• Journal of the Korean Vacuum Society
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• v.20 no.5
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• pp.361-366
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• 2011

An in-situ, real-time monitoring of GaN epilayers grown by low pressure metalorganic chemical vapor deposition system modified for spectral reflectance was performed. Reflectance spectrums from 190~861 nm were observed using p-polarized light with incident angle of $75^{\circ}$. All reflectance spectrums showed interference oscillation caused by multiple reflection within GaN epilayers, and the spectrum from GaN with low crystalline quality showed weak reflectance intensity and much low amplitude of the oscillation because many defects in GaN resulted in light scattering and absorption. Signal variation of reflected light which was selected around strong constructive wavelength range was also observed during $NH_3$ supplying and $NH_3$ cut-off. There was no significant change in signal intensity when $NH_3$ cut-off for 10 sec, but it showed higher intensity when $NH_3$ was cut off for over 30 sec and its intensity kept unchanged. This result indicates that GaN surface was N-terminated during $NH_3$ supplying but Ga-terminated during $NH_3$ cut-off because of high nitrogen equilibrium vapor pressure of GaN, and metallic Ga-terminated surface caused slightly higher reflectance intensity.

• Science of Emotion and Sensibility
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• v.14 no.4
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• pp.627-636
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• 2011

The purpose of this study is to develop the multi-modal interaction system. This system provides realistic and an immersive experience through multi-modal interaction. The system recognizes user behavior, intention, and attention, which overcomes the limitations of uni-modal interaction. The multi-modal interaction system is based upon gesture interaction methods, intuitive gesture interaction and attention evaluation technology. The gesture interaction methods were based on the sensors that were selected to analyze the accuracy of the 3-D gesture recognition technology using meta-analysis. The elements of intuitive gesture interaction were reflected through the results of experiments. The attention evaluation technology was developed by the physiological signal analysis. This system is divided into 3 modules; a motion cognitive system, an eye gaze detecting system, and a bio-reaction sensing system. The first module is the motion cognitive system which uses the accelerator sensor and flexible sensors to recognize hand and finger movements of the user. The second module is an eye gaze detecting system that detects pupil movements and reactions. The final module consists of a bio-reaction sensing system or attention evaluating system which tracks cardiovascular and skin temperature reactions. This study will be used for the development of realistic digital entertainment technology.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.341-343
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• 2006

The current spectral shape matching method (SSMM), developed by Ahn and Shanmugam (2004), relies on the assumption that the path radiance resulting from scattered photons due to air molecules and aerosols and possibly direct-reflected light from the air-sea interface is spatially homogeneous over the sub-scene of interest, enabling the retrieval of water-leaving radiances ($L_w$) from the satellite ocean color image data. This assumption remains valid for the clear atmospheric conditions, but when the distribution of aerosol loadings varies dramatically the above postulation of spatial homogeneity will be violated. In this study, we present the second version of SSMM which will take into account the horizontal variations of aerosol loading in the correction of atmospheric effects in SeaWiFS ocean color image data. The new version includes models for the correction of the effects of aerosols and Raleigh particles and a method fur computation of diffuse transmittance ($t_{os}$) as similar to SeaWiFS. We tested this method over the different optical environments and compared its effectiveness with the results of standard atmospheric correction (SAC) algorithm (Gordon and Wang, 1994) and those from in-situ observations. Findings revealed that the SAC algorithm appeared to distort the spectral shape of water-leaving radiance spectra in suspended sediments (SS) and algal bloom dominated-areas and frequently yielded underestimated or often negative values in the lower green and blue part of the electromagnetic spectrum. Retrieval of water-leaving radiances in coastal waters with very high sediments, for instance = > 8g $m^{-3}$, was not possible with the SAC algorithm. As the current SAC algorithm does not include models for the Asian aerosols, the water-leaving radiances over the aerosol-dominated areas could not be retrieved from the image and large errors often resulted from an inappropriate extrapolation of the estimated aerosol radiance from two IR bands to visible spectrum. In contrast to the above results, the new SSMM enabled accurate retrieval of water-leaving radiances in a various range of turbid waters with SS concentrations from 1 to 100 g $m^{-3}$ that closely matched with those from the in-situ observations. Regardless of the spectral band, the RMS error deviation was minimum of 0.003 and maximum of 0.46, in contrast with those of 0.26 and 0.81, respectively, for SAC algorithm. The new SSMM also remove all aerosol effects excluding areas for which the signal-to-noise ratio is much lower than the water signal.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.4
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• pp.22-30
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• 2001

In this paper we propose three classification algorithms to classify breast tumors that occur in duct into Benign, DCIS(ductal carcinoma in situ) NOS(invasive ductal carcinoma) The general approach for a creating classifier is composed of 2 steps: feature extraction and classification Above all feature extraction for a good classifier is very significance, because the classification performance depends on the extracted features, Therefore in the feature extraction step, we extracted morphology features describing the size of nuclei and texture features The internal structures of the tumor are reflected from wavelet transformed images with 10$\times$ and 40$\times$ magnification. Pariticulary to find the correlation between correct classification rates and wavelet depths we applied 1, 2, 3 and 4-level wavelet transforms to the images and extracted texture feature from the transformed images The morphology features used are area, perimeter, width of X axis width of Y axis and circularity The texture features used are entropy energy contrast and homogeneity. In the classification step, we created three classifiers from each of extracted features using discriminant analysis The first classifier was made by morphology features. The second and the third classifiers were made by texture features of wavelet transformed images with 10$\times$ and 40$\times$ magnification. Finally we analyzed and compared the correct classification rate of the three classifiers. In this study, we found that the best classifier was made by texture features of 3-level wavelet transformed images.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.4
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• pp.238-244
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• 2019

In this study, we compared and analyzed the performance of each Convolution Neural Network (CNN) by implementing the CNN that reflected the characteristics of the cerebral structure, in order to analyze the CNN that was used for the prediction of cybersickness, and provided the performance varying depending on characteristics of the brain. Dizziness has many causes, but the most severe symptoms are considered attributable to vestibular dysfunction associated with the brain. Brain waves serve as indicators showing the state of brain activities, and tend to exhibit differences depending on external stimulation and cerebral activities. Changes in brain waves being caused by external stimuli and cerebral activities have been proved by many studies and experiments, including the thesis of Martijn E. Wokke, Tony Ro, published in 2019. Based on such correlation, we analyzed brain wave data collected from dizziness-inducing environments and implemented the dizziness predictive artificial neural network reflecting characteristics of the cerebral structure. The results of this study are expected to provide a basis for achieving optimal performance of the CNN used in the prediction of dizziness, and for predicting and preventing the occurrence of dizziness under various virtual reality (VR) environments.

• Korean Journal of Optics and Photonics
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• v.24 no.4
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• pp.176-183
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• 2013

In this paper, we report the design, fabrication and characterization of the 3-Dimensional optical receiver for a Laser Detection And Ranging (LADAR) system. The optical receiver is composed of three parts; $16{\pm}16$ Geiger Mode InGaAs Avalanche Photodiode (APD) array device operated at 1560 nm wavelength, Read Out Integrated Circuit (ROIC) measuring the Time-Of-Flight (TOF) of the return signal reflected from target objects, a package and cooler maintaining the proper operational condition of the detector and control electronics. We can confirm that the LADAR system can detect the signal from a target up to 1.2 km away, and it showed low Dark Count Rate (DCR) of less than 140 kHz, and higher than 28%-Photon Detection Efficiency (PDE). This is considered to be the best performance of the $16{\pm}16$ FPA APD optical receiver for a LADAR system.

• Science of Emotion and Sensibility
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• v.15 no.1
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• pp.17-28
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• 2012

Recent development of 3D technologies made it possible that observers perceive 3D depth from two dimensional images. Despite this kind of technological development, when observers watch 3D display they experience 3D visual fatigue that they do not usually experience in real life. It is critical to measure visual fatigue in order to overcome the problem of 3D visual fatigue. The purpose of the present study was to develop a protocol to measure 3D visual fatigue based on an EEG signal and to examine its validity. The first experiment explored the possible ERP components that reflected visual fatigue in 2D and 3D conditions. The second experiment examined whether the feature of the component found in the first experiment was affected by the amount of binocular disparity. Both in Cz and Pz channels, the peak amplitude of P3 component was much lower in 3D rather than in 2D conditions, and it decreased as the amount of binocular disparity increased. The subjective 3D visual fatigue also increased with the amount of binocular disparity. These results imply that the peak amplitude of P3 component at Cz and Pz channels can be used as an index of 3D visual fatigue.

• Journal of the Korea Society for Simulation
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• v.27 no.4
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• pp.61-68
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• 2018

This paper deals with ground clutter model for FOD (foreign object debris) surveillance FMCW (frequency modulated continuous waveform) radar. In the FOD surveillance radar, it has received not only the signals reflected by FOD, but also the clutters of the surface of the runway and the grassland simultaneously. However, to detect the FOD, the clutter rejection algorithm is necessary because the RCS (radar cross section) of FOD is nearly same to RCS of the grassland. In addition, it is difficult to apply the MTI (moving target indicator) algorithm as the clutter rejection algorithm because both the FOD and the clutter coexist stationarily. Hence, to remove the stationary clutter, it is crucial to accurately generate clutter map considering the surface of road. In this paper, in order to generate the clutter map, the respective beat signal at every range bin is generated in the case of only the surface without FOD, and then the beat signal accumulated 100 times. And also, Weibull distribution is applied to the RCS value to take the scattering distribution of clutter into consideration. The simulation results show that FOD can be well detected by applying the generated clutter map to the FOD FMCW radar.

• Journal of IKEEE
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• v.26 no.3
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• pp.510-514
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• 2022

In this paper, we propose the development of high-sensitivity low-end radiation measuring sensor module. The proposed measurement sensor module is a scintillator + photomultiplier(SiPM) sensor optimization structure design, amplification and filter and control circuit design for sensor driver, control circuit design including short-distance communication, sensor mechanism design and manufacturing, and GUI development applied to prototypes consists of, etc. The scintillator + photomultiplier(SiPM) sensor optimization structure design is designed by checking the characteristics of the scintillator and the photomultiplier (SiPM) for the sensor structure design. Amplification, filter and control circuit design for sensor driver is designed to process fine scintillation signal generated by radiation with a scintillator using SiPM. Control circuit design including short-distance communication is designed to enable data transmission through MCU design to support short-range wireless communication function and wired communication support. The sensor mechanism design and manufacture is designed so that the glare generated by wrapping a reflective paper (mirroring) on the outside of the plastic scintillator is reflected to increase the efficiency in order to transmit the fine scintillation signal generated from the plastic scintillator to the photomultiplier(SiPM). The GUI development applied to the prototype expresses the date and time at the top according to each screen and allows the measurement unit and time, seconds, alarm level, communication status, battery capacity, etc. to be expressed. In order to evaluate the performance of the proposed system, the results of experiments conducted by an authorized testing institute showed that the radiation dose measurement range was 30 𝜇Sv/h ~ 10 mSv/h, so the results are the same as the highest level among products sold commercially at domestic and foreign. In addition, it was confirmed that the measurement uncertainty of ±7.4% was measured, and normal operation was performed under the international standard ±15%.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.200-208
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• 2022

In this study, an automatic information collection system and geographic information construction algorithm for the transportation disadvantaged using electric mobility aids are implemented using an object recognition model. Recognizes objects that the disabled person encounters while moving, and acquires coordinate information. It provides an improved route selection map compared to the existing geographic information for the disabled. Data collection consists of a total of four layers including the HW layer. It collects image information and location information, transmits them to the server, recognizes, and extracts data necessary for geographic information generation through the process of classification. A driving experiment is conducted in an actual barrier-free zone, and during this process, it is confirmed how efficiently the algorithm for collecting actual data and generating geographic information is generated.The geographic information processing performance was confirmed to be 70.92 EA/s in the first round, 70.69 EA/s in the second round, and 70.98 EA/s in the third round, with an average of 70.86 EA/s in three experiments, and it took about 4 seconds to be reflected in the actual geographic information. From the experimental results, it was confirmed that the walking weak using electric mobility aids can drive safely using new geographic information provided faster than now.