Multi-scale stacked sequential learning

Sequential learning is the discipline of machine learning that deals with dependent data such that neighboring labels exhibit some kind of relationship. The paper main contribution is two-fold: first, we generalize the stacked sequential learning, highlighting the key role of neighboring interactions modeling. Second, we propose an effective and efficient way of capturing and exploiting sequential correlations that takes into account long-range interactions. We tested the method on two tasks: text lines classification and image pixel classification. Results on these tasks clearly show that our approach outperforms the standard stacked sequential learning as well as state-of-the-art conditional random fields.     

Group interaction analysis in dynamic context.

Computer understanding of human actions and interactions is one of the key research issues in human computing. In this regard, context plays an essential role in semantic understanding of human behavioral and social signals from sensor data. This paper put forward an event-based dynamic context model to address the problems of context awareness in the analysis of group interaction scenarios. Event-driven multilevel dynamic Bayesian network is correspondingly proposed to detect multilevel events, which underlies the context awareness mechanism. Online analysis can be achieved, which is superior over previous works. Experiments in our smart meeting room demonstrate the effectiveness of our approach.     

The importance of different timings of excitatory and inhibitory pathways in neural field models

In this paper, we consider a neural field model comprised of two distinct populations of neurons, excitatory and inhibitory, for which both the velocities of action potential propagation and the time courses of synaptic processing are different. Using recently-developed techniques, we construct the Evans function characterising the stability of both stationary and travelling wave solutions, under the assumption that the firing rate function is the Heaviside step. We find that these differences in timing for the two populations can cause instabilities of these solutions, leading to, for example, stationary breathers. We also analyse "anti-pulses", a novel type of pattern for which all but a small interval of the domain (in moving coordinates) is active. These results extend previous work on neural fields with space-dependent delays, and demonstrate the importance of considering the effects of the different time-courses of excitatory and inhibitory neural activity.     

An improved correlation for the calculation of liquid thermal conductivity

Eighteen correlations appearing in the literature for the prediction of thermal conductivity, , of liquids are critically analyzed, and their reliability is checked using coherent input data and selected experimental values. The best results are obtained using the Reid, Sherwood, and Prausnitz correlation with a mean deviation of about 8% between predicted and experimental values. An improved correlation is proposed starting from the Viswanath equation, chosen because of its simplicity and convenience. The values of thermal conductivity obtained by this new correlation agree with the experimental values within 1%.     

基于不等时间间隔法的配电网重构

提出一种采用不等时间间隔法划分重构时间段的重构方法.将负荷曲线按变化幅度进行不等时间段划分,利用阈值限制开关动作次数,实现减小网损和操作费用的目的.通过仿真实验,证明该方法适用于工程实际的需要.     

青龙瀑布景区游客满意度实证研究

随着旅游业竞争的日趋激烈,旅游景点如何在竞争中脱颖而出,对顾客满意度影响因素分析和研究至关重要。文章以万州青龙大瀑布为例,通过对影响万州青龙大瀑布顾客满意度因素的问卷调查,将影响满意度的19个变量因素运用SPSS软件进行整理分析,运用因子分析法将19个变量归为四大公共因子,分别是旅游服务、旅游保障、景区宣传、景区管理四大类,并对其进行信度检测,随后构建了顾客满意度综合评价模型,最后对如何提高顾客满意度提出对策建议,以促进旅游景点服务质量的有效提高。     

Development of a Reconfigurable Platform for Manufacturing Equipment Control

In modern manufacturing equipment control area,controller is required to deliver higher computing capability for adopting advanced algorithms to meet speed and accuracy requirements,and reconfigurabilities for changing or(and)adding features or functions.This paper presents a methodology in design and implementation of a high performance and reconfigurable platform for manufacturing equipment control.This methodology is in virtue of system on a programmable chip(SoPC)technolo- gy but replacing the on-chip processor by an external high performance,floating-point digital signal processor(DSP).The appli- cation of the DSP is designed as a multi-threaded framework,which has more flexibilities than a traditional single-loop one.Fur- thermore,the field programmable gate array(FPGA)system can be reconfigured easily and quickly to meet a new requirement by dragging and dropping pre-built components in a SoPC building environment.As a result,the controller platform is more recon- figurable in terms of algorithms and functions.This platform is implemented in a 3-axis milling machine control and the result indicates that the design and implementation presented in this paper is feasible.     

基于语义激活的智能图形处理系统

全面分析了目前知识处理系统所存在的弊病,提出了下一代语义激活系统,探讨了新一代知识系统所应提供的服务;并将之运用于图形处理系统,阐明了图形数据从统一表示到有效存储、建模、再现和检索等一系列智能处理过程;进而提出了图形信息的语义表示和智能推理模型.     

Characterization of (Y,Gd) BxV1-xO4-x:Eu Phosphor Prepared by Coprecipitation Reaction

White body-color (Y, Gd)BxV1- xO4-x :Eu3 phosphors were prepared by coprecipitation reaction. Under VUV excitation at 147 nm, the red emission colorimetric purity of (Y, Gd)BxV1- xO4-x :Eu3 phosphor is much better than that of commercial PDP (plasma display panels) phosphor (Y, Gd)BO3:Eu3 . But its relative emission intensity is only about 90% of the commercial phosphor.