This work presents a new technique for automatic detection of marine vehicles in images and video of open sea. Users of such system include border guards, military, port safety, flow management, and sanctuary protection personnel. The source of images and video is a digital camera or a camcorder which is placed on a buoy or stationary mounted in a harbor facility. The system is intended to work autonomously, taking images of the surrounding ocean surface and analyzing them for the presence of marine vehicles. The goal of the system is to detect an approximate window around the ship. The proposed computer vision-based algorithm combines a horizon detection method with edge detection and postprocessing. Several datasets of still images are used to evaluate the performance of the proposed technique. For video sequences the original algorithm is further enhanced with a tracking algorithm that uses Kalman filter. A separate dataset of 30 video sequences 10 seconds each is used to test its performance. Promising results of the detection of ships are discussed and necessary improvements for achieving better performance are suggested.

There is a lack of research in the area of hedging future contracts, especially in illiquid or very volatile market conditions. It is important to understand the volatility of the oil and currency markets because reduced fluctuations in these markets could lead to better hedging performance. This study compared different hedging methods by using a hedging error metric, supplementing the Receding Horizontal Control and Stochastic Programming (RHCSP) method by utilizing the London Interbank Offered Rate with the Levy process. The RHCSP hedging method was investigated to determine if improved hedging error was accomplished compared to the Black-Scholes, Leland, and Whalley and Wilmott methods when applied on simulated, oil, and currency futures markets. A modified RHCSP method was also investigated to determine if this method could significantly reduce hedging error under extreme market illiquidity conditions when applied on simulated, oil, and currency futures markets. This quantitative study used chaos theory and emergence for its theoretical foundation. An experimental research method was utilized for this study with a sample size of 506 hedging errors pertaining to historical and simulation data. The historical data were from January 1, 2005 through December 31, 2012. The modified RHCSP method was found to significantly reduce hedging error for the oil and currency market futures by the use of a 2-way ANOVA with a t test and post hoc Tukey test. This study promotes positive social change by identifying better risk controls for investment portfolios and illustrating how to benefit from high volatility in markets. Economists, professional investment managers, and independent investors could benefit from the findings of this study.

The Gulf of Mexico commercial reef fish fishery has experienced significant management changes and disturbance in recent years, including transitioning two major fisheries from a traditional open access system into a limited entry individual fishing quota (IFQ) system in 2007 and 2010. Also in 2010, the Deepwater Horizon oil spill (DWH) released an estimated 4.9 million barrels of oil into the Gulf (~206 million U.S. gallons), and is still the largest U.S. environmental disaster to date. Emergency fishing closures initiated shortly after the oil spill began were successful in keeping tainted seafood from reaching markets. However, effects of DWH closures on fisher decision making, fishery productivity, and distribution of fishing effort all remain poorly understood. Understanding the range and magnitude of fishers’ responses to perturbations — including regulatory change and human-induced environmental disasters — is critical for designing effective management and disaster response policies that can meet biological, ecological, economic, social, and sustainability objectives. This work characterized the spatial and temporal patterns of productivity and fishing effort for the Gulf of Mexico (GoM) commercial reef fish fishery. Patterns of productivity and effort distribution were used to examine the response of fishers to management change and large-scale disturbance, namely the DWH fishing closures. Fisheries-dependent logbook trip reports were used to quantify revenue and catch-per-unit-effort (CPUE) patterns from 2000-2014. Novel to fisheries work in the GoM, complementary vessel monitoring systems (VMS) satellite tracking data were used to quantify high-resolution spatial distribution patterns over time, relative to the DWH fishing closures. A general linear modeling (GLM) approach was also used to examine which variables may have contributed to resilience of fishers after DWH closures. Results suggested that this fishery was largely resilient to the DWH fishing closures in 2010, although exact outcomes varied by region. Overall fleet-level productivity steadily increased over time, but regional patterns were based on major species in catch. Productivity in the western GoM was consistently highest over time, and trips in the west and central GoM were dominated by Red snapper (Lutjanus campechanus) and Vermilion snapper (Rhomboplites aurorubens). Trips in the east were dominated by Red grouper (Epinephelus morio) and Gag grouper (Mycteroperca microlepis). Shifts in spatial distribution to new productive fishing grounds or reduced competition via fewer vessels or trips may explain the increases in productivity observed over the study period. Consolidation in the fleet was apparent, with fewer individual vessels and fewer total trips over time. However, the rate of vessel drop out after DWH (5%) was far below the annual background attrition rate of ~14-20%. Relative productivity patterns inside vs. outside the boundaries of fishing closures did not change over time, and there were even some increases in productivity observed during and after DWH in the eastern GoM. Yet, vessels that dropped out after DWH were concentrated in the north-central and eastern GoM. Distribution of fishing grounds before and after DWH were highly similar, and there were increases in effort along the outer West Florida Shelf. Variability in revenue and CPUE, CPUE magnitude, and magnitude of grouper landings were significant predictors of dropping out of the fishery in the GLMs. Synergies with the Red snapper or Grouper-Tilefish IFQs may have “primed” the fishery for resilience by eliminating inconsistent or marginal fishers before the oil spill, and may further explain some of the spatially varying patterns of productivity and attrition after 2010. Resilience was likely also enhanced by the more than $2 billion in emergency compensation payments made to captains, crew, and vessel owners for lost fishing income and assistance with oil remediation efforts. This work stands to make a significant contribution to our understanding of how the DWH oil spill impacted fisheries and communities in the GoM. The results add to a growing body of literature suggesting that the acute population- and ecosystem-level impacts of the DWH oil spill were not as strong or severe as initially anticipated. This work also stands to make contributions to the broader understanding of how this fishery has performed in the wake of recent management change and major environmental disturbance.

Les déplacements à bord de véhicules de locomotion induisent souvent des stimulations sensorielles à l'origine d'illusions perceptives. Ces perceptions erronées de la position du corps ont été décrites dans la littérature sous le terme de désorientation spatiale, dont l'origine est principalement considérée comme otolithique. En effet, lors d'une accélération linéaire constante vers l'avant, le vecteur résultant de l'accélération imposée et de la gravité n'est plus aligné par rapport à la verticale gravitaire. Comme tout autre accéléromètre physique, le système otolithique ne peut différencier la gravité de toute autre accélération linéaire et va ainsi intégrer ce vecteur résultant, appelé accélération gravito-inertielle (AGI), comme la nouvelle verticale. Parmi les incidences comportementales les plus connues figurent les illusions d'élévation et oculogravique. Ces illusions se traduisent par une perception visuelle erronée de la position des objets en milieu d'hyperpesanteur. Ce travail doctoral s'intéresse i) aux sources d'informations sensorielles déterminantes dans les illusions perceptives en milieu d'hyperpesanteur, ii) aux différences inter-individuelles dans l'estimation de l'horizon visuel, et iii) au rôle des références égocentrée et exocentrée impliquées dans les illusions d'élévation et oculogravique. Nos résultats expérimentaux mettent en évidence : (1) le rôle fondamental de l'intensité gravito-inertielle dans la perception de l'horizon visuel, (2) l'effet couplé de l'orientation corporelle et de la perception visuelle égocentrée dans l'estimation de l'horizon visuel, (3) l'explication en termes otolithiques des différences inter-individuelles conséquentes à la modulation de l'intensité gravito-inertielle, (4) l'apport des informations somesthésiques, notamment pour l'illusion oculogravique. L'ensemble des travaux rapportés dans cette thèse suggère une approche sensorielle en termes otolithique et somesthésique, ainsi qu'une approche individuelle de la perception de l'horizon visuel gravitaire.

As air traffic congestion grows, air traffic flow management (ATFM) is becoming a great concern. ATFM deals with air traffic and the efficient utilization of the airport and airspace. Air traffic efficiency is heavily influenced by unanticipated factors, or uncertainties, which can come from several sources such as mechanical breakdown; however, weather is the main unavoidable cause of uncertainty. Because weather is unpredictable, it poses a critical challenge for ATFM in current airport and airspace operations. Convective weather results in congestion at airports as well as in airspace sectors. During times of congestion, the decision as how and when to send aircraft toward an airspace sector in the presence of weather is difficult. To approach this problem, we first propose a two-stage stochastic integer program by emphasizing a given single sector. By considering ground delay, cancellation, and cruise speed for each flight on the ground in the first stage, as well as air holding and diversion recourse actions for each flight in the air in the second stage, our model determines how aircraft are sent toward a sector under the uncertainty of weather. However, due to the large number of weather scenarios, the model is intractable in practice. To overcome the intractability, we suggest a rolling horizon method to solve the problem to near optimal. Lagrangian relaxation and subgradient method are used to justify the rolling horizon method. Since the rolling horizon method can be solved in real time, we can apply it to actual aircraft schedules to reduce the costs incurred on the ground as well as in airspace. We then extend our two-stage model to a multistage stochastic program, which increases the number of possible weather realizations and results a more efficient schedule in terms of costs. The rolling horizon method as well as Lagrangian relaxation and subgradient method are applied to this multistage model. An overall comparison among the previously described methodologies are presented.

Ce travail s'inscrit principalement dans le domaine de synthèse d'observateurs pour des synthèses non linéaires. D'une part le développement d'une nouvelle méthodologie de synthèse est proposée et d'autre part des résultats supplémentaires pour les observateurs à horizon glissant sont donnés. La première partie est plus directement dédiée aux rappels des notions de base d'observabilité des systèmes linéaires et non linéaires, ainsi qu'à la description des principales techniques de synthèse d'observateurs. De cette étude, il a été possible d'énoncer les avantages et les inconvénients de chaque méthode. Dans une deuxième partie et grâce à l'étude des différentes techniques de synthèse, une nouvelle méthodologie de synthèse d'observateur pour des systèmes non linéaires a été développée. Cette méthodologie divise un systhème en [n] problèmes d'optimisation scalaires, dénommés problèmes élémentaires, qui peuvent être résolus en parallèle en utilisant un solveur numérique de l'équation de Hamilton-Jacobi sclaire que pour de systèmes de grand ordre peut être très interessant de l'appliquer. La dernière partie est concentrée sur les observateurs à horizon glissant plus classiques et de traiter le cas où les hypothèses de régularité uniforme globale ne sont pas supposées. la description technique correspondante est donné à travers des définitions du rayon de régularité et du rayon d'observabilité.

Cette thèse propose une méthode originale d'estimation ensembliste d'états de procédés nonlinéaires discrets, qui est globalement convergente. La méthode est basée sur une technique d'estimation à horizon glissant par intervalles (IMHSE), couplé à une technique d'optimisation globale de fonctions non-linéaires qui utilise l'arithmétique par intervalles. En d'autres termes, la méthode IMHSE résout le problème d'estimation d'état d'un système dynamique par un problème statique d'optimisation globale non-linéaire par intervalles, sur un horizon de temps prédéfini. Les mesures faites hors ligne dans un procédé peuvent être utilisées facilement dans cet observateur ensembliste pour reconstruire les variables de l'état qui sont représentés par intervalles. Ce travail considère aussi la détection de dysfonctionnement d'un modèle en utilisant un observateur IMHSE multi-modèles (une propriété de plus donnée à notre observateur). L'objectif de cette approche multi-modèles est de détecter les variations dynamiques des paramètres du modèle dans le temps. Ces variations sont prises en considération en utilisant plusieurs modèles différents. Ces modèles seront commutés par notre observateur ensembliste pour reconstruire les états du système. Mis d'une façon simple, cette approche consiste à utiliser un modèle nominal pour l'état et d'autres modèles pour décrire les situations possibles de fonctionnement anormal (paramètres perturbés). L'algorithme nous permet de connaître en ligne quel est le meilleur modèle qui décrit le comportement réel du système. La technique proposée a été appliquée sur des modèles de procédés complexes biotechnologiques tel que la fermentation sur substrat solide, et à des bioprocédés décrit par des modèles hybrides. Les résultats obtenus par simulation montrent que ce type d'observateur a des avantages sur les autres observateurs et filtres, et qu'il peut être facilement appliqué dans un contexte industriel.

Waterflooding is a common type of oil recovery techniques where water is pumped into the reservoir for increased productivity. Reservoir states change with time, as such, different injection and production settings will be required to lead the process to optimal operation which is actually a dynamic optimization problem. This could be solved through optimal control techniques which traditionally can only provide an open-loop solution. However, this solution is not appropriate for reservoir production due to numerous uncertain properties involved. Models that are updated through the current industrial practice of ‘history matching’ may fail to predict reality correctly and therefore, solutions based on history-matched models may be suboptimal or non-optimal at all. Due to its ability in counteracting the effects uncertainties, direct feedback control has been proposed recently for optimal waterflooding operations. In this work, two feedback approaches were developed for waterflooding process optimization. The first approach is based on the principle of receding horizon control (RHC) while the second is a new dynamic optimization method developed from the technique of self-optimizing control (SOC). For the SOC methodology, appropriate controlled variables (CVs) as combinations of measurement histories and manipulated variables are first derived through regression based on simulation data obtained from a nominal model. Then the optimal feedback control law was represented as a linear function of measurement histories from the CVs obtained. Based on simulation studies, the RHC approach was found to be very sensitive to uncertainties when the nominal model differed significantly from the conceived real reservoir. The SOC methodology on the other hand, was shown to achieve an operational profit with only 2% worse than the true optimal control, but 30% better than the open-loop optimal control under the same uncertainties. The simplicity of the developed SOC approach coupled with its robustness to handle uncertainties proved its potentials to real industrial applications.

Visual surveillance in the maritime domain has been explored for more than a decade. Although it has produced a number of working systems and resulted in a mature technology, surveillance has been restricted to the port facilities or areas close to the coastline assuming a fixed-camera scenario. This dissertation presents several contributions in the domain of maritime surveillance. First, a novel algorithm for open-sea visual maritime surveillance is introduced. We explore a challenging situation with a camera mounted on a buoy or other floating platform. The developed algorithm detects, localizes, and tracks ships in the field of view of the camera. Specifically, our method is uniquely designed to handle a rapidly moving camera. Its performance is robust in the presence of a random relatively-large camera motion. In the context of ship detection, a new horizon detection scheme for a complex maritime domain is also developed. Second, the performance of the ship detection algorithm is evaluated on a dataset of 55,000 images. Accuracy of detection of up to 88% of ships is achieved. Lastly, we consider the topic of detection of the vanishing line of the ocean surface plane as a way to estimate the horizon in difficult situations. This allows extension of the ship-detection algorithm to beyond open-sea scenarios.

Outdoor workers are often subjected to thermal conditions beyond the comfort zone, but to what degree do such conditions affect the health and safety of those workers is still a matter requiring further investigation. The purpose of this study is to examine the relationship between thermal conditions and (1) heat-related disorders and (2) acute injuries using injury and illness data collected during the BP Deepwater Horizon clean-up operations. Over an eleven month period, 5,485 cases were identified as either heat-related or an acute injury (incident type) and further divided by severity. Daily weather data were used to estimate the wet bulb globe temperature (WBGT) based on the time of day. Heat Stress Levels intervals were defined using the estimated WBGT. Labor-hours by month were estimated by the prevailing shift length in the month and the number of workers. The incidents were assigned a Heat Stress Level and the number of labor-hours by heat stress level were determined. The next step was to calculate the incident rate ratio by Heat Stress Level against the baseline of thermal comfort. The results indicated that the rate ratios for heat-related disorders and acute injury increased for thermal conditions from 24⁰C-WBGT to 30⁰C-WBGT. There was a further significant increase in rate ratio for heat-related injury above 33 °C-WBGT. It was notable that the incident rates for both heat-related disorders and acute injuries increased at thermal conditions generally considered to be below the occupational exposure limit (OEL) at 30 ⁰C-WBGT. The rate of heat-related disorders increased substantially above the occupational exposure limit.