The multitude of services delivered over the Internet would have been difficult to fathom 40 years ago when much of the initial design was being undertaken. As a consequence, the resulting architecture did not make provisions for differentiating between, and managing the potentially conflicting requirements of different types of services such as real-time voice communication and peer-to-peer file sharing. This shortcoming has resulted in a situation whereby services with conflicting requirements often interfere with each other and ultimately decrease the effectiveness of the Internet as an enabler of new and transformative services. The ability to passively identify different types of Internet traffic then would address this shortcoming and enable effective management of conflicting types of services, in addition to facilitating a better understanding of how the Internet is used in general. Recent attempts at developing such techniques have shown promising results in simulation environments but perform considerably worse when deployed into real-world scenarios. One possible reason for this descrepancy can be attributed to the implicit assumption shared by recent approaches regarding the degree of similarity between the many networks which comprise the Internet. This thesis quantifies the degradation in performance which can be expected when such an assumption is violated as well as demonstrating alternative classification techniques which are less sensitive to such violations.

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This thesis investigates the influence of predator movements upon habitat selection and foraging success. It deals with two very distinct datasets one from a marine system, the snow crab (Chionoecetes opilio) fishery, and the second from a freshwater system, an experimental rainbow trout (Oncorhynchus mykiss) aquaculture operation. Deriving a standardized measure of catch from logbook data is important because catch per unit effort (CPUE) is used in fisheries analysis to estimate abundance, but it some cases CPUE is a biased estimate. For the snow crab fishery, a relative abundance measure was developed using fisher movements and logbook data that reflected commercially available biomass and produced an improved relative abundance estimate. Results from the aquaculture dataset indicate that escaped farmed rainbow trout continue to use the cage site when waste feed is available, while native lake trout do not interact with the cage. Once access to waste feed is removed, both lake trout and escaped rainbow trout do not use the cage site. This thesis uses methods to identify patterns and behaviours using movement tracks to increase our understanding of predator habitat usage.

Ce travail de thèse poursuit une perspective double dans l'usage conjoint des méthodes de Monte Carlo séquentielles (MMS) et de l'algorithme Espérance-Maximisation (EM) dans le cadre des modèles de Markov cachés présentant une structure de dépendance markovienne d'ordre supérieur à 1 au niveau de la composante inobservée. Tout d'abord, nous commençons par un exposé succinct de l'assise théorique des deux concepts statistiques à travers les chapitres 1 et 2 qui leurs sont consacrés. Dans un second temps, nous nous intéressons à la mise en pratique simultanée des deux concepts au chapitre 3 et ce dans le cadre usuel où la structure de dépendance est d'ordre 1. L'apport des méthodes MMS dans ce travail réside dans leur capacité à approximer efficacement des fonctionnelles conditionnelles bornées, notamment des quantités de filtrage et de lissage dans un cadre non linéaire et non gaussien. Quant à l'algorithme EM, il est motivé par la présence à la fois de variables observables et inobservables (ou partiellement observées) dans les modèles de Markov Cachés et singulièrement les mdèles de volatilité stochastique étudié. Après avoir présenté aussi bien l'algorithme EM que les méthodes MCs ainsi que quelques unes de leurs propriétés dans les chapitres 1 et 2 respectivement, nous illustrons ces deux outils statistiques au travers de la calibration d'un modèle de volatilité stochastique. Cette application est effectuée pour des taux change ainsi que pour quelques indices boursiers au chapitre 3. Nous concluons ce chapitre sur un léger écart du modèle de volatilité stochastique canonique utilisé ainsi que des simulations de Monte Carlo portant sur le modèle résultant. Enfin, nous nous efforçons dans les chapitres 4 et 5 à fournir les assises théoriques et pratiques de l'extension des méthodes Monte Carlo séquentielles notamment le filtrage et le lissage particulaire lorsque la structure markovienne est plus prononcée. En guise d'illustration, nous donnons l'exemple d'un modèle de volatilité stochastique dégénéré dont une approximation présente une telle propriété de dépendance.

The fast clearing of faults is essential for preventing equipment damage and preserving the stability of the power transmission systems with smaller operating margins. This thesis examined the application of fault generated transients for fast detection and isolation of faults in a transmission system. The basis of the transient based protection scheme developed and implemented in this thesis is the fault current directions identified by a set of relays located at different nodes of the system. The direction of the fault currents relative to a relay location is determined by comparing the signs of the wavelet coefficients of the currents measured in all branches connected to the node. The faulted segment can be identified by combining the fault directions identified at different locations in the system. In order to facilitate this, each relay is linked with the relays located at the adjacent nodes through a telecommunication network. In order to prevent possible malfunctioning of relays due to transients originating from non-fault related events, a transient recognition system to supervise the relays is proposed. The applicability of different classification methods to develop a reliable transient recognition system was examined. A Hidden Markov Model classifier that utilizes the energies associated with the wavelet coefficients of the measured currents as input features was selected as the most suitable solution. Performance of the protection scheme was evaluated using a high voltage transmission system simulated in PSCAD/EMTDC simulation software. The custom models required to simulate the complete protection scheme were implemented in PSCAD/EMTDC. The effects of various factors such as fault impedance, signal noise, fault inception angle and current transformer saturation were investigated. The performance of the protection scheme was also tested with the field recorded signals. Hardware prototypes of the fault direction identification scheme and the transient classification system were implemented and tested under different practical scenarios using input signals generated with a real-time waveform playback instrument. The test results presented in this thesis successfully demonstrate the potential of using transient signals embedded in currents for detection, localization and recognition of faults in transmission networks in a fast and reliable manner.

The automotive industry is growing bigger each year. The central concern for any automotive company is driver and passenger safety. Many automotive companies have developed driver assistance systems, to help the driver and to ensure driver safety. These systems include adaptive cruise control, lane departure warning, lane change assistance, collision avoidance, night vision, automatic parking, traffic sign recognition, and driver fatigue detection. In this thesis, we aim to build a driver fatigue detection system that advances the research in this area. Using vision in detecting driver fatigue is commonly the key part for driver fatigue detection systems. We have decided to investigate different direction. We examine the driver's voice, heart rate, and driving performance to assess fatigue level. The system consists of three main modules: the audio module, the heart rate and other signals module, and the Bayesian network module. The audio module analyzes an audio recording of a driver and tries to estimate the level of fatigue for the driver. A Voice Activity Detection (VAD) module is used to extract driver speech from the audio recording. Mel-Frequency Cepstrum Coefficients, (MFCC) features are extracted from the speech signal, and then Support Vector Machines (SVM) and Hidden Markov Models (HMM) classifiers are used to detect driver fatigue. Both classifiers are tuned for best performance, and the performance of both classifiers is reported and compared. The heart rate and other signals module uses heart rate, steering wheel position, and the positions of the accelerator, brake, and clutch pedals to detect the level of fatigue. These signals' sample rates are then adjusted to match, allowing simple features to be extracted from the signals, and SVM and HMM classifiers are used to detect fatigue level. The performance of both classifiers is reported and compared. Bayesian networks' abilities to capture dependencies and uncertainty make them a sound choice to perform the data fusion. Prior information (Day/Night driving and previous decision) is also incorporated into the network to improve the final decision. The accuracies of the audio and heart rate and other signals modules are used to calculate certain CPTs for the Bayesian network, while the rest of the CPTs are calculated subjectively. The inference queries are calculated using the variable elimination algorithm. For those time steps where the audio module decision is absent, a window is defined and the last decision within this window is used as a current decision. The performance of the system is assessed based on the average accuracy per second. A dataset was built to train and test the system. The experimental results show that the system is very promising. The performance of the system was assessed based on the average accuracy per second; the total accuracy of the system is 90.5%. The system design can be easily improved by easily integrating more modules into the Bayesian network.

This thesis investigates the influence of predator movements upon habitat selection and foraging success. It deals with two very distinct datasets one from a marine system, the snow crab (Chionoecetes opilio) fishery, and the second from a freshwater system, an experimental rainbow trout (Oncorhynchus mykiss) aquaculture operation. Deriving a standardized measure of catch from logbook data is important because catch per unit effort (CPUE) is used in fisheries analysis to estimate abundance, but it some cases CPUE is a biased estimate. For the snow crab fishery, a relative abundance measure was developed using fisher movements and logbook data that reflected commercially available biomass and produced an improved relative abundance estimate. Results from the aquaculture dataset indicate that escaped farmed rainbow trout continue to use the cage site when waste feed is available, while native lake trout do not interact with the cage. Once access to waste feed is removed, both lake trout and escaped rainbow trout do not use the cage site. This thesis uses methods to identify patterns and behaviours using movement tracks to increase our understanding of predator habitat usage.

In this work we investigated the in vivo and in vitro ecological conditions that can favour the fumonisin production, both free and hidden forms, in the maize-Fusarium verticillioides pathosystem. Samples of different maize hybrids have been collected from dough to the harvest maturity to follow the trend of fungal incidence and both fumonisin forms contamination, but also the changes in chemical composition. Differences in the level of contamination have been found among hybrids during the growing season. Furthermore, the production of fumonisins has been found correlated to the total lipids content, another parameter that changed during the growing season. This finding underlined the existence of a relationship between toxin contamination and fatty acids composition of the hybrids. Recently the existence of a cross talk between plant and pathogen has been demonstrated, based on some oxidized signal molecules (oxylipins) produced from fatty acid precursors. This result was also confirmed by the molecular analysis on the in vitro pathosystem that showed differences in the activation of the genes involved in plant and fungal oxylipins production during the incubation time. Also post-harvest contamination of maize was investigated in this study, with particular attention to the effects of the drying treatment, a common post-harvest practice aimed at decreasing the water availability, and to the storage capacity of a new low cost storage system, silo bag. The drying treatment was showed to affect fumonisins content, in particular an increased fumonisins contamination was detected after heat treatments. This increment seemed to be produced by chemical changes of matrix components, caused by high temperature, that produced the release of hidden fumonisin in free form. Silo bags were shown to be an effective system to store cereals because no significant change occurred in fungi or toxins contamination during a 9-month storage. Therefore, being more flexible and less expensive than traditional store houses, they should be very useful for farmers.

The fast clearing of faults is essential for preventing equipment damage and preserving the stability of the power transmission systems with smaller operating margins. This thesis examined the application of fault generated transients for fast detection and isolation of faults in a transmission system. The basis of the transient based protection scheme developed and implemented in this thesis is the fault current directions identified by a set of relays located at different nodes of the system. The direction of the fault currents relative to a relay location is determined by comparing the signs of the wavelet coefficients of the currents measured in all branches connected to the node. The faulted segment can be identified by combining the fault directions identified at different locations in the system. In order to facilitate this, each relay is linked with the relays located at the adjacent nodes through a telecommunication network. In order to prevent possible malfunctioning of relays due to transients originating from non-fault related events, a transient recognition system to supervise the relays is proposed. The applicability of different classification methods to develop a reliable transient recognition system was examined. A Hidden Markov Model classifier that utilizes the energies associated with the wavelet coefficients of the measured currents as input features was selected as the most suitable solution. Performance of the protection scheme was evaluated using a high voltage transmission system simulated in PSCAD/EMTDC simulation software. The custom models required to simulate the complete protection scheme were implemented in PSCAD/EMTDC. The effects of various factors such as fault impedance, signal noise, fault inception angle and current transformer saturation were investigated. The performance of the protection scheme was also tested with the field recorded signals. Hardware prototypes of the fault direction identification scheme and the transient classification system were implemented and tested under different practical scenarios using input signals generated with a real-time waveform playback instrument. The test results presented in this thesis successfully demonstrate the potential of using transient signals embedded in currents for detection, localization and recognition of faults in transmission networks in a fast and reliable manner.

Improving the performance of the wireless multihop ad hoc networks faces several challenges. In omni-directional antenna based solutions, the use of the RTS/CTS mechanism does not completely eliminate the hidden-terminal and exposed-terminal problems. Deafness is an additional challenge to the directional antenna based solutions. This dissertation, first develops analytical models for quantifying the throughput and delay in wireless multihop ad hoc networks. The models consider the impact of hidden terminals using the realistic signal to interference and noise ratio model and consider random node distribution. The proposed analysis is applicable to many wireless MAC protocols and applications. The analytical results reveal several important issues. The first issue is quantifying the impact of adjusting the transmission range on the throughput and delay in wireless multihop ad hoc networks. The other issue is the hidden terminal region is closely related to the distance between the transmitter and the receiver. Thus, it is possible to adjust the transmission range to optimize the whole network performance. These results provide important guidelines for network planning and protocol optimization in wireless multihop ad hoc networks. Second, it proposes a new Enhanced Busy-tone Multiple Access (EBTMA) medium access control (MAC) protocol for minimizing the negative impact of both the hidden-terminal and the exposed-terminal problems. The new protocol can also enhance the reliability of packet broadcasts and multicasts which are important for many network control functions such as routing. Different from other busy-tone assisted MAC protocols, the protocol uses a non-interfering busy-tone signal in a short period of time, in order to notify all hidden terminals without blocking a large number of nodes for a long time. In addition, the proposed EBTMA protocol can co-exist with the existing 802.11 MAC protocol, so it can be incrementally deployed. Third, it investigates how to support the directional antennas in ad hoc multihop networks for achieving higher spatial multiplexing gain and thus higher network throughput. A new MAC protocol called Dual Sensing Directional MAC (DSDMAC) protocol for wireless ad hoc networks with directional antennas is proposed. The proposed protocol differs from the existing protocols by relying on a dual sensing strategy to identify deafness, resolve the hidden-terminal problem and to avoid unnecessary blocking. Finally, this dissertation provides important results that help for network planning and protocol optimization in wireless multihop ad hoc networks in quantifying the impact of transmission range on the throughput and the delay. The accuracy of these results has been verified with extensive discrete event simulations. / Graduate