Abstract
The pulse pressure waveform has, for long, been known as a fundamental biomedical signal and its analysis is recognized as a non-invasive, simple, and resourceful technique for the assessment of arterial vessels condition observed in several diseases. In the current paper, waveforms from non-invasive optical probe that measures carotid artery distension profiles are compared with the waveforms of the pulse pressure acquired by intra-arterial catheter invasive measurement in the ascending aorta. Measurements were performed in a study population of 16 patients who had undergone cardiac catheterization. The hemodynamic parameters: area under the curve (AUC), the area during systole (AS) and the area during diastole (AD), their ratio (AD/AS) and the ejection time index (ETI), from invasive and non-invasive measurements were compared. The results show that the pressure waveforms obtained by the two methods are similar, with 13% of mean value of the root mean square error (RMSE). Moreover, the correlation coefficient demonstrates the strong correlation. The comparison between the AUCs allows the assessment of the differences between the phases of the cardiac cycle. In the systolic period the waveforms are almost equal, evidencing greatest clinical relevance during this period. Slight differences are found in diastole, probably due to the structural arterial differences. The optical probe has lower variability than the invasive system (13% vs 16%). This study validates the capability of acquiring the arterial pulse waveform with a non-invasive method, using a non-contact optical probe at the carotid site with residual differences from the aortic invasive measurements.

Abstract
This paper describes the major elements of the Goldratt's framework - the Theory of Constraints (TOC) - in the banking sector, and examines the factors involved in the decision to adopt the TOC by companies in this sector. Through a deep literature review, analyzing similar cases that apply the Goldratt's framework in services and in manufacturing and the several views of its components, we aim at formulating a framework specifically for the banking system. The study uses a qualitative methodology supported by the information extracted from reality as it is framed in a multi-case study model. As part of the quantitative approach, we test several research hypotheses raised from the review of existing studies in the area. The main factors that influence the decision to adopt the TOC are the nature and the characteristics of the banking service, the attitude towards change, the leadership and the commitment of the entire institution. By using the Goldratt's approach outlined in this article, through the location of the constraints and develop practical measurement to facilitate the banking process improvements, banks can improve resource utilization, revenues and employee satisfaction.

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.