Abstract
The concept of combining the power of several independent factories to achieve complex manufacturing processes as so-called virtual manufacturing enterprises is not new and has been addressed by several research projects in recent years. However, there is still a need for adequate methodological support and tools for modelling, structuring and controlling of the next generation of manufacturing systems, such as the virtual factory. In this research, a conceptual virtual factory reference model is presented with the goal to provide companies with general guidelines to manage and monitor the business processes that are needed to create, execute, and dissolve a virtual factory. The virtual factory reference model was built taking into account industrial's requirements and by reviewing the literature in several relevant fields of research such as collaborative networks, supply networks, manufacturing networks, supply chain management, and business processes. Afterwards, it has been validated through its application to future virtual factories of three different industrial sectors: machinery, energy, and semiconductor.

Abstract
Over the last few decades, surveillance applications have been an extremely useful tool to prevent dangerous situations and to identify abnormal activities. Although, the majority of surveillance videos are often subjected to different noises that corrupt structured patterns and fine edges. This makes the image processing methods even more difficult, for instance, object detection, motion segmentation, tracking, identification and recognition of humans. This paper proposes a novel filtering technique named robust bilateral and temporal (RBLT), which resorts to a spatial and temporal evolution of sequences to conduct the filtering process while preserving relevant image information. A pixel value is estimated using a robust combination of spatial characteristics of the pixel's neighborhood and its own temporal evolution. Thus, robust statics concepts and temporal correlation between consecutive images are incorporated together which results in a reliable and configurable filter formulation that makes it possible to reconstruct highly dynamic and degraded image sequences. The filtering is evaluated using qualitative judgments and several assessment metrics, for different Gaussian and Salt Pepper noise conditions. Extensive experiments considering videos obtained by stationary and non-stationary cameras prove that the proposed technique achieves a good perceptual quality of filtering sequences corrupted with a strong noise component.

Abstract
This paper explores a technique denoted LASCA to solve large scale optimization problems with metaheuristics by reducing the search space dimension with autoassociative neural networks. The technique applies autoencoders as a reversible mapping between the original problem space and a reduced space. A metaheuristic then evolves in the latter, having its objective function assessed in the original space. The technique is illustrated with an application of an Evolutionary Particle Swarm Optimization (EPSO) algorithm to four benchmarking unconstrained optimization functions and to a wind-hydro constrained coordination problem. The new technique allows an improvement in the quality of the solutions attained.

Abstract
Emerging technologies arising in modern power systems have propelled the presence of new agents to manipulate these facilities. Participation of plug-in electric vehicles (PIEVs) in the electricity market is one of the main issues in this environment. PIEV participation in market place can affect the agent's strategy. Therefore, this paper investigates two states of power system where individual aggregators participate in the power market on behalf of home-charged PIEVs and parking lots (PLs) separately, as well as the coordinated version of the problem. Several scenarios are developed for deriving specific characteristics of PIEVs in home levels and in PLs. An optimization model is built and solved using mixed integer linear programming. The results are produced to suggest the optimum procedure for an aggregator to whether take the authority of home-charging PIEVs and PLs individually or coordinately.

Abstract
A system using laser speckle effect is proposed to segment images reflecting vibration movements of diffuse targets. Longitudinal movements are difficult to identify when simple imaging systems are used. The proposed system produces a two dimensional segmentation of the target and it is sensitive to longitudinal movements. The speckle effect, produced when coherent light is reflected and interferes when hitting rough surfaces, can be used in order to accomplish this purpose. A pattern with high and low intensity spots is observed depending on the illuminated scene. In our optical system, two silicone membranes are illuminated using a beam expanded laser source and their patterns are recorded using a video camera. One of the membranes experiences a longitudinal controlled movement while the remaining scene is still. Speckle data is processed using a temporal gradient and a regional entropy computation. This method produces a binary individual pixel classification. Four sets of parameters have been tested for the entropy computation and the area under the receiver operating characteristic (ROC) curve was used to select the best one. The selected set-up achieved a ROC value of 0.9879. A data set with 12 different membrane velocities was used to define the threshold that maximizes the classifier accuracy. This threshold was applied to a validation data-set composed by 4 sinusoidal movements with distinct velocities. The accuracy of this technique has achieved values between 92% and 97%. The results show that the target was accurately identified with the optical non-contact apparatus and the developed algorithm.

Abstract
APEX was developed as a framework for ubiquitous computing (ubicomp) prototyping through virtual environments. In this paper the framework is used as a platform for developing a serious game designed to instruct and to inform. The paper describes the Asthma game, a game aimed at raising awareness among children of asthma triggers in the home. It is designed to stimulate a healthier life-style for those with asthma and respiratory problems. The game was developed as the gamification of a checklist for the home environment of asthma patients.