• Journal of the Society of Disaster Information
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• v.4 no.2
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• pp.10-27
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• 2008

When the ground is excavated adjacent to the existing tunnel, which is loaded by the surcharge on the ground surface, the tunnel stability would be very sensitive to the deformation of the ground induced by the horizontal displacement of braced wall. The stability of the existing surcharged tunnel could be controlled by pre-loading on the braced wall. In this paper, it was investigated, if it would be possible to keep the existing surcharged tunnel stable by preventing the horizontal displacement of a braced wall by imposing the pre-loading during the ground excavation. For this purpose, large scale model tests were performed in a scale 1/10 at the test pit which was 2.0m in width and 6.0m in height and 4.0m in length. Isotropic test ground was constructed homogeneously by wet sand. Model tunnel was constructed in the test ground. Surcharge was loaded on the ground surface above the tunnel. During the tests, the behavior of model tunnel and model braced wall was measured. Numerical analyses were also performed in the same condition as the tests. And their results were compared to that of the model tests. Consequently, the effect of a surcharge could be compensated by imposing the pre-loading on the braced wall. The existing tunnel and the braced wall could be kept stable by preventing the horizontal displacement of the braced wall through pre-loading, although the tunnel is surcharged.

• Journal of The Korean Astronomical Society
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• v.29 no.spc1
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• pp.23-24
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• 1996

We reexamined CDM texture large-scale structure (LSS) formation model. We confirmed that texture model is consistent with 4-year COBE data both in an open and a critical matter density (${\Omega}_0$ = 1) universes, and then obtained normalization for density perturbation power spectrum. We next compare the power spectrum with LSS observation data. Contrary to the previous literature, we found that texture model matches with these data in an open universe no better than in an ${\Omega}_0$ = 1 universe. We also found that the model is more likely to fit these data in a cosmological constant dominated ($\Lambda-$) universe.

• Journal of Convergence for Information Technology
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• v.7 no.5
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• pp.83-88
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• 2017

This paper describes the azimuth accuracy test of phase comparison direction finding method using F-16 fighter scale-down model. When the antennas are placed on the bottom of a fighter, reflection signals caused by an aircraft structure arises and an azimuth error occurs. In this research, the F-16 fighter scale-down model was made to 5:1, and five antennas were placed on the bottom of the model, then the radio waves of emitters were received by the antennas in the $0-360^{\circ}$ azimuth angles. The accuracy test was performed by numerically analyzing the phases of the radio waves received by the five antennas. The azimuth error of the phase comparison direction finding with scale-down model was measured to be less than $0.5^{\circ}$ when the signal noise ratio was larger then 0dB, and it could be very useful for the design of the phase comparison direction finding method of the fighter.

• Wind and Structures
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• v.15 no.1
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• pp.43-64
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• 2012

Many potential small wind turbine locations are near obstacles such as buildings and shelterbelts, which can have a significant, detrimental effect on the local wind climate. A neural network-based model has been developed which predicts mean wind speed and turbulence intensity at points in an obstacle's region of influence, relative to unsheltered conditions. The neural network was trained using measurements collected in the wakes of 18 scale building models exposed to a simulated rural atmospheric boundary layer in a wind tunnel. The model obstacles covered a range of heights, widths, depths, and roof pitches typical of rural buildings. A field experiment was conducted using three unique full scale obstacles to validate model predictions and wind tunnel measurements. The accuracy of the neural network model varies with the quantity predicted and position in the obstacle wake. In general, predictions of mean velocity deficit in the far wake region are most accurate. The overall estimated mean uncertainties associated with model predictions of normalized mean wind speed and turbulence intensity are 4.9% and 12.8%, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.579-585
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• 2019

Increasing the detection probability of underwater targets necessitates securing the towing stability of the active towed SONAR. In this paper, to confirm the effects of tail wing fin on towing attitude and towing stability, two scale model experiments and one sea trials were conducted and the results were analyzed. The scale model tests measured the towing behavior of each of the tail fin shapes according to towing speed in a towing tank. The shape of the tail fin used in the scale model test was tested with an I-type tail fine and four Y-type tail fins, totaling five tail fins of the two kinds. The first scale model test confirmed that the Y-type tail fin was superior to the I-type tail fin in towing attitude and towing stability. The second scale model test confirmed the characteristics of the vertical tail fin height increase and the lower horizontal tail fin inclination angle application shape based on the Y-type tail fin. The shape of the application of the lower horizontal tail fin inclination angle showed the best performance. In order to verify the results of the scale model test, a full size model was constructed, sea trials were performed, and the towing attitude was measured. The results were similar to those of the scale model test.

• Computers and Concrete
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• v.7 no.4
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• pp.303-315
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• 2010

In this paper, we present a new finite Timoshenko beam element with a model for ultimate load computation of reinforced concrete frames. The proposed model combines the descriptions of the diffuse plastic failure in the beam-column followed by the creation of plastic hinges due to the failure or collapse of the concrete and or the re-bars. A modified multi-scale analysis is performed in order to identify the parameters for stress-resultant-based macro model, which is used to described the behavior of the Timoshenko beam element. The micro-scale is described by using the multi-fiber elements with embedded strain discontinuities in mode 1, which would typically be triggered by bending failure mode. A special attention is paid to the influence of the axial force on the bending moment - rotation response, especially for the columns behavior computation.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.344-346
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• 2004

IKONOS 1m satellite imagery is particularly well suited for 3-D feature extraction and 1 :5,000 scale topographic mapping. Because the image line and sample calculated by given RPCs have the error of more than 11m, in order to be able to perform feature extraction and topographic mapping, rational polynomial coefficients(RPCs) camera model that are derived from the very complex IKONOS sensor model to describe the object-image geometry must be refined by several Ground Control Points(GCPs). This paper presents a quantitative evaluation of the geometric accuracy that can be achieved with IKONOS imagery by refining the offset and scaling factors of RPCs using several GCPs. If only two GCPs are available, the offsets and scale factors of image line and sample are updated. If we have more than three GCPs, four parameters of the offsets and scale factors of image line and sample are refined first, and then six parameters of the offsets and scale factors of latitude, longitude and height are updated. The stereo images acquired by IKONOS satellite are tested using six ground points. First, the RPCs model was refined using 2 GCPs and 4 check points acquired by GPS. The results from IKONOS stereo images are reported and these show that the RMSE of check point acquired from left images and right are 1.021m and 1.447m. And then we update the RPCs model using 4 GCPs and 2 check points. The RMSE of geometric accuracy is 0.621 m in left image and 0.816m in right image.

• Journal of the Korean Geotechnical Society
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• v.34 no.4
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• pp.49-55
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• 2018

A pre-load of bracing was imposed to prevent the horizontal displacement on the strut of the braced wall adjacent to the building during the ground excavation. For this purpose, large scale model tests were conducted, without and with pre-load on braced wall. Adjacent building load was also imposed in different locations, that were 0 m, 1D, 2D on ground surface. In this study, model tests in 1:10 scale were performed in real construction sequences, and adjacent building was 12 m in width and the size of model test pit was 2 m in width, 6 m in height, and 4 m in length. As a result, it was found that the stability of the existing building adjacent to the braced wall within Rankine's active zone could be greatly enhanced when the horizontal displacement of the braced wall was reduced by applying a pre-load. which was larger than the designated axial force on the strut of the braced wall.

• Journal of Environmental Health Sciences
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• v.22 no.1
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• pp.5-11
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• 1996

The more accurate estimation of the pollutant loadings from nonpoint source is needed to evaluate water quality of water resources such as river and reservoir. Therefore this study was performed to grasp the scale and characteristics of pollutant. In this study, STORM model was applied to I-cheon district to estimate runoff and pollutant loading of SS, BOD, T-N and $PO_4-P$. The results estimated by STORM model were fitted well to surveyed water quality in flow, SS and BOD. The annual loadings were estimated to be 36,463 kg/$km^3$/yr of SS, 8,090 kg/$km^3$/yr of BOD, 4,435 kg/$km^3$/yr of T-N and 358 kg/$km^3$/yr of $PO_4-P$. It was also found that the monthly pollutant loadings of SS, BOD, $PO_4-P$ were greatest in May and T-N in April.

• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.309-316
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• 2022

This investigation is aimed at automatic text summarization on large-scale Vietnamese datasets. Vietnamese articles were collected from newspaper websites and plain text was extracted to build the dataset, that included 1,101,101 documents. Next, a new single-document extractive text summarization model was proposed to evaluate this dataset. In this summary model, the k-means algorithm is used to cluster the sentences of the input document using different text representations, such as BoW (bag-of-words), TF-IDF (term frequency - inverse document frequency), Word2Vec (Word-to-vector), Glove, and FastText. The summary algorithm then uses the trained k-means model to rank the candidate sentences and create a summary with the highest-ranked sentences. The empirical results of the F1-score achieved 51.91% ROUGE-1, 18.77% ROUGE-2 and 29.72% ROUGE-L, compared to 52.33% ROUGE-1, 16.17% ROUGE-2, and 33.09% ROUGE-L performed using a competitive abstractive model. The advantage of the proposed model is that it can perform well with O(n,k,p) = O(n^(k+2/p)) + O(nlog₂n) + O(np) + O(nk²) + O(k) time complexity.