• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.133-141
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• 2006

Recently many wearable computers have been developed. But they still have many user interface problems from both an input and output perspective. This paper presents a wearable user interface based on EOG(electrooculogram) sensing circuit and marker recognition. In the proposed user interface, the EOG sensor circuit which tracks the movement of eyes by sensing the potential difference across the eye is used as a pointing device. Objects to manipulate are represented human readable markers. And the marker recognition system detects and recognize markers from the camera input image. When a marker is recognized, the corresponding property window and method window are displayed to the head mounted display. Users manipulate the object by selecting a property or a method item from the window. By using the EOG sensor circuit and the marker recognition system, we can manipulate an object with only eye movement in the wearable computing environment.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.7
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• pp.741-749
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• 2003

In this paper, we investigated the degree of compensation for WDM channel signal distortion due to chromatic dispersion, self phase modulation(SPM) and cross phase modulation(XPM). The considered system is 120 Gbps (3${\times}$40 Gbps) intensity modulation direct detection(IM/DD) WDM transmission system with path-averaged intensity approximation(PAIA) mid-span spectral inversion(MSSI) as compensation method. This system have highly nonlinear dispersion shifted fiber(HNL-DSF) as nonlinear medium in optical phase conjugator(OPC). We use 1 dB eye opening peralty(EOP) in order to evaluate the characteristics of compensation for distorted WDM channels. We confirmed that improvement of transmission distance and performance is achieved by MSSI method to distorted long-haul IM/DD WDM channels due to chromatic dispersion, SPM and XPM. And in the aspect of compensation for distorted pulse due to XPM, the MSSI method is effective to IM/DD WDM transmission system with high fiber dispersion coefficient.

• The Journal of the Korea Contents Association
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• v.13 no.1
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• pp.1-8
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• 2013

The accuracy of a real facial recognition system can be varied according to the accuracy of the eye detection algorithm when we design and implement a semi-automatic facial recognition algorithm depending on the eye position of a database. In this paper, a fully automatic facial recognition algorithm is proposed such that Gabor and LBP features are extracted from fiducial points of a face graph which was created by using fiducial points based on the eyes, nose, mouth and border lines of a face, fitted on the face image. In this algorithm, the recognition performance could be increased because a face graph can be fitted on a face image automatically and fiducial points based LPB features are implemented with the basic Gabor features. The simulation results show that the proposed algorithm can be used in real-time recognition for more than 1,000 faces and produce good recognition performance for each data set.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.2
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• pp.195-201
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• 2005

This paper describes preliminary results we have obtained in developing a computer vision system based on active IR illumination for real time gaze tracking for interactive graphic display. Unlike most of the existing gaze tracking techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person, our gaze tracker can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using the Generalized Regression Neural Networks (GRNN). With GRNN, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Furthermore, the mapping function can generalize to other individuals not used in the training. The effectiveness of our gaze tracker is demonstrated by preliminary experiments that involve gaze-contingent interactive graphic display.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.1
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• pp.15-22
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• 2005

In this paper, we propose a face recognition system by using the CCD color image. We first get the face candidate image by using YCbCr color model and adaptive skin color information. And we use it initial curve of active contour model to extract face region. We use the Eye map and mouth map using color information for extracting facial feature from the face image. To obtain center point of Log-polar image, we use extracted facial feature from the face image. In order to obtain feature vectors, we use extracted coefficients from DCT and wavelet transform. To show the validity of the proposed method, we performed a face recognition using neural network with BP learning algorithm. Experimental results show that the proposed method is robuster with higher recogntion rate than the conventional method for the rotation and scale variant.

• Korean Journal of Radiology
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• v.2 no.4
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• pp.197-203
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• 2001

Objective: To compare the clinical utility of contrast-enhanced color Doppler US in the differentiation of retinal detachment (RD) from vitreous membrane (VM) with that of various conventional US modalities, and to analyze the enhancement patterns in cases showing an enhancement effect. Materials and Methods: In 32 eyes examined over a recent two-year period, RD (n=14) and VM (n=18) were confirmed by surgery (n=28) or clinical follow-up (n=4). In all cases, gray-scale, color Doppler, and power Doppler US were performed prior to contrast injection, and after the intravenous injection of Levovist (Schering, Berlin) by hand for 30 seconds at a dose of 2.5 g and a concentration of 300 mg/mL via an antecubital vein, contrast-enhanced color Doppler US was performed. At Doppler US, the diagnostic criterion for RD and VM was whether or not color signals were visualized in membranous structures. Results: Diagnostic accuracy was 78% at gray-scale US, 81% at color Doppler US, 59% at power Doppler US, and 97% at contrast-enhanced color Doppler US. The sensitivity of color Doppler US to color signals in RD increased from 57% to 93% after contrast enhancement. The enhancement patterns observed were signal accentuation (n=3), signal extension (n=2), signal addition (n=3), and new signal visualization (n=5). Conclusion: Contrast-enhanced color Doppler US was the most accurate US modality for differentiating RD from VM, showing a significantly increased signal detection rate in RD.

• Journal of the Korea Society of Computer and Information
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• v.29 no.8
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• pp.43-51
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• 2024

This paper proposes a method for acquiring and analyzing ocular data using a special-purpose diver mask targeted at divers who primarily engage in underwater activities. This involves tracking the user's gaze with the help of a custom-built ocular dataset and a YOLOv8-nano model developed for this purpose. The model achieved an average processing time of 45.52ms per frame and successfully recognized states of eyes being open or closed with 99% accuracy. Based on the analysis of the ocular data, a gaze tracking algorithm was developed that can map to real-world coordinates. The validation of this algorithm showed an average error rate of about 1% on the x-axis and about 6% on the y-axis.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.82-90
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• 2014

In this paper, a couple of 4-channel differential transimpedance amplifier arrays are realized in a standard 0.18um CMOS technology for the applications of linear LADAR(laser detection and ranging) systems. Each array targets 1.25-Gb/s operations, where the current-mode chip consists of current-mirror input stage, a single-to-differential amplifier, and an output buffer. The input stage exploits the local feedback current-mirror configuration for low input resistance and low noise characteristics. Measurements demonstrate that each channel achieves $69-dB{\Omega}$ transimpedance gain, 2.2-GHz bandwidth, 21.5-pA/sqrt(Hz) average noise current spectral density (corresponding to the optical sensitivity of -20.5-dBm), and the 4-channel total power dissipation of 147.6-mW from a single 1.8-V supply. The measured eye-diagrams confirms wide and clear eye-openings for 1.25-Gb/s operations. Meanwhile, the voltage-mode chip consists of inverter input stage for low noise characteristics, a single-to-differential amplifier, and an output buffer. Test chips reveal that each channel achieves $73-dB{\Omega}$ transimpedance gain, 1.1-GHz bandwidth, 13.2-pA/sqrt(Hz) average noise current spectral density (corresponding to the optical sensitivity of -22.8-dBm), and the 4-channel total power dissipation of 138.4-mW from a single 1.8-V supply. The measured eye-diagrams confirms wide and clear eye-openings for 1.25-Gb/s operations.

• Korean Journal of Veterinary Service
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• v.38 no.3
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• pp.145-153
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• 2015

In this study, we developed a loop-mediated isothermal amplification (LAMP) with hydroxynaphtol blue dye (HNB) for rapid and direct visual detection of porcine circovirus 2 DNA with high sensitivity and specificity. The LAMP was completed in 40 min at $63^{\circ}C$, and the results of the LAMP can be confirmed by naked eye without any detection process. The sensitivity of the LAMP was 10-fold higher than that of the commercial PCR (cPCR) and real time PCR (rPCR) previously reported. In clinical application, the PCV2 detection rate of the LAMP was the same on porcine tissue samples (75.0%, 36/48) between porcine blood samples (75.0%, 39/52). The PCV2 detection rate (75.0%) of LAMP was higher than those of the cPCR and rPCR (67.3%, 35/52) in blood samples. In conclusion, the LAMP developed in the study could be an useful alternative method for the detection of PCV2 in the swine disease diagnostic laboratories.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.117-126
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• 2020

A maritime object detection system is an intelligent assistance system to maritime autonomous surface ship(MASS). It detects automatically floating debris, which has a clash risk with objects in the surrounding water and used to be checked by a captain with a naked eye, at a similar level of accuracy to the human check method. It is used to detect objects around a ship. In the past, they were detected with information gathered from radars or sonar devices. With the development of artificial intelligence technology, intelligent CCTV installed in a ship are used to detect various types of floating debris on the course of sailing. If the speed of processing video data slows down due to the various requirements and complexity of MASS, however, there is no guarantee for safety as well as smooth service support. Trying to solve this issue, this study conducted research on the minimization of computation volumes for video data and the increased speed of data processing to detect maritime objects. Unlike previous studies that used the Hough transform algorithm to find the horizon and secure the areas of interest for the concerned objects, the present study proposed a new method of optimizing a binarization algorithm and finding areas whose locations were similar to actual objects in order to improve the speed. A maritime object detection system was materialized based on deep learning CNN to demonstrate the usefulness of the proposed method and assess the performance of the algorithm. The proposed algorithm performed at a speed that was 4 times faster than the old method while keeping the detection accuracy of the old method.