• Title/Summary/Keyword: Local feature

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The clinical observation of patient with Headache Treated by Trigger point acupuncture therapy (발통점(發通點)을 이용(利用)한 두통(頭痛) 치험례(治驗例) 보고(報告))

  • Lee Seung-Yeon;Kim Jang-Hyun
    • The Journal of Pediatrics of Korean Medicine
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    • v.12 no.1
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    • pp.133-143
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    • 1998
  • Myofascial pain syndrome is one of the pain syndrome resulted from myofascia which covered muscles and clinically characteristic feature by sensitive trigger point in skeletal muscles and referred pain reactivated by stimulating each trigger point. The origin of headache are local lesion such as head, chest, abdominal organ, systemic lesion with fever or in toxic state. the other factors are consciousness, personality, anxiety, depression, which cause muscle strain in physiological environment. The Oriental Medical therapy for headache has herb medication and acupuncture. especially acupuncture therapy has not only classical systemic acupuncture(體鍼) but also neo-acupuncture(新鍼) such as commonly using auricular acupuncture(耳鍼) and manual acupuncture (手鍼), recently trigger point acupuncture is used. The author analyzed 27 cases of patient with headache treated by trigger point acupuncture therapy in Dong-yu Oriental Medical Hospital from March 1st 1997 to February 28th 1998. The following results were obtained. 1. The sex ratio of the female was 59.26%(16 cases) and male was 40.74%(11 cases), the ratio of high school student was 62.96%(17cases) as first. 2. The headache duration ratio of 2-3 years was 37.04%(10 cases) as first, 1-2 years was 25.93%(7 cases) as second. 3. The portion ratio of whole headache was 33.33%(9 cases) as first, lateral headache was 29.63%(8 cases) as second 4. The combined symptoms ratio of anorexia was 40.74%(11 cases) as first, fatigue was 33.33%(9 cases) as second, neck stiffness and dizziness was each 25.93%(7 cases) as third. 5. The therapeutic duration ratio of below 1 week was 29.63%(8 cases) as first, 2-3 weeks was 22.22%(6 cases) as second, 1-2 weeks and 3-4 weeks was each 18.52%(5 cases) as third. 6. The ratio of family history was 11 cases(40.74%). mother with headache was 6 cases, father was 3 cases, and brothers & sisters was 2 cases. 7. The herb medication ratio of Chungsanggyuntongtang(淸上?痛湯) was 37.04%(10 cases), Kamiondamtang(加味溫膽湯) was 22.22%(6 cases), Hyangsapyunguisan(香砂平胃散) was 18.25%(5 cases) etc. 8. The remedial effect ratio of good was 25.93%(7 cases), fair was 48.15%(13 cases), not improved was 7.41%(2 cases), side effect was 3.70%(1 cases), and unknown was 14.81%(4 cases).

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Development of the Operating Cost Estimation Models to Evaluate the Validity of Urban Railway Investment (도시철도 투자타당성 평가를 위한 운영비용 추정모형 개발)

  • KIM, Dong Kyu;PARK, Shin Hyoung;KIM, Ki Hyuk
    • Journal of Korean Society of Transportation
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    • v.34 no.5
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    • pp.465-475
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    • 2016
  • Since inaccurate demand estimation for recent urban rail construction may result in financial burden to cities, precise prediction for operating cost as well as construction costs is necessary to avoid or reduce budget loss of the local or central government. The operating cost is directly related to the public fare and affect a policy to determine the rate system. Therefore, there is a pressing need to develop an estimating model for reliable operating cost of urban railway. This study introduces a new model to estimate the operating cost with new variables. It provides a better prediction in accuracy and reliability compared to the existing model, considering the feature of urban railway. For verification of our model, railway operation data from a few cities for the last five years were comprehensively examined to determine variables that affect the operating cost. The operating cost was estimated in a dummy regression model using five independent variables, which were average distance between stations, daily trains distance, total passenger capacity of a train in a train, driving mode(manned/unmanned), and investment type(financial/private).

The Environmental Preservation and Sustainable Use of Apsan(Mountain) in Daegu (대구 앞산의 환경보존과 지속가능한 이용)

  • Jeon, Young-Gweon
    • Journal of the Korean association of regional geographers
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    • v.12 no.6
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    • pp.645-655
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    • 2006
  • Apsan, as part of the main ecosystem of Daegu city, plays an important role for maintaining the environmental sustainability of the large city. Especially varieties of valuable resources, which are cultural, historical, biological, geomorphological and geological, are distributed around Apsan. Therefore the positive preservation plan is required. This paper aims to examine the environmental characteristics of Apsan and then suggests the following ideas for the environmental preservation and sustainable use of Apsan. 1) 'The New Map of Apsan' that includes more exact information needs to be produced. 2) The Apsan ecosystem management plan should be made under the precision natural ecology investigation. 3) For the protection of inanimate object resources, such as geographical feature and geology, the Geotourism Department needs to be established within Daegu metropolitan office of education or the tourism division of Daegu city government. 4) An effective environmental-impact-assessment system should be officially established. 5) the positive administrative and financial support system led by local NGOs is required for the Apsan environmental protection activities and education. 6) It is necessary to bring out into the open prayer sites to prevent forest fire. 7) 'The nature rest year system' enforcement is required to restore the damaged ecological space of Apsan.

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Accelerated Loarning of Latent Topic Models by Incremental EM Algorithm (점진적 EM 알고리즘에 의한 잠재토픽모델의 학습 속도 향상)

  • Chang, Jeong-Ho;Lee, Jong-Woo;Eom, Jae-Hong
    • Journal of KIISE:Software and Applications
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    • v.34 no.12
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    • pp.1045-1055
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    • 2007
  • Latent topic models are statistical models which automatically captures salient patterns or correlation among features underlying a data collection in a probabilistic way. They are gaining an increased popularity as an effective tool in the application of automatic semantic feature extraction from text corpus, multimedia data analysis including image data, and bioinformatics. Among the important issues for the effectiveness in the application of latent topic models to the massive data set is the efficient learning of the model. The paper proposes an accelerated learning technique for PLSA model, one of the popular latent topic models, by an incremental EM algorithm instead of conventional EM algorithm. The incremental EM algorithm can be characterized by the employment of a series of partial E-steps that are performed on the corresponding subsets of the entire data collection, unlike in the conventional EM algorithm where one batch E-step is done for the whole data set. By the replacement of a single batch E-M step with a series of partial E-steps and M-steps, the inference result for the previous data subset can be directly reflected to the next inference process, which can enhance the learning speed for the entire data set. The algorithm is advantageous also in that it is guaranteed to converge to a local maximum solution and can be easily implemented just with slight modification of the existing algorithm based on the conventional EM. We present the basic application of the incremental EM algorithm to the learning of PLSA and empirically evaluate the acceleration performance with several possible data partitioning methods for the practical application. The experimental results on a real-world news data set show that the proposed approach can accomplish a meaningful enhancement of the convergence rate in the learning of latent topic model. Additionally, we present an interesting result which supports a possible synergistic effect of the combination of incremental EM algorithm with parallel computing.

Acinetobacter pullorum sp. nov., Isolated from Chicken Meat

  • Elnar, Arxel G.;Kim, Min-Gon;Lee, Ju-Eun;Han, Rae-Hee;Yoon, Sung-Hee;Lee, Gi-Yong;Yang, Soo-Jin;Kim, Geun-Bae
    • Journal of Microbiology and Biotechnology
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    • v.30 no.4
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    • pp.526-532
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    • 2020
  • A bacterial strain, designated B301T and isolated from raw chicken meat obtained from a local market in Korea, was characterized and identified using a polyphasic taxonomic approach. Cells were gram-negative, non-motile, obligate-aerobic coccobacilli that were catalase-positive and oxidase-negative. The optimum growth conditions were 30℃, pH 7.0, and 0% NaCl in tryptic soy broth. Colonies were round, convex, smooth, and cream-colored on tryptic soy agar. Strain B301T has a genome size of 3,102,684 bp, with 2,840 protein-coding genes and 102 RNA genes. The 16S rRNA gene analysis revealed that strain B301T belongs to the genus Acinetobacter and shares highest sequence similarity (97.12%) with A. celticus ANC 4603T and A. sichuanensis WCHAc060041T. The average nucleotide identity and digital DNA-DNA hybridization values for closely related species were below the cutoff values for species delineation (95-96% and 70%, respectively). The DNA G+C content of strain B301T was 37.0%. The major respiratory quinone was Q-9, and the cellular fatty acids were primarily summed feature 3 (C16:1 ω6c/C16:1 ω7c), C16:0, and C18:1 ω9c. The major polar lipids were phosphatidylethanolamine, diphosphatidyl-glycerol, phosphatidylglycerol, and phosphatidyl-serine. The antimicrobial resistance profile of strain B301T revealed the absence of antibiotic-resistance genes. Susceptibility to a wide range of antimicrobials, including imipenem, minocycline, ampicillin, and tetracycline, was also observed. The results of the phenotypic, chemotaxonomic, and phylogenetic analyses indicate that strain B301T represents a novel species of the genus Acinetobacter, for which the name Acinetobacter pullorum sp. nov. is proposed. The type strain is B301T (=KACC 21653T = JCM 33942T).

Efficient Data Representation of Stereo Images Using Edge-based Mesh Optimization (윤곽선 기반 메쉬 최적화를 이용한 효율적인 스테레오 영상 데이터 표현)

  • Park, Il-Kwon;Byun, Hye-Ran
    • Journal of Broadcast Engineering
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    • v.14 no.3
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    • pp.322-331
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    • 2009
  • This paper proposes an efficient data representation of stereo images using edge-based mesh optimization. Mash-based two dimensional warping for stereo images mainly depends on the performance of a node selection and a disparity estimation of selected nodes. Therefore, the proposed method first of all constructs the feature map which consists of both strong edges and boundary lines of objects for node selection and then generates a grid-based mesh structure using initial nodes. The displacement of each nodal position is iteratively estimated by minimizing the predicted errors between target image and predicted image after two dimensional warping for local area. Generally, iterative two dimensional warping for optimized nodal position required a high time complexity. To overcome this problem, we assume that input stereo images are only horizontal disparity and that optimal nodal position is located on the edge include object boundary lines. Therefore, proposed iterative warping method performs searching process to find optimal nodal position only on edge lines along the horizontal lines. In the experiments, we compare our proposed method with the other mesh-based methods with respect to the quality by using Peak Signal to Noise Ratio (PSNR) according to the number of nodes. Furthermore, computational complexity for an optimal mesh generation is also estimated. Therefore, we have the results that our proposed method provides an efficient stereo image representation not only fast optimal mesh generation but also decreasing of quality deterioration in spite of a small number of nodes through our experiments.

Trend Analysis of Lunar Exploration Missions for Lunar Base Construction (달 기지 건설을 대비한 국내외 달 탐사 동향 분석)

  • Hong, Sungchul;Shin, Hyu-Soung
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.7
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    • pp.144-152
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    • 2018
  • Lunar exploration, which was led by the United States and the former Soviet Union, ceased in the 1970s. On the other hand, since massive lunar ice deposits and rare resources were found in 1990s, European Union, China, Japan, and India began to participate in lunar exploration to secure future lunar resource as well as to construct a lunar base. In the near future, it is expected that national space agencies and private industries will participate in the lunar exploration together. Their missions will include the exploration and sample return of lunar resources. Lunar resources have a close relationship with the lunar in-situ resource utilization (ISRU). To construct a lunar base, it is inevitable to bring huge amounts of resources from Earth. Water and oxygen, however, will need to be produced from local lunar resources and lunar terrain feature will need to be used to construct the lunar base. Therefore, in this paper, the global trends on lunar exploration and lunar construction technology are investigated and compared along with the ISRU technology to support human exploration and construct a lunar base on the Moon's surface.

Data Mining based Forest Fires Prediction Models using Meteorological Data (기상 데이터를 이용한 데이터 마이닝 기반의 산불 예측 모델)

  • Kim, Sam-Keun;Ahn, Jae-Geun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.8
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    • pp.521-529
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    • 2020
  • Forest fires are one of the most important environmental risks that have adverse effects on many aspects of life, such as the economy, environment, and health. The early detection, quick prediction, and rapid response of forest fires can play an essential role in saving property and life from forest fire risks. For the rapid discovery of forest fires, there is a method using meteorological data obtained from local sensors installed in each area by the Meteorological Agency. Meteorological conditions (e.g., temperature, wind) influence forest fires. This study evaluated a Data Mining (DM) approach to predict the burned area of forest fires. Five DM models, e.g., Stochastic Gradient Descent (SGD), Support Vector Machines (SVM), Decision Tree (DT), Random Forests (RF), and Deep Neural Network (DNN), and four feature selection setups (using spatial, temporal, and weather attributes), were tested on recent real-world data collected from Gyeonggi-do area over the last five years. As a result of the experiment, a DNN model using only meteorological data showed the best performance. The proposed model was more effective in predicting the burned area of small forest fires, which are more frequent. This knowledge derived from the proposed prediction model is particularly useful for improving firefighting resource management.

Contactless Fingerprint Recognition Based on LDP (LDP 기반 비접촉식 지문 인식)

  • Kang, Byung-Jun;Park, Kang-Ryoung;Yoo, Jang-Hee;Moon, Ki-Young;Kim, Jeong-Nyeo;Shin, Jae-Ho
    • Journal of Korea Multimedia Society
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    • v.13 no.9
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    • pp.1337-1347
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    • 2010
  • Fingerprint recognition is a biometric technology to identify individual by using fingerprint features such ridges and valleys. Most fingerprint systems perform the recognition based on minutiae points after acquiring a fingerprint image from contact type sensor. They have an advantage of acquiring a clear image of uniform size by touching finger on the sensor. However, they have the problems of the image quality can be reduced in case of severely dry or wet finger due to the variations of touching pressure and latent fingerprint on the sensor. To solve these problems, the contactless capturing devices for a fingerprint image was introduced in previous works. However, the accuracy of detecting minutiae points and recognition performance are reduced due to the degradation of image quality by the illumination variation. So, this paper proposes a new LDP-based fingerprint recognition method. It can effectively extract fingerprint patterns of iterative ridges and valleys. After producing histograms of the binary codes which are extracted by the LDP method, chi square distance between the enrolled and input feature histograms is calculated. The calculated chi square distance is used as the score of fingerprint recognition. As the experimental results, the EER of the proposed approach is reduced by 0.521% in comparison with that of the previous LBP-based fingerprint recognition approach.

Contrast Enhancement Using a Density based Sub-histogram Equalization Technique (밀도기반의 분할된 히스토그램 평활화를 통한 대비 향상 기법)

  • Yoon, Hyun-Sup;Han, Young-Joon;Hahn, Hern-Soo
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.46 no.1
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    • pp.10-21
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    • 2009
  • In order to enhance the contrast in the regions where the pixels have similar intensities, this paper presents a new histogram equalization scheme. Conventional global equalization schemes over-equalizes those regions so that too bright or dark pixels are resulted and local equalization schemes produce unexpected discontinuities at the boundaries of the blocks. The proposed algorithm segments the original histogram into sub-histograms with reference to brightness level and equalizes each sub-histogram with the limited extents of equalization considering its mean and variance. The final image is determined as the weighted sum of the equalized images obtained by using the sub-histogram equalizations. By limiting the maximum and minimum ranges of equalization operations on individual sub-histograms, the over-equalization effect is eliminated. Also the result image does not miss feature information in low density histogram region since the remaining these area is applied separating equalization. This paper includes how to determine the segmentation points in the histogram. The proposed algorithm has been tested with more than 100 images having various contrast in the images and the results are compared to the conventional approaches to show its superiority.