The IoT has made it possible to connect and control more devices than ever before, opening up new avenues for efficiency and creativity. However, new problems have emerged as a result of this explosion of linked devic...
详细信息
A new electroencephalographic current density reconstruction method is introduced using a physiologically based nonlinear modeling that describes better the dynamic behavior of the neural activity. In addition, time-v...
详细信息
A new electroencephalographic current density reconstruction method is introduced using a physiologically based nonlinear modeling that describes better the dynamic behavior of the neural activity. In addition, time-variant parameters are considered into the model to capture the dynamics for normal and pathological states measured from signals. The method is implemented by Unscented Kalman filtering approach. The performance of the new method is evaluated (in terms of mean square error) by application to simulated EEG data over several noise conditions, and a considerable improvement over linear estimation approaches is found.
Epilepsy is a brain pathology that affects approximately 40 million people in the world. The most utilized clinical test for epilepsy diagnose is the electroencephalogram (EEG). For this reason, nowadays are being dev...
详细信息
Epilepsy is a brain pathology that affects approximately 40 million people in the world. The most utilized clinical test for epilepsy diagnose is the electroencephalogram (EEG). For this reason, nowadays are being developed multiple tools devised for automatic seizure detection on EEG signals. In this work, several approaches of TFR estimation for detection of epileptic events in EEG recordings are compared. Parametric (stochastic evolving and local estimation) TFR estimators as well as non-parametric (STFT, SPWV and CWT) are under study. Comparison is made according with the achieved performance using a recently proposed methodology for TFR based classification. Results show similar outcomings with all approaches for TFR estimation, achieving accuracy rates from 96 to 99%. Best performance was found for STFT and STTVAR approaches for TFR estimation.
The reuse of software components is an approach that exploits experience and capitalized knowledge during software development. Software reuse aims to optimize the cost and time of developing high quality software. Th...
详细信息
The reuse of software components is an approach that exploits experience and capitalized knowledge during software development. Software reuse aims to optimize the cost and time of developing high quality software. The efficient and relevant reuse is the one that allows reusing components of high heterogeneity. We exploit this concept of reusing software components to software process modeling; therefore, we use the concept of software process model component (SPMC). This paper presents an overview of environments for reusing software process model components, and advances the bases of a new approach for the modeling software process based on components. Unlike the existing environments, our approach focuses in the one hand, on the strong heterogeneity of software process model components, and in the other hand, on the diversity of their origin. The advantage of our approach is that it applies a reverse engineering technique for the components that are not necessarily created in the system, but that may come from external software process models; also, from process models not oriented components.
For problem solving in the artificial intelligence, this paper presents a new hyper-distributed hyper-parallel approach based on the bifurcations and synchronizations of the hierarchical distributed chaotic dynamic sy...
详细信息
For problem solving in the artificial intelligence, this paper presents a new hyper-distributed hyper-parallel approach based on the bifurcations and synchronizations of the hierarchical distributed chaotic dynamic systems. By using Chua's circuits arrays, the realization of the hyper-distributed hyper-parallel heuristic algorithms for real-time search of any implicit AND/OR graph is discussed. The approach not only combines the advantages of both the traditional sequential symbolic logic and the conventional neural network approaches, but also overcomes their drawbacks in many respects.< >
This book constitutes the refereed proceedings of the 9th VLDB Workshop on Secure Data Management held in Istanbul, Turkey, in August 27, 2012.;The 12 revised full papers presented were carefully reviewed and selected...
详细信息
ISBN:
(数字)9783642328732
ISBN:
(纸本)9783642328725
This book constitutes the refereed proceedings of the 9th VLDB Workshop on Secure Data Management held in Istanbul, Turkey, in August 27, 2012.;The 12 revised full papers presented were carefully reviewed and selected from 22 submissions. The papers are organized in topical sections on privacy protection, access control, secure storage on the cloud, and trust on the Web.
暂无评论