Tools for mixed-criticality partitioned systems: partitioning algorithm and extensibility support

The development of mixed-criticality virtualized multicore systems poses new challenges that are being subject of active research work. There is an additional complexity: it is now required to identify a set of partitions, and allocate applications to partitions. In this job, a number of issues have to be considered, such as the criticality level of the application, security and dependability requirements, operating system used by the application, time requirements granularity, specific hardware needs, etc. MultiPARTES [6] toolset relies on Model Driven Engineering (MDE) [12], which is a suitable approach in this setting. In this paper, it is described the support provided for automatic system partitioning generation and toolset extensibility.

Feasibility assessment of the interactive use of a Monte Carlo algorithm in treatment planning for intraoperative electron radiation therapy

This work analysed the feasibility of using a fast, customized Monte Carlo (MC) method to perform accurate computation of dose distributions during pre- and intraplanning of intraoperative electron radiation therapy (IOERT) procedures. The MC method that was implemented, which has been integrated into a specific innovative simulation and planning tool, is able to simulate the fate of thousands of particles per second, and it was the aim of this work to determine the level of interactivity that could be achieved. The planning workflow enabled calibration of the imaging and treatment equipment, as well as manipulation of the surgical frame and insertion of the protection shields around the organs at risk and other beam modifiers. In this way, the multidisciplinary team involved in IOERT has all the tools necessary to perform complex MC dosage simulations adapted to their equipment in an efficient and transparent way. To assess the accuracy and reliability of this MC technique, dose distributions for a monoenergetic source were compared with those obtained using a general-purpose software package used widely in medical physics applications. Once accuracy of the underlying simulator was confirmed, a clinical accelerator was modelled and experimental measurements in water were conducted. A comparison was made with the output from the simulator to identify the conditions under which accurate dose estimations could be obtained in less than 3 min, which is the threshold imposed to allow for interactive use of the tool in treatment planning. Finally, a clinically relevant scenario, namely early-stage breast cancer treatment, was simulated with pre- and intraoperative volumes to verify that it was feasible to use the MC tool intraoperatively and to adjust dose delivery based on the simulation output, without compromising accuracy. The workflow provided a satisfactory model of the treatment head and the imaging system, enabling proper configuration of the treatment planning system and providing good accuracy in the dosage simulation.

Hybrid Monte Carlo dose algorithm for low energy X-rays intraoperative radiation therapy

Low energy X-rays Intra-Operative Radiation Therapy (XIORT) treatment delivered during surgery (ex: INTRABEAM, Carl Zeiss, and Axxent, Xoft) can benefit from accurate and fast dose prediction in a patient 3D volume.

Validation of a phase space determination algorithm for intraoperative radiation therapy

Monte-Carlo (MC) methods are a valuable tool for dosimetry in radiotherapy, including Intra-Operative Electron Radiotherapy (IOERT), since effects such as inhomogeneities or beam hardening may be realistically reproduced.

A genetic algorithm for slope stability analyses with concave slip surfaces using custom operators

Heuristic methods are popular tools to find critical slip surfaces in slope stability analyses. A new genetic algorithm (GA) is proposed in this work that has a standard structure but a novel encoding and generation of individuals with custom-designed operators for mutation and crossover that produce kinematically feasible slip surfaces with a high probability. In addition, new indices to assess the efficiency of operators in their search for the minimum factor of safety (FS) are proposed. The proposed GA is applied to traditional benchmark examples from the literature, as well as to a new practical example. Results show that the proposed GA is reliable, flexible and robust: it provides good minimum FS estimates that are not very sensitive to the number of nodes and that are very similar for different replications

Quality-optimization algorithm based on stochastic dynamic programming for MPEG DASH video streaming

In contrast to traditional push-based protocols, adaptive streaming techniques like Dynamic Adaptive Streaming over HTTP (DASH) fix attention on the client, who dynamically requests different-quality portions of the content to cope with a limited and variable bandwidth but aiming at maximizing the quality perceived by the user. Since DASH adaptation logic at the client is not covered by the standard, we propose a solution based on Stochastic Dynamic Programming (SDP) techniques to find the optimal request policies that guarantee the users' Quality of Experience (QoE). Our algorithm is evaluated in a simulated streaming session and is compared with other adaptation approaches. The results show that our proposal outperforms them in terms of QoE, requesting higher qualities on average.

An optimal yet fast pruning algorithm to reduce latency in multiview prediction structures

We propose a new algorithm for the design of prediction structures with low delay and limited penalty in the rate-distortion performance for multiview video coding schemes. This algorithm constitutes one of the elements of a framework for the analysis and optimization of delay in multiview coding schemes that is based in graph theory. The objective of the algorithm is to find the best combination of prediction dependencies to prune from a multiview prediction structure, given a number of cuts. Taking into account the properties of the graph-based analysis of the encoding delay, the algorithm is able to find the best prediction dependencies to eliminate from an original prediction structure, while limiting the number of cut combinations to evaluate. We show that this algorithm obtains optimum results in the reduction of the encoding latency with a lower computational complexity than exhaustive search alternatives.

Grouped sparsity algorithm for multichannel intracardiac ECG synchronization

In this paper, a new method is presented to ensure automatic synchronization of intracardiac ECG data, yielding a three-stage algorithm. We first compute a robust estimate of the derivative of the data to remove low-frequency perturbations. Then we provide a grouped-sparse representation of the data, by means of the Group LASSO, to ensure that all the electrical spikes are simultaneously detected. Finally, a post-processing step, based on a variance analysis, is performed to discard false alarms. Preliminary results on real data for sinus rhythm and atrial fibrillation show the potential of this approach.

YODA MAPK kinase kinase regulates a novel immunity pathway conferring broad-spectrum resistance to pathogens

Plant mitogen-activated protein kinase (MAPK) casca des transduce environmental molecular signals and developmental cues into cellular responses. Among these signals are the pathogen-associated molecular patterns (PAMPs) that upon recognition by plant pattern recognition receptors (PRR), including Receptor-Like Kinases (RLKs), activate MAPK cascades that regulate PAMP-triggered immunity responses (PTI).

Application of Independent Components Analysis with the JADE algorithm and NIR hyperspectral imaging for revealing food adulteration

In recent years, Independent Components Analysis (ICA) has proven itself to be a powerful signal-processing technique for solving the Blind-Source Separation (BSS) problems in different scientific domains. In the present work, an application of ICA for processing NIR hyperspectral images to detect traces of peanut in wheat flour is presented. Processing was performed without a priori knowledge of the chemical composition of the two food materials. The aim was to extract the source signals of the different chemical components from the initial data set and to use them in order to determine the distribution of peanut traces in the hyperspectral images. To determine the optimal number of independent component to be extracted, the Random ICA by blocks method was used. This method is based on the repeated calculation of several models using an increasing number of independent components after randomly segmenting the matrix data into two blocks and then calculating the correlations between the signals extracted from the two blocks. The extracted ICA signals were interpreted and their ability to classify peanut and wheat flour was studied. Finally, all the extracted ICs were used to construct a single synthetic signal that could be used directly with the hyperspectral images to enhance the contrast between the peanut and the wheat flours in a real multi-use industrial environment. Furthermore, feature extraction methods (connected components labelling algorithm followed by flood fill method to extract object contours) were applied in order to target the spatial location of the presence of peanut traces. A good visualization of the distributions of peanut traces was thus obtained

Logarithmical hopping encoding: a low computational complexity algorithm for image compression

LHE (logarithmical hopping encoding) is a computationally efficient image compression algorithm that exploits the Weber–Fechner law to encode the error between colour component predictions and the actual value of such components. More concretely, for each pixel, luminance and chrominance predictions are calculated as a function of the surrounding pixels and then the error between the predictions and the actual values are logarithmically quantised. The main advantage of LHE is that although it is capable of achieving a low-bit rate encoding with high quality results in terms of peak signal-to-noise ratio (PSNR) and image quality metrics with full-reference (FSIM) and non-reference (blind/referenceless image spatial quality evaluator), its time complexity is O( n) and its memory complexity is O(1). Furthermore, an enhanced version of the algorithm is proposed, where the output codes provided by the logarithmical quantiser are used in a pre-processing stage to estimate the perceptual relevance of the image blocks. This allows the algorithm to downsample the blocks with low perceptual relevance, thus improving the compression rate. The performance of LHE is especially remarkable when the bit per pixel rate is low, showing much better quality, in terms of PSNR and FSIM, than JPEG and slightly lower quality than JPEG-2000 but being more computationally efficient.

Functional characterization of YODA, a mitogen-activated protein kinase kinase kinase (MAP3K) that regulates a novel innate immunity pathway in Arabidopsis thaliana

Las cascadas de señalización mediadas por proteína quinasas activadas por mitógeno (MAP quinasas) son capaces de integrar y transducir señales ambientales en respuestas celulares. Entre estas señales se encuentran los PAMPs/MAMPs (Pathogen/Microbe-Associated Molecular Patterns), que son moléculas de patógenos o microorganismos, o los DAMPs (Damaged-Associated Molecular Patterns), que son moléculas derivadas de las plantas producidas en respuesta a daño celular. Tras el reconocimiento de los PAMPs/DAMPs por receptores de membrana denominados PRRs (Pattern Recognition Receptors), como los receptores con dominio quinasa (RLKs) o los receptores sin dominio quinasa (RLPs), se activan respuestas moleculares, incluidas cascadas de MAP quinasas, que regulan la puesta en marcha de la inmunidad activada por PAMPs (PTI). Esta Tesis describe la caracterización funcional de la MAP quinasa quinasa quinasa (MAP3K) YODA (YDA), que actúa como un regulador clave de la PTI en Arabidopsis. Se ha descrito previamente que YDA controla varios procesos de desarrollo, como la regulación del patrón estomático, la elongación del zigoto y la arquitectura floral. Hemos caracterizado un alelo mutante hipomórfico de YDA (elk2 o yda11) que presenta una elevada susceptibilidad a patógenos biótrofos y necrótrofos. Notablemente, plantas que expresan una forma constitutivamente activa de YDA (CA-YDA), con una deleción en el dominio N-terminal, presentan una resistencia de amplio espectro frente a diferentes tipos de patógenos, incluyendo hongos, oomicetos y bacterias, lo que indica que YDA juega un papel importante en la regulación de la resistencia de las plantas a patógenos. Nuestros datos indican que esta función es independiente de las respuestas inmunes mediadas por los receptores previamente caracterizados FLS2 y CERK1, que reconocen los PAMPs flg22 y quitina, respectivamente, y que están implicados en la resistencia de Arabidopsis frente a bacterias y hongos. Hemos demostrado que YDA controla la resistencia frente al hongo necrótrofo Plectosphaerella cucumerina y el patrón estomático mediante su interacción genética con la RLK ERECTA (ER), un PRR implicado en la regulación de estos procesos. Por el contrario, la interacción genética entre ER y YDA en la regulación de otros procesos de desarrollo es aditiva en lugar de epistática. Análisis genéticos indicaron que MPK3, una MAP quinasa que funciona aguas abajo de YDA en el desarrollo estomático, es un componente de la ruta de señalización mediada por YDA para la resistencia frente a P. cucumerina, lo que sugiere que el desarrollo de las plantas y la PTI comparten el módulo de transducción de MAP quinasas asociado a YDA. Nuestros experimentos han revelado que la resistencia mediada por YDA es independiente de las rutas de señalización reguladas por las hormonas de defensa ácido salicílico, ácido jasmónico, ácido abscísico o etileno, y también es independiente de la ruta de metabolitos secundarios derivados del triptófano, que están implicados en inmunidad vegetal. Además, hemos demostrado que respuestas asociadas a PTI, como el aumento en la concentración de calcio citoplásmico, la producción de especies reactivas de oxígeno, la fosforilación de MAP quinasas y la expresión de genes de defensa, no están afectadas en el mutante yda11. La expresión constitutiva de la proteína CA-YDA en plantas de Arabidopsis no provoca un aumento de las respuestas PTI, lo que sugiere la existencia de mecanismos de resistencia adicionales regulados por YDA que son diferentes de los regulados por FLS2 y CERK1. En línea con estos resultados, nuestros datos transcriptómicos revelan una sobre-representación en plantas CA-YDA de genes de defensa que codifican, por ejemplo, péptidos antimicrobianos o reguladores de muerte celular, o proteínas implicadas en la biogénesis de la pared celular, lo que sugiere una conexión potencial entre la composición e integridad de la pared celular y la resistencia de amplio espectro mediada por YDA. Además, análisis de fosfoproteómica indican la fosforilación diferencial de proteínas relacionadas con la pared celular en plantas CA-YDA en comparación con plantas silvestres. El posible papel de la ruta ER-YDA en la regulación de la integridad de la pared celular está apoyado por análisis bioquímicos y glicómicos de las paredes celulares de plantas er, yda11 y CA-YDA, que revelaron cambios significativos en la composición de la pared celular de estos genotipos en comparación con la de plantas silvestres. En resumen, nuestros datos indican que ER y YDA forman parte de una nueva ruta de inmunidad que regula la integridad de la pared celular y respuestas defensivas, confiriendo una resistencia de amplio espectro frente a patógenos. ABSTRACT Plant mitogen-activated protein kinase (MAPK) cascades transduce environmental signals and developmental cues into cellular responses. Among these signals are the pathogen- or microbe-associated molecular patterns (PAMPs or MAMPs) and the damage-associated molecular patterns (DAMPs). These PAMPs/DAMPs, upon recognition by plant pattern recognition receptors (PRRs), such as Receptor-Like Kinases (RLKs) and Receptor-Like Proteins (RLPs), activate molecular responses, including MAPK cascades, which regulate the onset of PAMP-triggered immunity (PTI). This Thesis describes the functional characterization of the MAPK kinase kinase (MAP3K) YODA (YDA) as a key regulator of Arabidopsis PTI. YDA has been previously described to control several developmental processes, such as stomatal patterning, zygote elongation and inflorescence architecture. We characterized a hypomorphic, non-embryo lethal mutant allele of YDA (elk2 or yda11) that was found to be highly susceptible to biotrophic and necrotrophic pathogens. Remarkably, plants expressing a constitutive active form of YDA (CA-YDA), with a deletion in the N-terminal domain, showed broad-spectrum resistance to different types of pathogens, including fungi, oomycetes and bacteria, indicating that YDA plays a relevant function in plant resistance to pathogens. Our data indicated that this function is independent of the immune responses regulated by the well characterized FLS2 and CERK1 RLKs, which are the PRRs recognizing flg22 and chitin PAMPs, respectively, and are required for Arabidopsis resistance to bacteria and fungi. We demonstrate that YDA controls resistance to the necrotrophic fungus Plectosphaerella cucumerina and stomatal patterning by genetically interacting with ERECTA (ER) RLK, a PRR involved in regulating these processes. In contrast, the genetic interaction between ER and YDA in the regulation of other ER-associated developmental processes was additive, rather than epistatic. Genetic analyses indicated that MPK3, a MAP kinase that functions downstream of YDA in stomatal development, also regulates plant resistance to P. cucumerina in a YDA-dependent manner, suggesting that the YDA-associated MAPK transduction module is shared in plant development and PTI. Our experiments revealed that YDA-mediated resistance was independent of signalling pathways regulated by defensive hormones like salicylic acid, jasmonic acid, abscisic acid or ethylene, and of the tryptophan-derived metabolites pathway, which are involved in plant immunity. In addition, we showed that PAMP-mediated PTI responses, such as the increase of cytoplasmic Ca2+ concentration, reactive oxygen species (ROS) burst, MAPK phosphorylation, and expression of defense-related genes are not impaired in the yda11 mutant. Furthermore, the expression of CA-YDA protein does not result in enhanced PTI responses, further suggesting the existence of additional mechanisms of resistance regulated by YDA that differ from those regulated by the PTI receptors FLS2 and CERK1. In line with these observations, our transcriptomic data revealed the over-representation in CA-YDA plants of defensive genes, such as those encoding antimicrobial peptides and cell death regulators, and genes encoding cell wall-related proteins, suggesting a potential link between plant cell wall composition and integrity and broad spectrum resistance mediated by YDA. In addition, phosphoproteomic data revealed an over-representation of genes encoding wall-related proteins in CA-YDA plants in comparison with wild-type plants. The putative role of the ER-YDA pathway in regulating cell wall integrity was further supported by biochemical and glycomics analyses of er, yda11 and CA-YDA cell walls, which revealed significant changes in the cell wall composition of these genotypes compared with that of wild-type plants. In summary, our data indicate that ER and YDA are components of a novel immune pathway that regulates cell wall integrity and defensive responses, which confer broad-spectrum resistance to pathogens.

The Balanced Cross-Layer Design Routing Algorithm in Wireless Sensor Networks Using Fuzzy Logic

Recently, the cross-layer design for the wireless sensor network communication protocol has become more and more important and popular. Considering the disadvantages of the traditional cross-layer routing algorithms, in this paper we propose a new fuzzy logic-based routing algorithm, named the Balanced Cross-layer Fuzzy Logic (BCFL) routing algorithm. In BCFL, we use the cross-layer parameters’ dispersion as the fuzzy logic inference system inputs. Moreover, we give each cross-layer parameter a dynamic weight according the value of the dispersion. For getting a balanced solution, the parameter whose dispersion is large will have small weight, and vice versa. In order to compare it with the traditional cross-layer routing algorithms, BCFL is evaluated through extensive simulations. The simulation results show that the new routing algorithm can handle the multiple constraints without increasing the complexity of the algorithm and can achieve the most balanced performance on selecting the next hop relay node. Moreover, the Balanced Cross-layer Fuzzy Logic routing algorithm can adapt to the dynamic changing of the network conditions and topology effectively.

Deciduous tree reconstruction algorithm based on cylinder fitting from mobile terrestrial laser scanned point clouds

Vector reconstruction of objects from an unstructured point cloud obtained with a LiDAR-based system (light detection and ranging) is one of the most promising methods to build three dimensional models of orchards. The cylinder fitting method for woody structure reconstruction of leafless trees from point clouds obtained with a mobile terrestrial laser scanner (MTLS) has been analysed. The advantage of this method is that it performs reconstruction in a single step. The most time consuming part of the algorithm is generation of the cylinder direction, which must be recalculated at the inclusion of each point in the cylinder. The tree skeleton is obtained at the same time as the cluster of cylinders is formed. The method does not guarantee a unique convergence and the reconstruction parameter values must be carefully chosen. A balanced processing of clusters has also been defined which has proven to be very efficient in terms of processing time by following the hierarchy of branches, predecessors and successors. The algorithm was applied to simulated MTLS of virtual orchard models and to MTLS data of real orchards. The constraints applied in the method have been reviewed to ensure better convergence and simpler use of parameters. The results obtained show a correct reconstruction of the woody structure of the trees and the algorithm runs in linear logarithmic time

Design Parameter Analysis of Point Absorber WEC via an Evolutionary-Algorithm-Based Dimensioning Tool

Wave energy conversion has an essential difference from other renewable energies since the dependence between the devices design and the energy resource is stronger. Dimensioning is therefore considered a key stage when a design project of Wave Energy Converters (WEC) is undertaken. Location, WEC concept, Power Take-Off (PTO) type, control strategy and hydrodynamic resonance considerations are some of the critical aspects to take into account to achieve a good performance. The paper proposes an automatic dimensioning methodology to be accomplished at the initial design project stages and the following elements are described to carry out the study: an optimization design algorithm, its objective functions and restrictions, a PTO model, as well as a procedure to evaluate the WEC energy production. After that, a parametric analysis is included considering different combinations of the key parameters previously introduced. A variety of study cases are analysed from the point of view of energy production for different design-parameters and all of them are compared with a reference case. Finally, a discussion is presented based on the results obtained, and some recommendations to face the WEC design stage are given.