9 resultados para implementation issues

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Virtual machines emulating hardware devices are generally implemented in low-level languages and using a low-level style for performance reasons. This trend results in largely difficult to understand, difficult to extend and unmaintainable systems. As new general techniques for virtual machines arise, it gets harder to incorporate or test these techniques because of early design and optimization decisions. In this paper we show how such decisions can be postponed to later phases by separating virtual machine implementation issues from the high-level machine-specific model. We construct compact models of whole-system VMs in a high-level language, which exclude all low-level implementation details. We use the pluggable translation toolchain PyPy to translate those models to executables. During the translation process, the toolchain reintroduces the VM implementation and optimization details for specific target platforms. As a case study we implement an executable model of a hardware gaming device. We show that our approach to VM building increases understandability, maintainability and extendability while preserving performance.

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Virtual machines (VMs) emulating hardware devices are generally implemented in low-level languages for performance reasons. This results in unmaintainable systems that are difficult to understand. In this paper we report on our experience using the PyPy toolchain to improve the portability and reduce the complexity of whole-system VM implementations. As a case study we implement a VM prototype for a Nintendo Game Boy, called PyGirl, in which the high-level model is separated from low-level VM implementation issues. We shed light on the process of refactoring from a low-level VM implementation in Java to a high-level model in RPython. We show that our whole-system VM written with PyPy is significantly less complex than standard implementations, without substantial loss in performance.

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Balancing the frequently conflicting priorities of conservation and economic development poses a challenge to management of the Swiss Alps Jungfrau-Aletsch World Heritage Site (WHS). This is a complex societal problem that calls for a knowledge-based solution. This in turn requires a transdisciplinary research framework in which problems are defined and solved cooperatively by actors from the scientific community and the life-world. In this article we re-examine studies carried out in the region of the Swiss Alps Jungfrau-Aletsch WHS, covering three key issues prevalent in transdisciplinary settings: integration of stakeholders into participatory processes; perceptions and positions; and negotiability and implementation. In the case of the Swiss Alps Jungfrau-Aletsch WHS the transdisciplinary setting created a situation of mutual learning among stakeholders from different levels and backgrounds. However, the studies showed that the benefits of such processes of mutual learning are continuously at risk of being diminished by the power play inherent in participatory approaches.

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In recent years controversial discussions arose during major animal disease outbreaks in the EU about the ethical soundness of mass culling. In contrast to numerous publications about ethical issues and laboratory animals/animal experiments, literature concerning ethical deliberations in the case of mass culling as a means of outbreak control remain scarce. Veterinarians in charge of decision about and implementation of mass culling actions find themselves in an area of conflict in between the officially required animal disease control policy and a public that is increasingly critical. Those veterinarians are faced with the challenge to defend the relevant decisions against all stakeholders and also themselves. In this context an interdisciplinary workshop was initiated in Switzerland in October 2007 with ethicians and (official) veterinarians from Germany, Switzerland and Austria. With the aim to identify ethical components of animal disease control for official veterinarians, talks and moderated group discussions took place. This article summarizes selected discussion points and conclusions.

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OBJECTIVES To summarize the current status of clinicopathological and molecular markers for the prediction of recurrence or progression or both in non-muscle-invasive and survival in muscle-invasive urothelial bladder cancer, to address the reproducibility of pathology and molecular markers, and to provide directions toward implementation of molecular markers in future clinical decision making. METHODS AND MATERIALS Immunohistochemistry, gene signatures, and FGFR3-based molecular grading were used as molecular examples focussing on prognostics and issues related to robustness of pathological and molecular assays. RESULTS The role of molecular markers to predict recurrence is limited, as clinical variables are currently more important. The prediction of progression and survival using molecular markers holds considerable promise. Despite a plethora of prognostic (clinical and molecular) marker studies, reproducibility of pathology and molecular assays has been understudied, and lack of reproducibility is probably the main reason that individual prediction of disease outcome is currently not reliable. CONCLUSIONS Molecular markers are promising to predict progression and survival, but not recurrence. However, none of these are used in the daily clinical routine because of reproducibility issues. Future studies should focus on reproducibility of marker assessment and consistency of study results by incorporating scoring systems to reduce heterogeneity of reporting. This may ultimately lead to incorporation of molecular markers in clinical practice.

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Cloudification of the Centralized-Radio Access Network (C-RAN) in which signal processing runs on general purpose processors inside virtual machines has lately received significant attention. Due to short deadlines in the LTE Frequency Division Duplex access method, processing time fluctuations introduced by the virtualization process have a deep impact on C-RAN performance. This paper evaluates bottlenecks of the OpenAirInterface (OAI is an open-source software-based implementation of LTE) cloud performance, provides feasibility studies on C-RAN execution, and introduces a cloud architecture that significantly reduces the encountered execution problems. In typical cloud environments, the OAI processing time deadlines cannot be guaranteed. Our proposed cloud architecture shows good characteristics for the OAI cloud execution. As an example, in our setup more than 99.5% processed LTE subframes reach reasonable processing deadlines close to performance of a dedicated machine.

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Two of the main issues in wireless industrial Internet of Things applications are interoperability and network lifetime. In this work we extend a semantic interoperability platform and introduce an application-layer sleepy nodes protocol that can leverage on information stored in semantic repositories. We propose an integration platform for managing the sleep states and an application layer protocol based upon the Constraint Application Layer protocol. We evaluate our system on windowing based task allocation strategies, aiming for lower overall energy consumption that results in higher network lifetime.