• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.105-114
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• 2006

In ubiquitous environment where various kinds of computers are embedded in persons, objects and environment and they are interconnected and can be used in my place as necessary, different types of data need to be exchanged between heterogeneous machines through home network. In the environment, the efficient processing, transmission and monitoring of image data are essential technologies. We need to make research not only on traditional image processing such as spatial and visual resolution, color expression and methods of measuring image quality but also on transmission rate on home network that has a limited bandwidth. The present study proposes a new motion vector estimation algorithm for transmitting, processing and controlling image data, which is the core part of contents in home network situation and, using algorithm, implements a real time monitoring system of multi dimensional images transmitted from multiple cameras. Image data of stereo cameras to be transmitted in different environment in angle, distance, etc. are preprocessed through reduction, magnification, shift or correction, and compressed and sent using the proposed metamorphosis hierarchical motion vector estimation algorithm for the correction of motion. The proposed algorithm adopts advantages and complements disadvantages of existing motion vector estimation algorithms such as whole range search, three stage search and hierarchical search, and estimates efficiently the motion of images with high variation of brightness using an atypical small size macro block. The proposed metamorphosis hierarchical motion vector estimation algorithm and implemented image systems can be utilized in various ways in ubiquitous environment.

• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.127-132
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• 2006

K-NN (k-Nearest Neighbors), which is a well-known instance-based learning algorithm, simply stores entire training patterns in memory, and uses a distance function to classify a test pattern. K-NN is proven to show satisfactory performance, but it is notorious formemory usage and lengthy computation. Various studies have been found in the literature in order to minimize memory usage and computation time, and NGE (Nested Generalized Exemplar) theory is one of them. In this paper, we propose RPA (Recursive Partition Averaging) and IRPA (Incremental RPA) which is an incremental version of RPA. RPA partitions the entire pattern space recursively, and generates representatives from each partition. Also, due to the fact that RPA is prone to produce excessive number of partitions as the number of features in a pattern increases, we present IRPA which reduces the number of representative patterns by processing the training set in an incremental manner. Our proposed methods have been successfully shown to exhibit comparable performance to k-NN with a lot less number of patterns and better result than EACH system which implements the NGE theory.

• The KIPS Transactions:PartD
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• v.13D no.5 s.108
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• pp.633-640
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• 2006

Spatial clustering, which groups similar objects based on their distance, connectivity, or their relative density in space, is an important component of spatial data mining. Density-based and grid-based clustering are two main clustering approaches. The former is famous for its capability of discovering clusters of various shapes and eliminating noises, while the latter is well known for its high speed. Clustering large data sets has always been a serious challenge for clustering algorithms, because huge data set would make the clustering process extremely costly. In this paper, we propose an enhanced Density-Grid based Clustering algorithm for Large spatial database by setting a default number of intervals and removing the outliers effectively with the help of a proper measurement to identify areas of high density in the input data space. We use a density threshold DT to recognize dense cells before neighbor dense cells are combined to form clusters. When proposed algorithm is performed on large dataset, a proper granularity of each dimension in data space and a density threshold for recognizing dense areas can improve the performance of this algorithm. We combine grid-based and density-based methods together to not only increase the efficiency but also find clusters with arbitrary shape. Synthetic datasets are used for experimental evaluation which shows that proposed method has high performance and accuracy in the experiments.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.267-274
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• 2017

The purpose of this research was to develop and present methods to detect sinkholes which can exist underneath the surface of the ground. First, we buried a water tank with dimensions $1.8{\times}0.8{\times}0.8m$ at a distance of 1.8 m from the surface. This played the role of the sinkhole. Secondly, we created a square zone with sides 12 meters away from the buried water tank. Within this zone, we measured the gravity at 1-meter intervals using a Scintrex CG5 relative gravimeter with a resolution of 0.001 mGal. Additionally, we performed three-dimensional (3-D) gravity modeling to calculate the theoretical values of the relative gravity around our model sinkhole. The resulting values for the relative gravity around the sinkhole depended on the method used. The measured effect of gravity was 0.036 mGal and the effect calculated using 3-D modeling was 0.024 mGal. Our results suggest that sinkholes that are similar in size to the water tank used in this study can be detected using relative gravity surveys. Smaller sinkholes can be detected by reducing the intervals between the relative gravity measurements.

• The Plant Pathology Journal
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• v.36 no.6
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• pp.536-557
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• 2020

Sugarcane yellow leaf virus (SCYLV) is a distinct member of the Polerovirus genus of the Luteoviridae family. SCYLV is the major limitation to sugarcane production worldwide and presently occurring in most of the sugarcane growing countries. SCYLV having high genetic diversity within the species and presently ten genotypes are known to occur based on the complete genome sequence information. SCYLV is present in almost all the states of India where sugarcane is grown. Virion comprises of 180 coat protein units and are 24-29 nm in diameter. The genome of SCYLV is a monopartite and comprised of single-stranded (ss) positive-sense (+) linear RNA of about 6 kb in size. Virus genome consists of six open reading frames (ORFs) that are expressed by sub-genomic RNAs. The SCYLV is phloem-limited and transmitted by sugarcane aphid Melanaphis sacchari in a circulative and non-propagative manner. The other aphid species namely, Ceratovacuna lanigera, Rhopalosiphum rufiabdominalis, and R. maidis also been reported to transmit the virus. The virus is not transmitted mechanically, therefore, its transmission by M. sacchari has been studied in different countries. SCYLV has a limited natural host range and mainly infect sugarcane (Sachharum hybrid), grain sorghum (Sorghum bicolor), and Columbus grass (Sorghum almum). Recent insights in the protein-protein interactions of Polerovirus through protein interaction reporter (PIR) technology enable us to understand viral encoded proteins during virus replication, assembly, plant defence mechanism, short and long-distance travel of the virus. This review presents the recent understandings on virus biology, diagnosis, genetic diversity, virus-vector and host-virus interactions and conventional and next generation management approaches.

• Journal of Korean Society of Transportation
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• v.34 no.4
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• pp.341-353
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• 2016

Highway is mainly in charge of middle-long distance of vehicular travel. Trip length has shown a growing trend due to increased commute distances by the relocation of public agencies. For this reason, the proportion of driver-driven accidents, caused by their fatigue or sleepiness, are very high on highways. However, existing studies related to accident prediction have mainly considered external factors, such as road conditions, environmental factors and vehicle factors, without driving behavior. In this study, we suggested an accident index (FDR, Fatigued Driving Rate) based on traffic behavior using large-scale Car Navigation path data, and exlpored the relationship between FDR and traffic accidents. As a result, FDR and traffic accidents showed a high correlation. This confirmed the need for a paradigm shift (from facilities to travel behavior) in traffic accident prediction studies. FDR proposed in this study will be utilized in a variety of fields. For example, in providing information to prevent traffic accidents (sleepiness, reckless driving, etc) in advance, utilization of core technologies in highway safety diagnostics, selection of priority location of rest areas and shelter, and selection of attraction methods (rumble strips, grooving) for attention for fatigued sections.

• Journal of Korean Society of Transportation
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• v.35 no.3
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• pp.220-233
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• 2017

Traffic volumes are fundamental data widely used in various traffic analysis, such as origin-and-destination establishment, total traveled kilometer distance calculation, congestion evaluation, and so on. The low number of links collecting the traffic-volume data in a large urban highway network has weakened the quality of the analyses in practice. This study proposes a method to estimate the traffic volume data on a highway link where no collection device is available by introducing a spatial statistic technique with (1) the traffic-volume data from TOPIS, and National Transport Information Center in the Ministry of Land, Infrastructure, and (2) the navigation data from private navigation. Two different component models were prepared for the interrupted and the uninterrupted flows respectively, due to their different traffic-flow characteristics: the piecewise constant function and the regression kriging. The comparison of the traffic volumes estimated by the proposed method against the ones counted in the field showed that the level of error includes 6.26% in MAPE and 5,410 in RMSE, and thus the prediction error is 20.3% in MAPE.

• Horticultural Science & Technology
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• v.31 no.5
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• pp.580-589
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• 2013

This study was carried out to evaluate the suitability of microsatellite markers for varietal identification and genetic relationship of 170 commercial pepper cultivars. The relationship between marker genotypes and 11 pepper cultivars with different morphological traits was also analyzed. Of the 302 pairs of microsatellite primers screened against 11 pepper cultivars, 24 pairs were highly polymorphic in terms of number of alleles. These markers were applied for the construction of DNA profile data base for 170 commercial pepper cultivars. A total of 164 polymorphic amplified fragments were obtained from 24 microsatellite primers. The average polymorphism information content was 0.673 ranging from 0.324 to 0.824. One hundred and sixty four microsatellite alleles were used to calculate Jaccard's distance coefficients using unweighted pair group method. A clustering group of varieties, based on the results of microsatellite analysis, were categorized into 3 major groups corresponding to morphological traits. The phenogram discriminated all varieties by markers genotypes. These microsatellite markers will be useful as a tool for protection of plant breeders' intellectual property rights through variety identification in distinctness, uniformity and stability test.

• Korean Journal of Ecology and Environment
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• v.41 no.1
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• pp.98-103
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• 2008

Genetic diversity and population genetic structure within or among three stream populations (Gab, Baekgok and Ji streams) of Korean endangered natural monument fish, Iksookimia choii, were assessed by amplified fragment length polymorphism (AFLP). AFLP analysis using three primer combinations generated 104 to 106 AFLP bands, and percent polymorphic bands were similar in those three populations ranging 21.5 to 24.5%. Heterozygosity and genetic diversity within or among populations were quite low for all of these populations with average values ranging from 0.067 to 0.084 and from 0.076 to 0.087, respectively. Analyses of pairwise distance and genetic similarity among three populations of I. choii also revealed the similar results with very low genetic differentiation one another. Although pairwise Fst values were very low, our data clearly indicated distinct genetic differentiation among the three populations. This is the first report concerning the genetic diversity and differentiation of this species, and provides basic genetic information that should facilitate attempts to conserve this species.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.3
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• pp.175-186
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• 2017

In this study was to survey method of national/public land actual condition survey to utilization of UAV, in order to evaluate the economic and accuracy. we carried out the comparative evaluation of the cadastral status surveying in terms of accuracy of parcel checkpoint, economical costs. The results are summarized as follows. First, average position error of the orthoimage was 0.033m in X error, 0.023m in Y error when the RMSE average calculated 0.046m from the intersection of plane distance connections. Secondly, it was appeared the accuracy of the orthophotograph is 0.076m at the maximum RMSE of the UAV orthoimage check point and 0.042m at the minimum RMSE compared with the VRS-GNSS survey results. Thirdly, when the allowable error specified in the implementing regulation of the current cadastral survey is applied, all of the checkpoint of 0.360m tolerance corresponding to the scale of 1/1,200 is satisfied. Finally, UAV utilization method in national/public land actual condition survey is 26,497,436(KRW) cheaper than cadastral survey method for In the economic evaluation of national/public land actual condition survey. Therefore, as a result of this study shows that the method of utilizing UAV in the national/public land actual condition survey satisfies legal standards in terms of accuracy and economical aspect is a way to further reduce the local government budget.