The implementation of titanium dioxide (TiO2) as a photocatalyst material in hydrogen (H2) evolution reaction (HER) has embarked renewed interest in the past decade. Rapid electron-hole pairs recombination and wide ba...
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In this paper we consider the estimation of unknown parameters in Bayesian inverse problems. In most cases of practical interest, there are several barriers to performing such estimation, This includes a numerical app...
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The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integratin...
The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries, the boundaries of both are constantly expanding, and their connections are becoming closer.
The objective of this study is to develop a wind farm placement and investment methodology based on a linear optimization *** problem has a major significance for the investment success for the projects of renewable e...
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The objective of this study is to develop a wind farm placement and investment methodology based on a linear optimization *** problem has a major significance for the investment success for the projects of renewable energy such as wind *** this study,a mesoscale approach is adopted whereby the wind farm location is investigated in comparison with a microscale approach where the location of each individual turbine is *** study focuses on the placement of a wind farm by economical optimization constrained by the power system,wind resources,and *** optimization is introduced in this context at the power system which is constrained by wind farm planning.
Infectious disease threats to individual and public health are numerous, varied and frequently unexpected. Artificial intelligence (AI) and related technologies, which are already supporting human decision making in e...
The computation of the radiative transfer equation is expensive mainly due to two stiff terms:the transport term and the collision *** stiffness in the former comes from the fact that particles(such as photons)travel ...
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The computation of the radiative transfer equation is expensive mainly due to two stiff terms:the transport term and the collision *** stiffness in the former comes from the fact that particles(such as photons)travel at the speed of light,while that in the latter is due to the strong scattering in the optically thick *** study the fully implicit scheme for this equation to account for the *** main challenge in the implicit treatment is the coupling between the spacial and angular coordinates that requires the large size of the to-be-inverted matrix,which is also ill-conditioned and not necessarily *** main idea is to utilize the spectral structure of the ill-conditioned matrix to construct a pre-conditioner,which,along with an exquisite split of the spatial and angular dependence,significantly improve the condition number and allows a matrix-free *** also design a fast solver to compute this pre-conditioner explicitly in *** method is shown to be efficient in both diffusive and free streaming limit,and the computational cost is comparable to the state-of-the-art *** examples including anisotropic scattering and two-dimensional problems are provided to validate the effectiveness of our method.
Using electronic health records (EHR) data for predicting the condition of patients who are in need of emergency care is a promising application of machine learning. With the help of machine learning, complex problems...
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One of the main challenges in modeling massive stars to the onset of core collapse is the computational bottleneck of nucleosynthesis during advanced burning stages. The number of isotopes formed requires solving a la...
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In this paper,we propose a simple energy decaying iterative thresholding algorithm to solve the two-phase minimum compliance *** material domain is implicitly represented by its characteristic function,and the problem...
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In this paper,we propose a simple energy decaying iterative thresholding algorithm to solve the two-phase minimum compliance *** material domain is implicitly represented by its characteristic function,and the problem is formulated into a minimization problem by the principle of minimum complementary *** prove that the energy is decreasing in each *** effective continuation schemes are proposed to avoid trapping into the local *** results on 2D isotropic linear material demonstrate the effectiveness of the proposed methods.
The sensitivity of power system operations uncertainties that originate from distributed renewable generation, natural disasters like hurricanes, and changing loads such as vehicle charging needs careful engineering f...
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The sensitivity of power system operations uncertainties that originate from distributed renewable generation, natural disasters like hurricanes, and changing loads such as vehicle charging needs careful engineering for reliable, resilient and robust power systems. The power system is a global sensitivity problem since each input uncertainty varies the output and all the variables simultaneously that have higher order interactions between inputs, unlike local sensitivity. The article assesses and compares the global sensitivity methods of Sobol’ sensitivity indices, the activity scores of the active subspace method, and Shapley values, to assess the importance of input parameters in the IEEE 14-bus modified test system. The limitations and advantages of each approach are illustrated to reduce the complexity of the model by performing uncertainty quantification for the output by global sensitivity indices in the IEEE 14-bus modified test system.
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