A new optimizing parameter approach of LSSVM multiclass classification model

The parameter values of kernel function affect classification results to a certain extent. In the paper, a multiclass classification model based on improved least squares support vector machine (LSSVM) is presented. In the model, the non-sensitive loss function is replaced by quadratic loss function, and the inequality constraints are replaced by equality constraints. Consequently, quadratic programming problem is simplified as the problem of solving linear equation groups, and the SVM algorithm is realized by least squares method. When the LSSVM is used in multiclass classification, it is presented to choose parameter of kernel function on dynamic, which enhances preciseness rate of classification. The Fibonacci symmetry searching algorithm is simplified and improved. The changing rule of kernel function searching region and best shortening step is studied. The best multiclass classification results are obtained by means of synthesizing kernel function searching region and best shortening step. The simulation results show the validity of the model.     

Phoneme recognition using an adaptive supervised manifold learning algorithm

To effectively handle speech data lying on a nonlinear manifold embedded in a high-dimensional acoustic space, in this paper, an adaptive supervised manifold learning algorithm based on locally linear embedding (LLE) for nonlinear dimensionality reduction is proposed to extract the low-dimensional embedded data representations for phoneme recognition. The proposed method aims to make the interclass dissimilarity maximized, while the intraclass dissimilarity minimized in order to promote the discriminating power and generalization ability of the low-dimensional embedded data representations. The performance of the proposed method is compared with five well-known dimensionality reduction methods, i.e., principal component analysis, linear discriminant analysis, isometric mapping (Isomap), LLE as well as the original supervised LLE. Experimental results on three benchmarking speech databases, i.e., the Deterding database, the DARPA TIMIT database, and the ISOLET E-set database, demonstrate that the proposed method obtains promising performance on the phoneme recognition task, outperforming the other used methods.     

Hoeffding bound based evolutionary algorithm for symbolic regression

In symbolic regression area, it is difficult for evolutionary algorithms to construct a regression model when the number of sample points is very large. Much time will be spent in calculating the fitness of the individuals and in selecting the best individuals within the population. Hoeffding bound is a probability bound for sums of independent random variables. As a statistical result, it can be used to exactly decide how many samples are necessary for choosing i individuals from a population in evolutionary algorithms without calculating the fitness completely. This paper presents a Hoeffding bound based evolutionary algorithm (HEA) for regression or approximation problems when the number of the given learning samples is very large. In HEA, the original fitness function is used in every k generations to update the approximate fitness obtained by Hoeffding bound. The parameter 1?δ is the probability of correctly selecting i best individuals from population P, which can be tuned to avoid an unstable evolution process caused by a large discrepancy between the approximate model and the original fitness function. The major advantage of the proposed HEA algorithm is that it can guarantee that the solution discovered has performance matching what would be discovered with a traditional genetic programming (GP) selection operator with a determinate probability and the running time can be reduced largely. We examine the performance of the proposed algorithm with several regression problems and the results indicate that with the similar accuracy, the HEA algorithm can find the solution more efficiently than tradition EA. It is very useful for regression problems with large number of training samples.     

The effect of adding Ni and Ge microelements on the electromigration resistance of low-Ag based SnAgCu solder

Low-Ag-based Pb-free solder and its evaluation for electromigration (EM) reliability are research areas of active development. This paper studies the effect of adding Ni and Ge microelements on the EM behavior of low-Ag-based SnAgCu solder. Comparative measurements of the EM resistance of Sn1.0Ag0.5Cu (SAC) and Sn1.0Ag0.5Cu0.07Ni0.01Ge (SACNG) solders (in wt?%) were conducted. In these experiments, SACNG showed a higher EM resistance than SAC. It was concluded that adding Ni and Ge enhanced the EM resistance of low-Ag-based SnAgCu solders. This shows the same effect of Ni and Ge on the EM resistance as that which has been reported for Sn3.5Ag0.5Cu solder. An analysis of these observations suggests that grain boundary sliding plays a dominant role in stress relaxation and causes hillock growth. Based on this assumption, a possible mechanism was proposed to explain the effects of Ni and Ge on the EM resistance of SnAgCu solder.     

Rubber-assisted embossing of polymer thin films using molds with through-thickness microchannels

A flexible microfluidic chip is difficult to fabricate using the standard hot embossing technology. In this study, rubber-assisted embossing of polymer thin films using molds with through-thickness microchannels was investigated. The polymer film was thermoformed into the microchannels by rubber as a soft counter-tool. Different processing conditions, as well as material selections, affecting the thickness uniformity and replicated depth were examined. Results indicated that smoother surfaces on the embossed articles were created, and the thickness uniformity and the depth of the embossed channel were significantly affected by the embossing temperature, the embossing pressure, and the rubber hardness. The embossed film was sealed on one side with a layer of transparent adhesive film to form closed microchannels, and desired 3-D flow characteristics were obtained with this flexible microfluidic chip.     

Fabrication of PZT nano dot array and their ferroelectric properties

This paper demonstrates a promising and low-cost method for fabricating PZT nano-dot array by using sol–gel template method combined with laser interference lithography. ZrO₂ template with the pitch of 1?μm is firstly fabricated by sol–gel method and laser interference with a 325?nm He-Cd laser. Afterwards, PZT nano dot array with diameter of 500?nm and thickness of 20?nm is prepared on the ZrO₂ template. Atomic force microscope results show that the PZT nano dot array is uniform and highly ordered. Ferroelectric properties of PZT nano dot array are in situ measured through online-operation of TF analyzer and AFM. A ferroelectric hysteresis loop is obtained for the PZT nano dot.     

碳酸钙沉淀势理论计算模型及其应用

水质化学稳定性评价指数较多,其中碳酸钙沉淀势(CCPP)是一个能定量分析CaCO3溶解或沉淀的精确指数.从理论上推导了CCPP计算模型,并基于Matlab计算求解.模型计算结果与已有相关软件的计算结果相比,该理论模型的计算值更接近试验结果,可以用其代替试验值进行水质化学稳定性分析.     

绍兴滨海新城分质供水运行实践经验

根据绍兴市水资源现状与绍兴滨海新城开发实际情况,在分析绍兴滨海新城分质供水的必要性和可行性基础上,介绍了滨海新城分质供水的模式、范围,以及为提高供水安全性,在分质供水的两路供水管适当位置设置连通管等具体实施办法.总结了滨海新城分质供水实践中存在的水质、水量、水压等方面的问题,指出了分质供水运行管理制度、操作规程和紧急事故应对措施以及国家关于工业水质方面规范制度的不足.     

Performance of Sewage Sludge Treatment and Electricity Generation by Different Configuration Microbial Fuel Cells

This paper compared the degradation efficiency of sludge organic matters and electric-production by two typical microbial fuel cells——dual-chamber microbial fuel cell(DMFC)and single chamber air cathode microbial fuel cell(SAMFC),and the variations of sludge protein,polysaccharide and ammonia nitrogen within the systems were also investigated.The results showed that the concentration of sludge soluble chemical oxygen demand,protein and carbohydrate of DMFC are higher than these of SAMFC during the systems operation,while DMFC can achieve a better ammonia nitrogen removal than SAMFC.Under the same operation condition,the stable voltage output of DMFC and SAMFC is 0.61 V and 0.37 V;the maximum power density of DMFC and SAMFC is 2.79 W/m3and 1.25 W/m3;TCOD removal efficiency of DMFC and SAMFC is 34.14%and 28.63%for 12 d,respectively.Meanwhile,DMFC has a higher coulomb efficiency than SAMFC,but both are less than5%.The results showed that DMFC present a better performance on sludge degradation and electric-production.     

浅谈多媒体教室设备管理与维护

随着多媒体技术在高校的普及,多媒体教室需求也急剧上升,由此多媒体教室设备的安全问题、多媒体教室的设备操作问题、多媒体教室的管理模式问题、多媒体设备故障处理问题等也应运而生。本文就多媒体教室设备的管理和维护中存在的问题展开分析并提出解决问题的方法。