• Journal of the Microelectronics and Packaging Society
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• v.29 no.4
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• pp.29-34
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• 2022

A fabrication process of smart windows with controllable visible light transmittance by using retardation films is proposed. The 𝛌/4-phase retardation films that can convert a linearly polarized light into circularly polarized light are achieved through photo-alignment layers and reactive mesogen (RM) coating process. Two sheets of the fabricated retardation films with different orientation angles induced to light transmission mode (45°/-45°) and light blocking mode (45°/45°) for visible wavelength. We evaluated retardation characteristics according to the thickness of the birefringent RM material and found out the optimal condition for the film with 𝚫n·d of 𝛌/4-phase. The proposed structure of the smart window exhibited the light blocking ratio improved by more than 20% in the visible wavelength (380 nm to 780 nm). Finally, it was confirmed that the feasibility of the window structure by applying to a prototype for a smart window with a size of 150 × 150 mm².

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.555-562
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• 2019

This paper presents soil deformation measurement in model chamber based on photogrammetry. We created an aluminum framed acrylic model chamber with soil inside and applied photogrammetry to measure soil deformation caused by loading tests. The soil consists of 40% black and 60% regular sand to create image contrast in soil images. In preprocessing, the self camera calibration was carried out for IOPs (Interior Orientation Parameters), followed by the space resection to estimate EOPs (Exterior Orientation Parameters) using control points located along the aluminum frame. Image matching was applied to measure the soil displacement. We tested different matching window sizes and the effect of image smoothing. Experimental results showed that 65x65 pixels of window size produced better soil deformation map and the image smoothing was useful to suppress the matching outliers. In conclusion, photogrammetry was able to efficiently generated soil deformation map.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2341-2348
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• 2009

An intrusion detection technique based on host consider system call sequence or system call arguments. These two ways are suitable when system call sequence or order and length of system call arguments are out of order. However, there are two disadvantages which a false positive rate and a false negative rate are high. In this paper we propose the T-N2SCD detection model based on Time Window in order to reduce false positive rate and false negative rate. Data for using this experiment is provided from DARPA. As experimental results, the proposed model showed that the false positive rate and the false negative rate are lowest at an interval of 1000ms than at different intervals.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.48 no.4
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• pp.6-13
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• 2011

Due to its robustness to illumination change, normalized cross-correlation based similarity measurement is widely used in many machine vision applications. However, its inefficient computation structure is not adequate for real-time embedded vision system. In this paper, we present an efficient hardware architecture based on a normalized cross correlation (NCC) for fast image similarity measure. The proposed architecture simplifies window-sum process of the NCC using the integral-image. Relieving the overhead to constructing integral image, we make it possible to process integral image construction at the same time that pixel sequences are inputted. Also the proposed segmented integral image method can reduce the buffer size for storing integral image data.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.3
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• pp.86-92
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• 2000

In this paper, we develop protocol analyzer that can analyze and monitor LAN(Local Area Network)-based TCP/IP protocol using the OOP(object-oriented programming) in Windows98/NT environment. TCP/IP(Transmission Control Protocol/Internet Protocol) protocol analyzer is consist of interface hardware, protocol analysis software and GUI(Graphic User Interface). It is designed for the real-time analysis using the real-time object. In results of Performance test, TCP/IP Protocol analyzer is showed that it can analyze and monitor without frame error in LAN-based. Also, developed protocol analyser operates better than conventional protocol analyzer in performance. It can be used in maintenance fields of communication and network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6B
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• pp.575-583
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• 2004

In this paper, we extend the multiple time scale control framework to the window-based congestion control, in particular, such as the TCP. This is performed by interfacing the TCP with a large time scale control module which adjusts the aggressiveness of the bandwidth consumption behavior exhibited by the TCP as a function of large time scale Self-Similar network state. i.e., conformation that exceeds the horizon of the feedback loop as determined by the RTT. How to effectively utilize such an information-due to its probabilistic nature, dispersion over the multiple time scales, and affection on the top of the existing window-based congestion controls-is a non-trivial problem. The evaluation performance of the multiple time scale TCP is facilitated by a simulation of the bench-mark environment which is based on the physical modeling of a self-similar traffic. We explicate our methodology for discerning and evaluating the impact of changes in transport protocols in the protocol stack under the self-similar traffic conditions. We discuss issues arising in the comparative performance evaluation under heavy-tailed workloads.

• Journal of IKEEE
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• v.24 no.1
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• pp.147-153
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• 2020

Conventional lane detection algorithms have problems in that the detection rate is lowered in road environments having a large change in curvature and illumination. The probabilistic Hough transform method has low lane detection rate since it exploits edges and restrictive angles. On the other hand, the method using a sliding window can detect a curved lane as the lane is detected by dividing the image into windows. However, the detection rate of this method is affected by road slopes because it uses affine transformation. In order to detect lanes robustly and avoid obstacles, we propose driving assist system using semantic segmentation based on deep learning. The architecture for segmentation is SegNet based on VGG-16. The semantic image segmentation feature can be used to calculate safety space and predict collisions so that we control a vehicle using adaptive-MPC to avoid objects and keep lanes. Simulation results with CARLA show that the proposed algorithm detects lanes robustly and avoids unknown obstacles in front of vehicle.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11C
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• pp.940-947
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• 2010

Motion Compensated Frame Interpolation(MCFI) has been used to reduce motion jerkiness for dynamic scenes and motion blurriness for LCD-panel display as post processing for high quality display. However, MCFI that directly uses the motion information often suffers from annoying artifacts such as blockiness, ghost effects, and deformed structures. So in this paper, we propose a novel edge-based adaptively weighted vector median filter as post-processing. At first, the proposed method generates an edge direction map through a sobel mask and a weighted maximum frequent filter. And then, outlier MVs are removed by average of angle difference and replaced by a median MV of $3{\times}3$ window. Finally, weighted vector median filter adjusts the weighting values based on edge direction derived from spatial coherence between the edge direction continuity and motion vector. The results show that the performance of PSNR and SSIM are higher up to 0.5 ~ 1 dB and 0.4 ~ 0.8 %, respectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.08a
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• pp.73-76
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• 2008

We present a area-based method for stereo matching using varying weights. A central problem in a area-based stereo matching is different result from selecting a window size. Most of the previous window-based methods iteratively update windows. However, the iterative methods very sensitive the initial disparity estimation and are computationally expensive. To resolve this problem, we proposed a new function to assign weights to pixels using features. To begin with, we extract features in a given stereo images based on edge. We adjust the weights of the pixels in a given window based on correlation of the stereo images. Then, we match pixels in a given window between the reference and target images of a stereo pair. The proposed method is compared to existing matching strategies using both synthetic and real images. The experimental results show the improved accuracy of the proposed method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.1
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• pp.39-45
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• 2022

In this paper, we propose methods to improve image-based auto-focus that can compensate for drawbacks of traditional auto-focus control. When adjusting the focus, there is a problem that the focus window cannot be set to the same position if the camera's LOS is not directed at the same location and flow or shake. To address this issue, we applied image tracking techniques to improve optimal focus localization accuracy. And also, although the same focus value should be calculated at the same focus step, but different values can be calculated by camera's fine shaking or image disturbance due to atmospheric scattering. To tackle this problem a SAFS (Stable Adjacency Frame Selection) has been proposed. As a result of this study, our proposed methodology shows more accurate than traditional methods in terms of finding best focus position.