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1

Klein, M., and R. Rabadán. ", orientifolds with vector structure." Nuclear Physics B 596, no. 1-2 (2001): 197–230. http://dx.doi.org/10.1016/s0550-3213(00)00698-2.

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2

Adamuščín, C., S. Dubnička, and A. Z. Dubničková. "Electromagnetic structure of vector mesons." EPJ Web of Conferences 81 (2014): 05001. http://dx.doi.org/10.1051/epjconf/20148105001.

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3

Witten, Edward. "Toroidal compactification without vector structure." Journal of High Energy Physics 1998, no. 02 (1998): 006. http://dx.doi.org/10.1088/1126-6708/1998/02/006.

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4

Tian, Tian, Min Li, Yiwei Ma, Song Li, Tao Geng, and Libo Yuan. "Highly sensitive vector bending sensor based on chirped core fiber structure." Chinese Optics Letters 23, no. 2 (2025): 021204. https://doi.org/10.3788/col202523.021204.

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5

Kurahara, Kohei, and Hiroyuki Nakanishi. "Magnetic Field Vector Structure of NGC6946." Galaxies 7, no. 2 (2019): 59. http://dx.doi.org/10.3390/galaxies7020059.

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Анотація:
We studied large-scale magnetic field reversals of a galaxy based on a magnetic vector map of NGC6946. The magnetic vector map was constructed based on the polarization maps in the C and X bands after the determination of the geometrical orientation of a disk with the use of an infrared image and the velocity field, according to the trailing spiral arm assumption. We examined the azimuthal variation of the magnetic vector and found that the magnetic pitch angle changes continually as a function of the azimuthal angle in the inter-arm region. However, the direction of the magnetic field had 180
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6

Williams, Robert A., Siegfried Krewald, and Kevin Linen. "Vector resonances and electromagnetic nucleon structure." Physical Review C 51, no. 2 (1995): 566–72. http://dx.doi.org/10.1103/physrevc.51.566.

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7

Bachas, Constantin, Massimo Bianchi, Ralph Blumenhagen, Dieter Lüst, and Timo Weigand. "Comments on orientifolds without vector structure." Journal of High Energy Physics 2008, no. 08 (2008): 016. http://dx.doi.org/10.1088/1126-6708/2008/08/016.

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8

Voigt, Hans-Michael. "Structure formation, vector optimization and evolution." Annual Review in Automatic Programming 12 (January 1985): 251–54. http://dx.doi.org/10.1016/0066-4138(85)90036-9.

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9

García-Pacheco, Francisco Javier, and Enrique Naranjo-Guerra. "Inner structure in real vector spaces." Georgian Mathematical Journal 27, no. 3 (2020): 361–66. http://dx.doi.org/10.1515/gmj-2018-0048.

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Анотація:
AbstractInternal points were introduced in the literature of topological vector spaces to characterize the finest locally convex vector topology. In this manuscript we generalize the concept of internal point in real vector spaces by introducing a type of points, called inner points, that allows us to provide an intrinsic characterization of linear manifolds, which was not possible by using internal points. We also characterize infinite dimensional real vector spaces by means of the inner points of convex sets. Finally, we prove that in convex sets containing internal points, the set of inner
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10

Kim, H. Ch, K. Goeke, T. Ledwig та S. i. Nam. "Photoproduction of the Θ + and its vector and axial-vector structure". Chinese Physics C 33, № 12 (2009): 1279–84. http://dx.doi.org/10.1088/1674-1137/33/12/038.

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11

Yinghui Pan, Jian Luo, Jinqiao Chen, and Bo Li. "A New Vector Identification Method Based on Vector Structure and Suffix Tree." Journal of Convergence Information Technology 5, no. 6 (2010): 73–78. http://dx.doi.org/10.4156/jcit.vol5.issue6.7.

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12

Ouchi, Masaya. "A structure theorem for prehomogeneous vector spaces." Fixed Point Theory 20, no. 1 (2019): 271–88. http://dx.doi.org/10.24193/fpt-ro.2019.1.18.

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13

Baxter, Laurence A., and Seung Min Lee. "Structure functions with finite minimal vector sets." Journal of Applied Probability 26, no. 1 (1989): 196–201. http://dx.doi.org/10.2307/3214331.

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Анотація:
A continuum structure function (CSF) y is a non-decreasing mapping from the unit hypercube to the unit interval. Define whereas γ (γ) < α for all y < x}, the set of minimal vectors to level α. This paper examines CSFs for which each Pα is finite. It is shown that if γ is such a CSF and X is a vector of independent random variables, the distribution of γ (X) is readily calculated. Further, if γ is an arbitrary right-continuous CSF, the distribution of γ (X) may be approximated arbitrarily closely by that of γ′(X) where γ′ is a right-continuous CSF for which each minimal vector set is fini
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14

Mandle, Anil Kumar. "Protein Structure Prediction Using Support Vector Machine." International Journal on Soft Computing 3, no. 1 (2012): 67–78. http://dx.doi.org/10.5121/ijsc.2012.3106.

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15

Amin, Mustafa A., Mudit Jain, Rohith Karur, and Philip Mocz. "Small-scale structure in vector dark matter." Journal of Cosmology and Astroparticle Physics 2022, no. 08 (2022): 014. http://dx.doi.org/10.1088/1475-7516/2022/08/014.

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Анотація:
Abstract We investigate the differences in the small-scale structure of vector dark matter (VDM) and scalar dark matter (SDM) using 3+1 dimensional simulations of single/mul­ticomponent Schrödinger-Poisson system. We find that the amount of wave interference, core-to-halo mass ratio (and its scatter), spin of the core, as well as the shape of the central regions of dark matter halos can distinguish VDM and SDM. Starting with a collection of idealized halos (self-gravitating solitons) as an initial condition, we show that the system dynamically evolves to an approximately spherically symmetric
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16

Agaev, S. S., K. Azizi, and H. Sundu. "Vector resonance X1(2900) and its structure." Nuclear Physics A 1011 (July 2021): 122202. http://dx.doi.org/10.1016/j.nuclphysa.2021.122202.

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17

FOLEY, D. H., and E. P. TORRES. "Population structure of an island malaria vector." Medical and Veterinary Entomology 20, no. 4 (2006): 393–401. http://dx.doi.org/10.1111/j.1365-2915.2006.00647.x.

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18

Baxter, Laurence A., and Seung Min Lee. "Structure functions with finite minimal vector sets." Journal of Applied Probability 26, no. 01 (1989): 196–201. http://dx.doi.org/10.1017/s0021900200041942.

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Анотація:
A continuum structure function (CSF) y is a non-decreasing mapping from the unit hypercube to the unit interval. Define whereas γ (γ) < α for all y < x}, the set of minimal vectors to level α. This paper examines CSFs for which each Pα is finite. It is shown that if γ is such a CSF and X is a vector of independent random variables, the distribution of γ (X) is readily calculated. Further, if γ is an arbitrary right-continuous CSF, the distribution of γ (X) may be approximated arbitrarily closely by that of γ′(X) where γ′ is a right-continuous CSF for which each minimal vector set
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19

Yandong, Wang, Gong Jianya, Huang Juntao, and Deng Yuejin. "The CNSDTF topological vector model and structure." Geo-spatial Information Science 2, no. 1 (1999): 104–8. http://dx.doi.org/10.1007/bf02826728.

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20

Souza, C. E. R., J. A. O. Huguenin, and A. Z. Khoury. "Topological phase structure of vector vortex beams." Journal of the Optical Society of America A 31, no. 5 (2014): 1007. http://dx.doi.org/10.1364/josaa.31.001007.

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21

Ward, J. J., L. J. McGuffin, B. F. Buxton, and D. T. Jones. "Secondary structure prediction with support vector machines." Bioinformatics 19, no. 13 (2003): 1650–55. http://dx.doi.org/10.1093/bioinformatics/btg223.

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22

Glucksman, Marc J., S. Bhattacharjee, and Lee Makowski. "Three-dimensional structure of a cloning vector." Journal of Molecular Biology 226, no. 2 (1992): 455–70. http://dx.doi.org/10.1016/0022-2836(92)90960-r.

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23

K�lm�n, B�la. "Vector magnetic field measurements and penumbral structure." Solar Physics 135, no. 2 (1991): 299–317. http://dx.doi.org/10.1007/bf00147502.

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24

Chu, Chi-Hsiang, Mong-Na Lo Huang, Shih-Feng Huang, and Ray-Bing Chen. "Bayesian structure selection for vector autoregression model." Journal of Forecasting 38, no. 5 (2019): 422–39. http://dx.doi.org/10.1002/for.2573.

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25

Ignatochkina, L. A. "Reeb vector field of almost contact metric structure as affine motion." Differential Geometry of Manifolds of Figures, no. 53 (2022): 59–67. http://dx.doi.org/10.5922/0321-4796-2022-53-6.

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Анотація:
Smooth manifold with almost contact metric structure (i. e., almost contact metric manifold) was considered in this paper. We used a modern version of Cartan’s method of external forms to conduct our study. We assume that its Reeb vector field is affine motion. We got formulas for components of second covariant differential of contact form for an arbi­trary almost contact metric manifold. Criterion for affine motion of Reeb vector field has been obtained for arbitrary almost contact metric mani­fold in this paper. It is proved that if Reeb vector field of almost contact structure is affine mot
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26

Chen, Jian Guo, and Zhao Guang Li. "Application of Support Vector Machine in Springback Forecasting for Steel Structure." Applied Mechanics and Materials 166-169 (May 2012): 1366–69. http://dx.doi.org/10.4028/www.scientific.net/amm.166-169.1366.

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Анотація:
Support vector machine is applied to springback forecasting for steel structure in the paper. In the steel structure, pressure-pad-force, friction coefficient and die filleted corner have a certain influence on springback amount.We employ BP neural network to compare with support vector machine to show the superiority of support vector machine in this study. Finally,we give the comparison of the prediction error of springback for steel structure between support vector machine and BP neural network. Evidently,the springback prediction for steel structure of support vector machine is better than
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27

IVAN, GHEORGHE, and VASILE POPUTA. "Vector subgroupoids. The computation of all vector subgroupoids of a modular vector groupoid." Carpathian Journal of Mathematics 28, no. 2 (2012): 265–70. http://dx.doi.org/10.37193/cjm.2012.02.10.

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A vector groupoid is an algebraic structure which combines the concepts of groupoid and vector space such that these are compatible. In this paper we study the vector subgroupoids. Also, the vector subgroupoids of a modular vector groupoid are computed.
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28

Jaouen, Vincent, Paulo González, Simon Stute, et al. "Variational segmentation of vector-valued images with gradient vector flow." IEEE Trans Image Process 23, no. 11 (2014): 4773–85. https://doi.org/10.1109/TIP.2014.2353854.

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In this paper, we extend the gradient vector flow field for robust variational segmentation of vector-valued images. Rather than using scalar edge information, we define a vectorial edge map derived from a weighted local structure tensor of the image that enables the diffusion of the gradient vectors in accurate directions through the 4D gradient vector flow equation. To reduce the contribution of noise in the structure tensor, image channels are weighted according to a blind estimator of contrast. The method is applied to biological volume delineation in dynamic PET imaging, and validated on
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29

Zmyślony, Roman, Ivan Zezula, and Arkadiusz Kozioł. "Application of Jordan Algebra for Testing Hypotheses About Structure of Mean Vector in Model with Block Compound Symmetric Covariance Structure." Electronic Journal of Linear Algebra 33 (May 16, 2018): 41–52. http://dx.doi.org/10.13001/1081-3810.3748.

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In this article authors derive test for structure of mean vector in model with block compound symmetric covariance structure for two-level multivariate observations. One possible structure is so called structured mean vector when its components remain constant over sites or over time points, so that mean vector is of the form $\boldsymbol{1}_{u}\otimes\boldsymbol{\mu}$ with $\boldsymbol{\mu}=(\mu_1,\mu_2,\ldots,\mu_m)'\in\mathbb{R}^m$. This hypothesis is tested against alternative of unstructured mean vector, which can change over sites or over time points.
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30

Zemliak, Alexander, and Jorge Espinosa-Garcia. "Analysis of the structure of different optimization strategies." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 39, no. 3 (2020): 583–93. http://dx.doi.org/10.1108/compel-09-2019-0370.

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Purpose In this paper, on the basis of a previously developed approach to circuit optimization, the main element of which is the control vector that changes the form of the basic equations, the structure of the control vector is determined, which minimizes CPU time. Design/methodology/approach The circuit optimization process is defined as a controlled dynamic system with a special control vector. This vector serves as the main tool for generalizing the problem of circuit optimization and produces a huge number of different optimization strategies. The task of finding the best optimization str
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31

Luschevskaya, E. V., O. E. Solovjeva, O. V. Teryaev, and M. S. Prokudin. "Magnetic structure of vector mesons in lattice QCD." EPJ Web of Conferences 182 (2018): 02077. http://dx.doi.org/10.1051/epjconf/201818202077.

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We have explored the response of the charged vector mesons on the external magnetic field. The g-factor of the charged vector ρ and K* mesons has been found. For the charged vector ρ meson the magnetic polarizability and hyperpolarizability have been calculated depending on the spin projection on the the magnetic field. We have estimated the intervals of the magnetic field for which the nonlinear terms in field give a significant contribution to the meson energy.
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32

Hyeon O, Seung. "Convexity Analysis of Option Embedded Bonds." Journal of Derivatives and Quantitative Studies 12, no. 1 (2004): 23–49. http://dx.doi.org/10.1108/jdqs-01-2004-b0002.

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Анотація:
Interest rate risk hedge strategies usually assume that term structure of interest rates in moving under a specific way. If a real term structure is moving differently from the assumed term structure movement, the interest rate risk hedge strategies assuming the special term structure movement may incur unexpected large loss for a bond portfolio manager. Hence an interest rate risk hedge strategy which could be effective under various types of term structure movements has been strongly needed by bond portfolio managers. Duration vector strategies have been developed to satisfy this practical n
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33

Zhao, Xiaoyu, and Shihua Fu. "Trajectory tracking approach to logical (control) networks." AIMS Mathematics 7, no. 6 (2022): 9668–82. http://dx.doi.org/10.3934/math.2022538.

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Анотація:
<abstract><p>Vector form expression of logical (control) networks is presented. From this aspect, the trajectory table is proposed to investigate Boolean networks. Based on it, the topology structure, controllability and observability of logical (control) networks are analyzed. Compared to the method of logical matrix, vector form expression called structure vector method decreases the computational complex. Numerical examples show that the complexity of the structure vector method is greatly reduced.</p></abstract>
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34

Piltan, Farzin, Bach Phi Duong, and Jong-Myon Kim. "Deep Learning-Based Adaptive Neural-Fuzzy Structure Scheme for Bearing Fault Pattern Recognition and Crack Size Identification." Sensors 21, no. 6 (2021): 2102. http://dx.doi.org/10.3390/s21062102.

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Анотація:
Bearings are complex components with onlinear behavior that are used to mitigate the effects of inertia. These components are used in various systems, including motors. Data analysis and condition monitoring of the systems are important methods for bearing fault diagnosis. Therefore, a deep learning-based adaptive neural-fuzzy structure technique via a support vector autoregressive-Laguerre model is presented in this study. The proposed scheme has three main steps. First, the support vector autoregressive-Laguerre is introduced to approximate the vibration signal under normal conditions and ex
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35

Lina Guo, Lina Guo, and Zhilie Tang Zhilie Tang. "Vectorial structure and beam quality of vector-vortex Bessel–Gauss beams in the farfield." Chinese Optics Letters 10, s1 (2012): S12601–312604. http://dx.doi.org/10.3788/col201210.s12601.

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36

Yang. "Modeling of Sound-structure Interactions for Designing a Piezoelectric Micro-Cantilever Acoustic Vector Sensor." Journal of the Acoustical Society of Korea 34, no. 2 (2015): 108. http://dx.doi.org/10.7776/ask.2015.34.2.108.

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37

García-Pacheco, Francisco Javier, Soledad Moreno-Pulido, Enrique Naranjo-Guerra, and Alberto Sánchez-Alzola. "Non-Linear Inner Structure of Topological Vector Spaces." Mathematics 9, no. 5 (2021): 466. http://dx.doi.org/10.3390/math9050466.

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Анотація:
Inner structure appeared in the literature of topological vector spaces as a tool to characterize the extremal structure of convex sets. For instance, in recent years, inner structure has been used to provide a solution to The Faceless Problem and to characterize the finest locally convex vector topology on a real vector space. This manuscript goes one step further by settling the bases for studying the inner structure of non-convex sets. In first place, we observe that the well behaviour of the extremal structure of convex sets with respect to the inner structure does not transport to non-con
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38

Wang, Jinliang, and Yuming Chen. "Threshold dynamics of a vector-borne disease model with spatial structure and vector-bias." Applied Mathematics Letters 100 (February 2020): 106052. http://dx.doi.org/10.1016/j.aml.2019.106052.

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39

BECK, DOUGLAS H., and BARRY R. HOLSTEIN. "NUCLEON STRUCTURE AND PARITY-VIOLATING ELECTRON SCATTERING." International Journal of Modern Physics E 10, no. 01 (2001): 1–41. http://dx.doi.org/10.1142/s0218301301000381.

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Анотація:
We review the area of strange quark contributions to nucleon structure. In particular, we focus on current models of strange quark vector currents in the nucleon and the associated parity-violating elastic electron scattering experiments from which vector and axial-vector currents are extracted.
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40

LI, Hui, Yu ZHOU, Masahiro TAKEI, Yoshifuru SAITO, and Kiyoshi HORII. "Visualization of Turbulent Structure Using Vector Wavelet Transform." Journal of the Visualization Society of Japan 20, no. 1Supplement (2000): 385–88. http://dx.doi.org/10.3154/jvs.20.1supplement_385.

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41

Ciriza, Eleonora. "The Local Structure of a Liouville Vector Field." American Journal of Mathematics 115, no. 4 (1993): 735. http://dx.doi.org/10.2307/2375011.

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42

Carbó-Dorca, Ramon. "Boolean hypercubes and the structure of vector spaces." Journal of Mathematical Sciences and Modelling 1, no. 1 (2018): 1–14. http://dx.doi.org/10.33187/jmsm.413116.

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43

KOBIS, ELISABETH, and CHRISTIANE TAMMER. "Robust vector optimization with a variable domination structure." Carpathian Journal of Mathematics 33, no. 3 (2017): 343–51. http://dx.doi.org/10.37193/cjm.2017.03.09.

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Анотація:
In this paper we propose a new definition of robustness for uncertain vector-valued optimization problems equipped with a variable domination structure, derive scalarization results and present algorithms for computing robust solutions.
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44

Prymushko, A. N. "Vector Data Structure Research in Scala Programming Language." Èlektronnoe modelirovanie 41, no. 6 (2019): 107–14. http://dx.doi.org/10.15407/emodel.41.06.107.

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45

Gao, Wei, and Zheng Tian. "Latent ancestral graph of structure vector autoregressive models." Journal of Systems Engineering and Electronics 21, no. 2 (2010): 233–38. http://dx.doi.org/10.3969/j.issn.1004-4132.2010.02.010.

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46

Shafer, Douglas S. "Structure and Stability of Gradient Polynomial Vector Fields." Journal of the London Mathematical Society s2-41, no. 1 (1990): 109–21. http://dx.doi.org/10.1112/jlms/s2-41.1.109.

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47

Yuasa, H. J., J. A. Cox, and T. Takagi. "Genomic Structure of the Amphioxus Calcium Vector Protein." Journal of Biochemistry 126, no. 3 (1999): 572–77. http://dx.doi.org/10.1093/oxfordjournals.jbchem.a022488.

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48

Granger, Michel, and Mathias Schulze. "On the formal structure of logarithmic vector fields." Compositio Mathematica 142, no. 03 (2006): 765–78. http://dx.doi.org/10.1112/s0010437x06001916.

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49

Wu, H. R., and F. J. Paoloni. "The structure of vector radix fast Fourier transforms." IEEE Transactions on Acoustics, Speech, and Signal Processing 37, no. 9 (1989): 1415–24. http://dx.doi.org/10.1109/29.31295.

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50

Yang, Jianke, and Yu Tan. "Fractal Structure in the Collision of Vector Solitons." Physical Review Letters 85, no. 17 (2000): 3624–27. http://dx.doi.org/10.1103/physrevlett.85.3624.

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