• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.705-708
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• 2018

Among biometrics commercialized for security, iris recognition technology has the most excellent security for the probability of the match between individuals is the lowest. Current commercialized iris recognition technology has excellent recognition ability, but this technology has a fatal drawback. Without the user's active cooperation, it cannot recognize the iris correctly. To make up for this weakness, recent trend of iris recognition development mounts a non-volunteering, unconstrained method. According to this information, the objective of this research is developing a module that can identify people iris from a video acquired by high performance infrared camera in a range of 3m and in a involuntary way. For this, we import images from the video and find people's face and eye positions from the images using Haar classifier trained through Cascade training method. finally, we crop the iris by Hough circle transform and compare it with data from the database to identify people.

• Journal of information and communication convergence engineering
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• v.8 no.5
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• pp.575-580
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• 2010

Eye gaze as a form of input was primarily developed for users who are unable to use usual interaction devices such as keyboard and the mouse; however, with the increasing accuracy in eye gaze detection with decreasing cost of development, it tends to be a practical interaction method for able-bodied users in soon future as well. This paper explores a low-cost, robust, rotation and illumination independent eye gaze system for gaze enhanced user interfaces. We introduce two brand-new algorithms for fast and sub-pixel precise pupil center detection and 2D Eye Gaze estimation by means of deformable template matching methodology. In this paper, we propose a new algorithm based on the deformable angular integral search algorithm based on minimum intensity value to localize eyeball (iris outer boundary) in gray scale eye region images. Basically, it finds the center of the pupil in order to use it in our second proposed algorithm which is about 2D eye gaze tracking. First, we detect the eye regions by means of Intel OpenCV AdaBoost Haar cascade classifiers and assign the approximate size of eyeball depending on the eye region size. Secondly, using DAISMI (Deformable Angular Integral Search by Minimum Intensity) algorithm, pupil center is detected. Then, by using the percentage of black pixels over eyeball circle area, we convert the image into binary (Black and white color) for being used in the next part: DTBGE (Deformable Template based 2D Gaze Estimation) algorithm. Finally, using DTBGE algorithm, initial pupil center coordinates are assigned and DTBGE creates new pupil center coordinates and estimates the final gaze directions and eyeball size. We have performed extensive experiments and achieved very encouraging results. Finally, we discuss the effectiveness of the proposed method through several experimental results.

• Journal of electromagnetic engineering and science
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• v.11 no.2
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• pp.76-82
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• 2011

In this paper, a novel design for a dual-band negative group delay circuit (NGDC) is proposed. Composite right/left-handed (CRLH) ${\lambda}/4$ short stubs are employed as a dual-band resonator. A CRLH ${\lambda}/4$ short stub is composed of a typical transmission line element as the right-handed component and a high-pass lumped element section as the left-handed component. It is possible to simultaneously obtain open impedances at two separate frequencies by the combination of distinctive phase responses of the right/left-handed components. Negative group delay (NGD) can be obtained at two frequencies by using dual-band characteristics of the CRLH stub. In order to achieve a bandwidth extension, the proposed structure consists of a two-stage dual-band NGDC with different center frequencies connected in a cascade. According to the experiment performed, with wide-band code division multiple access (WCDMA) and worldwide interoperability for microwave access (WiMAX), NGDs of $-3.0{\pm}0.4$ ns and $-3.1{\pm}0.5$ ns are obtained at 2.12~2.16 GHz and 3.46~3.54 GHz, respectively.

• Journal of the Korea Society of Computer and Information
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• v.19 no.6
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• pp.19-26
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• 2014

An ensemble classifier system is a widely-used multi-classifier system, which combines the results from each classifier and, as a result, achieves better classification result than any single classifier used. Several methods have been used to build an ensemble classifier including boosting, which is a cascade method where misclassified examples in previous stage are used to boost the performance in current stage. Boosting is, however, a serial method which does not form a complete feedback loop. In this paper, proposed is context sensitive SVM ensemble (CASE) which adopts SVM, one of the best classifiers in term of classification rate, as a basic classifier and clustering method to divide feature space into contexts. As CASE divides feature space and trains SVMs simultaneously, the result from one component can be applied to the other and CASE achieves better result than boosting. Experimental results prove the usefulness of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.6
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• pp.1095-1106
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• 1994

This paper presents a method for determining optimal grayscale function processing(FP) morphological filters under the least square (LMS) error criterion. The optimal erosion and dilation filters with a grayscale structuring element(GSE) are determined by minimizing the mean square error (MSE) between the desired signal and the filter output. It is shown that convergence of the erosion and dilation filters can be achieved by a proper choice of the step size parameter of the LMS algorithm. In an attempt to determine optimal closing and opening filters, a matrix representation of both opening and closing with a basis matrix is proposed. With this representation, opening and closing are accomplished by a local matrix operation rather than cascade operations. The LMS and back-propagation algorithm are utilzed for obtaining the optimal basis matrix for closing and opening. Some results of optimal morphological filters applied to 2-D images are presented.

• The Korean Journal of Applied Statistics
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• v.31 no.5
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• pp.539-554
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• 2018

Effective interaction between user and device is considered an important ability of IoT devices. For some applications, it is necessary to recognize human facial expressions in real time and make accurate judgments in order to respond to situations correctly. Therefore, many researches on facial image analysis have been preceded in order to construct a more accurate and faster recognition system. In this study, we constructed an automatic recognition system for facial expressions through two steps - a facial recognition step and a classification step. We compared various models with different sets of data with pixel information, landmark coordinates, Euclidean distances among landmark points, and arctangent angles. We found a fast and efficient prediction model with only 30 principal components of face landmark information. We applied several prediction models, that included linear discriminant analysis (LDA), random forests, support vector machine (SVM), and bagging; consequently, an SVM model gives the best result. The LDA model gives the second best prediction accuracy but it can fit and predict data faster than SVM and other methods. Finally, we compared our method to Microsoft Azure Emotion API and Convolution Neural Network (CNN). Our method gives a very competitive result.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.4 s.346
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• pp.16-22
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• 2006

Gigabit transimpedance amplifiers are realihzed in submicron CMOS technologies for Gigabit Ethernet applications. The regulated cascode technique is exploited to enhance the bandwidth and noise performance simultaneously so that it can isolate the large input parasitic capacitance including photodiode capacitance from the determination of the bandwidth. The 1.25Gb/s TIA implemented in a 0.6um CMOS technology shows the measured results of 58dBohm transimpedance gain, 950MHz bandwidth for a 0.5pF photodiode capacitance, 6.3pA/sqrt(Hz) average noise current spectral density, and 85mW power dissipation from a single 5V supply. In addition, a 10Gb/s TIA is realized in a 0.18um CMOS incorporating the RGC input and the inductive peaking techniques. It provides 59.4dBohm transimpedance gain, 8GHz bandwidth for a 0.25pF photodiode capacitance, 20pA/sqrt(Hz) noise current spectral density, and 14mW power consumption for a single 1.8V supply.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.1A
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• pp.104-112
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• 2005

Some design techniques for high speed and low power pipelined 8-bit ADC are described. To perform high-speed operation with relatively low power consumption, open loop architecture is adopted, while closed loop architecture (with MDAC) is used in conventional pipeline ADC. A distributed track and hold amplifier and a cascading structure are also adopted to increase the sampling rate. To reduce the power consumption and the die area, the number of amplifiers in each stage are optimized and reduced with proposed zero-crossing point generation method. At 500-MHz sampling rate, simulation results show that the power consumption is 210mW including digital logic with 1.8V power supply. And the targeted ADC achieves ENOB of about 8-bit with input frequency up to 200-MHz and input range of 1.2Vpp (Differential). The ADC is designed using a $0.18{\mu}m$ 6-Metal 1-Poly CMOS process and occupies an area of $900{\mu}m{\times}500{\mu}m$

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.101-106
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• 2014

This paper presents a wide dynamic range radio-frequency (RF) root-mean-square (RMS) power detector using an automatic gain control (AGC) loop. The AGC loop consists of a variable gain amplifier (VGA), RMS conversion block and gain control block. The VGA exploits dB-linear gain characteristic of the cascade VGA. The proposed circuit utilizes full-wave squaring and generates a DC voltage proportional to the RMS of an input RF signal. The proposed RMS power detector operates from 500MHz to 5GHz. The detecting input signal range is from 0 dBm to -70 dBm or more with a conversion gain of -4.53 mV/dBm. The proposed RMS power detector is designed in a 65-nm 1.2-V CMOS process, and dissipates a power of 5 mW. The total active area is $0.0097mm^2$.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.4
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• pp.149-156
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• 2022

In the current COVID-19 pandemic, fake news and misinformation related to COVID-19 have been causing serious confusion in our society. To accurately detect such fake news, social context-based methods have been widely studied in the literature. They detect fake news based on the social context that indicates how a news article is propagated over social media (e.g., Twitter). Most existing COVID-19 related datasets gathered for fake news detection, however, contain only the news content information, but not its social context information. In this case, the social context-based detection methods cannot be applied, which could be a big obstacle in the fake news detection research. To address this issue, in this work, we collect from Twitter the social context information based on CoAID, which is a COVID-19 news content dataset built for fake news detection, thereby building CoAID⁺ that includes both the news content information and its social context information. The CoAID⁺ dataset can be utilized in a variety of methods for social context-based fake news detection, thus would help revitalize the fake news detection research area. Finally, through a comprehensive analysis of the CoAID⁺ dataset in various perspectives, we present some interesting features capable of differentiating real and fake news.