In much feminist literature, patriarchy has often been studied as a predictive variable for attitudes toward or acts of violence against women. However, rarely has patriarchy been examined as an outcome across studies. The current study works toward filling this gap by examining several individual-and neighborhood-level factors that might influence patriarchy. Specifically, this research seeks to determine if neighborhood-level attributes related to socioeconomic status, family composition, and demographic information affect patriarchal views after individual-level correlates of patriarchy were controlled. Findings suggest that factors at both the individual- and neighborhood levels, particularly familial characteristics and dynamics, do influence the endorsement of patriarchal views.

In much feminist literature, patriarchy has often been studied as a predictive variable for attitudes toward or acts of violence against women. However, rarely has patriarchy been examined as an outcome across studies. The current study works toward filling this gap by examining several individual-and neighborhood-level factors that might influence patriarchy. Specifically, this research seeks to determine if neighborhood-level attributes related to socioeconomic status, family composition, and demographic information affect patriarchal views after individual-level correlates of patriarchy were controlled. Findings suggest that factors at both the individual- and neighborhood levels, particularly familial characteristics and dynamics, do influence the endorsement of patriarchal views.

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This document sets out to describe the process of creating the artistic and technical endeavor that culminated in the lighting design for Temple University Theater's October 2015 production of Anything Goes. This is an in-depth reflection and analysis of the initial impressions, personal goals, script analysis, lighting concept, and execution that went into the creation of the design from first reading to realized design. / Theater

The goal of this thesis is to take an in depth look at the process of creating a scenic design for Temple Theatre’s production of Anything Goes by Cole Porter. This paper will break down the designer’s personal process in developing the design. In addition, it will break down the process of translating the design into a realized set. In particular, a look at how Anything Goes worked in relation to an ideal production situation. / Theater

Background: In recent years, computer vision has undergone significant advancements, revolutionizing fields such as robotics, augmented reality, and autonomoussystems. Key to this transformation is Simultaneous Localization and Mapping(SLAM), a fundamental technology that allows machines to navigate and interactintelligently with their surroundings. Challenges persist in harmonizing spatial andsemantic understanding, as conventional methods often treat these tasks separately,limiting comprehensive evaluations with shared datasets. As applications continueto evolve, the demand for accurate and efficient image segmentation ground truthbecomes paramount. Manual annotation, a traditional approach, proves to be bothcostly and resource-intensive, hindering the scalability of computer vision systems.This thesis addresses the urgent need for a cost-effective and scalable solution byfocusing on the creation of accurate and efficient image segmentation ground truth,bridging the gap between spatial and semantic tasks. Objective: This thesis addresses the challenge of creating an efficient image segmentation ground truth to complement datasets with spatial ground truth. Theprimary objective is to reduce the time and effort taken for annotation of datasets. Method: Our methodology adopts a systematic approach to evaluate and combineexisting annotation techniques, focusing on precise object detection and robust segmentation. By merging these approaches, we aim to enhance annotation accuracywhile streamlining the annotation process. This approach is systematically appliedand evaluated across multiple datasets, including the NYU V2 dataset(consists ofover 1449 images), ARID(real-world sequential dataset), and Italian flats(sequentialdataset created in blender). Results: The developed pipeline demonstrates promising outcomes, showcasing asubstantial reduction in annotation time compared to manual annotation, thereby addressing the challenges posed by the cost and resource intensiveness of the traditionalapproach. We observe that although not initially optimized for SLAM datasets, thepipeline performs exceptionally well on both ARID and Italian flats datasets, highlighting its adaptability to real-world scenarios. Conclusion: In conclusion, this research introduces an innovative annotation pipeline,offering a systematic and efficient approach to annotation. It tries to bridge the gapbetween spatial and semantic tasks, addressing the pressing need for comprehensiveannotation tools in this domain.

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Background:The dynamic field of computer vision and artificial intelligence has continually evolved, pushing the boundaries in areas like semantic segmentation andenvironmental recognition, pivotal for indoor scene analysis. This research investigates the integration of these two technologies, examining their synergy and implicayions for enhancing indoor scene understanding. The application of this integrationspans across various domains, including smart home systems for enhanced ambientliving, navigation assistance for Cleaning robots, and advanced surveillance for security. Objectives: The primary goal is to assess the impact of integrating semantic segmentation data on the accuracy of environmental recognition algorithms in indoor environments. Additionally, the study explores how environmental context can enhance the precision and accuracy of contour-aware semantic segmentation. Methods: The research employed an extensive methodology, utilizing various machine learning models, including standard algorithms, Long Short-Term Memorynetworks, and ensemble methods. Transfer learning with models like EfficientNet B3, MobileNetV3 and Vision Tranformer was a key aspect of the experimentation. The experiments were designed to measure the effect of semantic segmentation on environmental recognition and its reciprocal influence. Results: The findings indicated that the integration of semantic segmentation data significantly enhanced the accuracy of environmental recognition algorithms. Conversely, incorporating environmental context into contour-aware semantic segmentation led to notable improvements in precision and accuracy, reflected in metrics such as Mean Intersection over Union(MIoU). Conclusion: This research underscores the mutual enhancement between semantic segmentation and environmental recognition, demonstrating how each technology significantly boosts the effectiveness of the other in indoor scene analysis. The integration of semantic segmentation data notably elevates the accuracy of environmental recognition algorithms, while the incorporation of environmental context into contour-aware semantic segmentation substantially improves its precision and accuracy.The results also open avenues for advancements in automated annotation processes, paving the way for smarter environmental interaction.

Vehicle-to-Anything (V2X) est un terme générique qui explique l'utilisation de batteries de véhicules électriques pour obtenir une valeur supplémentaire lors de périodes de non-utilisation. Les services V2X génèrent des revenus de la batterie grâce à la charge dynamique monodirectionnelle (V1X) ou bidirectionnelle (V2X) afin de fournir des avantages au réseau électrique, de réduire la consommation énergétique des bâtiments et des maisons ou de fournir une alimentation de secours aux charges. Une méta-analyse du potentiel économique donne des résultats contradictoires avec la littérature et indique que la gestion de la consommation électrique, l'adéquation des ressources et le report de l’investissement dans le réseau ont plus de valeur que d’arbitrage sur les marchés d’énergie et réserve secondaire. Bien que je convienne que le développement soit pour et par le marché, je souligne que V2X se développera dans les limites du contexte réglementaire; les régulateurs ont donc un rôle de catalyseur à jouer.Une question importante est de savoir dans quelle mesure une utilisation supplémentaire de la batterie du véhicule affectera la capacité de la batterie au cours de sa durée de vie. Il est donc essentiel de comprendre les subtilités de la dégradation de la batterie pour estimer les coûts. Les batteries Li-ion sont des systèmes électrochimiques compliqués qui présentent deux phénomènes de dégradation simultanés, le vieillissement calendaire et le vieillissement cyclique. Dans les applications véhiculaires, le vieillissement du calendrier a tendance à être l’effet dominant de dégradation de la durée de vie, ce qui réduit le temps, élément le plus important de la dégradation; par conséquent, le coût de la dégradation dépend fondamentalement du temps.Une affirmation centrale de cette thèse est que le coût marginal de V2X n’est ni nul ni négligeable comme l’a accepté la littérature économique, mais dépend fortement de la dégradation de la batterie. Nous proposons ici une théorie des coûts marginaux V2X qui repose sur deux principes: 1.) il existe un coût d’efficacité associé au chargement de la batterie, et 2.) le véritable coût de dégradation de V2X prend en compte le coût d’opportunité, c’est-à-dire, la dégradation au-delà de ce qu’aurait été l’utilisation normale du véhicule.Avoir un concept clair du coût marginal de V2X, permet de comptabiliser et d’équilibrer correctement tous les coûts réels: coût de l’électricité, coûts d’efficacité du système et dégradation de la batterie. Cela permettra d’élaborer des stratégies de charge optimales et d’informer correctement les offres du marché de l’énergie. Il en résulte une compréhension plus nuancée des coûts marginaux. L’impact de la batterie V2X sur la vie de la batterie pourrait être considéré comme un coût, un bénéfice ou nul. Je conclus que le V2X peut offrir une valeur économique supérieure à celle précédemment entendue et que cette valeur supplémentaire sera réalisée grâce à l'amélioration simultanée de l'efficacité de la charge et de la réduction de la dégradation de la batterie EV. / Vehicle-to-Anything (V2X) is an umbrella term to explain the use of electric vehicle batteries to derive additional value during times of non-use. V2X services generate revenue from the battery asset through dynamic mono-directional (V1X) or bi-directional (V2X) charging to provide benefits to the electric grid, to reduce energy consumption of buildings and homes, or to provide back-up power to loads. A meta-analysis of economic potential gives results contradictory to the literature and indicates that Bill Management, Resource Adequacy, and Network Deferral are more valuable than Energy Arbitrage and Spinning Reserves. While I concur that development is of and by the market, I emphasize that V2X will develop within the constraints of the regulatory environment; therefore regulators have an enabling role to play.An important question is to what extent additional use of the vehicle battery will affect battery capacity over its lifetime, therefore understanding the intricacies of battery degradation is crucial to estimate costs. Li-ion batteries are complicated electrochemical systems which exhibit two concurrent degradation phenomena, Calendar Aging and Cycling Aging. In vehicular applications, Calendar Aging tends to be the dominating life degradation effect, which reduces to time being the most important component of degradation; therefore degradation cost is fundamentally time-dependent.A central claim of this dissertation is that gls{v2x} Marginal Cost is not zero nor negligible as the economic literature has accepted but is highly dependent on battery degradation. Herein, a gls{v2x} Marginal Cost Theory is proposed which is based on two main principles: 1.) there is an efficiency cost associated with charge operation, and 2.) the true gls{v2x} degradation cost takes opportunity cost into account, that is, only considers degradation beyond what would have been experienced by operating the vehicle normally.Having a clear concept of gls{v2x} Marginal Cost which can properly account for and balance all true costs: the cost of electricity, the system-efficiency costs, and battery degradation, will allow for development of optimal charge strategies and will properly inform energy market bids. This results in a more nuanced understanding of marginal costs as the resultant battery lifetime impact from gls{v2x} can be either be considered a cost, a benefit, or zero. I conclude that gls{v2x} may offer greater economic value than previously understood and that this additional value will be realized through the simultaneous improvement in charge efficiency and reduction of gls{ev} battery degradation.