Charles;Khardon, Roni
    • The Bulletin of The Korean Astronomical Society
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    • v.36 no.2
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    • pp.64-64
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    • 2011
  • We present a new quasi-stellar object (QSO) selection algorithm using a Support Vector Machine, a supervised classification method, on a set of extracted time series features including period, amplitude, color, and autocorrelation value. We train a model that separates QSOs from variable stars, non-variable stars, and microlensing events using 58 known QSOs, 1629 variable stars, and 4288 non-variables in the MAssive Compact Halo Object (MACHO) database as a training set. To estimate the efficiency and the accuracy of the model, we perform a cross-validation test using the training set. The test shows that the model correctly identifies ~80% of known QSOs with a 25% false-positive rate. The majority of the false positives are Be stars. We applied the trained model to the MACHO Large Magellanic Cloud (LMC) data set, which consists of 40 million lightcurves, and found 1620 QSO candidates. During the selection, none of the 33,242 known MACHO variables were misclassified as QSO candidates. In order to estimate the true false-positive rate, we crossmatched the candidates with astronomical catalogs including the Spitzer Surveying the Agents of a Galaxy's Evolution (SAGE) LMC catalog and a few X-ray catalogs. The results further suggest that the majority of the candidates, more than 70%, are QSOs.

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Mechanical Testing and Nonlinear Material Properties for Finite Element Analysis of Rubber Components (고무부품의 유한요소해석을 위한 재료시험 및 비선형 재료물성에 관한 연구)

  • Kim, Wan-Doo;Kim, Wan-Soo;Kim, Dong-Jin;Woo, Chang-Soo;Lee, Hak-Joo
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.28 no.6
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    • pp.848-859
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    • 2004
  • Mechanical testing methods to determine the material constants for large deformation nonlinear finite element analysis were demonstrated for natural rubber. Uniaxial tension, uniaxial compression, equi-biaxial tension and pure shear tests of rubber specimens are performed to achieve the stress-strain curves. The stress-strain curves are obtained after between 5 and 10 cycles to consider the Mullins effect. Mooney and Ogden strain-energy density functions, which are typical form of the hyperelastic material, are determined and compared with each other. The material constants using only uniaxial tension data are about 20% higher than those obtained by any other test data set. The experimental equations of shear elastic modulus on the hardness and maximum strain are presented using multiple regression method. Large deformation finite element analysis of automotive transmission mount using different material constants is performed and the load-displacement curves are compared with experiments. The selection of material constant in large deformation finite element analysis depend on the strain level of component in service.

On the Warming Effects due to Artificial Constructions in a Large Housing Complex (대규모 주택단지내의 인공구조물에 의한 승온화효과에 관한 연구)

  • 김해동;이송옥;구현숙
    • Journal of Environmental Science International
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    • v.12 no.7
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    • pp.705-713
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    • 2003
  • In mid-August 2002, under clear summer pressure patterns, we carried out an intensive meteorological observation to examine the warming effects due to artificial constructions in a large housing complex. We set an automatic weather system(AWS) at two places in a bare soil surface within a limited development district and an asphalt surface within a large apartment residence area, respectively. As a result of observation, it became clear that the difference of the surface air(ground) temperature between the bare soil surface and its peripheral asphalt area reached about 4$^{\circ}C$(13$^{\circ}C$) at the maximum from diurnal variation of surface temperatures on AWS data. Through the heat balance analysis using measurement data, it became clear that the thermal conditions at two places are dependent on the properties of surface material. The latent heat flux over the bare soil surface reached to about 300 W/㎡, which is more than a half of net radiation during the daytime. On the other hand, it was nearly zero over the asphalt surface. Hence, the sensible heat flux over the asphalt surface was far more than that of the bare soil surface. The sensible heat flux over the asphalt surface showed about 20∼30 W/㎡ during the night. It was released from asphalt surface which have far more heat capacity than that of bare soil surface.

Impact of Government Response to COVID-19 on the Role of GVC and Transportation

  • Hyuksoo Cho;Sang-kyun Kim
    • Journal of Korea Trade
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    • v.27 no.2
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    • pp.22-46
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    • 2023
  • Purpose - study aims to investigate the relationships between global value chain (GVC)- and transportation-related determinants and economic performance. Also, moderating effects of COVID-19 on the relationships are theoretically and empirically discussed. A limitation of previous studies includes their over-reliance on the opportunities of GVC participation and larger transportation. This study represents the challenges associated with them. Also, it shows how GVC and logistics can be difficult in case of a market fluctuation such as COVID-19. Design/methodology - The sample for this study includes 828 observations from 138 countries. A semi-panel data set has been used. Six observations for each country are used to empirically test the hypotheses and a Two-way cluster model is conducted. Findings - It is confirmed that GVC forward participation contributes more than the backward participation to enhance performance. Transportation infrastructure is critical, but large scales of marine and air transportations are not positive in terms of economic performance. Stricter government response to COVID-19 negatively moderates economic performance by GVC backward participation and transportation infrastructure. Originality/value - The spread of COVID-19 is causing a severe collapse of GVC and transportation. This study empirically verifies the moderating effects of the government stringency on GVC and transportation. Previous studies usually discuss a positive impact of GVC and transportation size on economic performance. However, this study aims to show various challenges behind GVC participation and large scale transportation.

Interpolation on data with multiple attributes by a neural network

  • Azumi, Hiroshi;Hiraoka, Kazuyuki;Mishima, Taketoshi
    • Proceedings of the IEEK Conference
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    • 2002.07b
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    • pp.814-817
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    • 2002
  • High-dimensional data with two or more attributes are considered. A typical example of such data is face images of various individuals and expressions. In these cases, collecting a complete data set is often difficult since the number of combinations can be large. In the present study, we propose a method to interpolate data of missing combinations from other data. If this becomes possible, robust recognition of multiple attributes is expectable. The key of this subject is appropriate extraction of the similarity that the face images of same individual or same expression have. Bilinear model [1]has been proposed as a solution of this subjcet. However, experiments on application of bilinear model to classification of face images resulted in low performance [2]. In order to overcome the limit of bilinear model, in this research, a nonlinear model on a neural network is adopted and usefulness of this model is experimentally confirmed.

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Estimation of Gini-Simpson index for SNP data

  • Kang, Joonsung
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.6
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    • pp.1557-1564
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    • 2017
  • We take genomic sequences of high-dimensional low sample size (HDLSS) without ordering of response categories into account. When constructing an appropriate test statistics in this model, the classical multivariate analysis of variance (MANOVA) approach might not be useful owing to very large number of parameters and very small sample size. For these reasons, we present a pseudo marginal model based upon the Gini-Simpson index estimated via Bayesian approach. In view of small sample size, we consider the permutation distribution by every possible n! (equally likely) permutation of the joined sample observations across G groups of (sizes $n_1,{\ldots}n_G$). We simulate data and apply false discovery rate (FDR) and positive false discovery rate (pFDR) with associated proposed test statistics to the data. And we also analyze real SARS data and compute FDR and pFDR. FDR and pFDR procedure along with the associated test statistics for each gene control the FDR and pFDR respectively at any level ${\alpha}$ for the set of p-values by using the exact conditional permutation theory.

Federated Named Data Networking Testbed for Climate Science

  • Ni, Alexander;Lim, Huhnkuk
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.42 no.4
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    • pp.780-784
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    • 2017
  • Data discovery and distribution application that is utilized by climate, high energy physics, and other scientific communities are experiencing performance and large scale data managing problems, that are rooted from the shortcomings of IP architecture. To solve this problem, newly developed data managing applications based on NDN architecture were introduced. In this letter, we present the federated NDN testbed with an NDN-based climate science application and the set of experiments that reflect the performance of NDN based climate application in general with determined and applied optimization.

LARGE EDDY SIMULATION OF ORDINARY & EMERGENCY VENTILATION FLOW IN UNDERGROUND SUBWAY STATION (지하역사 승강장 및 대합실 평상시 비상시 급·배기 환기 Large Eddy Simulation)

  • Jang, Yong-Jun;Ryu, Ji-Min;Park, Duck-Shin
    • Journal of computational fluids engineering
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    • v.18 no.3
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    • pp.72-78
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    • 2013
  • The turbulent flow behavior of air supply and exhaustion in the Shin-gum-ho subway station is analyzed for ordinary and emergency state. The depth of Shin-gum-ho station is 43.6m which consists of the island-type platform(8th floor in underground) and a two-story lobby (first & second floor in underground). An emergency stairway connects between the platform and the lobby. Ventilation operation mode for ordinary state is set up as a combination of air supply and exhaustion in the lobby and platform, while for emergency state it is set up as a full air supply in the lobby and a full exhaustion in the platform. The entire station is covered for simulation. The ventilation diffusers are modeled as 95 square shapes of $0.6m{\times}0.6m$ in the lobby and as 222 square shapes of $0.6m{\times}0.6m$ and 4 rectangular shapes of $1.2m{\times}0.8m$ in the platform. The total of 7.5million grids are generated and whole domain is divided to 22 blocks for MPI efficiency of calculation. Large eddy simulation(LES) is applied to solve the momentum equation and Smagorinsky model($C_s$=0.2) is used as SGS(subgrid scale) model. The time-averaged velocity fields are compared to experimental data and show a good agreement with it.

Concurrency Control for Updating a Large Spatial Object (큰 공간 객체의 변경을 위한 동시성 제어)

  • Seo Young Duk;Kim DongHyun;Hong Bong Hee
    • Journal of KIISE:Databases
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    • v.32 no.1
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    • pp.100-110
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    • 2005
  • The update transactions to be executed in spatial databases usually have been known as interactive and long duration works. To improve the parallelism of concurrent updates, it needs multiple transactions concurrently update a large spatial object which has a spatial extensions larger than workspace of a client. However, under the existing locking protocols, it is not possible to concurrently update a large spatial object because of conflict of a write lock This paper proposes a partial locking scheme of enabling a transaction to set locks on parts of a big object. The partial locking scheme which is an exclusive locking scheme set by user, acquires locks for a part of the big object to restrict the unit of concurrency control to a partial object of a big object. The scheme gives benefits of improving the concurrency of un updating job for a large object because it makes the lock control granularity finer.