• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2001.11a
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• pp.207-208
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• 2001

• Convergence Security Journal
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• v.8 no.4
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• pp.97-104
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• 2008

Recently, the wireless positioning techniques and mobile computing techniques have rapidly developed to use location data of moving objects. The more the number of moving objects is numerous and the more periodical sampling of locations is frequent, the more location data of moving objects become very large. Hence the system should be able to efficiently manage mass location data, support various spatio-temporal queries for LBS, and solve the uncertainty problem of moving objects. Therefore, in this paper, innovating the location data of moving object effectively, we propose Rend 3DR-tree method to decrease the dead space and complement the overlapping of nodes by utilizing 3DR-tree with the indexing structure to support indexing of current data and history data.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.65-75
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• 2005

Moving-objects databases should efficiently support database queries that refer to the trajectories and positions of continuously moving objects. To improve the performance of these queries. an efficient indexing scheme for continuously moving objects is required. To my knowledge, range queries on current positions cannot be handled by the 3D R-tree and the TB-tree. In order to handle range queries on current and past positions. I modified the original 3D R-tree to keep the now tags. Most of spatio-temporal index structures suffer from the fact that they cannot efficiently process range queries past positions of moving objects. To address this issue. we propose an access method, called the Tagged Adaptive 3DR-tree (or just TA3DR-tree), which is based on the original 3D R-tree method. The results of our extensive experiments show that the Tagged Adaptive 3DR-tree outperforms the original 3D R-tree and the TB-tree typically by a big margin.

• The KIPS Transactions:PartD
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• v.12D no.4 s.100
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• pp.507-520
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• 2005

The R-trees are usually used for an index of trajectories in moving-objects databases. However, they need to access a number of nodes to trace same trajectories because of considering only a spatial proximity. Overlaps and dead spaces should be minimized to enhance the performance of range queries in moving-objects indexes. Trajectories of moving-objects should be preserved to enhance the performance of the trajectory queries. In this paper, we propose the TP3DR-tree(Trajectory Preserved 3DR-tree) using clusters of trajectories for range and trajectory queries. The TP3DR-tree uses two split policies: one is a spatial splitting that splits the same trajectory by clustering and the other is a time splitting that increases space utilization. In addition, we use connecting information in non-leaf nodes to enhance the performance of combined-queries. Our experiments show that the new index outperforms the others in processing queries on various datasets.

• Journal of the Korean Data and Information Science Society
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• v.23 no.5
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• pp.993-1003
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• 2012

The purpose of this study was to estimate the determinants of victory and defeat through analyzing records of Korean men pro-basketball. Statistical models of victory and defeat were established by collecting present basketball records (2010-2011, 2011-2012 season). Korea Basketball League (KBL) informs records of every pro-basketball game data. The six offence variables (2P%, 3P%, FT%, OR, AS, TO), and the four defense variables (DR, ST, GD, BS) were used in this study. PASW program was used for logistic regression and Answer Tree program was used for the decision tree. All significance levels were set at .05. Major results were as follows. In the logistic regression, 2P%, 3P%, and TO were three offense variables significantly affecting victory and defeat, and DR, ST, and BS were three significant defense variables. Offensive variables 2P%, 3P%, TO, and AS are used in constructing the decision tree. The highest percentage of victory was 80.85% when 2P% was in 51%-58%, 3P% was more than 31 percent, and TO was less than 11 times. In the decision tree of the defence variables, the highest percentage of victory was 94.12% when DR was more than 24, ST was more than six, and BS was more than two times.

• Journal of KIISE:Databases
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• v.33 no.4
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• pp.396-408
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• 2006

Moving object databases manage a large amount of past location data which are accumulated as the time goes. To retrieve fast the past location of moving objects, we need index structures which consider features of moving objects. The KDB-tree has a good performance in processing range queries. Although we use the KDB-tree as an index structure for moving object databases, there has an over-split problem in the spatial domain since the feature of moving object databases is to increase the time domain. Because the over-split problem reduces spatial regions in the MBR of nodes inverse proportion to the number of splits, there has a problem that the cost for processing spatial-temporal range queries is increased. In this paper, we propose the dynamic split strategy of the KDB-tree to process efficiently the spatial-temporal range queries. The dynamic split strategy uses the space priority splitting method for choosing the split domain, the recent time splitting policy for splitting a point page to maximize the space utilization, and the last division policy for splitting a region page. We compare the performance of proposed dynamic split strategy with the 3DR-tree, the MV3R-tree, and the KDB-tree. In our performance study for range queries, the number of node access in the MKDB-tree is average 30% less than compared index structures.

• JSTS:Journal of Semiconductor Technology and Science
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• v.10 no.4
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• pp.276-281
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• 2010

A 2.5 V feed-forward second-order deltasigma modulator for audio application is presented. A 9-level quantizer with a tree-structured dynamic element matching (DEM) was employed to improve the linearity by shaping the distortion resulted from the capacitor mismatch of the feedback digital-toanalog converter (DAC). A chopper stabilization technique (CHS) is used to reduce the flicker noise in the first integrator. The prototype delta-sigma analogto-digital converter (ADC) implemented in a 65 nm 1P8M CMOS process occupies 0.747 $mm^2$ and achieves 109.1 dB dynamic range (DR), 85.4 dB signal-to-noise ratio (SNR) in a 24 kHz audio signal bandwidth, while consuming 14.75 mW from a 2.5 V supply.

• Journal of Forest and Environmental Science
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• v.32 no.2
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• pp.129-139
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• 2016

Study was conducted to investigate tree diversity and its population and regeneration status in homegardens of upper Assam, Northeast India through field study by quadrat method. A total of 154 tree species have been recorded from 135 studied homegardens under 109 genera 53 families. Most of these species (79%) are indigenous to our country, while the rest (21%) arealiens (naturalized and cultivated exotics) by origin. Tree species richness per homegarden varies greatly in different homegardens and is ranged from 5 to 52 tree species with a mean of 22 ($SE{\pm}0.58$). A. malaccensis is the most dominant tree species in the studied homegardens contributed 34% of the total tree density of the documented trees. The tree density is much higher with 4,259 individuals $ha^{-1}$ but, basal area ($36.32m^2ha^{-1}$) is very less. Based on the number of individuals present, very rare species is accounted for 10%, rare species 39%, common species 19%, dominants 14% and predominant species 18% in the present study. The population density of 154 tree species is 4,259 (individuals $ha^{-1}$) for adults (>3.18 cm DBH), 5,902 (individuals $ha^{-1}$) for saplings and 38,164 (individuals $ha^{-1}$) for seedlings. The density of seedlings>saplings>adults represents good regeneration status of tree species in studied homegardens. The population structure study showed that about 8% tree species have good regeneration status, 9% have fair regeneration status, 48% have poor regeneration status and 34% tree species have no regeneration. Study suggests that research and development action is needed to stimulate regeneration of those tree species which having high importance value indices but showing poor or no regeneration. Based on present observation, it can be conclude that homegarden can emerge as an effective means for both economic well-being and biodiversity conservation in upper Assam, Northeast India.

• Asia-Pacific Journal of Business
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• v.12 no.4
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• pp.13-40
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• 2021

Purpose - The purpose of this study is to predict corporate corruption in emerging markets such as Brazil, Russia, India, and China (BRIC) using different machine learning techniques. Since corruption is a significant problem that can affect corporate performance, particularly in emerging markets, it is important to correctly identify whether a company engages in corrupt practices. Design/methodology/approach - In order to address the research question, we employ predictive analytic techniques (machine learning methods). Using the World Bank Enterprise Survey Data, this study evaluates various predictive models generated by seven supervised learning algorithms: k-Nearest Neighbour (k-NN), Naïve Bayes (NB), Decision Tree (DT), Decision Rules (DR), Logistic Regression (LR), Support Vector Machines (SVM), and Artificial Neural Network (ANN). Findings - We find that DT, DR, SVM and ANN create highly accurate models (over 90% of accuracy). Among various factors, firm age is the most significant, while several other determinants such as source of working capital, top manager experience, and the number of permanent full-time employees also contribute to company corruption. Research implications or Originality - This research successfully demonstrates how machine learning can be applied to predict corporate corruption and also identifies the major causes of corporate corruption.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.44.4-45
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• 2015

We investigate the properties of galaxies belonging to the filaments in cosmic void regions, using the void catalogue constructed by Pan et al. (2012) from the SDSS DR7. To identify galaxy filaments within a void, voids with 30 or more galaxies are selected as a sample. We identify 3067 filaments in 1050 voids by applying the filament finding algorithm based on minimal spanning tree and reducing processes to spatial distribution of the void galaxies. We study the correlations between galaxy properties and the specific size of filament which quantifies the degree of the filament straightness. For example, the average magnitude and the magnitude of the faintest galaxy in filament decrease as the straightness of the filament increases. We also find that the correlations become stronger in rich filaments than in poor ones with fewer member galaxies. We discuss a physical explanation to our findings and their cosmological implications.