Neural networks complemented with genetic algorithms and fuzzy systems for predicting nitrogenous effluent variables in wastewater treatment plants

This work focuses on the prediction of the two main nitrogenous variables that describe the water quality at the effluent of a Wastewater Treatment Plant. We have developed two kind of Neural Networks architectures based on considering only one output or, in the other hand, the usual five effluent variables that define the water quality: suspended solids, biochemical organic matter, chemical organic matter, total nitrogen and total Kjedhal nitrogen. Two learning techniques based on a classical adaptative gradient and a Kalman filter have been implemented. In order to try to improve generalization and performance we have selected variables by means genetic algorithms and fuzzy systems. The training, testing and validation sets show that the final networks are able to learn enough well the simulated available data specially for the total nitrogen

Computational and Energy Costs of Cryptographic Algorithms on Handheld Devices

Networks are evolving toward a ubiquitous model in which heterogeneousdevices are interconnected. Cryptographic algorithms are required for developing securitysolutions that protect network activity. However, the computational and energy limitationsof network devices jeopardize the actual implementation of such mechanisms. In thispaper, we perform a wide analysis on the expenses of launching symmetric and asymmetriccryptographic algorithms, hash chain functions, elliptic curves cryptography and pairingbased cryptography on personal agendas, and compare them with the costs of basic operatingsystem functions. Results show that although cryptographic power costs are high and suchoperations shall be restricted in time, they are not the main limiting factor of the autonomyof a device.

The role of PLK-1 in asynchronous cell division of two-cell stage "C. elegans" embryos

Summary Acquisition of lineage-specific cell cycle duration is an important feature of metazoan development. In Caenorhabditis a/egans, differences in cell cycle duration are already apparent in two-cell stage embryos, when the larger anterior blastomere AB divides before the smaller posterior blastomere P1. This time difference is under the control of anterior-posterior (A-P) polarity cues set by the PAR proteins. The mechanism by which these cues regulate the cell cycle machinery differentially in AB and P1 are incompletely understood. Previous work established that retardation of P1 cell division is due in part to preferential activation of an ATL1/CHK-1 dependent checkpoint in P1 but how the remaining time difference is controlled was not known at the onset of my work. The principal line of work in this thesis established that differential timing relies also on a mechanism that promotes mitosis onset preferentially in AB. The polo-like kinase PLK-1, a positive regulator of mitotic entry, is distributed in an asymmetric manner in two-cell stage embryos, with more protein present in AB than in P1. We find that PLK-1 asymmetry is regulated by anterior-posterior (A-P) polarity cues through preferential protein retention in the embryo anterior. Importantly, mild inactivation of plk-1 by RNAi delays entry into mitosis in P1 but not in AB, in a manner that is independent of ATL-1/CHK-1. Together, these findings favor a model in which differential timing of mitotic entry in C. elegans embryos relies on two complementary mechanisms: ATL-1/CHK-1 dependent preferential retardation in P1 and PLK-1 dependent preferential promotion in AB, which together couple polarity cues and cell cycle progression during early development. Besides analyzing PLK-1 asymmetry and its role in differential timing of two-cells stage embryos, we also characterized t2190, a mutant that exhibits reduced differential timing between AB and P1. We found this mutant to be a new allele of par-1. Additionally, we analyzed the role of NMY-2 in regulating the asynchrony of two-cell stage embryos, which may be uncoupled from its role in A-P polarity establishment and carried out a preliminary analysis of the mechanism underlying CDC-25 asymmetry between AB and P,. Overall, our works bring new insights into the mechanism controlling cell cycle progression in early C. elegans embryos. As most of the players important in C. elegans are conserved in other organisms, analogous mechanisms may be utilized in polarized cells of other species. Résumé Au cours du développement, les processus de division cellulaire sont régulés dans l'espace et le temps afin d'aboutir à la formation d'un organisme fonctionnel. Chez les Métazoaires, l'un des mécanismes de contrôle s'effectue au niveau de la durée du cycle cellulaire, celle-ci étant specifiée selon la lignée cellulaire. L'embryon du nématode Caenorhabditis elegans apparaît comme un excellent modèle d'étude de la régulation temporelle du cycle cellulaire. En effet, suite à la première division du zygote, l'embryon est alors composé de deux cellules de taille et d'identité différentes, appelées blastomères AB et P1. Ces deux cellules vont ensuite se diviser de manière asynchrone, le grand blastomère antérieur AB se divisant plus rapidement que le petit blastomère postérieur P1. Cette asynchronie de division est sous le contrôle des protéines PAR qui sont impliquées dans l'établissement de l'axe antéro-postérieur de l'embryon. A ce jour, les mécanismes moléculaires gouvernant ce processus d'asynchronie ne sont que partiellement compris. Des études menées précédemment ont établit que le retard de division observé dans le petit blastomère postérieur P1 était dû, en partie, à l'activation préférentielle dans cette cellule de ATL-1/CHK-1, protéines contrôlant la réponse à des erreurs dans le processus de réplication de l'ADN. L'analyse des autres mécanismes responsables de la différence temporelle d'entrée en mitose des deux cellules a été entreprise au cours de cette thèse. Nous avons considéré la possibilité que l'asynchronie de division était du à l'entrée préférentielle en mitose du grand blastomère AB. Nous avons établi que la protéine kinase PLK-1 (polo-like kinase 1), impliquée dans la régulation positive de la mitose, était distribuée de manière asymétrique dans l'embryon deux cellules. PLK-1 est en effet enrichi dans le blastomère AB. Cette localisation asymétrique de PLK-1 est sous le contrôle des protéines PAR et semble établie via une rétention de PLK-1 dans la cellule AB. Par ailleurs, nous avons démontré que l'inactivation partielle de plk-7 par interférence à ARN (RNAi) conduit à un délai de l'entrée en mitose de la cellule P1 spécifiquement, indépendamment des protéines régulatrices ATL-1/CHK-1. En conclusion, nous proposons un modèle de régulation temporelle de l'entrée en mitose dans l'embryon deux cellules de C. elegans basé sur deux mécanismes complémentaires. Le premier implique l'activation préférentielle des protéines ATL-1/CHK-1, et conduit à un retard d'entrée en mitose spécifiquement dans la cellule P1. Le second est basé sur la localisation asymétrique de la protéine kinase PLK-1 dans la cellule AB et induit une entrée précoce en mitose de cette cellule. Par ailleurs, nous avons étudié un mutant appelé t2190 qui réduit la différence temporelle d'entrée en mitose entre les cellules AB et P1. Nous avons démontré que ce mutant correspondait à un nouvel allèle du Bene par-1. De plus, nous avons analysé le rôle de NMY-2, une protéine myosine qui agit comme moteur moléculaire sur les filaments d'active; dans la régulation de l'asynchronie de division des blastomères AB et P1, indépendamment de sa fonction dans l'établissement de l'axe antéro-postérieur. Par ailleurs, nous avons commencé l'étude du mécanisme moléculaire régulant la localisation asymétrique entre les cellules AB et P1 de la protéine phosphatase CDC25, qui est également un important régulateur de l'entrée en mitose. En conclusion, ce travail de thèse a permis une meilleure compréhension des mécanismes gouvernant la progression du cycle cellulaire dans l'embryon précoce de C. elegans. Etant donné que la plupart des protéines impliquées dans ces processus sont conservées chez d'autres organismes multicellulaires, il apparaît probable que les mécanismes moléculaires révélés dans cette étude soit aussi utilisés chez ceux-ci.

Environmental data mining and modeling based on machine learning algorithms and geostatistics

The paper presents some contemporary approaches to spatial environmental data analysis. The main topics are concentrated on the decision-oriented problems of environmental spatial data mining and modeling: valorization and representativity of data with the help of exploratory data analysis, spatial predictions, probabilistic and risk mapping, development and application of conditional stochastic simulation models. The innovative part of the paper presents integrated/hybrid model-machine learning (ML) residuals sequential simulations-MLRSS. The models are based on multilayer perceptron and support vector regression ML algorithms used for modeling long-range spatial trends and sequential simulations of the residuals. NIL algorithms deliver non-linear solution for the spatial non-stationary problems, which are difficult for geostatistical approach. Geostatistical tools (variography) are used to characterize performance of ML algorithms, by analyzing quality and quantity of the spatially structured information extracted from data with ML algorithms. Sequential simulations provide efficient assessment of uncertainty and spatial variability. Case study from the Chernobyl fallouts illustrates the performance of the proposed model. It is shown that probability mapping, provided by the combination of ML data driven and geostatistical model based approaches, can be efficiently used in decision-making process. (C) 2003 Elsevier Ltd. All rights reserved.

Robust power allocation algorithms for MIMO OFDM systems with imperfect CSI

This paper presents a Bayesian approach to the design of transmit prefiltering matrices in closed-loop schemes robust to channel estimation errors. The algorithms are derived for a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Two different optimizationcriteria are analyzed: the minimization of the mean square error and the minimization of the bit error rate. In both cases, the transmitter design is based on the singular value decomposition (SVD) of the conditional mean of the channel response, given the channel estimate. The performance of the proposed algorithms is analyzed,and their relationship with existing algorithms is indicated. As withother previously proposed solutions, the minimum bit error rate algorithmconverges to the open-loop transmission scheme for very poor CSI estimates.

Probabilistic algorithms for blind adaptive multiuser detection

In this paper, two probabilistic adaptive algorithmsfor jointly detecting active users in a DS-CDMA system arereported. The first one, which is based on the theory of hiddenMarkov models (HMM’s) and the Baum–Wech (BW) algorithm,is proposed within the CDMA scenario and compared withthe second one, which is a previously developed Viterbi-basedalgorithm. Both techniques are completely blind in the sense thatno knowledge of the signatures, channel state information, ortraining sequences is required for any user. Once convergencehas been achieved, an estimate of the signature of each userconvolved with its physical channel response (CR) and estimateddata sequences are provided. This CR estimate can be used toswitch to any decision-directed (DD) adaptation scheme. Performanceof the algorithms is verified via simulations as well as onexperimental data obtained in an underwater acoustics (UWA)environment. In both cases, performance is found to be highlysatisfactory, showing the near–far resistance of the analyzed algorithms.

Performance of noninvasive ventilation algorithms on ICU ventilators during pressure support: a clinical study.

To evaluate the impact of noninvasive ventilation (NIV) algorithms available on intensive care unit ventilators on the incidence of patient-ventilator asynchrony in patients receiving NIV for acute respiratory failure. Prospective multicenter randomized cross-over study. Intensive care units in three university hospitals. Patients consecutively admitted to the ICU and treated by NIV with an ICU ventilator were included. Airway pressure, flow and surface diaphragmatic electromyography were recorded continuously during two 30-min periods, with the NIV (NIV+) or without the NIV algorithm (NIV0). Asynchrony events, the asynchrony index (AI) and a specific asynchrony index influenced by leaks (AIleaks) were determined from tracing analysis. Sixty-five patients were included. With and without the NIV algorithm, respectively, auto-triggering was present in 14 (22%) and 10 (15%) patients, ineffective breaths in 15 (23%) and 5 (8%) (p = 0.004), late cycling in 11 (17%) and 5 (8%) (p = 0.003), premature cycling in 22 (34%) and 21 (32%), and double triggering in 3 (5%) and 6 (9%). The mean number of asynchronies influenced by leaks was significantly reduced by the NIV algorithm (p < 0.05). A significant correlation was found between the magnitude of leaks and AIleaks when the NIV algorithm was not activated (p = 0.03). The global AI remained unchanged, mainly because on some ventilators with the NIV algorithm premature cycling occurs. In acute respiratory failure, NIV algorithms provided by ICU ventilators can reduce the incidence of asynchronies because of leaks, thus confirming bench test results, but some of these algorithms can generate premature cycling.

Investigation of discrete imaging models and iterative image reconstruction in differential X-ray phase-contrast tomography.

Differential X-ray phase-contrast tomography (DPCT) refers to a class of promising methods for reconstructing the X-ray refractive index distribution of materials that present weak X-ray absorption contrast. The tomographic projection data in DPCT, from which an estimate of the refractive index distribution is reconstructed, correspond to one-dimensional (1D) derivatives of the two-dimensional (2D) Radon transform of the refractive index distribution. There is an important need for the development of iterative image reconstruction methods for DPCT that can yield useful images from few-view projection data, thereby mitigating the long data-acquisition times and large radiation doses associated with use of analytic reconstruction methods. In this work, we analyze the numerical and statistical properties of two classes of discrete imaging models that form the basis for iterative image reconstruction in DPCT. We also investigate the use of one of the models with a modern image reconstruction algorithm for performing few-view image reconstruction of a tissue specimen.

Algorithms and cryptographic protocols using elliptic curves

En els darrers anys, la criptografia amb corbes el.líptiques ha adquirit una importància creixent, fins a arribar a formar part en la actualitat de diferents estàndards industrials. Tot i que s'han dissenyat variants amb corbes el.líptiques de criptosistemes clàssics, com el RSA, el seu màxim interès rau en la seva aplicació en criptosistemes basats en el Problema del Logaritme Discret, com els de tipus ElGamal. En aquest cas, els criptosistemes el.líptics garanteixen la mateixa seguretat que els construïts sobre el grup multiplicatiu d'un cos finit primer, però amb longituds de clau molt menor. Mostrarem, doncs, les bones propietats d'aquests criptosistemes, així com els requeriments bàsics per a que una corba sigui criptogràficament útil, estretament relacionat amb la seva cardinalitat. Revisarem alguns mètodes que permetin descartar corbes no criptogràficament útils, així com altres que permetin obtenir corbes bones a partir d'una de donada. Finalment, descriurem algunes aplicacions, com són el seu ús en Targes Intel.ligents i sistemes RFID, per concloure amb alguns avenços recents en aquest camp.

Reduction of respiratory motion artifacts for free-breathing whole-heart coronary MRA by weighted iterative reconstruction.

PURPOSE: To combine weighted iterative reconstruction with self-navigated free-breathing coronary magnetic resonance angiography for retrospective reduction of respiratory motion artifacts. METHODS: One-dimensional self-navigation was improved for robust respiratory motion detection and the consistency of the acquired data was estimated on the detected motion. Based on the data consistency, the data fidelity term of iterative reconstruction was weighted to reduce the effects of respiratory motion. In vivo experiments were performed in 14 healthy volunteers and the resulting image quality of the proposed method was compared to a navigator-gated reference in terms of acquisition time, vessel length, and sharpness. RESULT: Although the sampling pattern of the proposed method contained 60% more samples with respect to the reference, the scan efficiency was improved from 39.5 ± 10.1% to 55.1 ± 9.1%. The improved self-navigation showed a high correlation to the standard navigator signal and the described weighting efficiently reduced respiratory motion artifacts. Overall, the average image quality of the proposed method was comparable to the navigator-gated reference. CONCLUSION: Self-navigated coronary magnetic resonance angiography was successfully combined with weighted iterative reconstruction to reduce the total acquisition time and efficiently suppress respiratory motion artifacts. The simplicity of the experimental setup and the promising image quality are encouraging toward future clinical evaluation. Magn Reson Med 73:1885-1895, 2015. © 2014 Wiley Periodicals, Inc.

Statistical modelling of CSP solving algorithms performance

The goal of this work is to try to create a statistical model, based only on easily computable parameters from the CSP problem to predict runtime behaviour of the solving algorithms, and let us choose the best algorithm to solve the problem. Although it seems that the obvious choice should be MAC, experimental results obtained so far show, that with big numbers of variables, other algorithms perfom much better, specially for hard problems in the transition phase.

All-sky search algorithms for monochromatic signals in bar gravitational wave detector data

In this paper we design and develop several filtering strategies for the analysis of data generated by a resonant bar gravitational wave (GW) antenna, with the goal of assessing the presence (or absence) therein of long-duration monochromatic GW signals, as well as the eventual amplitude and frequency of the signals, within the sensitivity band of the detector. Such signals are most likely generated in the fast rotation of slightly asymmetric spinning stars. We develop practical procedures, together with a study of their statistical properties, which will provide us with useful information on the performance of each technique. The selection of candidate events will then be established according to threshold-crossing probabilities, based on the Neyman-Pearson criterion. In particular, it will be shown that our approach, based on phase estimation, presents a better signal-to-noise ratio than does pure spectral analysis, the most common approach.

Decreasing Proportion of Recent Infections among Newly Diagnosed HIV-1 Cases in Switzerland, 2008 to 2013 Based on Line-Immunoassay-Based Algorithms.

BACKGROUND: HIV surveillance requires monitoring of new HIV diagnoses and differentiation of incident and older infections. In 2008, Switzerland implemented a system for monitoring incident HIV infections based on the results of a line immunoassay (Inno-Lia) mandatorily conducted for HIV confirmation and type differentiation (HIV-1, HIV-2) of all newly diagnosed patients. Based on this system, we assessed the proportion of incident HIV infection among newly diagnosed cases in Switzerland during 2008-2013. METHODS AND RESULTS: Inno-Lia antibody reaction patterns recorded in anonymous HIV notifications to the federal health authority were classified by 10 published algorithms into incident (up to 12 months) or older infections. Utilizing these data, annual incident infection estimates were obtained in two ways, (i) based on the diagnostic performance of the algorithms and utilizing the relationship 'incident = true incident + false incident', (ii) based on the window-periods of the algorithms and utilizing the relationship 'Prevalence = Incidence x Duration'. From 2008-2013, 3'851 HIV notifications were received. Adult HIV-1 infections amounted to 3'809 cases, and 3'636 of them (95.5%) contained Inno-Lia data. Incident infection totals calculated were similar for the performance- and window-based methods, amounting on average to 1'755 (95% confidence interval, 1588-1923) and 1'790 cases (95% CI, 1679-1900), respectively. More than half of these were among men who had sex with men. Both methods showed a continuous decline of annual incident infections 2008-2013, totaling -59.5% and -50.2%, respectively. The decline of incident infections continued even in 2012, when a 15% increase in HIV notifications had been observed. This increase was entirely due to older infections. Overall declines 2008-2013 were of similar extent among the major transmission groups. CONCLUSIONS: Inno-Lia based incident HIV-1 infection surveillance proved useful and reliable. It represents a free, additional public health benefit of the use of this relatively costly test for HIV confirmation and type differentiation.

False normal Lung Clearance Index in infants with cystic fibrosis due to software algorithms.

BACKGROUND: Lung clearance index (LCI), a marker of ventilation inhomogeneity, is elevated early in children with cystic fibrosis (CF). However, in infants with CF, LCI values are found to be normal, although structural lung abnormalities are often detectable. We hypothesized that this discrepancy is due to inadequate algorithms of the available software package. AIM: Our aim was to challenge the validity of these software algorithms. METHODS: We compared multiple breath washout (MBW) results of current software algorithms (automatic modus) to refined algorithms (manual modus) in 17 asymptomatic infants with CF, and 24 matched healthy term-born infants. The main difference between these two analysis methods lies in the calculation of the molar mass differences that the system uses to define the completion of the measurement. RESULTS: In infants with CF the refined manual modus revealed clearly elevated LCI above 9 in 8 out of 35 measurements (23%), all showing LCI values below 8.3 using the automatic modus (paired t-test comparing the means, P < 0.001). Healthy infants showed normal LCI values using both analysis methods (n = 47, paired t-test, P = 0.79). The most relevant reason for false normal LCI values in infants with CF using the automatic modus was the incorrect recognition of the end-of-test too early during the washout. CONCLUSION: We recommend the use of the manual modus for the analysis of MBW outcomes in infants in order to obtain more accurate results. This will allow appropriate use of infant lung function results for clinical and scientific purposes. Pediatr Pulmonol. 2015; 50:970-977. © 2015 Wiley Periodicals, Inc.