Sang-Geol Lee

Differential effects of morphine- and cocaine-induced nNOS immunoreactivity in the dentate gyrus of hippocampus of mice lacking μ-opioid receptors

This study investigated the expression of nNOS after repeated morphine or cocaine administration in order to determine if nNOS (neuronal nitric oxide synthase) is involved in the morphine- or cocaine-induced behavioral sensitization in mu-opioid receptor knockout (MOR(-/-)) mice. Higher numbers of nNOS-positive cells were observed in the dentate gyrus of the hippocampus (DG) of the wild-type (MOR(+/+)) mice repeatedly treated with either morphine or cocaine than in the saline treated MOR(+/+) mice (morphine, +122%; cocaine, +82%). Moreover, the MOR(-/-) mice also showed significantly higher morphine- or cocaine-induced nNOS expression levels in the DG than in the saline treated MOR(+/+) mice (morphine, +234%; cocaine, +54%). The MOR(-/-) mice showed a significantly higher morphine-induced nNOS expression level (+103%) or a lower cocaine-induced nNOS expression level (+38%) in the DG than in the morphine- or cocaine-treated MOR(+/+) mice. These results suggest that morphine and cocaine sensitization is differentially regulated by the mu-opioid receptors in MOR(-/-) mice via the nNOS systems in the DG.

Style classification and visualization of art painting's genre using self-organizing maps

With the spread of digitalization of art paintings, research on diverse scientific approaches on painted images has become active. In this paper, the method of classifying painting styles by extracting various features from paintings is suggested. Global features are extracted using the color-based statistical computation and composition-based local features of paintings are extracted through the segmentation of objects within the paintings to classify the styles of the paintings. Based on the extracted features, paintings are categorized by style using SOM, which are then analyzed through visualization using the map. We have proved the feasibility of the proposed method of categorizing paintings by style, and the objective features of paintings can contribute to the research on art history and aesthetics.

Motion quaternion-based motion estimation method of MYO using K-means algorithm and Bayesian probability

AbstractThere are diverse types of devices based on natural user interface/experience for humanized computing. One such device, the MYO allows the measurement of arm motions and uses them as an interface based on gestures. There are several research works for measuring the arm motions using MYOs. For example, one of the studies defines two types of motions for a forearm and for an upper arm, respectively. The orientations of the two types are measured by two MYOs. Bayesian probabilities are calculated based on the measured orientations and are utilized to estimate the orientations of the upper arm that is not being measured. However, because the orientation of the MYO can be expressed by one quaternion, the Bayesian probability by quaternions is more accurate than the Bayesian probability by each element of quaternions. This paper proposes a motion estimation method to increase the accuracy of motion estimation. The orientations obtained from MYO are expressed by one quaternion and are clustered by K-means. In the experiments, the performance of the proposed method was validated by analyzing the difference between estimated motion quaternions and measured motion quaternions, which showed enhanced performance.