This study addresses the deficiencies in the assumptions of the results in Chen and Yang, 2017 [1] due to the lack of uniformity. We first show the missing hypothesis by presenting a counterexample. Then we prove why ...
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A semi-analytical finite element method(SAFEM),based on the two-scale asymptotic homogenization method(AHM)and the finite element method(FEM),is implemented to obtain the effective properties of two-phase fiber-reinfo...
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A semi-analytical finite element method(SAFEM),based on the two-scale asymptotic homogenization method(AHM)and the finite element method(FEM),is implemented to obtain the effective properties of two-phase fiber-reinforced composites(FRCs).The fibers are periodically distributed and unidirectionally aligned in a homogeneous *** framework addresses the static linear elastic micropolar problem through partial differential equations,subject to boundary conditions and perfect interface contact *** mathematical formulation of the local problems and the effective coefficients are presented by the *** local problems obtained from the AHM are solved by the FEM,which is denoted as the *** numerical results are provided,and the accuracy of the solutions is analyzed,indicating that the formulas and results obtained with the SAFEM may serve as the reference points for validating the outcomes of experimental and numerical computations.
Thanks to advancements in technology, the importance of computational methods used in tasks like storing and processing data is increasing as the data produced becomes more complex in both size and detail. Methods suc...
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Amidst the rapidly expanding integration of large language models(LLMs)across various sectors(ranging from everyday applications to specialized fields demanding stringent regulatory adherence),our investigation seeks ...
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Amidst the rapidly expanding integration of large language models(LLMs)across various sectors(ranging from everyday applications to specialized fields demanding stringent regulatory adherence),our investigation seeks to determine how well these models can support medical device software *** device classification functions to systematically categorize devices according to their designated use,associated risk levels,and requisite regulatory oversight,thereby providing a structured framework for ensuring safety and efficacy as mandated by regulatory authorities.
Corrosion poses a significant challenge in industries due to material degradation and high maintenance costs, making effective inhibitors essential. Recent studies suggest expired pharmaceuticals as alternative corros...
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In this study, two deep learning models for automatic tattoo detection were analyzed;a modified Convolutional Neural Network (CNN) and pre-trained ResNet-50 model. In order to achieve this, ResNet-50 uses transfer lea...
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Topological edge states arise in non-Hermitian parity-time(PT)-symmetric systems, and manifest themselves as bright or dark edge states, depending on the imaginary components of their eigenenergies. As the spatial pro...
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Topological edge states arise in non-Hermitian parity-time(PT)-symmetric systems, and manifest themselves as bright or dark edge states, depending on the imaginary components of their eigenenergies. As the spatial probabilities of dark edge states are suppressed during the non-unitary dynamics, it is a challenge to observe them experimentally. Here we report the experimental detection of dark edge states in photonic quantum walks with spontaneously broken PT symmetry, thus providing a complete description of the topological phenomena therein. We experimentally confirm that the global Berry phase in PT-symmetric quantum-walk dynamics unambiguously defines topological invariants of the system in both the PT-symmetry-unbroken and-broken regimes. Our results establish a unified framework for characterizing topology in PT-symmetric quantum-walk dynamics, and provide a useful method to observe topological phenomena in PT-symmetric non-Hermitian systems in general.
The design and construction of delivering announcements using a web-based SMS gateway aims to help overcome problems that often occur at pioneer airports;this is because when passengers want to travel, many passengers...
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In this research study, we compare the predictive performance of two advanced deep learning-based models in order to provide a solution to TACE (Transarterial Chemoembolization) response prediction in HCC (Hepatocellu...
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Thanks to advancements in technology, the importance of computational methods used in tasks like storing and processing data is increasing as the data produced becomes more complex in both size and detail. Methods suc...
Thanks to advancements in technology, the importance of computational methods used in tasks like storing and processing data is increasing as the data produced becomes more complex in both size and detail. Methods such as Tucker Decomposition, CANDECOMP/PARAFAC, Alternating Least Squares and their derivations, are widely used in the field to meet the requirements in numerous areas. These cases contain expressing high-dimensional data using lower-dimensional tensors, cleansing the data of errors that occur during data acquisition while also ensuring an efficient compression. This study proposes a new method that exploits the tensor structure of 3-dimensional data by calculating the lower-dimensional components via Enhanced Multivariance Products Representation and produces a superior approximation compared to well-known tensor decomposition methods. An iterative process is established to calculate the optimal support tensors and to determine the lower-dimensional components, which in further steps are employed to reconstruct the approximation.
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