Global slowing of network oscillations in mouse neocortex by diazepam

SCHEFFZUK, C. , KUKUSHKA, V. , VYSSOTSKI, A. L. , DRAGUHN, A. , TORT, A. B. L. , BRANKACK, J. . Global slowing of network oscillations in mouse neocortex by diazepam. Neuropharmacology , v. 65, p. 123-133, 2013.

Estudo e implementação de algoritmos inteligentes para detecção e classificação de falhas na medição de gás natural

This master dissertation presents the study and implementation of inteligent algorithms to monitor the measurement of sensors involved in natural gas custody transfer processes. To create these algoritmhs Artificial Neural Networks are investigated because they have some particular properties, such as: learning, adaptation, prediction. A neural predictor is developed to reproduce the sensor output dynamic behavior, in such a way that its output is compared to the real sensor output. A recurrent neural network is used for this purpose, because of its ability to deal with dynamic information. The real sensor output and the estimated predictor output work as the basis for the creation of possible sensor fault detection and diagnosis strategies. Two competitive neural network architectures are investigated and their capabilities are used to classify different kinds of faults. The prediction algorithm and the fault detection classification strategies, as well as the obtained results, are presented

Um sistema para gestão do conhecimento em ameaças, vulnerabilidades e seus efeitos

Attacks to devices connected to networks are one of the main problems related to the confidentiality of sensitive data and the correct functioning of computer systems. In spite of the availability of tools and procedures that harden or prevent the occurrence of security incidents, network devices are successfully attacked using strategies applied in previous events. The lack of knowledge about scenarios in which these attacks occurred effectively contributes to the success of new attacks. The development of a tool that makes this kind of information available is, therefore, of great relevance. This work presents a support system to the management of corporate security for the storage, retrieval and help in constructing attack scenarios and related information. If an incident occurs in a corporation, an expert must access the system to store the specific attack scenario. This scenario, made available through controlled access, must be analyzed so that effective decisions or actions can be taken for similar cases. Besides the strategy used by the attacker, attack scenarios also exacerbate vulnerabilities in devices. The access to this kind of information contributes to an increased security level of a corporation's network devices and a decreased response time to occurring incidents

Desenvolvimento de perfis aerodinâmicos a partir de suas características utilizando redes neurais artificiais

One of the current major concerns in engineering is the development of aircrafts that have low power consumption and high performance. So, airfoils that have a high value of Lift Coefficient and a low value for the Drag Coefficient, generating a High-Efficiency airfoil are studied and designed. When the value of the Efficiency increases, the aircraft s fuel consumption decreases, thus improving its performance. Therefore, this work aims to develop a tool for designing of airfoils from desired characteristics, as Lift and Drag coefficients and the maximum Efficiency, using an algorithm based on an Artificial Neural Network (ANN). For this, it was initially collected an aerodynamic characteristics database, with a total of 300 airfoils, from the software XFoil. Then, through the software MATLAB, several network architectures were trained, between modular and hierarchical, using the Back-propagation algorithm and the Momentum rule. For data analysis, was used the technique of cross- validation, evaluating the network that has the lowest value of Root Mean Square (RMS). In this case, the best result was obtained for a hierarchical architecture with two modules and one layer of hidden neurons. The airfoils developed for that network, in the regions of lower RMS, were compared with the same airfoils imported into the software XFoil