Off-line Chinese handwriting recognition using multi-stage neural network architecture

In this paper, we propose a Multi-stage Neural Network Architecture (MNNA) which integrates several neural networks and various feature extraction approaches into a unique pattern recognition system. General mechanism for designing the MNNA is presented. A three-stage fully connected feedforward neural networks system is designed for Handwritten Chinese Character Recognition (HCCR). Different feature extraction methods are employed at each stage. Experiments show that the three-stage neural network HCCR system has achieved impressive performance and the preliminary results are very encouraging.published_or_final_versio

Scattering Analysis of Electromagnetic Materials Using Fast Dipole Method Based on Volume Integral Equation

The fast dipole method (FDM) is extended to analyze the scattering of dielectric and magnetic materials by solving the volume integral equation (VIE). The FDM is based on the equivalent dipole method (EDM) and can achieve the separation of the field dipole and source dipole, which reduces the complexity of interactions between two far groups (such as group i and group j) from O(NiNj) to O(Ni+Nj), where Ni and Nj are the numbers of dipoles in group i and group j, respectively. Targets including left-handed materials (LHMs), which are a kind of dielectric and magnetic materials, are calculated to demonstrate the merits of the FDM. Furthermore, in this study we find that the convergence may become much slower when the targets include LHMs compared with conventional electromagnetic materials. Numerical results about convergence characteristics are presented to show this property

A Decoupling Control Strategy for Multilayer Register System in Printed Electronic Equipment

Register accuracy is an important index to evaluate the quality of electronic products printed by gravure printed electronic equipment. However, the complex relationships of multilayer register system make the problem of decoupling control difficult to be solved, which has limited the improvement of register accuracy for the gravure printed electronic equipment. Therefore, this paper presents an integrated decoupling control strategy based on feedforward control and active disturbance rejection control (ADRC) to solve the strong coupling, strong interference, and time-delay problems of multilayer register system. First of all, a coupling and nonlinear model is established according to the multilayer register working principle in gravure printing, and then a linear model of the register system is derived based on the perturbation method. Secondly, according to the linear model, a decoupling control strategy is designed based on feedforward control and ADRC for the multilayer register system. Finally, the results of computer simulation show that the proposed control methodology can realize a decoupling control and has good control performance for multilayer register system

A Broadband Spectrum Sensing Algorithm in TDCS Based on ICoSaMP Reconstruction

In order to solve the problem that the wideband compressive sensing reconstruction algorithm cannot accurately recover the signal under the condition of blind sparsity in the low SNR environment of the transform domain communication system. This paper use band occupancy rates to estimate sparseness roughly, at the same time, use the residual ratio threshold as iteration termination condition to reduce the influence of the system noise. Therefore, an ICoSaMP(Improved Compressive Sampling Matching Pursuit) algorithm is proposed. The simulation results show that compared with CoSaMP algorithm, the ICoSaMP algorithm increases the probability of reconstruction under the same SNR environment and the same sparse degree. The mean square error under the blind sparsity is reduced

Exosomal microRNA-Based therapies for skin diseases

Based on engineered cell/exosome technology and various skin-related animal models, exosomal microRNA (miRNA)-based therapies derived from natural exosomes have shown good therapeutic effects on nine skin diseases, including full-thickness skin defects, diabetic ulcers, skin burns, hypertrophic scars, psoriasis, systemic sclerosis, atopic dermatitis, skin aging, and hair loss. Comparative experimental research showed that the therapeutic effect of miRNA-overexpressing exosomes was better than that of their natural exosomes. Using a dual-luciferase reporter assay, the targets of all therapeutic miRNAs in skin cells have been screened and confirmed. For these nine types of skin diseases, a total of 11 animal models and 21 exosomal miRNA-based therapies have been developed. This review provides a detailed description of the animal models, miRNA therapies, disease evaluation indicators, and treatment results of exosomal miRNA therapies, with the aim of providing a reference and guidance for future clinical trials. There is currently no literature on the merits or drawbacks of miRNA therapies compared with standard treatments

DRMC: A Generalist Model with Dynamic Routing for Multi-Center PET Image Synthesis

Multi-center positron emission tomography (PET) image synthesis aims at recovering low-dose PET images from multiple different centers. The generalizability of existing methods can still be suboptimal for a multi-center study due to domain shifts, which result from non-identical data distribution among centers with different imaging systems/protocols. While some approaches address domain shifts by training specialized models for each center, they are parameter inefficient and do not well exploit the shared knowledge across centers. To address this, we develop a generalist model that shares architecture and parameters across centers to utilize the shared knowledge. However, the generalist model can suffer from the center interference issue, \textit{i.e.} the gradient directions of different centers can be inconsistent or even opposite owing to the non-identical data distribution. To mitigate such interference, we introduce a novel dynamic routing strategy with cross-layer connections that routes data from different centers to different experts. Experiments show that our generalist model with dynamic routing (DRMC) exhibits excellent generalizability across centers. Code and data are available at: https://github.com/Yaziwel/Multi-Center-PET-Image-Synthesis.Comment: This article has been early accepted by MICCAI 2023,but has not been fully edited. Content may change prior to final publicatio

Exposure to Electric Vehicle Technology at Home and Work Can Fuel Market Growth

Sales of plug-in electric vehicles (PEVs), which include battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs), have grown substantially in recent years. To encourage PEV adoption, policymakers have offered monetary incentives for new PEV purchases, invested in charging infrastructure, and provided use-based incentives like High-Occupancy Vehicle (HOV) lane access and parking benefits. But questions remain regarding where, for how long, and how much promotion and government support might be necessary to achieve the state’s targets. Existing research on technology diffusion indicates that exposure through neighbors, workplace peers, and other acquaintances can legitimize new technology for the mass market and accelerate its market penetration. Researchers from the University of California, Davis and Irvine examined the adoption of PEVs in California between 2014 and 2016, both spatially and temporally, to gain a better understanding of the technology diffusion process and the effect of technology exposure, while controlling for sociodemographic factors and the effect of PEV incentive programs on PEV adoption in the state. This policy brief summarizes the findings from that research and provides policy implications.View the NCST Project Webpag

Plug-in Electric Vehicle Diffusion in California: Role of Exposure to New Technology at Home and Work

The market for plug-in electric vehicles (PEVs) that primarily include battery electric vehicles (BEVs) and plug-in hybrid vehicles (PHEVs) has been rapidly growing in California for the past few years. Given the targets for PEV penetration in the state, it is important to have a better understanding of the pattern of technology diffusion and the factors that are driving the process. Using spatial analysis and Poisson count models, the researchers identify the importance of a neighborhood effect (at home locations) and workplace effect (at commute destinations) in supporting the diffusion of PEV technology in California. In the case of new BEV sales, they found that exposure to one additional BEV or PHEV within a 1-mile radius of a block group centroid is associated with a 0.2% increase in BEV sales in the block group. Interestingly, for new PHEV sales, the neighborhood effect of BEV sales is negative, suggesting that enhanced exposure to this type of technology (which is differentiated in distinctive ways from PHEVs) may impact new PHEV sales through a substitution effect. Specifically, higher BEV concentration in an area can have an overall negative effect on new PHEV sales. While the neighborhood effect at residential locations is important, the workplace effect also has a notably important effect on new PEV sales. Both effects work in combination with socioeconomic, demographic, policy, and built environment factors in encouraging PEV adoption. These results suggest that policymakers should consider targeted programs and investments that can boost the impact of neighborhood and peer effects on PEV salesView the NCST Project Webpag