• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.277-287
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• 2003

Acetolactate synthase (ALS, EC 4.1.3.18; also referred to as acetohydroxy acid synthase) catalyzes the first common step in the biosynthesis of valine, leucine, and isoleucine in microorganisms and plants. Recently X-ray structure of yeast ALS was available. Pair-wise alignment of yeast and tobacco ALS sequences revealed 63% sequence similarity. Using Deep View and automatic modeling on Swiss model server, we have generated reliable models of tobacco ALS based on yeast ALS template with a calculated pair-wise RMSD of 0.86 Angstrom. Functional roles of four residues located on the subunit interface (H142, El43, M350, and R376) were examined by site-directed mutagenesis. Seven mutants were generated and purified, of which three mutants (H142T, M350V, and R376F) were found to be inactivated under various assay conditions. The H142k mutant showed moderately altered kinetic properties. The E143A mutant increased 10-fold in K$_m$ value while other parameters remained unchanged. The M350C mutant was strongly resistant to three tested herbicides, while the R376k mutant can bind with herbicide carder at similar affinity to that of wild type enzyme, as determined by tryptophan quenching study. Except M350V mutant, all other mutants were ate to bind with cofactor FAD. Taken together, it is likely that residues H142 and E143 are located at the active site, while residues M350 and R376 are possibly located at the overlapping region of active site and herbicide binding site of the enzyme. Our data also allows us to hypothesize that the interaction between side chains of residues M350 and R376 are probably essential for the correct conformation of the active site. It remains to be elucidated that, whether the herbicide, upon binding with enzyme, inactivates the enzyme by causing change in the active site allosterically, which is unfavorable for catalytic activity.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1285-1293
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• 2010

This study suggests the design and implementation of an e-mentoring system, which creates more than one role models to help adult learners of cyber university to improve their academic performance and to successfully complete their education. The benefits of this system are as following; First, automatic matching system is built in consideration of mutual requests between mentor and mentee. And the system enforces all participants to actively participate in the program by sharing ideas and to improve their academic performance with specific academic goals. Second, participants are rewarded at the end of the program for their performance by an evaluation system developed for assessing role models and participants' activities. Also, the system encourages best mentors to remain in the program and help adult learners to improve academic performance.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.481-492
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• 2007

In this paper, a method for automatic indexing of contents to reduce effort for inputting paper information and constructing index is considered. Existing document analysis methods can't analyse various table of contents of journal paper formats efficiently because they have many exceptions. In this paper, various contents formats for journals, which have different features from those for general documents, are analysed and described. The principal elements that we want to represent are titles, authors, and pages for each papers. Thus, the three principal elements are modeled according to the order of their arrangement, and their features are extracted. And a table of content recognition system of journal is implemented, based on the proposed modeling method. The accuracy of exact extraction ratio of 91.5% on title, author, and page type on 660 published papers of various journals is obtained.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.3
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• pp.773-784
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• 2014

This study evaluated the applicability of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP) rainfall generation model for modeling extreme rainfalls and floods in Korean Peninsula. Firstly, using the ISPSO (Isolated Species Particle Swarm Optimization) method, the parameters of the MBLRP model were estimated at the 61 ASOS (Automatic Surface Observation System) rain gauges located across Korean Peninsula. Then, the synthetic rainfall time series with the length of 100 years were generated using the MBLRP model for each of the rain gauges. Finally, design rainfalls and design floods with various recurrence intervals were estimated based on the generated synthetic rainfall time series, which were compared to the values based on the observed rainfall time series. The results of the comparison indicate that the design rainfalls based on the synthetic rainfall time series were smaller than the ones based on the observation by 20% to 42%. The amount of underestimation increased with the increase of return period. In case of the design floods, the degree of underestimation was 31% to 50%, which increases along with the return period of flood and the curve number of basin.

• Journal of the Korea Concrete Institute
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• v.21 no.5
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• pp.599-609
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• 2009

This paper discusses generalized modeling schemes for both reinforced concrete (RC) and post-tensioned (PT) flat plate buildings. In this modeling approach, nonlinear behavior due to slab flexure, moment and shear transfer at slab-column connections, and punching shear was included along with linear secant stiffness of each member or connection that accounts for concrete cracking. This generalized model was capable of simulating all different scenarios of slab-column connection failures such as brittle punching, flexure-shear interactive failure, and flexural failure followed by drift-induced punching. Furthermore, automatic detection of drift-induced punching shear and subsequent backbone curve modifications were realistically modelled by incorporating the limit state model, in which gravity shear versus drift capacity relations were adopted. The validation of the model was conducted using one-third scale two-story by two-bay RC and PT flat plate frames. The comparisons revealed that the model was robust and effective.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.4
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• pp.359-365
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• 2008

This paper focused on generation of more accurate DEM and analysis of accuracy. For this, we applied suitable sensor modeling technique for each satellite image and automatic pyramid matching using image pyramid was applied. Matching algorithm based on epipolarity and scene geometry also was applied for stereo matching. IKONOS, Quickbird, SPOT-5, Kompsat-2 were used for experiments. In particular, we applied orbit-attitude sensor modeling technique for Kompsat-2 and performed DEM generation successfully. All DEM generated show good quality. Assessment was carried out using USGS DTED and we also compared between DEM generated in this research and DEM generated from common software. All DEM had $9m{\sim}12m$ Mean Absolute Error and $13m{\sim}16m$ RMS Error. Experimental results show that the DEMs of good performance which is similar to or better than result of DEMs generated from common software.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.2
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• pp.239-245
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• 2020

Recently, BIM (Building Information Modeling) are widely being utilized in Construction industry. However, most structures that have been constructed in the past do not have BIM. For structures without BIM, the use of SfM (Structure from Motion) techniques in the 2D image obtained from the camera allows the generation of 3D model point cloud data and BIM to be established. However, since these generated point cloud data do not contain semantic information, it is necessary to manually classify what elements of the structure. Therefore, in this study, deep learning was applied to automate the process of classifying structural components. In the establishment of deep learning network, Inception-ResNet-v2 of CNN (Convolutional Neural Network) structure was used, and the components of bridge structure were learned through transfer learning. As a result of classifying components using the data collected to verify the developed system, the components of the bridge were classified with an accuracy of 96.13 %.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.9
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• pp.731-738
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• 2014

The mission of UAV has been expanded from a land to an ocean based on an enhancement of its technologies. Korea Aerospace Research Institute (KARI) also tries to expand the mission of tilt rotor UAV to an ocean, in which the shipboard landing of UAV is required. However the environment of an oceanic operation is severer than that of land due to salty, fogy, and windy condition. The landing point for automatic landing is not fixed due to movement of shipboard in roll, pitch, and heave. It makes the oceanic operation and landing of UAV difficult. In order to conduct an oceanic operation of tilt rotor UAV, this paper presents that the sea wave modeling according to the sea state is conducted and the shipboard landing of tilt rotor UAV under the sea wave is tested and evaluated through the flight simulator for UAV.

• Journal of the Korea Safety Management & Science
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• v.9 no.6
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• pp.123-135
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• 2007

In the recent years, the companies have manually recorded a production status in a work diary or have mainly used a bar code in order to collect each process's progress status, production performance and quality information in the production and logistics process in real time. But, it requires an additional work because the worker's record must be daily checked or the worker must read it with the bar code scanner. At this time, data's accuracy is decreased owing to the worker's intention or mistake, and it causes the problem of the system's reliability. Accordingly, in order to solve such problem, the companies have introduced RFID which comes into the spotlight in the latest automatic identification field. In order to introduce the RFID technology, the process flow must be analyzed, but the ASME sign used by most manufacturing companies has the difficult problem when the aggregation event occurs. Hence, in this study, the RFID logistic flow analysis Modeling Notation was proposed as the signature which can analyze the manufacturing logistic flow amicably, and the manufacturing logistic flow by industry type was analyzed by using the proposed RFID logistic flow analysis signature. Also, to monitor real-time information through EPCglobal network, EPCISEvent template by industry was proposed, and it was utilized as the benchmarking case of companies for RFID introduction. This study suggested to ensure the decision-making on real-time information through EPCglobal network. This study is intended to suggest the Modeling Notation suitable for RFID characteristics, and the study is intended to establish the business step and to present the vocabulary.

• Journal of KIISE:Software and Applications
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• v.28 no.9
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• pp.649-661
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• 2001

While the conventional edge detection can be considered as the problem of determining the existence of edges at certain locations, the fuzzy edge modeling can be considered as the problem of determining the membership values of edges. Thus, if the location of an edge is unclear, or if the intensity function is different from the ideal edge model, the degree of edgeness at the location is represented as a fuzzy membership value. Using the concept of fuzzy edgeness, an automatic smoothing parameter evaluation and selection method for a conventional edge detector is proposed. This evaluation method uses the fuzzy edge modeling, and can analyze the effect of smoothing parameter to determine an optimal parameter for a given image. By using the selected parameter we can detect least ambiguous edges of a detection method for an image. The effectiveness of the parameter evaluation method is analyzed and demonstrated using a set of synthetic and real images.