Artefact detection and removal algorithms for EEG diagnostic systems

The electroencephalogram (EEG) is a medical technology that is used in the monitoring of the brain and in the diagnosis of many neurological illnesses. Although coarse in its precision, the EEG is a non-invasive tool that requires minimal set-up times, and is suitably unobtrusive and mobile to allow continuous monitoring of the patient, either in clinical or domestic environments. Consequently, the EEG is the current tool-of-choice with which to continuously monitor the brain where temporal resolution, ease-of- use and mobility are important. Traditionally, EEG data are examined by a trained clinician who identifies neurological events of interest. However, recent advances in signal processing and machine learning techniques have allowed the automated detection of neurological events for many medical applications. In doing so, the burden of work on the clinician has been significantly reduced, improving the response time to illness, and allowing the relevant medical treatment to be administered within minutes rather than hours. However, as typical EEG signals are of the order of microvolts (μV ), contamination by signals arising from sources other than the brain is frequent. These extra-cerebral sources, known as artefacts, can significantly distort the EEG signal, making its interpretation difficult, and can dramatically disimprove automatic neurological event detection classification performance. This thesis therefore, contributes to the further improvement of auto- mated neurological event detection systems, by identifying some of the major obstacles in deploying these EEG systems in ambulatory and clinical environments so that the EEG technologies can emerge from the laboratory towards real-world settings, where they can have a real-impact on the lives of patients. In this context, the thesis tackles three major problems in EEG monitoring, namely: (i) the problem of head-movement artefacts in ambulatory EEG, (ii) the high numbers of false detections in state-of-the-art, automated, epileptiform activity detection systems and (iii) false detections in state-of-the-art, automated neonatal seizure detection systems. To accomplish this, the thesis employs a wide range of statistical, signal processing and machine learning techniques drawn from mathematics, engineering and computer science. The first body of work outlined in this thesis proposes a system to automatically detect head-movement artefacts in ambulatory EEG and utilises supervised machine learning classifiers to do so. The resulting head-movement artefact detection system is the first of its kind and offers accurate detection of head-movement artefacts in ambulatory EEG. Subsequently, addtional physiological signals, in the form of gyroscopes, are used to detect head-movements and in doing so, bring additional information to the head- movement artefact detection task. A framework for combining EEG and gyroscope signals is then developed, offering improved head-movement arte- fact detection. The artefact detection methods developed for ambulatory EEG are subsequently adapted for use in an automated epileptiform activity detection system. Information from support vector machines classifiers used to detect epileptiform activity is fused with information from artefact-specific detection classifiers in order to significantly reduce the number of false detections in the epileptiform activity detection system. By this means, epileptiform activity detection which compares favourably with other state-of-the-art systems is achieved. Finally, the problem of false detections in automated neonatal seizure detection is approached in an alternative manner; blind source separation techniques, complimented with information from additional physiological signals are used to remove respiration artefact from the EEG. In utilising these methods, some encouraging advances have been made in detecting and removing respiration artefacts from the neonatal EEG, and in doing so, the performance of the underlying diagnostic technology is improved, bringing its deployment in the real-world, clinical domain one step closer.

Profiling side-channel attacks on cryptographic algorithms

Traditionally, attacks on cryptographic algorithms looked for mathematical weaknesses in the underlying structure of a cipher. Side-channel attacks, however, look to extract secret key information based on the leakage from the device on which the cipher is implemented, be it smart-card, microprocessor, dedicated hardware or personal computer. Attacks based on the power consumption, electromagnetic emanations and execution time have all been practically demonstrated on a range of devices to reveal partial secret-key information from which the full key can be reconstructed. The focus of this thesis is power analysis, more specifically a class of attacks known as profiling attacks. These attacks assume a potential attacker has access to, or can control, an identical device to that which is under attack, which allows him to profile the power consumption of operations or data flow during encryption. This assumes a stronger adversary than traditional non-profiling attacks such as differential or correlation power analysis, however the ability to model a device allows templates to be used post-profiling to extract key information from many different target devices using the power consumption of very few encryptions. This allows an adversary to overcome protocols intended to prevent secret key recovery by restricting the number of available traces. In this thesis a detailed investigation of template attacks is conducted, along with how the selection of various attack parameters practically affect the efficiency of the secret key recovery, as well as examining the underlying assumption of profiling attacks in that the power consumption of one device can be used to extract secret keys from another. Trace only attacks, where the corresponding plaintext or ciphertext data is unavailable, are then investigated against both symmetric and asymmetric algorithms with the goal of key recovery from a single trace. This allows an adversary to bypass many of the currently proposed countermeasures, particularly in the asymmetric domain. An investigation into machine-learning methods for side-channel analysis as an alternative to template or stochastic methods is also conducted, with support vector machines, logistic regression and neural networks investigated from a side-channel viewpoint. Both binary and multi-class classification attack scenarios are examined in order to explore the relative strengths of each algorithm. Finally these machine-learning based alternatives are empirically compared with template attacks, with their respective merits examined with regards to attack efficiency.

Power system parameters forecasting using Hilbert-Huang transform and machine learning

A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and a feature analysis of initial retrospective data using the Hilbert-Huang transform and machine learning algorithms. The random forests and gradient boosting trees learning techniques were examined. The decision tree techniques were used to rank the importance of variables employed in the forecasting models. The Mean Decrease Gini index is employed as an impurity function. The resulting hybrid forecasting models employ the radial basis function neural network and support vector regression. A part from introduction and references the paper is organized as follows. The second section presents the background and the review of several approaches for short-term forecasting of power system parameters. In the third section a hybrid machine learningbased algorithm using Hilbert-Huang transform is developed for short-term forecasting of power system parameters. Fourth section describes the decision tree learning algorithms used for the issue of variables importance. Finally in section six the experimental results in the following electric power problems are presented: active power flow forecasting, electricity price forecasting and for the wind speed and direction forecasting.

Intérêt clinique de la recherche des auto-anticorps

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Weighted and two-stage least squares estimation of semiparametric truncated regression models

This paper provides a root-n consistent, asymptotically normal weighted least squares estimator of the coefficients in a truncated regression model. The distribution of the errors is unknown and permits general forms of unknown heteroskedasticity. Also provided is an instrumental variables based two-stage least squares estimator for this model, which can be used when some regressors are endogenous, mismeasured, or otherwise correlated with the errors. A simulation study indicates that the new estimators perform well in finite samples. Our limiting distribution theory includes a new asymptotic trimming result addressing the boundary bias in first-stage density estimation without knowledge of the support boundary. © 2007 Cambridge University Press.

An alphavirus vector overcomes the presence of neutralizing antibodies and elevated numbers of Tregs to induce immune responses in humans with advanced cancer.

Therapeutic anticancer vaccines are designed to boost patients' immune responses to tumors. One approach is to use a viral vector to deliver antigen to in situ DCs, which then activate tumor-specific T cell and antibody responses. However, vector-specific neutralizing antibodies and suppressive cell populations such as Tregs remain great challenges to the efficacy of this approach. We report here that an alphavirus vector, packaged in virus-like replicon particles (VRP) and capable of efficiently infecting DCs, could be repeatedly administered to patients with metastatic cancer expressing the tumor antigen carcinoembryonic antigen (CEA) and that it overcame high titers of neutralizing antibodies and elevated Treg levels to induce clinically relevant CEA-specific T cell and antibody responses. The CEA-specific antibodies mediated antibody-dependent cellular cytotoxicity against tumor cells from human colorectal cancer metastases. In addition, patients with CEA-specific T cell responses exhibited longer overall survival. These data suggest that VRP-based vectors can overcome the presence of neutralizing antibodies to break tolerance to self antigen and may be clinically useful for immunotherapy in the setting of tumor-induced immunosuppression.

Reduction of malaria prevalence by indoor residual spraying: a meta-regression analysis.

Indoor residual spraying (IRS) has become an increasingly popular method of insecticide use for malaria control, and many recent studies have reported on its effectiveness in reducing malaria burden in a single community or region. There is a need for systematic review and integration of the published literature on IRS and the contextual determining factors of its success in controlling malaria. This study reports the findings of a meta-regression analysis based on 13 published studies, which were chosen from more than 400 articles through a systematic search and selection process. The summary relative risk for reducing malaria prevalence was 0.38 (95% confidence interval = 0.31-0.46), which indicated a risk reduction of 62%. However, an excessive degree of heterogeneity was found between the studies. The meta-regression analysis indicates that IRS is more effective with high initial prevalence, multiple rounds of spraying, use of DDT, and in regions with a combination of Plasmodium falciparum and P. vivax malaria.

Integrated vector management for malaria control in Uganda: knowledge, perceptions and policy development.

BACKGROUND: Integrated vector management (IVM) is increasingly being recommended as an option for sustainable malaria control. However, many malaria-endemic countries lack a policy framework to guide and promote the approach. The objective of the study was to assess knowledge and perceptions in relation to current malaria vector control policy and IVM in Uganda, and to make recommendations for consideration during future development of a specific IVM policy. METHODS: The study used a structured questionnaire to interview 34 individuals working at technical or policy-making levels in health, environment, agriculture and fisheries sectors. Specific questions on IVM focused on the following key elements of the approach: integration of chemical and non-chemical interventions of vector control; evidence-based decision making; inter-sectoral collaboration; capacity building; legislation; advocacy and community mobilization. RESULTS: All participants were familiar with the term IVM and knew various conventional malaria vector control (MVC) methods. Only 75% thought that Uganda had a MVC policy. Eighty percent (80%) felt there was inter-sectoral collaboration towards IVM, but that it was poor due to financial constraints, difficulties in involving all possible sectors and political differences. The health, environment and agricultural sectors were cited as key areas requiring cooperation in order for IVM to succeed. Sixty-seven percent (67%) of participants responded that communities were actively being involved in MVC, while 48% felt that the use of research results for evidence-based decision making was inadequate or poor. A majority of the participants felt that malaria research in Uganda was rarely used to facilitate policy changes. Suggestions by participants for formulation of specific and effective IVM policy included: revising the MVC policy and IVM-related policies in other sectors into a single, unified IVM policy and, using legislation to enforce IVM in development projects. CONCLUSION: Integrated management of malaria vectors in Uganda remains an underdeveloped component of malaria control policy. Cooperation between the health and other sectors needs strengthening and funding for MVC increased in order to develop and effectively implement an appropriate IVM policy. Continuous engagement of communities by government as well as monitoring and evaluation of vector control programmes will be crucial for sustaining IVM in the country.

Lognormal and gamma mixed negative binomial regression

In regression analysis of counts, a lack of simple and efficient algorithms for posterior computation has made Bayesian approaches appear unattractive and thus underdeveloped. We propose a lognormal and gamma mixed negative binomial (NB) regression model for counts, and present efficient closed-form Bayesian inference; unlike conventional Poisson models, the proposed approach has two free parameters to include two different kinds of random effects, and allows the incorporation of prior information, such as sparsity in the regression coefficients. By placing a gamma distribution prior on the NB dispersion parameter r, and connecting a log-normal distribution prior with the logit of the NB probability parameter p, efficient Gibbs sampling and variational Bayes inference are both developed. The closed-form updates are obtained by exploiting conditional conjugacy via both a compound Poisson representation and a Polya-Gamma distribution based data augmentation approach. The proposed Bayesian inference can be implemented routinely, while being easily generalizable to more complex settings involving multivariate dependence structures. The algorithms are illustrated using real examples. Copyright 2012 by the author(s)/owner(s).

Assessment of toxicity and biodistribution of recombinant AAV8 vector-mediated immunomodulatory gene therapy in mice with Pompe disease.

A preclinical safety study was conducted to evaluate the short- and long-term toxicity of a recombinant adeno-associated virus serotype 8 (AAV2/8) vector that has been developed as an immune-modulatory adjunctive therapy to recombinant human acid α-glucosidase (rhGAA, Myozyme) enzyme replacement treatment (ERT) for patients with Pompe disease (AAV2/8-LSPhGAApA). The AAV2/8-LSPhGAApA vector at 1.6 × 10(13) vector particles/kg, after intravenous injection, did not cause significant short- or long-term toxicity. Recruitment of CD4(+) (but not CD8(+)) lymphocytes to the liver was elevated in the vector-dosed male animals at study day (SD) 15, and in group 8 animals at SD 113, in comparison to their respective control animals. Administration of the vector, either prior to or after the one ERT injection, uniformly prevented the hypersensitivity induced by subsequent ERT in males, but not always in female animals. The vector genome was sustained in all tissues through 16-week postdosing, except for in blood with a similar tissue tropism between males and females. Administration of the vector alone, or combined with the ERT, was effective in producing significantly increased GAA activity and consequently decreased glycogen accumulation in multiple tissues, and the urine biomarker, Glc4, was significantly reduced. The efficacy of the vector (or with ERT) was better in males than in females, as demonstrated both by the number of tissues showing significantly effective responses and the extent of response in a given tissue. Given the lack of toxicity for AAV2/8LSPhGAApA, further consideration of clinical translation is warranted in Pompe disease.

Interactions spatiales et auto-organisation des végétations semi-arides

Les recherches récapitulées dans cette thèse de doctorat ont porté sur les causes de l’organisation spatiale des végétations périodiques. Ces structures paysagères aux motifs réguliers, tachetés, tigrés ou labyrinthiques, d’échelle décamétrique à hectométrique, couvrant des étendues considérables sur au moins trois continents, constituent un cas d’école dans l’étude des processus endogènes présidant à l’hétérogénéité du couvert végétal. Ces structures prennent place sur un substrat homogène, mis à part la rétroaction du couvert lui-même, et sont marquées par des écotones abrupts et la persistance d’une proportion considérable de sol nu. Plusieurs modèles ont mis en avant l’existence possible d’un phénomène d’auto-organisation du couvert, qui verrait une structure d’ensemble émerger des interactions locales entre individus. Ces modèles se basent sur le jeu simultané de la consommation de la ressource (compétition) et de l’amélioration de l’un ou l’autre des éléments du bilan de la même ressource par le couvert (facilitation). La condition à l’existence d’une structure d’ensemble spatialement périodique et stable réside dans une différence entre la portée de la compétition (plus grande) et celle de la facilitation. L’apparition de ces structures est modulée par le taux de croissance biologique, qui est le reflet des contraintes extérieures telles que l’aridité, le pâturage ou la coupe de bois. Le modus operandi des interactions spatiales supposées entre individus reste largement à préciser.

Nos recherches ont été menées au sud-ouest de la République du Niger, à l’intérieur et dans les environs du parc Régional du W. Trois axes ont été explorés :(i) Une étude de la dépendance spatiale entre la structure de la végétation (biovolumes cartographiés) et les paramètres du milieu abiotique (relief, sol), sur base d’analyses spectrales et cross-spectrales par transformée de Fourier (1D et 2D). (ii) Une étude diachronique (1956, 1975 et 1996) à large échelle (3000 km²) de l’influence de l’aridité et des pressions d’origine anthropique sur l’auto-organisation des végétations périodiques, basée sur la caractérisation de la structure spatiale des paysages sur photos aériennes via la transformée de Fourier en 2D. (iii) Trois études portant sur les interactions spatiales entre individus :En premier lieu, via l’excavation des systèmes racinaires (air pulsé) ;Ensuite, par un suivi spatio-temporel du bilan hydrique du sol (blocs de gypse) ;Enfin, via le marquage de la ressource par du deutérium.

Nous avons ainsi pu établir que les végétations périodiques constituent bien un mode d’auto-organisation pouvant survenir sur substrat homogène et modulé par les contraintes climatiques et anthropiques. Un ajustement rapide entre l’organisation des végétations périodiques et le climat a pu être montrée en zone protégée. La superficie et l’organisation des végétations périodiques y ont tour à tour progressé et régressé en fonction d’épisodes secs ou humides. Par contre, en dehors de l’aire protégée, la possibilité d’une restauration du couvert semble fortement liée au taux d’exploitation des ressources végétales. Ces résultats ont d’importantes implications quant à la compréhension des interactions entre climat et écosystèmes et à l’évaluation de leurs capacités de charge. La caractérisation de la structure spatiale des végétations arides, notamment par la transformée de Fourier d’images HR, devrait être généralisée comme outil de monitoring de l’état de ces écosystèmes. Nos études portant sur les modes d’interactions spatiales ont permis de confirmer l’existence d’une facilitation à courte portée du couvert végétal sur la ressource. Cependant, cette facilitation ne semble pas s’exercer sur le terme du bilan hydrique traditionnellement avancé, à savoir l’infiltration, mais plutôt sur le taux d’évaporation (deux fois moindre à l’ombre des canopées). Ce mécanisme exclut l’existence de transferts diffusifs souterrains entre sols nu et fourrés. Des transferts inverses semblent d’ailleurs montrés par le marquage isotopique. L’étude du bilan hydrique et la cartographie du micro-relief, ainsi que la profondeur fortement réduite de la zone d’exploitation racinaire, jettent de sérieux doutes quant au rôle communément admis des transferts d’eau par ruissellement/diffusion de surface en tant que processus clé dans la compétition à distance entre les plantes. L’alternative réside dans l’existence d’une compétition racinaire de portée supérieure aux canopées. Cette hypothèse trouve une confirmation tant par les rhizosphères excavées, superficielles et étendues, que dans le marquage isotopique, montrant des contaminations d’arbustes situés à plus de 15 m de la zone d’apport. De même, l’étude du bilan hydrique met en évidence les influences simultanées et contradictoires (facilitation/compétition) des ligneux sur l’évapotranspiration.

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This PhD thesis gathers results of a research dealing with the causes of the spatial organisation of periodic vegetations. These landscape structures, featuring regular spotted, labyrinthine or banded patterns of decametric to hectometric scale, and extending over considerable areas on at least three continents, constitute a perfect study case to approach endogenous processes leading to vegetation heterogeneities. These patterns occur over homogeneous substratum, except for vegetation’s own feedbacks, and are marked by sharp ecotones and the persistence of a considerable amount of bare soil. A number of models suggested a possible case of self-organized patterning, in which the general structure would emerge from local interactions between individuals. Those models rest on the interplay of competitive and facilitative effects, relating to soil water consumption and to soil water budget enhancement by vegetation. A general necessary condition for pattern formation to occur is that negative interactions (competition) have a larger range than positive interactions (facilitation). Moreover, all models agree with the idea that patterning occurs when vegetation growth decreases, for instance as a result of reduced water availability, domestic grazing or wood cutting, therefore viewing patterns as a self-organised response to environmental constraints. However the modus operandi of the spatial interactions between individual plants remains largely to be specified.

We carried out a field research in South-West Niger, within and around the W Regional Park. Three research lines were explored: (i) The study of the spatial dependency between the vegetation pattern (mapped biovolumes) and the factors of the abiotic environment (soil, relief), on the basis of spectral and cross-spectral analyses with Fourier transform (1D and 2D). (ii) A broad scale diachronic study (1956, 1975, 1996) of the influence of aridity and human induced pressures on the vegetation self-patterning, based on the characterisation of patterns on high resolution remote sensing data via 2D Fourier transform. (iii) Three different approaches of the spatial interactions between individuals: via root systems excavation with pulsed air; via the monitoring in space and time of the soil water budget (gypsum blocks method); and via water resource labelling with deuterated water.

We could establish that periodic vegetations are indeed the result of a self-organisation process, occurring in homogeneous substratum conditions and modulated by climate and human constraints. A rapid adjustment between vegetation patterning and climate could be observed in protected zones. The area and patterning of the periodic vegetations successively progressed and regressed, following drier or wetter climate conditions. On the other hand, outside protected areas, the restoration ability of vegetation appeared to depend on the degree of vegetation resource exploitation. These results have important implications regarding the study of vegetation-climate interactions and the evaluation of ecosystems’ carrying capacities. Spatial pattern characterisation in arid vegetations using Fourier transform of HR remote sensing data should be generalised for the monitoring of those ecosystems. Our studies dealing with spatial interaction mechanisms confirmed the existence of a short range facilitation of the cover on water resource. However, this facilitation does not seem to act through the commonly accepted infiltration component, but rather on the evaporative rate (twice less within thickets). This mechanism excludes underground diffusive transfers between bare ground and vegetation. Inverse transfers were even shown by deuterium labelling. Water budget study and micro-elevation mapping, along with consistent soil shallowness, together cast serious doubts on the traditional mechanism of run-off/diffusion of surface water as a key process of the long range competition between plants. An alternative explanation lies in long range root competition. This hypothesis find support as well in the excavated root systems, shallow and wide, as in isotopic labelling, showing contaminations of shrubs located up to 15 m of the irrigated area. Water budget study also evidenced simultaneous contradictory effects (facilitation/competition) of shrubs on evapotranspiration.

Experimental study of modulational instability and vector solitons in optical fibers

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An extension of Purcell's vector method with applications to panel element equations

The classical Purcell's vector method, for the construction of solutions to dense systems of linear equations is extended to a flexible orthogonalisation procedure. Some properties are revealed of the orthogonalisation procedure in relation to the classical Gauss-Jordan elimination with or without pivoting. Additional properties that are not shared by the classical Gauss-Jordan elimination are exploited. Further properties related to distributed computing are discussed with applications to panel element equations in subsonic compressible aerodynamics. Using an orthogonalisation procedure within panel methods enables a functional decomposition of the sequential panel methods and leads to a two-level parallelism.

A higher order Hopfield network for vector quantisation

A higher order version of the Hopfield neural network is presented which will perform a simple vector quantisation or clustering function. This model requires no penalty terms to impose constraints in the Hopfield energy, in contrast to the usual one where the energy involves only terms quadratic in the state vector. The energy function is shown to have no local minima within the unit hypercube of the state vector so the network only converges to valid final states. Optimisation trials show that the network can consistently find optimal clusterings for small, trial problems and near optimal ones for a large data set consisting of the intensity values from the digitised, grey-level image.

Mode shape expansion using perturbed force vector approach

A new technique for mode shape expansion in structural dynamic applications is presented based on the perturbed force vector approach. The proposed technique can directly adopt the measured incomplete modal data and include the effect of the perturbation between the analytical and test models. The results show that the proposed technique can provide very accurate expanded mode shapes, especially in cases when significant modelling error exists in the analytical model and limited measurements are available.