Abstract
This paper presents an optimal framework for the resilience-oriented design (ROD) in distribution networks to protect these grids against extreme weather events such as earthquakes and floods. This strategy minimizes the summation of daily investment and repair costs of back up distributed generation (DG), hardening and tie lines, operation cost of network and DGs, and load shedding cost. Also, it considers AC power flow equations, system operation limits and planning and reconfiguration constraints. This problem is generally a mixed integer nonlinear programming (MINLP) problem, but it is converted to a mixed integer linear programming (MILP) problem to achieve a globally optimal solution with a low computation time. Moreover, the Benders decomposition (BD) approach is used for the proposed problem to obtain higher computation speed in large scale networks. In addition, this problem includes uncertain parameters such as load, energy price, and availability of network equipment in the case of extreme weather conditions. Hence, a scenario-based stochastic programming (SBSP) approach is used to model these uncertain parameters in the proposed ROD method, based on a hybrid approach, including roulette wheel mechanism (RWM) and the simultaneous backward method. The proposed problem is simulated on 33-bus and large-scale 119-bus distribution networks to prove its capabilities in different case studies.

Abstract
The need for the operational reserve is growing due to the increase of variability and intermittency in both generation and demand sides. Hence, energy storage systems (ESSs) are considered as an alternative source of the reserve, while conventional generators are not efficient based on economic and environmental perspectives. This paper studies an enhanced model for ESSs? participation as a fast reserve provider. The day-ahead scheduling of ESSs within scenarios disturbs their stored energy in the sequence of hours. This issue can dramatically increase or decrease the stored energy of ESSs and threatens the safety of operational planning. The proposed model of this paper introduces coordination strategies for the deployment of fast reserves of ESSs. The stochastic model of this paper considers the fluctuations of wind speed and also the load forecasting errors as the source of uncertainties. A decomposition-based method is employed to reduce the complexity of the model dealing with a large number of variables. A modified version of the IEEE RTS-24 test system is used to evaluate different strategies for managing of ESSs? reservoir. The result shows that large deviations of the reservoir can make the operation of ESSs infeasible in uncoordinated strategies. Also, two proposed strategies for performance under normal and conservative criteria provide choices for system operators based on the desired level of security. Besides, the deployment of fast reserves of ESSs improves operation quality by the money-saving and increasing the quality of power delivery.

Abstract

Abstract
The increase of global competitiveness, the ability of organizations to effectively use information technologies, and to focus on innovation and creativity are recognized as being important. In this context, the hypothesis of resorting to known creativity techniques or adaptations to help innovation in the field of Software Engineering appears to be challenging. This paper proposes a methodology for introducing creativity and innovation techniques in the Requirements Engineering process in order to build more agile and efficient Information Systems. The method uses a variety of creative techniques that are thought to be appropriate to the different stages of the process and is inspired by existing creative problem-solving methods and techniques, in particular in the Creative Problem-Solving Process, Productive Thinking Model and the Creative Potentiation Method. The study of the method allowed its application, through the use of various creativity techniques, in a real context in a social institution - the Social Center for Support to the Community of São Domingos. The application of the methodology allowed the identification of new opportunities that allowed the organization to devise service delivery strategies that were more suited to the needs of people.

Abstract
Electrical energy consumption pattern has always been important for power distribution companies, because load variations and method of electricity consumption affect energy losses amount. For this, distribution companies frequently encourage the network users to correct their energy consumption behavior by suggesting some incentives. Reconfiguration of distribution systems for a specific load pattern is an effective way to reduce the losses. Hence, some papers have considered load variations in distribution system reconfiguration (DSR) to show importance of consumption pattern for reconfiguration decisions. However, most of specialized studies have been ignored load changes in their reconfiguration models because of a significant increase in computational burden and processing time. On the other hand, neglecting the consumption pattern causes the energy losses is calculated inaccurately. Therefore, this paper intends to evaluate effect of load pattern on reconfiguration plans in order to find out importance of considering load variations in energy losses minimization via DSR. The analysis has been conducted on well-known distribution systems by AMPL (a classic optimization tool).

Abstract
Lower limb amputation is a condition affecting millions of people worldwide. Patients are often prescribed with lower limb prostheses to aid their mobility, but these prostheses require frequent adjustments through an iterative and manual process, which heavily depends on patient feedback and on the prosthetist's experience. New computer-aided design and manufacturing technologies have been emerging as a way to improve the fitting process by creating virtual socket models. Statistical Shape modelling was used to create 3D models of transtibial (TT) and transfemoral (TF) sockets. Their generalization errors were, respectively, 6.8 +/- 1.8 mm and 10.5 +/- 1.6 mm, while specificity errors were 9.7 +/- 0.6 mm and 9.8 +/- 0.2 mm. In both models, a visual analysis showed that biomechanically meaningful features were captured: the largest variations found for both types were in the length of the residual limb and in the perimeter variation along the limb. The results obtained proved that statistical shape modelling methods can be applied to TF and TT sockets, with several potential applications in the orthoprosthetic field: generation of new plausible shapes and on-demand socket design adjustments.