Mooring systems for floating facilities that are used offshore to produce oil and gas, consisting of individual mooring lines and foundations, are currently designed on the basis of individual components and on a case-by-case basis. The most heavily loaded line and anchor are checked under extreme loading conditions (hurricane and loop current) with the system of lines intact and with one line removed. However, the performance of the entire mooring system depends more directly on the performance of the system of lines and foundations rather than on the performance of a single component. In this study, a floating production system design originally developed by the industry consortium, DeepStar, was chosen for study. The mooring system was designed for three different nominal water depths: 1000, 2000 and 3000 m. It is a classic spar with steel mooring lines in 1000 m of water and polyester mooring lines in deeper depths. Based on simulated results of loads on mooring lines and foundations using a numerical model, reliability analyses were conducted using representative probabilistic descriptions of the extreme met-ocean conditions, hurricanes and loop currents, in the Gulf of Mexico. The probability of failure of individual mooring line components during a 20-year design life is calculated first, followed by that of a complete mooring line which consists of top and bottom chains, a steel cable or polyester rope at the middle and a suction caisson foundation, and finally that of the mooring system. It is found that foundations have failure probabilities that are more than an order of magnitude smaller than those for lines under extreme loading. Mooring systems exhibit redundancy in that the failure of the most heavily loaded component during an extreme event does not necessarily lead to failure of the system. The system reliability and redundancy are greater for the taut versus semi-taut systems and is greater for designs governed by loop current versus hurricane events. Although this study concerns about the mooring systems of a classical spar, the methodology of the reliability analysis and the conclusions made in this study may have important implications to the other deepwater mooring systems / text

published_or_final_version / Physics / Master / Master of Philosophy

Η παρούσα διπλωματική εργασία πραγματοποιήθηκε από 8/2013-9/2014 στο τμήμα ηλεκτρολόγων μηχανικών & τεχνολογίας υπολογιστών του πανεπιστημίου Πατρών, υπό την επίβλεψη του καθηγητή Γαβριήλ Γιαννακόπουλου. Σκοπός της παρούσας διπλωματικής είναι η σχεδίαση και ο έλεγχος στατικού σειριακού αντισταθμιστή με στόχο την αντιστάθμιση συμμετρικών και ασύμμετρων βυθίσεων τάσης σε ευαίσθητα φορτία. Αρχικά γίνεται μια γενική αναφορά στην δομή των συστημάτων ηλεκτρικής ενέργειας στην έννοια της ποιότητας ισχύος και στις διαταραχές που μπορούν να εμφανιστούν σε ένα σύστημα ηλεκτρικής ενέργειας. Έπειτα παρουσιάζονται μέθοδοι βελτίωσης της ποιότητας ισχύος και συγκεκριμένα των διαταραχών που οφείλονται σε βυθίσεις τάσεις. Κατόπιν περιγράφεται η δομή και ο τρόπος λειτουργίας της διάταξης που θα χρησιμοποιηθεί για την αντιστάθμιση της τάσης (Στατικός Σειριακός Αντισταθμιστής). Αναλύεται το σύστημα ελέγχου (Διπλός Διανυσματικός Ελεγκτής, Double Vector Controller) και παρουσιάζονται τα αποτελέσματα της προσομοίωσης διαφόρων τύπων βραχυκυκλωμάτων με την χρήση του Στατικού Σειριακού Αντισταθμιστή (Static Series Compensator). / The present work was carried out by 8 / 2013-9 / 2014 in the Department of Electrical and Computer Engineering,in the University of Patras, under the supervision of Professor Gabriel Giannakopoulos. The purpose of this project is the design and control of serial static compensator designed to compensate symmetrical and asymmetrical voltage drops to sensitive loads. Originally made ​​a general reference to the structure of power systems in the sense of power quality and disturbances that can occur in a power system. Then, the study methods for improving power quality and specific disorders caused dips trends. After describing the structure and function of the device to be used to compensate for the voltage (Serial Static Compensator). Analyzed control system, Double Vector Controller and presented the results of the simulation of various types of short circuits using the Serial Static Compensator

The effects of deep fat frying and oven baking on mass transfer (moisture loss and oil uptake), color and textural characteristics of chicken nuggets were studied. Deep fat frying was performed at three oil temperatures, namely 150, 170 and 190°C. The frying times were 1, 2, 3 and 4 min. Oven baking was accomplished at three temperature levels: 200, 220, and 240°C, and the baking times were 10, 15, 20 and 25 min. / Moisture content of the breading portion of the fried chicken nuggets decreased following a typical drying curve and ranged from 0.90 to 0.22 g/g (db), while the moisture content of the core portion of the chicken nuggets decreased almost linearly and ranged from 1.96 to 1.4 g/g (db). Fat contents of the breading and core portions increased linearly with time. Generally, frying temperature significantly affected the moisture contents of the breading and core. It also affected the fat content of the core but not that of the breading. (Abstract shortened by UMI.)

Anorexia Nervosa (AN) has the highest mortality rate of any psychiatric condition, and despite its recognition for centuries, remains a significant treatment challenge. Marked by firmly entrenched maladaptive beliefs about body, weight and food, as well as high rates of psychiatric comorbidity, AN is a chronic illness in a large proportion of patients. The neural substrates of AN are now beginning to emerge, and appear to be related to dysfunctional, primarily limbic, circuits driving pathological thoughts and behaviours. Deep Brain Stimulation (DBS) is a neurosurgical procedure where implanted electrodes are used to regulate activity in critical nodes comprising such aberrant circuits. The promise of DBS in motor-circuit conditions, such as Parkinson’s Disease, has driven it’s investigation in other circuit-based disorders, including some psychiatric conditions. Converging evidence from clinical and imaging literatures suggests that AN is in large part a disorder of emotional processing, wherein disordered mood, anxiety, and affective dysregulation contribute to disease maintenance and are obstacles to effective treatment. The subcallosal cingulate (SCC), a key medial frontal structure involved in affective processing, has further been directly implicated in AN relevant pathways. As such, this work had three broad objectives: i) to establish the safety and initial efficacy of SCC DBS in a group of chronic and highly-refractory AN patients; ii) to show that SCC DBS can have network wide cerebral metabolic influence, on AN-relevant circuits and structures; and, iii) to investigate whether structural brain features, including hippocampal volume changes, are correlated with clinical outcomes of DBS. Our results showed that DBS is safe in AN, and associated in some patients with significant improvements in mood, anxiety and, over time, weight and treatment-response. Imaging results further showed DBS to be associated with substantial changes in glucose utilization in disease-relevant circuits, with preliminary evidence supporting a relationship between hippocampal volume changes and clinical improvements. In the context of highly refractory disease, these promising results suggest that DBS can inform AN circuit models, and be explored as a novel therapeutic option for treatment-resistant patients.

Anorexia Nervosa (AN) has the highest mortality rate of any psychiatric condition, and despite its recognition for centuries, remains a significant treatment challenge. Marked by firmly entrenched maladaptive beliefs about body, weight and food, as well as high rates of psychiatric comorbidity, AN is a chronic illness in a large proportion of patients. The neural substrates of AN are now beginning to emerge, and appear to be related to dysfunctional, primarily limbic, circuits driving pathological thoughts and behaviours. Deep Brain Stimulation (DBS) is a neurosurgical procedure where implanted electrodes are used to regulate activity in critical nodes comprising such aberrant circuits. The promise of DBS in motor-circuit conditions, such as Parkinson’s Disease, has driven it’s investigation in other circuit-based disorders, including some psychiatric conditions. Converging evidence from clinical and imaging literatures suggests that AN is in large part a disorder of emotional processing, wherein disordered mood, anxiety, and affective dysregulation contribute to disease maintenance and are obstacles to effective treatment. The subcallosal cingulate (SCC), a key medial frontal structure involved in affective processing, has further been directly implicated in AN relevant pathways. As such, this work had three broad objectives: i) to establish the safety and initial efficacy of SCC DBS in a group of chronic and highly-refractory AN patients; ii) to show that SCC DBS can have network wide cerebral metabolic influence, on AN-relevant circuits and structures; and, iii) to investigate whether structural brain features, including hippocampal volume changes, are correlated with clinical outcomes of DBS. Our results showed that DBS is safe in AN, and associated in some patients with significant improvements in mood, anxiety and, over time, weight and treatment-response. Imaging results further showed DBS to be associated with substantial changes in glucose utilization in disease-relevant circuits, with preliminary evidence supporting a relationship between hippocampal volume changes and clinical improvements. In the context of highly refractory disease, these promising results suggest that DBS can inform AN circuit models, and be explored as a novel therapeutic option for treatment-resistant patients.

Deep generative neural networks such as the Deep Belief Network and Deep Boltzmann Machines have been used successfully to model high dimensional visual data. However, they are not robust to common variations such as occlusion and random noise. In this thesis, we explore two strategies for improving the robustness of DBNs. First, we show that a DBN with sparse connections in the first layer is more robust to variations that are not in the training set. Second, we develop a probabilistic denoising algorithm to determine a subset of the hidden layer nodes to unclamp. We show that this can be applied to any feedforward network classifier with localized first layer connections. By utilizing the already available generative model for denoising prior to recognition, we show significantly better performance over the standard DBN implementations for various sources of noise on the standard and Variations MNIST databases.

This qualitative research study seeks to answer the question: Which instructional design approaches for blended learning encourage deep learning? This grounded theory research captures the lived experiences of instructional designers and faculty members in converting courses at the post-secondary level from traditional, face-to-face delivery to blended delivery using educational technology. Study results provide insight into the complexities involved in the design and development of blended delivery courses and shed light on the complications that can arise with course conversion. The study also opens a window into design approaches to foster deep learning, clarifying the importance of targeting high levels of learning in the course syllabus / outline, and then aligning every part of the course to the specific learning outcomes identified. Study results culminate in a set of recommended instructional design approaches that foster deep learning in a blended learning environment. / 2013-08

This thesis examined the reproductive biology of the poorly-known deep-water gorgonian Acanella arbuscula from the Northwest Atlantic. Colonies were collected from The Gully in 2007 and 2010 between 914 and 1860 m depth, and the Flemish Cap in 2009 between 671 and 1264 m. Mean polyp fecundity was relatively high for both females and males, and the large oocyte size suggests that A. arbuscula produces lecithotrophic larvae. This species may have overlapping periodic or seasonal cycles of gametogenesis, and the absence of planulae suggests that A. arbuscula is a broadcast spawner. No spatial variation in the reproductive characteristics of this species was found, suggesting that environmental conditions are similar between the two sites. Female polyp fecundity decreased with increasing depth, which may be due to the high cost of producing oocytes versus sperm. The relatively high mean polyp fecundity, probable lecithotrophic larval development, and broadcast spawning may allow for the wide dispersal and settlement of A. arbuscula across the North Atlantic.

In this autoethnographic personal narrative, I share my multifaceted journey of developing ecological embodied cognition in the context of climate change, specifically in the West Kootenay region of British Columbia. Through spending time alone with the other-than-human world and using a deliberate practice of mindfulness to develop a participatory postmodern worldview, I seek to integrate multiple ways of knowing to complement my existing strengths of scientific, positivist understanding of the world. I suggest that expanding my (our) metaphoric construct of self to include ecological self, is vital to deepening sustainable relationships with nature and with other humans. I depict and evoke for readers my personal experience as a potential model of adaptation and worldview change. As environmental educator and education leader in the public school system, I will bring these new skills and ways of knowing and being to the classroom, to more meaningfully promote sustainability initiatives and behaviors.