A new dynamic Bayesian network approach for determining effective connectivity from fMRI data

Two techniques based on the Bayesian network (BN), Gaussian Bayesian network and discrete dynamic Bayesian network (DBN), have recently been used to determine the effective connectivity from functional magnetic resonance imaging (fMRI) data in an exploratory manner and to provide a new method for exploring the interactions among brain regions. However, Gaussian BN ignores the temporal relationships of interactions among brain regions, while discrete DBN loses a great deal of information by discretizing the data. To overcome these limitations, the current study proposes a new BN method based on Gaussian assumptions, termed Gaussian DBN, to capture the temporal characteristics of connectivity with less associated loss of information. A set of synthetic data were generated to measure the robustness of this method to noise, and the results were compared with discrete DBN. In addition, real fMRI data obtained from twelve normal subjects in the resting state was used to further demonstrate and validate the effectiveness of the Gaussian DBN method. The results demonstrated that the Gaussian DBN was more robust than discrete DBN and an improvement over BN.     

Backstepping control for output-constrained nonlinear systems based on nonlinear mapping

In this paper, nonlinear mapping (NM)-based backstepping control design is presented for a class of strict-feedback nonlinear systems with output constraint. By mapping output value set onto the set of all real numbers, the constrained system is transformed into a new strict-feedback unconstrained system to employ the traditional backstepping control while simultaneously preventing the constraint from being violated. It is proved that the original system has the similar convergence and bounded properties with the new one. Besides the nominal case where full knowledge of the plant is available, we also tackle scenarios wherein parametric uncertainties are present. Furthermore, the comparison with barrier Lyapunov function-based algorithm reveals the advantages of NM algorithm. The closed-loop system is guaranteed to be stable in the sense that all signals involved remain bounded, and the tracking error converges to zero asymptotically. Simulation studies illustrate the performance of the proposed control.     

Collaborative representation with reduced residual for face recognition

Collaboration representation-based classification (CRC) was proposed as an alternative approach to the sparse representation method with similar efficiency. The CRC is essentially a competition scheme for the training samples to compete with each other in representing the test sample, and the training class with the minimum representation residual from the test sample wins the competition in the classification. However, the representation error is usually calculated based on the Euclidean distance between a test sample and the weighted sum of all the same-class samples. This paper exploits alternative methods of calculating the representation error in the CRC methods to reduce the representation residual in a more optimal way, so that the sample classes compete with each other in a closer range to represent the test sample. A large number of face recognition experiments on three face image databases show that the CRC methods with optimized presentation residual achieve better performance than the original CRC, and the maximum improvement in classification accuracy is up to 12 %.     

Wavelet twin support vector machine

Twin support vector machine (TWSVM) is a research hot spot in the field of machine learning in recent years. Although its performance is better than traditional support vector machine (SVM), the kernel selection problem still affects the performance of TWSVM directly. Wavelet analysis has the characteristics of multivariate interpolation and sparse change, and it is suitable for the analysis of local signals and the detection of transient signals. The wavelet kernel function based on wavelet analysis can approximate any nonlinear functions. Based on the wavelet kernel features and the kernel function selection problem, wavelet twin support vector machine (WTWSVM) is proposed by this paper. It introduces the wavelet kernel function into TWSVM to make the combination of wavelet analysis techniques and TWSVM come true. The experimental results indicate that WTWSVM is feasible, and it improves the classification accuracy and generalization ability of TWSVM significantly.     

除草剂对不同栽培方式水稻药害的评价

选取酰胺类、磺酰脲类、硫代氨基甲酸酯类、杂环类、脲类、苯氧羧酸类等常用化学除草剂,以超常规剂量用移液和喷雾两种方式对抛栽和直播籼、粳稻进行药剂试验。研究结果明确了各种除草剂对水稻的药害症状;籼粳稻对各药剂的敏感差异;以及清水冲洗、搁田、施肥等措施对某些除草剂品种造成的水稻药害的缓解作用。     

乳胶漆的PVC和CPVC

介绍了乳胶漆的PVC及CPVC和涂膜性能的关系;讨论了乳液的粒径大小、成膜温度等因素对CPVC的影响。     

新时期景德镇陶瓷产业的保护与发展

景德镇陶瓷不仅历史悠久,而且品类众多,技艺精湛,文化内涵丰富。在手工业时代,它是生活的创造者;在当代,它成为历史文化的一种记忆和象征,以其独特形态自立于以现代设计为主体的科技文明之中,成为民族传统文化艺术的载体,发挥着从经济到艺术的多种功能。但是近些年来,在经济文化大发展的背景下,景德镇陶瓷产业却呈现总体不够景气、生产销售萎缩、工艺技术没有突破、后继无人等问题。我们应该清楚地认识到对于景德镇陶瓷产业的保护和发展的迫切性,以及改善现状、进行创新与应用的重要性,其保护与发展遭遇到了发展经济、技术更新和文化变迁等一系列矛盾,需要去探讨和研究。     

Na2S-SO2反应体系中H2S产生的过饱和态分析

向Na2S溶液中通入低浓度SO2气体以生成H2S，H2S从液相中逸出时，存在一突跃现象。本文根据这一现象，结合Y．T．Shah等提出的吸收－反应－解吸体系中过饱和态存在的条件，通过理论分析，得出在Na2S-SO2-H2S4反应体系中H2S解吸存在过饱和现象。     

Si加入量对Si_3N_4-SiC复合材料性能的影响

固定其他组分配比不变,仅改变配方中Si粉加入量即Si粉从10％增加到60％,经过准静态氮化法反应烧结制得Si3N4——SiC复合材料,并对其进行力学性能、XRD和SEM检测,实验结果显示:随着Si加入量的增加,复合材料的强度逐渐增大,而密度却呈现减小趋势,生成的Si3N4-中β-Si3N4含量增加,形成的网络结构的致密度也相应增大,但β-Si3N4晶粒减小。