Статті в журналах: "Modèle de covariance"

1

LALOË, D. "La genèse et le développement des concepts de l’évaluation génétique classique." INRAE Productions Animales 24, no. 4 (September 8, 2011): 323–30. http://dx.doi.org/10.20870/productions-animales.2011.24.4.3264.

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On décrit les aspects fondamentaux de l'évaluation génétique à travers quelques grandes étapes :- l'explicitation des concepts-clés de génotype et phénotype,- le modèle polygénique de Fisher, et la formulation de la covariance entre apparentés,- les apports d'Henderson qui, couplés avec l'explosion des capacités informatiques, ont permis l'évaluation génétique simultanée de millions d'animaux. Ces concepts, modèles et méthodes s'inscrivent dans une approche instrumentaliste qui ne prétend pas refléter la réalité. Leur efficacité a été prouvée à travers la réalisation d'un progrès génétique dans toutes les espèces évaluées.

2

El Aabaribaoune, Mohammad, Emanuele Emili, and Vincent Guidard. "Estimation of the error covariance matrix for IASI radiances and its impact on the assimilation of ozone in a chemistry transport model." Atmospheric Measurement Techniques 14, no. 4 (April 13, 2021): 2841–56. http://dx.doi.org/10.5194/amt-14-2841-2021.

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Abstract. In atmospheric chemistry retrievals and data assimilation systems, observation errors associated with satellite radiances are chosen empirically and generally treated as uncorrelated. In this work, we estimate inter-channel error covariances for the Infrared Atmospheric Sounding Interferometer (IASI) and evaluate their impact on ozone assimilation with the chemistry transport model MOCAGE (Modèle de Chimie Atmosphérique à Grande Echelle). The method used to calculate observation errors is a diagnostic based on the observation and analysis residual statistics already adopted in many numerical weather prediction centres. We used a subset of 280 channels covering the spectral range between 980 and 1100 cm−1 to estimate the observation-error covariance matrix. This spectral range includes ozone-sensitive and atmospheric window channels. We computed hourly 3D-Var analyses and compared the resulting O3 fields against ozonesondes and the measurements provided by the Microwave Limb Sounder (MLS) and by the Ozone Monitoring Instrument (OMI). The results show significant differences between using the estimated error covariance matrix with respect to the empirical diagonal matrix employed in previous studies. The validation of the analyses against independent data reports a significant improvement, especially in the tropical stratosphere. The computational cost has also been reduced when the estimated covariance matrix is employed in the assimilation system, by reducing the number of iterations needed for the minimizer to converge.

3

Valette-Florence, Rita, and Pierre Valette-Florence. "Effets des émotions et de la personnalité de la marque sur l’engagement du consommateur via les effets médiateurs de la confiance et de l’attachement à la marque." Recherche et Applications en Marketing (French Edition) 35, no. 1 (June 26, 2019): 87–116. http://dx.doi.org/10.1177/0767370119846075.

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Résumé Adossé aux concepts de personnalité de la marque et d’émotions, cet article s’attache à montrer leur incidence respective sur les principales variables de la relation à la marque, la confiance, l’attachement et l’engagement global envers la marque. Basé sur un panel conséquent de consommateurs, les traitements statistiques sont conduits selon une analyse des structures de covariance (ASC) ou une approche des moindres carrés partiels (PLS), en prenant soin de tenir compte de l’erreur de mesure. Le modèle correspondant valide l’incidence des émotions et de la personnalité de la marque sur l’engagement du consommateur via les effets médiateurs de la confiance et de l’attachement à la marque. Plus précisément, les résultats montrent la médiation totale de la confiance au regard de l’impact de la personnalité de la marque sur l’engagement. Ils indiquent également la médiation partielle, mais centrale, exercée par l’attachement sur l’engagement. Enfin, les analyses soulignent la stabilité des résultats sur les 6 marques testées dans cette recherche. Elles illustrent cependant des différences notables entre les marques suivant leur caractère évaluatif ou hédonique.

4

Autin, Claude, Jacques Fearnley, and Ronald Rioux. "Effets des erreurs dans les coefficients structuraux d’un modèle intersectoriel « rectangulaire ». Une approche de type Monte-Carlo." L'Actualité économique 51, no. 1 (July 14, 2009): 86–95. http://dx.doi.org/10.7202/800607ar.

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The most simple rectangular input-output models use two rectangular matrices: R a market coefficient matrix, A* a production coefficient matrix. A given exogenous demand Xo determines the sectorial activity levels X* = [I — RA*]-1Xo. We assume that A* is random with expectation A. We study the distribution of the "error" X* — X with X = [I — RA]-1Xo. (1) For the statistically independent elements of A*, we analytically prove that X < EX*. (2) In the more realistic case of statistically dependent elements of A*. (a) One submatrix of A* with T non zero elements is chosen. The probabilistic model which generates the T coefficients is as follows: a* = (1 — μ)a + μ(S/n) b* où a* is the vector of the T random elements, a is the expectation of a* whose components are observed values of a real input-output model, S is the sum of components of a, μ is a parameter between zero and one, b* is a multinomial random vector with T components and parameters n, number of drawings during an experiment, and a/S, the corresponding probabilities. We control the variability of a* through μ and n. For a given experiment, we get a realisation of A* and we compute X*. K independent experiments allow us to estimate the expectation and the variance-covariance matrix of X*, simultaneous confidence intervals for the expectation of the components of X*, and also a few global measures of errors on X*. The Canadian model for 1961 (16 productive sectors, 40 commodities), is tested with that model. The main result is: the relative errors, measured according to the variation coefficients, are greatly reduced when we pass from the "errors" on a* to the corresponding "errors" on X*. (b) The same random model is also simultaneously applied to 2 or 3 sub-matrices of A*.

5

Dao, Elizabeth, Cindy K. Barha, John R. Best, Ging-Yuek Hsiung, Roger Tam, and Teresa Liu-Ambrose. "The Effect of Aerobic Exercise on White Matter Hyperintensity Progression May Vary by Sex." Canadian Journal on Aging / La Revue canadienne du vieillissement 38, no. 02 (March 14, 2019): 236–44. http://dx.doi.org/10.1017/s0714980818000582.

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RÉSUMÉCette étude a exploré l’efficacité de l’entraînement aérobie (EA) pour atténuer la progression de l’hyperintensité de la matière blanche (HMB) et les différences liées au sexe pour cette intervention. Un essai contrôlé randomisé a été mené pour évaluer l’effet de l’EA sur la cognition de personnes ayant un déficit cognitif d’origine vasculaire. Les participants ont été répartis aléatoirement entre deux groupes : 6 mois d’EA ou soins standards (groupe contrôle). Dans un sous-groupe de participants, l’imagerie par résonance magnétique a été utilisée pour quantifier le volume affecté par la HMB. Un modèle d’analyse de la covariance a permis de mettre en évidence une interaction sexe x groupe significative (p = 0,03). En effet, les femmes du groupe EA ont démontré une plus grande progression de l’hyperintensité de la matière blanche que les femmes du groupe contrôle (p = 0,05) pendant la durée de cette étude (6 mois). Chez les hommes, aucune différence n’a été observée entre les deux groupes (p = 0,31). Dans le groupe EA, les hommes ont montré une progression significativement moindre de la HMB, comparativement aux femmes (p = 0,01) après 6 mois. Ainsi, les effets de l’EA sur la progression de la HMB pourraient varier selon le sexe, et l’EA pourrait freiner la progression de la HMB chez les hommes, mais non chez les femmes.

6

Varga, Štefan. "Estimations of covariance components in mixed linear models." Mathematica Bohemica 121, no. 1 (1996): 29–33. http://dx.doi.org/10.21136/mb.1996.125947.

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7

Quesada-Ruiz, Samuel, Jean-Luc Attié, William A. Lahoz, Rachid Abida, Philippe Ricaud, Laaziz El Amraoui, Régina Zbinden, et al. "Benefit of ozone observations from Sentinel-5P and future Sentinel-4 missions on tropospheric composition." Atmospheric Measurement Techniques 13, no. 1 (January 14, 2020): 131–52. http://dx.doi.org/10.5194/amt-13-131-2020.

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Abstract. We present an observing simulated system experiment (OSSE) dedicated to evaluate the potential added value from the Sentinel-4 and the Sentinel-5P observations on tropospheric ozone composition. For this purpose, the ozone data of Sentinel-4 (Ultraviolet Visible Near-infrared) and Sentinel-5P (TROPOspheric Monitoring Instrument) on board a geostationary (GEO) and a low-Earth-orbit (LEO) platform, respectively, have been simulated using the DISAMAR inversion package for the summer 2003. To ensure the robustness of the results, the OSSE has been configured with conservative assumptions. We simulate the reality by combining two chemistry transport models (CTMs): the LOng Term Ozone Simulation – EURopean Operational Smog (LOTOS-EUROS) and the Transport Model version 5 (TM5). The assimilation system is based on a different CTM, the MOdèle de Chimie Atmosphérique à Grande Echelle (MOCAGE), combined with the 3-D variational technique. The background error covariance matrix does not evolve in time and its variance is proportional to the field values. The simulated data are formed of six eigenvectors to minimize the size of the dataset by removing the noise-dominated part of the observations. The results show that the satellite data clearly bring direct added value around 200 hPa for the whole assimilation period and for the whole European domain, while a likely indirect added value is identified but not for the whole period and domain at 500 hPa, and to a lower extent at 700 hPa. In addition, the ozone added value from Sentinel-5P (LEO) appears close to that from Sentinel-4 (GEO) in the free troposphere (200–500 hPa) in our OSSE. The outcome of our study is a result of the OSSE design and the choice within each of the components of the system.

8

Fonseca, Wéverton José Lima, Wéverson Lima Fonseca, Laylson da Silva Borges, Amauri Felipe Evangelista, Paulo Henrique Amaral Araújo de Sousa, Genilson Sousa do Nascimento, Carlandia Pacheco de Figueiredo, et al. "ESTIMATES COVARIANCE FUNCTIONS TO GOATS MILK PRODUCTION USING REGRESSION MODELS RANDOM." Nucleus Animalium 7, no. 2 (November 30, 2015): 83–92. http://dx.doi.org/10.3738/1982.2278.1498.

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9

Adlouni, Salaheddine El, and Taha B. M. J. Ouarda. "Comparaison des méthodes d’estimation des paramètres du modèle GEV non stationnaire." Revue des sciences de l'eau 21, no. 1 (April 29, 2008): 35–50. http://dx.doi.org/10.7202/017929ar.

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Résumé L’analyse fréquentielle des événements extrêmes est un des outils privilégiés pour l’estimation des débits de crue et de leurs périodes de retour. En analyse fréquentielle, les observations doivent être indépendantes et identiquement distribuées (iid). Ces hypothèses ne sont pas souvent respectées et les paramètres de la loi à ajuster sont fonction du temps ou de covariables. Le modèle GEV non stationnaire permet de tenir compte de cette dépendance. L’objectif du présent travail est de comparer la méthode du maximum de vraisemblance pour l’estimation des quantiles à la méthode du maximum de vraisemblance généralisée (GML) et à une généralisation de la méthode des L‑moments dans le cas non stationnaire. Trois modèles sont considérés : le modèle stationnaire (GEV0), le cas où le paramètre de position est une fonction linéaire de la covariable (GEV1) et le cas d’une dépendance quadratique (GEV2). Un cas d’étude des précipitations à une station de la Californie montre le potentiel des modèles non stationnaires.

10

Fariña, Bibiana, Jonay Toledo, Jose Ignacio Estevez, and Leopoldo Acosta. "Improving Robot Localization Using Doppler-Based Variable Sensor Covariance Calculation." Sensors 20, no. 8 (April 17, 2020): 2287. http://dx.doi.org/10.3390/s20082287.

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This paper describes a localization module for an autonomous wheelchair. This module includes a combination of various sensors such as odometers, laser scanners, IMU and Doppler speed sensors. Every sensor used in the module features variable covariance estimation in order to yield a final accurate localization. The main problem of a localization module composed of different sensors is the accuracy estimation of each sensor. Average static values are normally used, but these can lead to failure in some situations. In this paper, all the sensors have a variable covariance estimation that depends on the data quality. A Doppler speed sensor is used to estimate the covariance of the encoder odometric localization. Lidar is also used as a scan matching localization algorithm, comparing the difference between two consecutive scans to obtain the change in position. Matching quality gives the accuracy of the scan matcher localization. This structure yields a better position than a traditional odometric static covariance method. This is tested in a real prototype and compared to a standard fusion technique.

11

Štulajter, František. "Consistency of linear and quadratic least squares estimators in regression models with covariance stationary errors." Applications of Mathematics 36, no. 2 (1991): 149–55. http://dx.doi.org/10.21136/am.1991.104452.

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12

Bacher, F. "L'utilisation des modèles dans l'analyse des structures de covariance." L'année psychologique 99, no. 1 (1999): 99–122. http://dx.doi.org/10.3406/psy.1999.28549.

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13

Elmer, Jonathan, and Müfit Sezer. "Degree bounds for modular covariants." Forum Mathematicum 32, no. 4 (July 1, 2020): 905–10. http://dx.doi.org/10.1515/forum-2019-0196.

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AbstractLet {V,W} be representations of a cyclic group G of prime order p over a field {\Bbbk} of characteristic p. The module of covariants {\Bbbk[V,W]^{G}} is the set of G-equivariant polynomial maps {V\rightarrow W}, and is a module over {\Bbbk[V]^{G}}. We give a formula for the Noether bound {\beta(\Bbbk[V,W]^{G},\Bbbk[V]^{G})}, i.e. the minimal degree d such that {\Bbbk[V,W]^{G}} is generated over {\Bbbk[V]^{G}} by elements of degree at most d.

14

Chang, Carol, and Jerzy Weyman. "Representations of quivers with free module of covariants." Journal of Pure and Applied Algebra 192, no. 1-3 (September 2004): 69–94. http://dx.doi.org/10.1016/j.jpaa.2004.02.015.

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15

Yan, Peihui, Jinguang Jiang, Fangning Zhang, Dongpeng Xie, Jiaji Wu, Chao Zhang, Yanan Tang, and Jingnan Liu. "An Improved Adaptive Kalman Filter for a Single Frequency GNSS/MEMS-IMU/Odometer Integrated Navigation Module." Remote Sensing 13, no. 21 (October 27, 2021): 4317. http://dx.doi.org/10.3390/rs13214317.

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Aiming at the GNSS receiver vulnerability in challenging urban environments and low power consumption of integrated navigation systems, an improved robust adaptive Kalman filter (IRAKF) algorithm with real-time performance and low computation complexity for single-frequency GNSS/MEMS-IMU/odometer integrated navigation module is proposed. The algorithm obtains the scale factor by the prediction residual, and uses it to adjust the artificially set covariance matrix of the observation vector under different GNSS solution states, so that the covariance matrix of the observation vector changes continuously with the complex scene. Then, the adaptive factor is calculated by the Mahalanobis distance to inflate the state prediction covariance matrix. In addition, the one-step prediction Kalman filter is introduced to reduce the computational complexity of the algorithm. The performance of the algorithm is verified by vehicle experiments in the challenging urban environments. Experiments show that the algorithm can effectively weaken the effects of abnormal model deviations and outliers in the measurements and improve the positioning accuracy of real-time integrated navigation. It can meet the requirements of low power consumption real-time vehicle navigation applications in the complex urban environment.

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BENTALHA, Z., and M. TAHIRI. "A NOTE ON SLq(2) COVARIANCE AND QUANTUM EUCLIDEAN PLANE." Modern Physics Letters A 22, no. 14 (May 10, 2007): 1031–37. http://dx.doi.org/10.1142/s0217732307021342.

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A quantum analogue of SL(2) covariance is given. The method consists of defining a bilinear form on SL q(2) co-module, then we ask the defined form to be invariant under SL q(2) co-actions. We showed that the required invariance leads to the standard algebraic structure of SL q(2) ideal. On the other hand, the geometry of the three-dimensional quantum Euclidean space has been evoked by computing the quantum Euclidean metric, the quantum Euclidean "distance" (the central element) and the relation of orthogonality of SO q(3) quantum group.

17

Xu, Hongfu, Haiyong Luo, Zijian Wu, Fan Wu, Linfeng Bao, and Fang Zhao. "Towards Predicting the Measurement Noise Covariance with a Transformer and Residual Denoising Autoencoder for GNSS/INS Tightly-Coupled Integrated Navigation." Remote Sensing 14, no. 7 (March 31, 2022): 1691. http://dx.doi.org/10.3390/rs14071691.

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The tightly coupled navigation system is commonly used in UAV products and land vehicles. It adopts the Kalman filter to combine raw satellite observations, including the pseudorange, pseudorange rate and Doppler frequency, with the inertial measurements to achieve high navigational accuracy in GNSS-challenged environments. The accurate estimation of measurement noise covariance can ensure the quick convergence of the Kalman filter and the accuracy of the navigation results. Existing tightly coupled integrated navigation systems employ either constant noise covariance or simple noise covariance updating methods, which cannot accurately reflect the dynamic measurement noises. In this article, we propose an adaptive measurement noise estimation algorithm using a transformer and residual denoising autoencoder (RDAE), which can dynamically estimate the covariance of measurement noise. The residual module is used to solve the gradient degradation problem. The DAE is adopted to learn the essential characteristics from the noisy ephemeris data. By introducing the attention mechanism, the transformer can effectively learn the time and space dependency of long-term ephemeris data, and thus dynamically adjusts the noise covariance with the predicted factors. Extensive experimental results demonstrate that our method can achieve sub-meter positioning accuracy in the outdoor open environment. In a GNSS-degraded environment, our proposed method can still obtain about 3 m positioning accuracy. Another test on a new dataset also confirms that our proposed method has reasonable robustness and adaptability.

18

Crann, Jason. "Amenability and Covariant Injectivity of Locally Compact Quantum Groups II." Canadian Journal of Mathematics 69, no. 5 (October 1, 2017): 1064–86. http://dx.doi.org/10.4153/cjm-2016-031-5.

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AbstractBuilding on our previous work, we study the non-relative homology of quantum group convolution algebras. Our main result establishes the equivalence of amenability of a locally compact quantum group and 1-injectivity of as an operator -module. In particular, a locally compact group G is amenable if and only if its group von Neumann algebra VN(G) is 1-injective as an operator module over the Fourier algebra A(G). As an application, we provide a decomposability result for completely bounded -module maps on , and give a simpliûed proof that amenable discrete quantum groups have co-amenable compact duals, which avoids the use of modular theory and the Powers-Størmer inequality, suggesting that our homological techniques may yield a new approach to the open problem of duality between amenability and co-amenability.

19

Kabouya, M., and C. Michel. "Estimation des ressources en eau superficielle aux pas de temps mensuel et annuel, application à un pays semi-aride." Revue des sciences de l'eau 4, no. 4 (April 12, 2005): 569–87. http://dx.doi.org/10.7202/705116ar.

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On connait l'extrême variabilité des ressources en eau superficielle et les problèmes que cela pose en aménagement du territoire. En conséquence, générer de longues séries de débits annuels (ou mensuels) est une nécessité pour l'étude de la disponibilité des ressources en eau (BURGES et LETTENMAIER, 1977). Cette génération de longues séries peut se faire à partir de la connaissance des pluies si l'on dispose d'un modèle fiable de transformation pluie-débit. Un premier modèle linéaire visant à l'estimation du seul débit annuel, déjà utile pour un premier dégrossissage de la ressource, est bâti à partir de la pluie annuelle et de sa répartition entre les mois. Il constitue un outil de base que l'on a jugé néanmoins un peu trop rudimentaire. La recherche d'un modèle conceptuel simple nous a semblé une voie plus prometteuse. Exploitant une recherche déjà entreprise sur ce type de modèle au pas de temps journalier, on a construit un modèle mensuel à trois paramètres dont l'élaboration a été justifiée point par point par une meilleure efficacité des résultats fournis sur une soixantaine de bassins versants appartenant à la partie septentrionale de l'Algérie. Nous avons analysé les paramètres du modèle et obtenu une estimation approchée de la matrice des variances-covariances de ces paramètres afin de disposer d'un outil similaire à celui existant pour le modèle linéaire général.

20

Dupuy, Jean-François, Ion Grama, and Mounir Mesbah. "Normalité asymptotique des estimateurs semiparamétriques dans le modèle de Cox avec covariable manquante nonignorable." Comptes Rendus Mathematique 336, no. 1 (January 2003): 81–84. http://dx.doi.org/10.1016/s1631-073x(03)00003-7.

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21

Yang, Haotian, Bin Zhou, Lixin Wang, Qi Wei, Feng Ji, and Rong Zhang. "Performance and Evaluation of GNSS Receiver Vector Tracking Loop Based on Adaptive Cascade Filter." Remote Sensing 13, no. 8 (April 12, 2021): 1477. http://dx.doi.org/10.3390/rs13081477.

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In the scenario of high dynamics and low C/N0, the discriminator output of a GNSS tracking loop is noisy and nonlinear. The traditional method uses a fixed-gain loop filter for error estimation, which is prone to lose lock and causes inaccurate navigation and positioning. This paper proposes a cascaded adaptive vector tracking method based on the KF+EKF architecture through the GNSS Software defined receiver in the signal tracking module and the navigation solution module. The linear relationships between the pseudo-range error and the code phase error, the pseudo-range rate error and the carrier frequency error are obtained as the measurement, and the navigation filter estimation is performed. The signal C/N0 ratio and innovation sequence are used to adjust the measurement noise covariance matrix and the process noise covariance matrix, respectively. Then, the estimated error value is used to correct the navigation parameters and fed back to the local code/carrier NCO. The field vehicle test results show that, in the case of sufficient satellite signals, the positioning error of the proposed method has a slight advantage compared with the traditional method. When there is signal occlusion or interference, the traditional method cannot achieve accurate positioning. However, the proposed method can maintain the same accuracy for the positioning results.

22

Zhang, Gao Wei, Xiao Yu Zhang, Chun Lei Song, and Ting Ting Wang. "Research and Design of MEMS SINS/GPS Integrated Navigation System Based on Adaptive Filter." Applied Mechanics and Materials 341-342 (July 2013): 1048–52. http://dx.doi.org/10.4028/www.scientific.net/amm.341-342.1048.

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A MIMU/GPS integrated navigation system principle prototype is designed, and the structure of the system is introduced by different module. To handle the influence of Kalman filter parameters on system filtering performance (Including the system noise variance matrix Q and measurement noise covariance matrix R), adaptive estimation Kalman filter is designed. The test results show that satisfactory performance can be obtained using adaptive estimation techniques for the low-cost MIMU/GPS integrated navigation.

23

Haapasalo, Erkka, and Juha-Pekka Pellonpää. "Covariant KSGNS construction and quantum instruments." Reviews in Mathematical Physics 29, no. 07 (August 2017): 1750020. http://dx.doi.org/10.1142/s0129055x17500209.

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We study completely positive (CP) [Formula: see text]-sesquilinear-form-valued maps on a unital [Formula: see text]-algebra [Formula: see text], where the sesquilinear forms operate on a module over a [Formula: see text]-algebra [Formula: see text]. We also study the cases when either one or both of the algebras are von Neumann algebras. Moreover, we assume that the CP maps are covariant with respect to actions of a symmetry group. This allows us to view these maps as generalizations of covariant quantum instruments. We determine minimal covariant dilations (KSGNS constructions) for covariant CP maps to find necessary and sufficient conditions for a CP map to be extreme in convex subsets of normalized covariant CP maps. As a special case, we study covariant quantum observables and instruments whose value space is a transitive space of a unimodular type-I group. Finally, we discuss the case of instruments that are covariant with respect to a square-integrable representation.

24

Hanen, Albert. "Un théorème limite pour les covariances des spins dans le modèle de Sherrington–Kirkpatrick avec champ externe." Annals of Probability 35, no. 1 (January 2007): 141–79. http://dx.doi.org/10.1214/009117906000000665.

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25

Rahmatika, Helsa, Sri Rahayu Lestari, and Murni Sapta Sari. "A PBL-Based Circulatory System E-Module Based on Research Results to Improve Students’ Critical Thinking Skills and Cognitive Learning Outcome." JPI (Jurnal Pendidikan Indonesia) 9, no. 4 (December 3, 2020): 565. http://dx.doi.org/10.23887/jpi-undiksha.v9i4.25647.

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The low of students’ critical thinking skills and cognitive learning outcomes can be caused by learning difficulties. One of the causes is the lack of availability of learning resources that are relevant and easily applied. The aim of this research is to produce a Problem Based Learning-based e-module based on the results of research that is valid, practical, and effective. The development model used is ADDIE with stages are analyze, design, develop, implement, and evaluate. The resulting e-module is very valid and very practical with the validation value by content expert=100%, learning expert=98,65%, field practitioners=92,85%, and then the value of practicality=86,99%. The result of quade’s rank analysis of covariance test with p-value is 0,000<α (α=0.05) and the result of ANCOVA test with p-value is 0,000<α. The conclusion is Problem Based Learning-based e-module based on the results of research can improve critical thinking skills and cognitive learning outcomes of students.

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Wu, Huawei, Congjin Ye, Yuanjin Zhang, Jingquan Nie, Yong Kuang, and Zhixiong Li. "Remaining Useful Life Prediction of an IGBT Module in Electric Vehicles Statistical Analysis." Symmetry 12, no. 8 (August 8, 2020): 1325. http://dx.doi.org/10.3390/sym12081325.

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The whole life cycle of an insulated gate bipolar transistor (IGBT) is a kind of asymmetry process, while the whole life cycles of a set of IGBTs can be regarded as a symmetry process. Modelling these symmetry characteristics of the IGBT life cycles enables the improvement of the remaining useful life (RUL) prediction performance. For this purpose, based on the key failure mechanism of IGBT in electric vehicles, a new method for estimating the RUL of an IGBT module is proposed based on the two-stress acceleration synthesis environment of junction temperature and vibration. The maximum likelihood estimation (MLE) was employed to estimate the logarithmic standard deviation and covariance matrix. The Shapiro–Wilk (S–W) test was performed to investigate the satisfaction degree of the RUL of the IGBT module to the lognormal distribution. The accelerated life test datasets of the IGBT module were analyzed using the Weibull++ software. The analysis results demonstrate that the IGBT lifetime is confirmed to lognormal distribution, and the accelerated model accords with the generalized Eyring acceleration model. The proposed method can estimate IGBT RUL in a short time, which provides a certain technical reference for the reliability analysis of the IGBT module.

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Herbig, Hans-Christian, Daniel Herden, and Christopher Seaton. "Hilbert series associated to symplectic quotients by SU2." International Journal of Algebra and Computation 30, no. 07 (July 24, 2020): 1323–57. http://dx.doi.org/10.1142/s0218196720500435.

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We compute the Hilbert series of the graded algebra of real regular functions on the symplectic quotient associated to an [Formula: see text]-module and give an explicit expression for the first nonzero coefficient of the Laurent expansion of the Hilbert series at [Formula: see text]. Our expression for the Hilbert series indicates an algorithm to compute it, and we give the output of this algorithm for all representations of dimension at most [Formula: see text]. Along the way, we compute the Hilbert series of the module of covariants of an arbitrary [Formula: see text]- or [Formula: see text]-module as well as its first three Laurent coefficients.

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Schenkel, Alexander. "Module parallel transports in fuzzy gauge theory." International Journal of Geometric Methods in Modern Physics 11, no. 03 (March 2014): 1450021. http://dx.doi.org/10.1142/s0219887814500212.

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In this paper, we define and investigate a notion of parallel transport on finite projective modules over finite matrix algebras. Given a derivation-based differential calculus on the algebra and a connection on the module, we construct for every derivation X a module parallel transport, which is a lift to the module of the one-parameter group of algebra automorphisms generated by X. This parallel transport morphism is determined uniquely by an ordinary differential equation depending on the covariant derivative along X. Based on these parallel transport morphisms, we define a basic set of gauge invariant observables, i.e. functions from the space of connections to the complex numbers. For modules equipped with a Hermitian structure, we prove that this set of observables is separating on the space of gauge equivalence classes of Hermitian connections. This solves the gauge copy problem for fuzzy gauge theories.

29

Chang, J. F., N. Viovy, N. Vuichard, P. Ciais, T. Wang, A. Cozic, R. Lardy, et al. "Incorporating grassland management in ORCHIDEE: model description and evaluation at 11 eddy-covariance sites in Europe." Geoscientific Model Development 6, no. 6 (December 20, 2013): 2165–81. http://dx.doi.org/10.5194/gmd-6-2165-2013.

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Abstract. This study describes how management of grasslands is included in the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) process-based ecosystem model designed for large-scale applications, and how management affects modeled grassland–atmosphere CO2 fluxes. The new model, ORCHIDEE-GM (grassland management) is enabled with a management module inspired from a grassland model (PaSim, version 5.0), with two grassland management practices being considered, cutting and grazing. The evaluation of the results from ORCHIDEE compared with those of ORCHIDEE-GM at 11 European sites, equipped with eddy covariance and biometric measurements, shows that ORCHIDEE-GM can realistically capture the cut-induced seasonal variation in biometric variables (LAI: leaf area index; AGB: aboveground biomass) and in CO2 fluxes (GPP: gross primary productivity; TER: total ecosystem respiration; and NEE: net ecosystem exchange). However, improvements at grazing sites are only marginal in ORCHIDEE-GM due to the difficulty in accounting for continuous grazing disturbance and its induced complex animal–vegetation interactions. Both NEE and GPP on monthly to annual timescales can be better simulated in ORCHIDEE-GM than in ORCHIDEE without management. For annual CO2 fluxes, the NEE bias and RMSE (root mean square error) in ORCHIDEE-GM are reduced by 53% and 20%, respectively, compared to ORCHIDEE. ORCHIDEE-GM is capable of modeling the net carbon balance (NBP) of managed temperate grasslands (37 ± 30 gC m−2 yr−1 (P < 0.01) over the 11 sites) because the management module contains provisions to simulate the carbon fluxes of forage yield, herbage consumption, animal respiration and methane emissions.

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Lacasa, Fabien, and Julien Grain. "Fast and easy super-sample covariance of large-scale structure observables." Astronomy & Astrophysics 624 (April 2019): A61. http://dx.doi.org/10.1051/0004-6361/201834343.

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We present a numerically cheap approximation to super-sample covariance (SSC) of large-scale structure cosmological probes, first in the case of angular power spectra. No new elements are needed besides those used to predict the considered probes, thus relieving analysis pipelines from having to develop a full SSC modeling, and reducing the computational load. The approximation is asymptotically exact for fine redshift bins Δz → 0. We furthermore show how it can be implemented at the level of a Gaussian likelihood or a Fisher matrix forecast as a fast correction to the Gaussian case without needing to build large covariance matrices. Numerical application to a Euclid-like survey show that, compared to a full SSC computation, the approximation nicely recovers the signal-to-noise ratio and the Fisher forecasts on cosmological parameters of the wCDM cosmological model. Moreover, it allows for a fast prediction of which parameters are going to be the most affected by SSC and at what level. In the case of photometric galaxy clustering with Euclid-like specifications, we find that σ8, ns, and the dark energy equation of state w are particularly heavily affected. We finally show how to generalize the approximation for probes other than angular spectra (correlation functions, number counts, and bispectra) and at the likelihood level, allowing for the latter to be non-Gaussian if necessary. We release publicly a Python module allowing the implementation of the SSC approximation and a notebook reproducing the plots of the article.

31

Hou, Rujie, Zhenyi Chen, Jinglong Chen, Shuilong He, and Zitong Zhou. "Imbalanced fault identification via embedding-augmented Gaussian prototype network with meta-learning perspective." Measurement Science and Technology 33, no. 5 (February 3, 2022): 055102. http://dx.doi.org/10.1088/1361-6501/ac3c1d.

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Abstract In practical engineering, the number of acquired fault samples from different categories can be vastly different due to the low probability of key equipment malfunctioning. When training the imbalanced data, many methods focus on balancing the number of samples or weights between different categories, which may be time-consuming and easy to over-fit. To address this problem, we propose the embedding-augmented Gaussian prototype network (EGPN), which applies a new training mechanism from the perspective of meta-learning. We only train the categories with large samples and the remaining categories only appear in the testing process to calculate untrained prototypes. EGPN includes a feature-embedding augmented module, weighted prototype module and metric module. Firstly, ordinary convolution and dilated convolution are mixed to capture different frequency bands simultaneously, and the residual attention module is added to highlight key features and suppress unimportant features. Different prototypes are calculated by weighting to the embedding vectors through the Gaussian covariance matrix. Finally, the classification is done according to the modified distance. The experiments in the two datasets indicate that the proposed method can effectively recognize the untrained categories with only a few samples used as the prototypes, and can tackle the problem of identifying imbalanced fault data efficiently.

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Mohd Shukri, Ahmad Adnan, Che Nidzam Che Ahmad, and Norhayati Daud. "IMPLEMENTING A CELIK STEM MODULE IN EMPOWERING EIGHTH-GRADERS’ CREATIVE THINKING." International Journal of Education, Psychology and Counseling 4, no. 32 (September 15, 2019): 219–37. http://dx.doi.org/10.35631/ijepc.4320021.

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The purpose of this study is to examine the contributions of the Celik STEM Module developed on pupils’ creative thinking in the science classrooms. A quasi-experimental study involved a non-equivalent control group with a sample of 60 eighth-graders aged 13 years old from a boarding school in Baling, Kedah. The sample was divided into two groups; 30 pupils of the treatment group and 30 pupils of the control group. Data were collected from pre-post-creative thinking test (CTT) scores. One-way analysis of covariance at a significance level p < .05 was performed in analyzing the data. After adjusting for pretest scores, there was a significant difference between the two sample groups on posttest scores on the CTT, F (1,57) = 16.639, p = .000, partial eta squared = .226. Besides, there was a significant and moderate relationship between the pretest and posttest scores on the CTT, as indicated by partial eta squared = .082. In conclusion, teaching and learning of the Reproduction topic through STEM integration applied in the module is better than regular instruction. The results of the present study showed that this alternative teaching method has been proven effective in developing and empowering pupils’ creative thinking.

33

Button, Tanya M. M., John K. Hewitt, Soo Hyun Rhee, Susan E. Young, Robin P. Corley, and Michael C. Stallings. "Examination of the Causes of Covariation Between Conduct Disorder Symptoms and Vulnerability to Drug Dependence." Twin Research and Human Genetics 9, no. 1 (February 1, 2006): 38–45. http://dx.doi.org/10.1375/twin.9.1.38.

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AbstractConduct disorder (CD) symptoms and substance dependence commonly co-occur. Both phenotypes are highly heritable and a common genetic influence on the covariation has been suggested. The aim of this study was to determine the extent to which genes and environment contribute to the covariance between CD and drug dependence using twins from the Colorado Longitudinal Twin Sample and the Colorado Twin Registry. A total of 880 twin pairs (237 monozygotic [MZ] female, 195 MZ male, 116 dizygotic [DZ] female, 118 DZ male and 214 DZ opposite-sex) aged 13 to 18 (mean = 15.65) were included in the analysis. CD was assessed by lifetime Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association, 1994) symptom count and a polysubstance dependence vulnerability index was developed from responses to the Composite International Diagnostic Interview — Substance Abuse Module. A bivariate Cholesky Decomposition model was used to partition the cause of variation and covariation of the two phenotypes. No sex-limitation was observed in our data, and male and female parameter estimates were constrained to be equal. Both CD symptoms and dependence vulnerability were significantly heritable, and genes, shared environment and nonshared environment all contributed to the covariation between them. Genes contributed 35% of the phenotypic covariance, shared environment contributed 46%, and nonshared environmental influences contributed the remaining 19% to the phenotypic covariance. Therefore, there appears to be pleiotropic genetic influence on CD symptoms and dependence vulnerability.

34

Chang, J., N. Viovy, N. Vuichard, P. Ciais, T. Wang, A. Cozic, R. Lardy, et al. "Incorporating grassland management in a global vegetation model: model description and evaluation at 11 eddy-covariance sites in Europe." Geoscientific Model Development Discussions 6, no. 2 (May 8, 2013): 2769–812. http://dx.doi.org/10.5194/gmdd-6-2769-2013.

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Abstract. This study describes how management of grasslands is included in the ORCHIDEE process-based ecosystem model designed for large-scale applications, and how management affects modeled grassland-atmosphere CO2 fluxes. The new model, ORCHIDEE-GM (Grassland Management) is enabled with a management module inspired from a grassland model (PaSim, version 5.0), with two grassland management practices being considered, cutting and grazing, respectively. The evaluation of the results from ORCHIDEE compared with those of ORCHIDEE-GM at 11 European sites equipped with eddy covariance and biometric measurements, shows that ORCHIDEE-GM can capture realistically the cut-induced seasonal variation in biometric variables (LAI: Leaf Area Index; AGB: Aboveground Biomass) and in CO2 fluxes (GPP: Gross Primary Productivity; TER: Total Ecosystem Respiration; and NEE: Net Ecosystem Exchange). But improvements at grazing sites are only marginal in ORCHIDEE-GM, which relates to the difficulty in accounting for continuous grazing disturbance and its induced complex animal-vegetation interactions. Both NEE and GPP on monthly to annual timescales can be better simulated in ORCHIDEE-GM than in ORCHIDEE without management. ORCHIDEE-GM is capable to model the net carbon balance (NBP) of managed grasslands better than ORCHIDEE, because the management module allows to simulate the carbon fluxes of forage yield, herbage consumption, animal respiration and methane emissions.

35

Wan, Jian, Peiwen Ren, and Qiang Guo. "Application of Interactive Multiple Model Adaptive Five-Degree Cubature Kalman Algorithm Based on Fuzzy Logic in Target Tracking." Symmetry 11, no. 6 (June 5, 2019): 767. http://dx.doi.org/10.3390/sym11060767.

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Aiming at the shortcomings of low precision, hysteresis, and poor robustness of the general interactive multimodel algorithm in the “snake-like” maneuver tracking of anti-ship missiles, an interactive multimodel adaptive five-degree cubature Kalman algorithm based on fuzzy logic (FLIMM5ACKF) is proposed. The algorithm mainly includes adaptive five-degree cubature Kalman algorithm (A5CKF) and fuzzy logic algorithm (FL). A5CKF uses the Sage–Husa noise estimation principle to propose a state error covariance adaptive five-degree cubature Kalman algorithm to improve the performance of state estimation. Then, the fuzzy logic algorithm (FL) is added to the model probability update module to control the model probability update module. Finally, by setting the same tracking model simulation analysis, the algorithm has better convergence speed, tracking effect and robustness than the interactive multimodel cubature Kalman algorithm (IMMCKF), the interactive multimodel five-degree cubature Kalman algorithm (IMM5CKF) and the interactive multimodel adaptive five-degree cubature Kalman (IMMA5CKF).

36

Liu, Runmin, Xin Ning, Weiwei Cai, and Guangjun Li. "Multiscale Dense Cross-Attention Mechanism with Covariance Pooling for Hyperspectral Image Scene Classification." Mobile Information Systems 2021 (May 4, 2021): 1–15. http://dx.doi.org/10.1155/2021/9962057.

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In recent years, learning algorithms based on deep convolution frameworks have gradually become the research hotspots in hyperspectral image classification tasks. However, in the classification process, high-dimensionality problems with large amounts of data and feature redundancy with interspectral correlation of hyperspectral images have not been solved efficiently. Therefore, this paper investigates data dimensionality reduction and feature extraction and proposes a novel multiscale dense cross-attention mechanism algorithm with covariance pooling (MDCA-CP) for hyperspectral image scene classification. The multisize convolution module can detect subtle changes in the hyperspectral images’ spatial and spectral dimensions between the pixels in the local areas and are suitable for extracting hyperspectral data with complex and diverse types of structures. For traditional algorithms that assign attention weights in a one-way manner, thus leading to the loss of feature information, the dense cross-attention mechanism proposed in this study can jointly distribute the attention weights horizontally and vertically to efficiently capture the most representative features. In addition, this study also uses covariance pooling to further extract the features of hyperspectral images from the second order. Experiments have been conducted on three well-known hyperspectral datasets, and the results thus obtained show that the MDCA-CP algorithm is superior compared to the other well-known methods.

37

Wu, Qu, Xingjie Peng, Guanlin Shi, Yingrui Yu, Qing Li, and Kan Wang. "Nuclear data sensitivity analysis and uncertainty propagation in the KYADJ whole-core transport code." EPJ Web of Conferences 239 (2020): 22012. http://dx.doi.org/10.1051/epjconf/202023922012.

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Nuclear data sensitivity analysis and uncertainty propagation have been extensively applied to nuclear data adjustment and uncertainty quantification in the field of nuclear engineering. Sensitivity and Uncertainty (S&U) analysis is developed in the KYADJ whole-core transport code in order to meet the requirement of advanced reactor design. KYADJ aims to use two-dimension Method of Characteristic (MOC) and one-dimension discrete ordinate (SN) coupled method to solve the neutron transport equation and achieve one-step direct transport calculation of the reactor core. Developing sensitivity and uncertainty analysis module in KYADJ can minimize deviations caused by modeling approximation and enhance calculation efficiency. This work describes the application of the classic perturbation theory to the KYADJ transport solver. In order to obtain uncertainty, a technique is proposed for processing a covariance data file in 45-group energy grid instead of 44-group SCALE 6.1 covariance data which is extensively used in various codes. Numerical results for Uncertainty Analysis in Modelling (UAM) benchmarks and the SF96 benchmark are presented. The results agree well with the reference and the capability of S&U analysis in KYADJ is verified.

38

Ma, Ji, Chen Hao, Lixun Liu, and Yuekai Zhou. "Perturbation Theory-Based Whole-Core Eigenvalue Sensitivity and Uncertainty (SU) Analysis via a 2D/1D Transport Code." Science and Technology of Nuclear Installations 2020 (February 1, 2020): 1–13. http://dx.doi.org/10.1155/2020/9428580.

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For nuclear reactor physics, uncertainties in the multigroup cross sections inevitably exist, and these uncertainties are considered as the most significant uncertainty source. Based on the home-developed 3D high-fidelity neutron transport code HNET, the perturbation theory was used to directly calculate the sensitivity coefficient of keff to the multigroup cross sections, and a reasonable relative covariance matrix with a specific energy group structure was generated directly from the evaluated covariance data by using the transforming method. Then, the “Sandwich Rule” was applied to quantify the uncertainty of keff. Based on these methods, a new SU module in HNET was developed to directly quantify the keff uncertainty with one-step deterministic transport methods. To verify the accuracy of the sensitivity and uncertainty analysis of HNET, an infinite-medium problem and the 2D pin-cell problem were used to perform SU analysis, and the numerical results demonstrate that acceptable accuracy of sensitivity and uncertainty analysis of the HNET are achievable. Finally, keff SU analysis of a 3D minicore was analyzed by using the HNET, and some important conclusions were also drawn from the numerical results.

39

AKUESON, P., and D. GUREVICH. "COTANGENT AND TANGENT MODULES ON QUANTUM ORBITS." International Journal of Modern Physics B 14, no. 22n23 (September 20, 2000): 2335–47. http://dx.doi.org/10.1142/s0217979200001850.

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Let [Formula: see text] be the "coordinate ring" of a quantum sphere. We introduce the cotangent module on the quantum sphere as a one-sided [Formula: see text]-module and show that there is no Yang–Baxter type operator converting it into a [Formula: see text]-bimodule which would be a flatly deformed object w.r.t. its classical counterpart. This implies non-flatness of any covariant differential calculus on the quantum sphere making use of the Leibniz rule. Also, we introduce the cotangent and tangent modules on generic quantum orbits and discuss some related problems of "braided geometry".

40

Hanen, Albert. "Un théorème limite pour les covariances des spins en deux sites dans le modèle de Sherrington–Kirkpatrick avec champ externe." Comptes Rendus Mathematique 342, no. 2 (January 2006): 147–50. http://dx.doi.org/10.1016/j.crma.2005.11.026.

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41

Rozora, I. V. "Analytical properties of sample paths of some stochastic processes." Bulletin of Taras Shevchenko National University of Kyiv. Series: Physics and Mathematics, no. 4 (2020): 11–15. http://dx.doi.org/10.17721/1812-5409.2020/4.1.

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The study of the analytical properties of random processes and their functionals, without a doubt, was and remains the relevant topic of the theory of random processes. The first result from which the study of the local properties of random processes began is Kolmogorov’s theorem on sample continuity with probability one. The classic result for Gaussian random processes is Dudley’s theorem. This paper is devoted to the study of local properties of sample paths of random processes that can be represented as a sum of squares of Gaussian random processes. Such processes are called square-Gaussian. We investigate the sufficient conditions of sample continuity with probability 1 for square-Gaussian processes based on the convergence of entropy Dudley type integrals. The estimation of the distribution of the continuity module is studied for square-Gaussian random processes. It is considered in detail an example with an estimator (correlogram) of the covariance function of a Gaussian stationary random process. The conditions on continuity of correlogram’s trajectories with probability one are found and the distribution of the continuity module is also estimated.

42

Siddiqi, Muhammad Hameed, Madallah Alruwaili, Amjad Ali, Saad Alanazi, and Furkh Zeshan. "Human Activity Recognition Using Gaussian Mixture Hidden Conditional Random Fields." Computational Intelligence and Neuroscience 2019 (August 18, 2019): 1–14. http://dx.doi.org/10.1155/2019/8590560.

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In healthcare, the analysis of patients’ activities is one of the important factors that offer adequate information to provide better services for managing their illnesses well. Most of the human activity recognition (HAR) systems are completely reliant on recognition module/stage. The inspiration behind the recognition stage is the lack of enhancement in the learning method. In this study, we have proposed the usage of the hidden conditional random fields (HCRFs) for the human activity recognition problem. Moreover, we contend that the existing HCRF model is inadequate by independence assumptions, which may reduce classification accuracy. Therefore, we utilized a new algorithm to relax the assumption, allowing our model to use full-covariance distribution. Also, in this work, we proved that computation wise our method has very much lower complexity against the existing methods. For the experiments, we used four publicly available standard datasets to show the performance. We utilized a 10-fold cross-validation scheme to train, assess, and compare the proposed model with the conditional learning method, hidden Markov model (HMM), and existing HCRF model which can only use diagonal-covariance Gaussian distributions. From the experiments, it is obvious that the proposed model showed a substantial improvement with p value ≤0.2 regarding the classification accuracy.

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BEGGS, EDWIN, and IBTISAM MASMALI. "A LERAY SPECTRAL SEQUENCE FOR NONCOMMUTATIVE DIFFERENTIAL FIBRATIONS." International Journal of Geometric Methods in Modern Physics 10, no. 05 (April 3, 2013): 1350015. http://dx.doi.org/10.1142/s0219887813500151.

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This paper describes the Leray spectral sequence associated to a differential fibration. The differential fibration is described by base and total differential graded algebras. The cohomology used is noncommutative differential sheaf cohomology. For this purpose, a sheaf over an algebra is a left module with zero curvature covariant derivative. As a special case, we can recover the Serre spectral sequence for a noncommutative fibration.

44

Kamhi, J. Frances, Iulian Ilieş, and James F. A. Traniello. "Social Complexity and Brain Evolution: Comparative Analysis of Modularity and Integration in Ant Brain Organization." Brain, Behavior and Evolution 93, no. 1 (2019): 4–18. http://dx.doi.org/10.1159/000497267.

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The behavioral demands of living in social groups have been linked to the evolution of brain size and structure, but how social organization shapes investment and connectivity within and among functionally specialized brain regions remains unclear. To understand the influence of sociality on brain evolution in ants, a premier clade of eusocial insects, we statistically analyzed patterns of brain region size covariation as a proxy for brain region connectivity. We investigated brain structure covariance in young and old workers of two formicine ants, the Australasian weaver ant Oecophylla smaragdina, a pinnacle of social complexity in insects, and its socially basic sister clade Formica subsericea. As previously identified in other ant species, we predicted that our analysis would recognize in both species an olfaction-related brain module underpinning social information processing in the brain, and a second neuroanatomical cluster involved in nonolfactory sensorimotor processes, thus reflecting conservation of compartmental connectivity. Furthermore, we hypothesized that covariance patterns would reflect divergence in social organization and life histories either within this species pair or compared to other ant species. Contrary to our predictions, our covariance analyses revealed a weakly defined visual, rather than olfactory, sensory processing cluster in both species. This pattern may be linked to the reliance on vision for worker behavioral performance outside of the nest and the correlated expansion of the optic lobes to meet navigational demands in both species. Additionally, we found that colony size and social organization, key measures of social complexity, were only weakly correlated with brain modularity in these formicine ants. Worker age also contributed to variance in brain organization, though in different ways in each species. These findings suggest that brain organization may be shaped by the divergent life histories of the two study species. We compare our findings with patterns of brain organization of other eusocial insects.

45

ELSAEV, Yakub V. "On a dilation of a some class of completely positive maps." Tambov University Reports. Series: Natural and Technical Sciences, no. 127 (2019): 333–39. http://dx.doi.org/10.20310/2686-9667-2019-24-127-333-339.

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In this article we investigate sesquilinear forms defined on the Cartesian product of Hilbert C^*-module M over C^*-algebra B and taking values in B. The set of all such defined sesquilinear forms is denoted by S_B (M). We consider completely positive maps from locally C^*-algebra A to S_B (M). Moreover we assume that these completely positive maps are covariant with respect to actions of a group symmetry. This allow us to view these maps as generalizations covariant quantum instruments which are very important for the modern quantum mechanic and the quantum field theory. We analyze the dilation problem for these class of maps. In order to solve this problem we construct the minimal Stinespring representation and prove that every two minimal representations are unitarily equivalent.

46

SKEIDE, MICHAEL. "ISOMETRIC DILATIONS OF REPRESENTATIONS OF PRODUCT SYSTEMS VIA COMMUTANTS." International Journal of Mathematics 19, no. 05 (May 2008): 521–39. http://dx.doi.org/10.1142/s0129167x08004790.

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We construct a weak dilation of a not necessarily unital CP-semigroup to an E-semigroup acting on the adjointable operators of a Hilbert module with a unit vector. We construct the dilation in such a way that the dilating E-semigroup has a pre-assigned product system. Then, making use of the commutant of von Neumann correspondences, we apply the dilation theorem to prove that covariant representations of product systems admit isometric dilations.

47

Li, Xin, Tao Li, Ziqi Chen, Kaiwen Zhang, and Runliang Xia. "Attentively Learning Edge Distributions for Semantic Segmentation of Remote Sensing Imagery." Remote Sensing 14, no. 1 (December 26, 2021): 102. http://dx.doi.org/10.3390/rs14010102.

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Semantic segmentation has been a fundamental task in interpreting remote sensing imagery (RSI) for various downstream applications. Due to the high intra-class variants and inter-class similarities, inflexibly transferring natural image-specific networks to RSI is inadvisable. To enhance the distinguishability of learnt representations, attention modules were developed and applied to RSI, resulting in satisfactory improvements. However, these designs capture contextual information by equally handling all the pixels regardless of whether they around edges. Therefore, blurry boundaries are generated, rising high uncertainties in classifying vast adjacent pixels. Hereby, we propose an edge distribution attention module (EDA) to highlight the edge distributions of leant feature maps in a self-attentive fashion. In this module, we first formulate and model column-wise and row-wise edge attention maps based on covariance matrix analysis. Furthermore, a hybrid attention module (HAM) that emphasizes the edge distributions and position-wise dependencies is devised combing with non-local block. Consequently, a conceptually end-to-end neural network, termed as EDENet, is proposed to integrate HAM hierarchically for the detailed strengthening of multi-level representations. EDENet implicitly learns representative and discriminative features, providing available and reasonable cues for dense prediction. The experimental results evaluated on ISPRS Vaihingen, Potsdam and DeepGlobe datasets show the efficacy and superiority to the state-of-the-art methods on overall accuracy (OA) and mean intersection over union (mIoU). In addition, the ablation study further validates the effects of EDA.

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Panyushev, Dmitri I. "Parabolic Subgroups with Abelian Unipotent Radical as a Testing Site for Invariant Theory." Canadian Journal of Mathematics 51, no. 3 (June 1, 1999): 616–35. http://dx.doi.org/10.4153/cjm-1999-028-9.

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AbstractLet L be a simple algebraic group and P a parabolic subgroup with Abelian unipotent radical Pu. Many familiar varieties (determinantal varieties, their symmetric and skew-symmetric analogues) arise as closures of P-orbits in Pu. We give a unified invariant-theoretic treatment of various properties of these orbit closures. We also describe the closures of the conormal bundles of these orbits as the irreducible components of some commuting variety and show that the polynomial algebra k[Pu] is a free module over the algebra of covariants.

49

Everall, Andrew, Douglas Boubert, Sergey E. Koposov, Leigh Smith, and Berry Holl. "Completeness of the Gaia-verse – IV. The astrometry spread function of Gaia DR2." Monthly Notices of the Royal Astronomical Society 502, no. 2 (February 1, 2021): 1908–24. http://dx.doi.org/10.1093/mnras/stab041.

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ABSTRACT Gaia Data Release 2 (DR2) published positions, parallaxes, and proper motions for an unprecedented 1331 909 727 sources, revolutionizing the field of Galactic dynamics. We complement this data with the astrometry spread function (ASF), the expected uncertainty in the measured positions, proper motions, and parallax for a non-accelerating point source. The ASF is a Gaussian function for which we construct the 5D astrometric covariance matrix as a function of position on the sky and apparent magnitude using the Gaia DR2 scanning law and demonstrate excellent agreement with the observed data. This can be used to answer the question ‘What astrometric covariance would Gaia have published if my star was a non-accelerating point source?’. The ASF will enable characterization of binary systems, exoplanet orbits, astrometric microlensing events, and extended sources that add an excess astrometric noise to the expected astrometry uncertainty. By using the ASF to estimate the unit weight error of Gaia DR2 sources, we demonstrate that the ASF indeed provides a direct probe of the excess source noise. We use the ASF to estimate the contribution to the selection function of the Gaia astrometric sample from a cut on astrometric_sigma5d_max showing high completeness for G < 20 dropping to ${\lt} 1{{\ \rm per\ cent}}$ in underscanned regions of the sky for G = 21. We have added an ASF module to the python package scanninglaw (https://github.com/gaiaverse/scanninglaw) through which users can access the ASF.

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Ullah, Israr, Muhammad Fayaz, and DoHyeun Kim. "Improving Accuracy of the Kalman Filter Algorithm in Dynamic Conditions Using ANN-Based Learning Module." Symmetry 11, no. 1 (January 16, 2019): 94. http://dx.doi.org/10.3390/sym11010094.

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Prediction algorithms enable computers to learn from historical data in order to make accurate decisions about an uncertain future to maximize expected benefit or avoid potential loss. Conventional prediction algorithms are usually based on a trained model, which is learned from historical data. However, the problem with such prediction algorithms is their inability to adapt to dynamic scenarios and changing conditions. This paper presents a novel learning to prediction model to improve the performance of prediction algorithms under dynamic conditions. In the proposed model, a learning module is attached to the prediction algorithm, which acts as a supervisor to monitor and improve the performance of the prediction algorithm continuously by analyzing its output and considering external factors that may have an influence on its performance. To evaluate the effectiveness of the proposed learning to prediction model, we have developed the artificial neural network (ANN)-based learning module to improve the prediction accuracy of the Kalman filter algorithm as a case study. For experimental analysis, we consider a scenario where the Kalman filter algorithm is used to predict actual temperature from noisy sensor readings. the Kalman filter algorithm uses fixed process error covariance R, which is not suitable for dynamic situations where the error in sensor readings varies due to some external factors. In this study, we assume variable error in temperature sensor readings due to the changing humidity level. We have developed a learning module based on ANN to estimate the amount of error in current readings and to update R in the Kalman filter accordingly. Through experiments, we observed that the Kalman filter with the learning module performed better (4.41%–11.19%) than the conventional Kalman filter algorithm in terms of the root mean squared error metric.

Статті в журналах з теми "Modèle de covariance"

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