• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.35.4-35.4
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• 2019

We have conducted a 22 GHz very long baseline interferometry (VLBI) survey of 281 local (z < 0.05) active galactic nuclei (AGNs) selected from the Swift Burst Alert Telescope (BAT) 70-month ultra hard X-ray (14-195 keV) catalog. The main goal is to investigate the relation between the strengths of black hole accretion and the parsec-scale nuclear jet, which is expected to tightly correlate but has not been observationally confirmed yet. The BAT AGN Spectroscopic Survey (BASS) provides the least biased AGN sample against obscuration including both Seyfert types, hence it makes an ideal parent sample for studying the nuclear jet properties of an overall AGN population. Using the Korean VLBI Network (KVN), the KVN and VERA Array (KaVA), and the Very Long Baseline Array (VLBA), we observed 281 objects with a 22 GHz flux > 30 mJy, detecting 11 targets (~4% of VLBI detection rate). This implies that the fraction of X-ray AGNs which are currently ejecting a strong nuclear jet is very small. Although our 11 sources span a wide range of pc-scale morphological types, from compact to complex, they lie on a tight linear relation between accretion luminosity and nuclear jet luminosity. Our finding may indicate that the power of nuclear jet is directly responsible for the amount of black hole accretion. We also have probed the fundamental plane of black hole activity in VLBI scale (e.g., few milli-arcsecond). The results from our high-frequency VLBI radio study support that the change of jet luminosity and size follows what is predicted by the AGN evolution scenario based on the Eddington ratio (ƛ$_{Edd}$) - column density ($N_H$) plane, proposed by a previous study.

• Science of Emotion and Sensibility
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• v.15 no.2
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• pp.259-268
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• 2012

In a P300-based concealed information test (P300 CIT), the result of the test is greatly affected by the value of the probe stimulus. With a probe stimulus of low value, the detection rate decreases. The aim of this study was to determine whether the pupil-based concealed information test (Pupil CIT) could be used in addition to the P300 CIT for the probes of low value. Participants were told to choose one card from a deck of five cards (space 2, 3, 4, 5, 6), Then a P300 CIT and a Pupil CIT for the selected card were administered. P300s were measured at 3 scalp sites (Fz, Cz, and Pz), and the pupil sizes of left and right eyes were recorded. The P300 amplitude measured at Fz, Cz, and Pz was significantly different between the probe and irrelevant stimuli. And, in the Pupil CIT, the pupil size was also different between the two stimuli for both eyes. The detection rates of the P300 CIT were 44% at Fz and Cz sites and 36% at Pz site. And the detection rates of the Pupil CIT were 52% for the left eye and 60% for the right eye. There is a trend that the detection rate of the Pupil CIT was higher than that of the P300 CIT, but the difference didn't reach significance partly because of the relatively small sample size. The correlation between the decision based on the P300 CIT and that based on the Pupil CIT was not significant. As a conclusion, it is recommended to use a Pupil CIT instead of a P300 CIT when the value of the probe is low. And a combination of the measures may be superior to either one of them in detection rate.

• Science of Emotion and Sensibility
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• v.13 no.3
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• pp.541-550
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• 2010

The present study examined whether the physical similarity of test stimuli affects P300 amplitude and detection accuracy for the P300-based concealed information test (P300 CIT). As the participant pretended suffering from memory impairment by an accident, own name was used as a concealed information to be probed by the P300 CIT in which the participant discriminated between a target and other (probe, irrelevant) stimuli. One group of participants was tested in the easy task condition with low physical similarity among stimuli, the other group was tested in the difficult task condition with high physical similarity among stimuli. Using the base-to-peak P300 amplitude, the interaction effect of task difficulty and stimulus type was significant at $\alpha$=.1 level (p=.052). In the easy task condition the difference of P300 amplitude between the probe and the irrelevant stimuli was significant, while in the difficult task condition the difference was not significant. Using peak-to-peak P300 amplitude, on the other hand, the interaction effect of task difficulty and stimulus type was not significant with significant differences of P300 amplitude between the probe and the irrelevant stimuli in both task difficulty conditions. The difference of detection accuracy between task conditions was not significant with both measures of P300 amplitude although the difference was much smaller when peak-to-peak P300 amplitude was used. The results suggest that the efficiency of P300 CIT would not decrease even when the perceptual similarity among test stimuli is high.

• Science of Emotion and Sensibility
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• v.21 no.2
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• pp.113-124
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• 2018

The logical assumption of the comparison question test (CQT) is that the guilty person pays more attention to the relevant questions than to the comparison questions, and that the innocent person pays more attention to the comparison questions than to the relevant questions. The purpose of this study was to verify the logic of the comparison question test using functional magnetic resonance imaging (fMRI). The participants were tested for brain responses during a mock crime and performed the CQT under guilty and innocent conditions. After brain imaging, we evaluated the psychological burden of responding to the relevant questions and comparison questions. In the guilty conditions, the degree of burden was higher for the relevant questions than the comparison questions, and there was no significant difference in the innocent conditions. The fMRI results showed that, in the guilty conditions, greater activation was observed in the right superior temporal gyrus and right inferior frontal gyrus when relevant questions were presented relative to comparison questions. Based on these findings, the logical assumption of the CQT was discussed.

• BMB Reports
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• v.36 no.2
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• pp.179-184
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• 2003

Duchenne muscular dystrophy (DMD) is the most common hereditary neuromuscular disease. It is inherited manifestations. In some rare cases, the disease can also be manifested in females. The aim of the present study was to determine the molecular alteration in two cases of nonrelated DMD symptomatic carriers with no previous history of DMD. Multiplex PCR is commonly used to search for deletion in the DMD gene of affected males. This method could not be used in females because the normal X chromosome masks the deletion of the mutated one. Therefor, we used a set of seven highly polymorphic dinucleotide $(CA)_n$ repeat markers that lie within the human dystrophin gene. The deletions were evidenced by hemizygosity of the loci under study. We localized a deletion in the locus 7A (intron 7) on the maternal X chromosome in one case, and a deletion in the region of introns 49 and 50 on the paternal X chromosome in the other. The use of microsatellite genotyping within the DMD gene enables the detection of the mutant allele in female carriers. It is also a useful method to provide DMD families with more accurate genetic counseling.

• Development and Reproduction
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• v.13 no.4
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• pp.291-296
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• 2009

In most larvae of ascidian, two sensory pigment cells, otolith and ocellus, lie in their brain vesicle. They also have a third type of sensory cells: hydrostatic pressure receptor (Hpr) cells. The Hpr cells were presumed to be hydrostatic pressure-detection cells, but their precise functions is still disputed. In this study, we investigated whether an FGF signaling is involved in formation of Hpr cells. When fertilized eggs were injected with Hr-FGF9/16/20 antisense MO, the resulting larvae showed severe abnormalities with no expression of the Hpr cell-specific Hpr-1 antigen. Similar results were obtained using an FGF receptor inhibitor, SU5402, and an MEK inhibitor, U0126. Embryos treated with SU5402 or U0126 during the 32-cell and hatching stages did not express the Hpr-1 antigen. To elucidate the temporal requirement for the FGF signaling in formation of Hpr cells, embryos were treated with SU5402 for 2 h, or U0126 for 20 min during various embryonic stages. Larvae treated with SU5402 from the 16-cell stage to the 64-cell stage did not express the Hpr-1 antigen, whereas those treated at the early gastrula stage expressed the Hpr-1 antigen. When U0126 treatment was carried out at various stages between the 8-cell and late gastrula stages, larvae scarcely formed the Hpr cells. They showed expression of the Hpr-1 antigen when embryos were placed in U0126 just before the neural plate stage. These results suggest that FGF9/16/20 signaling is involved in formation of Hpr cells from the primary neural induction stage to the late gastrula stage.

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.25-33
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• 2006

We propose a method that automatically classifies the images into the object and non-object images. An object image is the image with object(s). An object in an image is defined as a set of regions that lie around center of the image and have significant color distribution against the other surround (or background) regions. We define four measures based on the characteristics of an object to classify the images. The center significance is calculated from the difference in color distribution between the center area and its surrounding region. Second measure is the variance of significantly correlated colors in the image plane. Significantly correlated colors are first defined as the colors of two adjacent pixels that appear more frequently around center of an image rather than at the background of the image. Third one is edge strength at the boundary of candidate for the object. By the way, it is computationally expensive to extract third value because central objects are extracted. So, we define fourth measure which is similar with third measure in characteristic. Fourth one can be calculated more fast but show less accuracy than third one. To classify the images we combine each measure by training the neural network and SYM. We compare classification accuracies of these two classifiers.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.