Scielo RSS <![CDATA[Computación y Sistemas]]> vol. 20 num. 2 lang. en <![CDATA[SciELO Logo]]> <![CDATA[Editorial]]> <![CDATA[Self-Adaptive Differential Evolution Hyper-Heuristic with Applications in Process Design]]> Abstract. The paper presents a differential evolution (DE)-based hyper-heuristic algorithm suitable for the optimization of mixed-integer non-linear programming (MINLP) problems. The hyper-heuristic framework includes self-adaptive parameters, an ε-constrained method for handling constraints, and 18 DE variants as low-level heuristics. Using the proposed approach, we solved a set of classical test problems on process synthesis and design and compared the results with those of several state-of-the-art evolutionary algorithms. To verify the consistency of the proposed approach, the above-mentioned comparison was made with respect to the percentage of convergences to the global optimum (NRC) and the average number of objective function evaluations (NFE) over several trials. Thus, we found that the proposed methodology significantly improves performance in terms of NRC and NFE. <![CDATA[Personnel Selection in a Competitive Environment]]> Abstract The personnel selection problem is a classical decision making problem. It refers to the process of choosing candidates who match, possibly to some degree, the qualifications required to perform a certain job. Personnel selection is an important activity for organizations and usually the outcome of a personnel selection method is an overall ranking of the candidates. This paper introduces two new results. First, we propose an alternative approach to the personnel selection problem in which the interaction of two competing decision makers (employers), who must select two subsets of persons from a common list of candidates, is considered. Second, given the rankings of the candidates for each employer, a method based on the game theory is presented to solve this problem. <![CDATA[An Experimental Study of Evolutionary Product-Unit Neural Network Algorithm]]> This paper aims to obtain empirical information about the behavior of an Evolutionary Product-Unit Neural Network (EPUNN) in different scenarios. To achieve this, an extensive evaluation was conducted on 21 data sets for the classification task. Then, we evaluated EPUNN on eleven noisy data sets, on sixteen imbalanced data sets, and on ten missing values data sets. As a result of this evaluation process, we conclude that there does not exist a significant difference between EPUNN and the four algorithms assessed; the accuracy of EPUNN rapidly worsen in the presence of noise, so we do not recommend its utilization in noisy environments; we found a tendency to robustness in EPUNN while the imbalance ratio grows; finally, we can state that it is able to handle missing data, but in this kind of data, a significant performance deterioration was manifested. For future work, we recommend to assess the impact of irrelevant attributes on EPUNN performance. In addition, an extension of noisy data set evaluation would be opportune. <![CDATA[Fractional Complex Dynamical Systems for Trajectory Tracking using Fractional Neural Network]]> In this paper the problem of trajectory tracking is studied. Based on Lyapunov theory, a control law that achieves global asymptotic stability of the tracking error between a fractional recurrent neural network and the state of each single node of the fractional complex dynamical network is obtained. To illustrate the analytic results we present a tracking simulation of a simple network with four different nodes and five non-uniform links. <![CDATA[Smoothing the High Level Canonical Piecewise-Linear Model by an Exponential Approximation of its Basis-Function]]> Abstract Piecewise-linear models constitute an attractive alternative to construct a function whose graph fits a finite set of discrete points. These models are preferably selected over other approximation strategies like polynomials or splines. Although there are several piecewise-linear models reported in literature, the so-called High Level Canonical has the remarkable advantage of emerging from a well-structured algorithmic methodology to efficiently determine the parameters of any given piecewise-linear function. However, as it happens in all other piecewise-linear models, it also has the problem of lack of differentiability at the breakpoints. In order to solve this problem, an approach based on an exponential approximation of the basis-function is proposed as a strategy to transform the High Level Canonical piecewise-linear model into a smooth-piecewise one. This mathematical transformation ensures the existence and continuity of the nth-order derivatives of the resulting smooth model. Besides of this, it is observed that by applying the piecewise-linear to smooth transformation, the number of terms of the resulting smooth representation can significantly be reduced due to a great number of them can be approximated by a line equation. In order to verify the effectiveness of this proposal, numerical simulations performed on one-dimensional and two-dimensional functions are reported. <![CDATA[Validating Design Patterns for Mobile Groupware Applications by Expert Users: a USAER Case]]> Abstract The objective of this research work was to analyze the pertinence of a set of design patterns for mobile groupware applications. The pertinence of said contribution was supported by 11 participant members of an educational support group (USAER). The perception of expert users is commonly used in Human-Computer Interaction to improve and validate design strategies such as the proposed one. In this case the feedback provided by the participants helped to ensure that the knowledge offered by the set of patterns is adequate and accurate. A distilled feedback would lead to well-designed user interfaces for mobile groupware applications. <![CDATA[Relationship between the Inverses of a Matrix and a Submatrix]]> Abstract A simple and straightforward formula for computing the inverse of a submatrix in terms of the inverse of the original matrix is derived. General formulas for the inverse of submatrices of order n - k as well as block submatrices are derived. The number of additions (or subtractions) and multiplications (or divisions) on the formula is calculated. A variety of numerical results are shown. <![CDATA[Unsupervised Opinion Polarity Detection based on New Lexical Resources]]> Abstract There are polarity detection techniques based on the lexicon of opinion words and those based on machine learning techniques. In this paper, we focus on unsupervised polarity detection using lexical resources. We present the SentiWordNet 4.0 and the SpanishSentiWordNet in order to solve the detected drawbacks of previous resources. The integration of the proposed resources is solved by combining them in the PolarityDetection library, which is integrated to PosNeg Opinion 2.0 and facilitates obtaining high accuracy and recall values. <![CDATA[Automatic Detection of Similarity of Programs in Karel Programming Language based on Natural Language Processing Techniques]]> Este artículo presenta un método para calcular la similitud entre programas (código fuente). La tarea es útil, por ejemplo, para la clasificación temática de programas o detección de reuso de código (digamos, en el caso de plagio). Usamos para los experimentos el lenguaje de programación Karel. Para determinar la similitud entre programas y/o ideas de soluciones similares utilizamos un enfoque basado en técnicas de procesamiento de lenguaje natural y de recuperación de información. Estas técnicas usan la representación de un documento como un vector de valores de características. Usualmente, las características son n-gramas de palabras o de caracteres. Posteriormente, se puede aplicar el análisis semántico latente para reducir la dimensionalidad de este espacio vectorial. Finalmente, se usa el aprendizaje automático supervisado para la clasificación de textos (o programas que son textos también) parecidos. Para validar el método propuesto, se compiló un corpus de programas para 100 tareas diferentes con un total de 9,341 códigos y otro corpus para 34 tareas adicionalmente clasificado por la idea de solución, formado por 374 códigos. Los resultados experimentales muestran que para el corpus con ideas de solución es mejor la representación con trigramas de caracteres, mientras que para el corpus completo los mejores resultados se obtienen con trigramas de términos y la aplicación del análisis semántico latente.<hr/>In this paper, we present a method for calculating similarity between programs (source codes). One of the applications of the task is detection of code reuse, for example, in the case of plagiarism. The Karel programming language is used for experiments. In order to determine similarity between Karel programs and/or similar software solutions, we make use of techniques from the fields of natural language processing and information retrieval. These techniques use representations of documents as vectors of features and their values. Usually, the features are n-grams of words or n-grams of characters. In addition, we consider application of the latent semantic analysis for reduction of the number of dimensions of the vector space. Finally, we use a supervised machine learning approach for classification of texts (or programs, which are texts as well) based on their similarity. For evaluation of the proposed method, two corpora were developed: the first corpus is composed of 100 different programs with a total of 9,341 source codes. The second corpus consists of 34 tasks with a total of 374 codes, which are grouped by the proposed solution. Our experiments showed that for the first corpus, the best results were obtained using trigrams of terms (words) accompanied with application of latent semantic analysis, while for the second corpus, the best representation was achieved using character trigrams. <![CDATA[Integrated Routing and Positioning in Mobile Ad Hoc Networks]]> Resumen En este artículo se presenta el primer marco de trabajo para posicionamiento y enrutamiento multicast integrados en redes móviles ad hoc (MANETs por sus siglas en ingles). Este nuevo enfoque utiliza la misma senalizaci&lt;5n de control basada en regiones de interés para soportar tanto enrutamiento como posicionamiento. Se presenta POSTAL PRIME, que es una instancia de este marco de trabajo para enrutamiento y posicionamiento integrados. POSTAL PRIME calcula componentes conexos de la red que contienen tanto a las fuentes de datos como los destinos en el caso de enrutamiento, así como las referencias y los nodos con interés en conocer su posicion en el caso de posicionamiento. El objetivo de las regiones de interés es restringir la diseminacion de senalizacion de control a estas regiones de forma tal que se aumente la reutilizacion espacial del ancho de banda. Para estimar la posicion de un nodo, POSTAL PRIME introduce un método novedoso llamado multilateracion probabilística que determina la posicion de un nodo basado en la posicion de tres o más referencias y las distancias estimadas de manera imprecisa hacia ellas. Para evaluar la eficacia de POSTAL PRIME, se presenta un análisis detallado basado en simulaciones realistas. Los resultados muestran que POSTAL PRIME supera el desempeno de la funcionalidad combinada de ODMRP+Amorphous, que son los algoritmos de enrutamiento y posicionamiento más representativos en MANETs.<hr/>Abstract This work presents the first integrated framework for positioning and multicast routing in mobile ad hoc networks (MANETs). In this new approach, the same control signaling is used to support multicast routing and positioning, eliminating the distinction between on-demand and proactive signaling, which are substituted by interest-driven signaling. We also present the POSTAL PRIME protocol which is an instantiation of this integrated routing and positioning framework. We use the concept of region of interest to identify connected components of the network that include sources and destinations in the case of routing, and beacons and nodes with interest in computing their position in the case of positioning. This way, we can restrict the dissemination of control signaling to these regions, augmenting the spatial reutilization of bandwidth. POSTAL PRIME also introduces the probabilistic multilateration method for estimating the position of a node based on the position of three or more references and noisy estimates of distances to them. To assess the effectiveness of POSTAL PRIME, we present a detailed simulation-based analysis. The experimental results show that POSTAL PRIME outperforms the combined use of ODMRP+Amorphous, which are the most representative multicast routing and positioning protocols in MANETs.