2013
Authors
Shamsuzzoha, A; Kankaanpaa, T; Carneiro, LM; Almeida, R; Chiodi, A; Fornasiero, R;
Publication
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
Abstract
In order to stay competitive and avoid being smashed by large companies, small- and medium-sized enterprises (SMEs) need to establish and manage dynamic and non-hierarchical networks to respond to market opportunities, ensuring a quick response, unique products with competitive prices and high product quality. This article proposes an innovative methodological approach and ICT platform to support non-hierarchical collaboration between SMEs for customised product design and manufacturing. The ICT services are based on mapping a methodology on an open source platform in order to apply low cost solutions to SMEs. Two case studies in the fashion industry have been analysed and used to test the proposed approach for network management.
2013
Authors
Sousa, A; Matos, R;
Publication
PROCEEDINGS OF THE 2013 8TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI 2013)
Abstract
Massification of higher education institution promotes the importance of peer education and team work as important educational tools. As such, teams frequently produce several deliverables that should be organized and evaluated throughout a given course. Some submissions should then be attributed to the team rather than the individual and searching for a given type of deliverable from a given team becomes an important concern in terms of organization and ease of usage in evaluating assignments. The course "Projeto FEUP", used as case study and surely many others benefit from an at-least partially automated production of an organized set of all deliverables from a given course in a given year - a course portfolio, a task made easier by the usage of the presented ideas and the prototype implemented in the Moodle Learning Management System. This article shows details of the implementation and the lessons learned. The prototype was tested in the mentioned test course that has about one thousand students enrolled and a course portfolio was successfully created.
2013
Authors
Macedo, N; Guimaraes, T; Cunha, A;
Publication
2013 28TH IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING (ASE)
Abstract
Models are paramount in model-driven engineering. In a software project many models may coexist, capturing different views of the system or different levels of abstraction. A key and arduous task in this development method is to keep all such models consistent, both with their meta-models (and the respective constraints) and among themselves. This paper describes Echo, a tool that aims at simplifying this task by automating inconsistency detection and repair using a solver based engine. Consistency between different models can be specified by bidirectional model transformations, and is guaranteed to be recovered by minimal updates on the inconsistent models. The tool is freely available as an Eclipse plugin, developed on top of the popular EMF framework, and supports constraints and transformations specified in the OMG standard languages OCL and QVT-R, respectively.
2013
Authors
Costa, LM; Pereira, JE; Filipe, VM; Magalhaes, LG; Couto, PA; Gonzalo Orden, JM; Raimondo, S; Geuna, S; Mauricio, AC; Nikulina, E; Filbin, MT; Varejao, ASP;
Publication
BEHAVIOURAL BRAIN RESEARCH
Abstract
Numerous animal model studies in the past decade have demonstrated that pharmacological elevation of cyclic AMP (cAMP) alone, or in combination with other treatments, can promote axonal regeneration after spinal cord injury. Elevation of cAMP via the phosphodiesterase 4 (PDE4) inhibitor, rolipram, decreases neuronal sensitivity to myelin inhibitors, increases growth potential and is neuroprotective. Rolipram's ability to cross the blood-brain barrier makes it a practical and promising treatment for CNS regeneration. However, several studies have questioned the efficacy of rolipram when given alone. The purpose of this investigation was to determine the effects of continuous administration of rolipram, given alone for 2 weeks, following a moderate T10 contusion injury in rat. Functional recovery was evaluated using the 21-point Basso, Beattie and Bresnahan (BBB) locomotor recovery scale and the beam walk. We used threedimensional (3D) instrumented gait analysis to allow detailed assessment and quantification of hindlimb motion. The amount of the damaged tissue and spared white matter was estimated stereologically. Our results show that administration of rolipram following acute spinal cord contusion results in improved motor performance at each time-point. Dynamic assessment of foot motion during treadmill walking revealed a significantly decreased external rotation during the entire step cycle after 8 weeks in rolipram-treated animals. Stereological analysis revealed no significant differences in lesion volume and length. By contrast, spared white matter was significantly higher in the group treated with rolipram. Our results suggest a therapeutic role for rolipram delivered alone following acute SCI.
2013
Authors
Michell, S; Moore, B; Pinho, LM;
Publication
Ada-Europe
Abstract
The widespread use of multi-CPU computers is challenging programming languages, which need to adapt to be able to express potential parallelism at the language level. In this paper we propose a new model for fine grained parallelism in Ada, putting forward a syntax based on aspects, and the corresponding semantics to integrate this model with the existing Ada tasking capabilities. We also propose a standard interface and show how it can be extended by the user or library writers to implement their own parallelization strategies. © 2013 Springer-Verlag.
2013
Authors
Gama, J;
Publication
Informatica (Slovenia)
Abstract
The developments of information and communication technologies dramatically change the data collection and processing methods. Data mining is now moving to the era of bounded rationality. In this work we discuss the implications of the resource constraints impose by the data stream computational model in the design of learning algorithms. We analyze the behavior of stream mining algorithms and present future research directions including ubiquitous stream mining and self-adaption models.
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