Abstract
This paper addresses the developing of Learning-Assisted Intelligent Scheduling Systems that uses active learning by accumulation and interpretation of scheduling experience or even by observation of expert's decisions. The design of intelligent systems (IS) that learn with experts is a very hard and challenging domain because current systems are becoming more and more complex and subject to rapid changes. The model for the proposed system will be presented.

Abstract
The Arterial Pressure Waveform (APW) can provide essential information about arterial wall integrity and arterial stiffness. Most of APW analysis frameworks individually process each hemodynamic parameter and do not evaluate inter-dependencies in the overall pulse morphology. The key contribution of this work is the use of machine learning algorithms to deal with vectorized features extracted from APW. With this purpose, we follow a five-step evaluation methodology: (1) a custom-designed, non-invasive, electromechanical device was used in the data collection from 50 subjects; (2) the acquired position and amplitude of onset, Systolic Peak (SP), Point of Inflection (Pi) and Dicrotic Wave (DW) were used for the computation of some morphological attributes; (3) pre-processing work on the datasets was performed in order to reduce the number of input features and increase the model accuracy by selecting the most relevant ones; (4) classification of the dataset was carried out using four different machine learning algorithms: Random Forest, BayesNet (probabilistic), J48 (decision tree) and RIPPER (rule-based induction); and (5) we evaluate the trained models, using the majority-voting system, comparatively to the respective calculated Augmentation Index (AIx). Classification algorithms have been proved to be efficient, in particular Random Forest has shown good accuracy (96.95%) and high area under the curve (AUC) of a Receiver Operating Characteristic (ROC) curve (0.961). Finally, during validation tests, a correlation between high risk labels, retrieved from the multi-parametric approach, and positive AIx values was verified. This approach gives allowance for designing new hemodynamic morphology vectors and techniques for multiple APW analysis, thus improving the arterial pulse understanding, especially when compared to traditional single-parameter analysis, where the failure in one parameter measurement component, such as Pi, can jeopardize the whole evaluation. © 2013 by the authors; licensee MDPI, Basel, Switzerland.

Abstract
In clinical practice, high-resolution computed tomography (HRCT) is a reference in the diagnosis, quantification, and follow-up of lung emphysema. In this study, differential lacunarity analysis was applied to HRCT images of the chest in order to quantify the texture of healthy and emphysematous regions of the lung parenchyma. The used approach to compute lacunarity is a multiscale technique that takes advantage of the extensive scale used in the acquisition of CT images. The results show that the extracted features are discriminatory of the considered lung patterns, being suitable to integrate clinical applications for the characterization of disease patterns in HRCT images.

Abstract
This work presents numerical results related to an in-line Mach-Zehnder interferometer used as a refractive index sensor. The in-line Mach-Zehnder is based on abrupt tapers in standard single mode optical fiber. Numerical simulations were carried out using commercial software based on Beam Propagation Method in order to analyze the sensitivity response in terms of wavelength shift when this sensor is bent at certain radii of curvature. We realized that application of bending in the In-line Mach-Zehnder interferometer enhanced considerably the sensitivity of this sensor to the external refractive index. The best result was achieved for a radius of curvature of 10 mm (similar to 500 nm/RIU for the refractive index range of 1.33 to 1.41) improving the sensitivity about eight times in comparison with the case with no bent.

Abstract
This book provides techniques to tackle the design challenges raised by the increasing diversity and complexity of emerging, heterogeneous architectures for embedded systems. It describes an approach based on techniques from software engineering called aspect-oriented programming, which allow designers to control today's sophisticated design tool chains, while maintaining a single application source code. Readers are introduced to the basic concepts of an aspect-oriented, domain specific language that enables control of a wide range of compilation and synthesis tools in the partitioning and mapping of an application to a heterogeneous (and possibly multi-core) target architecture. Several examples are presented that illustrate the benefits of the approach developed for applications from avionics and digital signal processing. Using the aspect-oriented programming techniques presented in this book, developers can reuse extensive sections of their designs, while preserving the original application source-code, thus promoting developer productivity as well as architecture and performance portability. Describes an aspect-oriented approach for the compilation and synthesis of applications targeting heterogeneous embedded computing architectures. Includes examples using an integrated tool chain for compilation and synthesis. Provides validation and evaluation for targeted reconfigurable heterogeneous architectures. Enables design portability, given changing target devices. Allows developers to maintain a single application source code when targeting multiple architectures. © Springer Science+Business Media New York 2013. All rights are reserved.

Abstract
Large deployment of distributed generation into distribution systems brings new challenges regarding the shift from the passive to the active control paradigm. These challenges have been extended to the field of dynamic equivalence. Developing effective reduced order models for active distribution network cells for dynamic and stability studies require a careful evaluation of the techniques that have been used in conventional power systems. Thus, a survey of the existing approaches is presented in this paper. Also a critical overview is provided regarding their application to active distribution network cells and microgrids. Technical requirements are identified and recommendations are provided.