• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.10
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• pp.38-45
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• 2002

This paper presents the new Compact 2D ADI-FDTD(Alternating-Direction Implicit Finite-Difference Time-Domain) method, where the time step is no longer restricted by the numerical stability condition. This method is an accelerating algorithm for the conventional Compact 2D FDTD method. To validate this algorithm, we have analyzed the dispersion characteristics of the hollow rectangular waveguide and the shielded microstrip line. The results of the proposed method are very well agreed with those of both the conventional analytic method and the Compact 2D FDTD method. The CPU time for analysis of this method is very much reduced compared with the conventional Compact 2D FDTD method. The proposed method is valuable as a fast algorithm in the research of dispersion characteristics of the waveguide structures.

• Annual Conference on Human and Language Technology
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• 2001.10d
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• pp.146-154
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• 2001

본 논문에서는 개념망 구축을 위해 사전 뜻풀이말에서 추출 가능한 의미속성의 분포 정보를 기반으로 어휘 연관도를 측정하고자 한다. 먼저 112,000여 개의 사전 뜻풀이말을 대상으로 품사 태그와 의미 태그가 부여된 코퍼스에서 의미속성을 추출한다. 추출 가능한 의미속성은 체언류, 부사류, 용언류 등이 있는데 본 논문에서는 일차적으로 명사류와 수식 관계에 있는 용언류 중 관형형 전성어미('ㄴ/은/는')가 부착된 것을 대상으로 한다. 추출된 공기쌍 45,000여 개를 대상으로 정제 작업을 거쳐 정보이론의 상호 정보량(MI)을 이용하여 명사류와 용언류의 연관도를 측정한다. 한편, 자료의 희귀성을 완화하기 위해 수식 관계의 명사류와 용언류는 기초어휘를 중심으로 유사어 집합으로 묶어서 작업을 하였다. 이러한 의미속성의 분포 정보를 통해 측정된 어휘 연관도는 의미속성의 공유 정도를 계산하여 개념들간에 계층구조를 구축하는 데 이용할 수 있다.

• Speech Sciences
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• v.15 no.2
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• pp.177-189
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• 2008

This study was to investigate diadochokinetic (DDK) rate, regularity and mean flow rate of articulation valves in dysarthria. DDK rate, mean airflow rate (MFR) and regularity of DDK syllable repetitions of vocal function /ihi/, tongue function /ta/, velopharyngeal function /bm/, and labial function /pa/ in 24 normal and dysarthric speakers were measured. Aerophone Ⅱ and Motor Speech Profile were used for data recording and analysis. The results of the findings were as follows: First, there were significant differences between the dysarthria and the normal group in DDK rate. DDK rates in ataxic dysarthria were the lowest and spastic, flaccid, and hypokinetic dysarthria followed in sequence. Second, there was a significant difference between the dysarthria and the normal group in DDK regularity. Third, there was a significant difference between dysarthria groups and normal group in DDK MFR. Finally, there was a significant difference between the 4 groups of dysarthria and the normal group in DDK air flow tracking. The results of this study can be guidelines for normal DDK rate, regularity and flow rate in dysarthria groups. In addition, their differential diagnoses and descriptions are important to make a decision on medical and behavioral management of the individuals with disorders according to DDK characteristics.

• Phonetics and Speech Sciences
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• v.9 no.3
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• pp.67-74
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• 2017

An increase in speech intelligibility has been found in Clear Speech compared to conversational speech. Clear Speech is defined by decreased articulation rates and increased frequency and length of pauses. The objective of the present study was to investigate improvement in immediate speech intelligibility in 10 patients with Parkinson's disease (age range: 46 to 75 years) using Clear Speech. This experiment has been performed using the Phonatory Aerodynamic System 6600 after the participants read the first sentence of a Sanchaek passage and the "List for Adults 1" in the Sentence Recognition Test (SRT) using casual speech and Clear Speech. Acoustic and aerodynamic parameters that affect speech intelligibility were measured, including mean F0, F0 range, intensity, speaking rate, mean airflow rate, and respiratory rate. In the Sanchaek passage, use of Clear Speech resulted in significant differences in mean F0, F0 range, speaking rate, and respiratory rate, compared with the use of casual speech. In the SRT list, significant differences were seen in mean F0, F0 range, and speaking rate. Based on these findings, it is claimed that speech intelligibility can be affected by adjusting breathing and tone in Clear Speech. Future studies should identify the benefits of Clear Speech through auditory-perceptual studies and evaluate programs that use Clear Speech to increase intelligibility.

• Journal of Radiation Protection and Research
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• v.14 no.2
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• pp.18-22
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• 1989

In order to calibrate the CR-39 Solid State Nuclear Track Detector (SSNTD), a closed -circulation type SSNTD-Calibration-System containing a radon-cup with the Millipore filter has been set-up, and the tracks produced on the SSNTD were measured for the known amount of radon concentration. Calibration factor for the time integrated radon concentration as a function of the track density on CR-39 was estimated to be $0.24{\pm}0.09(pCi/l)\;day/(Tr/cm^2)$.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.12 no.7
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• pp.1131-1138
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• 2001

This paper presents the new Compact 2D Haar-wavelet-based MultiResolution Time-Domain method (MRTD) as an accelerating algorithm for the conventional Compact BD Finite-Difference Time-Domain method (FDTD). To validate this algorithm, we analyzed the dispersion characteristics of the hollow rectangular waveguide and dielectric slab-loaded rectangular waveguide. The results of the proposed method are very weal agreed with those of both the conventional analytic method and the Compact 2D FDTD method. The CPU time for analysis of this method is reduced to about a half of the conventional Compact 2D FDTD method. The proposed method is valuable as a fast algorithm in the research of dispersion characteristics of waveguide structures.

• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.149-154
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• 2006

The main purpose of document summarization is to reduce the complexity of documents that are consisted of sub-themes. Also it is to create summarization which includes the sub-themes. This paper proposes a summarization system which could extract any salient sentences in accordance with sub-themes by using graph division. A document can be represented in graphs by using chosen representative terms through term relativity analysis based on co-occurrence information. This graph, then, is subdivided to represent sub-themes through connected information. The divided graphs are types of sentence clustering which shows a close relationship. When salient sentences are extracted from the divided graphs, summarization consisted of core elements of sentences from the sub-themes can be produced. As a result, the summarization quality will be improved.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.43-46
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• 2023

호흡기 관련 전염병의 주된 증상인 기침은 공기 중에 감염된 병원균을 퍼트리며 비감염자가 해당 병원균에 노출된 경우 높은 확률로 해당 전염병에 감염될 위험이 있다. 또한 사람들이 많이 모이는 공공장소 및 실내 공간에서의 기침 탐지 및 조치는 전염병의 대규모 유행을 예방할 수 있는 효율적인 방법이다. 따라서 본 논문에서는 탐지해야 하는 기침 소리 및 일상생활 속 발생할 수 있는 기침과 유사한 배경 소리 들을 Mel-Spectrogram으로 변환한 후 시각화된 특징을 CNN 모델에 학습시켜 기침 탐지를 진행하며, 일반적으로 사용되는 사전 학습된 CNN 모델에 제안된 Attention 모듈의 적용이 기침 탐지 성능 향상에 도움이 됨을 입증하였다.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.329-352
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• 2022

It is reported that particulate matter(PM) penetrates the lungs and blood vessels and causes various heart diseases and respiratory diseases such as lung cancer. The subway is a means of transportation used by an average of 10 million people a day, and although it is important to create a clean and comfortable environment, the level of particulate matter pollution is shown to be high. It is because the subways run through an underground tunnel and the particulate matter trapped in the tunnel moves to the underground station due to the train wind. The Ministry of Environment and the Seoul Metropolitan Government are making various efforts to reduce PM concentration by establishing measures to improve air quality at underground stations. The smart air quality management system is a system that manages air quality in advance by collecting air quality data, analyzing and predicting the PM concentration. The prediction model of the PM concentration is an important component of this system. Various studies on time series data prediction are being conducted, but in relation to the PM prediction in subway stations, it is limited to statistical or recurrent neural network-based deep learning model researches. Therefore, in this study, we propose four transformer-based models including spatiotemporal transformers. As a result of performing PM concentration prediction experiments in the waiting rooms of subway stations in Seoul, it was confirmed that the performance of the transformer-based models was superior to that of the existing ARIMA, LSTM, and Seq2Seq models. Among the transformer-based models, the performance of the spatiotemporal transformers was the best. The smart air quality management system operated through data-based prediction becomes more effective and energy efficient as the accuracy of PM prediction improves. The results of this study are expected to contribute to the efficient operation of the smart air quality management system.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.3
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• pp.13-24
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• 2018

For government and public institutions, civil complaints containing direct requirements of citizens can be utilized as important data in developing policies. However, it is difficult to draw accurate requirements using text mining methods since the nature of the complaint text is unstructured. In this study, a new method is proposed that draws the exact requirements of citizens, improving the previous text mining in analyzing the data of civil complaints. The new text-mining method is based on the principle of Co-Occurrences Structure Map, and it is structured by two-step association analysis, so that it consists of the first-order related word and a second-order related word based on the core subject word. For the analysis, 3,004 cases posted on the electronic bulletin board of Busan City for the year 2016 are used. This study's academic contribution suggests a method deriving the requirements of citizens from the civil affairs data. As a practical contribution, it also enables policy development using civil service data.