19172237
A verification method for solutions of nonsmooth equations
This paper proposes a verification method for the existence of solutions of nonsmooth equations. We generalize the Krawczyk operator to nonsmooth equations by using the mean-value theorem for nonsmooth functions. We establish a semi-local convergence theorem for the generalized Newton method for nonsmooth equations. The proposed method is a combination of the generalized Krawczyk operator and the semi-local convergence theorem.ZusammenfassungDieser Artikel schlägt eine Methode zur Verifizierung der Existenz von Lösungen nicht-differenzierbarer Gleichungen vor. Wir verallgemeinern den Krawczyk-Operator auf nicht-differenzierbare Gleichungen indem wir den Mittelwertsatz für nicht-differenzierbare Funktionen benutzen. Wir entwickeln einen semilokalen Konvergenzsatz für das verallgemeinerte Newton-Verfahren, angewendet auf nicht-differenzierbare Gleichungen. Die vorgeschlagene Methode ist eine Kombination aus dem verallgemeinerten Krawczyk-Operator und dem semi-lokalen Konvergenzsatz.
8507685
Global and superlinear convergence of the smoothing Newton method and its application to general box constrained variational inequalities
The smoothing Newton method for solving a system of nonsmooth equations F(x) = 0, which may arise from the nonlinear complementarity problem, the variational inequality problem or other problems, can be regarded as a variant of the smoothing method. At the kth step, the nonsmooth function F is approximated by a smooth function f(.,∈ κ ), and the derivative of f(.,∈ κ ) at x k is used as the Newton iterative matrix. The merits of smoothing methods and smoothing Newton methods are global convergence and convenience in handling. In this paper, we show that the smoothing Newton method is also superlinearly convergent if F is semismooth at the solution and f satisfies a Jacobian consistency property. We show that most common smooth functions, such as the Gabriel-More function, have this property. As an application, we show that for box constrained variational inequalities if the involved function is P- uniform, the iteration sequence generated by the smoothing Newton method will converge to the unique solution of the problem globally and superlinearly (quadratically).
33892015
A Multiple-Criteria Quadratic Programming Approach to Network Intrusion Detection
The early and reliable detection and deterrence of malicious attacks, both from external and internal sources are a crucial issue for today’s e-business. There are various methods available today for intrusion detection; however, every method has its limitations and new approaches should still be explored. The objectives of this study are twofold: one is to discuss the formulation of Multiple Criteria Quadratic Programming (MCQP) approach, and to investigate the applicability of the quadratic classification method to the intrusion detection problem. The demonstration of successful Multiple Criteria Quadratic Programming application in intrusion detection can add another option to network security toolbox. The classification results are examined by cross-validation and improved by an ensemble method. The results demonstrated that MCQP is excellent and stable. Furthermore, the outcome of MCQP can be improved by the ensemble method.
12374753
Efficient Method for Geometric Attribute Estimation
A new method is proposed to estimate the discrete geometric attributes, such as normal vector and curvature. The method contains two steps: points sampling and 4D Shepard interpolation. In the first step, we extract points from point cloud and estimate the attribute of the sampled points. During the second step, we interpolate a global 4D Shepard surface over these sampled points and compute the attribute of each point in point cloud. This method is very effective for using a new global surface model. It benefits many applications such as segmentation, feature extraction, data preprocessing and etc. Application examples are given to verify the proposed method.
12010325
An information-based sequence distance and its application to whole mitochondrial genome phylogeny
MOTIVATION
Traditional sequence distances require an alignment and therefore are not directly applicable to the problem of whole genome phylogeny where events such as rearrangements make full length alignments impossible. We present a sequence distance that works on unaligned sequences using the information theoretical concept of Kolmogorov complexity and a program to estimate this distance.


RESULTS
We establish the mathematical foundations of our distance and illustrate its use by constructing a phylogeny of the Eutherian orders using complete unaligned mitochondrial genomes. This phylogeny is consistent with the commonly accepted one for the Eutherians. A second, larger mammalian dataset is also analyzed, yielding a phylogeny generally consistent with the commonly accepted one for the mammals.


AVAILABILITY
The program to estimate our sequence distance, is available at http://www.cs.cityu.edu.hk/~cssamk/gencomp/GenCompress1.htm. The distance matrices used to generate our phylogenies are available at http://www.math.uwaterloo.ca/~mli/distance.html.
38299768
A simplified method for testing the IBM pipeline partial-scan microprocessor
This paper describes a simple test generation method for a high-performance, pipelined partial-scan microprocessor using an automatic test generation tool which was optimized for combinational logic in generating manufacturing test data. Without this method the test generation tool would have had great difficulty in generating the test data needed to achieve the required high fault coverage. User-specified clocking sequences are also allowed for design flexibility. A description of this method is provided and the experimental results are discussed.
34040250
Connected domination critical graphs
Abstract A dominating set in a graph G is a connected dominating set of G if it induces a connected subgraph of G . The minimum number of vertices in a connected dominating set of G is called the connected domination number of G , and is denoted by γ c ( G ). The purpose of this paper is to initiate an investigation of those graphs which are critical in the following sense: for each υ, μ ϵ V (G) with υ not adjacent to u , γ c ( G + υ u ) c ( G ). Thus, G is k -γ c -critical if γ c ( G ) = k and for each edge e ∉ E ( G ), γ c ( G + e ) k . First we discuss whether some particular classes of graphs are γ c -critical. Then 2-γ c -critical graphs are characterized. Finally, the properties of the 3-γ c -critical graphs are studied.
14272026
Fully automated facial symmetry axis detection in frontal color images
We consider the problem of automatically detecting a facial symmetry axis in what we will call a standard human face image (acquired when the subject is looking directly into the camera, in front of a clean gray background under controlled illumination). Images of this kind are encountered in face recognition scenarios; this detection should facilitate more sophisticated facial image processing. The proposed method is based on GLDH (gray level difference histogram) analysis and consists of three components: (1) the face region detection stage crops an approximate face region out of the background, (2) symmetry detection discovers a vertical axis to optimally bisect the region of interest, assuming it is bilaterally symmetric, and (3) orientation adjustment aligns the angle of the symmetry axis with the orientation of the face. An implementation of the method is described, and results are presented. This detector's robust performance is evidenced by its success finding symmetry axes in more than 7,500 images collected from 600 distinct subjects. One of our method's most noteworthy contributions is that, according to our experimental results, many of the automatically detected axes are more accurate than the reference axes. Our automated detector is a powerful tool because it is not as susceptible to human error as its manual counterpart and, as the first application of its kind, it could potentially serve as a new biometric.