• Proceedings of the KIEE Conference
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• 2005.04a
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• pp.203-206
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• 2005

본 연구에서는 카오스 2중 Tent 사상에 의한 랜덤 주파수 캐리어 발생기를 제안하고 있다. 제안된 방법은 2중 텐트사상의 분기트리(Bifurcation Tree)에서 카오스 발생 영역인 $\lambda$=0.99을 이용하여 랜덤 수글 발생시키고 있다. 제안된 방법과 종전의 LCG(Linear Congruential Generator)에 의한 방법의 고조파 스펙트럼을 실험에 의하여 비교 검토하였다.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.267-268
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• 2007

A dynamic range compression algorithm using Markov random field (MRF) modeling to display high dynamic range (HDR) images on low dynamic range (LDR) devices is proposed in this work. The proposed algorithm separates foreground objects from the background using the edge information, and then compresses the color differences across the edges based on the MRF modeling. By minimizing a cost function using belief propagation, the proposed algorithm can provide an effective LDR image. Simulation results show that the proposed algorithm provides good results.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.781-790
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• 1999

In this paper we consider estimation of cancer incidence rates for local areas. The raw estimates usually are based on small sample sizes and hence are usually unreliable. A hierarchical Bayes generalized linear model is used which connects the local areas thereby enabling one to 'borrow strength' Random effects with pairwise difference priors model the spatial structure in the data. The methods are applied to cancer incidence estimation for census tracts in a certain region of the state of New York.

• Journal of Plant Biotechnology
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• v.1 no.2
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• pp.109-115
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• 1999

A linkage map of Capsicum annuum L. was constructed by random amplified polymorphic DNA (RAPD) markers followed in a backcross population of an intraspecific cross between cultivars HDA210 and Yatsufusa. A total of 420 random primers were tested and 311 polymorphic bands were generated by 158 random primers. Among them, 86 Yatsufusa specific bands generated by 52 primers were examined for mapping. Most bands except three segregated in Mendelian fashion fitting the expected 1:1 ratio. The total length of the map was 533 cM distributed in 15 linkage groups. The map distance between adjacent markers ranged 0 to 32.8 cM, with an average distance of 9.1 cM (63 markers). Some markers were clustered and this may be due to the amplification of a repetitive sequence by the RAPDs. Primer pairs for a sequence characterized amplified region (SCAR) were developed and the segregation scores by the SCAR primers were in accordance with the RAPD data. Two QTL markers for number of axillary shoots and for early flowering were developed. One QTL for early flowering located in the linkage group 3 and explained 61 "io of the phenotypic variation. The other QTL for the number of axillary shoots located in the linkage group 4 explained 55 % of the phenotypic variation.tion.

• Journal of Communications and Networks
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• v.8 no.1
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• pp.93-105
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• 2006

The domination of the Internet by TCP-based services has spawned many efforts to provide high network utilization with low loss and delay in a simple and scalable manner. Active queue management (AQM) algorithms attempt to achieve these goals by regulating queues at bottleneck links to provide useful feedback to TCP sources. While many AQM algorithms have been proposed, most suffer from instability, require careful configuration of nonintuitive control parameters, or are not practical because of slow response to dynamic traffic changes. In this paper, we propose a new AQM algorithm, hybrid random early detection (HRED), that combines the more effective elements of recent algorithms with a random early detection (RED) core. HRED maps instantaneous queue length to a drop probability, automatically adjusting the slope and intercept of the mapping function to account for changes in traffic load and to keep queue length within the desired operating range. We demonstrate that straightforward selection of HRED parameters results in stable operation under steady load and rapid adaptation to changes in load. Simulation and implementation tests confirm this stability, and indicate that overall performances of HRED are substantially better than those of earlier AQM algorithms. Finally, HRED control parameters provide several intuitive approaches to trading between required memory, queue stability, and response time.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.1
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• pp.29-35
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• 2003

In this paper, we propose an improved image decryption system using a phase-encoded image and the principle of interference. An original image and a random image consist of only binary values. The phase-encoded original image is encrypted into a binary phase-only image by multiplying with a phase-encoded random key. Therefore the phase-encoded images have two phase values 0 or $\pi$. The proposed decryption technique is simply performed by interfering between a reference wave and a direct pixel-to-pixel mapping of the encrypted image with a decrypting key. Optical experiments confirmed that the proposed technique is a simple and robust architecture for optical encryption.

• Journal of Environmental Impact Assessment
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• v.33 no.2
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• pp.53-63
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• 2024

Biodiversity holds significant importance within the framework of environmental impact assessment, being utilized in site selection for development, understanding the surrounding environment, and assessing the impact on species due to disturbances. The field of environmental impact assessment has seen substantial research exploring new technologies and models to evaluate and predict biodiversity more accurately. While current assessments rely on data from fieldwork and literature surveys to gauge species richness indices, limitations in spatial and temporal coverage underscore the need for high-resolution biodiversity assessments through species richness mapping. In this study, leveraging data from the 4th National Ecosystem Survey and environmental variables, we developed a species distribution model using Random Forest. This model yielded mapping results of 24 mammalian species' distribution, utilizing the species richness index to generate a 100-meter resolution map of species richness. The research findings exhibited a notably high predictive accuracy, with the species distribution model demonstrating an average AUC value of 0.82. In addition, the comparison with National Ecosystem Survey data reveals that the species richness distribution in the high-resolution species richness mapping results conforms to a normal distribution. Hence, it stands as highly reliable foundational data for environmental impact assessment. Such research and analytical outcomes could serve as pivotal new reference materials for future urban development projects, offering insights for biodiversity assessment and habitat preservation endeavors.

• The Journal of Engineering Geology
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• v.34 no.1
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• pp.51-65
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• 2024

Landslides are natural disasters that causes significant property damage worldwide every year. In Korea, damage due to landslides is increasing owing to the effects of climate change, and it is important to identify the factors that increase the prevalence of landslides in order to reduce the damage they cause. Therefore, this study used a random forest model to analyze the importance of 14 factors in influencing landslide damage in a specific area of Chungju, Chungcheongbuk-do province, Korea. The random forest model performed accurately with an AUC of 0.87 and the most-important factors were ranked in the order of aspect, slope, distance to valley, and elevation, suggesting that topographic factors such as aspect and slope more greatly influence landslide damage than geological or soil factors such as rock type and soil thickness. The results of this study are expected to provide a basis for mapping and predicting landslide damage, and for research focused on reducing landslide damage.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.391-399
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• 2012

This paper proposes a particle filter approach for SLAM(Simultaneous Localization and Mapping) of a mobile robot. The SLAM denotes estimation of both the robot location and map while the robot navigates in an unknown environment without map. The proposed method estimates robot location simultaneously with the locations of the ultrasonic beacons which constitute landmarks for navigation. The particle filter method represents the locations of the robot and landmarks in probabilistic manner by the distribution of particles. The method takes care of the uncertainty of the landmarks' location as well as that of the robot motion. Therefore, the locations of the landmarks are updated including uncertainty at every sampling time. Performance of the proposed method is verified through simulation and experiments. The method yields practically useful mapping information even if the range data from the landmarks include random noise. Also, it provides more accurate and robust estimation of the robot location than the usual least squares methods or dead-reckoning method.

• Smart Structures and Systems
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• v.30 no.6
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• pp.687-701
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• 2022

Inevitable response loss under complex operational conditions significantly affects the integrity and quality of measured data, leading the structural health monitoring (SHM) ineffective. To remedy the impact of data loss, a common way is to transfer the recorded response of available measure point to where the data loss occurred by establishing the response mapping from measured data. However, the current research has yet addressed the structural condition changes afterward and response mapping learning from a small sample. So, this paper proposes a novel data driven structural response reconstruction method based on a sophisticated designed generating adversarial network (UAGAN). Advanced deep learning techniques including U-shaped dense blocks, self-attention and a customized loss function are specialized and embedded in UAGAN to improve the universal and representative features extraction and generalized responses mapping establishment. In numerical validation, UAGAN efficiently and accurately captures the distinguished features of structural response from only 40 training samples of the intact structure. Besides, the established response mapping is universal, which effectively reconstructs responses of the structure suffered up to 10% random stiffness reduction or structural damage. In the experimental validation, UAGAN is trained with ambient response and applied to reconstruct response measured under earthquake. The reconstruction losses of response in the time and frequency domains reached 16% and 17%, that is better than the previous research, demonstrating the leading performance of the sophisticated designed network. In addition, the identified modal parameters from reconstructed and the corresponding true responses are highly consistent indicates that the proposed UAGAN is very potential to be applied to practical civil engineering.