With the evolution of high-performancecomputer and data center interconnect communication rates from 53.125Gbps to 106.25Gbps, high-speed serial interfaces face a dramatic increase in BER challenges, which seriously ...
详细信息
In this paper,we present a novel surface mesh generation approach that splits B-rep geometry models into isotropic triangular meshes based on neural networks and splitting *** the first stage,a recursive method is des...
详细信息
In this paper,we present a novel surface mesh generation approach that splits B-rep geometry models into isotropic triangular meshes based on neural networks and splitting *** the first stage,a recursive method is designed to generate plentiful data to train the neural network model *** the second stage,the implemented mesh generator,ISpliter,maps each surface patch into the parameter plane,and then the trained neural network model is applied to select the optimal splitting line to divide the patch into subdomains continuously until they are all *** the third stage,ISpliter remaps the 2D mesh back to the physical space and further optimizes *** typical cases are evaluated to compare the mesh quality generated by ISpliter and two baselines,Gmsh and *** results show that ISpliter can generate isotropic triangular meshes with high average quality,and the generated meshes are comparable to those generated by the other two software under the same configuration.
As near-infrared spectroscopy technology is increasingly applied in fields such as biomedicine, food detection, and night vision, the demand for efficient near-infrared light sources is growing rapidly. However, tradi...
详细信息
The Domain Name System (DNS) plays a crucial role in contemporary internet infrastructure. Despite the geographical distance of public DNS servers posing a challenge in minimizing domain name resolution latency, there...
详细信息
Behavior trees (BTs) as a control structure in robotics are increasingly being used in safety-critical domains, which makes it very important to verify the correctness of BTs. This fast abstract reports our in-progres...
详细信息
As the condensed matter analog of Majorana fermion, the Majorana zero-mode is well known as a building block of fault-tolerant topological quantum computing. This review focuses on the recent progress of Majorana expe...
详细信息
As the condensed matter analog of Majorana fermion, the Majorana zero-mode is well known as a building block of fault-tolerant topological quantum computing. This review focuses on the recent progress of Majorana experiments, especially experiments about semiconductor-superconductor hybrid devices. We first sketch Majorana zero-mode formation from a bottom-up view,which is more suitable for beginners and experimentalists. Then, we survey the status of zero-energy state signatures reported recently, from zero-energy conductance peaks, the oscillations, the quantization, and the interactions with extra degrees of freedom. We also give prospects of future experiments for advancing one-dimensional semiconductor nanowire-superconductor hybrid materials and devices.
We designed a reconfigurable dual-interferometer coupled silicon nitride microring *** tuning the integrated heater on interferometer's arms,the"critical coupling"bandwidth of resonant mode is continuous...
详细信息
We designed a reconfigurable dual-interferometer coupled silicon nitride microring *** tuning the integrated heater on interferometer's arms,the"critical coupling"bandwidth of resonant mode is continuously adjustable whose quality factor varies from 7.9×10^(4) to 1.9×10^(5) with the extinction ratio keeping higher than 25 *** a variety of coupling spanning from"under-coupling"to"over-coupling"were achieved,showing the ability to tune the quality factor from 6.0×10^(3) to 2.3×10^(5).Our design can provide an adjustable filtering method on silicon nitride photonic chip and contribute to optimize the nonlinear process for quantum photonics and all-optical signal processing.
Learning the causal relationships among variables from observational data has been a significant problem in statistics and data mining, and one such algorithm is the PC algorithm. However, the existing CPU-based imple...
详细信息
The uncertainty in the position and size of occluding objects greatly affects the extraction of identity features in facial recognition, which is a challenge that existing methods fail to effectively address. To tackl...
详细信息
Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model ***,dishonest clouds may infer user data,resulting in user data *** schemes have achie...
详细信息
Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model ***,dishonest clouds may infer user data,resulting in user data *** schemes have achieved secure outsourced computing,but they suffer from low computational accuracy,difficult-to-handle heterogeneous distribution of data from multiple sources,and high computational cost,which result in extremely poor user experience and expensive cloud computing *** address the above problems,we propose amulti-precision,multi-sourced,andmulti-key outsourcing neural network training ***,we design a multi-precision functional encryption computation based on Euclidean ***,we design the outsourcing model training algorithm based on a multi-precision functional encryption with multi-sourced ***,we conduct experiments on three *** results indicate that our framework achieves an accuracy improvement of 6%to 30%.Additionally,it offers a memory space optimization of 1.0×2^(24) times compared to the previous best approach.
暂无评论