金刚烷最新研究

金刚烷是近 30年来发展起来的一种新型精细化工原料。简要介绍了金刚烷的分子结构、性质及其主要用途 ,重点对近年来国内外报道过的金刚烷合成方法进行了评述 ,在此基础上指出了金刚烷化工的未来发展趋势。     

D.c. conduction studies on thermally evaporated neodymium oxide thin films

Aluminium-neodymium oxide-aluminium thin film capacitors have been prepared by thermal evaporation and the d.c. conduction properties of these films have been studied. The thicknesses of the films have been determined by a multiple beam interferometer. The current-voltage power-law dependence showed that the conduction in these films is space-charge limited. The linear dependence of the current density on the square root of the applied field confirmed the exponential trap distribution. The trap density has been found to be of the order of 10²⁶ m^–3. It has also been observed that the Schottky type of conduction is predominant in the high-field region and the height of the Schottky barrier has been determined. It is seen that the conduction mechanism is an activated process with the activation energy decreasing with increasing field.     

Modal Kalman filtering based impedance relaying

An algorithm is presented for computer distance relaying. It is based on modal Kalman filtering (MKF) to estimate fundamental phasors, MKF exploits all the measurement information available from a three-phase line and is founded on enhanced models of the electromagnetic transients noise. To support the modeling of noise for different faults, a study of nontrivial electrical networks with accurate electromagnetic transients modeling is made for 400 kV transmission lines. MKF fits the behavior of the different modal noise for the Clarke phasors, but it is invariant for each type of fault, assuring robustness and minimum error variance. To computer distance, Clarke αB phasors are transformed to +/- symmetrical components, and then a well-known expression is used to computer the positive impedance. Statistical analysis if presented to assess observation time versus estimation accuracy for the different types of line faults     

A study of mixtures of poly(ethylene oxide) with polystyrene or poly(styrene-co-acrylic acid) by inverse gas chromatography and viscosimetry

Summary Systems of poly(ethylene oxide)/polystyrene and of poly(ethylene oxide)/poly(styrene-co-acrylic acid) of different ratios were studied by inverse gas chromatography using benzene and n-decane as molecule probes and by viscosimetry in tetrahydrofuran. The transition temperatures as shown in the retention diagrams and the interaction parameters as determined by inverse gas chromatography and by viscosimetry showed that whereas poly(ethylene oxide) is incompatible with polystyrene, the introduction of amounts of acrylic acid groups into polystyrene chains by free radical copolymerization led to compatible systems of the acidic copolymer with the poly(ethylene oxide).     

Network regression with predictive clustering trees

Network data describe entities represented by nodes, which may be connected with (related to) each other by edges. Many network datasets are characterized by a form of autocorrelation, where the value of a variable at a given node depends on the values of variables at the nodes it is connected with. This phenomenon is a direct violation of the assumption that data are independently and identically distributed. At the same time, it offers an unique opportunity to improve the performance of predictive models on network data, as inferences about one entity can be used to improve inferences about related entities. Regression inference in network data is a challenging task. While many approaches for network classification exist, there are very few approaches for network regression. In this paper, we propose a data mining algorithm, called NCLUS, that explicitly considers autocorrelation when building regression models from network data. The algorithm is based on the concept of predictive clustering trees (PCTs) that can be used for clustering, prediction and multi-target prediction, including multi-target regression and multi-target classification. We evaluate our approach on several real world problems of network regression, coming from the areas of social and spatial networks. Empirical results show that our algorithm performs better than PCTs learned by completely disregarding network information, as well as PCTs that are tailored for spatial data, but do not take autocorrelation into account, and a variety of other existing approaches.     

基于改进粒子群优化算法的BP神经网络在大坝变形分析中的应用

BP神经网络以其对非线性系统的强大映射能力而被广泛应用于模糊性、随机性强的大坝变形预测分析中。传统的BP神经网络由于初始权值和阈值的随机性,容易导致网络在训练过程中极易陷入局部最小值,同时存在网络收敛速度慢等缺点。针对传统算法的不足,采用改进的粒子群算法(IPSO)对BP网络的初始权值和阈值给予优化,建立大坝变形预测的IPSO-BP模型,并与PSO-BP网络模型进行对比。结果表明,改进的IPSO-BP模型具有收敛速度更快、预测精度更高的优点。该方法可供大坝安全监测和预警分析参考。     

山区高速公路单向纵坡箱梁桥梁体纵向滑移分析

随着我国经济的增长,越来越多的高速公路相继建成通车。特别是一些山区高速公路,由于受到地势条件的限制,多呈纵坡大、展线复杂、区域小气候影响大。近年来,我国山区高速公路互通桥梁相继出现梁体滑移导致伸缩缝挤死,造成桥面出现隆起现象,严重影响行车安全。通过对某高速公路某座互通主线桥伸缩缝挤死导致桥面隆起的现象进行了深入调查,结合施工质量、设计理念对病害产生的原因进行了分析研究,并对病害提出了针对性的维修处治建议。为山区高速公路互通立交桥梁的设计、施工、养护工作有一定的指导意义。     

Silicon neuron: digital hardware implementation of the quartic model

This paper presents an FPGA implementation of the quartic neuron model. This approach uses digital computation to emulate individual neuron behavior. We implemented the neuron model using fixed-point arithmetic operation. The neuron model’s computations are performed in arithmetic pipelines. It was designed in VHDL language and simulated prior to mapping in the FPGA. We show that the proposed FPGA implementation of the quartic neuron model can emulate the electrophysiological activities in various types of cortical neurons and is capable of producing a variety of different behaviors, with diversity similar to that of neuronal cells. The neuron family of this digital neuron can be modified by appropriately adjusting the neuron model’s parameters.