With intrinsic giant anomalous Hall and Nernst effects, Weyl ferromagnet C02MnGa stands as an ideal candidate for exploring efficient charge-to-spin conversions. In this work, by utilizing the high-quality epitaxial C...
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ISBN:
(数字)9798350362213
ISBN:
(纸本)9798350362220
With intrinsic giant anomalous Hall and Nernst effects, Weyl ferromagnet C02MnGa stands as an ideal candidate for exploring efficient charge-to-spin conversions. In this work, by utilizing the high-quality epitaxial C02MnGa single films, we observed a sizable unidirectional magnetoresistance. Surprisingly, the isotropic crystallographic axis dependence of unidirectional magnetoresistance, together with its linear scaling to the C02MnGa thickness, neither can be explained by the conventional spin current drift-diffusion process. By employing heat equation, we analytically derived the current induced vertical temperature gradient, and unambiguously show the thickness dependence of unidirectional magnetoresistance induced by anomalous Nernst effects. Our work provides direct evidences of thermoelectric voltages in the nonlinear transport that may be extended to other material systems as well.
Object pose estimation is a fundamental computer vision problem with broad applications in augmented reality and robotics. Over the past decade, deep learning models, due to their superior accuracy and robustness, hav...
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We build upon recent work on using Machine Learning models to estimate Hamiltonian parameters using continuous weak measurement of qubits as input. We consider two settings for the training of our model: (1) supervise...
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The search for two-dimensional multiferroic materials is an exciting yet challenging endeavor. Recently, Song et al. reported the exciting discovery of type-II multiferroic order in an antiferromagnetic (AFM) NiI2 sin...
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This paper proposes an application of a new observer theory for non-linear systems developed previously to solve the Cryptanalysis problem of a special class of pseudorandom generators which are commonly used in Crypt...
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This paper proposes an application of a new observer theory for non-linear systems developed previously to solve the Cryptanalysis problem of a special class of pseudorandom generators which are commonly used in Cryptography. The Cryptanalysis problem addressed here is that of the recovery of internal state of the non-linear dynamic stream generator from the output stream. The proposed methodology is termed as observability attack. It is also shown that for a special class of generators, the computations are of complexity O (D 4 ) in pre-computation and of O(D) for online computation, where D = σ d i=0 (n i) for this class of stream generators with n states and d the degree of the output function. The attack is technically applicable over general finite fields as well as most dynamic systems arising from models of stream ciphers and appropriate bounds on computation are estimated. From these complexity bounds, it follows that this attack is feasible in realistic cases and gives important estimates of time and memory resources required for Cryptanalysis of a class of stream ciphers.
This paper considers distributed online convex optimization with time-varying constraints. In this setting, a network of agents makes decisions at each round, and then only a portion of the loss function and a coordin...
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The insistence of this paper is to design Fractional order-proportional Integral Derivative (FO-PID) and Integral order –Proportional Integral Derivative (IO-PID) controllers for trajectory tracking control of Twin r...
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The insistence of this paper is to design Fractional order-proportional Integral Derivative (FO-PID) and Integral order –Proportional Integral Derivative (IO-PID) controllers for trajectory tracking control of Twin rotor Multiple Input Multiple Output (MIMO) system (TRMS). The aim of these designed controllers is to move the main and tail actuator at the desired angles accurately to fulfill the demanding attributes so that TRMS should stabilize while hovering. The controller parameters of both the controllers are optimized using fmincon function as well as Multiobjective genetic algorithm. Both the controller are tested in real time and their performance are compared for control of yaw and pitch angles of TRMS. Manual disturbances are given at after 40 seconds of first given disturbance, and the designed controllers are highly capable in diminishing quickly the effect of manual perturbations given to the main and tail rotor of TRMS. From experiment it is observed from comparative performance that FO-PID controller tuned using multiobjective genetic algorithm give best performance in term of time taken to stabilization after the given disturbance.
An optimization method is proposed in this paper for novel deployment of given number of directional landmarks (location and pose) within a given region in the 3-D task space. This new deployment technique is built on...
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Waves seriously impact port construction, worldwide route planning, military activities, and wave power generation. To improve the accuracy of significant wave height prediction, we proposed a novel prediction method,...
Waves seriously impact port construction, worldwide route planning, military activities, and wave power generation. To improve the accuracy of significant wave height prediction, we proposed a novel prediction method, a multi-layer perceptron combined with a backpropagation adjustment (MLP-BP) prediction model that combines mutation mode decomposition (VMD) and a simulated annealing optimization algorithm (SA). Firstly, we use the variable modulus method to decompose the significant wave height sequence data and transform the wave height sequence into multiple different sub-modes (IMF) to reduce the complexity and non-stationarity of the data. Secondly, the simulated annealing algorithm (SA) is used to optimize the weight and bias of the MLP-BP neural network to find the optimal parameter configuration and improve the performance and generalization ability of the prediction model. Finally, the decomposed sub-modal components of each significant wave height sequence are inserted into the MLP-BP neural network and the predicted values of each element are summed to obtain the final significant wave height prediction. The prediction results of the SSA-MLP-BP, PSO-MLP-BP, SA-MLP-BP, and VMD-SA-MLP-BP were compared and demonstrated that the VMD-SA-MLP-BP model performed best. The MAE, MAPE, MSE, RMSE, and R2 of the prediction evaluation indexes were 0.036 m, 11.7%, 0.004 m 2 , 0.067 m, and 0.983, respectively, which performed well in predicting significant wave height.
Previous controlled experiments on single-lane ring roads [1] have shown that a single partially autonomous vehicle (AV) can effectively mitigate traffic waves. This naturally prompts the question of how these finding...
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