• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.405-413
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• 2012

Low misclassification performance is significant with high classification accuracy for a reliable diagnosis of ECG signals, and diagnosing abnormal state as normal state can especially raises a deadly problem to a person in ECG test. In this paper, we propose detection and classification method of abnormal rhythm by rule-based rhythm classification reflecting clinical criteria for disease. Rule-based classification classifies rhythm types using rule-base for feature of rhythm section, and rule-base deduces decision results corresponding to professional materials of clinical and internal fields. Experimental results for the MIT-BIH arrhythmia database show that the applicability of proposed method is confirmed to classify rhythm types for normal sinus, paced, and various abnormal rhythms, especially without misclassification in detection aspect of abnormal rhythm.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.624-630
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• 2010

As electrocardiogram(ECG) signals are generally sampled with a frequency of over 200Hz, a method to compress diagnostic information without losing data is required to store and transmit them efficiently. In this paper, an ECG signal compression method, which uses feature points based on curvature, is proposed. The feature points of P, Q, R, S, T waves, which are critical components of the ECG signal, have large curvature values compared to other vertexes. Thus, these vertexes are extracted with the proposed method, which uses local extremum of curvatures. Furthermore, in order to minimize reconstruction errors of the ECG signal, extra vertexes are added according to the iterative vertex selection method. Through the experimental results on the ECG signals from MIT-BIH Arrhythmia database, it is concluded that the vertexes selected by the proposed method preserve all feature points of the ECG signals. In addition, they are more efficient than the AZTEC(Amplitude Zone Time Epoch Coding) method.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.57-78
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• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.2
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• pp.293-300
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• 2012

This study was to investigate the unsuitable rate of the storage facilities, the changes in corrosion process over time after installation according to the status, the time to install the facilities, years elapsed after facilities installation, inspection of methods and motivation, and so on, based on the results of the inspection at the petroleum storage facilities conducted by domestic soil-relate specialized agency to derive optimal management plans which meet the status of soil contamination facilities. The results showed that the facilities more than 5 years after the initial leak test at the time of the installation need to be inspected periodically by considering costs of leak test and remediation of polluted soil. The inspection period can be decided by cost and leak test methods showing discrepancies for the results obtained from individual test whether it was direct or indirect. To compensate these matters, we suggested that the direct inspection method on regular schedule is recommended. On the other hand, the inspection can be voluntarily completed to ease burden of the results by inspection or equivalent level to this inspection method. Also, it may need improved construction supervision and performance test system to minimize the occurrence of the nature defects in installing the facilities as well as the upgrade program for the facilities during intervals of inspection period.

• Journal of Chest Surgery
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• v.34 no.11
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• pp.809-822
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• 2001

Background: Ischemic preconditioning(IP) is known to be effective in the protection of myocardial necrosis, arrhythmia, and the restoration of the myocardial function in the ischemia-reperfusion state of the heart. However the exact mechanism is not clearly understood. The purpose of this study was to elucidate the trigger mechanism 7f IP on the restoration of the myocardial function after ischemia-reperfusion. Material and Method: By connecting a Langendorff perfusion apparatus with an isolated heart of a rat, the normal temperature of the heart was maintained. The experiment was conducted in seven groups, which were divided according to the preconditioning stimuli and blockage methods Group I(n=10) was a group without IP, Group II(n=10) a group of three-minute IP, Group III(n=10) a group of PEIP, Group IV(n=10) a group of clonidine IP, Group V(n=10) a group of If after reserpine, Group Vl(n=10) a group of PE & prazosin IP, and Group Vll(n=10) a group of clonidine & yohimbine IP. Hemodynamic parameters of DP, LVEDP, $\pm$dP/dT and the changes of perfusion in the coronary artery were evaluated. Result: Developed pressure and +dP/dT changed per unit time. After 20 minutes of reperfusion, those of Group II and III were 63.1$\pm$3.7%, 64.8$\pm$4.6% and 64.5$\pm$4.6%, 63.8$\pm$4.4%, which improved more significantly than those of Group I(P<0.05), However, there were no significant differences between the Groups V and Vl, and Group I. Conclusion: The Brief ischemic preconditioning and pharmacological preconditioning using $\alpha$-receptor sympatho-mimetics have protecting effects on the restoration of myocardial function after reperfusion. And the protecting effect of preconditioning seems to be related to sympathetic neurotransmitters and to the selective action of the $\alpha$$_1$-adrenergic receptor.

• Journal of the Mineralogical Society of Korea
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• v.18 no.4 s.46
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• pp.277-288
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• 2005

Perlite, a hydrated volcanic glass, occurs mainly as a bed-like body, and is distributed intermittently along the unconformity surface between the Beomgockri Group and its lower formations, viz. Janggi Group. The perlite is intimately associated with surrounding pumiceous welded tuff and rhyodacites in space and time. Compared to the typical perlite, the perlite is rather silica-poor and impure, and thus, includes lots of phenocrysts and rock fragments. Nearly the perlite is compositionally rather close to a pitchstone than a perlite in water contents. Petrographic comparison between perlite and associated volcanic to volcaniclastic rocks indicates that pumiceous welded tuff and rhyodacite seem to be Protolith of the Perlite. A Zr/$TiO_{2}$-Nb/Y diagram and field occurrence of perlite and their protolithic rocks also conforms the above interpretation. Kn addition, remnant vesicles in perlite strongly reflect that the precursor of perlitic glass appeared to be pumice fragment as well as volcanic glass. The perlite was diagenetically formed by way of a pervasive water-rock interaction at the deposition of the Manghaesan Formation in lacustrine environment. During perlitization, $SiO_{2}$ and alkali tend to be consistently depleted. Preexisting system of the Beomgockri Group based on the perlite formation should be corrected, because the perlite was formed diagenetically without lateral persistence in its occurrence.