• Title/Summary/Keyword: orthogonal least square

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Nuclear magnetic resonance-based metabolomics analysis and characteristics of beef in different fattening periods

  • Jeong, Jin Young;Baek, Youl-Chang;Ji, Sang Yun;Oh, Young Kyun;Cho, Soohyun;Seo, Hyun-Woo;Kim, Minseok;Lee, Hyun-Jeong
    • Journal of Animal Science and Technology
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    • v.62 no.3
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    • pp.321-333
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    • 2020
  • Beef quality is influenced by the fattening period. Therefore, meat metabolomics profiles from the different fattening periods (e.g., short-term vs. long-term) were analyzed for identify potential indicators using nuclear magnetic resonance. Additionally, blood, free fatty acid, sensory, and mineral compositions in Korean steers were determined. Blood, free fatty acid, and mineral concentrations showed significant differences between short-term and long-term groups that were fed different diets. However, there were no sensory differences in the two fattening groups. Additionally, the metabolic profiles of meats were clearly separated based on multivariate orthogonal partial least square discriminant analysis. Six metabolites of variable importance in the projection plot were identified and showed high sensitivity as candidate markers for meat characteristics. In particular, lactate, carnosine, and creatine could be directly linked to scientific indicators of the fattening stage (31 vs. 28 mo) of meat. Our findings suggest that the metabolomics approach could be a powerful method for the detection of novel signatures underlying the managing period of beef.

DETERMINATION OF THE INVARIANT POINT OF THE KOREAN VLBI NETWORK RADIO TELESCOPES: FIRST RESULTS AT THE ULSAN AND TAMNA OBSERVATORIES

  • Yoo, Sung-Moon;Jung, Taehyun;Lee, Sung-Mo;Yoon, Ha Su;Park, Han-Earl;Chung, Jong-Kyun;Roh, Kyoung-Min;Wi, Seog Oh;Cho, Jungho;Byun, Do-Young
    • Journal of The Korean Astronomical Society
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    • v.51 no.5
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    • pp.143-153
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    • 2018
  • We present the first results of the invariant point (IVP) coordinates of the KVN Ulsan and Tamna radio telescopes. To determine the IVP coordinates in the geocentric frame (ITRF2014), a coordinate transformation method from the local frame, in which it is possible to survey using the optical instrument, to the geocentric frame was adopted. The least-square circles are fitted in three dimensions using the Gauss-Newton method to determine the azimuth and elevation axes in the local frame. The IVP in the local frame is defined as the mean value of the intersection points of the azimuth axis and the orthogonal vector between the azimuth and elevation axes. The geocentric coordinates of the IVP are determined by obtaining the seven transformation parameters between the local frame and the east-north-up (ENU) geodetic frame. The axis-offset between the azimuth and elevation axes is also estimated. To validate the results, the variation of coordinates of the GNSS station installed at KVN Ulsan was compared to the movement of the IVP coordinates over 9 months, showing good agreement in both magnitude and direction. This result will provide an important basis for geodetic and astrometric applications.

Automatic Object Recognition in 3D Measuring Data (3차원 측정점으로부터의 객체 자동인식)

  • Ahn, Sung-Joon
    • The KIPS Transactions:PartB
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    • v.16B no.1
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    • pp.47-54
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    • 2009
  • Automatic object recognition in 3D measuring data is of great interest in many application fields e.g. computer vision, reverse engineering and digital factory. In this paper we present a software tool for a fully automatic object detection and parameter estimation in unordered and noisy point clouds with a large number of data points. The software consists of three interactive modules each for model selection, point segmentation and model fitting, in which the orthogonal distance fitting (ODF) plays an important role. The ODF algorithms estimate model parameters by minimizing the square sum of the shortest distances between model feature and measurement points. The local quadric surface fitted through ODF to a randomly touched small initial patch of the point cloud provides the necessary initial information for the overall procedures of model selection, point segmentation and model fitting. The performance of the presented software tool will be demonstrated by applying to point clouds.

Active mass driver control system for suppressing wind-induced vibration of the Canton Tower

  • Xu, Huai-Bing;Zhang, Chun-Wei;Li, Hui;Tan, Ping;Ou, Jin-Ping;Zhou, Fu-Lin
    • Smart Structures and Systems
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    • v.13 no.2
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    • pp.281-303
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    • 2014
  • In order to suppress the wind-induced vibrations of the Canton Tower, a pair of active mass driver (AMD) systems has been installed on the top of the main structure. The structural principal directions in which the bending modes of the structure are uncoupled are proposed and verified based on the orthogonal projection approach. For the vibration control design in the principal X direction, the simplified model of the structure is developed based on the finite element model and modified according to the field measurements under wind excitations. The AMD system driven by permanent magnet synchronous linear motors are adopted. The dynamical models of the AMD subsystems are determined according to the open-loop test results by using nonlinear least square fitting method. The continuous variable gain feedback (VGF) control strategy is adopted to make the AMD system adaptive to the variation in the intensity of wind excitations. Finally, the field tests of free vibration control are carried out. The field test results of AMD control show that the damping ratio of the first vibration mode increases up to 11 times of the original value without control.

Analysis of metabolomic patterns in thoroughbreds before and after exercise

  • Jang, Hyun-Jun;Kim, Duk-Moon;Kim, Kyu-Bong;Park, Jeong-Woong;Choi, Jae-Young;Oh, Jin Hyeog;Song, Ki-Duk;Kim, Suhkmann;Cho, Byung-Wook
    • Asian-Australasian Journal of Animal Sciences
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    • v.30 no.11
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    • pp.1633-1642
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    • 2017
  • Objective: Evaluation of exercise effects in racehorses is important in horseracing industry and animal health care. In this study, we compared metabolic patterns between before and after exercise to screen metabolic biomarkers for exercise effects in thoroughbreds. Methods: The concentration of metabolites in muscle, plasma, and urine was measured by $^1H$ nuclear magnetic resonance (NMR) spectroscopy analysis and the relative metabolite levels in the three samples were compared between before and after exercise. Subsequently, multivariate data analysis based on the metabolic profiles was performed using orthogonal partial least square discriminant analysis (OPLS-DA) and variable important plots and t-test was used for basic statistical analysis. Results: From $^1H$ NMR spectroscopy analysis, 35, 25, and 34 metabolites were detected in the muscle, plasma, and urine. Aspartate, betaine, choline, cysteine, ethanol, and threonine were increased over 2-fold in the muscle; propionate and trimethylamine were increased over 2-fold in the plasma; and alanine, glycerol, inosine, lactate, and pyruvate were increased over 2-fold whereas acetoacetate, arginine, citrulline, creatine, glutamine, glutarate, hippurate, lysine, methionine, phenylacetylglycine, taurine, trigonelline, trimethylamine, and trimethylamine N-oxide were decreased below 0.5-fold in the urine. The OPLS-DA showed clear separation of the metabolic patterns before and after exercise in the muscle, plasma, and urine. Statistical analysis showed that after exercise, acetoacetate, arginine, glutamine, hippurate, phenylacetylglycine trimethylamine, trimethylamine N-oxide, and trigonelline were significantly decreased and alanine, glycerol, inosine, lactate, and pyruvate were significantly increased in the urine (p<0.05). Conclusion: In conclusion, we analyzed integrated metabolic patterns in the muscle, plasma, and urine before and after exercise in racehorses. We found changed patterns of metabolites in the muscle, plasma, and urine of racehorses before and after exercise.

Coherent Multiple Target Angle-Tracking Algorithm (코히어런트 다중 표적 방위 추적 알고리즘)

  • Kim Jin-Seok;Kim Hyun-Sik;Park Myung-Ho;Nam Ki-Gon;Hwang Soo-Bok
    • The Journal of the Acoustical Society of Korea
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    • v.24 no.4
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    • pp.230-237
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    • 2005
  • The angle-tracking of maneuvering targets is required to the state estimation and classification of targets in underwater acoustic systems. The Problem of angle-tracking multiple closed and crossing targets has been studied by various authors. Sword et al. Proposed a multiple target an91e-tracking algorithm using angular innovations of the targets during a sampling Period are estimated in the least square sense using the most recent estimate of the sensor output covariance matrix. This algorithm has attractive features of simple structure and avoidance of data association problem. Ryu et al. recently Proposed an effective multiple target angle-tracking algorithm which can obtain the angular innovations of the targets from a signal subspace instead of the sensor output covariance matrix. Hwang et al. improved the computational performance of a multiple target angle-tracking algorithm based on the fact that the steering vector and the noise subspace are orthogonal. These algorithms. however. are ineffective when a subset of the incident sources are coherent. In this Paper, we proposed a new multiple target angle-tracking algorithm for coherent and incoherent sources. The proposed algorithm uses the relationship between source steering vectors and the signal eigenvectors which are multiplied noise covariance matrix. The computer simulation results demonstrate the improved Performance of the Proposed algorithm.

Comparative metabolomic analysis in horses and functional analysis of branched chain (alpha) keto acid dehydrogenase complex in equine myoblasts under exercise stress

  • Jeong-Woong, Park;Kyoung Hwan, Kim;Sujung, Kim;Jae-rung, So;Byung-Wook, Cho;Ki-Duk, Song
    • Journal of Animal Science and Technology
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    • v.64 no.4
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    • pp.800-811
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    • 2022
  • The integration of metabolomics and transcriptomics may elucidate the correlation between the genotypic and phenotypic patterns in organisms. In equine physiology, various metabolite levels vary during exercise, which may be correlated with a modified gene expression pattern of related genes. Integrated metabolomic and transcriptomic studies in horses have not been conducted to date. The objective of this study was to detect the effect of moderate exercise on the metabolomic and transcriptomic levels in horses. In this study, using nuclear magnetic resonance (NMR) spectroscopy, we analyzed the concentrations of metabolites in muscle and plasma; we also determined the gene expression patterns of branched chain (alpha) keto acid dehydrogenase kinase complex (BCKDK), which encodes the key regulatory enzymes in branched-chain amino acid (BCAA) catabolism, in two breeds of horses, Thoroughbred and Jeju, at different time intervals. The concentrations of metabolites in muscle and plasma were measured by 1H NMR (nuclear magnetic resonance) spectroscopy, and the relative metabolite levels before and after exercise in the two samples were compared. Subsequently, multivariate data analysis based on the metabolic profiles was performed using orthogonal partial least square discriminant analysis (OPLS-DA), and variable important plots and t-test were used for basic statistical analysis. The stress-induced expression patterns of BCKDK genes in horse muscle-derived cells were examined using quantitative reverse transcription polymerase chain reaction (qPCR) to gain insight into the role of transcript in response to exercise stress. In this study, we found higher concentrations of aspartate, leucine, isoleucine, and lysine in the skeletal muscle of Jeju horses than in Thoroughbred horses. In plasma, compared with Jeju horses, Thoroughbred horses had higher levels of alanine and methionine before exercise; whereas post-exercise, lysine levels were increased. Gene expression analysis revealed a decreased expression level of BCKDK in the post-exercise period in Thoroughbred horses.