Exploratory analysis of brain connectivity with ICA.

Covariance-based methods of exploration of functional connectivity of the brain from functional magnetic resonance imaging (fMRI) experiments, such as principal component analysis (PCA) and structural equation modeling (SEM), require a priori knowledge such as an anatomical model to infer functional connectivity. In this research, a hybrid method, combining independent component analysis (ICA) and SEM, which is capable of deriving functional connectivity in an exploratory manner without the need of a prior model is introduced. The spatial ICA (SICA) derives independent neural systems or sources involved in task-related brain activation, while an automated method based on the SEM finds the structure of the connectivity among the elements in independent neural systems. Unlike second-order approaches used in earlier studies, the task-related neural systems derived from the ICA provide brain connectivity in the complete statistical sense. The use and efficacy of this approach is illustrated on two fMRI datasets obtained from a visual task and a language reading task.     

炉壁集束碳氧枪在电炉中的应用

介绍了鄂钢电炉厂70t consteel 电炉使用炉壁集束碳氧枪后对经济指标的改善,以及在生产实践中的冶金效果.     

TRT入口方管道爆裂原因剖析

介绍了鞍钢7#高炉TRT装置入口方管道爆裂事故经过,进行了原因分析,并提出了解决措施。     

电致伸缩陶瓷微位移器非线性的数值方法补偿

本文通过对电致伸缩陶瓷材料的非线性进行分析。找到了补偿电致伸缩陶瓷非线性的数值方法，并对不同回程大小的电滞回线进行了分段处理，使补偿结果更为精确。     

Explicit robust schemes for implementation of a class of principal value-based constitutive models: Symbolic and numeric implementation

The issue of developing effective and robust schemes to implement a class of the Ogden-type hyperelastic constitutive models is addressed. To this end, special purpose functions (running under MACSYMA) are developed for the symbolic derivation, evaluation, and automatic FORTRAN code generation of explicit expressions for the corresponding stress function and material tangent stiffness tensors. These explicit forms are valid over the entire deformation range, since the singularities resulting from repeated principal-stretch values have been theorectically removed. The required computational algorithms are outlined, and the resulting FORTRAN computer code is presented.     

Integrated scheduling of flexible manufacturing systems employingautomated guided vehicles

Centralized and distributed automated guided vehicle system (AGVS) models for materials handling, and the model for part processing are integrated into a single coherent model. This formulation can be used to collectively schedule and control the entire flexible manufacturing system (FMS) as opposed to the traditional separate scheduling of part processing and material handling. The two AGVS models are based on Petri nets and can be directly used in the scheduling method that uses Petri nets for formulation and heuristic search for solution. This method employs a global search to seek the optimal operation of an entire FMS. Scheduling examples are presented and the method compares favorably with the results simulated using heuristic dispatch rules     

A neural network control system with parallel adaptive enhancementsapplicable to nonlinear servomechanisms

In this paper, we present a technique for using an additional parallel neural network to provide adaptive enhancements to a basic fixed neural network-based nonlinear control system. This proposed parallel adaptive neural network control system is applicable to nonlinear dynamical systems of the type commonly encountered in many practical position control servomechanisms. Properties of the controller are discussed, and it is shown that if Gaussian radial basis function networks are used for the additional parallel neural network, uniformly stable adaptation is assured and the approximation error converges to zero asymptotically. In the paper, the effectiveness of the proposed parallel adaptive neural network control system is demonstrated in real-time implementation experiments for position control in a servomechanism with asymmetrical loading and changes in the load     

Enhancement of oxide break-up by implantation of fluorine inpoly-Si emitter contacted p+-n shallow junctionformation

In this study, it is demonstrated that the incorporation of fluorine can enhance poly-Si/Si interfacial oxide break-up in the poly-Si emitter contacted p⁺-n shallow junction formation. The annealing temperature for breaking up the poly-Si/Si interfacial oxide has been found to be as low as 900°C. As a result, the junction depth of the BF₂-implanted device is much larger than that of the boron-implanted device