• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.29-37
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• 2019

Synthetic Aperture Radar (SAR) observations are powerful tools to monitor surface's displacement very accurately, induced by earthquake, volcano, ground subsidence, glacier movement, etc. Especially, radar interferometry (InSAR) which utilizes phase information related to distance from sensor to target, can generate displacement map in line-of-sight direction with accuracy of a few cm or mm. Due to decorrelation effect, however, degradation of coherence in the InSAR application often prohibit from construction of differential interferogram. Offset tracking method is an alternative approach to make a two-dimensional displacement map using intensity information instead of the phase. However, there is limitation in that the offset tracking requires very intensive computation power and time. In this paper, efficiency of parallel computing has been investigated using high performance computer for estimation of glacier velocity. Two TanDEM-X SAR observations which were acquired on September 15, 2013 and September 26, 2013 over the Narsap Sermia in Southwestern Greenland were collected. Atotal of 56 of 2.4 GHz Intel Xeon processors(28 physical processors with hyperthreading) by operating with linux environment were utilized. The Gamma software was used for application of offset tracking by adjustment of the number of processors for the OpenMP parallel computing. The processing times of the offset tracking at the 256 by 256 pixels of window patch size at single and 56 cores are; 26,344 sec and 2,055 sec, respectively. It is impressive that the processing time could be reduced significantly about thirteen times (12.81) at the 56 cores usage. However, the parallel computing using all the processors prevent other background operations or functions. Except the offset tracking processing, optimum number of processors need to be evaluated for computing efficiency.

• Journal of Korean Medicine for Obesity Research
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• v.18 no.2
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• pp.57-63
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• 2018

Objectives: Metabolic syndrome is defined by a cluster of major cardiovascular risk factors: obesity, insulin resistance, dyslipidemia, and arterial hypertension. Several members of a large family of nonselective cation entry channels, e.g., transient receptor potential vanilloid 4 (TRPV4) channels have been associated with the development of dyslipidemia and hypertension. The purpose of this study was to investigate the effects of Leejung-tang (Lizhong-tang), Rikkunshito, and Bojungikgi-tang (Buzhongyiqi-tang) on TRPV4 channel. Methods: Human embryonic kidney 293 cells stably transfected with the TRPV4 expression vectors were maintained in Dulbecco's modified Eagle's medium supplemented with 10% fetal bovine serum, 1% penicillin/streptomycin, $5{\mu}g/mL$ blasticidin, and 0.4 mg/mL zeocin in a humidified 20% $O_2/10%$ $CO_2$ atmosphere at $37^{\circ}C$. Whole-cell patch clamp recordings were obtained using an Axopatch 700B amplifier and pClamp v.10.4 software (Molecular Devices, San Jose, CA, USA), and signals were digitalized at 5 kHz using Digidata 1422A. Results: Leejung-tang and Rikkunshito (10, 30 and 50 mg/mL) had no effects on the TRPV4 whole-cell currents at dose dependent manner. However, Bojungikgi-tang (10, 30, and 50 mg/mL) inhibited the TRPV4 whole-cell currents in a dose dependent manner and the half maximal inhibitory concentration (IC50) of Bojungikgi-tang was 18.2 mg/mL. Conclusions: These results suggest that Bojungikgi-tang plays an important roles to inhibit the TRPV4 channel, suggesting that Bojungikgi-tang is considered one of the candidate agents for the treatment of metabolic syndrome such as dyslipidemia and hypertension.

• Progress in Medical Physics
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• v.8 no.1
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• pp.3-15
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• 1997

Adrenal chromaffin cells secrete catecholamine in response to acetylcholine. The secretory response has absolute requirement for extracellular calcium, indication that $Ca^{2+}$ influx through voltage dependent $Ca^{2+}$ channel (VDCC) is the primary trigger of the secretion cascade. Although the existence of various types of $Ca^{2+}$ channels has been explored using patch clamp technique in adrenal chromaffin cells, the contribution of different types of $Ca^{2+}$ channels to catecholamine secretion remains to be established. To investigate the quantative contribution of different types of $Ca^{2+}$ channels to cate-cholamine secretion, $Ca^{2+}$ current($I_{Ca}$) and the resultant membrane capacitance increment($\Delta{C}_{m}$) were simultaneoulsy measured. Software based phasor detector technique was used to monitor $\Delta{C}_{m}$. After blockade of L type VDCC with nicardipine (1$\mu$M), $I_{ca}$ was blocked to 43.85$\pm$6.72%(mean$\pm$SEM) of control and the resultant ㅿC$_{m}$ was reduced ot 30.10$\pm$16.44% of control. In the presence of nicardipine and $\omega$-conotoxin in GVIA(l$\mu$M), an N type VDCC antagonist, $I_{ca}$ was blocked to 11.62$\pm$2.96% of control and the resultant $\Delta{C}_{m}$ was reduced to 26.13$\pm$8.25% of control. Finally, in the presence of L, N, and P type $Ca^{2\pm}$ channel antagonists(nicardipine, $\omega$-Conotoxin GVIA, and $\omega$-agatoxin IVA, respectively), $I_{ca}$ and resultant $\Delta{C}_{m}$ were almost completely blocked. From the observation of parallel effects of $Ca^{2+}$ channel antagonists on $I_{ca}$ and $\Delta{C}_{m}$, it was concluded that L, N, and also P type $Ca^{2+}$ channels served and $Ca^{2+}$ source for exocytosis and no difference was observed in their efficiency to evoke exocytosis amost L, N, and P type $Ca^{2+}$ channels.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.4
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• pp.187-194
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• 2016

When performing experiments in indoor and outdoor environment, we need a system that monitors a volunteer to prevent dangerous situations and efficiently manages the data in real time. We developed a guidance device for visually impaired person that guides the user to walk safely to the destination in the previous study. We set a POI (Point of Interest) of a specific location indoors and outdoors and tracks the user's position and navigate the walking path using artificial markers and ZigBee modules as landmark. In addition, we develop path finding algorithm to be used for navigation in the guidance device. In the test bed, the volunteers are exposed to dangerous situations and can be an accident due to malfunction of the device since they are visually impaired person or normal person wearing a eye patch. Therefore the device requires a system that remotely monitors the volunteer wearing guidance device and manages indoor or outdoor a lot of map data. In this paper, we introduce a managing system that monitors the volunteers remotely and handles map data efficiently. We implement a management system which can monitor the volunteer in order to prevent a hazardous situation and effectively manage large amounts of data. In addition, we verified the effectiveness of the proposed system through various experiments.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.2
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• pp.43-50
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• 2018

Biometric information computing is greatly influencing both a computing system and Big-data system based on the bio-information system that combines bio-signal sensors and bio-information processing. Unlike conventional data formats such as text, images, and videos, biometric information is represented by text-based values that give meaning to a bio-signal, important event moments are stored in an image format, a complex data format such as a video format is constructed for data prediction and analysis through time series analysis. Such a complex data structure may be separately requested by text, image, video format depending on characteristics of data required by individual biometric information application services, or may request complex data formats simultaneously depending on the situation. Since previous bio-information processing computing systems depend on conventional computing component, computing structure, and data processing method, they have many inefficiencies in terms of data processing performance, transmission capability, storage efficiency, and system safety. In this study, we propose an improved biosensing converged big data computing architecture to build a platform that supports biometric information processing computing effectively. The proposed architecture effectively supports data storage and transmission efficiency, computing performance, and system stability. And, it can lay the foundation for system implementation and biometric information service optimization optimized for future biometric information computing.