A Hybrid Global Minimization Scheme for Accurate Source Localization in Sensor Networks

We consider the localization problem of multiple wideband sources in a multi-path environment by coherently taking into account the attenuation characteristics and the time delays in the reception of the signal. Our proposed method leaves the space for unavailability of an accurate signal attenuation model in the environment by considering the model as an unknown function with reasonable prior assumptions about its functional space. Such approach is capable of enhancing the localization performance compared to only utilizing the signal attenuation information or the time delays. In this paper, the localization problem is modeled as a cost function in terms of the source locations, attenuation model parameters and the multi-path parameters. To globally perform the minimization, we propose a hybrid algorithm combining the differential evolution algorithm with the Levenberg-Marquardt algorithm. Besides the proposed combination of optimization schemes, supporting the technical details such as closed forms of cost function sensitivity matrices are provided. Finally, the validity of the proposed method is examined in several localization scenarios, taking into account the noise in the environment, the multi-path phenomenon and considering the sensors not being synchronized

A New Approach of Parallelism and Load Balance for the Apriori Algorithm

The main goal of data mining is to discover relevant information on digital content. The Apriori algorithm is widely used to this objective, but its sequential version has a low performance when execu- ted over large volumes of data. Among the solutions for this problem is the parallel implementation of the algorithm, and among the parallel implementations presented in the literature that based on Apriori, it highlights the DPA (Distributed Parallel Apriori) [10]. This paper presents the DMTA (Distributed Multithread Apriori) algorithm, which is based on DPA and exploits the parallelism level of threads in order to increase the performance. Besides, DMTA can be executed over heterogeneous hardware platform, using different number of cores. The results showed that DMTA outperforms DPA, presents load balance among processes and threads, and it is effective in current multicore architectures

Analysis of Errors of Profile Transformation Scale

A necessity to improve the quality of textile products and reduce production costs associated with losses of raw materials in the processing requires the development of automated quality inspection systems for all steps of textile production. Promising is the use of contactless methods of nondestructive testing based on the methods of vision.The object of research is a device to inspect the shape of textile packages by shadow projection method for monitoring in real time.A series of experiments and theoretical research are conducted aimed at the study of structural parameters of the device to inspect the shape of the packing by the shadow projection method, providing the required accuracy. On the basis of the mutual arrangement of the structural elements of the light source, camera shutter and inspected bobbin, the impact of each of them on the scale transformation error for inspection of the package shape of cross winding is defined.This result allows to select the mutual arrangement of design elements and to set their permissible variations of devices to inspect the package shape of cross winding by the shadow projection method.Inspection of package shape in the process of their developments will prevent the formation of defective packages. It will increase a percentage of defect packages and the loss of raw material in the textile industry, which ultimately will raise its efficiency

Learning fuzzy rules with evolutionary algorithms - An analytic approach

This paper provides an analytical approach to fuzzy rule base optimization. While most research in the area has been done experimentally, our theoretical considerations give new insights to the task. Using the symmetry that is inherent in our formulation, we show that the problem of finding an optimal rule base can be reduced to solving a set of quadratic equations that generically have a one dimensional solution space. This alternate problem specification can enable new approaches for rule base optimization.Jens Kroeske, Adam Ghandar, Zbigniew Michalewicz and Frank Neuman