In this paper, we show and utilize new results on the relationship between passivity, zero dynamics and stable dynamic invertibility of linear parameter-varying (LPV) systems. Furthermore, an optimization-based system...
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ISBN:
(数字)9781728113982
ISBN:
(纸本)9781728113999
In this paper, we show and utilize new results on the relationship between passivity, zero dynamics and stable dynamic invertibility of linear parameter-varying (LPV) systems. Furthermore, an optimization-based systematic passivity analysis procedure and a passivating output projection are proposed for asymptotically stable rational LPV systems in the linear fractional representation (LFR) form having at least as many independent output signals as input signals. The storage function is searched in a quadratic form with a symmetric rational parameter-dependent matrix. In order to form a square system and then to satisfy the Kalman-Yakubovich- Popov (KYP) properties, a parameter-dependent output projection matrix is searched in the LFR form. The nonlinear parameter dependence from the linear matrix inequality (LMI) and equality (LME) conditions provided by the KYP lemma is factorized out using the linear fractional transformation (LFT). Then, Finsler's lemma and affine annihilators are used to relax the sufficient affine parameter-dependent LMI and LME conditions. As an application example, a stable system inversion is addressed and demonstrated on a benchmark rational LPV model.
Denial-of-service (DOS) attacks are the most frequent attacks in Cloud. Usually this type of attack consists in sending a large number of requests that will overwhelm the functioning of Cloud. DOS attack implies IP sp...
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ISBN:
(纸本)9781538623510;9781538623503
Denial-of-service (DOS) attacks are the most frequent attacks in Cloud. Usually this type of attack consists in sending a large number of requests that will overwhelm the functioning of Cloud. DOS attack implies IP spoofing because each request needs to be different. So the server will consume its resources and it will not be able to reply to a legitimate connection request. SYN floods are the second most common type of DOS attack for Cloud in the last 3 years. SYN floods exploit the flaws in TCP three-way handshake procedures. The attacker sends multiple SYN requests from a spoofed IP address. The server will allocate all the resources needed without receiving any ACK from the attacker. We propose an approach of solving this type of attack for Big Data in Cloud while respecting the Service Level Agreement (SLA) and show that the improvement is considerable.
This paper discusses dynamic properties of discrete Volterra equations of convolution type. The asymptotic separation of solutions is studied. More precisely, a polynomial lower bound for the norm of differences betwe...
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This paper discusses dynamic properties of discrete Volterra equations of convolution type. The asymptotic separation of solutions is studied. More precisely, a polynomial lower bound for the norm of differences between two different solutions of discrete Volterra equations of convolution type is presented. We apply this result to the theory of fractional difference equations.
Memetic Algorithms (MAs) are a class of stochastic global search heuristics in which Evolutionary Algorithms (EAs) - based approaches are combined usually with heuristic local searches. This hybridization is meant to ...
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Memetic Algorithms (MAs) are a class of stochastic global search heuristics in which Evolutionary Algorithms (EAs) - based approaches are combined usually with heuristic local searches. This hybridization is meant to reach solutions that would otherwise be unreachable by evolution or a local method alone. In this work, we propose three Local Search (LS) algorithms for hybridization with an existing Evolutionary Algorithm with Pareto ranking in order to define biological intelligence using the concepts of useful and utility and therefore to zoom on the basin of attraction of promising realistic solutions. Our experimental results with these memetic algorithms in the game of Checkers show how we can learn the organization of behaviors into paths of behaviors of different lengths and frequencies and then reveal the true nature of these behaviors.
The massive student participation in computer Supported Collaborative Learning (CSCL) sessions from online classrooms requires intense tutor engagement to track and evaluate individual student participation. In this s...
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The preliminary research on stationary sign language hand gesture recognition with use of convolutional neural networks is presented. Three tests are presented that differ in number of gesture types, that is, by class...
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Development of new technologies has resulted in the significant expansion of biological research, among which studies in the area of genomics, transcriptomics, proteomics, and metabolomics are the leading ones. In the...
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Development of new technologies has resulted in the significant expansion of biological research, among which studies in the area of genomics, transcriptomics, proteomics, and metabolomics are the leading ones. In the majority of omics studies, the goal is to identify reliable molecular biomarkers and pathways associated with the examined process. In almost all cases, a list of differentially expressed genes or proteins is constructed, which is not easy to obtain for some experimental designs. In our work, we mainly focus on the experiments with small sample size. The goal was to determine the robust proteomic signature of radiation exposure in the mouse model. Our selection algorithm combines mathematical modelling of signal and its fold change distributions with the comprehensive effect size analysis. Thanks to the data-driven automated thresholding of the protein absolute or relative (fold change) expressions, and Cohens effect size based filters, the obtained proteomic signature demonstrated a higher level of consistency and functional coherency. The additional, intuitively expected, signalling pathways were identified when compared to the standard statistical approach.
Microgrid control becomes more and more developed with the application of this concept on a larger scale. This paper defines the modern microgrid concept and evaluates the possible architectures and control hierarchy....
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The detection, localization and evaluation of small flooded areas can contribute to decrease the economical damages of such disasters. The cheapest and most accurate method is to segment the aerial images taken from U...
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The detection, localization and evaluation of small flooded areas can contribute to decrease the economical damages of such disasters. The cheapest and most accurate method is to segment the aerial images taken from UAV. In this paper, we propose a new method for detection of regions of interest, like flooding in rural areas, using Generative Adversarial Networks (GAN) and Graphics Processing Units (GPU). The classical GPU is used to create, by parallel calculation of textural features, extracted from the co-occurrence matrix, the supervised mask of flood segmentation in the images from the learning set. Based on these images and their associated real masks, the weights of the generator and discriminator are established. A set of 40 images were used for the learning phase and another set of 60 images were used for method validation. The results demonstrate that the proposed method provide a high accuracy and robustness, comparing with other papers for flooding evaluation. Even if it is a relative long time to learn the GAN, in the operational phase the time for image segmentation process is very short.
Today's industry is facing an increased need for implementing intelligent manufacturing solutions, capable of integrating existing machinery with new technologies. Current solutions do not provide support for anal...
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Today's industry is facing an increased need for implementing intelligent manufacturing solutions, capable of integrating existing machinery with new technologies. Current solutions do not provide support for analyzing vast amounts of data. Also, implementation of cloud architectures proved inappropriate for real-time or near real-time processing and control because of the network latency. Under these considerations, the new paradigm of fog computing provides promising characteristics enabling greater scalability, fast reaction time and increasing security through a local private processing cloud structure. This paper evaluates the integration capabilities between existing technologies with new devices for seamless integration of the fog computing paradigm and provides an architecture solution for this upgrade.
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