• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.876-881
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• 2003

This study focused on to design and toanalysis of a myoelectronic hand. We considered a low frequency factor in human life and to quantify low frequency which a human body responded to using a 1-axis ant a 3-axis accelerometer. The dynamic myoelectronic hand are important for tasks such a continuous prosthetic control and a EMG signal recognition, which have not been successfully mastered by the most neural approached To control myoelectronic hand, classifying myoelectronic patterns are also important. Experimental results of FEM are 110㎫ on Thumb, 200㎫ on Index finger, 220㎫ on Middle finger 260㎫ on Ring finger and 270㎫ on Little finger. Experimental results of accelerometer are 1.4-0.4(m/s2) ,(5-20(〔Hz〕) in Feeding activity and 0.4-0(m/s2) (0-10〔Hz〕) in Lifting activity. Considering these facts, we suggest a new type myoelectronic hand.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.87-93
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• 2019

In this paper, we propose a real-time drone-based violent protest detection system. Our proposed system uses drones to detect scenes of violent protest in real-time. The important problem is that the victims and violent actions have to be manually searched in videos when the evidence has been collected. Firstly, we focused to solve the limitations of existing collecting evidence devices by using drone to collect evidence live and upload in AWS(Amazon Web Service)[1]. Secondly, we built a Deep Learning based violence detection model from the videos using Yolov3 Feature Pyramid Network for human activity recognition, in order to detect three types of violent action. The built model classifies people with possession of gun, swinging pipe, and violent activity with the accuracy of 92, 91 and 80.5% respectively. This system is expected to significantly save time and human resource of the existing collecting evidence.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.832-837
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• 2007

Many researchers are studying brain activity to using functional Magnetic Resonance Imaging (fMRI), Time Resolved Spectroscopy(TRS), Electroencephalography(EEG), and etc. They are used detection of seizures or epilepsy and deception detection in the main. In this paper, we focus on emotion recognition by recording brain waves. We specially use fMRI, TRS, and EEG for measuring brain activity Researchers are experimenting brain waves to get only a measuring apparatus or to use both fMRI and EEG. This paper is measured that we take images of fMRI and TRS about brain activity as human emotions and then we take data of EEG signals. Especially, we focus on EEG signals analysis. We analyze not only original features in brain waves but also transferred features to classify into five sections as frequency. And we eliminate low frequency from 0.2 to 4Hz for EEG artifacts elimination.

• Journal of the Korea Convergence Society
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• v.11 no.5
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• pp.9-17
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• 2020

Human activity recognition(HAR) using smartphones is a hot research topic in computational intelligence. Smartphones are equipped with a variety of sensors. Fusing the data of these sensors could enable applications to recognize a large number of activities. However, these devices have fewer resources because of the limited number of sensors available, and feature selection and classification methods are required to achieve optimal performance and efficient feature extraction. This paper proposes a smartphone-based HAR scheme according to these requirements. The proposed method in this paper extracts time-domain features from acceleration sensors, gyro sensors, and barometer sensors, and recognizes activities with high accuracy by applying KDA and SVM. This approach selects the most relevant feature of each sensor for each activity. Our comparison results shows that the proposed system outperforms previous smartphone-based HAR systems.

• Advances in robotics research
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• v.2 no.2
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• pp.129-140
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• 2018

With the increasing demand for the development of human pose estimation, such as human-computer interaction and human activity recognition, there have been numerous approaches to detect the 2D poses of people in images more efficiently. Despite many years of human pose estimation research, the estimation of human poses with images remains difficult to produce satisfactory results. In this study, we propose a robust 2D human body pose estimation method using an RGB camera sensor. Our pose estimation method is efficient and cost-effective since the use of RGB camera sensor is economically beneficial compared to more commonly used high-priced sensors. For the estimation of upper-body joint positions, semantic segmentation with a fully convolutional network was exploited. From acquired RGB images, joint heatmaps accurately estimate the coordinates of the location of each joint. The network architecture was designed to learn and detect the locations of joints via the sequential prediction processing method. Our proposed method was tested and validated for efficient estimation of the human upper-body pose. The obtained results reveal the potential of a simple RGB camera sensor for human pose estimation applications.

• Smart Media Journal
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• v.10 no.2
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• pp.55-60
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• 2021

In this research, we design and perform experiment to investigate whether neuronal activity patterns elicited while solving game tasks are spontaneously reactivated in during sleep. In order to recognize human activity EEG-fMRI signals are used at the same time. Experimental results shows that reward for the success of tasks performed before sleeping have an effect on sleep brain activity. The study uncovers a neural mechanism whereby rewarded life experiences are preferentially replayed and consolidated while we sleep.

• The Plant Pathology Journal
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• v.21 no.4
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• pp.301-309
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• 2005

Trichoderma species/isolates exhibited varied degree of agglutination on sclerotial (Sc) and hyphal (Hy) surface of Macrophomina phaseolina. The agglutination efficiencies on Sc and Hy ranged from $11\;to\;57\%$. Isolates of T. harzianum (Th) and T. viride (Tv) showed greater agglutination on Sc ($23-57\%$) and Hy ($16-47\%$). Different enzymes (trypsin, pepsin, proteinase k, a-chymotrypsin, lyticase and glucosidase) and inhibitors (tunicamycin, cycloheximide, brefeldin A, sodium azide, dithiothreitol and SDS) reduced the agglutination potential of conidia of Th-23/98 and Tv-25/98; however, the extent of response varied greatly in different treatments. Different fractions of Th-23/98 and Tv-25/98 exhibited haemagglutinating reaction with human blood group A, B, AB and O. Haemagglutinating activity was inhibited by different sugars and glycoproteins tested. Crude haemagglutinating protein from outer cell wall protein fraction of Th-23/98 and Tv-25/98 were eluted on Sephadex G-100 column. Initially Th-23/98 and Tv-25/98 exhibited two peaks showing no agglutination activity; however, lectin activity was detected in the third peak. Similar to crude lectin, the purified lectin also exhibited haemagglutinating activity with different erythrocyte source. SDS-PAGE analysis of partially purified lectin revealed single band with an estimated molecular mass of 55 and 52 kDa in Th-23/98 and Tv-25/98, respectively. Trypsin, chymotrypsin and b-1,3-glucanase totally inhibited lectin activity. Similarly, various pH also affected the haemagglutinating activity of Th-23/98 and Tv-25/98. From the present observations, it can be concluded that the recognition/attachment of mycoparasite (T. harzianum and T. viride) to the host surface (M. phaseolina) may be most likely due to lectin-carbohydrate interaction.

• BMB Reports
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• v.38 no.6
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• pp.690-694
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• 2005

Transcription termination of the human mitochondrial genome requires specific binding to termination factor mTERF. In this study, mTERF was produced in E. coli and purified by two-step chromatography. mTERF-binding DNA sequences were isolated from a pool of randomized sequences by the repeated selection of bound sequences by gel-mobility shift assay and polymerase chain reaction. Sequencing and comparison of the 23 isolated clones revealed a 16-bp consensus sequence of 5'-GTG$\b{TGGC}$AGANCCNGG-3' in the light-strand (underlined residues were absolutely conserved), which nicely matched the genomic 13-bp terminator sequence 5'-$\b{TGGC}$AGAGCCCGG-3'. Moreover, mTERF binding assays of heteroduplex and single-stranded DNAs showed mTERF recognized the light strand in preference to the heavy strand. The preferential binding of mTERF with the light-strand may explain its distinct orientation-dependent termination activity.

• Proceedings of the KSPS conference
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• 2007.05a
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• pp.39-40
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• 2007

For efficient interaction between human and robots, speech interface is a core problem especially in noisy and reverberant conditions. This paper analyzes main issues of spoken language interface for humanoid robots, such as sound source localization, voice activity detection, and speaker recognition.

• Archives of Pharmacal Research
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• v.28 no.12
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• pp.1317-1323
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• 2005

In an attempt to examine the ability of benzisothiazole-based drugs to interact with $\beta$-adrenoceptors, a series of 1,2-benzisothiazole derivatives, which were substituted with various propanolamine or oxypropanolamine side chains in the 2 or 3 position, were synthesised and tested. The pharmacological activity of these compounds at the ,$\beta$-adrenoceptors was examined using isolated rat atria and small intestinal segments, which preferentially express the $\beta_{1}$- and $\beta_{3}$-adrenoceptor-mediated responses, respectively. None of these products showed any $\beta$-adrenoceptor agonistic activity. In contrast, the 2- and 3-substituted isopropyl, tert-butyl, benzyl, and piperonyl derivatives 2a-d and 3a-d elicited surmountable inhibition of the isoprena­line-induced chronotropic effects in the atria, suggesting competitive antagonism at the $\beta_{1}$­recognition site. The $pA_{2}$ values revealed tert-butyl 3b and the isopropyl substituted piperonyl derivatives 3a to be the most effective. Remarkably, many of the 2-substituted propanolamines were less active than the corresponding 3-substituted oxypropanolamines. With the exception of compound 3b, none of these drugs antagonised the muscle relaxant activity of isoprenaline in the intestine, suggesting no effect on the $\beta_{3}$-adrenoceptors. These results confirm the ability of the benzisothiazole ring to interact with the $\beta$-adrenoceptors, and demonstrate that 2-substitution with propanolamine or 3-substitution with oxypropanolamine groups yields compounds with preferential antagonistic activity at the cardiac $\beta_{1}$adrenoceptors. The degree of antagonism depends strongly on both the nature of the substituent and its position on the benzisothiazole ring.