Abstract
The smart grid concept increases the observability and controllability of the distribution system, which creates conditions for bi-directional control of Distributed Energy Resources (DER). The high penetration of Renewable Energy Resources (RES) in the distribution grid may create technical problems (e.g., voltage problems, branch congestion) in both transmission and distribution systems. The flexibility from DER can be explored to minimize RES curtailment and increase its hosting capacity. This paper explores the use of the Monte Carlo Simulation to estimate the flexibility range of active and reactive power at the boundary nodes between transmission and distribution systems, considering the available flexibility at the distribution grid level (e.g., demand response, on-load tap changer transformers). The obtained results suggest the formulation of an optimization problem in order to overcome the limitations of the Monte Carlo Simulation, increasing the capability to find extreme points of the flexibility map and reducing the computational effort.

Abstract
This paper presents an enhanced simulation platform composed by the integration of two distinct multi-agent based simulators. The two simulators are: (i) the Multi-Agent Simulator of Competitive Electricity Markets (MASCEM), which provides a simulation platform for electricity markets participation, considering scenarios based on real data from several distinct market operators; and (ii) the Multi-Agent Smart Grid Platform (MASGriP), which facilitates the simulation of smart grids and microgrids, by modeling the power network at the distribution level, and representing the main entities that act in this scope. With the cooperation between the two simulation platforms, huge studying opportunities under different perspectives are provided, resulting in an important contribution in the fields of transactive energy, electricity markets, and smart grids. A case study is presented, showing the potentialities for interaction between players of the two ecosystems, namely by demonstrating a case in which a smart grid operator, which manages the internal resources of a smart grid, is able to participate in electricity market negotiations to sell the surplus of generation in some periods of the day, and buy the necessary power to satisfy the demand of smart grid consumers in other periods of the day. © 2015 IEEE.

Abstract
Fast volumetric cardiac imaging requires to reduce the number of transmit events within a single volume. One way of achieving this is by limiting the field-of-view (FOV) of the recording to the anatomically relevant domain only (e.g. the myocardium when investigating cardiac mechanics). Although fully automatic solutions towards myocardial segmentation exist, translating that information in a fast ultrasound scan sequence is not trivial. The aim of this study was therefore to develop a methodology to automatically define the FOV from a volumetric dataset in the context of anatomical scanning. Hereto, a method is proposed where the anatomical relevant space is automatically identified as follows. First, the left ventricular myocardium is localized in the volumetric ultrasound recording using a fully automatic real-time segmentation framework (i.e. BEAS). Then, the extracted meshes are employed to define a binary mask identifying myocardial voxels only. Later, using these binary images, the percentage of pixels along a given image line that belong to the myocardium is calculated. Finally, a spatially continuous FOV that covers 'T' percentage of the myocardium is found by means of a ring-shaped template matching, giving as a result the opening angle and 'thickness' for a conical scan. This approach was tested on 27 volumetric ultrasound datasets, a T = 85% was used. The mean initial opening angle for a conical scan was of 19.67±8.53° while the mean 'thickness' of the cone was 19.01±3.35°. Therefore, a reduction of 48.99% in the number of transmit events was achieved, resulting in a frame rate gain factor of 1.96. As a conclusion, anatomical scanning in combination with new scanning sequences techniques can increase frame rate significantly while keeping information of the relevant structures for functional imaging. © 2015 IEEE.

Abstract
In this paper, an indirect approach to the dual-mode adaptive robust controller (DMARC) is proposed, which combines the typical transient and robustness properties of variable structure systems with a smooth control signal in steady state, typical of conventional adaptive controllers, as model reference adaptive controller. The aim of this indirect version, here named indirect DMARC, is to provide a more intuitive controller design, based on physical plant parameters, as resistances, inertia moments, capacitances, and so on, maintaining DMARC properties. In this paper, a stability analysis for the proposed controller and simulations to an unstable second-order plant will be presented. Copyright (c) 2013 John Wiley & Sons, Ltd.

Abstract
The continuous change in the manufacturing world is demanding more flexible, responsive and accurate planning tools, which are able to assist the decision-makers to take tactical and strategic decisions on short notice with a high level of confidence. For this purpose, these tools should dynamically explore different operative scenarios in the planning procedure and produce information about key performance indicators. This paper describes the development of an agent-based strategic planner, combining the flexibility of multi-agent systems principles with the optimization capability of a Mixed Integral Programming technique. The tool is integrated in an ecosystem of heterogeneous decision-making systems through an Enterprise Service Bus that also provides access to legacy data.

Abstract
Rendering photorealistic images is a costly process which can take up to several days in the case of high quality images. In most cases, the task of sampling the incident radiance function to evaluate the illumination integral is responsible for an important share of the computation time. Therefore, to reach acceptable rendering times, the illumination integral must be evaluated using a limited set of samples. Such a restriction raises the question of how to obtain the most accurate approximation possible with such a limited set of samples. One must thus ensure that sampling produces the highest amount of information possible by carefully placing and weighting the limited set of samples. Furthermore, the integral evaluation should take into account not only the information brought by sampling but also possible information available prior to sampling, such as the integrand smoothness. This idea of sparse information and the need to fully exploit the little information available is present throughout this book. The presented methods correspond to the state-of-the-art solutions in computer graphics, and take into account information which had so far been underexploited (or even neglected) by the previous approaches. The intended audiences are Ph.D. students and researchers in the field of realistic image synthesis or global illumination algorithms, or any person with a solid background in graphics and numerical techniques. Table of Contents: Introduction / Spherical Fibonacci Point Sets for QMC Estimates of Illumination Integrals / Bayesian Monte Carlo for Global Illumination / Bibliography / Authors' Biographies Copyright © 2015 by Morgan & Claypool.