Benchmarking Least Squares Support Vector Machine Classifiers

In Support Vector Machines (SVMs), the solution of the classification problem is characterized by a (convex) quadratic programming (QP) problem. In a modified version of SVMs, called Least Squares SVM classifiers (LS-SVMs), a least squares cost function is proposed so as to obtain a linear set of equations in the dual space. While the SVM classifier has a large margin interpretation, the LS-SVM formulation is related in this paper to a ridge regression approach for classification with binary targets and to Fisher's linear discriminant analysis in the feature space. Multiclass categorization problems are represented by a set of binary classifiers using different output coding schemes. While regularization is used to control the effective number of parameters of the LS-SVM classifier, the sparseness property of SVMs is lost due to the choice of the 2-norm. Sparseness can be imposed in a second stage by gradually pruning the support value spectrum and optimizing the hyperparameters during the sparse approximation procedure. In this paper, twenty public domain benchmark datasets are used to evaluate the test set performance of LS-SVM classifiers with linear, polynomial and radial basis function (RBF) kernels. Both the SVM and LS-SVM classifier with RBF kernel in combination with standard cross-validation procedures for hyperparameter selection achieve comparable test set performances. These SVM and LS-SVM performances are consistently very good when compared to a variety of methods described in the literature including decision tree based algorithms, statistical algorithms and instance based learning methods. We show on ten UCI datasets that the LS-SVM sparse approximation procedure can be successfully applied.     

The Relationship Between Inhibition of Return and Saccade Trajectory Deviations.

After presentation of a peripheral cue, a subsequent saccade to the cued location is delayed (inhibition of return: IOR). Furthermore, saccades typically deviate away from the cued location. The present study examined the relationship between these inhibitory effects. IOR and saccade trajectory deviations were found after central (endogenous) and peripheral (exogenous) cuing of attention, and both effects were larger with an onset cue than with a color singleton cue. However, a dissociation in time course was found between IOR and saccade trajectory deviations. Saccade trajectory deviations occurred at short delays between the cue and the saccade, but IOR was found at longer delays. A model is proposed in which IOR is caused by inhibition applied to a preoculomotor attentional map, whereas saccade trajectory deviations are caused by inhibition applied to the saccade map, in which the final stage of oculomotor programming takes place. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A functional correspondence between call-by-need evaluators and lazy abstract machines

We bridge the gap between compositional evaluators and abstract machines for the lambda-calculus, using closure conversion, transformation into continuation-passing style, and defunctionalization of continuations. This article is a followup of our article at PPDP 2003, where we consider call by name and call by value. Here, however, we consider call by need.We derive a lazy abstract machine from an ordinary call-by-need evaluator that threads a heap of updatable cells. In this resulting abstract machine, the continuation fragment for updating a heap cell naturally appears as an ‘update marker’, an implementation technique that was invented for the Three Instruction Machine and subsequently used to construct lazy variants of Krivine's abstract machine. Tuning the evaluator leads to other implementation techniques such as unboxed values. The correctness of the resulting abstract machines is a corollary of the correctness of the original evaluators and of the program transformations used in the derivation.     

钢试样中Na、K类杂质元素来源的新发现

对钢试样制备过程和加工钢试样时机床所用切割液的组成进行了分析,切割液中的Na含量接近15％,K含量接近9％。对同一断口试样的能谱分析结果表明,无切割液残留物时断口处未见Na、K类杂质元素,有切割液残留物时断口处发现了含Na、K类杂质元素,而且其它成分也与切割液的成分相近。确定机床所用切割液是钢试样中的Na、K类杂质元素的来源之一。建议在分析钢试样时,应做断口能谱分析,排除留在钢试样上的机床切割液残留物对分析结果的影响。     

Generalized ordering-search for learning directed probabilistic logical models

Recently, there has been an increasing interest in directed probabilistic logical models and a variety of formalisms for describing such models has been proposed. Although many authors provide high-level arguments to show that in principle models in their formalism can be learned from data, most of the proposed learning algorithms have not yet been studied in detail. We introduce an algorithm, generalized ordering-search, to learn both structure and conditional probability distributions (CPDs) of directed probabilistic logical models. The algorithm is based on the ordering-search algorithm for Bayesian networks. We use relational probability trees as a representation for the CPDs. We present experiments on a genetics domain, blocks world domains and the Cora dataset. Editors: Stephen Muggleton, Ramon Otero, Simon Colton.     

Effect of the post-deposition annealing on electrical characteristics of MIS structures with HfO2/SiO2 gate dielectric stacks

In this work, we report on effects of post-deposition annealing on electrical characteristics of metal–insulator–semiconductor (MIS) structures with HfO₂/SiO₂ double gate dielectric stacks. Obtained results have shown the deterioration of electro-physical properties of MIS structures, e.g. higher interface traps density in the middle of silicon forbidden band (D_itmb), as well as non-uniform distribution and decrease of breakdown voltage (U_br) values, after annealing above 400 °C. Two potential hypothesis of such behavior were proposed: the formation of interfacial layer between hafnia and silicon dioxide and the increase of crystallinity of HfO₂ due to the high temperature treatment. Furthermore, the analysis of conduction mechanisms in investigated stacks revealed Poole–Frenkel (P–F) tunneling at broad range of electric field intensity.     

Lower-error and area-efficient antilogarithmic converters with bit-correction schemes

In this article, we have proposed fast lower-error and area-efficient antilogarithmic converters. By employing new approximation schemes with two-region shift-and-add operations, our proposed converters can perform high-speed conversions from logarithmic numbers to binary numbers. Synthesis results show that our proposed converters can achieve time savings of over 32.5% and can save 42.3% of the area used compared with previously proposed methods. In addition, the percent error ranges for various logarithmic number system (LNS)-based operations used by our proposed logarithmic processor are lower than those of previous methods. Our proposed converters can be applied to LNS-based processors to ease the tremendous computation overhead and boost the performance.     

Morphology,thermal and mechanical properties of PVC/MMT nanocomposites prepared by solution blending and solution blending + melt compounding

Two types of montmorillonite (MMT), natural sodium montmorillonite (Na-MMT) and organically modified montmorillonite (OMMT), in different amounts of 1, 2, 5, 10 and 25 phr (parts per hundred resin), were dispersed in rigid poly (vinyl chloride) by two different methods: solution blending and solution blending + melt compounding. The effects on morphology, thermal and mechanical properties of the PVC/MMT nanocomposites were studied by varying the amount of Na-MMT and OMMT in both methods. SEM and XRD analysis revealed that possible intercalated and exfoliated structures were obtained in all of the PVC/MMT nanocomposites. Thermogravimetric analysis revealed that PVC/Na-MMT nanocomposites have better thermal stability than PVC/OMMT nanocomposites and PVC. In general, PVC/MMT nanocomposites prepared by solution blending + melt compounding revealed improved thermal properties compared to PVC/MMT nanocomposites prepared by solution blending. Vicat tests revealed a significant decrease in Vicat softening temperature of PVC/MMT nanocomposites prepared by solution blending + melt compounding compared to unfilled PVC.