Segurança em redes sem fio: estudo sobre o desenvolvimento de conjuntos de dados para comparação de IDS

Pós-graduação em Engenharia Elétrica - FEIS

Quantifizierung von Steinschlagrisiken an Straßen

Thema: Quantifizierung von Steinschlagrisiken an Straßen Die Einschätzung eines bestehenden Steinschlagrisikos an Verkehrswegen ist in Gebirgs- und Mittelgebirgsregionen seit jeher eine Aufgabe, die mit verschiedensten Methoden und unterschiedlichem Aufwand bearbeitet wird. In der vorliegenden Untersuchung werden die maßgebenden Parameter zur Beschreibung einer Böschung aufgenommen und bewertet. Es wurde ein Arbeitsblatt entwickelt, in dem festgelegte Parameter erfasst werden, die teils mit Ankreuztechnik, teils mit der Eingabe von Daten, im Computer notiert werden. Das Arbeitsblatt umfasst vier Themenbereiche: Allgemeine Daten, Angaben zur Geometrie der Böschung, Angaben zum Verkehr und Angaben zum Gestein und Gebirge. Ein Computerprogramm, das auf der Basis der Software Excel von Microsoft erstellt wurde, vergibt nach der Dateneingabe Bewertungspunkte (1. Bewertungsschritt). Es werden Summen gebildet und die Teilbereiche bewertet (2. Bewertungsschritt). Jeder Teilbereich besitzt drei Bewertungsklassen. Die Verknüpfung der Bewertung der Teilbereiche Geometrische Angaben und Angaben zum Gestein und Gebirge stellt die eigentliche Risikoeinschätzung dar (3. Bewertungsschritt). Es gibt drei Einstufungen zur Beschreibung des Risikos: ð Der Verkehr ist durch Steinschlag sehr gering gefährdet. ð Der Verkehr ist durch Steinschlag gering gefährdet. Eine Detailüberprüfung muss erfolgen, da eine Gefährdung nicht auszuschließen ist. ð Der Verkehr ist gefährdet. Es besteht ein hohes Steinschlagrisiko. Bewertungen und Hinweise zu den Teilbereichen Allgemeine Daten und Angaben zum Verkehr kann der Anwender nach eigenem Ermessen zusätzlich nutzen. Die abschließende Risikoeinschätzung erfolgt durch den Anwender bzw. einen Sachverständigen.

Epidermal growth factor receptor (EGFR) is an independent adverse prognostic factor in esophageal adenocarcinoma patients treated with cisplatin-based neoadjuvant chemotherapy.

Neoadjuvant platin-based therapy is accepted as a standard therapy for advanced esophageal adenocarcinoma (EAC). Patients who respond have a better survival prognosis, but still a significant number of responder patients die from tumor recurrence. Molecular markers for prognosis in neoadjuvantly treated EAC patients have not been identified yet. We investigated the epidermal growth factor receptor (EGFR) in prognosis and chemotherapy resistance in these patients. Two EAC patient cohorts, either treated by neoadjuvant cisplatin-based chemotherapy followed by surgery (n=86) or by surgical resection (n=46) were analyzed for EGFR protein expression and gene copy number. Data were correlated with clinical and histopathological response, disease-free and overall survival. In case of EGFR overexpression, the prognosis for neoadjuvant chemotherapy responders was poor as in non-responders. Responders had a significantly better disease-free survival than non-responders only if EGFR expression level (p=0.0152) or copy number (p=0.0050) was low. Comparing neoadjuvantly treated patients and primary resection patients, tumors of non-responder patients more frequently exhibited EGFR overexpression, providing evidence that EGFR is a factor for indicating chemotherapy resistance. EGFR overexpression and gene copy number are independent adverse prognostic factors for neoadjuvant chemotherapy-treated EAC patients, particularly for responders. Furthermore, EGFR overexpression is involved in resistance to cisplatin-based neoadjuvant chemotherapy.

Detection and quantification of Flavobacterium psychrophilum in water and fish tissue samples by quantitative real time PCR.

BACKGROUND Flavobacterium psychrophilum is the agent of Bacterial Cold Water Disease and Rainbow Trout Fry Syndrome, two diseases leading to high mortality. Pathogen detection is mainly carried out using cultures and more rapid and sensitive methods are needed. RESULTS We describe a qPCR technique based on the single copy gene β' DNA-dependent RNA polymerase (rpoC). Its detection limit was 20 gene copies and the quantification limit 103 gene copies per reaction. Tests on spiked spleens with known concentrations of F. psychrophilum (106 to 101 cells per reaction) showed no cross-reactions between the spleen tissue and the primers and probe. Screening of water samples and spleens from symptomless and infected fishes indicated that the pathogen was already present before the outbreaks, but F. psychrophilum was only quantifiable in spleens from diseased fishes. CONCLUSIONS This qPCR can be used as a highly sensitive and specific method to detect F. psychrophilum in different sample types without the need for culturing. qPCR allows a reliable detection and quantification of F. psychrophilum in samples with low pathogen densities. Quantitative data on F. psychrophilum abundance could be useful to investigate risk factors linked to infections and also as early warning system prior to potential devastating outbreak.

Phytoplankton Scales of Variability in the California Current System: 2. Latitudinal Variability

The California Current System encompasses a southward flowing current which is perturbed by ubiquitous mesoscale variability. The extent to which latitudinal patterns of physical variability are reflected in the distribution of biological parameters is poorly known. To investigate the latitudinal distribution of chlorophyll variance, a wavelet analysis is applied to nearly 9 years (October 1997 to July 2006) of 1-km-resolution Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll concentration data at 5-day resolution. Peaks in the latitudinal distribution of chlorophyll variance coincide with features of the coastal topography. Maxima in variance are located offshore of Vancouver Island and downstream of Heceta Bank, Cape Blanco, Point Arena, and possibly Point Conception. An analysis of dominant wavelengths in the chlorophyll data reveals a transfer of energy into smaller scales is generated in the vicinity of the coastal capes. The latitudinal distribution of variance in sea level anomaly corresponds closely to the chlorophyll variance in the nearshore region (<100 km offshore), suggesting that the same processes determine the distribution of both. Farther offshore, there is no correspondence between latitudinal patterns of sea level anomaly and chlorophyll variance. This likely represents a transition from physical to biological control of the phytoplankton distribution.

INTEGRATIVE BIOMARKER IDENTIFICATION AND CLASSIFICATION USING HIGH THROUGHPUT ASSAYS

It is well accepted that tumorigenesis is a multi-step procedure involving aberrant functioning of genes regulating cell proliferation, differentiation, apoptosis, genome stability, angiogenesis and motility. To obtain a full understanding of tumorigenesis, it is necessary to collect information on all aspects of cell activity. Recent advances in high throughput technologies allow biologists to generate massive amounts of data, more than might have been imagined decades ago. These advances have made it possible to launch comprehensive projects such as (TCGA) and (ICGC) which systematically characterize the molecular fingerprints of cancer cells using gene expression, methylation, copy number, microRNA and SNP microarrays as well as next generation sequencing assays interrogating somatic mutation, insertion, deletion, translocation and structural rearrangements. Given the massive amount of data, a major challenge is to integrate information from multiple sources and formulate testable hypotheses. This thesis focuses on developing methodologies for integrative analyses of genomic assays profiled on the same set of samples. We have developed several novel methods for integrative biomarker identification and cancer classification. We introduce a regression-based approach to identify biomarkers predictive to therapy response or survival by integrating multiple assays including gene expression, methylation and copy number data through penalized regression. To identify key cancer-specific genes accounting for multiple mechanisms of regulation, we have developed the integIRTy software that provides robust and reliable inferences about gene alteration by automatically adjusting for sample heterogeneity as well as technical artifacts using Item Response Theory. To cope with the increasing need for accurate cancer diagnosis and individualized therapy, we have developed a robust and powerful algorithm called SIBER to systematically identify bimodally expressed genes using next generation RNAseq data. We have shown that prediction models built from these bimodal genes have the same accuracy as models built from all genes. Further, prediction models with dichotomized gene expression measurements based on their bimodal shapes still perform well. The effectiveness of outcome prediction using discretized signals paves the road for more accurate and interpretable cancer classification by integrating signals from multiple sources.

ILP Experiments in Detecting Traffic Problems

The paper describes experiments in automated acquisition of knowledge in traffic problem detection. Preliminary results show that ILP can be used to successfully learn to detect traffic problems.

Modelización del efecto de la pendiente de la vía sobre el consumo de vehículos turismo

El presente trabajo tiene por objetivo generar una metodología validada que permita predecir el consumo de vehículos turismo circulando en cualquier tramo de vía a partir del perfil orográfico y del diagrama velocidad-tiempo. Para la generación de la metodología, se ha realizado un modelo de simulación con el programa ADVISOR que permite calcular el consumo de combustible para un determinado recorrido en el que se tiene en cuenta el perfil orográfico. Este modelo fue validado con datos reales medidos con equipos on-board y se usó para calcular el consumo de combustible diferencial debido al efecto de la pendiente de la vía, al poderse simular con y sin pendiente. Se realizaron múltiples simulaciones de recorridos con velocidad máxima variable con el fin de obtener un número significativo de datos. Con los resultados de las diferentes simulaciones, se realizó un estudio estadístico, para determinar las variables influyentes y se generó una función estadística (Ecuación de Consumo Estimado – ECE) que permite calcular el consumo de combustible debido a la pendiente de la vía, conociendo el consumo del vehículo en carretera llana (sin pendiente). Esta función estadística generada (ECE), se validó con datos reales medidos en tráfico real. Con el fin de darle generalidad y aplicabilidad a la función generada, y teniendo en cuenta que el consumo de combustible en carretera llana no está siempre disponible, se ha calculado el consumo de combustible sin pendiente utilizando la metodología Copert 4, metodología oficial desarrollada por la Agencia de Medio Ambiente de Europa (EEA) para la estimación de emisiones y consumo de combustible que está basada en datos experimentales pero que no tiene en cuenta la pendiente de la vía. La Ecuación de Consumo Estimado (ECE) aplicada a los consumos calculados por la metodología Copert 4, se valida también usando datos reales medidos en tráfico real y se comprueba que esta función se ajusta considerablemente bien a la realidad, con un error en el consumo acumulado frente al del ensayo real de un 1% y una correlación con el consumo instantáneo del ensayo real de 0,93. Se concluye, que la Función de Consumo Estimado (ECE), permite predecir el efecto de la pendiente sobre el consumo de combustible de un vehículo turismo en tráfico real con un error menor del 1%. Abstract This projects aims to develop a validated methodology that enables to predict cars consumption while circulating at any kind of road section based on its orographic outline and the speed-time diagram. In order to develop this methodology, a simulation model has been performed with the programme ADVISOR, that allows fuel consumption calculation for an specific route in which the orographic outline is considered. This model was validated by real data measured with an on-board equipment and it was used to calculate the differential fuel consumption caused by the effect of the slope on the road, as it was possible to simulate with or without slope. Many simulations were run with routes with variable maximum speed, aiming to obtain a significant amount of data. An statistical study was carried out with the results of those simulations with the purpose to determine the influential variables and an statistical function ( Estimated Consumption Equation – ECE) that enables fuel consumption calculation due to the road’s slope when the consumption of a vehicle on horizontal road (without any slope) is known. This statistical function (ECE) was validated by real data measured in real traffic conditions. With the purpose to generalise the function and increase its applicability, considering that the consumption of a vehicle on horizontal road is not always available, the nonslope fuel consumption has been calculated through Copert 4 methodology, which is the official methodology developed by the European Environmental Agency (EEA) for emissions and fuel consumption calculation based on experimental data, but without taking into consideration the road’s slope. The Estimated Consumption Equation (ECE) applied to the consumption calculated through Copert 4 methodology is also validated using real data measured in real traffic conditions. It was verified that this function considerably adjusts to reality, with an error on the accumulated consumption compared to the real test of 1% and a correlation with the real test immediate fuel consumption of 0,93. It is concluded that the Estimated Consumption Equation (ECE) enables to predict the effect of the slope on the fuel consumption of a car in real traffic conditions with an error less than 1%.

Vehicle induced loads on pedestrian barriers

This paper is a continuation of a previous one, Sanz-Andrés, Santiago-Prowald, Baker and Quinn (J. Wind Eng. Ind. Aerodyn. 91 (2003) 925) concerning the loads generated on a structural panel (traffic sign) by vehicle running along the road, although obviously, the results are also applicable to the effects of other moving vehicles such as trains. The structural panel was modelized as a large plate whose largest dimension is perpendicular to the vehicle motion direction. In this paper a similar approach is used to develop a mathematical model for the vehicle-induced load on pedestrian barriers, modelized as a large plate whose largest dimension is parallel to the vehicle motion direction. The purpose of the work is to develop a model simple enough to give analytical results, although with the physical phenomena correctly accounted for, such as to be able to explain, at least qualitatively, the main characteristics of the phenomenon, as observed in the experiments performed by Quinn et al. (J. Wind Eng. Ind. Aerodyn. 89 (2001) 831). Actually, in spite of the model simplicity, results of the theoretical model show a reasonable good quantitative agreement with the experimental results. The aim of this and previous publications is to provide to the transport infrastructure community with some simple tools that can help to explain, and in some cases also to compute, the unsteady loading produced by moving vehicles on persons and installations placed close to the roads or tracks.

Sentiment classification for early detection of health alerts in the chemical textile domain

In the chemical textile domain experts have to analyse chemical components and substances that might be harmful for their usage in clothing and textiles. Part of this analysis is performed searching opinions and reports people have expressed concerning these products in the Social Web. However, this type of information on the Internet is not as frequent for this domain as for others, so its detection and classification is difficult and time-consuming. Consequently, problems associated to the use of chemical substances in textiles may not be detected early enough, and could lead to health problems, such as allergies or burns. In this paper, we propose a framework able to detect, retrieve, and classify subjective sentences related to the chemical textile domain, that could be integrated into a wider health surveillance system. We also describe the creation of several datasets with opinions from this domain, the experiments performed using machine learning techniques and different lexical resources such as WordNet, and the evaluation focusing on the sentiment classification, and complaint detection (i.e., negativity). Despite the challenges involved in this domain, our approach obtains promising results with an F-score of 65% for polarity classification and 82% for complaint detection.

A Bayesian approach to imposing curvature on distance functions

The estimated parameters of output distance functions frequently violate the monotonicity, quasi-convexity and convexity constraints implied by economic theory, leading to estimated elasticities and shadow prices that are incorrectly signed, and ultimately to perverse conclusions concerning the effects of input and output changes on productivity growth and relative efficiency levels. We show how a Bayesian approach can be used to impose these constraints on the parameters of a translog output distance function. Implementing the approach involves the use of a Gibbs sampler with data augmentation. A Metropolis-Hastings algorithm is also used within the Gibbs to simulate observations from truncated pdfs. Our methods are developed for the case where panel data is available and technical inefficiency effects are assumed to be time-invariant. Two models-a fixed effects model and a random effects model-are developed and applied to panel data on 17 European railways. We observe significant changes in estimated elasticities and shadow price ratios when regularity restrictions are imposed. (c) 2004 Elsevier B.V. All rights reserved.

Modelling the dynamics of cutting during turning

This thesis presents an approach to cutting dynamics during turning based upon the mechanism of deformation of work material around the tool nose known as "ploughing". Starting from the shearing process in the cutting zone and accounting for "ploughing", new mathematical models relating turning force components to cutting conditions, tool geometry and tool vibration are developed. These models are developed separately for steady state and for oscillatory turning with new and worn tools. Experimental results are used to determine mathematical functions expressing the parameters introduced by the steady state model in the case of a new tool. The form of these functions are of general validity though their coefficients are dependent on work and tool materials. Good agreement is achieved between experimental and predicted forces. The model is extended on one hand to include different work material by introducing a hardness factor. The model provides good predictions when predicted forces are compared to present and published experimental results. On the other hand, the extension of the ploughing model to taming with a worn edge showed the ability of the model in predicting machining forces during steady state turning with the worn flank of the tool. In the development of the dynamic models, the dynamic turning force equations define the cutting process as being a system for which vibration of the tool tip in the feed direction is the input and measured forces are the output The model takes into account the shear plane oscillation and the cutting configuration variation in response to tool motion. Theoretical expressions of the turning forces are obtained for new and worn cutting edges. The dynamic analysis revealed the interaction between the cutting mechanism and the machine tool structure. The effect of the machine tool and tool post is accounted for by using experimental data of the transfer function of the tool post system. Steady state coefficients are corrected to include the changes in the cutting configuration with tool vibration and are used in the dynamic model. A series of oscillatory cutting tests at various conditions and various tool flank wear levels are carried out and experimental results are compared with model—predicted forces. Good agreement between predictions and experiments were achieved over a wide range of cutting conditions. This research bridges the gap between the analysis of vibration and turning forces in turning. It offers an explicit expression of the dynamic turning force generated during machining and highlights the relationships between tool wear, tool vibration and turning force. Spectral analysis of tool acceleration and turning force components led to define an "Inertance Power Ratio" as a flank wear monitoring factor. A formulation of an on—line flank wear monitoring methodology is presented and shows how the results of the present model can be applied to practical in—process tool wear monitoring in • turning operations.

Quasi-lossless data transmission with ultra-long Raman fibre laser based amplification

The project consists of an experimental and numerical modelling study of the applications of ultra-long Raman fibre laser (URFL) based amplification techniques for high-speed multi-wavelength optical communications systems. The research is focused in telecommunications C-band 40 Gb/s transmission data rates with direct and coherent detection. The optical transmission performance of URFL based systems in terms of optical noise, gain bandwidth and gain flatness for different system configurations is evaluated. Systems with different overall span lengths, transmission fibre types and data modulation formats are investigated. Performance is compared with conventional Erbium doped fibre amplifier based system to evaluate system configurations where URFL based amplification provide performance or commercial advantages.

Quality-driven resource utilization methods for video streaming in wireless communication networks

This research is focused on the optimisation of resource utilisation in wireless mobile networks with the consideration of the users’ experienced quality of video streaming services. The study specifically considers the new generation of mobile communication networks, i.e. 4G-LTE, as the main research context. The background study provides an overview of the main properties of the relevant technologies investigated. These include video streaming protocols and networks, video service quality assessment methods, the infrastructure and related functionalities of LTE, and resource allocation algorithms in mobile communication systems. A mathematical model based on an objective and no-reference quality assessment metric for video streaming, namely Pause Intensity, is developed in this work for the evaluation of the continuity of streaming services. The analytical model is verified by extensive simulation and subjective testing on the joint impairment effects of the pause duration and pause frequency. Various types of the video contents and different levels of the impairments have been used in the process of validation tests. It has been shown that Pause Intensity is closely correlated with the subjective quality measurement in terms of the Mean Opinion Score and this correlation property is content independent. Based on the Pause Intensity metric, an optimised resource allocation approach is proposed for the given user requirements, communication system specifications and network performances. This approach concerns both system efficiency and fairness when establishing appropriate resource allocation algorithms, together with the consideration of the correlation between the required and allocated data rates per user. Pause Intensity plays a key role here, representing the required level of Quality of Experience (QoE) to ensure the best balance between system efficiency and fairness. The 3GPP Long Term Evolution (LTE) system is used as the main application environment where the proposed research framework is examined and the results are compared with existing scheduling methods on the achievable fairness, efficiency and correlation. Adaptive video streaming technologies are also investigated and combined with our initiatives on determining the distribution of QoE performance across the network. The resulting scheduling process is controlled through the prioritization of users by considering their perceived quality for the services received. Meanwhile, a trade-off between fairness and efficiency is maintained through an online adjustment of the scheduler’s parameters. Furthermore, Pause Intensity is applied to act as a regulator to realise the rate adaptation function during the end user’s playback of the adaptive streaming service. The adaptive rates under various channel conditions and the shape of the QoE distribution amongst the users for different scheduling policies have been demonstrated in the context of LTE. Finally, the work for interworking between mobile communication system at the macro-cell level and the different deployments of WiFi technologies throughout the macro-cell is presented. A QoEdriven approach is proposed to analyse the offloading mechanism of the user’s data (e.g. video traffic) while the new rate distribution algorithm reshapes the network capacity across the macrocell. The scheduling policy derived is used to regulate the performance of the resource allocation across the fair-efficient spectrum. The associated offloading mechanism can properly control the number of the users within the coverages of the macro-cell base station and each of the WiFi access points involved. The performance of the non-seamless and user-controlled mobile traffic offloading (through the mobile WiFi devices) has been evaluated and compared with that of the standard operator-controlled WiFi hotspots.

New business strategies of football clubs

The study investigates new strategies of football clubs in function of last few years’ trends in European football leagues. There were many changes in international professional football during the last 10-15 years that had significant effect on the success of certain clubs. We show empirical evidences about these effects based on data about revenues, transfer balance, financial and sport successes. We focus on Western European leagues and classify clubs based on their business and sport strategies.