• Korean Journal of Clinical Pharmacy
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• v.26 no.1
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• pp.84-95
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• 2016

Objective: Atrial fibrillation (AF) guidelines have been published in the USA and Europe. Recently, the USA and Europe have updated their guidelines, respectively. These new AF guidelines help in addressing key management issues in clinical situations. This study, therefore, systematically compared guidelines for rate and rhythm control pharmacotherapy of patients with AF between the USA (American College of Cardiology and American Heart Association, ACC/AHA) and Europe (European Society of Cardiology, ESC). Methods: This study investigated and compared American guidelines (2014) and European guidelines (2010 and 2012). Results: Generally, there are four meaningful differences between ACC/AHA and ESC guidelines. Important differences are treatment classification system, level of recommendation, drug list, and dosage. In addition, ACC/AHA described pharmacokinetic drug interactions for antiarrhythmic drugs. ESC emphasized ECG and atrioventricular nodal slowing as feature of antiarrhythmic drugs. Conclusion: This research addresses important use of anti-arrhythmic drugs and movement to accept recent recommendations in Korea. For the successful application of the guidelines, a role of pharmacists is crucial in clinical situation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10C
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• pp.965-974
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• 2007

In this paper, we proposed the feature selection algorithm for multi-class genre classification. In our proposed algorithm, we developed GMM separation score based on Gaussian mixture model for measuring separability between two genres. Additionally, we improved feature subset selection algorithm based on sequential forward selection for multi-class genre classification. Instead of setting criterion as entire genre separability measures, we set criterion as worst genre separability measure for each sequential selection step. In order to assess the performance proposed algorithm, we extracted various features which represent characteristics such as timbre, rhythm, pitch and so on. Then, we investigate classification performance by GMM classifier and k-NN classifier for selected features using conventional algorithm and proposed algorithm. Proposed algorithm showed improved performance in classification accuracy up to 10 percent for classification experiments of low dimension feature vector especially.

• Journal of Broadcast Engineering
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• v.14 no.5
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• pp.573-588
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• 2009

In this paper, we propose a novel video quality degradation monitoring scheme titled VR-VQMS(Visual Rhythm based Video Quality Monitoring Scheme) over an IPTV service prone to packet losses during network transmission. Proposed scheme quantifies the amount of quality degradation due to packet losses, and can be classified into a RR(reduced-reference) based quality measurement scheme exploiting visual rhythm data of H.264-encoded video frames at a media server and reconstructed ones at an Set-top Box as feature information. Two scenarios, On-line and Off-line VR-VQMS, are proposed as the practical solutions. We define the NPSNR(Networked Peak-to-peak Signal-to-Noise Ratio) modified by the well-known PSNR as a new objective quality metric, and several additional objective and subjective metrics based on it to obtain the statistics on timing, duration, occurrence, and amount of quality degradation. Simulation results show that the proposed method closely approximates the results from 2D video frames and gives good estimation of subjective quality(i.e.,MOS(mean opinion score)) performed by 10 test observers. We expect that the proposed scheme can play a role as a practical solution to monitor the video quality experienced by individual customers in a commercial IPTV service, and be implemented as a small and light agent program running on a resource-limited set-top box.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.4
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• pp.33-38
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• 2009

This paper proposes an automatic equalizer control method in automobile audio system. The proposed method discriminates the music segment from the consecutive real-time audio stream of the radio and the equalizer is controlled automatically according to the classified genre of the music segment. For enhancing the accuracy of the music genre classification in real-time, timbre feature and rhythm feature extracted from the consecutive audio stream is applied to GMM(Gaussian mixture model) classifier. The proposed method evaluates the performance of the music genre classification, which classified various audio segments segmented from the audio signal of the radio broadcast in automobile audio system into one of five music genres.

• ETRI Journal
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• v.44 no.3
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• pp.413-425
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• 2022

The study of literary texts is one of the earliest disciplines practiced around the globe. Poetry is artistic writing in which words are carefully chosen and arranged for their meaning, sound, and rhythm. Poetry usually has a broad and profound sense that makes it difficult to be interpreted even by humans. The essence of poetry is Rasa, which signifies mood or emotion. In this paper, we propose a poetry classification-based approach to automatically extract similar poems from a repository. Specifically, we perform a novel Rasa-based classification of Hindi poetry. For the task, we primarily used lexical features in a bag-of-words model trained using the support vector machine classifier. In the model, we employed Hindi WordNet, Latent Semantic Indexing, and Word2Vec-based neural word embedding. To extract the rich feature vectors, we prepared a repository containing 37 717 poems collected from various sources. We evaluated the performance of the system on a manually constructed dataset containing 945 Hindi poems. Experimental results demonstrated that the proposed model attained satisfactory performance.

• (The) Research of the performance art and culture
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• no.42
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• pp.233-256
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• 2021

The purpose of this article is to understand the characteristics and meanings of the Hwanghae-do Gutchum, or shamanic ritual dance. First, the characteristics of the Hwanghae-do Gutchum are summarized as follows. The regular dances that appear in all pieces of Gutgeori or the tune of Gut of the Hwanghae-do Gutchum feature Geosangchum, followed by domu and heojeonmu in the sequential order. The accompaniment rhythms are Geosang rhythm, Chum rhythm, and Yeonpung rhythm. The dance featuring mugu, or shaman implements held on shaman's hand as part of the Hwanghae-do Gutchum, which symbolizes the characteristics of deities, is the same as domu aligned with the dance rhythm and the whirling dance aligned with the Yeonpung rhythm. The name of mugu, mubok (shaman clothing) and/or deities may be used as the name of Gutchum but there is no originality of Gutchum. The Beokgu Chum and Samhyeon Chum as part of the Hwanghae-do Gutchum use Beockgu Jangdan and Samhyeon Jangdan, which deserves to have their originality acknowledged. Hwanghae-do Gutchum is closely related to the rhythm. The harmony of janggu player and a female shaman is essential in practicing the Hwanghae-do Gut. If a janggu player fails to perform to properly support the gut practice of a female shaman, the shaman is not able to proceed with a smooth practice and causes confusion. On the other hand, if the gut performance of a female shaman fails to catch up with the performance of janggu, the gut becomes plain and simple at best. Janggu is the single most important element that determines the success or failure of the Hwanghae-do Gutchum. A female shaman takes the harmony and collaboration with a janggu player so seriously that she is willing to reschedule the practice of gut if its schedule does not match that of the janggu player. The Hwanghae-do Gutchum is largely dependent on gyeolrye. However, the difference between the chum and the rhythm caused by gyeolrye has disappeared due to the intangible cultural assets. That is, designating an intangible cultural asset has resulted in eliminating all distinctive characteristics of Hwanghae-do Gutchum. With the distinction of gyeolrye becoming vague, they have lost interest in the genealogy of gut they have learned. It is no longer gyeolrye but the intangible cultural property system that serves as an important factor to distinguish chums.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.293-297
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• 1996

For the representative beat calculation and efficient rhythm analysis new method, that is, QRS typification were proposed. A problem that were resulted from pattern classification based on binary logic could be solved out by the fuzzy clustering and classification nodes could be reduced by using the proposed new feature vector. The accurate representative beat could be obtained by excluding the ST-T segment that happened outlier through ST-T segment typification procedure.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.179-184
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• 2022

With the development of information and communication technology, the production and distribution of digital contents is rapidly increasing, and the distribution of illegally copied contents also increases, causing various problems. In order to prevent illegal distribution of contents, a DRM (Digital Rights Management)-based approach can be used, but in a situation where the contents are already copied and distributed, a method of searching and detecting the duplicated contents is required. In this paper, a duplication detection method based on the contents of video content is proposed. The proposed method divides the video into scene units using the visual rhythm extracted from the video, and hierarchically applies the playback time and color feature values of each divided scene to quickly and efficiently detect duplicate videos in a large database. Through experiments, it was shown that the proposed method can reliably detect various replication modifications.

• Science of Emotion and Sensibility
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• v.19 no.1
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• pp.31-38
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• 2016

The brain and muscles both of which are composed of top-down structure occur the connectivity with the change of Electroencephalogram(EEG) and Electromyogram(EMG). In this paper, we studied the difference of functional connectivity between brain and muscles that by applying coherence method to EEG and EMG signals when users exercised upper limb with and without the movement intention. The changes in the EEG and EMG signals were inspected using coherence method. During the upper limb exercise, the mu (8~14 Hz) and beta (15~30 Hz) rhythms of the EEG signal at the motor cortex area are activated. And then the beta and piper (30~60 Hz) rhythms of the EMG signal are activated as well. The result of coherence analysis between EEG and EMG showed the coefficient of active exercise including movement intention is significantly higher than passive exercise. The coherence relations between cognitive response and muscle movement could interpret that the connectivity between the brain and muscle appear during active exercise with movement intention. The feature of coherence between brain and muscles by the status of movement intention will be useful in designing the rehabilitation system requiring feedback depending on the users' movement intention status.

• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.571-579
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• 2005

In this paper, we proposed an algorithm for arrhythmia classification, which is associated with the reduction of feature dimensions by linear discriminant analysis (LDA) and a support vector machine (SVM) based classifier. Seventeen original input features were extracted from preprocessed signals by wavelet transform, and attempts were then made to reduce these to 4 features, the linear combination of original features, by LDA. The performance of the SVM classifier with reduced features by LDA showed higher than with that by principal component analysis (PCA) and even with original features. For a cross-validation procedure, this SVM classifier was compared with Multilayer Perceptrons (MLP) and Fuzzy Inference System (FIS) classifiers. When all classifiers used the same reduced features, the overall performance of the SVM classifier was comprehensively superior to all others. Especially, the accuracy of discrimination of normal sinus rhythm (NSR), arterial premature contraction (APC), supraventricular tachycardia (SVT), premature ventricular contraction (PVC), ventricular tachycardia (VT) and ventricular fibrillation (VF) were $99.307\%,\;99.274\%,\;99.854\%,\;98.344\%,\;99.441\%\;and\;99.883\%$, respectively. And, even with smaller learning data, the SVM classifier offered better performance than the MLP classifier.