• Journal of Korea Spatial Information System Society
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• v.8 no.2 s.17
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• pp.39-52
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• 2006

With the recent the use of spatio-temporal data mining which can extract various knowledge such as movement patterns of moving objects in history data of moving object gets increasing. However, the existing movement pattern extraction methods create lots of candidate movement patterns when the minimum support is low. Therefore, in this paper, we suggest the STMPE(Spatio-Temporal Movement Pattern Extraction) algorithm in order to efficiently extract movement patterns of moving objects from the large capacity of spatio-temporal data. The STMPE algorithm generalizes spatio-temporal and minimizes the use of memory. Because it produces and keeps short-term movement patterns, the frequency of database scan can be minimized. The STMPE algorithm shows more excellent performance than other movement pattern extraction algorithms with time information when the minimum support decreases, the number of moving objects increases, and the number of time division increases.

• Journal of Radiation Protection and Research
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• v.9 no.2
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• pp.103-111
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• 1984

A convenient method of $^{99m}Tc$-methyl-ethyl-ketone (MEK) extraction technique was developed and a mobile $^{99m}Tc$-extraction generator was designed. The MEK extraction and the phase separation of $^{99m}TcO^-{_4}$ were carried out with a simple procedure in the same container. The shielding of $^{99}Mo$ radioactivity was made with one lead container. The system was simplified by shielding $^{99m}TcO_4{^-}({\gamma}_e=0.14\;MeV)$ separately. $^{99m}TcO^-{_4}\;in\;^{99m}Tc-MEK$ extract was recovered by adsorption and elution only, and therefore, the possibility of volatilization was reduced. The volume of $^{99m}TcO^{-}{_4}$-saline product was reduced to 1 ml by using a small alumina column and the column operation time was shortened. The separation time of $^{99m}Tc$ was reduced to 30 minutes, and the operation was carried out at the outside of the shielding. The system was designed to operate under the condition of bacteria-free.

• Applied Chemistry for Engineering
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• v.8 no.2
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• pp.220-229
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• 1997

Extraction of valuable light hydrocarbon from atmospheric residue using pentane as a solvent has been carried out. The SIMDIS was used to calculate the true boiling point of atmospheric residue containing complex components before the modeling of the extraction process could by performed. In order to simplify the procedure, modeling was adopted and a lumping method was used, such that a large number of compounds were divided into similar component classes called pseudocomponents. The modeling of the extraction process of the atmospheric residue-pentane system was based on the isothermal flash calculation, and the Peng-Robinson equation of state was used to calculate the fugacity coefficient of vapor and liquid phase during calculation steps of modeling. The agreement between the experiments and the calculations was reasonable considering the uncertainties involved in modeling such complex processes.

• Journal of Korean Society on Water Environment
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• v.22 no.5
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• pp.879-886
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• 2006

The analytical methods of polychlorinated dibenzo-p-dioxins, polychlorinated dibenzofurans (PCDD/Fs) for water sample with extremely low concentration was developed to extract large volume and to improve fast chromatography for clean up. Semi-automated solid phase extraction (SPE) system and column coupling chromatography using elution pump was optimized and applied to each processes of treatment plant. Results of disk type SPE indicated that this system was applicable below 40 L of aqueous sample with a flow rate of 0.08 ~ 0.2 L/min. Average recoveries of SPE using labeled sampling spike of $^{37}Cl$-2,3,7,8-TCDD was 97%. Column coupling method resulted in reduced clean up time, solvent volume, increased average recoveries with constant elution rate. The combined methods were applied to the monitoring of drinking water treatment plant. Limits of detection (LOD) of each process were calculated. For example, LOD of raw and treated water ranged 0.094~0.968 pg/L and 0.028~0.364 pg/L, respectively. Combined methods of extraction and cleanup techniques provided fast analysis of PCDD/Fs with high accuracy and low LODs for water samples.

• The KIPS Transactions:PartB
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• v.16B no.6
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• pp.497-502
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• 2009

In this paper, we introduce an automatic product feature extracting system that improves the efficiency of product review analysis. Our system consists of 2 parts: a review collection and correction part and a product feature extraction part. The former part collects reviews from internet shopping malls and revises spoken style or ungrammatical sentences. In the latter part, product features that mean items that can be used as evaluation criteria like 'size' and 'style' for a skirt are automatically extracted by utilizing term statistics in reviews and web documents on the Internet. We choose nouns in reviews as candidates for product features, and calculate degree of association between candidate nouns and products by combining inner association degree and outer association degree. Inner association degree is calculated from noun frequency in reviews and outer association degree is calculated from co-occurrence frequency of a candidate noun and a product name in web documents. In evaluation results, our extraction method showed an average recall of 90%, which is better than the results of previous approaches.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.11
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• pp.411-418
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• 2018

With the proliferation of artificial intelligence technology, it is becoming important to obtain, store, and utilize scientific data in research and science sectors. A number of methods for extracting meaningful objects such as graphs and tables from research articles have been proposed to eventually obtain scientific data. Existing extraction methods using heuristic approaches are hardly applicable to electronic documents having heterogeneous manuscript formats because they are designed to work properly for some targeted manuscripts. This paper proposes a prototype of an object extraction system which exploits a recent deep-learning technology so as to overcome the inflexibility of the heuristic approaches. We implemented our trained model, based on the Faster R-CNN algorithm, using the Google TensorFlow Object Detection API and also composed an annotated data set from 100 research articles for training and evaluation. Finally, a performance evaluation shows that the proposed system outperforms a comparator adopting heuristic approaches by 5.2%.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.521-523
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• 1997

With Extraction Transient Data from Booster Pump System, This paper establishs system model equation. and This equation is capable of PID control. Using Ziegler-Nichole tunning method of PID, Constantly estimated control method is done.

• Journal of KIISE
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• v.42 no.3
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• pp.367-378
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• 2015

This study was directed at the design of a hybrid algorithm for competition relation extraction. Previous works on relation extraction have relied on various lexical and deep parsing indicators and mostly utilize only the machine learning method. We present a new algorithm integrating machine learning with various filtering methods. Some simple but useful features for competition relation extraction are also introduced, and an optimum feature set is proposed. The goal of this paper was to increase the precision of competition relation extraction by combining supervised learning with various filtering methods. Filtering methods were employed for classifying compete relation occurrence, using distance restriction for the filtering of feature pairs, and classifying whether or not the candidate entity pair is spam. For evaluation, a test set consisting of 2,565 sentences was examined. The proposed method was compared with the rule-based method and general relation extraction method. As a result, the rule-based method achieved positive precision of 0.812 and accuracy of 0.568, while the general relation extraction method achieved 0.612 and 0.563, respectively. The proposed system obtained positive precision of 0.922 and accuracy of 0.713. These results demonstrate that the developed method is effective for competition relation extraction.

• Journal of Advanced Navigation Technology
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• v.27 no.3
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• pp.306-313
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• 2023

Realistic and graphics-based virtual reality content is based on 360-degree videos, and viewport extraction through the viewer's intention or automatic recommendation function is essential. This paper designs a viewport extraction system based on multiple object tracking in 360-degree videos and proposes a parallel computing structure necessary for multiple viewport extraction. The viewport extraction process in 360-degree videos is parallelized by composing pixel-wise threads, through 3D spherical surface coordinate transformation from ERP coordinates and 2D coordinate transformation of 3D spherical surface coordinates within the viewport. The proposed structure evaluated the computation time for up to 30 viewport extraction processes in aerial 360-degree video sequences and confirmed up to 5240 times acceleration compared to the CPU-based computation time proportional to the number of viewports. When using high-speed I/O or memory buffers that can reduce ERP frame I/O time, viewport extraction time can be further accelerated by 7.82 times. The proposed parallelized viewport extraction structure can be applied to simultaneous multi-access services for 360-degree videos or virtual reality contents and video summarization services for individual users.

• ETRI Journal
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• v.29 no.3
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• pp.292-299
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• 2007

In this paper, we present a speech recognition system using a throat microphone. The use of this kind of microphone minimizes the impact of environmental noise. Due to the absence of high frequencies and the partial loss of formant frequencies, previous systems using throat microphones have shown a lower recognition rate than systems which use standard microphones. To develop a high performance automatic speech recognition (ASR) system using only a throat microphone, we propose two methods. First, based on Korean phonological feature theory and a detailed throat signal analysis, we show that it is possible to develop an ASR system using only a throat microphone, and propose conditions of the feature extraction algorithm. Second, we optimize the zero-crossing with peak amplitude (ZCPA) algorithm to guarantee the high performance of the ASR system using only a throat microphone. For ZCPA optimization, we propose an intensification of the formant frequencies and a selection of cochlear filters. Experimental results show that this system yields a performance improvement of about 4% and a reduction in time complexity of 25% when compared to the performance of a standard ZCPA algorithm on throat microphone signals.