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It is the intent of this paper to locate the activation point in Transcranial Magnetic Stimulation (TMS) efficiently. The schemes of coil array in torus shape is presented to get the electromagnetic field distribution with ideal focusing capability. Then an improved adaptive genetic algorithm (AGA) is applied to the optimization of both value and phase of the current infused in each coil. Based on the calculated results of the optimized current configurations, ideal focusing capability is drawn as contour lines and 3-D mesh charts of magnitude of both magnetic and electric field within the calculation area. It is shown that the coil array has good capability to establish focused shape of electromagnetic distribution. In addition, it is also demonstrated that the coil array has the capability to focus on two or more targets simultaneously.

This paper presents a multi-innovation stochastic gradient parameter estimation algorithm for dual-rate sampled state-space systems with d -step time delay by the multi-innovation identification theory. Considering the stochastic disturbance in industrial process and using the gradient search, a multi-innovation stochastic gradient algorithm is proposed through expanding the scalar innovation into an innovation vector in order to obtain more accurate parameter estimates. The difficulty of identification is that the information vector in the identification model contains the unknown states. The proposed algorithm uses the state estimates of the observer instead of the state variables to realize the parameter estimation. The simulation results indicate that the proposed algorithm works well. [ABSTRACT FROM AUTHOR]

Photovoltaic storage system (PVSS) has been spawned with the combined application of photovoltaic (PV), energy storage (ES) and energy blockchain (EB), which has also made important contributions to the energy structure adjustment, energy transaction security and ecological environment protection. The establishment of a reasonable task matching mechanism can further improve the operation efficiency and quality of the system under the EB environment, and this paper consequently constructs a task matching model of PVSS based on GA-CLOUD-GS algorithm. Firstly, the decision-making committee is set up and the index system is determined for the to-be-matched task. Secondly, the Genetic Algorithm (GA) comprehensive weighting method is introduced to integrate the subjective and objective weights to achieve the weight optimization. Thirdly, the cloud model is used to obtain the preference order and priority order of the to-be-matched subjects. Fourthly, the Gale-Shapley (GS) algorithm is used to obtain the task matching results. Finally, the operability, the stability and the effectiveness of the model are separately verified through numerical simulation, sensitivity analysis and comparative analysis. Corresponding suggestions for the task matching of PVSS in the EB environment are also put forward according to the research content. • The necessity, superiority, and application scenarios of collaborative development between PVSS and EB are clarified, and the importance of research on task matching mechanism is identified. • A task matching mechanism model based on the GA-CLOUD-GS algorithm is established, the feasibility, stability, and effectiveness of the established model were verified. • Relevant suggestions are provided for the development of PVSS in the EB environment. [ABSTRACT FROM AUTHOR]

Abstract: Binary snow maps and fractional snow cover data are provided routinely from MODIS (Moderate Resolution Imaging Spectroradiometer). This paper investigates how the wide observation angles of MODIS influence the current snow mapping algorithm in forested areas. Theoretical modeling results indicate that large view zenith angles (VZA) can lead to underestimation of fractional snow cover (FSC) by reducing the amount of the ground surface that is viewable through forest canopies, and by increasing uncertainties during the gridding of MODIS data. At the end of the MODIS scan line, the total modeled error can be as much as 50% for FSC. Empirical analysis of MODIS/Terra snow products in four forest sites shows high fluctuation in FSC estimates on consecutive days. In addition, the normalized difference snow index (NDSI) values, which are the primary input to the MODIS snow mapping algorithms, decrease as VZA increases at the site level. At the pixel level, NDSI values have higher variances, and are correlated with the normalized difference vegetation index (NDVI) in snow covered forests. These findings are consistent with our modeled results, and imply that consideration of view angle effects could improve MODIS snow monitoring in forested areas. [Copyright &y& Elsevier]