Results 81 to 90 of about 154,479 (279)
Relative Linear Sets and Similarity of Matrices Whose Elements Belong to a Division Algebra [PDF]
M. H. Ingraham, M. C. Wolf
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Abstract The German Research Foundation has established the priority program SPP 100+. Its subject is monitoring bridge structures in civil engineering. The data‐driven methods cluster deals with the use of measurements and their special global and local analysis methods, which complement each other in an overall multi‐scale concept in order to realize
Maximilian Rohrer+13 more
wiley +1 more source
Corn cob pyrolysis: A systematic literature review of methods and applications
Mapping the research landscape of corn cob pyrolysis. Abstractas The agricultural sector is experiencing a surge in waste generation due to population growth, creating an urgent need to convert byproducts into value‐added products. Maize (Zea mays L.), a leading global crop, produces significant byproducts, such as corn cob, which are often undervalued.
Vilmar Steffen+5 more
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X‐Ray Absorption Studies of Local Structure of Dilute Ionic Species in Molten Salts
This article reviews the state of the art in the use of X‐ray absorption spectroscopy methods, both experimental and theoretical, for understanding the structure of dopant metal ions in molten salts. Recent strategies, including molecular dynamics simulations and neural network–assisted analysis of X‐ ray absorption spectroscopy as well as chemometrics
Kaifeng Zheng+11 more
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This work explores data acquisition and reduction protocols for atomic pair distribution scheme that enhances high‐angle data collection, and the effects of instrumental parameters on resulting pair distribution functions are examined. A correction for sample absorption in PDFgetX3 is introduced. Herein, data acquisition protocols are explored and data
Till Schertenleib+5 more
wiley +1 more source
A General Approach to Dropout in Quantum Neural Networks
Randomly dropping artificial neurons and all their connections in the training phase reduces overfitting issues in classical neural networks, thus improving performances on previously unseen data. The authors introduce different dropout strategies applied to quantum neural networks, learning models based on parametrized quantum circuits.
Francesco Scala+3 more
wiley +1 more source
First‐order Sobolev spaces, self‐similar energies and energy measures on the Sierpiński carpet
Abstract For any p∈(1,∞)$p \in (1,\infty)$, we construct p$p$‐energies and the corresponding p$p$‐energy measures on the Sierpiński carpet. A salient feature of our Sobolev space is the self‐similarity of energy. An important motivation for the construction of self‐similar energy and energy measures is to determine whether or not the Ahlfors regular ...
Mathav Murugan, Ryosuke Shimizu
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Benefits of Open Quantum Systems for Quantum Machine Learning
Quantum machine learning (QML), poised to transform data processing, faces challenges from environmental noise and dissipation. While traditional efforts seek to combat these hindrances, this perspective proposes harnessing them for potential advantages. Surprisingly, under certain conditions, noise and dissipation can benefit QML.
María Laura Olivera‐Atencio+2 more
wiley +1 more source
Computation of Difference Grobner Bases [PDF]
This paper is an updated and extended version of our note \cite{GR'06} (cf.\ also \cite{GR-ACAT}). To compute difference \Gr bases of ideals generated by linear polynomials we adopt to difference polynomial rings the involutive algorithm based on Janet ...
Vladimir P. Gerdt, Daniel Robertz
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