• 한국가시화정보학회:학술대회논문집
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• 2002.11a
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• pp.101-104
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• 2002

Simultaneous measurement of turbulent velocity and concentration field in a stirred mixer tank is carried out by using PIV/LIF technique. Instantaneous velocity fields are measured by a $1K\times1K$ CCD camera adopting the frame straddle method while the concentration fields are obtained by measuring the fluorescence intensity of Rhodamine B tracer excited by the second pulse of Nd:Yag laser light. Image distortion due to the camera view-angle is compensated by a mapping function. It is found that the general features of the mixing pattern are quite dependent on the local flow characteristics during the rapid decay of mean concentration. However, the small scale mixing seems to be independent on the local turbulent velocity fluctuation.

• The Korean Journal of Nuclear Medicine
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• v.37 no.1
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• pp.63-72
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• 2003

Functional MRI (fMRI) provides an indirect mapping of cerebral activity, based on the detection of the local blood flow and oxygenation changes following neuronal activity (Blood Oxygenation Level Dependent). fMRI allows us to study noninvasively the normal and pathological aspects of functional cortical organization. Each fMRI study compares two different states of activity. Echo-Planar Imaging is the technique that makes it possible to study the whole brain at a rapid pace. Activation maps are calculated from a statistical analysis of the local signal changes. fMRI is now becoming an essential tool in the neurofunctional evaluation of normal volunteers and many neurological patients as well as the reference method to image normal or pathologic functional brain organization.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1331-1346
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• 2018

Aiming at the problem that the gradient-based edge detection operators are sensitive to the noise, causing the pseudo edges, a triqubit-state measurement-based edge detection algorithm is presented in this paper. Combing the image local and global structure information, the triqubit superposition states are used to represent the pixel features, so as to locate the image edge. Our algorithm consists of three steps. Firstly, the improved partial differential method is used to smooth the defect image. Secondly, the triqubit-state is characterized by three elements of the pixel saliency, edge statistical characteristics and gray scale contrast to achieve the defect image from the gray space to the quantum space mapping. Thirdly, the edge image is outputted according to the quantum measurement, local gradient maximization and neighborhood chain code searching. Compared with other methods, the simulation experiments indicate that our algorithm has less pseudo edges and higher edge detection accuracy.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.63-66
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• 2018

Recently, a convolutional neural network (CNN) models at single image super-resolution have been very successful. Residual learning improves training stability and network performance in CNN. In this paper, we compare four convolutional neural network models for super-resolution (SR) to learn nonlinear mapping from low-resolution (LR) input image to high-resolution (HR) target image. Four models include general CNN model, global residual learning CNN model, local residual learning CNN model, and the CNN model with global and local residual learning. Experiment results show that the results are greatly affected by how skip connections are connected at the basic CNN network, and network trained with only global residual learning generates highest performance among four models at objective and subjective evaluations.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.56-76
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• 2022

This study shared with community mapping participants spatial analysis information, collected using smart devices, to give them an opportunity to objectively review their opinions. The study examined the impact of sharing such spatial information on residents' decision-making and perceptions. Yeongju-dong in Jung-gu district of Busan Metropolitan City, South Korea was selected for the case study; community mapping was carried out in Yeongju-dong to identify hazardous areas to improve pedestrian safety of primary school students. The community mapping participants drew a preliminary hazard map based on their experience and perception. Then, they drew a second hazard map after being given spatial information on pedestrian safety installations and pedestrian flow collected with smart devices including drones and sensors. Numerous changes in ranking across various sections occurred when the two maps were compared. There was a climb in the ranking of areas where the pedestrian flow was higher and lacked safety installations based on objective measurements over the perceptions of the participating people. Furthermore, according to a survey conducted among the participants, the provision of spatial analysis information using smart devices during community mapping process not only helped them recognize local community problems, but also raised their expectations that their submitted opinions would be reflected in policies. Moreover, the participants demonstrated increased self-confidence and faith in themselves as they were able to have more trust in the outcome they created.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.99-99
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• 2017

Chili pepper (Capsicum annum) is origin of subtropical region, and has been spread all over the world. It is increasing the production and consumption in recent year. Chili peppers are readily incorporated into local South Asian cuisines perhaps because people are already familiar with pungent and spicy flavors. Chili peppers, despite their fiery "hotness", are one of very popular spices known for their medicinal and health benefiting properties. Especially in South East Asia, they grow up so many cultivars of them recently, so it is so important crop world wide. In South East Asia, there are some articles about chili pepper in Thailand and Indonesia, but in Vietnam there is not so much information about chili pepper. In this paper, we analyzed genetic diversity in Vietnamese Chili pepper through the survey of local chili pepper. As a result, we got 38 kinds of chili fruits, 26 kinds of leaves and some information from farmers all in Vietnam. And I made the phylogenetic tree by SSR with 10 DNA markers. Finally we found the genetic similarities by regions.

• Structural Engineering and Mechanics
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• v.41 no.4
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• pp.559-573
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• 2012

An adaptive modeling and simulation technique is introduced for the effective and reliable fluid-structure interaction analysis using MSC/Dytran for large-scale complex pressurized liquid containment. The proposed method is composed of a series of the global rigid sloshing analysis and the locally detailed fluid-structure analysis. The critical time at which the system exhibits the severe liquid sloshing response is sought through the former analysis, while the fluid-structure interaction in the local region of interest at the critical time is analyzed by the latter analysis. Differing from the global coarse model, the local fine model considers not only the complex geometry and flexibility of structure but the effect of internal pressure. The locally detailed FSI problem is solved in terms of multi-material volume fractions and the flow and pressure fields obtained by the global analysis at the critical time are specified as the initial conditions. An in-house program for mapping the global analysis results onto the fine-scale local FSI model is developed. The validity and effectiveness of the proposed method are verified through an illustrative numerical experiment.

• Nuclear Engineering and Technology
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• v.50 no.1
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• pp.203-210
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• 2018

As the modernization of the nuclear instrumentation system progresses, research reactors have adopted digital wide-range neutron power measurement (DWRNPM) systems. These systems typically monitor the neutron flux across a range of over 10 decades. Because neutron detectors only measure the local neutron flux at their position, the local neutron flux must be converted to total reactor power through calibration, which involves mapping the local neutron flux level to a reference reactor power. Conventionally, the neutron power range is divided into smaller subranges because the neutron detector signal characteristics and the reference reactor power estimation methods are different for each subrange. Therefore, many factors should be considered when preparing the calibration procedure for DWRNPM channels. The main purpose of this work is to serve as a reference for performing the calibration of DWRNPM systems in research reactors. This work provides a comprehensive overview of the calibration of DWRNPM channels by describing the configuration of the DWRNPM system and by summarizing the theories of operation and the reference power estimation methods with their associated calibration procedure. The calibration procedure was actually performed during the commissioning of an open-pool type research reactor, and the results and experience are documented herein.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.995-1005
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• 2011

An efficient outdoor local localization method is suggested using multi-sensor fusion with MU-EKF (Multi-Update Extended Kalman Filter) for car-like mobile robots. In outdoor environments, where mobile robots are used for explorations or military services, accurate localization with multiple sensors is indispensable. In this paper, multi-sensor fusion outdoor local localization algorithm is proposed, which fuses sensor data from LRF (Laser Range Finder), Encoder, and GPS. First, encoder data is used for the prediction stage of MU-EKF. Then the LRF data obtained by scanning the environment is used to extract objects, and estimates the robot position and orientation by mapping with map objects, as the first update stage of MU-EKF. This estimation is finally fused with GPS as the second update stage of MU-EKF. This MU-EKF algorithm can also fuse more than three sensor data efficiently even with different sensor data sampling periods, and ensures high accuracy in localization. The validity of the proposed algorithm is revealed via experiments.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.4
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• pp.239-247
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• 2008

In a resource-limited wireless communication environment, various approaches to meet the ever growing application requirements in an efficient and transparent manner, are being researched and developed. Amongst many approaches, cross layer technique is by far one of the significant contributions that has undoubtedly revolutionized the way conventional layered architecture is perceived. In this paper, we propose a Universal Cross Layer Framework based on vertical layer architecture. The primary contribution of this paper is the functional architecture of the vertical layer which is primarily responsible for cross layer interaction management and optimization. The second contribution is the use of optimization cycle that comprises awareness parameters collection, mapping, classification and the analysis phases. The third contribution of the paper is the decomposition of the parameters into local and global network perspective for opportunistic optimization. Finally, we have shown through simulations how parameters' variations can represent local and global views of the network and how we can set local and global thresholds to perform opportunistic optimization.