RETRACTED ARTICLE: Design of traffic object recognition system based on machine learning

Neural Computing and Applications - In recent years, researchers have proposed many methods to solve the problem of obstacle detection. However, computer vision-based vehicle detection and...     

RETRACTED ARTICLE: Research on image classification method based on convolutional neural network

Neural Computing and Applications - Image classification method is currently the more popular image technology, but it still has certain problems in practice. In order to improve the image...     

Optimizing nonlinearity of piezoresistive pressure sensors by an asymmetric Wheatstone bridge

Microsystem Technologies - Since nonlinearity is critical to silicon piezoresistive pressure sensors, this paper combined theoretical analysis and simulation to study the effect of changing the...     

Toward practical adoption of i* framework: an automatic two-level layout approach

Requirements Engineering - Bridging the gap between academia and industry is an important issue to promote the practicality of i* framework. Researchers have been dealing with this issue from...     

Neural network’s selection of color in UI design of social software

Neural Computing and Applications - In recent years, the design of social software UI has become a design research focus in the field of design. Color affects many factors in UI design. However,...     

DM-CTSA: a discriminative multi-focused and complementary temporal/spatial attention framework for action recognition

Neural Computing and Applications - Video-based human action recognition remains a challenging task. There are three main limitations: (1) Most works are only restricted to single temporal scale...     

Insight into an unsupervised two-step sparse transfer learning algorithm for speech diagnosis of Parkinson’s disease

Neural Computing and Applications - Speech diagnosis of Parkinson’s disease (PD) as a non-invasive and simple diagnosis method is particularly worth exploring. However, the number of samples...     

Texture compensation with multi-scale dilated residual blocks for image denoising

Neural Computing and Applications - Deep convolutional neural networks have achieved great success for image denoising recently. However, increasing the depth of the neural network cannot...     

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.

     

Pricing Exotic Option Under Jump-Diffusion Models by the Quadrature Method

This paper extends the quadrature method to price exotic options under jump-diffusion models. We compute the transition density of jump-extended models using convolution integrals. Furthermore, a simpler and more efficient lattice grid is introduced to implement the recursion more directly in matrix form. It can be shown that a lot of running time can be saved. At last, we apply the developed approach to the different jump-extended models to demonstrate its universality and provide a detailed comparison for the discrete path-dependent options to demonstrate its advantages in terms of speed and accuracy.