• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.309-311
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• 2017

With the recent development of the Internet (IoT) technology, we have come to a very connected society. This paper focuses on the security aspects that can occur within the LPWA Network environment of the Internet of things, and proposes a new machine learning method considering next generation IPS / IDS that can detect and block unexpected and unusual behavior of devices.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.313-316
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• 2011

본 논문에서는 파티클 필터를 이용한 이동 로봇의 위치 추정 방법을 제안한다. 이동 로봇의 위치를 추정하기 위해알기 위해 이동 로봇에 설치되어 있는 초음파 센서를 이용하여 주변 환경과의 거리를 측정한다. 그리고 측정된 센서 값과 이동 동작의 불확실성을 고려하여, 위치 추정 오차를 줄이고자 가우스 확률분포와 파티클 필터 기법을 이용하여 이동 로봇의 위치를 추정한다. 본 논문에서는 구현된 시스템과 실험 결과를 소개한다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.3
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• pp.80-87
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• 2007

In this paper, we investigate an enhancement method for Western epigraphic images, which is based on local statistics. Image data is partitioned into two regions, background and information. Statistical and functional analyses are proceeded for image modeling. The Western epigraphic images, for the most part, have shown the Gaussian distribution. It is clarified that each region can be differentiated statistically. The local normalization process algorithm is designed on this model. The parameter is extracted and it‘s properties are verified with the size of moving window. The spatial gray-level distribution is modified and regions are differentiated by adjusting parameter and the size of moving window. Local statistics are utilized for realization of the enhancement, so that difference between regions can be enhanced and noise or speckles of region can be smoothed. Experimental results are presented to show the superiority of the proposed algorithm over the conventional methods.

• Communications for Statistical Applications and Methods
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• v.15 no.5
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• pp.737-752
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• 2008

About 1800, mathematicians combined analysis of error and probability theory into error theory. After developed by Gauss and Laplace, error theory was widely used in branches of natural science. Motivated by the successful applications of error theory in natural sciences, scientists like Adolph Quetelet tried to incorporate social statistics with error theory. But there were not a few differences between social science and natural science. In this paper we discussed topics raised then. The problems considered are as follows: the interpretation of individual man in society; the arguments against statistical methods; history of the measures for diversity. From the successes and failures of the $19^{th}$ century social statisticians, we can see how statistics became a science that is essential to both natural and social sciences. And we can see that those problems, which were not easy to solve for the $19^{th}$ century social statisticians, matter today too.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.294-302
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• 2018

To analyze the behavior of a soil beam under pore water pressure, the results of analytical solutions and finite element analysis (FEM) were compared quantitatively. In contrast to the results of the analytical solution, the horizontal stress obtained from the FEM did not show a symmetrical distribution. On the other hand, the horizontal stress became closer to symmetrical distribution as the number of elements of the soil beam were increased. A comparison of the horizontal stresses from the analytic solution with those obtained from Gaussian points of FEM showed that the magnitude of the tensile stress from the FEM using 3 elements was 6% of the maximum value of the analytical solution and the compressive stress from the FEM using the same elements was 37% of the maximum value of the analytical solution. The magnitude of the tensile stress from the FEM using 6 elements was 61% of the maximum value of the analytical solution and the magnitude of the compressive stress from the FEM using the elements was 83% of the maximum value of the analytical solution. Vertical stresses, which were obtained from the analytical solution, showed a continuous distribution with the depth of the soil beam, whereas the vertical stresses from the FEM showed a discrete distribution corresponding to each element. The results also showed that the average value of the vertical stresses of each element was close to that of the pore water pressure. A comparison of the vertical displacements computed at the near vertical center line of the soil beam from the FEM with those of the analytical solution showed that the magnitude of the vertical displacement from FEM using 3 elements was 35% of the value of the analytical solution and the magnitude of the vertical displacement from FEM using 6 elements was 57% of the value of the analytical solution.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.63-70
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• 2022

Although 2D Object detection has been largely improved in the past years with the advance of deep learning methods and the use of large labeled image datasets, 3D object detection from 2D imagery is a challenging problem in a variety of applications such as robotics, due to the lack of data and diversity of appearances and shapes of objects within a category. Google has just announced the launch of Objectron that has a novel data pipeline using mobile augmented reality session data. However, it also is corresponding to 2D-driven 3D object detection technique. This study explores more mature 2D object detection method, and applies its 2D projection to Objectron 3D lifting system. Most object detection methods use bounding boxes to encode and represent the object shape and location. In this work, we explore a stochastic representation of object regions using Gaussian distributions. We also present a similarity measure for the Gaussian distributions based on the Hellinger Distance, which can be viewed as a stochastic Intersection-over-Union. Our experimental results show that the proposed Gaussian representations are closer to annotated segmentation masks in available datasets. Thus, less accuracy problem that is one of several limitations of Objectron can be relaxed.

• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.748-760
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• 2012

In case brightness distribution is concentrated in a region, it is difficult to classify the image features. To solve this problem, we apply global histogram equalization and local histogram equalization to images. In case of global histogram equalization, it can be too bright or dark because it doesn't consider the density of brightness distribution. Thus, it is difficult to enhance the local contrast in the images. In case of local histogram equalization, it can produce unexpected blocks in the images. In order to enhance the contrast in the images, this paper proposes a local histogram equalization based on the Gaussian Mixture Models(GMMs) in regions of histogram. Mean and variance parameters in each regions is updated EM-algorithm repeatedly and then ranges of equalization on each regions. The experimental results performed with image of various contrasts show that the proposed algorithm is better than the global histogram equalization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.2
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• pp.334-343
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• 1997

Reference white in color television receiver can be achieved by adjusting the RGB gun current ratio and it is necessary to provide additional gain ratio adjustment for the RGB video signal. Generally, the gun current density profile has a gaussian distribution and the gain-bandwidth product of RGB channel amplifieris constant. Therefore brightness and spatial resolution are changed with variations in reference white of receiver. In this paper, the effect of RGB gun current and channel gain ratios on brightness and resolution of CPT is analyzed. Brightness is increased with the color temperature of referenc white because of Helmholtz-kohlrausch effect. The change in ligh output is more abrupt and spatial resolution is improved with unity current ratio. For more bright and improved ressolution we also present the range of color temperature of reference white for P22 phosphors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2939-2945
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• 2014

This paper has analyzed the change of threshold voltage for oxide structure of symmetric and asymmetric double gate(DG) MOSFET. The asymmetric DGMOSFET can be fabricated with different top and bottom gate oxide thickness, while the symmetric DGMOSFET has the same top and bottom gate oxide thickness. Therefore optimum threshold voltage is considered for top and bottom gate oxide thickness of asymmetric DGMOSFET, compared with the threshold voltage of symmetric DGMOSFET. To obtain the threshold voltage, the analytical potential distribution is derived from Possion's equation, and Gaussian distribution function is used as doping profile. We investigate for bottom gate voltage, channel length and thickness, and doping concentration how top and bottom gate oxide thickness influences on threshold voltage using this threshold voltage model. As a result, threshold voltage is greatly changed for oxide thickness, and we know the changing trend greatly differs with bottom gate voltage, channel length and thickness, and doping concentration.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.401-406
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• 2015

The change of subthreshold swing for channel length of asymmetric double gate(DG) MOSFET has been analyzed. The subthreshold swing is the important factor to determine digital chracteristics of transistor and is degraded with reduction of channel. The subthreshold swing for channel length of the DGMOSFET developed to solve this problem is investigated for channel thickness, oxide thickness, top and bottom gate voltage and doping concentration. Especially the subthreshold swing for asymmetric DGMOSFET to be able to be fabricated with different top and bottom gate structure is investigated in detail for bottom gate voltage and bottom oxide thickness. To obtain the analytical subthreshold swing, the analytical potential distribution is derived from Possion's equation, and Gaussian distribution function is used as doping profile. As a result, subthreshold swing is sensitively changed according to top and bottom gate voltage, channel doping concentration and channel dimension.