HAR-sEMG: A Dataset for Human Activity Recognition on Lower-Limb sEMG

Knowledge and Information Systems - In the past decade, human activity recognition (HAR) has grown in popularity due to its applications in security and entertainment. As recent years have...     

Feasibility of the indirect determination of blast-induced rock movement based on three new hybrid intelligent models

Engineering with Computers - The indirect and accurate determination of blast-induced rock movement has important significance in the reduction of ore loss and dilution and in the protection of...     

Two-Stage Method for Grouping News with Similar Topics

Programming and Computer Software - This paper is devoted to event detection as part of news stream analysis. An event is regarded as a group of news texts dedicated to one real-world fact or...     

Construction and verification of retinal vessel segmentation algorithm for color fundus image under BP neural network model

To improve the accuracy of retinal vessel segmentation, a retinal vessel segmentation algorithm for color fundus images based on back-propagation (BP) neural network is proposed according to the characteristics of retinal blood vessels. Four kinds of green channel image enhancement results of adaptive histogram equalization, morphological processing, Gaussian matched filtering, and Hessian matrix filtering are used to form feature vectors. The BP neural network is input to segment blood vessels. Experiments on the color fundus image libraries DRIVE and STARE show that this algorithm can obtain complete retinal blood vessel segmentation as well as connected vessel stems and terminals. When segmenting most small blood vessels, the average accuracy on the DRIVE library reaches 0.9477, and the average accuracy on the STARE library reaches 0.9498, which has a good segmentation effect. Through verification, the algorithm is feasible and effective for blood vessel segmentation of color fundus images and can detect more capillaries.

     

Compiler-directed scratchpad memory data transfer optimization for multithreaded applications on a heterogeneous many-core architecture

The Journal of Supercomputing - The heterogeneous many-core architecture plays an important role in the fields of high-performance computing and scientific computing. It uses accelerator cores with...     

A frequency-aware and energy-saving strategy based on DVFS for Spark

The Journal of Supercomputing - With the fast growth of big data applications, it has brought about a huge increase in the energy consumption for big data processing in Cloud data centers. In this...     

SESF-Fuse: an unsupervised deep model for multi-focus image fusion

Neural Computing and Applications - Muti-focus image fusion is the extraction of focused regions from different images to create one all-in-focus fused image. The key point is that only objects...     

EEG extended source imaging with structured sparsity and $$L_1$$ -norm residual

Neural Computing and Applications - It is a long-standing challenge to reconstruct the locations and extents of cortical neural activities from electroencephalogram (EEG) recordings, especially...     

Research on the Effects of Institutional Liquidation Strategies on the Market Based on Multi-agent Model

Based on the multi-agent model, an artificial stock market with four types of traders is constructed. On this basis, this paper focuses on comparing the effects of liquidation behavior on market liquidity, volatility, price discovery efficiency and long memory of absolute returns when the institutional trader adopts equal-order strategy, Volume Weighted Average Price (VWAP) strategy and Implementation Shortfall (IS) strategy respectively. The results show the following: (1) the artificial stock market based on multi-agent model can reproduce the stylized facts of real stock market well; (2) among these three algorithmic trading strategies, IS strategy causes the longest liquidation time and the lowest liquidation cost; (3) the liquidation behavior of institutional trader will significantly reduce market liquidity, price discovery efficiency and long memory of absolute returns, and increase market volatility; (4) in comparison, IS strategy has the least impact on market liquidity, volatility and price discovery efficiency, while VWAP strategy has the least impact on long memory of absolute returns.

     

基于USB总线的新型多路自整角信号发生器设计

目前,常用的自整角信号发生器大都采用像AD2S100这样的专用器件进行信号转换;这类器件往往都是国外制造,价格不菲,然而信号转换精度却只有0.2°～0.5°,对于某些高精度应用难以满足要求;为此,以C8051F340单片机为核心设计了一种基于USB总线的多路自整角信号发生器;设计摒弃了对专用芯片的需求,采用软件模拟方式进行信号解算和误差补偿,大大降低生产成本的同时,使信号全范围误差小于0.2°。经应用证明该信号发生器工作稳定、抗干扰强,有很高的实用价值。