• Journal of Broadcast Engineering
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• v.13 no.5
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• pp.685-695
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• 2008

This paper presents a method to segment the object of interest from a set of multi-view images with minimal user interaction. Specifically, after the user segments an initial image, we first estimate the transformations between foreground and background of the segmented image and the neighboring image, respectively. From these transformations, we obtain regions in the neighboring image that respectively correspond to the foreground and the background of the segmented image. We are then able to segment the neighboring image based on these regions, and iterate this process to segment the whole image set. Transformation of foregrounds are estimated by feature-based registration with free-form deformation, while transformation of backgrounds are estimated by homography constrained to affine transformation. Here, both are based on correspondence point pairs. Segmentation is done by estimating pixel color distributions and defining a shape prior based on the obtained foreground and background regions and applying them to a Markov random field (MRF) energy minimization framework for image segmentation. Experimental results demonstrate the effectiveness of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3B
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• pp.421-430
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• 2010

Now a days, as a communications network is being broadband, IPTV(Internet Protocol Television) service which provides various two-way TV service is increasing. But as the data which is transmitted between IPTV set-top box and smart card is almost transmitted to set-top box, the illegal user who gets legal authority by approaching to the context of contents illegally using McComac Hack Attack is not prevented perfectly. In this paper, set-top box access security model is proposed which is for the protection from McComac Hack Attack that tries to get permission for access of IPTV service illegally making data line which is connected from smart card to set-top box by using same kind of other set-top box which illegal user uses. The proposed model reports the result of test which tests the user who wants to get permission illegally by registration the information of a condition of smart card which is usable in set-top box in certification server so that it prevents illegal user. Specially, the proposed model strengthen the security about set-top box by adapting public key which is used for establishing neighbor link and inter-certification process though secret value and random number which is created by Pseudo random function.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.5
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• pp.1-8
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• 2008

The belief propagation method that has been studied recently yields good performance in disparity extraction. The method in which a target function is modeled as an energy function based on Markov random field(MRF), solves the stereo matching problem by finding the disparity to minimize the energy function. MRF models provide robust and unified framework for vision problem such as stereo and image restoration. the belief propagation method produces quite correct results, but it has difficulty in real time implementation because of higher computational complexity than other stereo methods. To relieve this problem, in this paper, we propose a fast algorithm of the belief propagation method. Energy function consists of a data term and a smoothness tern. The data term usually corresponds to the difference in brightness between correspondences, and smoothness term indicates the continuity of adjacent pixels. Smoothness information is created from messages, which are assigned using four different message arrays for the pixel positions adjacent in four directions. The processing time for four message arrays dominates 80 percent of the whole program execution time. In the proposed method, we propose an algorithm that dramatically reduces the processing time require in message calculation, since the message.; are not produced in four arrays but in a single array. Tn the last step of disparity extraction process, the messages are called in the single integrated array and this algorithm requires 1/4 computational complexity of the conventional method. Our method is evaluated by comparing the disparity error rates of our method and the conventional method. Experimental results show that the proposed method remarkably reduces the execution time while it rarely increases disparity error.

• Journal of the Korean Society for Railway
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• v.14 no.6
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• pp.526-534
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• 2011

In this study, proposed is the methodology to determine the upper limit for stiffness of rail pad for the ballasted and concrete track in high-speed railway in the viewpoint of running safety, considering the dynamic characteristics of train and track and the operation environment. For the track irregularity, one of the most important input parameters for traintrack interaction analysis, the reference vertical track irregularity PSDs(power spectral densities) for the ballasted and concrete track in a wide range of frequencies were proposed based on those presented in France and Germany and that obtained from the measured data at Kyeong-Bu 1st phase high-speed railway line. Using these reference PSD models, the input data for the vertical track irregularity data were regenerated by random generation process, and then, the wheel load reduction rates according to the stiffness of the rail pads have been calculated by the train-track interaction analysis technique. Finally, by comparing the wheel load reduction rates calculated with the derailment criteria prescribed in the Korean standards for railway vehicle safety criteria, the upper limits for the stiffness of rail pad have been proposed.

• Journal of Life Science
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• v.24 no.6
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• pp.612-617
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• 2014

The phenetic relationships among six natural populations of Equisetum pratense in Korea were investigated at the population level by constructing a tree based on Random Amplified Polymorphic DNA (RAPD) markers. RAPD analysis was also conducted to estimate genetic diversity and the population structure of E. pratense. A mean of 26.7% at the six population levels indicated polymorphism. E. pratense was found to have fewer alleles per locus (1.267) and fewer effective alleles per locus (1.176). Genetic diversity (0.102) in E. pratense is lower than the average for species with similar life history traits. Total genetic diversity values (HT) varied between 0.112 (OPD-07) and 0.445 (OPD-16), for an average overall polymorphic locus of 0.141. Inter-locus variation in the within-population genetic diversity ($H_S$) was low (0.102). Asexual reproduction, small population size, and the colonization process are proposed as possible factors contributing to the observed low genetic diversity in E. pratense. On a per-locus basis, the proportion of total genetic variation due to differences among populations ($G_{ST}$) ranged from 0.129 for OPD-07 to 0.455 for OPD-09, with a mean of 0.277. This indicated that about 27.7% of the total variation was among populations. Thus, genetic variation (72.3%) resided within populations. This study contributes new information for research on the taxonomy and population genetics of E. pratense.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.663-669
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• 2014

The electrical characteristics of RRAM with different annealing temperature and thickness have been measured and discussed. The devices with Pt/Ti top electrode of 150nm, Pt bottom electrode of 150nm, $HfO_2$ oxide thickness of 45nm and 70nm have been fabricated. The fabricated device were classified by 3 different kinds according to the annealing temperature, such as non-annealed, annealed at $500^{\circ}C$ and annealed at $850^{\circ}C$. The set and reset voltages and the variation of resistance with temperatures have been measured as electrical properties. From the measurement, it was found that the set voltages were decreased and the reset voltage were increased slightly, and thus the sensing window was decreased with increasing of measurement temperatures. It was remarkable that the device annealed at $850^{\circ}C$ showed the best performances. Although the device with thickness of 45nm showed better performances in the point of the sensing window, the resistance of 45nm devices was large relatively in the low resistive state. It can be expected to enhance the device performances with ultra thin RRAM if the defect generation could be reduced at the $HfO_2$ deposition process.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.77-88
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• 2021

Duck industry had a rapid growth in recent years. Nevertheless, researches to improve duck house environment are still not sufficient enough. Moisture generation of duck house litter is an important factor because it may cause severe illness and low productivity. However, the measuring process is difficult because it could be disturbed with animal excrements and other factors. Therefore, it has to be calculated according to the environmental data around the duck house litter. To cut through all these procedures, we built several machine learning regression model forecasting moisture generation of litter by measured environment data (air temperature, relative humidity, wind velocity and water contents). 5 models (Multi Linear Regression, k-Nearest Neighbors, Support Vector Regression, Random Forest and Deep Neural Network). have been selected for regression. By using R-Square, RMSE and MAE as evaluation metrics, the best accurate model was estimated according to the variables for each machine learning model. In addition, to address the small amount of data acquired through lab experiments, bootstrapping method, a technique utilized in statistics, was used. As a result, the most accurate model selected was Random Forest, with parameters of n-estimator 200 by bootstrapping the original data nine times.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.463-471
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• 2019

This paper proposes a method for reducing the complexity of LIC (Local Illuminance Compensation) for bi-directional inter prediction. The LIC performs local illumination compensation using neighboring reconstruction samples of the current block and the reference block to improve the accuracy of the inter prediction. Since the weight and offset required for local illumination compensation are calculated at both sides of the encoder and decoder using the reconstructed samples, there is an advantage that the coding efficiency is improved without signaling any information. Since the weight and the offset are obtained in the encoding prediction step and the decoding step, encoder and decoder complexity are increased. This paper proposes two methods for low complexity LIC. The first method is a method of applying illumination compensation with offset only in bi-directional prediction, and the second is a method of applying LIC after weighted average step of reference block obtained by bidirectional prediction. To evaluate the performance of the proposed method, BD-rate is compared with BMS-2.0.1 using B, C, and D classes of MPEG standard experimental image under RA (Random Access) condition. Experimental results show that the proposed method reduces the average of 0.29%, 0.23%, 0.04% for Y, U, and V in terms of BD-rate performance compared to BMS-2.0.1 and encoding/decoding time is almost same. Although the BD-rate was lost, the calculation complexity of the LIC was greatly reduced as the multiplication operation was removed and the addition operation was halved in the LIC parameter derivation process.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.6
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• pp.206-216
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• 2020

As the number of aging railway bridges in Korea increases, maintenance costs due to aging are increasing and continuous management is becoming more important. However, while the number of old facilities to be managed increases, there is a shortage of professional personnel capable of inspecting and diagnosing these old facilities. To solve these problems, this study presents an improved model that can detect Local damage to structures using machine learning techniques of AI technology. To construct a damage detection machine learning model, an analysis model of the bridge was set by referring to the design drawing of a non-ballasted plate-girder railroad bridge. Static strain data according to the damage scenario was extracted with the analysis model, and the Local damage index based on the reliability of the bridge was presented using statistical techniques. Damage was performed in a three-step process of identifying the damage existence, the damage location, and the damage severity. In the estimation of the damage severity, a linear regression model was additionally considered to detect random damage. Finally, the random damage location was estimated and verified using a machine learning-based damage detection classification learning model and a regression model.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.338-347
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• 2021

In this paper, the beta-ray sensor circuit used in the true random number generator was designed using DB HiTek's 0.18㎛ CMOS process. The CSA circuit proposed a circuit having a function of selecting a PMOS feedback resistor and an NMOS feedback resistor, and a function of selecting a feedback capacitor of 50fF and 100fF. And for the pulse shaper circuit, a CR-RC2 pulse shaper circuit using a non-inverting amplifier was used. Since the OPAMP circuit used in this paper uses single power instead of dual power, we proposed a circuit in which the resistor of the CR circuit and one node of the capacitor of the RC circuit are connected to VCOM instead of GND. And since the output signal of the pulse shaper does not increase monotonically, even if the output signal of the comparator circuit generates multiple consecutive pulses, the monostable multivibrator circuit is used to prevent signal distortion. In addition, the CSA input terminal, VIN, and the beta-ray sensor output terminal are placed on the top and bottom of the silicon chip to reduce capacitive coupling noise between PCB traces.