• Geomechanics and Engineering
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• v.20 no.5
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• pp.447-459
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• 2020

Based on the literature statistical method, the paper publication status of the isolated working face and the distribution of the rockburst coal mine were obtained. The numerical simulation method is used to study the stress distribution law of working face under different mining range. In addition, based on the similar material simulation test, the overlying strata failure modes and the deformation characteristics of coal pillars during the mining process of the isolated working face with thick-hard key strata are analyzed. The research shows that, under the influence of the key strata, the overlying strata formation above the isolated working face is a long arm T-type spatial structure. With the mining of the isolated working face, a series of damages occur in the coal pillars, causing the key strata to break and inducing the rockburst occurs. Combined with the mechanism of rockburst induced by the dynamic and static combined load, the source of dynamic and static load on the isolated working face is analyzed, and the rockburst monitoring methods and the prevention and control measures are proposed. Through the above research, the occurrence probability of rockburst can be effectively reduced, which is of great significance for the safe mining of deep coal mines.

• The Journal of Asian Finance, Economics and Business
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• v.1 no.1
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• pp.23-30
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• 2014

The aim of this research is theoretical and methodological approaches to the necessity of formation of innovation clusters as growth poles on the basis of statistical analysis and identification of specialization. In this research, we used methods, which will allow to analyze of innovative processes and to identify of prospective branches of specialization of the formation of innovative clusters in the spatial context. Keeping with the previous literature, the present study is determined by the novelty of the problem, concerning the formation and development of innovative clusters as growth poles, as well as large specifics of problems in our country in the framework of use of innovative clusters. An analysis was showed that Kazakhstan's regions have substantial differences in the groups of regions for most of the indicators have presented form a tightly located clusters and in the ratings of innovative susceptibility and innovative activity. This research has some practical implications, which have proved that innovative clusters become platforms as growth poles for introduction of advanced technologies, development of innovative companies, thereby providing a certain stability of the economy of the regions.

• The Journal of the Korea Contents Association
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• v.7 no.12
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• pp.303-310
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• 2007

Compressed video bitstreams are intended for real-time transmission over communication networks. Because video compression algorithms eliminate the temporal, spatial, and statistical redundancies, the coded video bitstreams are very sensitive to transmission errors. We propose an error resilient video coding technique to limit the effect of error propagation in low bit-rate video coding. The success of error resilient coding techniques relies on how accurately the transmission errors can be detected. To detect the transmission error, we propose a very simple error detection technique based on data hiding Next, we conceal the corrupted MB data using intra MB refresh and motion compensation with the estimated motion vector and compare the simulation results. This method will be useful in video communication in error Prone environment such as WCDMA networks.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.170-173
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• 2009

In this paper, we propose a fast intra prediction mode selection method in Scalable Video Coding(SVC) which is an emerging video coding standard as an extension of H.264/Advanced Video Coding(H.264/AVC). The proposed method decides a candidate intra prediction mode based on the characteristic of macroblock smoothness. Statistical analysis is applied to computing that smoothness in spatial enhancement layer. We also propose an early termination scheme for Intra_BL mode decision where the RD cost value of Intra_BL is utilized. Compared with JSVM software, our scheme can reduce about 55% of the computation complexity of intra prediction on average, while the performance degradation is negligible; For low QP values, the average PSNR loss is very negligible, equivalently the bit rate increases by 0.01%. For high QP values, the average PSNR loss is less than 0.01dB, which equals to 0.25% increase in bitrate on average.

• Atmosphere
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• v.20 no.3
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• pp.319-332
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• 2010

Sensitivity experiments of WRF model using different planetary boundary layer (PBL) and land surface model (LSM) parameterizations are evaluated for prediction of wind fields within the surface layer. The experiments were performed with three PBL schemes (YSU, Pleim, MYJ) in combination with three land surface models (Noah, RUC, Pleim). The WRF model was conducted on a nested grid from 27-km to 1-km horizontal resolution. The simulations validated wind speed and direction at 10 m and 80 m above ground level at a 1-km spatial resolution over the South Korea. Statistical verification results indicate that Pleim and YSU PBL schemes are in good agreement with observations at 10 m above ground level, while the MYJ scheme produced predictions similar to the observed wind speed at 80 m above ground level. LSM comparisons indicate that the RUC model performs best in predicting 10-m and 80-m wind speed. It is found that MYJ (PBL) - RUC (LSM) simulations yielded the best results for wind field in the surface layer. The choice of PBL and LSM parameterization will contribute to more accurate wind predictions for air quality studies and wind power using WRF.

• Current Research on Agriculture and Life Sciences
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• v.31 no.4
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• pp.233-239
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• 2013

Understanding the temporal variability of agricultural parameters derived from historical climate data is important for planning in agriculture. Therefore, this study assessed the magnitude and recent trends of the transpiration ratio defined as the crop water use per harvested yield for the period from 1980 to 2010. The crop water use was estimated using the Food and Agriculture Organization's Crop Wat model for eight administrative provinces in Korea. The temporal trends and spatial uncertainty were explored using the Mann-Kendall and Theil Sen's methods. The regional average rice yield was $6.31t\;ha^{-1}$(range 5.9 to $6.9t\;ha^{-1}$). The results showed that the rice yield in Korea increased by $26kg\;ha^{-1}yr^{-1}$. Overall, the regional average transpiration ratio was $1,298m^3t^{-1}$ (range 1,162 to $1,470m^3t^{-1}$). From 1980 to 2010, the transpiration ratio decreased by $8.2m^3t^{-1}$ (range 2.7 to $14.4m^3t^{-1}$), largely as a result of the increasing yield. The statistical approach to historical data used in this study also provides a basis for simulating the future transpiration ratio.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.286-289
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• 2007

This study is to develop a cloud detection algorit1un for COMS and it is currently tested by using MODIS level 2B and MTSAT-1R satellite radiance data. Unlike many existing cloud detection schemes which use a threshold method and traditional statistical methods, in this study a feed-forward neural network method with back-propagation algorit1un is used. MODIS level 2B products are matched with feature information of five-band MTSAT 1R image data to form the training dataset. The neural network is trained over the global region for the period of January to December in 2006 with 5 km spatial resolution. The main results show that this model is capable to detect complex cloud phenomena. And when it is applied to seasonal images, it shows reliable results to reflect seasonal characteristics except for snow cover of winter. The cloud detection by the neural network method shows 90% accuracy compared to the MODIS products.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.290-293
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• 2007

The land surface temperature (LST) derived from the meteorological satellite can be used to investigate the urban heat island (UHI) and its temporal variations. In this study, we developed LST retrieval algorithm from MTSAT-1R by means of a statistical regression analysis from radiative transfer simulations using MODTRAN 4 for a wide range of atmospheric, satellite viewing angle (SVA) and lapse rate conditions. 535 sets of thermodynamic initial guess retrieval (TIGR) were used for the radiative transfer simulations. Sensitivity and intercomparison results showed that the algorithm, developed in this study, estimated the LST with a similar bias and root mean square errors to that of other algorithms. The magnitude, spatial extent, and seasonal and diurnal variations of the UBI of Korean peninsula were well demonstrated by the LST derived from MTSAT-1R data. In general, the temporal variations of UHI clearly depend on the weather conditions and geographic environment of urban.

• The Korean Journal of Applied Statistics
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• v.25 no.4
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• pp.669-680
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• 2012

Noise removal of document images is a necessary step during preprocessing to recognize characters effectively because it has influences greatly on processing speed and performance for character recognition. We have considered using the spatial filters such as traditional mean filters and Gaussian filters, and wavelet transformed based methods for noise deduction in natural images. However, these methods are not effective for the noise removal of document images. In this paper, we present noise removal of document images using support vector regression. The proposed approach consists of two steps which are SVR training step and SVR test step. We construct an optimal prediction model using grid search with cross-validation in SVR training step, and then apply it to noisy images to remove noises in test step. We evaluate our SVR based method both quantitatively and qualitatively for noise removal in Korean, English and Chinese character documents, and compare it to some existing methods. Experimental results indicate that the proposed method is more effective and can get satisfactory removal results.

• Journal of Korean Society on Water Environment
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• v.31 no.6
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• pp.700-714
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• 2015

The characteristic of the water quality and pollutant discharge was analyzed at the units watershed of the total amount management in Han-river basin, and after classified in a similar area by multivariate statistical analysis, the main trend such as the water quality trend and pollutant discharge characteristic were analyzed. As a result of this study, the density of the pollutant at the unit watershed is not necessarily identified as discharge density, and the primary management watershed and targeted substances were analyzed depending on the operating status of the environmental infrastructure in watershed and the main pollution factor and discharge path per pollutants. As a result of cluster analysis, watersheds were classified into four groups according to discharge characteristics. It will be used when selecting target area of primary management that is appropriate to the characteristics of each river and establishing efficient water quality improvement plans.