• Title/Summary/Keyword: Coefficient Matrix

Search Result 844, Processing Time 0.022 seconds

Quantitative Analysis of Lysophosphatidic Acid in Human Plasma by Tandem Mass Spectrometry

  • Kim, Ho-Hyun;Yoon, Hye-Ran;Pyo, Dong-Jin
    • Bulletin of the Korean Chemical Society
    • /
    • v.23 no.8
    • /
    • pp.1139-1143
    • /
    • 2002
  • Analysis of lysophosphatidic acids (LPAs) is of clinical importance as they can serve a potential marker for ovarian and other gynecological cancers and obesity. It is critically important to develop a highly sensitive and specific method for the early detection of gynecological cancers to improve the overall outcome of this disease. We have established a novel quantification method of LPAs in human plasma by negative ionization tandem mass spectrometry (MS-MS) using multiple reaction monitoring (MRM) mode without the conventional TLC step. Protein-bound lipids, LPAs in plasma were extracted with methanol : chloroform (2:1) containing LPA C14:0 as an internal standard under acidic condition. Following back extraction with chloroform and water, the centrifuged lower phase was evaporated and reconstituted in methanol. The reconstituted solution was directly injected into electrospray source of MS/MS. For MRM mode, Q1 ions selected were m/z 409, 433, 435, 437 and 457 which corresponds to molecular mass [M-H]- of C16:0, C18:2, C18:1, C18:0 and C20:4 LPA, respectively. Q2 ions selected for MRM were m/z 79, phosphoryl product. Using MS/MS with MRM mode, all the species of LPAs were completely separated from plasma matrix without severe interferences. This method allowed simultaneous detection and quantification of different species of LPAs in a plasma over a linear dynamic range of 0.01-25 ㎛olL-1 . The detection limit of the method was 0.3 pmol/mL, with a correlation coefficient of 0.9983 in most LPAs analyzed. When applied to the plasmas of normal and gynecological cancer patients, this new method differentiated two different groups by way of total LPA level.

Application of Levenberg Marquardt Method for Calibration of Unsteady Friction Model for a Pipeline System (관수로 부정류 마찰항 보정을 위한 Levenberg Marquardt 방법의 적용연구)

  • Park, Jo Eun;Kim, Sang Hyun
    • Journal of Korea Water Resources Association
    • /
    • v.46 no.4
    • /
    • pp.389-400
    • /
    • 2013
  • In this study, a conventional pipeline unsteady friction model has been integrated into Levenberg Marquardt method to calibrate friction coefficient in a pipeline system. The method of characteristics has been employed as the modeling platform for the frequency dependant model of unsteady friction. In order to obtain Hessian and Jacobian matrix for optimization, the direct differentiation of pressure to friction factor was calculated and sensitivities to friction for heads and discharges were formulated for implementation to the integration constant in the characteristic method. Using a hypothetical simple pipeline system, time series of pressure, introduced by a sudden valve closure, were obtained for various Reynolds numbers. Convergency in fiction factors were evaluated both in steady and unsteady friction models. The comparison of calibration performance between the proposed method and genetic algorithm indicates that faster and stabler behaviour of Levenberg Marquardt method than those of evolutionary calibration.

Fuzzy Inference Systems Based on FCM Clustering Algorithm for Nonlinear Process (비선형 공정을 위한 FCM 클러스터링 알고리즘 기반 퍼지 추론 시스템)

  • Park, Keon-Jun;Kang, Hyung-Kil;Kim, Yong-Kab
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
    • /
    • v.5 no.4
    • /
    • pp.224-231
    • /
    • 2012
  • In this paper, we introduce a fuzzy inference systems based on fuzzy c-means clustering algorithm for fuzzy modeling of nonlinear process. Typically, the generation of fuzzy rules for nonlinear processes have the problem that the number of fuzzy rules exponentially increases. To solve this problem, the fuzzy rules of fuzzy model are generated by partitioning the input space in the scatter form using FCM clustering algorithm. The premise parameters of the fuzzy rules are determined by membership matrix by means of FCM clustering algorithm. The consequence part of the rules is expressed in the form of polynomial functions and the coefficient parameters of each rule are determined by the standard least-squares method. And lastly, we evaluate the performance and the nonlinear characteristics using the data widely used in nonlinear process.

Corrosion and Nanomechanical Behaviors of 16.3Cr-0.22N-0.43C-1.73Mo Martensitic Stainless Steel

  • Ghosh, Rahul;Krishna, S. Chenna;Venugopal, A.;Narayanan, P. Ramesh;Jha, Abhay K.;Ramkumar, P.;Venkitakrishnan, P.V.
    • Corrosion Science and Technology
    • /
    • v.15 no.6
    • /
    • pp.281-289
    • /
    • 2016
  • The effect of nitrogen on the electrochemical corrosion and nanomechanical behaviors of martensitic stainless steel was examined using potentiodynamic polarization and nanoindentation test methods. The results indicate that partial replacement of carbon with nitrogen effectively improved the passivation and pitting corrosion resistance of conventional high-carbon and high- chromium martensitic steels. Post-test observation of the samples after a potentiodynamic test revealed a severe pitting attacks in conventional martensitic steel compared with nitrogen- containing martensitic stainless steel. This was shown to be due to (i) microstructural refinement results in retaining a high-chromium content in the matrix, and (ii) the presence of reversed austenite formed during the tempering process. Since nitrogen addition also resulted in the formation of a $Cr_2N$ phase as a process of secondary hardening, the hardness of the nitrogen- containing steel is slightly higher than the conventional martensitic stainless steel under tempered conditions, even though the carbon content is lowered. The added nitrogen also improved the wear resistance of the steel as the critical load (Lc2) is less, along with a lower scratch friction coefficient (SFC) when compared to conventional martensitic stainless steel such as AISI 440C.

Genetic Diversity and Phylogenetic Relationships among Microsporidian Isolates from the Indian Tasar Silkworm, Antheraea mylitta, as Revealed by RAPD Fingerprinting Technique

  • Hassan, Wazid;Nath, B. Surendra
    • International Journal of Industrial Entomology and Biomaterials
    • /
    • v.29 no.2
    • /
    • pp.169-178
    • /
    • 2014
  • In this study, we investigated genetic diversity of 22 microsporidian isolates infecting tropical tasar silkworm, Antheraea mylitta collected from various geographical forest locations in the state of Jharkhand, India, using polymerase chain reaction (PCR)-based marker assay: random amplified polymorphic DNA (RAPD). A type species, NIK-1s_mys was used as control for comparison. The shape of mature microsporidians was found to be oval to elongate, measuring 3.80 to $5.10{\mu}m$ in length and 2.56 to $3.30{\mu}m$ in width. Of the 20 RAPD primers screened, 16 primers generated reproducible profiles with 298 polymorphic fragments displaying high degree of polymorphism (97%). A total of 14 RAPD primers produced 45 unique putative genetic markers, which were used to differentiate the microsporidians. Calculation of genetic distance coefficients based on dice coefficient method and clustering with un-weighted pair group method using arithmetic average (UPGMA) analysis was conducted to unravel the genetic diversity of microsporidians infecting tasar silkworm. The similarity coefficients varied from 0.059 to 0.980. UPGMA analysis generated a dendrogram with four microsporidian groups, which appear to be different from each other as well as from NIK-1s_mys. Two-dimensional distribution based on Euclidean distance matrix also revealed considerable variability among different microsporidians identified from the tasar silkworms. Clustering of few microsporidian isolates was in accordance with the geographic origin. The results indicate that the RAPD profiles and specific/unique genetic markers can be used for differentiating as well as to identify different microsporidians with considerable accuracy.

Discriminant analysis of grain flours for rice paper using fluorescence hyperspectral imaging system and chemometric methods

  • Seo, Youngwook;Lee, Ahyeong;Kim, Bal-Geum;Lim, Jongguk
    • Korean Journal of Agricultural Science
    • /
    • v.47 no.3
    • /
    • pp.633-644
    • /
    • 2020
  • Rice paper is an element of Vietnamese cuisine that can be used to wrap vegetables and meat. Rice and starch are the main ingredients of rice paper and their mixing ratio is important for quality control. In a commercial factory, assessment of food safety and quantitative supply is a challenging issue. A rapid and non-destructive monitoring system is therefore necessary in commercial production systems to ensure the food safety of rice and starch flour for the rice paper wrap. In this study, fluorescence hyperspectral imaging technology was applied to classify grain flours. Using the 3D hyper cube of fluorescence hyperspectral imaging (fHSI, 420 - 730 nm), spectral and spatial data and chemometric methods were applied to detect and classify flours. Eight flours (rice: 4, starch: 4) were prepared and hyperspectral images were acquired in a 5 (L) × 5 (W) × 1.5 (H) cm container. Linear discriminant analysis (LDA), partial least square discriminant analysis (PLSDA), support vector machine (SVM), classification and regression tree (CART), and random forest (RF) with a few preprocessing methods (multivariate scatter correction [MSC], 1st and 2nd derivative and moving average) were applied to classify grain flours and the accuracy was compared using a confusion matrix (accuracy and kappa coefficient). LDA with moving average showed the highest accuracy at A = 0.9362 (K = 0.9270). 1D convolutional neural network (CNN) demonstrated a classification result of A = 0.94 and showed improved classification results between mimyeon flour (MF)1 and MF2 of 0.72 and 0.87, respectively. In this study, the potential of non-destructive detection and classification of grain flours using fHSI technology and machine learning methods was demonstrated.

Microsoft Kinect-based Indoor Building Information Model Acquisition (Kinect(RGB-Depth Camera)를 활용한 실내 공간 정보 모델(BIM) 획득)

  • Kim, Junhee;Yoo, Sae-Woung;Min, Kyung-Won
    • Journal of the Computational Structural Engineering Institute of Korea
    • /
    • v.31 no.4
    • /
    • pp.207-213
    • /
    • 2018
  • This paper investigates applicability of Microsoft $Kinect^{(R)}$, RGB-depth camera, to implement a 3D image and spatial information for sensing a target. The relationship between the image of the Kinect camera and the pixel coordinate system is formulated. The calibration of the camera provides the depth and RGB information of the target. The intrinsic parameters are calculated through a checker board experiment and focal length, principal point, and distortion coefficient are obtained. The extrinsic parameters regarding the relationship between the two Kinect cameras consist of rotational matrix and translational vector. The spatial images of 2D projection space are converted to a 3D images, resulting on spatial information on the basis of the depth and RGB information. The measurement is verified through comparison with the length and location of the 2D images of the target structure.

Nonuniform Delayless Subband Filter Structure with Tree-Structured Filter Bank (트리구조의 비균일한 대역폭을 갖는 Delayless 서브밴드 필터 구조)

  • 최창권;조병모
    • The Journal of the Acoustical Society of Korea
    • /
    • v.20 no.1
    • /
    • pp.13-20
    • /
    • 2001
  • Adaptive digital filters with long impulse response such as acoustic echo canceller and active noise controller suffer from slow convergence and computational burden. Subband techniques and multirate signal processing have been recently developed to improve the problem of computational complexity and slow convergence in conventional adaptive filter. Any FIR transfer function can be realized as a serial connection of interpolators followed by subfilters with a sparse impulse response. In this case, each interpolator which is related to the column vector of Hadamard matrix has band-pass magnitude response characteristics shifted uniformly. Subband technique using Hadamard transform and decimation of subband signal to reduce sampling rate are adapted to system modeling and acoustic noise cancellation In this paper, delayless subband structure with nonuniform bandwidth has been proposed to improve the performance of the convergence speed without aliasing due to decimation, where input signal is split into subband one using tree-structured filter bank, and the subband signal is decimated by a decimator to reduce the sampling rate in each channel, then subfilter with sparse impulse response is transformed to full band adaptive filter coefficient using Hadamard transform. It is shown by computer simulations that the proposed method can be adapted to general adaptive filtering.

  • PDF

Thermal and Mechanical Properties of Short Fiber-Reinforced Epoxy Composites (단섬유 강화 에폭시 복합재료의 열적/기계적 특성)

  • Huang, Guang-Chun;Lee, Chung-Hee;Lee, Jong-Keun
    • Polymer(Korea)
    • /
    • v.33 no.6
    • /
    • pp.530-536
    • /
    • 2009
  • A cycloaliphatic epoxy/acidic anhydride system incorporating short carbon fibers (SCF) and short glass fibers (SGF) was fabricated and thermal/mechanical properties were characterized. At low filler content both SCF- and SGF-reinforced composites showed a similar decrease in coefficient of thermal expansion (CTE), measured by a thermomechanical analyzer, with increasing loadings, above which SCF became more effective than SGF at reducing the CTE. Experimental CTE data for the SCF-reinforced composites is best described by the rule of mixtures at lower SCF contents and by the Craft-Christensen model at higher SCF contents. Storage modulus (E') at $30^{\circ}C$ and $180^{\circ}C$ was greatly enhanced for short fiber-filled composites compared to unfilled specimens, Scanning electron microscopy of the fracture surfaces indicated that the decreased CTE and the increased E' of the short fiber-reinforced composites resulted from good interfacial adhesion between the fibers and epoxy matrix.

Nonlinear Process Modeling Using Hard Partition-based Inference System (Hard 분산 분할 기반 추론 시스템을 이용한 비선형 공정 모델링)

  • Park, Keon-Jun;Kim, Yong-Kab
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
    • /
    • v.7 no.4
    • /
    • pp.151-158
    • /
    • 2014
  • In this paper, we introduce an inference system using hard scatter partition method and model the nonlinear process. To do this, we use the hard scatter partition method that partition the input space in the scatter form with the value of the membership degree of 0 or 1. The proposed method is implemented by C-Means clustering algorithm. and is used for the initial center values by means of binary split. by applying the LBG algorithm to compensate for shortcomings in the sensitive initial center value. Hard-scatter-partitioned input space forms the rules in the rule-based system modeling. The premise parameters of the rules are determined by membership matrix by means of C-Means clustering algorithm. The consequence part of the rules is expressed in the form of polynomial functions and the coefficient parameters of each rule are determined by the standard least-squares method. The data widely used in nonlinear process is used to model the nonlinear process and evaluate the characteristics of nonlinear process.