• 대한음성학회지:말소리
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• 제53호
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• pp.17-35
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• 2005

A New Method of Extracting the Filter Characteristics of the Nasal Cavity Using Homorganic Nasal-Stop Sequences: A Preliminary R eportHansang ParkThis study provides a new method of extracting the filter characteristics of the nasal cavity. Korean lenis stops are realized as voiced in the homorganic nasal-lenis stop sequences between vowels. Since the only difference between the two members of the homorganic nasal- lenis stop sequences, such as [mb], [nd], and [ g], is whether the passage to the nasal cavity is open or not, the subtraction of the LPC spectrum of the voiced stop from that of the preceding nasal leads to the filter characteristics of the nasal cavity of an individual speaker regardless of place of articulation. The results suggest that various attempts should be made to extract a robust filter characteristics of the nasal cavity by giving variation to LPC coefficients and by paying particular attention to speech samples. This study is significant in that it provides a preliminary report about a new method of extracting the filter characteristics of the nasal cavity.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2001년도 춘계학술대회 논문집
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• pp.15-19
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• 2001

This paper describes effectiveness and characteristics of 3 P(point) task analysis as a new Ergonomic and Kansei design method for extracting user demand especially. The key point in 3 P task analysis is to describe the flow of tasks and extract any problems in each task. A solution of a problem means a user demand. 3 P task analysis cal eliminate an oversight of check items by examining the users' information processing level. The suers' information processing level was divided into the following three stages for problem extraction: acquirement of information ---> understanding and judgment ---> operation. Three stages has fourteenth cues such as difficulty of seeing, no emphasis, mapping for extracting problems. To link analysis results to the formulation of a product concept. I added a column on the right side of the table for writing the requirements (user demand) to resolve the problems extracted from each task. The requirements are extracted by using seventh cues. Finally 3 P task analysis was compared with group interview to make the characteristics of 3 P task analysis, especially extracting user demand, clear.

• 스마트미디어저널
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• 제10권1호
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• pp.39-46
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• 2021

본 연구는 뉴스 기사에서 기사문을 구성하는 문장별 중요도를 고려하여 요약문을 추출하는 방법에 관한 것으로 문장 중요도에 영향을 주는 특성으로 중심 문장(Topic Sentence)일 확률, 기사 제목 및 다른 문장과의 유사도, 문장 위치에 따른 가중치를 추출하여 문장 중요도를 계산하는 방법을 제안한다. 이때, 중심 문장(Topic Sentence)은 일반 문장과는 구별되는 특징을 가질 것이라는 가설을 세우고, 딥러닝 기반 분류 모델을 학습시켜 입력 문장에 대한 중심 문장 확률값을 구한다. 또한 사전학습된 ELMo 언어 모델을 활용하여 문맥 정보를 반영한 문장 벡터값을 기준으로 문장간 유사도를 계산하여 문장 특성으로 추출한다. LSTM 및 BERT 모델의 중심 문장 분류성능은 정확도 93%, 재현율 96.22%, 정밀도 89.5%로 높은 분석 결과가 나왔으며, 이렇게 추출된 문장 특성을 결합하여 문장별 중요도를 계산한 결과, 기존 TextRank 알고리즘과 비교하여 중심 문장 추출 성능이 10% 정도 개선된 것을 확인할 수 있었다.

• 대한본초학회지
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• 제26권4호
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• pp.89-94
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• 2011

Objective : Kyenegum has been frequently used for characterizing digestive symptoms in the traditional and oriental medicines. This study was conducted to investigate the characteristics of extracts from velvet antlers using the 4 different kinds of extracting methods. Methods : The extracts of velvet antlers were extracted using a $65^{\circ}C$ DW (9hrs), a Kyenegum crude enzyme, a $121^{\circ}C$ DW (2hrs), and a Kyenegum protease. To evaluate the characteristic of velvet antler extracts, we examined the brix, soluble solid, amino acid, mineral composition, and collagen protein. Results : As a result of the comparisons of velvet antlers extracted by the traditional extraction and the crude enzyme of kyenegum, the brix and soluble solid showed the higher contents for kyenegum enzymes. Also, mineral contents of the extracted velvet antlers were higher, particularly in Ca and P for those. The contents of collagen protein, hydroxyproline and hydroxylysine, were found to be more than twice in kyenegum protease compared with other extracting methods. Conclusion : These results indicated that the Kyenegum crude enzyme and protease are very effective to extract of velvet antlers.

• International Journal of Contents
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• 제2권3호
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• pp.27-32
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• 2006

We present an effective algorithm for automatic tracing of retinal vessel structure and vascular landmark extraction of bifurcations and ending points. In this paper we deal with vascular patterns from RGB images for personal identification. Vessel tracing algorithms are of interest in a variety of biometric and medical application such as personal identification, biometrics, and ophthalmic disorders like vessel change detection. However eye surface vasculature tracing in RGB images has many problems which are subject to improper illumination, glare, fade-out, shadow and artifacts arising from reflection, refraction, and dispersion. The proposed algorithm on vascular tracing employs multi-stage processing of ten-layers as followings: Image Acquisition, Image Enhancement by gray scale retinal image enhancement, reducing background artifact and illuminations and removing interlacing minute characteristics of vessels, Vascular Structure Extraction by connecting broken vessels, extracting vascular structure using eight directional information, and extracting retinal vascular structure, and Vascular Landmark Extraction by extracting bifurcations and ending points. The results of automatic retinal vessel extraction using jive different thresholds applied 34 eye images are presented. The results of vasculature tracing algorithm shows that the suggested algorithm can obtain not only robust and accurate vessel tracing but also vascular landmarks according to thresholds.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.379-382
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• 1997

This paper introduces a new vision technique for extracting roof edges of polyhedra having specularly reflecting surfaces. There have been many previous works on object recognition using edge information. But they can not be applied to specular objects since it is hard to acquire reliable camera images of specular objects. If there is a method which can extract the edges of specular objects, it is possible to apply edge-based recognition algorithms to specular objects. To acquire the reliable edge images of specular objects, scanned double pass retroreflection method is proposed, whose main physical characteristic is curvature-sensitive. This utility of the physical characteristic is motivated by the idea that roof edges can be characterized as local surfaces of high curvature. In this paper, the optical characteristics of double pass retroreflection are discussed and a series of simulation studies are performed to verify and analyze the sensor characteristics. The results from a series of simulations show the effectiveness of the proposed method.

• 센서학회지
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• 제32권2호
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• pp.105-109
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• 2023

In this study, we present a power-efficient driving method for gas sensor systems based on the analysis of input signal characteristics. The analysis of the gas sensor output signal characteristics in the frequency domain shows that most of the signal portions are distributed in a relatively low frequency region when extracting the gas sensor signal, which can lead to further performance improvement of the gas sensor system. Therefore, the proposed gas signal extracting technique changes the operating frequency of the read-out circuit based on the frequency characteristics of the output signal of the gas sensor, resulting in a reduction of power consumption at the whole system level. The proposed sensing technique, which can be applied to a general-purpose commercial gas sensor system, was implemented in a printed circuit board (PCB) to verify its effectiveness at the commercial level.

• 디지털산업정보학회논문지
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• 제14권4호
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• pp.35-45
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• 2018

Users are sharing many of contents such as text, image, video, and so on in SNS. There are various information as like as personal interesting, opinion, and relationship in social media contents. Therefore, many of recommendation systems or search systems are being developed through analysis of social media contents. In order to extract subject-related topics of social context being collected from social media channels in developing those system, it is necessary to develop ontologies for semantic analysis. However, it is difficult to develop formal ontology because social media contents have the characteristics of non-formal data. Therefore, we develop a social topic system based on semantic and subject correlation. First of all, an extracting system of social topic based on semantic relationship analyzes semantic correlation and then extracts topics expressing semantic information of corresponding social context. Because the possibility of developing formal ontology expressing fully semantic information of various areas is limited, we develop a self-extensible architecture of ontology for semantic correlation. And then, a classifier of social contents and feed back classifies equivalent subject's social contents and feedbacks for extracting social topics according semantic correlation. The result of analyzing social contents and feedbacks extracts subject keyword, and index by measuring the degree of association based on social topic's semantic correlation. Deep Learning is applied into the process of indexing for improving accuracy and performance of mapping analysis of subject's extracting and semantic correlation. We expect that proposed system provides customized contents for users as well as optimized searching results because of analyzing semantic and subject correlation.

• 대한전자공학회논문지SP
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• 제46권1호
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• pp.79-86
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• 2009

본 논문에서는 자연지진음과 인공지진음 특성 분석을 위해 스펙트럼 기울기 파라미터 추출을 위한 알고리즘을 제안하였다. 신뢰성을 높이기 위해 다양한 지역에서 실험을 실시하였고 제안한 알고리즘을 이용하여 실험 데이터로부터 자연지진음과 인공지진음의 기울기 지수를 추출함으로써 특성을 분석하였다. 실험 및 분석결과 자연지진음이 인공지진음보다 스펙트럼에서 고주파 감쇠가 크고 저주파대역에 집중되어 있어 자연지진음의 기울기 지수가 인공지진음의 기울기 지수보다 높은 것으로 나타났다.

• 한국식품영양학회지
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• 제27권1호
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• pp.89-98
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• 2014

In this study, soybean is used to produce soymilk according to various extracting methods and heating time. Specifically, the soy slurry is being filtered before being heated, or heated before being filtered. Following that the soymilk produced is freeze-dried to be powdered, and then, the quality characteristics of the powdered soymilk are mutually compared to determine the applicability of various food additives. The freeze-dried soymilk powder shows 2.03~6.35% of moisture content, and in terms of unit quantity, retained more proteins, which suggests that the ratio of protein extraction is higher than any other nutrients. Accordingly, the protein coefficient is significantly higher in soymilk powder being heated and processed than in raw soybeans. In particular, protein coefficient is the highest in the soymilk which is heated for 20 minutes before being filtered (SHBF20). The longer the heating time was, the trypsin inhibitor (TI) tended to be far less active. Such an inactivation seems to be more apparent in the "SHAF" soymilk powder than "SHBF" soymilk powder. Because protein had to be denaturated by heating for soymilk, the nitrogen solubility index (NSI) of soymilk powder is decreased considerably, while the protein digestibility, water absorption, emulsification and foaming activity all increase. Oil absorption tends to decrease slightly. As discussed above, the soymilk heated for 10 minutes after being filtered (SHAF10) and the soymilk heated for 20 minutes before being filtered (SHBF20) show optimum processing conditions for soymilk powder.