Abstract
Network oversubscription has long been used by Internet Service Providers (ISPs). While high oversubscription ratios can hamper the end user experience, low oversubscription rates may result in an under-utilization of resources. This paper investigates the impacts of oversubscription, both from a technical (OpEx, Energy footprint etc.) and from a value network point of view (Control and Value creation etc.). A multi-parameter sensitivity analysis of a power model is performed to establish that the choice of oversubscription ratio by an ISP can have a serious impact on their operational energy and capital expenditures. As a next step, a set of business model parameters are operationalized in order to evaluate and establish long-term and short-term impacts of network oversubscription on business stakeholders. Key findings include that there is a need to establish a fit between the technical and business gains of network oversubscription, and that is possible only when an ISP leverages its control and influence over its customer base to better understand and anticipate the network usage, thereby being able to promptly adapting the overall network oversubscription ratios. © 2012 IFIP International Federation for Information Processing.

Abstract
The Unit Commitment (UC) problem is a wellknown combinatorial optimization problem arising in operations planning of power systems. It is typically formulated as nonlinear mixed-integer programming problem and has been solved in the literature by a huge variety of optimization methods, ranging from exact methods (such as dynamic programming, branch-and-bound) to heuristic methods (genetic algorithms, simulated annealing, particle swarm). Here, we start by formulating the UC problem as a mixed-integer optimal control problem, with both binary-valued control variables and real-valued control variables. Then, we use a variable time transformation method to convert the problem into an optimal control problem with only real-valued controls. Finally, this problem is transcribed into a finite-dimensional nonlinear programming problem to be solved using an optimization solver.

Abstract

Abstract
With the advent of power system restructuring, there is now competition on the generation activity and the generation mix changed in many countries with the incentives to induce investments in renewables, in many cases, using volatile primary resources. Given this increase of the installed capacity in wind parks and PV stations as well as in hydro stations (as a way to address the mentioned volatility), investments in large thermal stations became more risky. In this scope, this paper describes a long term generation expansion planning model that can be used by generation companies to investigate the profitability of new thermal generation investments considering the increasing presence of renewables. This long term simulation tool uses System Dynamics, a framework particularly suited to mode the long term dependencies between different variables while incorporating delays on some decisions. At a final section this paper includes a Case Study based on a generation system that corresponds to a scaled version of the Portuguese system.

Abstract
Dermoscopy is a non-invasive diagnostic technique for the in vivo observation of pigmented skin lesions, and it is currently one of the most important imaging techniques for melanoma diagnosis. Since the diagnostic accuracy of dermoscopy significantly depends on the experience of the dermatologists, and the visual interpretation and examination of this kind of images is time consuming, several computer-aided diagnosis systems of digital dermoscopic images have been introduced. However, a reliable ground truth database of manually segmented images is necessary for the development and validation of automatic segmentation and classification methods. As the ground truth database have to be created by expert dermatologists, there is a need for the development of annotation tools that can support the manual segmentation of dermoscopic images, and this way make this task easier and practicable for dermatologists. In this paper we present an annotation tool for manual segmentation of dermoscopic images. This tool allows building up a ground truth database with the manual segmentations both of pigmented skin lesions and of other regions of interest, whose recognition is essential for the development of computer-aided diagnosis systems. © 2012 ACM.

Abstract
A probabilistic framework is defined to evaluate the values of the Confidence Factors (CFs) proposed in Eurocode 8 Part 3 (EC8-3) for the characterization of material properties. This evaluation is presented for the concrete compressive strength but its validity for other material properties can also be inferred from the results obtained. The number of material tests and the existence of prior knowledge are the essential aspects for the CF quantification. The probabilistic framework proposed in the first part of the study does not consider the existence of prior knowledge and is based on the concept of confidence intervals. In the second part of the study, the effects of prior knowledge are considered using a Bayesian framework. The combination of testing data obtained from different types of tests is also addressed as an extension of the referred Bayesian approach. Results indicate that the EC8-3 proposed CFs for KL1 and KL2 are adequate, but for KL3 it is suggested that a larger value should be used.