867 resultados para Profit-sharing.
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Rapid and affordable tumor molecular profiling has led to an explosion of clinical and genomic data poised to enhance the diagnosis, prognostication and treatment of cancer. A critical point has now been reached at which the analysis and storage of annotated clinical and genomic information in unconnected silos will stall the advancement of precision cancer care. Information systems must be harmonized to overcome the multiple technical and logistical barriers to data sharing. Against this backdrop, the Global Alliance for Genomic Health (GA4GH) was established in 2013 to create a common framework that enables responsible, voluntary and secure sharing of clinical and genomic data. This Perspective from the GA4GH Clinical Working Group Cancer Task Team highlights the data-aggregation challenges faced by the field, suggests potential collaborative solutions and describes how GA4GH can catalyze a harmonized data-sharing culture.
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The purpose of this study was to evaluate the effectiveness of the Creative Problem Solving (CPS) method in improving the leadership process in a non-profit organization. The research was designed around an intervention and structured in three stages (pre-consult, intervention and follow-up), with a team designated by management, in order to bring leadership cohesion to both departments of the organization and also between the board and executive management. The results, expressed in the tasks performed and in the interviews to team members, allowed us to conclude on the effectiveness of the CPS method to improve organizational leadership, by establishing a stronger relationship between departments, as well as, in the long term, between the board and executive management. These results highlight possible solutions to improve the leadership of non-profit organizations.
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Thesis (Ph.D.)--University of Washington, 2015
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The objective of this study is to better understand why selected urban freight solutions represent innovations that are technically feasible, economically profitable in different contexts, sustainable, transferable, and with tangible beneficial impacts. A total of 15 solutions are evaluated in the fields of Urban Consolidation Centre, clean and electric vehicles, IT solutions, use of urban waterways, and others. Three solutions are analysed more thoroughly, the Cityporto Padova, the Basel Exhibition Centre logistics support system, and the Berlin laboratory area test of the Bentobox. This paper ends with a transversal analysis of the solutions observed, and with methodological conclusions.
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Researchers want to run scientific experiments focusing on their disciplines. They do not want to know how and where the experiments are executed. Science gateways hide details by coordinating the execution of experiments using different infrastructures and workflow systems. ER-flow/SHIWA and SCI-BUS project developed repositories to share artefacts such as applications, portlets, workflows, etc. inside and among research communities. Sharing artefacts in re-positories enable gateway developers to reuse them when building a new gateway and/or creating a new application.
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The objective of this study is to better understand why selected urban freight solutions represent innovations that are technically feasible, economically profitable in different contexts, sustainable, transferable, and with tangible beneficial impacts. A total of 15 solutions are evaluated in the fields of Urban Consolidation Centre, clean and electric vehicles, IT solutions, use of urban waterways, and others. Three solutions are analysed more thoroughly, the Cityporto Padova, the Basel Exhibition Centre logistics support system, and the Berlin laboratory area test of the Bentobox. This paper ends with a transversal analysis of the solutions observed, and with methodological conclusions.
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E-scientists want to run their scientific experiments on Distributed Computing Infrastructures (DCI) to be able to access large pools of resources and services. To run experiments on these infrastructures requires specific expertise that e-scientists may not have. Workflows can hide resources and services as a virtualization layer providing a user interface that e-scientists can use. There are many workflow systems used by research communities but they are not interoperable. To learn a workflow system and create workflows in this workflow system may require significant efforts from e-scientists. Considering these efforts it is not reasonable to expect that research communities will learn new workflow systems if they want to run workflows developed in other workflow systems. The solution is to create workflow interoperability solutions to allow workflow sharing. The FP7 Sharing Interoperable Workflow for Large-Scale Scientific Simulation on Available DCIs (SHIWA) project developed two interoperability solutions to support workflow sharing: Coarse-Grained Interoperability (CGI) and Fine-Grained Interoperability (FGI). The project created the SHIWA Simulation Platform (SSP) to implement the Coarse-Grained Interoperability approach as a production-level service for research communities. The paper describes the CGI approach and how it enables sharing and combining existing workflows into complex applications and run them on Distributed Computing Infrastructures. The paper also outlines the architecture, components and usage scenarios of the simulation platform.
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— In the new learning environments, built width digital technologies, the need to promote quality of education resources, commonly known as Learning Objects, which can support formal and informal distance learning, emerge as one of the biggest challenge that educational institutions will have to face. Due to the fact that is expensive, the reuse and sharing became very important issue. This article presents a Learning Object Repository which aims to store, to disseminate and maintain accessible Learning Objects.
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Several projects in the recent past have aimed at promoting Wireless Sensor Networks as an infrastructure technology, where several independent users can submit applications that execute concurrently across the network. Concurrent multiple applications cause significant energy-usage overhead on sensor nodes, that cannot be eliminated by traditional schemes optimized for single-application scenarios. In this paper, we outline two main optimization techniques for reducing power consumption across applications. First, we describe a compiler based approach that identifies redundant sensing requests across applications and eliminates those. Second, we cluster the radio transmissions together by concatenating packets from independent applications based on Rate-Harmonized Scheduling.
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We present a 12(1 + 3R/(4m)) competitive algorithm for scheduling implicit-deadline sporadic tasks on a platform comprising m processors, where a task may request one of R shared resources.
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This paper proposes a dynamic scheduler that supports the coexistence of guaranteed and non-guaranteed bandwidth servers to efficiently handle soft-tasks’ overloads by making additional capacity available from two sources: (i) residual capacity allocated but unused when jobs complete in less than their budgeted execution time; (ii) stealing capacity from inactive non-isolated servers used to schedule best-effort jobs. The effectiveness of the proposed approach in reducing the mean tardiness of periodic jobs is demonstrated through extensive simulations. The achieved results become even more significant when tasks’ computation times have a large variance.
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This paper proposes a new strategy to integrate shared resources and precedence constraints among real-time tasks, assuming no precise information on critical sections and computation times is available. The concept of bandwidth inheritance is combined with a greedy capacity sharing and stealing policy to efficiently exchange bandwidth among tasks, minimising the degree of deviation from the ideal system's behaviour caused by inter-application blocking. The proposed capacity exchange protocol (CXP) focus on exchanging extra capacities as early, and not necessarily as fairly, as possible. This loss of optimality is worth the reduced complexity as the protocol's behaviour nevertheless tends to be fair in the long run and outperforms other solutions in highly dynamic scenarios, as demonstrated by extensive simulations.
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In this paper, we consider a Cournot competition between a nonprofit firm and a for-profit firm in a homogeneous goods market, with uncertain demand. Given an asymmetric tax schedule, we compute explicitly the Bayesian-Nash equilibrium. Furthermore, we analyze the effects of the tax rate and the degree of altruistic preference on market equilibrium outcomes.