A Romantic Comedy of Boats and Gardens: Selected Projects in Scenic Design and Technical Direction

When this play was given to me as one of my production assignments, I was both thrilled and terrified. I thoroughly enjoy Shakespeare, but I realized that this would also be the largest show of the year; it would be the only production to take place in the Morgan Theater, our largest and most challenging space. This was only my second time designing a realized production and I knew it would be a massive undertaking. However, I knew that having a realized Shakespeare design this early in my career would greatly help my portfolio. Also, my advisor told me that this could have been the best realized portfolio piece I could get during my time at Utah State, so I would need to make the most of it. In this piece especially, my advisor Shawn Fisher wanted me to focus on composition

Incorporation of a physically based melt pond scheme into the sea ice component of a climate model

The extent and thickness of the Arctic sea ice cover has decreased dramatically in the past few decades with minima in sea ice extent in September 2005 and 2007. These minima have not been predicted in the IPCC AR4 report, suggesting that the sea ice component of climate models should more realistically represent the processes controlling the sea ice mass balance. One of the processes poorly represented in sea ice models is the formation and evolution of melt ponds. Melt ponds accumulate on the surface of sea ice from snow and sea ice melt and their presence reduces the albedo of the ice cover, leading to further melt. Toward the end of the melt season, melt ponds cover up to 50% of the sea ice surface. We have developed a melt pond evolution theory. Here, we have incorporated this melt pond theory into the Los Alamos CICE sea ice model, which has required us to include the refreezing of melt ponds. We present results showing that the presence, or otherwise, of a representation of melt ponds has a significant effect on the predicted sea ice thickness and extent. We also present a sensitivity study to uncertainty in the sea ice permeability, number of thickness categories in the model representation, meltwater redistribution scheme, and pond albedo. We conclude with a recommendation that our melt pond scheme is included in sea ice models, and the number of thickness categories should be increased and concentrated at lower thicknesses

To control or not to control: How to organize employee-driven innovation

Nowadays organizations are increasingly understanding the relevance of employees for innovation. Innovative initiatives that involve larger groups of employees, despite their role and hierarchical position, are more and more diffused within companies. However, the literature on this topic is still at its infancy, especially considering those initiatives that are structured and organized by management. Using multiple case studies, performing 34 semistructured interviews in five different companies, we investigate how managers navigate alternative design choices when they organize employee-driven innovation (EDI). Our findings suggest companies adopt different structures to organize EDI (i.e., open, closed, and hybrid), depending on the desired goals they want to achieve (i.e., creating a community or producing innovation). In this paper, we provide a clustering of different EDI practices (i.e., community-nurturing practices, solution-based practices, and integrative practices), outlining how managers can configure different design choices (e.g., topic definition, team creation, ideas transfer, ideas filtering and evaluation, and task division and allocation) to drive employees' involvement and to produce innovation

The refreezing of melt ponds on Arctic sea ice

The presence of melt ponds on the surface of Arctic sea ice significantly reduces its albedo, inducing a positive feedback leading to sea ice thinning. While the role of melt ponds in enhancing the summer melt of sea ice is well known, their impact on suppressing winter freezing of sea ice has, hitherto, received less attention. Melt ponds freeze by forming an ice lid at the upper surface, which insulates them from the atmosphere and traps pond water between the underlying sea ice and the ice lid. The pond water is a store of latent heat, which is released during refreezing. Until a pond freezes completely, there can be minimal ice growth at the base of the underlying sea ice. In this work, we present a model of the refreezing of a melt pond that includes the heat and salt balances in the ice lid, trapped pond, and underlying sea ice. The model uses a two-stream radiation model to account for radiative scattering at phase boundaries. Simulations and related sensitivity studies suggest that trapped pond water may survive for over a month. We focus on the role that pond salinity has on delaying the refreezing process and retarding basal sea ice growth. We estimate that for a typical sea ice pond coverage in autumn, excluding the impact of trapped ponds in models overestimates ice growth by up to 265 million km3, an overestimate of 26%

Les ingénieurs et la globalisation financière

L’évolution du capitalisme globalisé génère des effets sur le monde du travail qui touchent désormais également la catégorie des cadres. Ainsi, les ingénieurs d’une entreprise française d’industrie nucléaire, traversée par les bouleversements engendrés par le « nouveau capitalisme », expriment des considérations à l’égard de celui‑ci pour le moins plurielles, allant de l’appropriation de la pensée néolibérale à des postures critiques. Mais malgré la disparité des jugements, ces ingénieurs fournissent, de façon quasi unanime, des explications de l’ordre économique qui visent à le légitimer en « naturalisant » et en décrivant comme centrale la figure du marché. Une telle légitimation de l’économique – qui possède des fondements matériels et idéels issus du procès de travail – peut être interprétée comme une emprise du marché en tant que domination de catégories de pensée relatives à une conception particulière des mécanismes économiques, assimilable au néolibéralisme.The evolution of globalised capitalism is producing effects on the world of work that are now also affecting the category of managers (cadres). Thus, in the nuclear industry, engineers in a French company undergoing drastic change engendered by the « new capitalism », express different kinds of views about the latter, ranging from the appropriation of neo‑liberal thinking to more critical positions. But despite the disparity of judgements, these engineers provide, in an almost unanimous way, explanations of the economic order which aim to legitimate it by « naturalising » the market and describing it as central. Such a legitimisation of the economic – which has material and intellectual foundations in the labour process – can be interpreted in terms of the hold of the market understood as the domination of categories of thought relative to a specific conception of economic processes, which can be assimilated to neo-liberalism

An architecture for adaptive task planning in support of IoT-based machine learning applications for disaster scenarios

The proliferation of the Internet of Things (IoT) in conjunction with edge computing has recently opened up several possibilities for several new applications. Typical examples are Unmanned Aerial Vehicles (UAV) that are deployed for rapid disaster response, photogrammetry, surveillance, and environmental monitoring. To support the flourishing development of Machine Learning assisted applications across all these networked applications, a common challenge is the provision of a persistent service, i.e., a service capable of consistently maintaining a high level of performance, facing possible failures. To address these service resilient challenges, we propose APRON, an edge solution for distributed and adaptive task planning management in a network of IoT devices, e.g., drones. Exploiting Jackson's network model, our architecture applies a novel planning strategy to better support control and monitoring operations while the states of the network evolve. To demonstrate the functionalities of our architecture, we also implemented a deep-learning based audio-recognition application using the APRON NorthBound interface, to detect human voices in challenged networks. The application's logic uses Transfer Learning to improve the audio classification accuracy and the runtime of the UAV-based rescue operations

Owl: Congestion Control with Partially Invisible Networks via Reinforcement Learning

Years of research on transport protocols have not solved the tussle between in-network and end-to-end congestion control. This debate is due to the variance of conditions and assumptions in different network scenarios, e.g., cellular versus data center networks. Recently, the community has proposed a few transport protocols driven by machine learning, nonetheless limited to end-to-end approaches. In this paper, we present Owl, a transport protocol based on reinforcement learning, whose goal is to select the proper congestion window learning from end-to-end features and network signals, when available. We show that our solution converges to a fair resource allocation after the learning overhead. Our kernel implementation, deployed over emulated and large scale virtual network testbeds, outperforms all benchmark solutions based on end-to-end or in-network congestion control

Modelling the fate of surface melt on the Larsen C Ice Shelf

Surface melt lakes lower the albedo of ice shelves, leading to additional surface melting. This can substantially alter the surface energy balance and internal temperature and density profiles of the ice shelf. Evidence suggests that melt lakes also played a pivotal role in the sudden collapse of the Larsen B Ice Shelf in 2002. Here a recently developed, high-physical-fidelity model accounting for the development cycle of melt lakes is applied to the Larsen C Ice Shelf, Antarctica’s most northern ice shelf and one where melt lakes have been observed. We simulate current conditions on the ice shelf using weather station and reanalysis data and investigate the impacts of potential future increases in precipitation and air temperature on melt lake formation, for which concurrent increases lead to an increase in lake depth. Finally, we assess the viability in future crevasse propagation through the ice shelf due to surface meltwater accumulation

Supporting Sustainable Virtual Network Mutations with Mystique

The abiding attempt of automation has also permeated the networks, with the ability to measure, analyze, and control themselves in an automated manner, by reacting to changes in the environment (e.g., demand). When provided with these features, networks are often labeled as "self-driving" or "autonomous". In this regard, the provision and orchestration of physical or virtual resources are crucial for both Quality of Service (QoS) guarantees and cost management in the edge/cloud computing environment. To effectively manage the lifecycle of these resources, an auto-scaling mechanism is essential. However, traditional threshold-based and recent Machine Learning (ML)-based policies are often unable to address the soaring complexity of networks due to their centralized approach. By relying on multi-agent reinforcement learning, we propose Mystique, a solution that learns from the load on links to establish the minimal set of active network resources. As traffic demands ebb and flow, our adaptive and self-driving solution can scale up and down and also react to failures in a fully automated, flexible, and efficient manner. Our results demonstrate that the presented solution can reduce network energy consumption while providing an adequate service level, outperforming other benchmark auto-scaling approaches