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Inspired from the mechanism of Fuzzy C-means (FCMs) which introduces a degree of fuzziness on the dissimilarity function based on distances, a fuzzy Expectation Maximization (EM) algorithm for Gaussian Mixture Models (GMMs) is proposed in this paper. In the fuzzy EM algorithm, the dissimilarity function is defined as the multiplicative inverse of probability density function. Different from FCMs,...
Edge contraction simplification based on DEM terrain algorithm is proposed as a new terrain simplification algorithm which is based on DEM terrain data characteristics. The algorithm introduces the gradient of triangle, and combines with gradient and the length of edges as weight of the vertex to represent the importance of a vertex. By using the vertex weight, we can constrain the region being affected...
Software behavior models play an important role in software development. They can be manually generated to specify the intended behavior of a system, or they can be reverse-engineered to capture the actual behavior of the system. Models may differ when they correspond to different versions of the system, or they may contain faults or inaccuracies. In these circumstances, it is important to be able...
This paper presents a case study implementation of a fading channel model for a recently introduced Global Positioning System (GPS) simulator from National Instruments. Existing models are discussed and implementation aspects are presented for a model which combines statistical properties of different multipath channels. The NI's GPS simulator is implemented in an open development environment, LabVIEW,...
This paper considers user equilibrium as a nonlinear complementarity problem when the Jacobian of arc travel cost function is symmetric and asymmetric. It shows solutions of user equilibrium exist and corresponding arc flow is unique. It also presents a novel modified FBLSA algorithm which makes full use of the advantage of dealing with large-size road network of column generation method.Finally,numerical...
Autonomous agents require trust and reputation concepts in order to identify communities of agents with which to interact reliably in ways analogous to humans. This paper defines a class of attacks called witness-based collusion attacks designed to exploit trust and reputation models. Empirical results demonstrate that unidimensional trust models are vulnerable to witness-based collusion attacks while...
Combining the interacting multiple model (IMM) and the unscented particle filter (UPF), a new multiple model filtering algorithm is presented. Multiple models can adapt to targets' high maneuvering. Particle filter can deal with the nonlinear or non-Gaussian problems and the unscented Kalman filter (UKF) may improve the approximate accuracy. Compared with other interacting multiple model algorithms...
Most current reputation models fail to calculate peerspsila reputation accurately when there is little transaction history between the peers. To this end, this paper presents a trust model combing reputation and credential which accepts inputs of both feedback and credential. The model is based on reputation-based trust model, and according to the correlation of credential and reputation, the model...
This paper presents an approach to the shortest path problem in time-dependent multimodal networks. The approach derives, from the initial graph, a more simplified and non-time-dependent structure, called abstract graph, by using ant colony optimization. Then, a time-dependent Dijkstra's algorithm is used to compute the shortest path on the new structure. This approach improves two previous solutions...
Modern data centers usually have computing resources sized to handle expected peak demand, but average demand is generally much lower than peak. This means that the systems in the data center usually operate at very low utilization rates. Past techniques have exploited this fact to achieve significant power savings, but they generally focus on centrally managed, throughput-oriented systems that process...
In this paper we extend and generalize previous work on robust adaptive control of uncertain plants using multiple models (the RMMAC methodology). We formulate and study the problem of robust adaptive control of open-loop unstable plants with structured and unstructured uncertainty in the presence of external disturbances, an issue that poses considerable theoretical and practical challenges. In particular,...
Nonlinear system identification is addressed by means of genetic programming. For a flexible selection of model structure and parameters, a multiobjective optimization of the tree encoded individuals is carried out, in terms of accuracy and parsimony. The paper suggests a new optimization algorithm based on the evolvement of two quasi-independent subpopulations, which makes use of a flexible migration...
Interactions between two applications encapsulated into Web services consist in series of message exchanges that must conform to service interfaces. The study reported in this text aims at dealing with the issues that arise when interactions between two services (a client and a provider) fail because their interfaces are incompatible. This may happen because the provider has evolved and its interface...
In this paper, a novel Mycielski based approach for wind speed data generation is developed and presented. The efficiency of the proposed approach is tested using hourly wind speed data obtained from Izmir region. To test the efficiency of the approach, the four year-long measured data are seperated into two parts: data belonging to first three years are used for training whereas the remaining one-year...
The test phase is one of the most important phases in software development. However, in practice, little research has been carried out in this field. Model-driven engineering is a new paradigm that can help to minimize test cases generation costs and can ensure quality of results. This paper presents the application of the MDE paradigm in the systematic, even automatic, generation of system test software.
Based on adaptive Gaussian mixture modelling this article presents the separation of foreground objects from frames of surveillance video taken at avenues and/or intersections. The paper also describes an approach for determining the lane fullness of a dedicated leg of an intersection. In order to give an accurate fullness measure the cast shadows that might be present in the segmented foregrounds...
The mixtures of factor analyzers (MFA) model allows data to be modeled as a mixture of Gaussians with a reduced parametrization. We present the formulation of a nonparametric form of the MFA model, the Dirichlet process MFA (DPMFA). The proposed model can be used for density estimation or clustering of high dimensional data. We utilize the DPMFA for clustering the action potentials of different neurons...
With the pressing in-time-market towards customized services, software product lines (SPL) are increasingly characterizing most of software landscape. SPL are mainly structured through offered features, where consistent composition and dynamic variability are the driving forces. We contribute to these two challenging problems when distribution and correctness are at stake. First, we soundly specify...
A Bayes net has qualitative and quantitative aspects: The qualitative aspect is its graphical structure that corresponds to correlations among the variables in the Bayes net. The quantitative aspects are the net parameters. This paper develops a hybrid criterion for learning Bayes net structures that is based on both aspects. We combine model selection criteria measuring data fit with correlation...
A brief simulation study of real-time packet dispersion mode-tracking using the Gaussian-mix model (originally devised for real-time background classification in moving pictures) and an adaptation of the kernel-density estimator is presented. The simulated environment consisted of two FIFO store-and-forward nodes where the probe packets interact with Poisson and Pareto-generated cross-traffic with...
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