• Title/Summary/Keyword: frequency filtering

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A study on optical coherence tomography system using optical fiber (광섬유를 이용한 광영상 단층촬영기에 관한연구)

  • 양승국;박양하;장원석;오상기;김현덕;김기문
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2004.04a
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    • pp.5-9
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    • 2004
  • In this paper, we studied the OCT(Optical Coherence Tomography) system which it has been extensively studied because of having some advantages such as high resolution cross-sectional images, low cost, and small size configuration. A basic principle of OCT system is Michelson interferometer. The characteristics of light source determine the resolution and the transmission depth. As a results, the light source have a commercial SLD with a central wavelength of 1,285 nm and FWHM(Full Width at Half Maximum) of 35.3 nm. The optical delay line part is necessary to equal of the optical path length with scattered light or reflected light from sample. In order to equal the optical path length, the stage which is attached to reference mirror is moved linearly by step motor And the interferometer is configured with the Michelson interferometer using single mod fiber, the scanner can be focused of the sample by using the reference arm. Also, the 2-dimensional cross-sectional images were measured with scanning the transverse direction of the sample by using step motor. After detecting the internal signal of lateral direction at a paint of sample, scanner is moved to obtain the cross-sectional image of 2-demensional by using step motor. Photodiode has been used which has high detection sensitivity, excellent noise characteristic, and dynamic range from 800 nm to 1,700 nm. It is detected mixed small signal between noise and interference signal with high frequency After filtering and amplifying this signal, only envelope curve of interference signal is detected. And then, cross-sectional image is shown through converting this signal into digitalized signal using A/D converter. The resolution of the OCT system is about 30$\mu\textrm{m}$ which corresponds to the theoretical resolution. Also, the cross-sectional image of ping-pong ball is measured. The OCT system is configured with Michelson interferometer which has a low contrast because of reducing the power of feedback interference light. Such a problem is overcomed by using the improved inteferometer. Also, in order to obtain the cross-sectional image within a short time, it is necessary to reduce the measurement time for improving the optical delay line.

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The Effect of Water Conveyance of Boryeong Dam on Structural Changes of Benthic Macroinvertebrates Community (보령댐 도수가 저서성 대형무척추동물 군집구조 변화에 미치는 영향)

  • An, Chae-Hui;Han, Jung-Soo;Choi, Jun-Kil;Lee, Hwang-Goo
    • Korean Journal of Environment and Ecology
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    • v.32 no.4
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    • pp.381-391
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    • 2018
  • The purpose of this study is to investigate the influence of artificial disturbances occurring during water conveyance frequency on benthic macro-invertebrate by comparing and analyzing data before and after the construction of Boryeong dam in Boryeong-si, Chungcheongnam-do. We conducted the survey eight times in four points from April 2016 to September 2017. A total of 13,447 individuals from 125 species, 70 families, 19 orders, 7 classes, and 4 phyla were collected. The result of the community analysis showed that the dominant index was 0.55 (${\pm}0.07$) to 0.47 (${\pm}0.08$), diversity index was 2.06 (${\pm}0.26$) to 2.23 (${\pm}0.28$), evenness index was 0.69 (${\pm}0.05$) to 0.70 (${\pm}0.04$), and richness index was 3.43 (${\pm}0.72$) to 4.03 (${\pm}0.91$). After conveyance, the dominance decreased while the diversity, evenness, and richness increased. The result of the functional group analysis showed the portion of scrapers, filtering-collectors increased while that of shredders, gathering-collectors decreased in the functional feeding group and that the proportion of climbers and clingers increased while that of burrowers and sprawlers decreased in the habitat orientation group. The result of analysis of community stability showed that St. 1 and St. 2 decreased resistance and resilience after conveyance and new species appeared in the III characteristics group while St. 3 and St. 4 did not show much difference. The result of multidimensional scaling analysis showed that the variation of similarity was the highest at St. 1 after conveyance, and the variation of similarity at St. 4 was the lowest.

Comparison of Ultrasound Image Quality using Edge Enhancement Mask (경계면 강조 마스크를 이용한 초음파 영상 화질 비교)

  • Jung-Min, Son;Jun-Haeng, Lee
    • Journal of the Korean Society of Radiology
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    • v.17 no.1
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    • pp.157-165
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    • 2023
  • Ultrasound imaging uses sound waves of frequencies to cause physical actions such as reflection, absorption, refraction, and transmission at the edge between different tissues. Improvement is needed because there is a lot of noise due to the characteristics of the data generated from the ultrasound equipment, and it is difficult to grasp the shape of the tissue to be actually observed because the edge is vague. The edge enhancement method is used as a method to solve the case where the edge surface looks clumped due to a decrease in image quality. In this paper, as a method to strengthen the interface, the quality improvement was confirmed by strengthening the interface, which is the high-frequency part, in each image using an unsharpening mask and high boost. The mask filtering used for each image was evaluated by measuring PSNR and SNR. Abdominal, head, heart, liver, kidney, breast, and fetal images were obtained from Philips epiq5g and affiniti70g and Alpinion E-cube 15 ultrasound equipment. The program used to implement the algorithm was implemented with MATLAB R2022a of MathWorks. The unsharpening and high-boost mask array size was set to 3*3, and the laplacian filter, a spatial filter used to create outline-enhanced images, was applied equally to both masks. ImageJ program was used for quantitative evaluation of image quality. As a result of applying the mask filter to various ultrasound images, the subjective image quality showed that the overall contour lines of the image were clearly visible when unsharpening and high-boost mask were applied to the original image. When comparing the quantitative image quality, the image quality of the image to which the unsharpening mask and the high boost mask were applied was evaluated higher than that of the original image. In the portal vein, head, gallbladder, and kidney images, the SNR, PSNR, RMSE and MAE of the image to which the high-boost mask was applied were measured to be high. Conversely, for images of the heart, breast, and fetus, SNR, PSNR, RMSE and MAE values were measured as images with the unsharpening mask applied. It is thought that using the optimal mask according to the image will help to improve the image quality, and the contour information was provided to improve the image quality.

A New Approach to Automatic Keyword Generation Using Inverse Vector Space Model (키워드 자동 생성에 대한 새로운 접근법: 역 벡터공간모델을 이용한 키워드 할당 방법)

  • Cho, Won-Chin;Rho, Sang-Kyu;Yun, Ji-Young Agnes;Park, Jin-Soo
    • Asia pacific journal of information systems
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    • v.21 no.1
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    • pp.103-122
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    • 2011
  • Recently, numerous documents have been made available electronically. Internet search engines and digital libraries commonly return query results containing hundreds or even thousands of documents. In this situation, it is virtually impossible for users to examine complete documents to determine whether they might be useful for them. For this reason, some on-line documents are accompanied by a list of keywords specified by the authors in an effort to guide the users by facilitating the filtering process. In this way, a set of keywords is often considered a condensed version of the whole document and therefore plays an important role for document retrieval, Web page retrieval, document clustering, summarization, text mining, and so on. Since many academic journals ask the authors to provide a list of five or six keywords on the first page of an article, keywords are most familiar in the context of journal articles. However, many other types of documents could not benefit from the use of keywords, including Web pages, email messages, news reports, magazine articles, and business papers. Although the potential benefit is large, the implementation itself is the obstacle; manually assigning keywords to all documents is a daunting task, or even impractical in that it is extremely tedious and time-consuming requiring a certain level of domain knowledge. Therefore, it is highly desirable to automate the keyword generation process. There are mainly two approaches to achieving this aim: keyword assignment approach and keyword extraction approach. Both approaches use machine learning methods and require, for training purposes, a set of documents with keywords already attached. In the former approach, there is a given set of vocabulary, and the aim is to match them to the texts. In other words, the keywords assignment approach seeks to select the words from a controlled vocabulary that best describes a document. Although this approach is domain dependent and is not easy to transfer and expand, it can generate implicit keywords that do not appear in a document. On the other hand, in the latter approach, the aim is to extract keywords with respect to their relevance in the text without prior vocabulary. In this approach, automatic keyword generation is treated as a classification task, and keywords are commonly extracted based on supervised learning techniques. Thus, keyword extraction algorithms classify candidate keywords in a document into positive or negative examples. Several systems such as Extractor and Kea were developed using keyword extraction approach. Most indicative words in a document are selected as keywords for that document and as a result, keywords extraction is limited to terms that appear in the document. Therefore, keywords extraction cannot generate implicit keywords that are not included in a document. According to the experiment results of Turney, about 64% to 90% of keywords assigned by the authors can be found in the full text of an article. Inversely, it also means that 10% to 36% of the keywords assigned by the authors do not appear in the article, which cannot be generated through keyword extraction algorithms. Our preliminary experiment result also shows that 37% of keywords assigned by the authors are not included in the full text. This is the reason why we have decided to adopt the keyword assignment approach. In this paper, we propose a new approach for automatic keyword assignment namely IVSM(Inverse Vector Space Model). The model is based on a vector space model. which is a conventional information retrieval model that represents documents and queries by vectors in a multidimensional space. IVSM generates an appropriate keyword set for a specific document by measuring the distance between the document and the keyword sets. The keyword assignment process of IVSM is as follows: (1) calculating the vector length of each keyword set based on each keyword weight; (2) preprocessing and parsing a target document that does not have keywords; (3) calculating the vector length of the target document based on the term frequency; (4) measuring the cosine similarity between each keyword set and the target document; and (5) generating keywords that have high similarity scores. Two keyword generation systems were implemented applying IVSM: IVSM system for Web-based community service and stand-alone IVSM system. Firstly, the IVSM system is implemented in a community service for sharing knowledge and opinions on current trends such as fashion, movies, social problems, and health information. The stand-alone IVSM system is dedicated to generating keywords for academic papers, and, indeed, it has been tested through a number of academic papers including those published by the Korean Association of Shipping and Logistics, the Korea Research Academy of Distribution Information, the Korea Logistics Society, the Korea Logistics Research Association, and the Korea Port Economic Association. We measured the performance of IVSM by the number of matches between the IVSM-generated keywords and the author-assigned keywords. According to our experiment, the precisions of IVSM applied to Web-based community service and academic journals were 0.75 and 0.71, respectively. The performance of both systems is much better than that of baseline systems that generate keywords based on simple probability. Also, IVSM shows comparable performance to Extractor that is a representative system of keyword extraction approach developed by Turney. As electronic documents increase, we expect that IVSM proposed in this paper can be applied to many electronic documents in Web-based community and digital library.