• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.2
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• pp.405-413
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• 2013

In this paper, a high-reliability differential paired 24-bit eFuse OTP memory with program-verify-read mode for PMICs is designed. In the proposed program-verify-read mode, the eFuse OTP memory can do a sensing margin test with a variable pull-up load in consideration of programmed eFuse resistance variation and can output a comparison result through a PFb (pass fail bar) pin by comparing a programmed datum with its read one. It is verified by simulation results that the sensing resistance is lower with $4k{\Omega}$ in case of the designed differential paired eFuse OTP memory than $50k{\Omega}$ in case of its dual-port eFuse OTP memory.

• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.359-375
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• 2017

We developed fog detection algorithm (KNU_FDA) based on the optical and textural properties of fog using satellite (COMS) and ground observation data. The optical properties are dual channel difference (DCD: BT3.7 - BT11) and albedo, and the textural properties are normalized local standard deviation of IR1 and visible channels. Temperature difference between air temperature and BT11 is applied to discriminate the fog from other clouds. Fog detection is performed according to the solar zenith angle of pixel because of the different availability of satellite data: day, night and dawn/dusk. Post-processing is also performed to increase the probability of detection (POD), in particular, at the edge of main fog area. The fog probability is calculated by the weighted sum of threshold tests. The initial threshold and weighting values are optimized using sensitivity tests for the varying threshold values using receiver operating characteristic analysis. The validation results with ground visibility data for the validation cases showed that the performance of KNU_FDA show relatively consistent detection skills but it clearly depends on the fog types and time of day. The average POD and FAR (False Alarm Ratio) for the training and validation cases are ranged from 0.76 to 0.90 and from 0.41 to 0.63, respectively. In general, the performance is relatively good for the fog without high cloud and strong fog but that is significantly decreased for the weak fog. In order to improve the detection skills and stability, optimization of threshold and weighting values are needed through the various training cases.

• Smart Structures and Systems
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• v.8 no.1
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• pp.17-37
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• 2011

The microcantilever (MCL) sensor is one of the most promising platforms for next-generation label-free biosensing applications. It outperforms conventional label-free detection methods in terms of portability and parallelization. In this paper, an overview of recent advances in our understanding of the coupling between biomolecular interactions and MCL responses is given. A dual compact optical MCL sensing platform was built to enable biosensing experiments both in gas-phase environments and in solutions. The thermal bimorph effect was found to be an effective nanomanipulator for the MCL platform calibration. The study of the alkanethiol self-assembly monolayer (SAM) chain length effect revealed that 1-octanethiol ($C_8H_{17}SH$) induced a larger deflection than that from 1-dodecanethiol ($C_{12}H_{25}SH$) in solutions. Using the clinically relevant biomarker C-reactive protein (CRP), we revealed that the analytical sensitivity of the MCL reached a diagnostic level of $1{\sim}500{\mu}g/ml$ within a 7% coefficient of variation. Using grazing incident x-ray diffractometer (GIXRD) analysis, we found that the gold surface was dominated by the (111) crystalline plane. Moreover, using X-ray photoelectron spectroscopy (XPS) analysis, we confirmed that the Au-S covalent bonds occurred in SAM adsorption whereas CRP molecular bindings occurred in protein analysis. First principles density functional theory (DFT) simulations were also used to examine biomolecular adsorption mechanisms. Multiscale modeling was then developed to connect the interactions at the molecular level with the MCL mechanical response. The alkanethiol SAM chain length effect in air was successfully predicted using the multiscale scheme.

• Proceedings of the KSRS Conference
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• v.1
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• pp.7-10
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• 2006

Four programs, i.e. TRMM, ADEOS2, ASTER, and ALOS are going on in Japanese Earth Observation programs. TRMM and ASTER are operating well, and TRMM operation will be continued to 2009. ADEOS2 was failed, but AMSR-E on Aqua is operating. ALOS (Advanced Land Observing Satellite) was successfully launched on $24^{th}$ Jan. 2006. ALOS carries three instruments, i.e., PRISM (Panchromatic Remote Sensing Instrument for Stereo Mapping), AVNIR-2 (Advanced Visible and Near Infrared Radiometer), and PALSAR (Phased Array L band Synthetic Aperture Radar). PRISM is a 3 line panchromatic push broom scanner with 2.5m IFOV. AVNIR-2 is a 4 channel multi spectral scanner with 10m IFOV. PALSAR is a full polarimetric active phased array SAR. PALSAR has many observation modes including full polarimetric mode and scan SAR mode. After the unfortunate accident of ADEOS2, JAXA still have plans of Earth observation programs. Next generation satellites will be launched in 2008-2012 timeframe. They are GOSAT (Greenhouse Gas Observation Satellite), GCOM-W and GCOM-C (ADEOS-2 follow on), and GPM (Global Precipitation Mission) core satellite. GOSAT will carry 2 instruments, i.e. a green house gas sensor and a cloud/aerosol imager. The main sensor is a Fourier transform spectrometer (FTS) and covers 0.76 to 15 ${\mu}m$ region with 0.2 to 0.5 $cm^{-1}$ resolution. GPM is a joint project with NASA and will carry two instruments. JAXA will develop DPR (Dual frequency Precipitation Radar) which is a follow on of PR on TRMM. Another project is EarthCare. It is a joint project with ESA and JAXA is going to provide CPR (Cloud Profiling Radar). Discussions on future Earth Observation programs have been started including discussions on ALOS F/O.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.374-377
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• 2007

Dual-channel Radiometers for Earth and Atmosphere Monitoring (DREAM) was developed as the Korean first spaceborne microwave radiometer for earth remote sensing. It is the main payload of the Science and Technology SATellite-2 (STSAT-2). STSAT-2 will be launched by Korea Space Launch Vehic1e-l (KSLV-1) at NARO Space Center in Korea in 2008. The DREAM is a two-channel, total power microwave radiometers with the center frequencies of 23.8 GHz and 37 GHz. The bandwidths of radiometer are 600 MHz at 23.8 GHz and 1000 MHz at 37 GHz. The integration time is 200 ms and the required sensitivity is less than 0.5 K. In this paper, we summarize the specification and performance of the developed DREAM firstly. And we describe system integration and performance test of DREAM mounted on spacecraft.

• Journal of Microbiology
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• v.44 no.3
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• pp.284-292
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• 2006

The cbb3 cytochrome c oxidase has the dual function as a terminal oxidase and oxygen sensor in the photosynthetic bacterium, Rhodobacter sphaeroides. The cbb3 oxidase forms a signal transduction pathway together with the PrrBA two-component system that controls photosynthesis gene expression in response to changes in oxygen tension in the environment. Under aerobic conditions the cbb3 oxidase generates an inhibitory signal, which shifts the equilibrium of PrrB kinase/phosphatase activities towards the phosphatase mode. Photosynthesis genes are thereby turned off under aerobic conditions. The catalytic subunit (CcoN) of the R. sphaeroides cbb3 oxidase contains five histidine residues (H2l4, B233, H303, H320, and H444) that are conserved in all CcoN subunits of the cbb3 oxidase, but not in the catalytic subunits of other members of copper-heme superfamily oxidases. H214A mutation of CcoN affected neither catalytic activity nor sensory (signaling) function of the cbb3 oxidase, whereas H320A mutation led to almost complete loss of both catalytic activity and sensory function of the cbb3 oxidase. H233V and H444A mutations brought about the partial loss of catalytic activity and sensory function of the cbb3 oxidase. Interestingly, the H303A mutant form of the cbb3 oxidase retains the catalytic function as a cytochrome c oxidase as compared to the wild-type oxidase, while it is defective in signaling function as an oxygen sensor. H303 appears to be implicated in either signal sensing or generation of the inhibitory signal to the PrrBA two-component system.

• Journal of Biomedical Engineering Research
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• v.35 no.5
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• pp.132-141
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• 2014

In an ordinary CT scan, a large number of projections with full field-of-view (FFOV) are necessary to reconstruct high resolution images. However, excessive x-ray dosage is a great concern in FFOV scan. Region-of-interest (ROI) CT or sparse-view CT is considered to be a solution to reduce x-ray dosage in CT scanning, but it suffers from bright-band artifacts or streak artifacts giving contrast anomaly in the reconstructed image. In this study, we propose an image reconstruction method to eliminate the bright-band artifacts and the streak artifacts simultaneously. In addition to the ROI scan for the interior projection data with relatively high sampling rate in the view direction, we get sparse-view exterior projection data with much lower sampling rate. Then, we reconstruct images by solving a constrained total variation (TV) minimization problem for the interior projection data, which is assisted by the exterior projection data in the compressed sensing (CS) framework. For the interior image reconstruction assisted by the exterior projection data, we implemented the proposed method which enforces dual data fidelity terms and a TV term. The proposed method has effectively suppressed the bright-band artifacts around the ROI boundary and the streak artifacts in the ROI image. We expect the proposed method can be used for low-dose CT scans based on limited x-ray exposure to a small ROI in the human body.

• Korean Journal of Remote Sensing
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• v.10 no.2
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• pp.83-107
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• 1994

Sea surface temperatures (SSTs) estimated by using the operational SST derivation equations of NOAA/NESDIS were compared with satellite-tracked drifter temperatures. As a result of eliminating cloud-filled or contaminated pixels through several cloud tests, 69 matchup points between the drifter temperatures and the SSTs estimated with NOAA satellite 9, 10. 11 and 12 data from August, 1993 to July, 1994 were collected. Multi-channel sea surface temperature(MCSST) using a split window technique showed an approximately $1.0{\circ}C$ rms error as compared with the drifting buoy temperatures for 69 coincidences. Accuracies for satellete-derived sea surface temperatures were evaluated for only NOAA-11 AVHRR data which had relatively large matchups of 35points as compared with other satellites. For the comparison of the oberved temperatures with the calculated SSTs, linear MCSST and nonlinear cross product sea surface temperature(CPSST) algorithms by the split, the dual and the triple window technique were used respectively. As a result, the split window CPSSTs showed the smallest rms error of $0.72{\circ}C$. Defferences between the split window SSTs and the drifter temperatures appeared th have a linear tendency against the drifter temperatures and also against the differences between AVHRR channel 4 and 5 brighness temperatures. This indicates some possibilities that satelite-derived SSTs operationally calculated from the NOAA/NESDIS equation in the seas around Korea have been underestimated as compared with actural SSTs in case sea water temperature is relatively low or the atmosphere over the sea surface is very dry like in winter, while overstimated in case of high temperature or very moist atmospheric equations based on local sea measurements around Korea instead of global measurements should be derived.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.737-746
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• 2022

Utilizing weather independent SAR images along with machine learning based object detector is effective in robust vessel monitoring. While conventional SAR images often applied amplitude data from Single Look Complex, exploitation of polarimetric parameters acquired from multiple polarimetric SAR images was yet to be implemented to vessel detection utilizing machine learning. Hence, this study used four polarimetric parameters (H, p₁, DoP, DPRVI) retrieved from eigen-decomposition and two backscattering coefficients (γ₀, _VV, γ₀, _VH) from radiometric calibration; six bands in total were respectively exploited from 52 Sentinel-1 SAR images, accompanied by vessel training data extracted from AIS information which corresponds to acquisition time span of the SAR image. Evaluating different cases of combination, the use of polarimetric indexes along with amplitude values derived enhanced vessel detection performances than that of utilizing amplitude values exclusively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.12
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• pp.3600-3607
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• 2009

This paper describes the development of a power sensor for wireless signal over the ultra wideband range of 300~3800MHz with the detecting range of 150mW~150W. The proposed power sensor fundamentally has the function of not only detecting wireless power, but recognizing frequency and measuring VSWR. The development of the power sensor is completed through the design of dual directional coupler, design of power detector block which produces DC data using the corresponding RF input power level, and establishment of collecting the exact calibration data. The dual directional coupler has the operating frequency of 300~3800MHz with the 0.085dB of insertion loss, and directivity of 30dB at least at 3800MHz. The developed power sensor has the capability of power sensing with less than 0.25dB of resolution as well as measuring VSWR of 1.17~1.96 under the practical operating situation of very high power up to 150W at 300~3800MHz.