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Abstract Traditional dynamic multiobjective evolutionary algorithms usually imitate the evolution of nature, maintaining diversity of population through different strategies and making the population track the Pareto optimal solution set efficiently after the environmental change. However, these algorithms neglect the role of the dynamic environment in evolution, leading to the lacking of active guieded search. In this paper, a dynamic multiobjective evolutionary algorithm based on a dynamic evolutionary environment model is proposed (DEE-DMOEA). When the environment has not changed, this algorithm makes use of the evolutionary environment to record the knowledge and information generated in evolution, and in turn, the knowledge and information guide the search. When a change is detected, the algorithm helps the population adapt to the new environment through building a dynamic evolutionary environment model, which enhances the diversity of the population by the guided method, and makes the environment and population evolve simultaneously. In addition, an implementation of the algorithm about the dynamic evolutionary environment model is introduced in this paper. The environment area and the unit area are employed to express the evolutionary environment. Furthermore, the strategies of constraint, facilitation and guidance for the evolution are proposed. Compared with three other state-of-the-art strategies on a series of test problems with linear or nonlinear correlation between design variables, the algorithm has shown its effectiveness for dealing with the dynamic multiobjective problems. [ABSTRACT FROM AUTHOR]

Abstract The paper discusses a niche area problem — the design of reduced-order multiple observers which can achieve the finite-time state reconstruction for Takagi–Sugeno multiple models with unknown inputs. The new reduced-order multiple observer obtained in this paper is only the second ever designed, the author of this paper continuing his work started one year ago with the introduction of the reduced-order multiple observer concept. The obtaining of the new reduced-order multiple observer is achieved by combining two classical reduced-order observers for linear time-invariant multivariable systems with unknown inputs and a full-order multiple observer for Takagi–Sugeno systems. The main innovative idea behind the design of the reduced-order multiple observer for Takagi–Sugeno systems described by the multiple models is the split of the multiple model into two subsystems: an unknown-input-free subsystem and an unknown-input-depending subsystem. The unknown-input-free subsystem is brought to the form of a standard multiple model and, in this situation, any algorithm to design full-order multiple observers can be used in the design of reduced-order multiple observers. The steps of the design procedure have been summarized and software implemented; then, the validation of the suggested algorithm has been done for two concrete cases associated to the motion of an aircraft during its landing Highlights • Paper discusses a niche area problem-design of reduced-order multiple observers. • The reduced-order observer designed is only the second one ever obtained. • The steps of the design procedure have been summarized and software implemented. • The observer's performances are compared with the ones of other observers. [ABSTRACT FROM AUTHOR]

Abstract In this work, we are interested in the steganography domain where the problem of security represents the basic key in the dissimulation of relevant information. The paper highlights two facets of research. The first facet represents a novel proposition of a naturally-inspired metaheuristic based on the smell sense of a honeybee insect. Herein, the collective foraging behavior is not explicitly intended but the search driven by smell sense is critical. The second facet highlights the proposition of two steganographic embedding schemes. The main idea behind the 2-Bit embedding scheme focus on the embedding rate of two secret bits by pixel. Compared to other steganographic algorithms, the intended bit that will support the elementary secret information can be anyone in the pixel byte provided that its content matches with the secret bit to embed. The proposed steganographic algorithm named HIBE takes advantage from transform domain since it presents more robustness against image processing attacks. And eventually, takes advantage from spatial domain since the lower distortion results achieved in comparison with other well-knew algorithm like HUGO, and WOW gives it more efficiency. Moreover, to evaluate its performance against steganalyzers methods based machine learning and classifiers some experiments were carried out on the BOSSbase dataset images. The reached results have shown that the used detectors, also well-knew, failed to classify the learned images as stego since their achieved detection accuracies approaches the random detection. [ABSTRACT FROM AUTHOR]

Network physical topology discovery is the key issue for network management and application, the physical topology discovery based on Address Forwarding Table (AFT) is a hot topic on current study. This paper defines three constraints of AFTs, and proposes a tree chopping algorithm based on AFTs satisfying down constraint, which can discover the physical topology of a subnet accurately. The proposed algorithm decreases the demand for AFT integrity dramatically, and is the loosest constraint for discovering physical topology which just relies on AFTs of down ports. The proposed algorithm can also be used in the switch domain of multiple subnets. [ABSTRACT FROM AUTHOR]

This paper presents the Discrete Wavelet based fusion techniques for combining perceptually important image features. SPIHT (Set Partitioning in Hierarchical Trees) algorithm is an efficient method for lossy and lossless coding of fused image. This paper presents some modifications on the SPIHT algorithm. It is based on the idea of insignificant correlation of wavelet coefficient among the medium and high frequency sub bands. In RE-MSPIHT algorithm, wavelet coefficients are scaled prior to SPIHT coding based on the sub band importance, with the goal of minimizing the MSE. [ABSTRACT FROM AUTHOR]

The K-means algorithm is a popular data-clustering algorithm. However, one of its drawbacks is the requirement for the number of clusters, K , to be specified before the algorithm is applied. This paper first reviews existing methods for selecting the number of clusters for the algorithm. Factors that affect this selection are then discussed and a new measure to assist the selection is proposed. The paper concludes with an analysis of the results of using the proposed measure to determine the number of clusters for the K-means algorithm for different data sets. [ABSTRACT FROM AUTHOR]

In the last decades, heuristic algorithms are widely used in solving problems in different fields of science and engineering. Most of these methods are inspired by natural phenomena, such as biological behaviours or physical principles. In this paper, a new optimization method based on the dynamic of sliding motion along a frictionless inclined plane is introduced. In the proposed algorithm, a collection of agents cooperate with each other and move toward better positions in the search space by employing Newton's second law and equations of motion. Our method is compared with other popular optimization algorithms and the results on 23 standard benchmark functions show its effectiveness in most cases. [ABSTRACT FROM AUTHOR]

S-measures are Loeb measures restricted to the sigma algebra generated by standard sets. This paper gives new extensions of the S-measure machinery, with applications to standard measure theory. [ABSTRACT FROM AUTHOR]

A new optimum approach is presented for strapdown coning algorithm design based on Explicit matching of desired response to expected coning input magnitude as a function of coning frequency. Unlike previous time or frequency Taylor series expansion techniques, the new method achieves optimization through minimum least-squares estimation over a user selected design frequency range. The error being minimized is the square of the weighted algorithm error, the weighting factor being user specified coning amplitude over frequency. This methodology allows the coning algorithm coefficients to be independently designed for each caning axis to achieve optimal balanced performance over the frequency range of expected coning inputs. Performance of the new algorithm design technique is evaluated by comparison with previous time and frequency-series approaches, in discrete and stochastic coning environments, and over a time based extreme dynamic maneuvering profile. A generalized method is presented for translating system performance requirements into expected coning amplitude versus frequency profiles for calculating Explicit algorithm coefficients, and for evaluating coning algorithm accuracy. The paper includes derivations of generalized formulas for calculating algorithm coefficients for previous time and frequency-series design approaches. [ABSTRACT FROM AUTHOR]

In this paper, we describe the conditions, providing the existence of splicing of the measures λ , μ and v - finite, finitely additive and integral functions of sets, defined on the algebras of subsets B and C of some set Ω and the algebra U, based on the algebras B and C . Moreover, we show that the measure λ should be a common extension of the measures μ and v , and λ(B∩C)= λ(B)λ(C) for any B ε B, C ε C. [ABSTRACT FROM AUTHOR]

The security of most elliptic curve cryptosystems is based on the intractability of the Elliptic Curve Discrete Logarithm Problem (ECDLP). Such a problem turns out to be computationally unfeasible when elliptic curves are suitably chosen. This paper provides an algorithm to obtain cryptographically good elliptic curves from a given one. The core of such a procedure lies on the usage of successive chains of isogenies, visiting different volcanoes of isogenies which are located in different l-cordilleras. [ABSTRACT FROM AUTHOR]

Abstract: This work is a continuation of [7]. In that paper, a sufficient condition was given on a real analytic fmlction g defined near 0 in C so that the algebra generated by z 2 and g 2 is dense in the space of continuous functions on D for all disks D close enough to the origin in C. By using the same methods and some ideas taken from the first named author''s thesis we deal with the case where g is only of class C 1 near 0. [Copyright &y& Elsevier]

In this paper, we consider random generalization of completely generalized nonlinear variational-like inclusions and propose an iterative algorithm for computing their approximate solutions. We prove that the approximate solutions obtained by proposed algorithm converge to the exact solution of our problem. [ABSTRACT FROM AUTHOR]

This paper proposes a systematic method to classify data with outliers. The essential techniques consist of the outlier detection and the fuzzy support vector machine (FSVM). In this approach, the main body set for each class is first determined by the outlier detection algorithm (ODA) that estimates the outliers based on the total similarity objective function. Then, incorporated with the total similarity measure of the ODA, a fuzzy membership degree is assigned to each training sample. Experiments show that the proposed method can greatly reduce the effects of outliers in the training process and the final decision surface of the FSVM is insensitive to outliers. [ABSTRACT FROM AUTHOR]

In this paper, we consider random generalization of completely generalized nonlinear variational-like inclusions and propose an iterative algorithm for computing their approximate solutions. We prove that the approximate solutions obtained by proposed algorithm converge to the exact solution of our problem. [ABSTRACT FROM AUTHOR]

Abstract: In a recent paper [Discrete Appl. Math. 130 (2003) 449–467], Yang, Ye, and Zhang investigate the problem of scheduling independent jobs on two identical machines, with a limit on the number of jobs that can be assigned to each single machine, so as to minimize the total weighted completion time of the jobs. They provide a semidefinite programming based, polynomial time approximation algorithm with a worst case ratio of . In this short technical note, we establish the existence of an FPTAS for this problem, and for the corresponding makespan minimization problem. [Copyright &y& Elsevier]

In this paper, we propose a new pedestrian detection algorithm, and use it to develop a real-time pedestrian detection system. The pedestrian detection algorithm can be functionally partitioned into two parts: moving object segmentation and pedestrian recognition. In moving object segmentation, we segment the moving objects in the scene by modified temporal differencing method. This method combines general temporal differencing method with detection nets. In pedestrian recognition, we obtain multi-type wavelet templates from input images. Interest points are extracted from wavelet templates. Then, feature points are extracted by statistical method from interest point templates. Finally, these feature points are fed into a trained multilayer back-propagation neural network. The output of the neural network implies the result -- pedestrian or non-pedestrian. From experiments, accuracy rate of recognition achieves 95%. We implement this algorithm in a real-time pedestrian detection system. The system can detect pedestrians in the scene in real time. The pedestrian detection rate is 92.58%. [ABSTRACT FROM AUTHOR]

In this paper, we explore the structure of the set of all regular equivalences (White and Reitz 1983), proving that it forms a lattice, and suggest a general approach to computing certain elements of the lattice. The resulting algorithm represents a useful complement to the White and Reitz algorithm, which can only find the maximal regular equivalence of a graph. Using this algorithm, it is possible to compute several well-known equivalences, such as structural equivalence. (Lorrain and White 1971), automorphic equivalence (Everett and Borgatti 1988), and Winship-Pattison equivalence (Winship and Mandel 1983). In addition, any number of other useful equivalences may be generated, providing suitable mathematical descriptions of them are available. [ABSTRACT FROM AUTHOR]

In this paper an algorithm is given which decides, for a domain with boundary composed of planar algebraic curve segments, whether an arbitrary point is inside or external to the domain. The algebraic curve segments of the algorithm are assumed to be contained in rectangles or other polygons (which may not contain other pieces of the curve). We discuss which curve segments have this representation. When the curves are conic sections, we give some simple rules for constructing the representation. [ABSTRACT FROM AUTHOR]

Repetitive substructures of two-dimensional arrays have been recently defined and studied in an attempt to parallel some of the analogous developments already known for strings. In the present paper we propose an O (log log n) time O(n3 log n) work optimally fast, optimal parallel CRCW-PRAM algorithm for detecting all repetitions of certain type in an n × n array. [Copyright &y& Elsevier]