• MALSORI
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• no.53
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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.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.05a
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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.

• Smart Media Journal
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• v.10 no.1
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• pp.39-46
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• 2021

This study is about a method of extracting a summary from a news article in consideration of the importance of each sentence constituting the article. We propose a method of calculating sentence importance by extracting the probabilities of topic sentence, similarity with article title and other sentences, and sentence position as characteristics that affect sentence importance. At this time, a hypothesis is established that the Topic Sentence will have a characteristic distinct from the general sentence, and a deep learning-based classification model is trained to obtain a topic sentence probability value for the input sentence. Also, using the pre-learned ELMo language model, the similarity between sentences is calculated based on the sentence vector value reflecting the context information and extracted as sentence characteristics. The topic sentence classification performance of the LSTM and BERT models was 93% accurate, 96.22% recall, and 89.5% precision, resulting in high analysis results. As a result of calculating the importance of each sentence by combining the extracted sentence characteristics, it was confirmed that the performance of extracting the topic sentence was improved by about 10% compared to the existing TextRank algorithm.

• The Korea Journal of Herbology
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• v.26 no.4
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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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• v.2 no.3
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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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• 1997.10a
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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.

• Journal of Sensor Science and Technology
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• v.32 no.2
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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.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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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.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.1
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• pp.79-86
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• 2009

This paper proposed an algorithm for extracting spectrum gradient parameter to analyze the characteristics of natural seismic sounds and artificial seismic sounds. The experiment was performed in various area to raise the reliability. The characteristics of natural seismic sounds and artificial seismic sounds were analyzed by extracting gradient indexes of artificial seismic sounds and natural seismic sounds from the data of experiment by using the proposed algorithm. As a result of the experiment and the analysis, gradient indexes of natural seismic sounds were higher than that of artificial seismic sounds because natural seismic sounds had higher attenuation at high-frequency than artificial seismic sounds did and natural seismic sounds were concentrated in low-frequency band.

• The Korean Journal of Food And Nutrition
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• v.27 no.1
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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.