• Korean journal of applied entomology
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• v.16 no.1 s.30
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• pp.65-67
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• 1977

Yield losses from rice dwarf virus infection are significant in Korea. Rice dwarf virus(RDV) was purified and RDV-antiserum was produced. The purified virus, mixed with an adjuvant(1:1) was injected every 10 to 14 days into rabbits. Three injections .were sufficient to produce an antiserum of 1/4,096 titer. The produced antisera will be used to facilitate the detection and identification of RDV in rice plants and in the RDV leafhopper vectors.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.678-681
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• 2004

In this paper, efficient tracking of a moving object using optimal representative blocks is implemented by a mobile robot with a pan-tilt camera. The key idea comes from the fact that when the image size of moving object is shrunk in an image frame according to the distance between the camera of mobile robot and the moving object, the tracking performance of a moving object can be improved by changing the size of representative blocks according to the object image size. Motion estimation using Edge Detection(ED) and Block-Matching Algorithm(BMA) is often used in the case of moving object tracking by vision sensors. However these methods often miss the real-time vision data since these schemes suffer from the heavy computational load. In this paper, the optimal representative block that can reduce a lot of data to be computed, is defined and optimized by changing the size of representative block according to the size of object in the image frame to improve the tracking performance. The proposed algorithm is verified experimentally by using a two degree-of-freedom active camera mounted on a mobile robot.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.19
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• pp.8035-8040
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• 2014

Gastric cancer is the second after lung cause of cancer-related mortality in the world. Early detection and treatment can lead to a long survival time. Recently microarrays and next generation sequencing (NGS) have become very useful tools of comprehensive research into gastric cancer, facilitating the identification of treatment targets and personalized treatments. However, there are numerous challenges from cancer target discovery to practical clinical benefits. Although there are many biomarkers and target agents, only a minority of patients are tested and treated accordingly. Microarray technology with maturity was established more than 10 years ago, and has been widely used in the study of functional genomics, systems biology, and genomes in medicine. Second generation sequencing technology is more recent, but development is very fast, and it has been applied to the genome, including sequencing and epigenetics and many aspects of functional genomics. Here we review insights gained from these studies regarding the technology of microarray and NGS, how to elucidate the molecular basis of gastric cancer and identify potential therapeutic targets, and how to analyse candidate genes. We also discuss the challenges and future directions of such efforts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3104-3120
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• 2017

The intelligent monitoring system has been successfully applied in many fields such as: monitoring of production lines, transportation, etc. Smart surveillance systems have been developed and proven effective in some specific areas such as monitoring of human activity, traffic, etc. Most of critical application monitoring systems involve object tracking as one of the key steps. However, task of tracking of moving object is not easy. In this paper, the authors propose a method to implement human object tracking in outdoor environment based on human features in shearlet domain. The proposed method uses shearlet transform which combines the human features with context-sensitiveness in order to improve the accuracy of human tracking. The proposed algorithm not only improves the edge accuracy, but also reduces wrong positions of the object between the frames. The authors validated the proposed method by calculating Euclidean distance and Mahalanobis distance values between centre of actual object and centre of tracked object, and it has been found that the proposed method gives better result than the other recent available methods.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1185-1199
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• 2016

Two phase sampling (double sampling) is often used when there is inadequate population information for proper stratification. Many recent papers have been devoted to the estimation method to improve the precision of the estimator using first phase information. In this study we suggested outlier weight adjustment methods to improve estimation precision based on the weight of the generalized ratio-cum-product estimator. Small simulation studies are conducted to compare the suggested methods and the usual method. Real data analysis is also performed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2554-2580
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• 2018

Lenstra-Lenstra-$Lov{\acute{a}}sz$ (LLL) is an effective receiving algorithm for Multiple-Input-Multiple-Output (MIMO) systems, which is believed can achieve full diversity in MIMO detection of fading channels. However, the LLL algorithm features polynomial complexity and shows poor performance in terms of convergence. The reduction of algorithmic complexity and the acceleration of convergence are key problems in optimizing the LLL algorithm. In this paper, a variant of the LLL algorithm, the Hybrid-Fix-and-Round LLL algorithm, which combines both fix and round measurements in the size reduction procedure, is proposed. By utilizing fix operation, the algorithmic procedure is altered and the size reduction procedure is skipped by the hybrid algorithm with significantly higher probability. As a consequence, the simulation results reveal that the Hybrid-Fix-and-Round-LLL algorithm carries a faster rate of convergence compared to the original LLL algorithm, and its algorithmic complexity is at most one order lower than original LLL algorithm in real field. Comparing to other families of LLL algorithm, Hybrid-Fix-and-Round-LLL algorithm can make a better compromise in performance and algorithmic complexity.

• Journal of Information Technology Applications and Management
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• v.12 no.4
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• pp.93-104
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• 2005

Recently, RFID/USN is one of fundamental technologies in information and communications networks. Low-Rate WPAN, IEEE802.15.4 is a low-cost communication network that allows wireless connectivity in applications with limited Power and relaxed throughput requirements. Its applications are building automation, personal healthcare, industrial control, consumer electronics, and so on. Some applications require location information. Of course location awareness is useful to improve usability of data Low-Rate WPAN Is regarded as a key specification of the sensor network with the characteristics of wireless communication, computing, energy scavenging, self-networking, and etc. Unfortunately ZigBee alliance propose a lot of applications based on location aware technologies, but the specification and low-rate WPAN devices don't support anything about location-based services. RSSI ( Received Signal Strength indication) is for energy detection to associate, channel selection, and etc. RSSI is used to find the location of a potable device in WLAN. In this paper we studied indoor location awareness using vector matching of RSSI in low-Rate wireless PAN. We analyzed the characteristics of RSSI according to distance and experimented location awareness. We implemented sensor nodes with different shapes and configured the sensor network for the location awareness with 4 fixed nodes and a mobile node. We try to contribute developing location awareness method using RSSI in 3-dimension space.

• Spatial Information Research
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• v.15 no.1
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• pp.25-33
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• 2007

The purpose of this study is to assess spatio-temporal variation of Imha Dam water quality according to suspended sediment algorithm using Landsat and SPOT 5 data. In order to learn synchronous suspended sediment concentrations(SSC) in Imha Dam waters, the satellite remote sensing data are analyzed. The key procedure of this research is that we should know the relationships between suspended sediment concentrations and satellite-detected reflectance. However, the SSC algorithm has the limitation that it must be compared calculated SSC with synchronous ground-truth data in the Dam water. Based upon the linear response from satellite-detected reflectance, SSC algorithm validated an efficient algorithm to estimate proportional factor and then derived an empirical equation far SSC estimations.

• International Journal of Concrete Structures and Materials
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• v.9 no.2
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• pp.133-143
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• 2015

This paper describes the test results and nonlinear analysis of reinforced concrete T-beams strengthened by bonded steel plates under increasing static loading conditions. The first part of this paper discusses the flexural tests on five T-beams, including the test model design (based on similarity principles), test programs, and test procedure. The second part discusses the nonlinear numerical analysis of the strengthened beams, in which a concrete damage plasticity model and a cohesive behavior were adopted. The numerical analysis results are compared with experimental data and show good agreement. The area of bonded steel plate and the anchor bolt spacing were found to have an impact on the cracking load, yield load, and ultimate load. An increase in the area of steel plate and a reduction of the anchor spacing could significantly improve the cracking and ultimate loads and decrease the damage of the beam.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.6
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• pp.11-20
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• 2007

This paper proposes a new efficient method to detect ellipses using a segment merging based Randomized Hough Transform. The key idea of the proposed method is to separate single line segments from an edge image, to estimate ellipses from any pair of the single line segments using Randomized Hough Transform (RHT), and to merge the ellipses. This algorithm is able to accuracy estimate the number of ellipses and largely improves the computational time by reducing iterations.