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841.
Intensional query answering by partial evaluation 总被引:1,自引:0,他引:1
Giuseppe de Giacomo 《Journal of Intelligent Information Systems》1996,7(3):205-233
842.
Cuenca Angel García Pedro Albertos Pedro Salt Julián 《International Journal of Control, Automation and Systems》2011,9(6):1194-1202
International Journal of Control, Automation and Systems - This paper presents a Non-Uniform Predictor-Observer (NUPO) based control approach in order to deal with two of the main problems related... 相似文献
843.
Sergio S��nchez Garc��a Ana G��mez Oliva Emilia P��rez Belleboni Iv��n Pau de la Cruz 《International Journal of Information Security》2011,10(6):351-372
At present, many countries allow citizens or entities to interact with the government outside the telematic environment through
a legal representative who is granted powers of representation. However, if the interaction takes place through the Internet,
only primitive mechanisms of representation are available, and these are mainly based on non-dynamic offline processes that
do not enable quick and easy identity delegation. This paper proposes a system of dynamic delegation of identity between two
generic entities that can solve the problem of delegated access to the telematic services provided by public authorities.
The solution herein is based on the generation of a delegation token created from a proxy certificate that allows the delegating
entity to delegate identity to another on the basis of a subset of its attributes as delegator, while also establishing in
the delegation token itself restrictions on the services accessible to the delegated entity and the validity period of delegation.
Further, the paper presents the mechanisms needed to either revoke a delegation token or to check whether a delegation token
has been revoked. Implications for theory and practice and suggestions for future research are discussed. 相似文献
844.
César García-Osorio Aida de Haro-García Nicolás García-Pedrajas 《Artificial Intelligence》2010,174(5-6):410-441
Instance selection is becoming increasingly relevant due to the huge amount of data that is constantly being produced in many fields of research. Although current algorithms are useful for fairly large datasets, scaling problems are found when the number of instances is in the hundreds of thousands or millions. When we face huge problems, scalability becomes an issue, and most algorithms are not applicable.Thus, paradoxically, instance selection algorithms are for the most part impracticable for the same problems that would benefit most from their use. This paper presents a way of avoiding this difficulty using several rounds of instance selection on subsets of the original dataset. These rounds are combined using a voting scheme to allow good performance in terms of testing error and storage reduction, while the execution time of the process is significantly reduced. The method is particularly efficient when we use instance selection algorithms that are high in computational cost. The proposed approach shares the philosophy underlying the construction of ensembles of classifiers. In an ensemble, several weak learners are combined to form a strong classifier; in our method several weak (in the sense that they are applied to subsets of the data) instance selection algorithms are combined to produce a strong and fast instance selection method.An extensive comparison of 30 medium and large datasets from the UCI Machine Learning Repository using 3 different classifiers shows the usefulness of our method. Additionally, the method is applied to 5 huge datasets (from three hundred thousand to more than a million instances) with good results and fast execution time. 相似文献
845.
846.
José A. de França Author Vitae Marcelo R. Stemmer Author Vitae 《Pattern recognition》2010,43(3):1180-1187
In recent years, the camera calibration using 1D patterns has been studied and improved by researchers all over the world. However, the progress in that area has been mainly in the sense of reducing the restrictions to the 1D pattern movement. On the other hand, the method's accuracy still demands improvements. In the present paper, the original technique proposed by Zhang is revisited and we demonstrate that the method's accuracy can be significantly improved, simply by analyzing and reformulating the problem. The numerical conditioning can be improved if a simple data normalization is performed. Furthermore, a non-linear solution based on the Partitioned Levenberg-Marquardt algorithm is proposed. That solution takes advantage of the problem's particular structure to reduce the computational complexity of the original method and to improve the accuracy. Tests using both synthetic and real images demonstrate that the calibration method using 1D patterns can be applied in practice, with accuracy comparable to other already traditional methods. 相似文献
847.
Pedro Casas Lionel Fillatre Sandrine Vaton Igor Nikiforov 《Journal of Network and Systems Management》2011,19(1):58-83
This paper presents a novel approach to deal with dynamic and highly uncertain traffic in dynamic network scenarios. The Reactive
Robust Routing (RRR) approach is introduced, a combination of proactive and reactive techniques to improve network efficiency
and robustness, simplifying network operation. RRR optimizes routing for normal-operation traffic, using a time-varying extension
of the already established Robust Routing technique that outperforms the stable approach. To deal with anomalous and unexpected
traffic variations, RRR uses a fast anomaly detection and localization algorithm that rapidly detects and localizes abrupt
changes in traffic flows, permitting an accurate routing adaptation. This algorithm presents well-established optimality properties
in terms of detection/localization rates and localization delay, which allows for generalization of results, independently
of particular evaluations. The algorithm is based on a novel parsimonious model for traffic demands which allows for detection
of anomalies using easily available aggregated-traffic measurements, reducing the overheads of data collection. 相似文献
848.
Javier Sánchez-Monedero Pedro A. Gutiérrez F. Fernández-Navarro C. Hervás-Martínez 《Neural Processing Letters》2011,34(2):101-116
Recently, a multi-objective Sensitivity–Accuracy based methodology has been proposed for building classifiers for multi-class problems. This technique is especially suitable for imbalanced and multi-class datasets. Moreover, the high computational cost of multi-objective approaches is well known so more efficient alternatives must be explored. This paper presents an efficient alternative to the Pareto based solution when considering both Minimum Sensitivity and Accuracy in multi-class classifiers. Alternatives are implemented by extending the Evolutionary Extreme Learning Machine algorithm for training artificial neural networks. Experiments were performed to select the best option after considering alternative proposals and related methods. Based on the experiments, this methodology is competitive in Accuracy, Minimum Sensitivity and efficiency. 相似文献
849.
Alberto Pardo Jo?o Paulo Fernandes Jo?o Saraiva 《Higher-Order and Symbolic Computation》2011,24(1-2):115-149
Functional programs often combine separate parts using intermediate data structures for communicating results. Programs so defined are modular, easier to understand and maintain, but suffer from inefficiencies due to the generation of those gluing data structures. To eliminate such redundant data structures, some program transformation techniques have been proposed. One such technique is shortcut fusion, and has been studied in the context of both pure and monadic functional programs. In this paper, we study several shortcut fusion extensions, so that, alternatively, circular or higher-order programs are derived. These extensions are also provided for effect-free programs and monadic ones. Our work results in a set of generic calculation rules, that are widely applicable, and whose correctness is formally established. 相似文献
850.
Oleksandr?PanchenkoEmail author Hasso?Plattner Alexander?B.?Zeier 《Information Systems Frontiers》2011,13(3):349-357
Enabling fast and detailed insights over large portions of source code is an important task in a global development ecosystem.
Numerous data structures have been developed to store source code and to support various structural queries, to help in navigation,
evaluation and analysis. Many of these data structures work with tree-based or graph-based representations of source code.
The goal of this project is to elaborate a data storage that enables efficient storing and fast querying of structural information.
The naive adjacency list method has been enhanced with the use of recent data compression approaches for column-oriented databases
to allow no-loss albeit compact storage of fine-grained structural data. The graph indexing has enabled the proposed data
model to expeditiously answer fine-grained structural queries. This paper describes the basics of the proposed approach and
illustrates its technical feasibility. 相似文献