An empirical performance comparison of some variations of thek-d Tree andBD tree

Database applications very often require a sophisticated class of storage structures in order to answer different types of queries efficiently. This often dictates that the file should be organized on multiple keys. Several storage structures have been proposed to satisfy these needs. Most of these are a generalization of the storage structures used for managing one-dimensional data. Thek-d tree is one such example and it is a natural generalization of the standard one-dimensional binary search tree. Recently, a new storage structure, called theBD tree, was proposed to manage multidimensional data. This structure has good dynamic characteristics. Several variations are possible on the basick-d tree structure. This paper studies the performance implications of three variations. Further, it provides an empirical performance comparison of thek-d tree andBD tree in database applications.     

Observer design methodology for stochastic and deterministic robustness

A unified observer with stochastic and deterministic robustness is developed in this paper so that an observer is less sensitive to both stochastic and deterministic uncertainties. For stochastic robustness, the norm of the observer gain and the lower bound of the observer decay rate are shown to be design factors which can minimize the upper bound of the estimation error variance. For deterministic robustness, the L ₂ norm-based condition number of the observer eigenvector matrix is utilized to address robust estimation performance against deterministic uncertainties. In order to justify the proposed method, a graphical approach is first introduced, and then a multi-objective optimization problem including linear matrix inequality constraints is formulated to provide the unified robustness.     

Document-level sentiment classification: An empirical comparison between SVM and ANN

Document-level sentiment classification aims to automate the task of classifying a textual review, which is given on a single topic, as expressing a positive or negative sentiment. In general, supervised methods consist of two stages: (i) extraction/selection of informative features and (ii) classification of reviews by using learning models like Support Vector Machines (SVM) and Na?¨ve Bayes (NB). SVM have been extensively and successfully used as a sentiment learning approach while Artificial Neural Networks (ANN) have rarely been considered in comparative studies in the sentiment analysis literature. This paper presents an empirical comparison between SVM and ANN regarding document-level sentiment analysis. We discuss requirements, resulting models and contexts in which both approaches achieve better levels of classification accuracy. We adopt a standard evaluation context with popular supervised methods for feature selection and weighting in a traditional bag-of-words model. Except for some unbalanced data contexts, our experiments indicated that ANN produce superior or at least comparable results to SVM’s. Specially on the benchmark dataset of Movies reviews, ANN outperformed SVM by a statistically significant difference, even on the context of unbalanced data. Our results have also confirmed some potential limitations of both models, which have been rarely discussed in the sentiment classification literature, like the computational cost of SVM at the running time and ANN at the training time.     

基于K-means聚类点密度的WSNs加权质心定位算法

为降低无线传感器网络(WSNs)在节点众多时算法复杂度,提高定位精度,提出一种基于K-means聚类点密度的WSNs加权质心定位算法(KCPD-WCLA).首先,对空间中随机大量布设的锚节点进行分组,利用三边测量定位法在二维平面上得到许多接近真实值的结果;然后将K-means聚类算法引入到WSNs的定位问题中,对K个聚类点密度加以考虑,利用加权质心定位算法(WCLA)得到定位结果.理论分析与仿真结果表明:计算复杂度明显降低,定位精度比多边定位算法(MLA)和WCLA有显著提高.     

DK-means: a deterministic K-means clustering algorithm for gene expression analysis

Pattern Analysis and Applications - Clustering has been widely applied in interpreting the underlying patterns in microarray gene expression profiles, and many clustering algorithms have been...     

Low sensitivity feedback gains for deterministic and stochastic control systems

The problem of obtaining output feedback gains to minimize a quadratic performance criterion which includes sensitivity variables is discussed. The equivalent stochastic problems are also studied and when a Kalman filter is allowed, the minimum variance estimate of the state is employed to implement the control. A set of non-linear matrix equations are obtained which constitute the necessary conditions that must be satisfied for an optimal solution. For the deterministic case it is shown that when no sensitivity is considered and the matrix which relates output and input is invertible, the usual Riccati formulation is obtained. The problem is also reformulated using a compensator and it is shown that it can be cast into an instantaneous feedback form.     

An empirical comparison of backtracking algorithms

In this paper we report the results of experimental studies of zero-level, one-level, and two-level search rearrangement backtracking. We establish upper and lower limits for the size problem for which one-level backtracking is preferred over zero-level and two-level methods, thereby showing that the zero-level method is best for very small problems. The one-level method is best for moderate size problems, and the two-level method is best for extremely large problems. Together with our theoretical asymptotic formulas, these measurements provide a useful guide for selecting the best search rearrangement method for a particular problem.     

Boundary stabilisation to non-stationary solutions for deterministic and stochastic parabolic-type equations

In this work, we design explicit, finite-dimensional boundary feedback laws for stabilisation to trajectories for parabolic-type equations. The simple form of the feedback allows to write the solution of the corresponding closed-loop equation in a mild formulation via a kernel; then, taking advantage of this, the stability is shown. As an application, null stabilisation for stochastic parabolic-type equations is deduced as well. As far as we know, the present work is the first result on boundary feedback stabilisation to trajectories and for stochastic parabolic-type equations, with stability guaranteed independent of how large the level of the noise is.     

Mode-superposition correction method for deterministic and stochastic analysis of structural systems

The role played by the modal analysis in the framework of structural dynamics is fundamental from both deterministic and stochastic point of view. However the accuracy obtained by means of the classical modal analysis is not always satisfactory. Therefore it is clear the importance of methods able to correct the modal response in such a way to obtain the required accuracy. Many methods have been proposed in the last years but they are meaningful only when the forcing function is expressed by an analytical function. Moreover in stochastic analysis they fail for white noise excitation. In the paper a method able to give a very accurate response for both deterministic and stochastic input is presented. This method is based upon the use of Ritz vectors together with the classical modal analysis. Numerical applications for both deterministic and stochastic inputs show the great accuracy of the proposed method.     

Tracking performance optimizations for deterministic and stochastic references via moving-average precompensator

A technique for designing moving-average precompensators that give the minimization of a tracking performance cost function while tracking either deterministic or stochastic reference inputs is presented. For deterministic reference inputs, the cost function is an infinite-time horizon quadratic sum of the dynamically weighted tracking error and dynamically weighted control input. For stochastic reference inputs, the sum of the variances of the dynamically weighted tracking error and dynamically weighted control input is minimized. The two types of cost function are shown to be equivalent and the same design technique is used for both. The precompensator is intended to be designed for use in cascade with a control system which has already been designed, possibly without regard to tracking. The minimization of the cost function is enhanced by increasing the number of terms in the precompensator above the minimum necessary to keep the cost finite. A simulation example is presented showing how performance improvements over pole-placement and error transfer function zero-placement controllers may be achieved.     

Some stochastic Leontief-Ford models and their deterministic equivalents

Some stochastic Leontief-Ford models of ecological-economic interaction and their deterministic equivalents are proposed. A theory of stochastic variants of ecological-economic structural-type functions is developed. Appropriate algorithms are developed. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 3–10, May–June 2007.     

Distributed asynchronous deterministic and stochastic gradient optimization algorithms

We present a model for asynchronous distributed computation and then proceed to analyze the convergence of natural asynchronous distributed versions of a large class of deterministic and stochastic gradient-like algorithms. We show that such algorithms retain the desirable convergence properties of their centralized counterparts, provided that the time between consecutive interprocessor communications and the communication delays are not too large.     

Approximate transient analysis for subclasses of deterministic and stochastic Petri nets

Transient analysis of non-Markovian stochastic Petri nets is a theoretically interesting and practically important problem. In this paper, we first present a method to compute bounds and an approximation on the average state sojourn times for a subclass of deterministic and stochastic Petri nets (DSPNs) where there is a single persistent deterministic transition that can become enabled only in a special state. Then, we extend this class by allowing the transition to become enabled in any state, as long as the time between successive enablings of the deterministic transition is independent of this state, and develop a new approximate transient analysis approach. In addition to renewal theory, we only make use of discrete and continuous Markov chain concepts. As an application, we use the model of a finite-capacity queue with a server subject to breakdowns, and assess the quality of our approximations.     

An empirical comparison of seven programming languages

Often heated, debates regarding different programming languages' effectiveness remain inconclusive because of scarce data and a lack of direct comparisons. The author addresses that challenge, comparatively analyzing 80 implementations of the phone-code program in seven different languages (C, C++, Java, Perl, Python, Rexx and Tcl). Further, for each language, the author analyzes several separate implementations by different programmers. The comparison investigates several aspects of each language, including program length, programming effort, runtime efficiency, memory consumption, and reliability. The author uses comparisons to present insight into program language performance     

An empirical comparison of generators for self similar simulated traffic

It is generally recognised that aggregated network traffic is self similar and that self similar traffic models should be used in simulation experiments when assessing the performance of a network. Many generators have been proposed to synthetically produce self similar simulation input; however most of them require the trace length to be known a priori. Four generators that allow continuous generation of self similar time series are evaluated in this work with respect to their ability to reproduce the desired level of self similarity. This extensive investigation uses ten times as many traces and twice the number of parameter values as previously reported. Three of the tested generators perform well but surprisingly the generator supplied with a widely used commercial network simulator is unusable. The reported results indicate that the generator based on multiplexing strictly alternating ON/OFF sources may perform better than generators based on chaotic maps, provided that more than 100 ON/OFF sources can be used. Three estimators for the degree of self similarity of a time series have been evaluated as part of the process, and the only acceptable one is based on a Wavelet decomposition of the traffic trace.     

Optimal controller for uncertain stochastic polynomial systems with deterministic disturbances

This article presents the optimal quadratic-Gaussian controller for uncertain stochastic polynomial systems with unknown coefficients and matched deterministic disturbances over linear observations and a quadratic criterion. The optimal closed-form controller equations are obtained through the separation principle, whose applicability to the considered problem is substantiated. As intermediate results, this article gives closed-form solutions of the optimal regulator, controller and identifier problems for stochastic polynomial systems with linear control input and a quadratic criterion. The original problem for uncertain stochastic polynomial systems with matched deterministic disturbances is solved using the integral sliding mode algorithm. Performance of the obtained optimal controller is verified in the illustrative example against the conventional quadratic-Gaussian controller that is optimal for stochastic polynomial systems with known parameters and without deterministic disturbances. Simulation graphs demonstrating overall performance and computational accuracy of the designed optimal controller are included.     

An empirical comparison of software fault tolerance and faultelimination

The authors compared two major approaches to the improvement of software-software fault elimination and software fault tolerance-by examination of the fault detection (and tolerance, where applicable) of five techniques: run-time assertions, multiversion voting, functional testing augmented by structural testing, code reading by stepwise abstraction, and static data-flow analysis. The focus was on characterizing the sets of faults detected by the techniques and on characterizing the relationships between these sets of faults. Two categories of questions were investigated: (1) comparison between fault elimination and fault tolerance techniques and (2) comparisons among various testing techniques. The results provide information useful for making decisions about the allocation of project resources, show strengths and weaknesses of the techniques studies, and indicate directions for future research     

An empirical comparison of textual and graphical data structuredocumentation for Cobol programs

The author presents the results of an experimental investigation into the comparative usefulness of textual tools and graphical tools for the program understanding phase of Cobol program maintenance. Both novice and experienced programmers are used as subjects. The results show a slight superiority for graphical tools when they are used by less experienced programmers. They cast doubt on the importance of rigid adherence to program design methodologies for experienced programmers and on the extensibility of experiments using relatively inexperienced student subjects