• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.95-104
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• 2004

This paper proposes an efficient remote video evaluation system that is matched well with personalized characteristics of students using information filtering based on user profile. For making a question in forms of video, a key frame extraction method based on coordinate, size and color information is proposed. And Question-mating intervals are extracted using gray-level histogram difference and time window. Also, question-making method that combined category-based system with keyword-based system is used for efficient evaluation. Therefore, students can enhance their study achievement through both supplementing their inferior area and preserving their interest area.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.5
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• pp.81-90
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• 2007

Watershed topographical information is required in hydrologic analysis, supporting efficient hydrologic model operation and managing water resources. Watershed topographical data extraction systems based on desktop GIS are abundant these days placing burdens for spatial data processing on users. This paper describes development of a Web-based Geographic Information Systems that can delineate the Geum River sub-basins and extract watershed topographical data in real time. Through this system, users can obtain a watershed boundary by selecting outlet location and then extracting topographical data including watershed area, boundary length, average altitude, slope distribution about the elevation range with Web browsers. Moreover, the system provides watershed hydrological data including land use, soil types, soil drainage conditions, and NRCS(Natural Resources Conservation Service) curve number for hydrologic model operation through grid overlay technique. The system operability was evaluated with the hydrological data of WAMIS(Water Management Information System) with the government operation Web site as reference data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5130-5143
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• 2019

Football (soccer) is one of the most popular sports in the world. A huge number of people watch live football matches by TV or Internet. A football match takes 90 minutes, but viewers may only want to watch a few highlights to save their time. As far as we know, there is no such a product that can be put into use to achieve intelligent highlight extraction from live football matches. In this paper, we propose an intelligent editing system for live football matches. Our system can automatically extract a series of highlights, such as goal, shoot, corner kick, red yellow card and the appearance of star players, from the live stream of a football match. Our system has been integrated into live streaming platforms during the 2018 FIFA World Cup and performed fairly well.

• Journal of the Korea Society of Computer and Information
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• v.15 no.6
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• pp.73-80
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• 2010

Vocabulary recognition system is providing inaccurate vocabulary and similar phoneme recognition due to reduce recognition rate. It's require method of similar phoneme recognition unrecognized and efficient feature extraction process. Therefore in this paper propose phoneme likelihood error correction improvement system using based on phoneme feature Bhattacharyya distance measurement. Phoneme likelihood is monophone training data phoneme using HMM feature extraction method, similar phoneme is induced recognition able to accurate phoneme using Bhattacharyya distance measurement. They are effective recognition rate improvement. System performance comparison as a result of recognition improve represent 1.2%, 97.91% by Euclidean distance measurement and dynamic time warping(DTW) system.

• Journal of KIISE:Software and Applications
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• v.32 no.9
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• pp.853-867
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• 2005

A number of content-based image search methods have been proposed to this point. Each of these systems uses different image data and generates different data depending on the extraction method of different characteristics that the search capabilities of each system cannot be compared and assessed. In particular, there is a problem of applying the identical image data onto the contents based image search system on the web that cannot be compared and assessed. To resolve such a problem, the XML-based FEMAL is hereby presented for extracting data of characteristics generated from specific search system in a way that can be recognized from other starch system. In the experiment using FEMAL, the extract data for characteristics is mutually communicated and integrated and the comparison assessment of search capability is seemed to be available.

• Journal of Integrative Natural Science
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• v.11 no.4
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• pp.167-183
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• 2018

Electroencephalogram (EEG) recording provides a new way to support human-machine communication. It gives us an opportunity to analyze the neuro-dynamics of human cognition. Machine learning is a powerful for the EEG classification. In addition, machine learning can compensate for high variability of EEG when analyzing data in real time. However, the optimal EEG electrode location must be prioritized in order to extract the most relevant features from brain wave data. In this paper, we propose an intelligent system model for the extraction of EEG data by training the optimal electrode location of EEG in a specific problem. The proposed system is basically a fuzzy system and uses a neural network structurally. The fuzzy clustering method is used to determine the optimal number of fuzzy rules using the features extracted from the EEG data. The parameters and weight values found in the process of determining the number of rules determined here must be tuned for optimization in the learning process. Genetic algorithms are used to obtain optimized parameters. We present useful results by using optimal rule numbers and non - symmetric membership function using EEG data for four movements with the right arm through various experiments.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.10
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• pp.1-7
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• 2020

In this study, a multichannel gas-liquid microextraction system is designed by integrating the automatic elution of extraction line and multichannel gas-purging liquid phase microextraction. The system uses an injection pump and inert gas to push the extraction solvent to a sample bottle of a gas-phase color autosampler and then implements multichannel gas-liquid microextraction and gas chromatography-mass spectrometry. The system also employs a three-way integrated micro-high-temperature heater, syringe pump, and microflow controller to realize the simultaneous processing of multiple groups of samples, thus improving the sample pretreatment speed and reproducibility and reducing human error. Autoinjection experiments were implemented with polycyclic aromatic hydrocarbon standard samples. The experiments show that the average recovery rate of the system exceeds 70%, and the relative standard among the channels is less than 15%.

• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.123-131
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• 2020

Along with the rapid development of artificial intelligence technology, natural language processing, which deals with human language, is also actively studied. In particular, BERT, a language model recently proposed by Google, has been performing well in many areas of natural language processing by providing pre-trained model using a large number of corpus. Although BERT supports multilingual model, we should use the pre-trained model using large amounts of Korean corpus because there are limitations when we apply the original pre-trained BERT model directly to Korean. Also, text contains not only vocabulary, grammar, but contextual meanings such as the relation between the front and the rear, and situation. In the existing natural language processing field, research has been conducted mainly on vocabulary or grammatical meaning. Accurate identification of contextual information embedded in text plays an important role in understanding context. Knowledge graphs, which are linked using the relationship of words, have the advantage of being able to learn context easily from computer. In this paper, we propose a system to extract Korean contextual information using pre-trained BERT model with Korean language corpus and knowledge graph. We build models that can extract person, relationship, emotion, space, and time information that is important in the text and validate the proposed system through experiments.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.6 no.1
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• pp.25-33
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• 2008

A selective separation of Actirlide(III) by a nPr-BTP/nitrobezene extraction system was studied. The nPr-BTP (2.6-Bis-(5.6-n-propyl-1.2.4-triazin-3-yl)-pyridine) of a environmentally -friendly CHN type was self-synthesized and its compatability with diluent and stability with nitric acid were investigated. At the 0.1M nPr-BTP/nitrobenzene-1M $HNO_3$ and O/A=2, extraction yields of Am used as a representative of Actinide(III) and Eu were about 85% and 8%, respectively, and the other RE elements such as Nd, Ce and Y were extracted less than 3% (separation factor of Am and Eu was about 60). Thus, there was no problems in the selective extraction of Actinide(III) from RE. The stripping yield of Am with 0.05M $HNO_3$ at O/A= 1, however, was about 43% and the maximum stripping yield was 65% at O/A=0.3. It is necessary to develop the stripping system including the stripping agent instead of nitric acid solution.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.6
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• pp.35-43
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• 2009

In the Computer Aided Diagnosis(CAD) System, the efficient way of classifying nodules from chest CT images of a patient is to perform the classification of the remaining part after the pulmonary vessel extraction. During the pulmonary vessel extraction, due to the small difference between the vessel and nodule features in imaging studies such as CT scans after having an injection of contrast, nodule maybe extracted along with the pulmonary vessel. Therefore, the pulmonary vessel extraction method plays an important role in the nodule classification process. In this paper, we propose a nodule reclassification method based on vessel thickness analysis. The proposed method consist of four steps, lung region searching step, vessel extraction and thinning step, vessel topology formation and correction step and the reclassification of nodule in the vessel candidate step. The radiologists helped us to compare the accuracy of the CAD system using the proposed method and the accuracy of general one. Experimental results show that the proposed method can extract pulmonary vessels and reclassify false-positive nodules accurately.