• Journal of the Economic Geographical Society of Korea
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• v.21 no.4
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• pp.321-334
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• 2018

There are many factors that cause uneven regional developments in the country and one of main factors is outflow of regional income or products. The purpose of this study is to analyze regional production runoff by comparing GRDP and GRNI in basic local governments level. In this study, GRNI of basic local governments are estimated by local income tax data, The results of the study are as follows. Firstly, GRNI is more concentrated than GRDP. The analysis of Moran I showed that the spatial autocor-relation of GRNI is more distinct than that of GRDP. Local Moran I analysis shows that spatial hot spots and cold spots are more apparent in GRNI than GRDP. Secondly, the outflows of GRDP into a small number of regions are apparent. In about 80% of basic local governments, the net outflows of GRDP occur. The large net outflow regions are cities where manufacturing industry has developed and in the 20 lowest net outflow rate regions, 70-80% of GRDP outflows. The large net inflow regions are metropolitan area in Seoul and large local cities. Seocho-gu, Yongsan-gu, and Gangnam-gu in Seoul have a large net inflows and net inflow rates are over 90% of GRDP.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.1
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• pp.127-136
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• 2019

Tunnel construction by TBMs should be supported by the performance of a screw conveyor in order to obtain the optimum penetration rate, so studies related to the screw conveyor performance have been being conducted. Compared to the study on the performance of the screw conveyor for the soil, however, the research on the performance of the screw conveyor for the rock is insufficient. Considering the domestic tunnel sites with more rock layers than soil layers, simulation of discharge of 6 types of rock chips by the screw conveyor was conducted using DEM. Regardless of the shape and volume of the rock chips, the discharge rates of the rock chips by the parallel placed screw conveyor at a speed of 10 RPM in the same rock mass were about 20% (standard deviation: 1.3%) of the maximum volume of discharge rate by the screw conveyor. It is expected that this study can be used as a reference material for screw conveyor design and operation in TBM excavations in rock masses.

• Journal of Korea Spatial Information System Society
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• v.9 no.1
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• pp.105-115
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• 2007

Data mining extracts interesting knowledge from a large database. Among numerous data mining techniques, research work is primarily concentrated on clustering and association rules. The clustering technique of the active research topics mainly deals with analyzing spatial and attribute data. And, the technique of association rules deals with identifying frequent patterns. There was an advanced apriori algorithm using an existing bit-clustering algorithm. In an effort to identify an alternative algorithm to improve apriori, we investigated FP-Growth and discussed the possibility of adopting bit-clustering as the alternative method to solve the problems with FP-Growth. FP-Growth using bit-clustering demonstrated better performance than the existing method. We used chess data in our experiments. Chess data were used in the pattern mining evaluation. We made a creation of FP-Tree with different minimum support values. In the case of high minimum support values, similar results that the existing techniques demonstrated were obtained. In other cases, however, the performance of the technique proposed in this paper showed better results in comparison with the existing technique. As a result, the technique proposed in this paper was considered to lead to higher performance. In addition, the method to apply bit-clustering to GML data was proposed.

• Korean Journal of Mineralogy and Petrology
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• v.33 no.3
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• pp.251-258
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• 2020

Single crystal of fully dehydrated and partially Ca²⁺-exchanged zeolites A (|Ca₄Na₄|[Si₁₂Al₁₂O₄₈]-LTA) was brought into contact with Se in fine pyrex capillary at 523 K for 5 days. Crystal structure of Se-sorbed |Ca₄Na₄|[Si₁₂Al₁₂O₄₈]-LTA has been determined by single-crystal X-ray diffraction techniques at 294 K in the cubic space group $Pm{\bar{3}}m$ (a = 12.2787(13) Å). The crystal structure of yellow |Ca₄Na₄Se₄|[Si₁₂Al₁₂O₄₈]-LTA has been refined to the final error indices of R₁/wR₂ = 0.0960/0.3483 with 327 reflections for which F_o > 4s(F_o). In this structure, 4 Na⁺ and 4 Ca²⁺ ions fill every 6-ring site: These ions are all found at three crystallographic positions, on 3-fold axes equipoints of opposite 6-rings. Selenium atoms are found at three crystallographically distinct positions: 2 Se atoms per unit cell at Se(1) are located opposite 6-rings in the sodalite cavity (Se(1)-Na(1) = 2.53(5) Å) and 1 at Se(2) opposite 4-rings (Se(2)-O(1) = 2.76(10) Å) and 1 at Se(3) opposite 6-rings in the large cavity (Se(3)-Na(1) = 2.48(5) Å). Two molecular of Se₂ (Se(1)-Se(1) = 2.37(7) or 2.90(8) Å and Se(2)-Se(3) = 2.91(5) ) Å) are found in all sodalite cavity and large cavity. Other clusters such as Se₄ and Se₈ could be existed in large cavity. The inter-selenium distances turned out to be longer that of gases Se₂ molecule.

• Progress in Medical Physics
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• v.14 no.4
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• pp.211-217
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• 2003

The Principal component analysis (PCA) is a well-known data analysis method that is useful in linear feature extraction and data compression. The PCA is a linear transformation that applies an orthogonal rotation to the original data, so as to maximize the retained variance. PCA is a classical technique for obtaining an optimal overall mapping of linearly dependent patterns of correlation between variables (e.g. neurons). PCA provides, in the mean-squared error sense, an optimal linear mapping of the signals which are spread across a group of variables. These signals are concentrated into the first few components, while the noise, i.e. variance which is uncorrelated across variables, is sequestered in the remaining components. PCA has been used extensively to resolve temporal patterns in neurophysiological recordings. Because the retinal signal is stochastic process, PCA can be used to identify the retinal spikes. With excised rabbit eye, retina was isolated. A piece of retina was attached with the ganglion cell side to the surface of the microelectrode array (MEA). The MEA consisted of glass plate with 60 substrate integrated and insulated golden connection lanes terminating in an 8${\times}$8 array (spacing 200 $\mu$m, electrode diameter 30 $\mu$m) in the center of the plate. The MEA 60 system was used for the recording of retinal ganglion cell activity. The action potentials of each channel were sorted by off­line analysis tool. Spikes were detected with a threshold criterion and sorted according to their principal component composition. The first (PC1) and second principal component values (PC2) were calculated using all the waveforms of the each channel and all n time points in the waveform, where several clusters could be separated clearly in two dimension. We verified that PCA-based waveform detection was effective as an initial approach for spike sorting method.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.1
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• pp.70-79
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• 2014

Following the technology developments of traffic network and communication for the wide area, the importance of the cooperation system to vitalize the wide area economy is increasing. Therefore, in this study, DongNam Kwon industry information system is established for the industrial information sharing based on GIS in the DongNam Kwon wide area economy. The DongNam Kwon is an industrial integration area centered with the manufacturing so that the operation of effective industrial cluster and cooperation systems are required across the administrational boundaries. To establish the database of the information, the information system was established utilizing already established industrial databases in Busan, Ulsan and Gyeongnam. But, various issues caused by the discordances among the data of each local government and the insufficiency of GIS based location information have been found. According to the analysis, the standardization considering the courses of collection, distributions and utilization are required immediately to solve the issues. This study establishes an 2-way industrial information system enabling the information creation and the phased approach between the administrator and the user in the bi-directions on the web by utilizing cadastral and numerical maps. The result of this study would have a meaning in providing a fundamental frame for cooperative responses and cooperation system for DongNam Kwon's industrial promotion using industrial information sharing.

• Journal of Internet Computing and Services
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• v.9 no.5
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• pp.117-130
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• 2008

This paper proposes a stable and robust method to distinct the color similarity for clothes using the LBG algorithm under various light sources, Since the conventional methods, such as the histogram intersection and the accumulated histogram, are profoundly sensitive to the changing of light environments, the distinction of color similarity for the same cloth can be different due to the complicated light sources. To reduce the effects of the light sources, the properties of hue and saturation which consistently sustain the characteristic of the color under the various changes of light sources are analyzed to define the characteristic of the color distribution. In a two-dimensional space determined by the properties of hue and saturation, the LBG algorithm, a non-parametric clustering approach, is applied to examine the color distribution of images for each clothes. The color similarity of images is defined by the average of Euclidean distance between the mapping clusters which are calculated from the result of clustering of both images. To prove the stability of the proposed method, the results of the color similarity between our method and the traditional histogram analysis based methods are compared using a dozen of cloth examples that obtained under different light environments. Our method successively provides the classification between the same cloth image pair and the different cloth image pair and this classification of color similarity for clothe images obtains the 91.6% of success rate.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.669-678
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• 2018

This study developed information technology infrastructures for building a driving environment analysis platform using various big data, such as vehicle sensing data, public data, etc. First, a small platform server with a parallel structure for big data distribution processing was developed with H/W technology. Next, programs for big data collection/storage, processing/analysis, and information visualization were developed with S/W technology. The collection S/W was developed as a collection interface using Kafka, Flume, and Sqoop. The storage S/W was developed to be divided into a Hadoop distributed file system and Cassandra DB according to the utilization of data. Processing S/W was developed for spatial unit matching and time interval interpolation/aggregation of the collected data by applying the grid index method. An analysis S/W was developed as an analytical tool based on the Zeppelin notebook for the application and evaluation of a development algorithm. Finally, Information Visualization S/W was developed as a Web GIS engine program for providing various driving environment information and visualization. As a result of the performance evaluation, the number of executors, the optimal memory capacity, and number of cores for the development server were derived, and the computation performance was superior to that of the other cloud computing.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.293-302
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• 2016

Since the electricity is produced and consumed simultaneously, predicting the electric load and securing affordable electric power are necessary for reliable electric power supply. In particular, a university campus is one of the highest power consuming institutions and tends to have a wide variation of electric load depending on time and environment. For these reasons, an accurate electric load forecasting method that can predict power consumption in real-time is required for efficient power supply and management. Even though various influencing factors of power consumption have been discovered for the educational institutions by analyzing power consumption patterns and usage cases, further studies are required for the quantitative prediction of electric load. In this paper, we build an electric load forecasting model by implementing and evaluating various machine learning algorithms. To do that, we consider three building clusters in a campus and collect their power consumption every 15 minutes for more than one year. In the preprocessing, features are represented by considering periodic characteristic of the data and principal component analysis is performed for the features. In order to train the electric load forecasting model, we employ both artificial neural network and support vector machine. We evaluate the prediction performance of each forecasting model by 5-fold cross-validation and compare the prediction result to real electric load.

• The KIPS Transactions:PartA
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• v.16A no.6
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• pp.411-418
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• 2009

Vector quantization algorithm based on fuzzy clustering has been widely used in the field of data compression since the use of fuzzy clustering analysis in the early stages of a vector quantization process can make this process less sensitive to its initialization. However, the process of fuzzy clustering is computationally very intensive because of its complex framework for the quantitative formulation of the uncertainty involved in the training vector space. To overcome the computational burden of the process, this paper introduces an array architecture for the implementation of fuzzy vector quantization (FVQ). The arrayarchitecture, which consists of 4,096 processing elements (PEs), provides a computationally efficient solution by employing an effective vector assignment strategy during the clustering process. Experimental results indicatethat the proposed parallel implementation providessignificantly greater performance and efficiency than appropriately scaled alternative array systems. In addition, the proposed parallel implementation provides 1000x greater performance and 100x higher energy efficiency than other implementations using today's ARMand TI DSP processors in the same 130nm technology. These results demonstrate that the proposed parallel implementation shows the potential for improved performance and energy efficiency.