• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.794-804
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• 2012

For the geometric computations on the protein molecules, the proximity queries, such as computing the minimum distance from an arbitrary point to the molecule or detecting the collision between a point and the molecule, are essential. For the proximity queries, the efficiency of the computation time can be different according to the data structure used for the molecule. In this paper, we present the data structures and algorithms for applying proximity queries to a molecule with GPU acceleration. We present two data structures, a voxel map and a sphere tree, where the molecule is represented as a set of spheres, and corresponding algorithms. Moreover, we show that the performance of presented data structures are improved from 3 to 633 times compared to the previous data structure for the molecules containing 1,000~15,000 atoms.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.48-52
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• 2010

In this paper, we introduce a new path planning algorithm which combines the merits of a visibility graph algorithm and an adaptive cell decomposition. We quantize a given map with empty cells, blocked cells, and mixed cells, then find the optimal path on the quantized map using a visibility graph algorithm. For reducing the number of the quantized cells we use the quad-tree technique which is used in an adaptive cell decomposition, and for improving the performance of the visibility checking in making a visibility graph we propose a new visibility checking method which uses the property of the quad-tree instead of the well-known rotational sweep-line algorithm. For the more efficient visibility checking, we propose two additional improvements for our suggested method. Both of them are used for reducing the visited cells in the quad-tree. The experiments for a performance comparison of our algorithm with other well-known algorithms show that our proposed method is superior to others.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.10
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• pp.909-914
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• 2012

The paper introduces the RFID location based Tree Management System (TMS) using UHF RFID tag and GPS. The bolt shape tag has been developed since the wood material has high dielectric constant. Since the characteristics and impedance of tag antenna can be changed by the material next to the tag, the plastic bolt shape tag antenna has to be carefully designed with consideration of the high dielectric constant of the wood material. The RFID TMS system has been utilized with the bolt shape tag antenna and GPS. The TMS system uses and links Google map to locate the location of the trees. Therefore, this system allow us to manage the trees economically and efficiently.

• Proceedings of the Korean Society of Plant Biotechnology Conference
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• 2002.04a
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• pp.101-109
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• 2002

A lot of SSRs (simple sequence repeats) in peach and pear from enriched genomic libraries and in peach from a cDNA library were developed. These SSRs were applied to other related species, giving phenograms of 52 Prunus and 60 pear accessions. Apple SSRs could also be successfully used in Pyrus spp. Thirteen morphological traits were characterized on the basis of the linkage map obtained from an $F_2$ population of peach. This map was compiled with those morphological markers and 83 DNA markers, including SSR markers used as anchor loci, to compare different peach maps. Molecular markers tightly linked to new root-knot nematode resistance genes were also found. A linkage map including disease-related genes, pear scab resistance and black spot susceptibility, in the Japanese pear Kinchaku were constructed using 118 RAPD markers. Another linkage map, of the European pear Bartlett, was also constructed with 226 markers, including 49 SSRs from pear, apple, peach and chewy. Maps of other Japanese pear cultivars, i.e., Kousui and Housui, were also constructed. These maps were the first results of pear species.

• Proceedings of the Korean Society of Plant Biotechnology Conference
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• 2002.04b
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• pp.101-109
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• 2002

A lot of SSRs (simple sequence repeats) in peach and pear from enriched genomic libraries and in peach from a cDHA library were developed. These SSRs were applied to other related species, giving phenograms of 52 Prunus and 60 pear accessions. Apple SSRs could also be successfully used in Pyrus spp. Thirteen morphological traits were characterized on the basis of the linkage map obtained from an Fa population of peach. This map was compiled with those morphological markers and 83 DHA markers, including SSR markers used as anchor loci, to compare different peach maps. Molecular markers tightly linked to new root-knot nematode resistance genes were also found. A linkage map including disease-related genes, pear scab resistance and black spot susceptibility, in the Japanese pear Kinchaku were constructed using 118 RAPD markers. Another linkage map, of the European pear Bartlett, was also constructed with 226 markers, including 49 SSRs from pear, apple, peach and cherry. Maps of other Japanese pear cultivars, i.e., Kousui and Housui, were also constructed. These maps were the first results of pear species.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.1-10
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• 2018

Wide-area monitoring of tree-related high impedance fault (THIF) efficiently contributes to increase reliability of large-scaled network, since the failure to early location of them may results in critical lines tripping and consequently large blackouts. In the first place, this wide-area monitoring of THIF requires managing the placement of sensors across large power grid network according to THIF detection objective. For this purpose, current paper presents a framework in which sensors are distributed according to a predetermined risk map. The proposed risk map determines the possibility of THIF occurrence on every branch in a power network, based on electrical conductivity of trees and their positions to power lines which extracted from spectral data. The obtained possibility value can be considered as a weight coefficient assigned to each branch in sensor placement problem. The next step after sensors deployment is to on-line monitor based on moving data window. In this on-line process, the received data window is evaluated for obtaining a correlation between low frequency and high frequency components of signal. If obtained correlation follows a specified pattern, received signal is considered as a THIF. Thereafter, if several faulted section candidates are found by deployed sensors, the most likely location is chosen from the list of candidates based on predetermined THIF risk map.

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.37-50
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• 2021

Query applications based on nested data, the most commonly used form of data representation on the web, especially precise query, is becoming more extensively used. MapReduce, a distributed architecture with parallel computing power, provides a good solution for big data processing. However, in practical application, query requests are usually concurrent, which causes bottlenecks in server processing. To solve this problem, this paper first combines a column storage structure and an inverted index to build index for nested data on MapReduce. On this basis, this paper puts forward an optimization strategy which combines query execution service tree and frequent sub-query trajectory to reduce the response time of frequent queries and further improve the efficiency of multi-user concurrent queries on large scale nested data. Experiments show that this method greatly improves the efficiency of nested data query.

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.23-30
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• 2015

As BigData is issued, many applications that operate based on the results of data analysis have been developed, typically applications are products recommend service of e-commerce application service system, search service on the search engine service and friend list recommend system of social network service. In this paper, we suggests a decision frequent pattern tree that is combined the origin frequent pattern tree that is mining similar pattern to appear in the data set of the existing data mining techniques and decision tree based on the theory of computer science. The decision frequent pattern tree algorithm improves about problem of frequent pattern tree that have to make some a lot's pattern so it is to hard to analyze about data. We also proposes to model for a Mapredue framework that is a programming model to help to operate in distributed environment.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.4
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• pp.49-65
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• 2022

Since trees in the city are green assets that create a healthy environment for the city, systematic management of trees improves urban ecosystem services. The sporadic urban tree information centered on the site is vast, and it is difficult to manage the data, so efforts to increase efficiency are needed. This paper summarizes tree data inventory based on data constructed by Seoul Green Trust activists and constructs and discloses online database maps using Tableau Software. In order to verify the utilization of the map, we divided into consumer and supplier aspects to collect various opinions and reflect feedback to implement tree database maps for each area and species of Seoul Forest. As a result, the utilization value of tree database in urban parks was presented. The technical significance of this study is to systematically record the process of constructing and implementing a dashboard directly using the Mapbox platform and Tableau Software in the field of landscaping for the first time in Korea. In addition, the implications and supplements of landscape information were derived by collecting user opinions on the results. This can be used as an exploratory basis in the process of developing online-based services such as web and apps by utilizing landscaping tree information in the future. Although the visualization database currently constructed has limitations that ordinary users cannot interact in both directions because it utilizes business intelligence tools in terms of service provision it has affirmed both the database construction and its usability in web public format. In the future it is essential to investigate the assets of the trees in the city park and to build a database as a public asset of the city. The survey participants positively recognized that information is intuitively presented based on the map and responded that it is necessary to provide information on the overall urban assets such as small parks and roadside trees by using open source maps in the future.

• International journal of advanced smart convergence
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• v.12 no.1
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• pp.92-100
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• 2023

Wireless communication technology is becoming increasingly prevalent in smart factories, but the rise in the number of wireless devices can lead to interference in the ISM band and obstacles like metal blocks within the factory can weaken communication signals, creating radio shadow areas that impede information exchange. Consequently, accurately determining the radio communication coverage range is crucial. To address this issue, a Radio Environment Map (REM) can be used to provide information about the radio environment in a specific area. In this paper, a technique for estimating an indoor REM usinga mobile robot and machine learning methods is introduced. The mobile robot first collects and processes data, including the Received Signal Strength Indicator (RSSI) and location estimation. This data is then used to implement the REM through machine learning regression algorithms such as Extra Tree Regressor, Random Forest Regressor, and Decision Tree Regressor. Furthermore, the numerical and visual performance of REM for each model can be assessed in terms of R2 and Root Mean Square Error (RMSE).