面向高速工业无线网络的TDMA MAC协议设计与实现

随着无线技术的发展,在工业自动化中引入无线技术已经成为一种潮流,同时TDMA机制由于可以完全避免冲突,因此在大规模高实时要求的面向车间的无线技术研究中受到了广泛关注,但现在面向车间的高速实时无线技术的研究大都局限于软件仿真。通过在商用802.11硬件上设计并实现面向车间级工业应用的高速工业无线TDMAMAC层协议,建立了一个基于TDMA的面向工业应用的高速无线网络原型系统,实验结果表明实验平台完全能够支撑毫秒级时隙调度的TDMA应用。     

VB教学方法浅析

程序设计是计算机专业课程中的重要内容之一。在程序设计课程教学中,如何解决程序设计本身枯燥、难懂这个问题,找到一条比较新颖的教学方式,一直是广大计算机教师颇感兴趣的课题。结合几年来VB程序设计的实际经验,并进行深刻的反思,总结出一个四步教学法。     

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.     

An Artificial Neural Network Classifier Design Based-on Variable Kernel and Non-Parametric Density Estimation

This paper proposes a probabilistic variant of the SOM-kMER (Self Organising Map-kernel-based Maximum Entropy learning Rule) model for data classification. The classifier, known as pSOM-kMER (probabilistic SOM-kMER), is able to operate in a probabilistic environment and to implement the principles of statistical decision theory in undertaking classification problems. A distinctive feature of pSOM-kMER is its ability in revealing the underlying structure of data. In addition, the Receptive Field (RF) regions generated can be used for variable kernel and non-parametric density estimation. Empirical evaluation using benchmark datasets shows that pSOM-kMER is able to achieve good performance as compared with those from a number of machine learning systems. The applicability of the proposed model as a useful data classifier is also demonstrated with a real-world medical data classification problem.     

Studying the protein-protein interactions in the postsynaptic density by means of immunoabsorption and chemical crosslinking

Postsynaptic densities (PSDs), isolated from porcine cerebral cortices, are large disk-shaped aggregates consisting of hundreds of different proteins. To study the protein-protein interactions in such complex supramolecules, we developed a procedure to break up the PSD's overall structure, while preserving some interactions between individual proteins. Using the resulting PSD sample and an indirect immunoabsorption procedure, PSD-95 was isolated along with the α- and β-subunits of calcium calmodulin-dependent protein kinase II (CaMKIIα and CaMKIIβ), α-tubulin, β-tubulin, and Chapsyn110. Similarly, CaMKIIα was isolated along with CaMKIIβ, α-tubulin, β-tubulin, and small amounts of PSD-95. The proteins isolated from PSDs treated with a cleavable bifunctional crosslinking reagent were further subjected to diagonal gel electrophoresis analysis, and the results indicated that CaMKIIα resides next to α-tubulin in the PSD. Overall, the results obtained here suggest that within the PSD, large aggregates of CaMKIIα, CaMKIIβ, α-tubulin, and β-tubulin may occur that indirectly associate with PSD-95 and Chapsyn110. Such a protein organization would allow interactions with F-actin in the cytoplasm and with proteins, such as N-methyl-D-aspartate receptors, which reside on the postsynaptic membrane. Furthermore, it would facilitate binding to proteins such as the various microtubule-associated proteins that reside in the core region of the PSD.     

Toxicoproteomics and its application to human health risk assessment

Toxicoproteomics is the use of proteomic technologies to better understand environmental and genetic factors, toxic mechanisms, and modes of action in response to acute exposure to toxicants and in the long-term development of diseases caused or influenced by these exposures. Use of toxicoproteomic technologies to identify key biochemical pathways, mechanisms, and biomarkers of exposure and toxicity will decrease the uncertainties that are associated with human health risk assessments. This review provides an overview of toxicoproteomics from human health risk assessment perspectives. Key toxicoproteomic technologies such as 2-D gel-based proteomic methods and toxicoproteomic approaches are described, and examples of applications of these technologies and methodologies in the risk assessment context are presented. The discussion includes a focus on challenges and future directions.     

单苯环氯取代指数法预测二噁类化合物PCDDs的正辛醇/水分配系数

采用单苯环氯取代指数作为氯代二苯并二口恶口英类化合物 (PCDDs)的分子结构描述符 ,通过正向逐步线性回归方法建立了PCDDs的logKow与分子结构描述符之间的定量关系模型。与文献报道的MOD模型相比 ,该模型不仅具有显著的相关性 (n =43,Radj=0 898,SE =0 195 ,在α =0 0 5时 ,F =2 0 45 5 ,p =0 0 0 0 0 ) ,而且对于分子结构具有更好的区分能力。利用建立的模型 ,对没有logKow文献值的其他 33种PCDDs化合物给出了预测值     

Pseudoelastic behavior in Y1−xPrxBa2Cu3Oy compounds

Tensile tests show that ferroelastic loops always occur at 100–150 K, 200–250 K and room temperature in the Y_1–xPr_xBa₂Cu₃O_y samples withx=0 and 0.1 for whichT _c is 92 K and 82.5 K respectively, and the shape memory effect is always observed in the compact sample near 130 K, just similar to that of thermal elastic martensitic alloys. The loss fraction (W/W) which is proportional to the area of ferroelastic loop as a function of temperature shows that there always exist static hysteresis (W/W) peaks at 130 K and 110 K which are attributed to the phaselike transition (PLT) characterized by the jump of lattice parameters. No ferroelastic loops and shape memory effect are observed in the range of 100 K to 150 K for the lowerT _c samples withx=0.3, 0.4 and 0.6.     

Interfacing industrial R&A equipment using Matlab

We present a toolbox that enables access to real robotics and automation (R&A) equipment from the MATLAB shell. If used in conjunction with a robotics toolbox, it will extend significantly their application, i.e., besides robotic simulation and data analysis, the user can interact online with the equipment he or she is using. This article briefly presents the software architecture adopted and how it was used to generate the MATLAB MEX files presented. It then exemplifies application to two types of equipment, complemented with a generic manipulation example using a robotic gripper. The utilization of this tool with force control experiments is also briefly explored