• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권2호
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• pp.438-455
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• 2024

Recently, many unsupervised learning-based models have emerged for Just Noticeable Difference (JND) estimation, demonstrating remarkable improvements in accuracy. However, these models suffer from a significant drawback is that their heavy reliance on handcrafted priors for guidance. This restricts the information for estimating JND simply extracted from regions that are highly related to handcrafted priors, while information from the rest of the regions is disregarded, thus limiting the accuracy of JND estimation. To address such issue, on the one hand, we extract the information for estimating JND in an Adversarial Complementary Learning (ACoL) way and propose an ACoL-JND network to estimate the JND by comprehensively considering the handcrafted priors-related regions and non-related regions. On the other hand, to make the handcrafted priors richer, we take two additional priors that are highly related to JND modeling into account, i.e., Patterned Masking (PM) and Contrast Masking (CM). Experimental results demonstrate that our proposed model outperforms the existing JND models and achieves state-of-the-art performance in both subjective viewing tests and objective metrics assessments.

• 한국정보통신학회논문지
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• 제12권6호
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• pp.1101-1106
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• 2008

청각장애인들은 건청인에 비해 의사소통의 기회가 적어 원만한 상호관계를 유지하는데 어려움이 있다. 이러한 문제는 청각장애인들이 구화를 대신해 몸짓이나 손짓을 이용하여 의사를 전달하는 수화를 건청 인들이 대부분 습득하고 있지 않아 청각장애 인들과 의사소통이 거의 불가능 한 것에서 초래된다. 따라서 본 논문에서는 건청인과 청각장애인들 간의 의사소통을 가능하게 하기 위한 전단계로 FCM 알고리즘을 이용한 지화 인식 방법을 제안한다. 제안된 방법 은 화상 카메라를 통해 얻어진 영상에서 YCbCr 컬러 공간과 HSI 컬러 공간을 이용하여 피부영역을 검출한 후, 추출된 피부영역에 4방향 윤곽선 추적 알고리즘을 적용하여 두 손의 위치를 추적한다. 그리고 추적한 두손의 영역에 대해 형태학적 정보를 이용하여 잡음을 제거한 후, 최종적으로 두 손의 영역을 추출한다. 추출된 손의 영역은 FCM 알고리즘을 적용하여 지화의 특징들을 분류하고 인식한다. 제안된 방법의 성능을 평가하기 위해 화상 카메라에서 획득한 지화 영상을 대상으로 실험한 결과, 두 손 영역의 추출과 지화 인식에 있어서 효과적인 것을 확인하였다.

• Journal of Ginseng Research
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• 제18권1호
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• pp.1-9
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• 1994

Sprague-Dawley rats were given freely with 15% ethanol (control) and 15% ethanol containing (1) 0.1% ginseng saponin, (2) 0.02% ginsenoside $Rb_1$, and (3) $Rg_1$ (tests) instead of water for 7 days and aldehyde dehydrogenase (ALDH) and monoamine oxidase (MAO) activity in different regions of brain were examined. In control group, total ALDH activity with indoleacetaldehyde and acetaldehyde as substrate in all different regions was lower than that of normal group except in the hippocampus. The inhibitory effect on the activity was prominent in the corpus striatum and was not in the hippocampus. However, low-$K_m$ ALDH activity in all different regions was much lower than that of normal group. A considerable decrease in mitochondria ALDH activity in cerebellum and striatum was also observed in control group. In test groups total, low-$K_m$, and mitochondria AkDH activities in all different regions were higher than those in control group. Although ALDH activity in the striatum of test group was higher than control group, it was relatively depressed as compared with normal. There was not found a remarkable difference in extent of stimulating effect on the AkDH activity according to the ginseng saponin components. When biogenic aldehydes were used as substrate, ALDH activity with 3,4-dihydroxy-phenylacetaldehyde (DOPAL) in all brain regions of control group was lower than that using 5-hydroxy-indoleacetaldehyde (HIAL) and 3,4-dihydroxyphenylglycolaldehyde (NORAL) as substrate. In control group, ALDH activity with biogenic aldehydes above mentioned was markedly inhibited in the striatum contrary to other regions. The higher ALDH activity with biogenic aldehydes in test group than in control was found in the striatum, cerebrum, and cerebellum. MAO activity in the cerebellum was inhibited in control group and slightly increased in test group. The results of present study suggest that the corpus striatum is significantly affected by ethanol exposure while the hippocampus is not and that ginseng saponin fraction and ginsenosid es might have a preventive effect against depression of brain ALDH activity by chronic administration of ethanol.

• 통합자연과학논문집
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• 제11권3호
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• pp.139-147
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• 2018

Hippocampal atrophy is a well-established imaging biomarker of Alzheimer disease (AD). However, hippocampus is a non-homogenous structure with cytoarchitecturally and functionally distinct sub-regions or subfield, with each region performing distinct functions. Certain regions of the subfield have shown selective vulnerability to AD. Here, we are interested in studying the effects of normal aging and mild cognitive impairment on these sub-regional volumes. With a reliable automated segmentation technique, we segmented these subregions of the hippocampus in 101 cognitively normal (CN), 135 early mild cognitive impairment (EMCI), 67 late mild cognitive impairment (LMCI) and 48 AD subjects. Thereby, dividing the hippocampus into hippocampal tail (tail), subiculum (SUB), cornu ammonis 1 (CA1), hippocampal fissure (fissure), presubiculum (PSUB), parasubiculum (ParaSUB), molecular layer (ML), granule cells/molecular layer/dentate gyrus (GCMLDG), cornu ammonis 3(CA3), cornu ammonis 4(CA4), fimbria and hippocampal-amygdala transition area (HATA). In this cross sectional study of 351 ADNI subjects, no differences in terms of age, gender, and years of education were observed among the groups. Though, the groups had statistically significant differences (p < 0.05 after the multiple comparison correction) in the Mini-Mental State Examination (MMSE) scores. There was asymmetrical volume loss in the early stages of AD with the left hemisphere showing volume loss in regions that were unaffected in the right hemisphere. Bilateral parasubiculum, right cornu ammonis 1, 3 and 4, right fimbria and right HATA regions did not show any volume loss till the late MCI stages. Our findings suggest that the hippocampal subfield regions are selectively vulnerable to AD and also that these vulnerabilities are asymmetrical especially during the early stages of AD.

• Journal of Acupuncture Research
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• 제17권4호
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• pp.130-138
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• 2000

Objectives : When sweating factor is excluded, to know the influence of acupuncture stimulation on electrical resistance. Methods : Regional anaesthesia(Lidocane 2%, 1ml, Subcutaneous injection) is applied to measured regions, 4cm round area including left Neiguan P6. So we can make adiaphoresis. Before and after acupucnture stimulation to Laogong P8, we measured the electrical resistance of anesthetized left Neiguan P6, anesthetized non-acupoint, normal left Ximen P4, and normal right Neiguan P6. For measurment, we use the 1.2V, DC system that has 100$k{\Omega}$ internal resistance Results : Under the adiaphoresis, Acupuncture stimulation makes the significant decrease of electrical resistance. In normal regions, so does it. Conclusions : When the acupuncture stimulation is applied to human boby, the decrease of electrical resistance is due not only to sweat secretion but also to other internal resistance.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1990년도 추계학술대회
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• pp.25-28
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• 1990

We tested the ability of two-dimensional echocardiograms of complete heart cycle in closed-chest human to discriminate between normal and infarcted myocardium using fixed window, Inter- and Intra-frame analysis. The results show that statistical parameter, MEAN, second order gray level statistics parameter, ASM and proposed parameter, HGE, I.T, can quantitatively distinguish between normal and Infarcted regions. The manner in which these parameters vary over the cardiac cycle is also a good indicator of the state of myocardium. The infarcted areas yield regions of higher Intensity throughout the cardiac cycle. Whereas, normal tissue demonstrates greater variability throughout the cardiac cycle.

• Communications for Statistical Applications and Methods
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• 제24권6호
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• pp.641-649
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• 2017

Multivariate confidence regions were defined using a chi-square distribution function under a normal assumption and were represented with ellipse and ellipsoid types of bivariate and trivariate normal distribution functions. In this work, an alternative confidence region using the multivariate quantile vectors is proposed to define the normal distribution as well as any other distributions. These lower and upper bounds could be obtained using quantile vectors, and then the appropriate region between two bounds is referred to as the quantile confidence region. It notes that the upper and lower bounds of the bivariate and trivariate quantile confidence regions are represented as a curve and surface shapes, respectively. The quantile confidence region is obtained for various types of distribution functions that are both symmetric and asymmetric distribution functions. Then, its coverage rate is also calculated and compared. Therefore, we conclude that the quantile confidence region will be useful for the analysis of multivariate data, since it is found to have better coverage rates, even for asymmetric distributions.

• 한국CDE학회논문집
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• 제2권2호
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• pp.77-84
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• 1997

This paper is concerning the development of multiple neural networks system of problem domains where the complete input space can be decomposed into several different regions, and these are known prior to training neural networks. We will adopt oblique decision tree to represent the divided input space and sel ect an appropriate subnetworks, each of which is trained over a different region of input space. The overall architecture of multiple neural networks system, called the federated architecture, consists of a facilitator, normal subnetworks, and tile networks. The role of a facilitator is to choose the subnetwork that is suitable for the given input data using information obtained from decision tree. However, if input data is close enough to the boundaries of regions, there is a large possibility of selecting the invalid subnetwork due to the incorrect prediction of decision tree. When such a situation is encountered, the facilitator selects a tile network that is trained closely to the boundaries of partitioned input space, instead of a normal subnetwork. In this way, it is possible to reduce the large error of neural networks at zones close to borders of regions. The validation of our approach is examined and verified by applying the federated neural networks system to the configuration design of a midship structure.

• 대한핵의학회지
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• 제26권2호
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• pp.251-256
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• 1992

Regional cerebral blood flow were measured in 10 patients with Parkinson's disease and 12 normal persons using $^{99m}Tc-HMPAO$ SPECT. Reconstructed images were interpreted qualitatively and were compared with those findings of CT. For the quantitative analysis, six pairs of region of interest matched with the perfusion territories of large cerebral arteries and cerebellar hemisphere were determined. From the count values, indices showing the degree of asymmetry between right and left cerebral or cerebellar hemisphere, cerebral asymmetry index (ASI) and percent index of cerebellar asymmetry (PIA), and an index showing change of each region, region to cerebellum ratio (RCR) were obtained. ASI of normal persons and patients were $0.082{\pm}0.033$ and $0.108{\pm}0.062$, respectively and PIA were $-0.4{\pm}0.7%$ and $-0.7{\pm}1.0%$, respectively, which showed no statistically significant difference between normal persons and patients. Among 10 RCR's, those of both regions of basal ganglia and both regions of anterior cerebral artery were significantly reduced. We concluded that the most significant reduction of regional cerebral blood flow in patients with Parkinson's disease was observed in the regions of basal ganglia and in the regions of anterior cerebral artery, and the degree of change in hemispheric blood flow was similar in both hemisphere.

• Journal of Animal Science and Technology
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• 제63권1호
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• pp.77-90
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• 2021

This study aimed to assess the impact of abnormal climate events on the production of Italian ryegrass (IRG), such as autumn low-temperature, severe winter cold and spring droughts in the central inland, southern inland and southern coastal regions. Seasonal climatic variables, including temperature, precipitation, wind speed, relative humidity, and sunshine duration, were used to set the abnormal climate events using principal component analysis, and the abnormal climate events were distinguished from normal using Euclidean-distance cluster analysis. Furthermore, to estimate the impact caused by abnormal climate events, the dry matter yield (DMY) of IRG between abnormal and normal climate events was compared using a t-test with 5% significance level. As a result, the impact to the DMY of IRG by abnormal climate events in the central inland of Korea was significantly large in order of severe winter cold, spring drought, and autumn low-temperature. In the southern inland regions, severe winter cold was also the most serious abnormal event. These results indicate that the severe cold is critical to IRG in inland regions. Meanwhile, in the southern coastal regions, where severe cold weather is rare, the spring drought was the most serious abnormal climate event. In particular, since 2005, the frequency of spring droughts has tended to increase. In consideration of the trend and frequency of spring drought events, it is likely that drought becomes a NEW NORMAL during spring in Korea. This study was carried out to assess the impact of seasonal abnormal climate events on the DMY of IRG, and it can be helpful to make a guideline for its vulnerability.