• Structural Engineering and Mechanics
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• v.19 no.2
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• pp.123-139
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• 2005

An automatic modal identification program is developed for continuous extraction of modal parameters of three cable-supported bridges in Hong Kong which are instrumented with a long-term monitoring system. The program employs the Complex Modal Indication Function (CMIF) algorithm for identifying modal properties from continuous ambient vibration measurements in an on-line manner. By using the LabVIEW graphical programming language, the software realizes the algorithm in Virtual Instrument (VI) style. The applicability and implementation issues of the developed software are demonstrated by using one-year measurement data acquired from 67 channels of accelerometers permanently installed on the cable-stayed Ting Kau Bridge. With the continuously identified results, variability in modal vectors due to varying environmental conditions and measurement errors is observed. Such an observation is very helpful for selection of appropriate measured modal vectors for structural health monitoring use.

• Spatial Information Research
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• v.22 no.2
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• pp.63-71
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• 2014

Ocean leisure sports have recently emerged as one of so-called blue ocean industries. They are sensitive to diverse environmental conditions such as current, temperature, and salinity, which can increase needs of forecasting data as well as in-situ observations for the ocean. In this context, a Web-based geovisualization system for coastal information produced by model forecasts was implemented for use in supporting various ocean activities. First, FVCOM(Finite Volume Coastal Ocean Model) was selected as a forecasting model, and its data was preprocessed by a spatial interpolation and sampling library. The interpolated raster data for water surface elevation, temperature, and salinity were stored in image files, and the vector data for currents including speed and direction were imported into a distributed DBMS(Database Management System). Web services in REST(Representational State Transfer) API(Application Programming Interface) were composed using Spring Framework and integrated with desktop and mobile applications developed on the basis of hybrid structure, which can realize a cross-platform environment for geovisualization.

• Spatial Information Research
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• v.18 no.4
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• pp.141-149
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• 2010

One of recent trends in Web-based GIS is the system development using FOSS (Free and Open Source Software). Open Source software is independent from the technologies of commercial software and can increase the reusability and extensibility of existing systems. In this study, we developed a Web-based GIS for interactive visualization of geographic information using Google Earth and spatial DBMS(database management system). Google Earth Plug-in and Google Earth API(application programming interface) were used to embed a geo-browser in the Web browser. In order to integrate the Google Earth with a spatial DBMS, we implemented a KML(Keyhole Markup Language) generator for transmitting server-side data according to user's query and converting the data to a variety of KML for geovisualization on the Web. Our prototype system was tested using time-series of LAI(leaf area index), forest map, and crop yield statistics. The demonstration included the geovisualization of raster and vector data in the form of an animated map and a 3-D choropleth map. We anticipate our KML generator and system framework will be extended to a more comprehensive geospatial analysis system on the Web.

• The Journal of the Acoustical Society of Korea
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• v.19 no.5
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• pp.3-8
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• 2000

In this paper, we studied design and implementation of a robust speech recognition system in noisy car environment. The reference pattern used in the system is DMS(Dynamic Multi-Section). Two separate acoustic models, which are selected automatically depending on the noisy car environment for the speech in a car moving at below 80km/h and over 80km/h are proposed. PLP(Perceptual Linear Predictive) of order 13 is used for the feature vector and OSDP (One-Stage Dynamic Programming) is used for decoding. The system also has the function of editing the phone-book for voice dialing. The system yields a recognition rate of 89.75% for male speakers in SI (speaker independent) mode in a car running on a cemented express way at over 80km/h with a vocabulary of 33 words. The system also yields a recognition rate of 92.29% for male speakers in SI mode in a car running on a paved express way at over 80km/h.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.9
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• pp.373-378
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• 2019

Since many programming sources are open online, problems with reckless plagiarism and copyrights are occurring. Among them, source codes produced by repeated authors may have unique fingerprints due to their programming characteristics. This paper identifies each author by learning from a Google Code Jam program source using deep neural network. In this case, the original creator's source is to be vectored using a pre-processing instrument such as predictive-based vector or frequency-based approach, TF-IDF, etc. and to identify the original program source by learning by using a deep neural network. In addition a language-independent learning system was constructed using a pre-processing machine and compared with other existing learning methods. Among them, models using TF-IDF and in-depth neural networks were found to perform better than those using other pre-processing or other learning methods.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.1
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• pp.63-69
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• 2015

In this paper, infrared reflector design targeting infrared stealth effect is presented using structural optimization based on the phase field method. The analysis model was determined to accomplish the design that an incident infrared wave was reflected to a desired direction. The design process was to maximize the objective value at the measuring domain located in a target region and the design objective was set to the Poynting vector value which represents the energy flux. Optimization results were obtained according to the variation of some parameter values related to the phase field method. The model with a maximum objective value was selected as the final optimal model. The optimal model was modified to eliminate the gray scale using the cut-off method and it confirmed improved performance. In addition, to check the desired effect in the middle wave infrared range(MWIR), the analysis was performed by changing the input wavelength. The finite element analysis and optimization process were performed by using the commercial package COMSOL combined with the Matlab programming.

• Journal of KIISE:Software and Applications
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• v.29 no.10
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• pp.684-693
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• 2002

Electronic Ink is a stored data in the form of the handwritten text or the script without converting it into ASCII by handwritten recognition on the pen-based computers and Personal Digital Assistants(PDAs) for supporting natural and convenient data input. One of the most Important issue is to search the electronic ink in order to use it. We proposed and implemented a script matching algorithm for the electronic ink. Proposed matching algorithm separated the input stroke into a set of primitive stroke using the curvature of the stroke curve. After determining the type of separated strokes, it produced a stroke feature vector. And then it calculated the distance between the stroke feature vector of input strokes and one of strokes in the database using the dynamic programming technique. We did various experiments and our algorithm showed high matching rate over 97.7% for only the Korean script and 94% for the data mixed Korean with the Chinese character.

• Journal of the Korea Society of Computer and Information
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• v.17 no.3
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• pp.67-76
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• 2012

Traffic classification plays an important role in traffic management. To traditional methods, P2P and encryption traffic may become a problem. Support Vector Machine (SVM) is a useful classification tool which is able to overcome the traditional bottleneck. The main disadvantage of SVM algorithms is that it's time-consuming to train large data set because of the quadratic programming (QP) problem. However, the useful support vectors are only a small part of the whole data. If we can discard the useless vectors before training, we are able to save time and keep accuracy. In this article, we discussed the feasibility to remove the useless vectors through a sequential method to accelerate training speed when dealing with large scale data.

• Journal of the Korea Computer Graphics Society
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• v.21 no.5
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• pp.21-27
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• 2015

In this paper, we presents visual effect(water, fire, smoke) simulation and interaction system for TV virtual studio. TV virtual studio seamlessly synthesizes CG background and a live performer standing on a TV green studio. Previous virtual studios focus on the registration of CG background and a performer in real world. In contrast to the previous systems, we can afford to make new types of TV scenes more easily by simulating interactive visual effects according to a performer. This requires the extraction of the performer motion to be transformed 3D vector field and simulate fluids by applying the vector field to Navier Stokes equation. To add realism to water VFX simulation and interaction, we also simulate the dynamic behavior of splashing fluids on the water surface. To provide real-time recording of TV programs, real-time VFX simulation and interaction is presented through a GPU programming. Experimental results show this system can be used practically for realizing water, fire, smoke VFX simulation and the dynamic behavior simulation of fish flocks inside ocean.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2106-2117
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• 2017

An effective statistical feature extraction approach of data sampling of fault in the combined transmission system is presented in this paper. The proposed algorithm leads to high accuracy at minimum cost to predict fault location and fault type classification. This algorithm requires impedance measurement data from one end of the transmission line. Modal decomposition is used to extract positive sequence impedance. Then, the fault signal is decomposed by using discrete wavelet transform. Statistical sampling is used to extract appropriate fault features as benchmark of decomposed signal to train classifier. Support Vector Machine (SVM) is used to illustrate the performance of statistical sampling performance. The overall time of sampling is not exceeding 1 1/4 cycles, taking into account the interval time. The proposed method takes two steps of sampling. The first step takes 3/4 cycle of during-fault and the second step takes 1/4 cycle of post fault impedance. The interval time between the two steps is assumed to be 1/4 cycle. Extensive studies using MATLAB software show accurate fault location estimation and fault type classification of the proposed method. The classifier result is presented and compared with well-established travelling wave methods and the performance of the algorithms are analyzed and discussed.