• 제목/요약/키워드: true rate

검색결과 533건 처리시간 0.023초

Comparison of In Vitro Digestion Kinetics of Cup-Plant and Alfalfa

  • Han, K.J.;Albrecht, K.A.;Mertens, D.R.;Kim, D.A.
    • Asian-Australasian Journal of Animal Sciences
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    • 제13권5호
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    • pp.641-644
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    • 2000
  • In vitro true digestibility of cup-plant (Silphium perfoliatum L.) is higher than other alternative forages and comparative to alfalfa (Medicago sativa L.) even at the high neutral detergent fiber (NDF) concentration. This study was conducted to determine whether the digestion kinetic parameters of cup-plant could explain high in vitro true digestibility of cup-plant at the several NDF levels. Cup-plant and alfalfa were both collected in Arlington and Lancaster, Wisconsin to meet the NDF content within 40 to 50% range. The collected samples were incubated with rumen juice to investigate the digestion kinetics at 3, 6, 9, 14, 20, 28, 36, 48, and 72 h. Kinetics was estimated by the model $R=D_0\;e-k(t-L)+U$ where R is residue remaining at time t, and $D_0$ is digestible fraction, k is digestion rate constant, L is discrete lag time, and U is indigestible fraction. Parameters of the model were estimated by the direct nonlinear least squares (DNLS) method. Digestion rate and potential extent of digestion were not statistically different in either forage. However, alfalfa had shorter lag time (p<0.05). The indigestible fraction increased with maturation in alfalfa and in cup-plant (p<0.05). The ratio of indigestible fraction to acid detergent lignin (ADL) was higher in cup-plant than in alfalfa (p<0.05). From the results, alfalfa is probably digested more rapidly than cup-plant, however, cup-plant maintains higher digestibility with maturation due to a relatively slower increase of indigestible fraction in NDF.

콘크리트 균열 탐지를 위한 딥 러닝 기반 CNN 모델 비교 (Comparison of Deep Learning-based CNN Models for Crack Detection)

  • 설동현;오지훈;김홍진
    • 대한건축학회논문집:구조계
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    • 제36권3호
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    • pp.113-120
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    • 2020
  • The purpose of this study is to compare the models of Deep Learning-based Convolution Neural Network(CNN) for concrete crack detection. The comparison models are AlexNet, GoogLeNet, VGG16, VGG19, ResNet-18, ResNet-50, ResNet-101, and SqueezeNet which won ImageNet Large Scale Visual Recognition Challenge(ILSVRC). To train, validate and test these models, we constructed 3000 training data and 12000 validation data with 256×256 pixel resolution consisting of cracked and non-cracked images, and constructed 5 test data with 4160×3120 pixel resolution consisting of concrete images with crack. In order to increase the efficiency of the training, transfer learning was performed by taking the weight from the pre-trained network supported by MATLAB. From the trained network, the validation data is classified into crack image and non-crack image, yielding True Positive (TP), True Negative (TN), False Positive (FP), False Negative (FN), and 6 performance indicators, False Negative Rate (FNR), False Positive Rate (FPR), Error Rate, Recall, Precision, Accuracy were calculated. The test image was scanned twice with a sliding window of 256×256 pixel resolution to classify the cracks, resulting in a crack map. From the comparison of the performance indicators and the crack map, it was concluded that VGG16 and VGG19 were the most suitable for detecting concrete cracks.

방광 팬텀 제작을 통한 충만여부에 따른 방광 주변 병변에 대한 영상 평가 (Development of Bladder Phantom and Image Evaluation of Lesion in the Vicinity according to Filling and Empty Bladder)

  • 박찬록;김재일;이홍재;김진의
    • 핵의학기술
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    • 제20권1호
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    • pp.24-27
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    • 2016
  • 방광 주변에 병변이 있는 환자의 경우 소변의 충만으로 방광 주변에 병변 평가의 영향이 있기 때문에 방광 팬텀을 직접 제작하여 방광 충만 여부에 따라 주변 병변이 미치는 영향을 평가하고자 한다. Biograph mCT40 (siemens, germany)을 사용하여 6개의 insert에 각각 14.8 MBq ($400{\mu}Ci$), Background 110 MBq (3 mCi), 방광에 74 MBq (2 mCi)를 주입하였다. NEMA IEC body 팬텀을 이용하여 고무풍선을 방광으로 대체하고 6개의 insert를 방광 주변 병변으로 설정하고, %BV, SUV, peak count rate의 영상평가 인자를 이용하여 비교하였다. % BV는 방광으로부터 거리가 멀수록 감소하는 것을 확인하였다. 방광으로부터 거리에 따른 hot sphere는 방광의 충만여부에 따라 $7.8{\pm}3.8%$의 SUV 차이가 났다. 방광으로부터의 거리가 0.4 cm 이하까지 방광을 비웠을 경우 평균 카운트가 약 14% 높게 측정되었으며, true count는 38% 감소한 반면, single count는 44%, random count는 61% 감소하였다. 그리고 그 이상의 거리에서는 큰 변화를 보이지 않았다. 그러므로 방광에 찬 소변이 주변 병변에 영향을 미치는 것을 확인하였고, 방광으로부터 거리가 가까울수록 영향이 크다는 것을 확인하였다. 방광이나 방광 주변에 병변이 있는 환자뿐만 아니라 PET-CT 검사를 하는 모든 환자에 있어 방광을 비우고 검사를 하는 것이 정확한 검사를 하는데 도움을 제공해 줄 것으로 사료된다.

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시그마포인트 칼만필터를 이용한 순환신경망 학습 및 채널등화 (A Recurrent Neural Network Training and Equalization of Channels using Sigma-point Kalman Filter)

  • 권오신
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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    • pp.3-5
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    • 2007
  • This paper presents decision feedback equalizers using a recurrent neural network trained algorithm using extended Kalman filter(EKF) and sigma-point Kalman filter(SPKF). EKF is propagated, analytically through the first-order linearization of the nonlinear system. This can introduce large errors in the true posterior mean and covariance of the Gaussian random variable. The SPKF addresses this problem by using a deterministic sampling approach. The features of the proposed recurrent neural equalizer And we investigate the bit error rate(BER) between EKF and SPKF.

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Maximum Likelihood Estimation of Continuous-time Diffusion Models for Exchange Rates

  • Choi, Seungmoon;Lee, Jaebum
    • East Asian Economic Review
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    • 제24권1호
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    • pp.61-87
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    • 2020
  • Five diffusion models are estimated using three different foreign exchange rates to find an appropriate model for each. Daily spot exchange rates expressed as the prices of 1 euro, 1 British pound and 100 Japanese yen in US dollars, respectively denoted by USD/EUR, USD/GBP, and USD/100JPY, are used. The maximum likelihood estimation method is implemented after deriving an approximate log-transition density function (log-TDF) of the diffusion processes because the true log-TDF is unknown. Of the five models, the most general model is the best fit for the USD/GBP, and USD/100JPY exchange rates, but it is not the case for the case of USD/EUR. Although we could not find any evidence of the mean-reverting property for the USD/EUR exchange rate, the USD/GBP, and USD/100JPY exchange rates show the mean-reversion behavior. Interestingly, the volatility function of the USD/EUR exchange rate is increasing in the exchange rate while the volatility functions of the USD/GBP and USD/100Yen exchange rates have a U-shape. Our results reveal that more care has to be taken when determining a diffusion model for the exchange rate. The results also imply that we may have to use a more general diffusion model than those proposed in the literature when developing economic theories for the behavior of the exchange rate and pricing foreign currency options or derivatives.

오염입자의 부착상태가 시각적인 세정효과에 미치는 영향 (State of Stain Particle's ADhesion and Its Influence on Visual Consequence of Soil-Removal)

  • 신영선
    • 대한가정학회지
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    • 제20권2호
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    • pp.45-51
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    • 1982
  • Degree of separation and adhesion of dye and stain particles has been measured usually by the rate of reflection of light. However, it could be proved that the relation between the quantity of stain and the rate of reflection greatly varied with kinds of stain and states of adhesion. For this study, several pieces of cotton and polyester having different states of stain adhesion were prepared by staining them with two kinds of artificial stain different in color: Ferric Oxide and Ferric Oxynate. Every piece went through soilremoval test which employed two surfactants: Anionic LAS and Cationic M2-100. After the operation, relations between quantity of pre-soilremoval stain and rate of reflection were measured, as well as those between quantity of post-soilremoval stain and rate of reflection. Rate of reflection and quantity of stain were not proportional in measurement to the pieces stained with Ferric Oxide and Ferric Oxynate. The consequence was also the same with cotton and polyester. That held true of the fat-stained textile. With the same quantity of stain, rate of reflection varied according to the magnitude of stain particles, and the state of adhesion influenced the magnitude of stain particles a great deal.

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A constitutive model for fiber-reinforced extrudable fresh cementitious paste

  • Zhou, Xiangming;Li, Zongjin
    • Computers and Concrete
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    • 제8권4호
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    • pp.371-388
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    • 2011
  • In this paper, time-continuous constitutive equations for strain rate-dependent materials are presented first, among which those for the overstress and the consistency viscoplastic models are considered. By allowing the stress states to be outside the yield surface, the overstress viscoplastic model directly defines the flow rule for viscoplastic strain rate. In comparison, a rate-dependent yield surface is defined in the consistency viscoplastic model, so that the standard Kuhn-Tucker loading/unloading condition still remains true for rate-dependent plasticity. Based on the formulation of the consistency viscoplasticity, a computational elasto-viscoplastic constitutive model is proposed for the short fiber-reinforced fresh cementitious paste for extrusion purpose. The proposed constitutive model adopts the von-Mises yield criterion, the associated flow rule and nonlinear strain rate-hardening law. It is found that the predicted flow stresses of the extrudable fresh cementitious paste agree well with experimental results. The rate-form constitutive equations are then integrated into an incremental formulation, which is implemented into a numerical framework based on ANSYS/LS-DYNA finite element code. Then, a series of upsetting and ram extrusion processes are simulated. It is found that the predicted forming load-time data are in good agreement with experimental results, suggesting that the proposed constitutive model could describe the elasto-viscoplastic behavior of the short fiber-reinforced extrudable fresh cementitious paste.

Building Linked Big Data for Stroke in Korea: Linkage of Stroke Registry and National Health Insurance Claims Data

  • Kim, Tae Jung;Lee, Ji Sung;Kim, Ji-Woo;Oh, Mi Sun;Mo, Heejung;Lee, Chan-Hyuk;Jeong, Han-Young;Jung, Keun-Hwa;Lim, Jae-Sung;Ko, Sang-Bae;Yu, Kyung-Ho;Lee, Byung-Chul;Yoon, Byung-Woo
    • Journal of Korean Medical Science
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    • 제33권53호
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    • pp.343.1-343.8
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    • 2018
  • Background: Linkage of public healthcare data is useful in stroke research because patients may visit different sectors of the health system before, during, and after stroke. Therefore, we aimed to establish high-quality big data on stroke in Korea by linking acute stroke registry and national health claim databases. Methods: Acute stroke patients (n = 65,311) with claim data suitable for linkage were included in the Clinical Research Center for Stroke (CRCS) registry during 2006-2014. We linked the CRCS registry with national health claim databases in the Health Insurance Review and Assessment Service (HIRA). Linkage was performed using 6 common variables: birth date, gender, provider identification, receiving year and number, and statement serial number in the benefit claim statement. For matched records, linkage accuracy was evaluated using differences between hospital visiting date in the CRCS registry and the commencement date for health insurance care in HIRA. Results: Of 65,311 CRCS cases, 64,634 were matched to HIRA cases (match rate, 99.0%). The proportion of true matches was 94.4% (n = 61,017) in the matched data. Among true matches (mean age 66.4 years; men 58.4%), the median National Institutes of Health Stroke Scale score was 3 (interquartile range 1-7). When comparing baseline characteristics between true matches and false matches, no substantial difference was observed for any variable. Conclusion: We could establish big data on stroke by linking CRCS registry and HIRA records, using claims data without personal identifiers. We plan to conduct national stroke research and improve stroke care using the linked big database.

수정 합성 HMT를 이용한 왜곡불변 패턴 인식 (Distortion invariant pattern recognition using Modified synthetic HMT)

  • 현영길;김종찬;김정우;도양회;김수중
    • 한국통신학회논문지
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    • 제24권7B호
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    • pp.1361-1369
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    • 1999
  • 다중 물체의 왜곡불변 인식을 위하여 수정합성형태소를 이용한 HMT를 제안하였다. HMT에서 중요한 문제 중의 하나는 오인식을 줄이고 다양한 모양의 왜곡된 물체를 검출하기 위하여 필요한 최적의 형태소를 결정하는 것이다. 제안된 형태소 합성방법은 이런 문제를 해결하는데 적절하다. 한 방법은 집합이론만을 이용하여 참영상의 형태소를 다단계로 합성하는 것이고, 다른 한 방법은 집합이론과 SDF합성법을 이용하여 참영상과 거짓영상의 형태소를 다단계로 합성하는 것이다. 시뮬레이션을 통하여 제안된 방법이 동일 집단의 왜곡된 물체를 인식하고, 다른 집단의 유사한 물체를 구분하여 인식할 수 있음을 확인하였다.

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교차점과 오차행렬을 이용한 사람 검출용 퍼지 분류기 진화 설계 (Evolutionary Design of Fuzzy Classifiers for Human Detection Using Intersection Points and Confusion Matrix)

  • 이준용;박소연;최병석;신승용;이주장
    • 제어로봇시스템학회논문지
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    • 제16권8호
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    • pp.761-765
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    • 2010
  • This paper presents the design of optimal fuzzy classifier for human detection by using genetic algorithms, one of the best-known meta-heuristic search methods. For this purpose, encoding scheme to search the optimal sequential intersection points between adjacent fuzzy membership functions is originally presented for the fuzzy classifier design for HOG (Histograms of Oriented Gradient) descriptors. The intersection points are sequentially encoded in the proposed encoding scheme to reduce the redundancy of search space occurred in the combinational problem. Furthermore, the fitness function is modified with the true-positive and true-negative of the confusion matrix instead of the total success rate. Experimental results show that the two proposed approaches give superior performance in HOG datasets.