Feature Selection using Fuzzy Support Vector Machines

The feature selection consists of obtaining a subset of these features to optimally realize the task without the irrelevant ones. Since it can provide faster and cost-effective learning machines and also improve the prediction performance of the predictors, it is a crucial step in machine learning. The feature selection methods using support machines have obtained satisfactory results, but the noises and outliers often reduce the performance. In this paper, we propose a feature selection approach using fuzzy support vector machines and compare it with the previous work, the results of experiments on the UCI data sets show that feature selection using fuzzy SVM obtains better results than using SVM.     

Electrochemical Immunoanalysis for Carcinoembryonic Antigen Based on Multilayer Architectures of Gold Nanoparticles and Polycation Biomimetic Interface on Glassy Carbon Electrode

This paper describes a layer‐by‐layer (LBL) self‐assembly process of chitosan (CTS) and gold nanoparticles (Au) on the pretreated negatively charged glassy carbon (GC) electrode to fabricate electrochemistry immunosensor with a nontoxic biomimetic interface, which provided an environment similar to a native system and allowed more freedom in orientation for immobilization of carcinoembryonic antibody (anti‐CEA) to monitor carcinoembryonic antigen (CEA). UV‐vis spectroscope, atomic force microscopy (AFM), and cyclic voltammetric (CV) measurements were used to follow the multilayer film formation. The performance of the biominetic interface and factors influencing the assay system were investigated in detail. The differential pulse voltammetry (DPV) current response is used for the CEA concentration assay. The dynamic range was from 0.50 to 80.00 ng mL^?1 with a detection limit of 0.27 ng mL^?1 at 3σ. In addition, the experiment results indicate that immobilization described in this proposed method exhibits a good sensitivity, selectivity, and stability.     

A simple solution of the van der Waerden permanent problem

The van der Waerden permanent problem was solved using mainly algebraic methods. A much simpler analytic proof is given using a new concept in optimization theory which may be of importance in the general theory of mathematical programming.     

On bulk-service MAP/PH L,N /1/N G-Queues with repeated attempts

We consider a retrial queue with a finite buffer of size N, with arrivals of ordinary units and of negative units (which cancel one ordinary unit), both assumed to be Markovian arrival processes. The service requirements are of phase type. In addition, a PH^L,N bulk service discipline is assumed. This means that the units are served in groups of size at least L, where 1≤ L≤ N. If at the completion of a service fewer than L units are present at the buffer, the server switches off and waits until the buffer length reaches the threshold L. Then it switches on and initiates service for such a group of units. On the contrary, if at the completion of a service L or more units are present at the buffer, all units enter service as a group. Units arriving when the buffer is full are not lost, but they join a group of unsatisfied units called “orbit”. Our interest is in the continuous-time Markov chain describing the state of the queue at arbitrary times, which constitutes a level dependent quasi-birth-and-death process. We start by analyzing a simplified version of our queueing model, which is amenable to numerical calculation and is based on spatially homogeneous quasi-birth-and-death processes. This leads to modified matrix-geometric formulas that reveal the basic qualitative properties of our algorithmic approach for computing performance measures. AMS Subject Classification: Primary 60K25 Secondary 68M20 90B22.     

相型同步启动时间的M／M／c排队系统

本文研究带有同步启动时间的Ｍ／Ｍ／ｃ系统，其中启动时间是相型变量，给出了稳态和等待时间分布等结果。     

Bayesian Object Identification: Variants

We present a Bayesian theory of object identification. Here, identifying an object means selecting a particular observation from a group of observations (variants), this observation (the regular variant) being characterized by a distributional model. In this sense, object identification means assigning a given model to one of several observations. Often, it is the statistical model of the regular variant, only, that is known. We study an estimator which relies essentially on this model and not on the characteristics of the “irregular” variants. In particular, we investigate under what conditions this variant selector is optimal. It turns out that there is a close relationship with exchangeability and Markovian reversibility. We finally apply our theory to the case of irregular variants generated from the regular variant by a Gaussian linear model.     

COMPLETE EXTREMAL SURFACES OF MIXED TYPE IN 3-DIMENSIONAL MINKOWSKI SPACE

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Hyperbolic spaces are of strictly negative type

We study finite metric spaces with elements picked from, and distances consistent with, ambient Riemannian manifolds. The concepts of negative type and strictly negative type are reviewed, and the conjecture that hyperbolic spaces are of strictly negative type is settled, in the affirmative. The technique of the proof is subsequently applied to show that every compact manifold of negative type must have trivial fundamental group, and to obtain a necessary criterion for product manifolds to be of negative type.

     

水电工程规划设计方案的自动生成及评价

本文介绍了在水电工程规划设计时，如何利用三次自然样条插值函数在有限个方案的基础上自动生成无限多个方案，然后采用多目标综合决策模型在其中选择最优方案的一种方法．文中还给出了程序流程，并以某水电站正常蓄水位选择作为实例，对方法进行了验证，结果与专家决策完全吻合．