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31.
Simon P. Wilson Francisco J. Samaniego 《IEEE transactions on pattern analysis and machine intelligence》2007,33(3):198-208
In the literature on statistical inference in software reliability, the assumptions of parametric models and random sampling of bugs have been pervasive. We argue that both assumptions are problematic, the first because of robustness concerns and the second due to logical and practical difficulties. These considerations motivate the approach taken in this paper. We propose a nonparametric software reliability model based on the order-statistic paradigm. The objective of the work is to estimate, from data on discovery times observed within a type I censoring framework, both the underlying distribution F from which discovery times are generated and N, the unknown number of bugs in the software. The estimates are used to predict the next time to failure. The approach makes use of Bayesian nonparametric inference methods, in particular, the beta-Stacy process. The proposed methodology is illustrated on both real and simulated data 相似文献
32.
Montserrat Bóo Francisco Argüello Javier D. Bruguera Emilio L. Zapata 《The Journal of VLSI Signal Processing》1997,17(1):57-73
A rate 1/n binary generic convolutional encoder is a shift-register circuit where the inputs are information bits and the outputs are blocks of n bits generated as linear combinations on the appropriate shift register contents. The decoding of the outputs of a convolutional encoder can be carried out by the well-known Viterbi algorithm. The communication pattern of the Viterbi Algorithm is given as a graph, called trellis, associated to the state diagram of the corresponding encoder. In this paper we present a methodology that permits the efficient mapping of the Viterbi algorithm onto a column of an arbitrary number of processors. This is done through the representation of the data flow by using mathematical operators which present an inmediate hardware projection. A single operator string has been obtained to represent a generic encoder through the study of the data flow of free-forward encoders and feed-back encoders. The formal model developed is employed for the partitioning of the computations among an arbitrary number of processors in such a way that the data are recirculated opimizing the use of the processors and the communications. As a result, we obtain a highly regular and modular architecture suitable for VLSI implementation. 相似文献
33.
Participating media with an inhomogeneous index of refraction make light follow curved paths. Simulating this in a global
illumination environment has usually been neglected due to the complexity of the calculations involved, sacrificing accurate
physical simulations for efficient visual results.
This paper aims to simulate non-linear media in a more reasonable time than previous works without losing physical correctness.
Accuracy is achieved by solving the Eikonal equation of geometrical optics, which describes the path followed by a light beam
that traverses a non-linear medium. This equation is used in the context of a photon mapping extension. 相似文献
34.
Nowadays, cities are the most relevant type of human settlement and their population has been endlessly growing for decades. At the same time, we are witnessing an explosion of digital data that capture many different aspects and details of city life. This allows detecting human mobility patterns in urban areas with more detail than ever before. In this context, based on the fusion of mobility data from different and heterogeneous sources, such as public transport, transport‐network connectivity and Online Social Networks, this study puts forward a novel approach to uncover the actual land use of a city. Unlike previous solutions, our work avoids a time‐invariant approach and it considers the temporal factor based on the assumption that urban areas are not used by citizens all the time in the same manner. We have tested our solution in two different cities showing high accuracy rates. 相似文献
35.
Quesada-Barriuso Pablo Blanco Heras Dora Argüello Francisco 《The Journal of supercomputing》2021,77(9):10040-10052
The Journal of Supercomputing - The high computational cost of the superpixel segmentation algorithms for hyperspectral remote sensing images makes them ideal candidates for parallel computation.... 相似文献
36.
Palomares Iván Martínez-Cámara Eugenio Montes Rosana García-Moral Pablo Chiachio Manuel Chiachio Juan Alonso Sergio Melero Francisco J. Molina Daniel Fernández Bárbara Moral Cristina Marchena Rosario de Vargas Javier Pérez Herrera Francisco 《Applied Intelligence》2021,51(9):6497-6527
Applied Intelligence - The17 Sustainable Development Goals (SDGs) established by the United Nations Agenda 2030 constitute a global blueprint agenda and instrument for peace and prosperity... 相似文献
37.
Moutafis Panagiotis García-García Francisco Mavrommatis George Vassilakopoulos Michael Corral Antonio Iribarne Luis 《Distributed and Parallel Databases》2021,39(3):733-784
Distributed and Parallel Databases - Given two datasets of points (called Query and Training), the Group (K) Nearest-Neighbor (GKNN) query retrieves (K) points of the Training with the smallest sum... 相似文献
38.
Julián Luengo José A. Sáez Francisco Herrera 《Soft Computing - A Fusion of Foundations, Methodologies and Applications》2012,16(5):863-881
Fuzzy rule-based classification systems (FRBCSs) are known due to their ability to treat with low quality data and obtain
good results in these scenarios. However, their application in problems with missing data are uncommon while in real-life
data, information is frequently incomplete in data mining, caused by the presence of missing values in attributes. Several
schemes have been studied to overcome the drawbacks produced by missing values in data mining tasks; one of the most well
known is based on preprocessing, formerly known as imputation. In this work, we focus on FRBCSs considering 14 different approaches
to missing attribute values treatment that are presented and analyzed. The analysis involves three different methods, in which
we distinguish between Mamdani and TSK models. From the obtained results, the convenience of using imputation methods for
FRBCSs with missing values is stated. The analysis suggests that each type behaves differently while the use of determined
missing values imputation methods could improve the accuracy obtained for these methods. Thus, the use of particular imputation
methods conditioned to the type of FRBCSs is required. 相似文献
39.
Mateus Ferreira-Satler Francisco P. Romero Victor H. Menendez-Dominguez Alfredo Zapata Manuel E. Prieto 《Soft Computing - A Fusion of Foundations, Methodologies and Applications》2012,16(7):1129-1141
Nowadays, the impact of technological developments on improving human activities is becoming more evident. In e-learning, this situation is no different. There are common to use systems that assist the daily activities of students and teachers. Typically, e-learning recommender systems are focused on students; however, teachers can also benefit from these type of tools. A recommender system can propose actions and resources that facilitate teaching activities like structuring learning strategies. In any case, a complete user’s representation is required. This paper shows how a fuzzy ontology can be used to represent user profiles into a recommender engine and enhances the user’s activities into e-learning environments. A fuzzy ontology is an extension of domain ontologies for solving the problems of uncertainty in sharing and reusing knowledge on the Semantic Web. The user profile is built from learning objects published by the user himself into a learning object repository. The initial experiment confirms that the automatically obtained fuzzy ontology is a good representation of the user’s preferences. The experiment results also indicate that the presented approach is useful and warrants further research in recommending and retrieval information. 相似文献
40.
Francisco Fernández-Navarro César Hervás-Martínez Roberto Ruiz Jose C. Riquelme 《Applied Soft Computing》2012,12(6):1787-1800
Radial Basis Function Neural Networks (RBFNNs) have been successfully employed in several function approximation and pattern recognition problems. The use of different RBFs in RBFNN has been reported in the literature and here the study centres on the use of the Generalized Radial Basis Function Neural Networks (GRBFNNs). An interesting property of the GRBF is that it can continuously and smoothly reproduce different RBFs by changing a real parameter τ. In addition, the mixed use of different RBF shapes in only one RBFNN is allowed. Generalized Radial Basis Function (GRBF) is based on Generalized Gaussian Distribution (GGD), which adds a shape parameter, τ, to standard Gaussian Distribution. Moreover, this paper describes a hybrid approach, Hybrid Algorithm (HA), which combines evolutionary and gradient-based learning methods to estimate the architecture, weights and node topology of GRBFNN classifiers. The feasibility and benefits of the approach are demonstrated by means of six gene microarray classification problems taken from bioinformatic and biomedical domains. Three filters were applied: Fast Correlation-Based Filter (FCBF), Best Incremental Ranked Subset (BIRS), and Best Agglomerative Ranked Subset (BARS); this was done in order to identify salient expression genes from among the thousands of genes in microarray data that can directly contribute to determining the class membership of each pattern. After different gene subsets were obtained, the proposed methodology was performed using the selected gene subsets as new input variables. The results confirm that the GRBFNN classifier leads to a promising improvement in accuracy. 相似文献