• Title/Summary/Keyword: 카파값

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Condenser Characteristics of Dielectric Soil Moisture Sensor (유전율 토양 수분 쎈서의 콘덴서 특성)

  • Oh, Yong-Taeg;Eorn, Ki-Cheol;Jo, In-Sang;Shin, Jae-Sung
    • Korean Journal of Soil Science and Fertilizer
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    • v.33 no.1
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    • pp.15-23
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    • 2000
  • RC oscillation method was applied to study the condenser characteristics of two metal sticks insulated by vinyl tube and used in the dielectric constant determinations of most soils. Its capacitance as influenced by the contacted ambient materials was measured as relative capacitance of the sensor sticks compared with the standard one on the RC oscillation circuit. According to the equivalent circuit of the sensor stick set, the measured capacitance was composed of a basic capacitance connected in parallel with sensor stick capacitance, which was composed of lineally connected vinyl tube capacitances and the sensing part capacitance. The dielectric constant (U) of the contacted ambient moist soil located in the sensing part around the sticks interrelated with the other parameters as following equation. $$\frac{1}{C-B}=\frac{k}{U}+Z$$ where C is the output total relative capacitance, B is the hidden and fixed basic relative capacitance, k is a constant related with U, and Z is a constant for the insulating vinyl tube capacitances determined by its thickness and dielectric constant. The constant k is determined by the spacing and length of sensor sticks. The Z value is theoretically an invariable constant, but it may become considerably bigger than the determined in lab if air tube is formed on the surface of sensor sticks by some shocks on them after their installation in soil. Due to the unstability of lab Z value, it may be better to revise it after sensor stick's installation in soil and no shaking shocks should be applied on them.

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Optimal Design of Friction Dampers based on the Story Shear Force Distribution of a Building Structure (경주지역에서 발생한 3개 지진의 지진원 및 지진파전파 매질특성에 관한 연구)

  • Jung, Je-Won;Kim, Jun-Kyoung
    • Journal of the Earthquake Engineering Society of Korea
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    • v.10 no.1 s.47
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    • pp.33-39
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    • 2006
  • Parameters including the seismic sources and the elastic wave propagation characteristics were analysed using the observed ground motions from 3 Kyoungju region earthquakes. The Levenberg-Marquardt algorithm was applied to invert all the variables non-linearly and simultaneously with S wave energy In frequency domain. Average stress drop of 3 events and local attenuation parameter ${\kappa}$ were estimated to about 48-bar and 0.0312 respectively. Regional attenuation parameter, Qo and ${\eta}$, were also estimated to be about 417 and 0.83. ${\kappa}$ values are much higher than that of EUS, even though smaller than that of WUS. All these values resultant from this study show that there are differences in some parameters of other studios due to differences in the governing equation. of acceleration motions

Quantitative Evaluation of Skin Condition According to Ayurvedic Constitution Classification (아유르베다 체질에 따른 피부 유형 분석)

  • Choi, Eun-Young
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.9
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    • pp.3375-3379
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    • 2010
  • Objective: The purpose of this study was to investigate the characteristics of facial skin parameters (hydration, lipid and pH) on forehead and cheek according to Ayurvedic constitution classification of Vata, Pitta and Kapha. The condition of hydration, lipid and pH in the facial skin was measured using non-invasive diagnostic technique. The collected data was analyzed with the SPSS 16.0 windows statistical program. Design: Eighty-nine Korean female subjects were recruited for this study and the average age of them was $19.9{\pm}0.84$ years. Three groups by the Ayurvedic constitution were classified by questionnaire. Results: There was a significant difference in hydration, lipid and pH according to Ayurvedic constitution. The measurement of hydration on the face depending on the constitution were shown in the order of Pitta, Kapha and Vata (p<0.001). The measurement of lipid on the face depending on the constitution were shown in the order of Kapha, Pitta and Vata (p<0.001, p<0.01). The measurement of pH on the face depending on the constitution were shown in the order of Kapha, Pitta and Vata (p<0.01). Conclusion: Facial skin surface seemed to be dependent on Ayurvedic constitution classification in Korean. These findings indicated that Ayurvedic constitution classification might be a useful esthetic treatment for caring facial skin in the future.

Named Entity Recognition for Patent Documents Based on Conditional Random Fields (조건부 랜덤 필드를 이용한 특허 문서의 개체명 인식)

  • Lee, Tae Seok;Shin, Su Mi;Kang, Seung Shik
    • KIPS Transactions on Software and Data Engineering
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    • v.5 no.9
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    • pp.419-424
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    • 2016
  • Named entity recognition is required to improve the retrieval accuracy of patent documents or similar patents in the claims and patent descriptions. In this paper, we proposed an automatic named entity recognition for patents by using a conditional random field that is one of the best methods in machine learning research. Named entity recognition system has been constructed from the training set of tagged corpus with 660,000 words and 70,000 words are used as a test set for evaluation. The experiment shows that the accuracy is 93.6% and the Kappa coefficient is 0.67 between manual tagging and automatic tagging system. This figure is better than the Kappa coefficient 0.6 for manually tagged results and it shows that automatic named entity tagging system can be used as a practical tagging for patent documents in replacement of a manual tagging.

Analysis of Diagnostic Performance of CT and EUS for Clinical TN Staging of Gastric Cancer (위암의 임상적 병기 설정을 위한 전산화단층촬영 및 초음파 내시경의 진단력 평가)

  • Shin, Ru-Mi;Lee, Ju-Hee;Lee, Moon-Soo;Park, Do-Joong;Kim, Hyung-Ho;Yang, Han-Kwang;Lee, Kuhn-Uk
    • Journal of Gastric Cancer
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    • v.9 no.4
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    • pp.177-185
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    • 2009
  • Purpose: Preoperative clinical staging of gastric cancer is very important for determining the treatment plans and predicting the prognosis. The previous reports regarding the accuracy of computed tomography or endoscopic ultrasound for the preoperative staging of gastric cancer have shown various outcomes. We analyzed the diagnostic performance of CT and EUS, which are important staging tools for the staging of TN gastric cancer. Materials and Methods: We retrospectively analyzed 1,174 patients who underwent gastrectomy for gastric cancer at Seoul National University Bundang Hostpital from May, 2003 to December, 2007. We derived the Kappa value to examine the agreement of the preoperative staging obtained from CT and EUS with the pathological staging. Results: The mean age of the 1,174 patients was $59.31{\pm}11.98$ years. Six hundred thirty seven patients had early gastric cancer and 536 had advanced gastric cancer. The diagnostic performance between CT and EUS for the T staging showed no significant difference between CT and EUS for the kappa values. The kappa values showed moderate agreement at 0.4039 (P=0.021) and 0.4201 (P=0.026), respectively. This suggests that there is no difference between the two examinations for the overall T staging. Analysis of the discrimination of mucosal and submucosal lesions with EUS showed an accuracy of 58.92% and a Kappa value of 0.206 (P<0.001), suggesting fair agreement and a lower diagnostic performance than expected. To differentiate lesions with stages higher than or equal to T2 or T3 from the lesion with stages lower than T2 or T3, respectively, adoption of the higher stage from the CT staging or the EUS staging showed a larger AUC of 0.84 than that from either stage alone. The CT-derived node stage had the higher diagnostic performance (68.55%) than that of the EUS-derived node stage (60.82%) for the node staging. Conclusion: The CT-derived stage and EUS-derived stage showed comparable results for determining the T stage of gastric cancer. Yet the higher stage of the two stages from CT and EUS most accurately discriminated between those lesions with stages higher than T2 and those lesions with stages lower than T2.

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Detection of Burned Forest Areas Using Landsat TM Images (Landsat TM 위성영상을 이용한 산불 발생지역의 탐지)

  • 김철민;이승호;노대균
    • Proceedings of the KSRS Conference
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    • 2001.03a
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    • pp.77-81
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    • 2001
  • 2000년 4월, 강원도 삼척일대에 크게 발생한 산불지역에 대해서 Landsat TM 인공위성 영상자료를 이용하여 산불의 피해지역을 조사분석하였다. 산불발생 전과 후의 2시기 위성영상을 이용하여 변화탐지 기법의 하나인 화상간차이법을 적용하였다. 분석결과 산불 발생지역의 탐지에는 NDVI를 유도하고 그 차이를 이용하는 것이 가장 탁월한 것으로 나타났다. 산불 피해지역을 구분하는 임계값을 표준편차$\times$0.9로 하였을 때, 현지조사 결과에 대한 전체정확도는 93.8%, 카파계수는 0.82로 매우 높았다.

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Classification of Heart Disease Using K-Nearest Neighbor Imputation (K-최근접 이웃 알고리즘을 활용한 심장병 진단 및 예측)

  • Park, Pyoung-Woo;Lee, Seok-Won
    • Proceedings of the Korea Information Processing Society Conference
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    • 2017.11a
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    • pp.742-745
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    • 2017
  • 본 논문은 심장질환 도메인에 데이터 마이닝 기법을 적용한 연구로, 기존 환자의 정보에 대하여 K-최근접 이웃 알고리즘을 통해 결측 값을 대체하고, 대표적인 예측 분류기인 나이브 베이지안, 소포트 벡터 머신, 그리고 다층 퍼셉트론을 적용하여 각각 결과를 비교 및 분석한다. 본 연구의 실험은 K 최적화 과정을 포함하고 10-겹 교차 검증 방식으로 수행되었으며, 비교 및 분석은 정확도와 카파 통계치를 통해 판별한다.

Assessment of Additional MRI-Detected Breast Lesions Using the Quantitative Analysis of Contrast-Enhanced Ultrasound Scans and Its Comparability with Dynamic Contrast-Enhanced MRI Findings of the Breast (유방자기공명영상에서 추가적으로 발견된 유방 병소에 대한 조영증강 초음파의 정량적 분석을 통한 진단 능력 평가와 동적 조영증강 유방 자기공명영상 결과와의 비교)

  • Sei Young Lee;Ok Hee Woo;Hye Seon Shin;Sung Eun Song;Kyu Ran Cho;Bo Kyoung Seo;Soon Young Hwang
    • Journal of the Korean Society of Radiology
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    • v.82 no.4
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    • pp.889-902
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    • 2021
  • Purpose To assess the diagnostic performance of contrast-enhanced ultrasound (CEUS) for additional MR-detected enhancing lesions and to determine whether or not kinetic pattern results comparable to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast can be obtained using the quantitative analysis of CEUS. Materials and Methods In this single-center prospective study, a total of 71 additional MR-detected breast lesions were included. CEUS examination was performed, and lesions were categorized according to the Breast Imaging-Reporting and Data System (BI-RADS). The sensitivity, specificity, and diagnostic accuracy of CEUS were calculated by comparing the BI-RADS category to the final pathology results. The degree of agreement between CEUS and DCE-MRI kinetic patterns was evaluated using weighted kappa. Results On CEUS, 46 lesions were assigned as BI-RADS category 4B, 4C, or 5, while 25 lesions category 3 or 4A. The diagnostic performance of CEUS for enhancing lesions on DCE-MRI was excellent, with 84.9% sensitivity, 94.4% specificity, and 97.8% positive predictive value. A total of 57/71 (80%) lesions had correlating kinetic patterns and showed good agreement (weighted kappa = 0.66) between CEUS and DCE-MRI. Benign lesions showed excellent agreement (weighted kappa = 0.84), and invasive ductal carcinoma (IDC) showed good agreement (weighted kappa = 0.69). Conclusion The diagnostic performance of CEUS for additional MR-detected breast lesions was excellent. Accurate kinetic pattern assessment, fairly comparable to DCE-MRI, can be obtained for benign and IDC lesions using CEUS.

The Land-cover Changes and Pattern Analysis in the Tidal Flats Using Post-classification Comparison Method: The Case of Taean Peninsula Region (선분류 후비교법을 이용한 간석지의 토지피복 변화 및 패턴 분석 - 태안반도 지역을 사례로 -)

  • Jang, Dong-Ho;Kim, Chan-Soo;Park, Ji-Hoon
    • Journal of the Korean Geographical Society
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    • v.45 no.2
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    • pp.275-292
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    • 2010
  • This study investigated the land-cover changes in the tidal flat of the Taean peninsula due to man-made environmental changes between 1972 and 2008, through time-series analysis based on a modified post-classification comparison method and multi-temporal satellite images. The analysis revealed that the land-cover of the tidal flat has changed from tidal flat to wetland and from wetland to paddy field between 1972 and 2008. Also, the pattern of detailed land-cover changes is as follows: tidal flat to wetland; lake and saltpan to bare land and paddy field. The accurate classification of each image is needed for the application of the post-classification comparison method. The overall accuracy of the classified images was found to be 95.33% on average, and the Kappa value was 0.941 on average.