625 resultados para Indigenous Knowledge Systems


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Wireless Mesh Networks (WMNs) are increasingly deployed to enable thousands of users to share, create, and access live video streaming with different characteristics and content, such as video surveillance and football matches. In this context, there is a need for new mechanisms for assessing the quality level of videos because operators are seeking to control their delivery process and optimize their network resources, while increasing the user’s satisfaction. However, the development of in-service and non-intrusive Quality of Experience assessment schemes for real-time Internet videos with different complexity and motion levels, Group of Picture lengths, and characteristics, remains a significant challenge. To address this issue, this article proposes a non-intrusive parametric real-time video quality estimator, called MultiQoE that correlates wireless networks’ impairments, videos’ characteristics, and users’ perception into a predicted Mean Opinion Score. An instance of MultiQoE was implemented in WMNs and performance evaluation results demonstrate the efficiency and accuracy of MultiQoE in predicting the user’s perception of live video streaming services when compared to subjective, objective, and well-known parametric solutions.

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Sustainable and equitable management of biodiversity in protected areas inhabited by indigenous peoples is often a challenge. It requires an intercultural dialogue based on local norms of resource use and indigenous knowledge. Moreover, mechanisms that generate economic incentives must be able to compete with income from illegal activities such as logging, mining, and land trafficking. Finally, efforts are needed to ensure that regulations and policies on conservation and resource extraction do not overlap and contradict each other, as this hampers efforts both to conserve biodiversity and to promote development at the local level.

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Among the efforts for the improvement of agricultural productivity, the cultivation of useful plants is particularly at the center of the Economic Enlightenment. In contrast to fodder and textile plants, cereals and potatoes, fruit trees are not included among its favoured subjects. This may be considered as astonishing in view of the significance that fruit has acquired in the contemporary diet. Be that as it may, efforts to improve fruit cultivation go back to even before the classical period of the Economic Enlightenment. The example of Bern in particular is suited to such an analysis over the Longue durée that covers the time from Daniel Rhagor’s «Pflantz-Gart» (1639) to the «Register of varieties of excellent species of pome fruits for the canton of Bern» (Stammregister, 1865). From the perspective of the history of knowledge, the connections between scholarly knowledge and local experience on the one hand and the changing actors in these knowledge systems on the other hand are of special interest here

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Cloud Computing is an enabler for delivering large-scale, distributed enterprise applications with strict requirements in terms of performance. It is often the case that such applications have complex scaling and Service Level Agreement (SLA) management requirements. In this paper we present a simulation approach for validating and comparing SLA-aware scaling policies using the CloudSim simulator, using data from an actual Distributed Enterprise Information System (dEIS). We extend CloudSim with concurrent and multi-tenant task simulation capabilities. We then show how different scaling policies can be used for simulating multiple dEIS applications. We present multiple experiments depicting the impact of VM scaling on both datacenter energy consumption and dEIS performance indicators.

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The Doctoral Workshop on Distributed Systems has been held at Kandersteg, Switzerland, from June 3-5, 2014. Ph.D. students from the Universities of Neuchâtel and Bern as well as the University of Applied Sciences of Fribourg presented their current research work and discussed recent research results. This technical report includes the extended abstracts of the talks given during the workshop.

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This chapter introduces a conceptual model to combine creativity techniques with fuzzy cognitive maps (FCMs) and aims to support knowledge management methods by improving expert knowledge acquisition and aggregation. The aim of the conceptual model is to represent acquired knowledge in a manner that is as computer-understandable as possible with the intention of developing automated reasoning in the future as part of intelligent information systems. The formal represented knowledge thus may provide businesses with intelligent information integration. To this end, we introduce and evaluate various creativity techniques with a list of attributes to define the most suitable to combine with FCMs. This proposed combination enables enhanced knowledge management through the acquisition and representation of expert knowledge with FCMs. Our evaluation indicates that the creativity technique known as mind mapping is the most suitable technique in our set. Finally, a scenario from stakeholder management demonstrates the combination of mind mapping with FCMs as an integrated system.

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Our research project develops an intranet search engine with concept- browsing functionality, where the user is able to navigate the conceptual level in an interactive, automatically generated knowledge map. This knowledge map visualizes tacit, implicit knowledge, extracted from the intranet, as a network of semantic concepts. Inductive and deductive methods are combined; a text ana- lytics engine extracts knowledge structures from data inductively, and the en- terprise ontology provides a backbone structure to the process deductively. In addition to performing conventional keyword search, the user can browse the semantic network of concepts and associations to find documents and data rec- ords. Also, the user can expand and edit the knowledge network directly. As a vision, we propose a knowledge-management system that provides concept- browsing, based on a knowledge warehouse layer on top of a heterogeneous knowledge base with various systems interfaces. Such a concept browser will empower knowledge workers to interact with knowledge structures.

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Long Term Evolution (LTE) represents the fourth generation (4G) technology which is capable of providing high data rates as well as support of high speed mobility. The EU FP7 Mobile Cloud Networking (MCN) project integrates the use of cloud computing concepts in LTE mobile networks in order to increase LTE's performance. In this way a shared distributed virtualized LTE mobile network is built that can optimize the utilization of virtualized computing, storage and network resources and minimize communication delays. Two important features that can be used in such a virtualized system to improve its performance are the user mobility and bandwidth prediction. This paper introduces the architecture and challenges that are associated with user mobility and bandwidth prediction approaches in virtualized LTE systems.

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Knowledge processes are critical to outsourced software projects. According to outsourcing research, outsourced software projects succeed if they manage to integrate the client’s business knowledge and the vendor’s technical knowledge. In this paper, we submit that this view may not be wrong, but incomplete in a significant part of outsourced software work, which is software maintenance. Data from six software-maintenance outsourcing transitions indicate that more important than business or technical knowledge can be application knowledge, which vendor engineers acquire over time during practice. Application knowledge was the dominant knowledge during knowledge transfer activities and its acquisition enabled vendor staff to solve maintenance tasks. We discuss implications for widespread assumptions in outsourcing research.

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Due to the increasing amount of data, knowledge aggregation, representation and reasoning are highly important for companies. In this paper, knowledge aggregation is presented as the first step. In the sequel, successful knowledge representation, for instance through graphs, enables knowledge-based reasoning. There exist various forms of knowledge representation through graphs; some of which allow to handle uncertainty and imprecision by invoking the technology of fuzzy sets. The paper provides an overview of different types of graphs stressing their relationships and their essential features.