Noise-agnostic adaptive image filtering without training references on an evolvable hardware platform

One of the main concerns of evolvable and adaptive systems is the need of a training mechanism, which is normally done by using a training reference and a test input. The fitness function to be optimized during the evolution (training) phase is obtained by comparing the output of the candidate systems against the reference. The adaptivity that this type of systems may provide by re-evolving during operation is especially important for applications with runtime variable conditions. However, fully automated self-adaptivity poses additional problems. For instance, in some cases, it is not possible to have such reference, because the changes in the environment conditions are unknown, so it becomes difficult to autonomously identify which problem requires to be solved, and hence, what conditions should be representative for an adequate re-evolution. In this paper, a solution to solve this dependency is presented and analyzed. The system consists of an image filter application mapped on an evolvable hardware platform, able to evolve using two consecutive frames from a camera as both test and reference images. The system is entirely mapped in an FPGA, and native dynamic and partial reconfiguration is used for evolution. It is also shown that using such images, both of them being noisy, as input and reference images in the evolution phase of the system is equivalent or even better than evolving the filter with offline images. The combination of both techniques results in the completely autonomous, noise type/level agnostic filtering system without reference image requirement described along the paper.

Evaluation, energy optimization, and spectrum analysis of an artificial noise technique to improve CWSN security

This paper presents the security evaluation, energy consumption optimization, and spectrum scarcity analysis of artificial noise techniques to increase physical-layer security in Cognitive Wireless Sensor Networks (CWSNs). These techniques introduce noise into the spectrum in order to hide real information. Nevertheless, they directly affect two important parameters in Cognitive Wireless Sensor Networks (CWSNs), energy consumption and spectrum utilization. Both are affected because the number of packets transmitted by the network and the active period of the nodes increase. Security evaluation demonstrates that these techniques are effective against eavesdropper attacks, but also optimization allows for the implementation of these approaches in low-resource networks such as Cognitive Wireless Sensor Networks. In this work, the scenario is formally modeled and the optimization according to the simulation results and the impact analysis over the frequency spectrum are presented.

Noise-induced attractor annihilation in the delayed feedback logistic map

We study dynamics of the bistable logistic map with delayed feedback, under the influence of white Gaussian noise and periodic modulation applied to the variable. This system may serve as a model to describe population dynamics under finite resources in noisy environment with seasonal fluctuations. While a very small amount of noise has no effect on the global structure of the coexisting attractors in phase space, an intermediate noise totally eliminates one of the attractors. Slow periodic modulation enhances the attractor annihilation.

Evaluation of noise environments during daily activities of university students

Noise conditions specifically in areas inside university facilities and its impact on the quality of life of university students aretopics that have received little attention. In this paper, a study of the noise conditions in which university students of various institutions in Madrid carry out their daily studies. A representative number of measurements were carried out using noise dosemeters and dataloggers in order to evaluate the levels of noise, noise dose and exposure to noise during study period and extracurricular activities. The results obtained in these measurements were compared with the recommendations given by current environmental noise regulations.This paper was complemented with a survey to get to know how students perceive the exposure to noise inuniversity environments.

Aeroacoustic noise prediction in high speed trains due to attached and detached flow

This paper aims to set out the influence of the flow field around high speed trains in open field. To achieve this parametric analysis of the sound pressure inside the train was performed. Three vibroacoustic models of a characteristic train section are used to predict the noise inside the train in open field by using finite element method FEM, boundary element method (BEM) and statistical energy analysis (SEA) depending on the frequency range of analysis. The turbulent boundary layer excitation is implemented as the only airborne noise source, in order to focus on the study of the attached and detached flow in the surface of the train. The power spectral densities of the pressure fluctuation in the train surface proposed by [Cockburn and Roberson 1974, Rennison et al. 2009] are applied on the exterior surface of the structural subsystems in the vibroacoustic models. An increase in the sound pressure level up to10 dB can be appreciated due to the detachment of the flow around the train. These results highlight the importance to determine the detached regions prediction, making critical the airborne noise due to turbulent boundary layer.

Madera termo-tratada de frondosas para uso estructural

La madera termotratada es madera modificada mediante un proceso térmico a elevadas temperaturas que le proporciona mayor estabilidad dimensional y durabilidad sin incorporar productos químicos perjudiciales para el medio ambiente. Hasta el momento se ha aplicado fundamentalmente a madera de coniferas por motivos económicos, siendo su uso más habitual en ambientes exteriores o de elevada humedad, como elementos de revestimiento no estructurales, carpinterías, mobiliario de jardín, etc. En la presente tesis se estudia la viabilidad de la madera termotratada de frondosas para uso estructural, en particular fresno (Fraxinus excelsior L) y haya (Fagus sylvatica L). Con este fin, y considerando que el termotratamiento modifica la estructura interna de la madera resultando en un nuevo material, se realizan estudios experimentales y numéricos para su caracterización. Estos trabajos se desarrollan bajo el enfoque de la Mecánica de Fractura debido a la pérdida de resistencia y aumento de fragilidad que presenta el material, especialmente a tracción perpendicular a las fibras. Así mismo, se lleva a cabo una recopilación de las bases, fundamentos y metodologías de esta teoría aplicados a madera sin tratar y otros materiales debido a la inexistencia de este tipo de estudios en madera termotratada. De igual manera se realiza un programa de caracterización mecánica del material para determinar sus propiedades elásticas considerando un modelo ortótropo, necesarios en la investigación del comportamiento a fractura. El trabajo derivó en el desarrollo de un nuevo método de ensayo para la determinación multiparamétrica a partir de un sólo espécimen, proporcionando resultados mucho más robustos que los obtenidos con la metodología convencional de ensayos. En base a los trabajos realizados, considerando las limitaciones de resistencia y fragilidad, así como la dudosa aplicabilidad de las normativas existentes en madera sin tratar, se aconseja no utilizar tratamientos térmicos intensos en elementos estructurales primarios. Se propone su aplicación en elementos secundarios, de manera que un posible colapso no implique una pérdida de fiabilidad global de la estructura. Se estudia la viabilidad de un panel sandwich innovador y ecológico para fachadas expuesto a cargas de viento, compuesto de madera termotratada en las caras y panel aislante de fibras de madera con función estructural en el alma. Esta investigación se desarrolló dentro del proyecto de investigación Europeo "Holiwood", Holistic implementation of European thermal treated hardwood (TMT) in the sector of construction industry and noise protection by sustainable, knowledge-based and value added products, perteneciente al sexto Programa Marco. ABSTRACT Hcat-trcatcd wood is modified wood by a thermal process at high temperatures which provides greater dimensional stability and durability without adding harmful chemicals to the environment. It has been mainly applied to softwoods due mainly to economical reasons, being its most common use outdoors or in high humidity environments, as non-structural elements, furniture, etc. The present Thesis studies the feasibility of heat-treated hardwoods for structural uses, particularly ash (Fraxinus excelsior L) and beech (Fagus sylvatica L). To this end, and considering that heat treatment modifies the internal structure of the wood resulting in a new material, experimental and numerical studies are performed for its characterization. This investigation is developed under the approach of Fracture Mechanics due to the loss of strength and the increase in brittlcncss of the material, especially in tension perpendicular to the grain. Likewise, it holds a collection of the bases, foundations and methodologies of this theory applied to untreated wood and other materials due to the lack of such studies in heat-treated wood. In addition, studies for the mechanical characterization of the material are performed in order to determine the elastic properties considering an orthotropic model. This work is necessary in the investigation of the fracture behavior. It led to the development of a new test method for multiparameter determination by using just a single specimen, providing much more robust results than those obtained with conventional test methodology. Based on this investigation, and considering the limitations of strength and brittleness, and the questionable applicability of existing standards for untreated wood, it is advised not to use intense heat treatments in primary structural elements. It is proposed the application to secondary elements, so that a possible collapse does not involve a loss of overall reliability of the structure. It is studied the feasibility of an innovative and ecological sandwich panel for facades exposed to wind loads, composed by heat-treated wood faces and insulating wood fiberboard with structural function in the core. This investigación was developed within the European research project "Holiwood", Holistic implementation of European thermal treated hardwood (TMT) in the sector of construction industry and noise protection by sustainable, knowledge-based and value added products, of the Sixth Framework Program.

A clustering technique for partial discharge and noise sources identification in power cables by means of waveform parameters

On-line partial discharge (PD) measurements have become a common technique for assessing the insulation condition of installed high voltage (HV) insulated cables. When on-line tests are performed in noisy environments, or when more than one source of pulse-shaped signals are present in a cable system, it is difficult to perform accurate diagnoses. In these cases, an adequate selection of the non-conventional measuring technique and the implementation of effective signal processing tools are essential for a correct evaluation of the insulation degradation. Once a specific noise rejection filter is applied, many signals can be identified as potential PD pulses, therefore, a classification tool to discriminate the PD sources involved is required. This paper proposes an efficient method for the classification of PD signals and pulse-type noise interferences measured in power cables with HFCT sensors. By using a signal feature generation algorithm, representative parameters associated to the waveform of each pulse acquired are calculated so that they can be separated in different clusters. The efficiency of the clustering technique proposed is demonstrated through an example with three different PD sources and several pulse-shaped interferences measured simultaneously in a cable system with a high frequency current transformer (HFCT).

Neuronal calcium sparks and intracellular calcium “noise”

Intracellular calcium ions are involved in many forms of cellular function. To accommodate so many control functions, a complex spatiotemporal organization of calcium signaling has developed. In both excitable and nonexcitable cells, calcium signaling was found to fluctuate. Sudden localized increases in the intracellular calcium concentration—or calcium sparks—were found in heart, striated and smooth muscle, Xenopus Laevis oocytes, and HeLa and P12 cells. In the nervous system, intracellular calcium ions were found important in key processes such as transmitter release, repetitive firing, and gene expression. Hence, we examined whether calcium sparks also exist in neurons. Using confocal laser-scanning microscopy and fluorescent probes, we found that calcium sparks exist in two types of neuronal preparations: the presynaptic boutons of the lizard neuromuscular junction and rat hippocampal neurons in cell culture. Control experiments exclude the possibility that these calcium sparks originate from instrumental or biological artifacts. Calcium sparks seem to be just the tip of the iceberg of a more general phenomenon of intracellular calcium “noise.” We speculate that calcium sparks and calcium noise may be of key importance in calcium signaling in the nervous system.

Perceptual learning reflects external noise filtering and internal noise reduction through channel reweighting

To investigate the nature of plasticity in the adult visual system, perceptual learning was measured in a peripheral orientation discrimination task with systematically varying amounts of external (environmental) noise. The signal contrasts required to achieve threshold were reduced by a factor or two or more after training at all levels of external noise. The strong quantitative regularities revealed by this novel paradigm ruled out changes in multiplicative internal noise, changes in transducer nonlinearites, and simple attentional tradeoffs. Instead, the regularities specify the mechanisms of perceptual learning at the behavioral level as a combination of external noise exclusion and stimulus enhancement via additive internal noise reduction. The findings also constrain the neural architecture of perceptual learning. Plasticity in the weights between basic visual channels and decision is sufficient to account for perceptual learning without requiring the retuning of visual mechanisms.

Noise in neurons is message dependent

Neuronal responses are conspicuously variable. We focus on one particular aspect of that variability: the precision of action potential timing. We show that for common models of noisy spike generation, elementary considerations imply that such variability is a function of the input, and can be made arbitrarily large or small by a suitable choice of inputs. Our considerations are expected to extend to virtually any mechanism of spike generation, and we illustrate them with data from the visual pathway. Thus, a simplification usually made in the application of information theory to neural processing is violated: noise is not independent of the message. However, we also show the existence of error-correcting topologies, which can achieve better timing reliability than their components.

Very intense pulse in the groundwater flow in fissurized-porous stratum

An asymptotic solution is obtained corresponding to a very intense pulse: a sudden strong increase and fast subsequent decrease of the water level at the boundary of semi-infinite fissurized-porous stratum. This flow is of practical interest: it gives a model of a groundwater flow after a high water period or after a failure of a dam around a collector of liquid waste. It is demonstrated that the fissures have a dramatic influence on the groundwater flow, increasing the penetration depth and speed of fluid penetration into the stratum. A characteristic property of the flow in fissurized-porous stratum is the rapid breakthrough of the fluid at the first stage deeply into the stratum via a system of cracks, feeding of porous blocks by the fluid in cracks, and at a later stage feeding of advancing fluid flow in fissures by the fluid, accumulated in porous blocks.

Cloning of the cDNA encoding the urotensin II precursor in frog and human reveals intense expression of the urotensin II gene in motoneurons of the spinal cord

Urotensin II (UII) is a cyclic peptide initially isolated from the caudal neurosecretory system of teleost fish. Subsequently, UII has been characterized from a frog brain extract, indicating that a gene encoding a UII precursor is also present in the genome of a tetrapod. Here, we report the characterization of the cDNAs encoding frog and human UII precursors and the localization of the corresponding mRNAs. In both frog and human, the UII sequence is located at the C-terminal position of the precursor. Human UII is composed of only 11 amino acid residues, while fish and frog UII possess 12 and 13 amino acid residues, respectively. The cyclic region of UII, which is responsible for the biological activity of the peptide, has been fully conserved from fish to human. Northern blot and dot blot analysis revealed that UII precursor mRNAs are found predominantly in the frog and human spinal cord. In situ hybridization studies showed that the UII precursor gene is actively expressed in motoneurons. The present study demonstrates that UII, which has long been regarded as a peptide exclusively produced by the urophysis of teleost fish, is actually present in the brain of amphibians and mammals. The fact that evolutionary pressure has acted to conserve fully the biologically active sequence of UII suggests that the peptide may exert important physiological functions in humans.

An approach to three-dimensional structures of biomolecules by using single-molecule diffraction images

We describe an approach to the high-resolution three-dimensional structural determination of macromolecules that utilizes ultrashort, intense x-ray pulses to record diffraction data in combination with direct phase retrieval by the oversampling technique. It is shown that a simulated molecular diffraction pattern at 2.5-Å resolution accumulated from multiple copies of single rubisco biomolecules, each generated by a femtosecond-level x-ray free electron laser pulse, can be successfully phased and transformed into an accurate electron density map comparable to that obtained by more conventional methods. The phase problem is solved by using an iterative algorithm with a random phase set as an initial input. The convergence speed of the algorithm is reasonably fast, typically around a few hundred iterations. This approach and phasing method do not require any ab initio information about the molecule, do not require an extended ordered lattice array, and can tolerate high noise and some missing intensity data at the center of the diffraction pattern. With the prospects of the x-ray free electron lasers, this approach could provide a major new opportunity for the high-resolution three-dimensional structure determination of single biomolecules.

Titration of chaos with added noise

Deterministic chaos has been implicated in numerous natural and man-made complex phenomena ranging from quantum to astronomical scales and in disciplines as diverse as meteorology, physiology, ecology, and economics. However, the lack of a definitive test of chaos vs. random noise in experimental time series has led to considerable controversy in many fields. Here we propose a numerical titration procedure as a simple “litmus test” for highly sensitive, specific, and robust detection of chaos in short noisy data without the need for intensive surrogate data testing. We show that the controlled addition of white or colored noise to a signal with a preexisting noise floor results in a titration index that: (i) faithfully tracks the onset of deterministic chaos in all standard bifurcation routes to chaos; and (ii) gives a relative measure of chaos intensity. Such reliable detection and quantification of chaos under severe conditions of relatively low signal-to-noise ratio is of great interest, as it may open potential practical ways of identifying, forecasting, and controlling complex behaviors in a wide variety of physical, biomedical, and socioeconomic systems.