• Proceedings of the Korea Society for Industrial Systems Conference
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• 2003.11a
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• pp.721-727
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• 2003

This study designed and implemented a system to extract of vowel from a word. The system is comprised of a voice feature extraction module and a neutral network module. The voice feature extraction module use a LPC(Linear Prediction Coefficient) model to extract a voice feature from a word. The neutral network module is comprised of a learning module and voice recognition module. The learning module sets up a learning pattern and builds up a neutral network to learn. Using the information of a learned neutral network, a voice recognition module extracts a vowel from a word. A neutral network was made to learn selected vowels(a, eo, o, e, i) to test the performance of a implemented vowel extraction recognition machine. Through this experiment, could confirm that speech recognition module extract of vowel from 4 words.

• Journal of Environmental Health Sciences
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• v.27 no.3
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• pp.107-112
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• 2001

This work reports the application of a hollow fiber module(HFM) for Cr(VI) extraction from heavy metal salts mixed solution by using microporous hydrophobic hollow fiber module. In HFM configuration, the organic extraction used for the extraction of Cr(VI) was di-(2-ethyl hexyl) phosphoric acid(D2EHPA) diluted with n-heptane. The study of HFM includes the influence of hydrodynamic and chemical condition, i.e., the flow rate of feed solution, the time of reactive extraction, the concentration of feed solution, and the pH of aqueous phase solutions. Several experiments with synthetic solution of different mixed components system of Cr(VI) solutions established optimum condition to achieve a clean separation of Cr(VI). It was possible to separate Cr(VI) in the presence of metal salts mixed solution, such as Zn(II), Ni(II), Cu(II), and Cd(II) using the HFM technique.

• Journal of KIBIM
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• v.9 no.3
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• pp.30-40
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• 2019

Extraction of fabrication documents is very important because it provides information related to tasks of fabrication and construction. Therefore, in the case of a prefabricated member such as a steel structure, it is necessary to improve the productivity of fabrication documents through 3D BIM. However, research and evidence data on direct comparison analysis of 3D BIM-based documents extraction versus 2D CAD-based documents extraction are hard to find. Thus, this study focuses on productivity analysis of 3D BIM based fabrication documents extraction. In this study, the productivity data of fabrication documents extraction for module construction of EPC project was analyzed. For the productivity analysis, a case study on the fabrication documents of Module A (1,965 sheets) and Module B (1,216 sheets) was conducted. Fabrication documents for each module include general arrangement drawing, assembly drawing, single part drawing and single plate drawing. Comparison of 2D CAD based fabrication documents extraction and 3D BIM based fabrication documents extraction, the productivity for the entire work was improved from 17 hours to 16 hours for Module A and 12 hours to 7 hours for Module B. Especially, the productivity of the assembly drawings, which occupies a large part of the fabrication documents, was improved by about 48.75% from the total time required from 281 hours to 144 hours.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.43-49
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• 2016

This paper presents the design and implementation of virtual aquarium by generating 3D models of fishes that are colored by viewers in an aim to create interaction among viewers and aquarium. The virtual aquarium system is composed of multiple texture extraction modules, a single interface module and a single display module. The texture extraction module recognize the QR code on the canvas to get information of the predefined mapping table and then extract the texture data for the corresponding 3D model. The scanned image is segmented and warp transformed onto the texture image by using the mapping information. The extracted texture is transferred to the interface module to save on the server computer and the interface module sends the fish code and texture information to the display module. The display module generates a fish on the virtual aquarium by using predefined 3D model with the transmitted texture. The fishes on the virtual aquarium have three different swimming methods: self-swimming, autonomous swimming, and leader-following swimming. The three different swimming methods are discussed in this paper. The future study will be the implementation of virtual aquarium based on storytelling to further increase interactions with the viewer.

• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.710-721
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• 1999

In this paper, we have designed and implemented a parameter extraction system for analyzing Internet using SNMP. The extraction system has two modules; one is collection request module, and the other is analysis request module. The collection request module generates a polling script, which is used to collect management information from the managed system periodically. With this collected data, analysis request module extracts analysis parameters. These parameters are traffic flow analysis, interface traffic analysis, packet traffic analysis, and management traffic analysis parameter. For management activity, we have introduced two-step-analysis-view. One is Summary-View, which is used find out malfunction of a system among the entire managed systems. The Other is Specific-View. With this view we can analyze the specific system with all our analysis parameters. To show available data as indicators for line capacity planning, network redesigning decision making of performance upgrade for a network device and things like that.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2073-2078
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• 2007

This study was performed to develop a dryer for home clothes using thermoelectric module. The thermoelectric module was used as a heat source and a dehumidification device because it has heating part and cooling part at once. To design for maximizing the energy efficiency and the rate of dehumidification, the parameters of the dryer using thermoelectric module are heat capacity and air flow rate. This study showed that the thermoelectric module can be used in the clothes dryer and energy efficiency of clothes dryer be better than that of electric heating dryer.

• Journal of the Regional Association of Architectural Institute of Korea
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• v.20 no.6
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• pp.81-87
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• 2018

In this paper, in order to maximize the input process efficiency of the building energy simulation field, the authors developed the automatic extraction module of spatial information based BIM geometry information. Existing research or software extracts geometry information based on object information, but it can not be used in the field of energy simulation because it is inconsistent with the geometry information of the object constituting the thermal zone of the actual building model. Especially, IFC-based geometry information extraction module is needed to link with other architectural fields from the viewpoint of reuse of building information. The study method is as follows. (1) Grasp the category and attribute information to be extracted for energy simulation and Analyze the IFC structure based on spatial information (2) Design the algorithm for extracting and reprocessing information for energy simulation from IFC file (use programming language Phython) (3) Develop the module that generates a geometry information database based on spatial information using reprocessed information (4) Verify the accuracy of the development module. In this paper, the reprocessed information can be directly used for energy simulation and it can be widely used regardless of the kind of energy simulation software because it is provided in database format. Therefore, it is expected that the energy simulation process efficiency in actual practice can be maximized.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.6
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• pp.309-317
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• 2022

In this paper, we propose a machine learning-based copy-move forgery detection network with dual branches. Because the rotation or scaling operation is frequently involved in copy-move forger, the conventional convolutional neural network is not effectively applied in detecting copy-move tampering. Therefore, we divide the input into rotation-invariant and scaling-invariant features based on the wavelet coefficients. Each of the features is input to different branches having the same structure, and is fused in the combination module. Each branch comprises feature extraction, correlation, and mask decoder modules. In the proposed network, VGG16 is used for the feature extraction module. To check similarity of features generated by the feature extraction module, the conventional correlation module used. Finally, the mask decoder model is applied to develop a pixel-level localization map. We perform experiments on test dataset and compare the proposed method with state-of-the-art tampering localization methods. The results demonstrate that the proposed scheme outperforms the existing approaches.

• Journal of Creative Information Culture
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• v.5 no.2
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• pp.145-156
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• 2019

In this study, we have developed and evaluated an information extracting module based on the named entity recognition technique. For the given purpose in this paper, the module was designed to apply to the problem dealing with extraction of postal address information from arbitrary documents without any prior knowledge on the document layout. From the perspective of information technique practice, our approach can be said as a probabilistic n-gram (bi- or tri-gram) method which is a generalized technique compared with a uni-gram based keyword matching. It is the main difference between our approach and the conventional methods adopted in natural language processing that applying sentence detection, tokenization, and POS tagging recursively rather than applying the models sequentially. The test results with approximately two thousands documents are presented at this paper.

• Journal of Korea Multimedia Society
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• v.18 no.10
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• pp.1172-1179
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• 2015

A wireless license plate region extracting module is proposed for LPR system controlling multiple gates. This module is cheaply implemented using Raspberry Pi which is open source and high performance. First, as the upper 1/3 of the captured image is discarded as it has no useful information on license plate. Using the OpenCV libraries the edge image is got by Canny algorithm after applying Gaussian filtering to gray image, and the labeling is conducted for 4 consecutive numbers in license plate. These numbers are located using various decision equations, and expanding the numbers region the final license plate region can be extracted. The result image is transferred to Server using wifi direct. Using the proposed module it becomes easy to set up and maintain the LPR system. The experimental results showed that the successful extracting rate was 98.4% using 500 car images with 640 × 480 resolution.