974 resultados para collaborative enterprise networks


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Part 17: Risk Analysis

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Part 16: Performance Measurement Systems

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Part 14: Interoperability and Integration

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Part 10: Sustainability and Trust

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Part 6: Engineering and Implementation of Collaborative Networks

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Part 6: Engineering and Implementation of Collaborative Networks

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Part 5: Service Orientation in Collaborative Networks

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The Authors describe first-hand experiences carried out within the framework of selected International projects aimed at developing collaborative research and education using the One Health (OH) approach. Special emphasis is given to SAPUVETNET, a series of projects co-financed under the EU-ALFA program, and aimed to support an International network on Veterinary Public Health (VPH) formed by Veterinary Faculties from Latin-America (LA) and Europe (EU). SAPUVETNET has envisaged a series of objectives/activities aimed at promoting and enhancing VPH research/training and intersectoral collaboration across LA and EU using the OH approach, as well as participating in research and/or education projects/networks under the OH umbrella, namely EURNEGVEC-European Network for Neglected Vectors & Vector-Borne Infections, CYSTINET-European Network on Taeniosis/Cysticercosis, and NEOH-Network for Evaluation of One Health; the latter includes expertise in multiple disciplines (e.g. ecology, economics, human and animal health, epidemiology, social and environmental sciences, etc.) and has the primary purpose of enabling quantitative evaluation of OH initiatives by developing a standardized evaluation protocol. The Authors give also an account of the ongoing creation of OHIN-OH International Network, founded as a spin-off result of SAPUVETNET. Finally, some examples of cooperation development projects characterised by an OH approach are also briefly mentioned.

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This paper describes the modeling of a weed infestation risk inference system that implements a collaborative inference scheme based on rules extracted from two Bayesian network classifiers. The first Bayesian classifier infers a categorical variable value for the weed-crop competitiveness using as input categorical variables for the total density of weeds and corresponding proportions of narrow and broad-leaved weeds. The inferred categorical variable values for the weed-crop competitiveness along with three other categorical variables extracted from estimated maps for the weed seed production and weed coverage are then used as input for a second Bayesian network classifier to infer categorical variables values for the risk of infestation. Weed biomass and yield loss data samples are used to learn the probability relationship among the nodes of the first and second Bayesian classifiers in a supervised fashion, respectively. For comparison purposes, two types of Bayesian network structures are considered, namely an expert-based Bayesian classifier and a naive Bayes classifier. The inference system focused on the knowledge interpretation by translating a Bayesian classifier into a set of classification rules. The results obtained for the risk inference in a corn-crop field are presented and discussed. (C) 2009 Elsevier Ltd. All rights reserved.

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Since collaborative networked organisations are usually formed by independent and heterogeneous entities, it is natural that each member holds his own set of values, and that conflicts among partners might emerge because of some misalignment of values. In contrast, it is often stated in literature that the alignment between the value systems of members involved in collaborative processes is a prerequisite for successful co-working. As a result, the issue of core value alignment in collaborative networks started to attract attention. However, methods to analyse such alignment are lacking mainly because the concept of 'alignment' in this context is still ill defined and shows a multifaceted nature. As a contribution to the area, this article introduces an approach based on causal models and graph theory for the analysis of core value alignment in collaborative networks. The potential application of the approach is then discussed in the virtual organisations' breeding environment context.

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Extended and networked enterprises distribute the design of products, planning of the production process, and manufacturing regionally if not globally. Employees are therefore confronted with collaborative work over remote sites. A cost effective collaboration depends highly on the organization maintaining a common understanding for this kind of work and a suitable support with information and communication technology. The usual face to face work is going to be replaced at least partly if not totally by computer mediated collaboration. Creating and maintaining virtual teams is a challenge to work conditions as well as technology. New developments on cost-effective connections are providing not only vision and auditory perception but also haptic perception. Research results for improving remote collaboration are presented. Individual, social and cultural aspects are considered as new requirements on the employees of networked and extended enterprises.

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Although the computational power of mobile devices has been increasing, it is still not enough for some classes of applications. In the present, these applications delegate the computing power burden on servers located on the Internet. This model assumes an always-on Internet connectivity and implies a non-negligible latency. The thesis addresses the challenges and contributions posed to the application of a mobile collaborative computing environment concept to wireless networks. The goal is to define a reference architecture for high performance mobile applications. Current work is focused on efficient data dissemination on a highly transitive environment, suitable to many mobile applications and also to the reputation and incentive system available on this mobile collaborative computing environment. For this we are improving our already published reputation/incentive algorithm with knowledge from the usage pattern from the eduroam wireless network in the Lisbon area.

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Most definitions of virtual enterprise (VE) incorporate the idea of extended and collaborative outsourcing to suppliers and subcontractors in order to achieve a competitive response to market demands (Webster, Sugden, & Tayles, 2004). As suggested by several authors (Browne & Zhang, 1999; Byrne, 1993; Camarinha-Matos & Afsarmanesh, 1999; Cunha, Putnik, & Ávila, 2000; Davidow & Malone, 1992; Preiss, Goldman, & Nagel, 1996), a VE consists of a network of independent enterprises (resources providers) with reconfiguration capability in useful time, permanently aligned with the market requirements, created to take profit from a specific market opportunity, and where each participant contributes with its best practices and core competencies to the success and competitiveness of the structure as a whole. Even during the operation phase of the VE, the configuration can change, to assure business alignment with the market demands, traduced by the identification of reconfiguration opportunities and continuous readjustment or reconfiguration of the VE network, to meet unexpected situations or to keep permanent competitiveness and maximum performance (Cunha & Putnik, 2002, 2005a, 2005b).