• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.355-363
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• 2011

Recently, as one of several methods to improve the performance of DVC(Distributed Video Coding) system, many research works are focusing on the iterative refinement of side information. Most of the conventional techniques are mainly based on the relationship between the reconstruction level and side information, or the vector median filtering of motion vectors, but, their performance improvements are restricted. In order to overcome the performance limit of the conventional schemes, in this paper, a side information generation scheme is designed by measuring the block-cost estimation. Then, by adaptively selecting the compensation mode using the received bit-plane information, we propose a block-adaptive iterative refinement which is efficient for non-symmetric moving objects. Computer simulations show that, by using the proposed refinement method, the performance can be improved up to 0.2 dB in rate-distortion.

• The Plant Pathology Journal
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• v.27 no.1
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• pp.37-43
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• 2011

Rice stripe virus (RSV) is one of serious epidemic pathogens for rice species grown in many Asian countries. Therefore, it is necessary to produce a diagnostic detection kit applicable in fields for RSV detection. In this study, RSV proteins that were derived from recombinant proteins and synthetic polypeptides as antigens were generated and were raised in rabbits for antiserum production. Among seven proteins in RSV, genes that code for NCP and NS3 proteins were cloned and subcloned into vector carrying His-tag protein and were expressed in E. coli. Of two recombinant proteins, only anti-NCP displayed stable hybridization signals in western blot analysis. Alternately, synthetic RSV polypeptides for CP, NCP, NS3 and NSvc4 we also generated and only antibodies against CP and NCP were very effective to detect RSV in both RSV infected rice and weed plants. However, antibodies against NS3 and NSvc4 showed weak specific bands as well as strong non-specific background due to the difference of viral proteins produced in the infected leaves. In summary, the antibodies generated against RSV proteins produced in this study will be useful for various assays such as for RSV diagnostic detection, immunoprecipitation, protein purification, and western blot analysis.

• Korean Journal of Poultry Science
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• v.42 no.3
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• pp.239-245
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• 2015

Transgenic animals have been widely used for developmental biology studies, as disease models, and even in industry such as transgenic bioreactor animals. For transgenic birds, quail has the great advantages of small body size, short generation time, and frequent egg production. To date, retroviral or lentiviral transduction has been used to generate transgenic quail for various purposes. However, the efficiency of transgenic offspring production with these methods is relatively low and viral vector usage has safety issues. Unfortunately, non-viral transgenesis has not been established in quail due to a deficiency of stem cell and germ cell culture systems. In this study, we established a direct in ovo lipofection method that could be used to create transgenic quail without germline-competent cells or viruses. To optimize the injection stage during embryo development, the liposome complex (containing piggyBacCMV-GFP and transposase plasmids) was introduced into an embryonic blood vessel at 50 hr, 55 hr or 60 hr. GFP expression was detected in various tissues (heart, kidney, liver and stomach) on day 12 of incubation under a fluorescence microscope. Additionally, GFP-positive cells were detected in the recipient embryonic gonads. In conclusion, the direct in ovo lipofection method with the piggyBac transposon could be an efficient and useful tool for generating transgenic quail.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.1
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• pp.68-76
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• 1999

The intuitive understanding of the dynamic pattern generation in asymmetric networks may be useful for developing models of dynamic information processing. In this paper, dynamic behavior of the ring connection neural network in which each neuron is only to its nearest neurons with binary synaptic weights of ±1, has been inconnected vestigated Simulation results show that dynamic behavior of the network can be classified into only three categories: fixed points, limit cycles with basin and limit cycles with no basin. Furthermore, the number and the type of limit cycles generated by the networks have been derived through analytical method. The sufficient conditions for a state vector of n-neuron network to produce a limit cycle of n- or 2n-period are also given The results show that the estimated number of limit cycle is an exponential function of n. On the basis of this study, cyclic connection neural network may be capable of storing a large number of dynamic information.

• Korean Journal of Remote Sensing
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• v.22 no.2
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• pp.123-129
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• 2006

High-resolution aerial color image offers great possibilities for geometric and semantic information for spatial data generation. However, shadow casts by buildings and trees in high-density urban areas obscure much of the information in the image giving rise to potentially inaccurate classification and inexact feature extraction. Though many researches have been implemented for solving shadow casts, few studies have been carried out about the extraction of features hindered by shadows from aerial color images in urban areas. This paper presents a asphalt road boundary extraction technique that combines information from aerial color image and LIDAR (LIght Detection And Ranging) data. The following steps have been performed to remove shadow effects and to extract road boundary from the image. First, the shadow regions of the aerial color image are precisely located using LEAR DSM (Digital Surface Model) and solar positions. Second, shadow regions assumed as road are corrected by shadow path reconstruction algorithms. After that, asphalt road boundary extraction is implemented by segmentation and edge detection. Finally, asphalt road boundary lines are extracted as vector data by vectorization technique. The experimental results showed that this approach was effective and great potential advantages.

• Journal of Magnetics
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• v.21 no.4
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• pp.509-515
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• 2016

We report on development of a ground-based bi-axial Search-Coil Magnetometer (SCM) designed to measure time-varying magnetic fields associated with magnetosphere-ionosphere coupling processes. The instrument provides two-axis magnetic field wave vector data in the Ultra Low Frequency or ULF (1 mHz to 5 Hz) range. ULF waves are well known to play an important role in energy transport and loss in geospace. The SCM will primarily be used to observe generation and propagation of the subclass of ULF waves. The analog signals produced by the search-coil magnetic sensors are amplified and filtered over a specified frequency range via electronics. Data acquisition system digitizes data at 10 samples/s rate with 16-bit resolution. Test results show that the resolution of the magnetometer reaches $0.1pT/{\sqrt{Hz}}$ at 1 Hz, and demonstrate its satisfactory performance, detecting geomagnetic pulsations. This instrument is scheduled to be installed at the Korean Antarctic station, Jang Bogo, in the austral summer 2016-2017.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1765-1794
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• 2019

Genetic Programming (GP) is an intelligence technique whereby computer programs are encoded as a set of genes which are evolved utilizing a Genetic Algorithm (GA). In other words, the GP employs novel optimization techniques to modify computer programs; imitating the way humans develop programs by progressively re-writing them for solving problems automatically. Trial programs are frequently altered in the search for obtaining superior solutions due to the base is GA. These are evolutionary search techniques inspired by biological evolution such as mutation, reproduction, natural selection, recombination, and survival of the fittest. The power of GAs is being represented by an advancing range of applications; vector processing, quantum computing, VLSI circuit layout, and so on. But one of the most significant uses of GAs is the automatic generation of programs. Technically, the GP solves problems automatically without having to tell the computer specifically how to process it. To meet this requirement, the GP utilizes GAs to a "population" of trial programs, traditionally encoded in memory as tree-structures. Trial programs are estimated using a "fitness function" and the suited solutions picked for re-evaluation and modification such that this sequence is replicated until a "correct" program is generated. GP has represented its power by modifying a simple program for categorizing news stories, executing optical character recognition, medical signal filters, and for target identification, etc. This paper reviews existing literature regarding the GPs and their applications in different scientific fields and aims to provide an easy understanding of various types of GPs for beginners.

• Journal of Plant Biotechnology
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• v.45 no.4
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• pp.364-368
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• 2018

The R2R3-type protein IbMYB1 transcription factor is a key regulator for anthocyanin biosynthesis in the storage roots of sweet potatoes. It was previously demonstrated that the IbMYB1 expression stimulates anthocyanin pigmentation in tobacco leaves, arabidopsis and storage roots of sweet potatoes. In this study, we generated the transgenic potato plants that express the IbMYB1 genes, which accumulated high levels of anthocyanins under the control of either the tuber-specific patatin (PAT) promoter or oxidative stress-inducible peroxidase anionic 2 (SWPA2) promoter. The PAT-MYB1 transgenic lines exhibited higher anthocyanin levels in the tuber than the empty vector control (EV) or SWPA2-MYB1 plants. When combined, our results indicated that overexpression of the IbMYB1 is a highly promising strategy for the generation of transgenic plants with enhanced tissue specific anthocyanin production.

• The Korean Journal of Applied Statistics
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• v.34 no.2
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• pp.153-166
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• 2021

A main goal of pharmacogenomics studies is to predict individual's drug responsiveness based on high dimensional genetic variables. Due to a large number of variables, feature selection is required in order to reduce the number of variables. The selected features are used to construct a predictive model using machine learning algorithms. In the present study, we applied several hybrid feature selection methods such as combinations of logistic regression, ReliefF, TurF, random forest, and LASSO to a next generation sequencing data set of 400 epilepsy patients. We then applied the selected features to machine learning methods including random forest, gradient boosting, and support vector machine as well as a stacking ensemble method. Our results showed that the stacking model with a hybrid feature selection of random forest and ReliefF performs better than with other combinations of approaches. Based on a 5-fold cross validation partition, the mean test accuracy value of the best model was 0.727 and the mean test AUC value of the best model was 0.761. It also appeared that the stacking models outperform than single machine learning predictive models when using the same selected features.

• Journal of IKEEE
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• v.24 no.4
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• pp.954-960
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• 2020

This paper proposes a speed variable proportional resonant current control method for a single-phase permanent magnet synchronous motor(PMSM). Due to the electromagnetic characteristics of a single-phase PMSM, negative and zero torques are generated in the part corresponding to the phase difference between the stator current and the back electromotive force. In addition, overcurrent limitation is required because of the low stator resistance and inductance in sensorless operation. When using the vector control for current control of single-phase PMSM under these conditions, processes of coordinate transformation, inverse coordinate transformation, and generation of virtual dq-axis components are required. However, the proposed variable speed proportional resonant current control method does not need the coordinate transformation used for AC motors. In this paper, we have confirmed stable maneuverability by using variable proportional resonant current control algorithm, and proposed sensorless control based on a mathematical model of a single-phase PMSM without a position sensor when reaching a constant speed. The usefulness of the current control method was verified through several experiments.