Abstract
The Arteriolar-to-Venular Ratio (AVR) is an index used for the early diagnosis of diseases such as diabetes, hypertension or cardiovascular pathologies. This paper presents three automatic approaches for the estimation of the AVR in retinal images that result from the combination of different methodologies in some of the processing phases used for AVR estimation. Each one of these methods includes vessel segmentation, vessel caliber estimation, optic disc detection or segmentation, region of interest determination, vessel classification into arteries and veins and finally AVR calculation. The values produced by the proposed methods on 40 images of the INSPIRE-AVR dataset were compared with a ground-truth obtained by two medical experts using a semi-automated system. The results showed that the measured AVRs are not statistically different from the reference, with mean errors similar to those achieved by the two experts, thus demonstrating the reliability of the herein proposed approach for AVR estimation.

Abstract

Abstract
The IEC 61499 standard provides an executable model for distributed control systems in terms of interacting function blocks. However, the current IEC 61499 standard lacks appropriate timing semantics for the specification of timing requirements, reasoning on timing properties at the model level, and for the timing verification of a specific deployment. In this paper we address this fundamental shortcoming by proposing Real-Time-4-FUN, a real-time semantics for IEC 61499. The key property is the preservation of non-determinism, allowing us to reason on (and verify) timing properties at the model level without assuming any specific scheduling policy or stipulating specific order of execution for the deployment. This provides for a clear separation of concerns, where the designer can focus on properties of the application prior to, and separately from, deployment verification. The proposed timing semantics is backwards compatible to the current standard, thus allow for reuse of existing designs. The transitional property allows timing requirements to propagate to downstream sub-systems, and can be utilized for scheduling both at device and network level. Based on a translation to RTFM-tasks and resources, IEC 61499 models can be analyzed, compiled and executed. As a proof of concept the timing semantics has been experimentally implemented in the RTFM-core language and the accompanying (thread based) RTFM-RT run-time system.

Abstract
Global competition and the customers demand for customized products with shorter due dates, marked the introduction of the Extended Enterprise. In this Extended Manufacturing Environment (EME), lean, virtual, networked and distributed enterprises collaborate to respond to the market demands. In this paper we study the influence of the batch size on Flexible Flow Shop makespan minimization problem FFC||Cmax for two multi-sites approaches, the FSBF (Flow Shop Based Factories) and the PMBF (Parallel-Machines Based Factories). The computational study demonstrates how the performance of the PMBF model decreases with the increase of batch size and determines the batch sizes in which the performance is similar. © 2015 AISTI.

Abstract
High penetration of Photovoltaic (PV) systems, a variable resource, poses challenges to the stability and power quality of electrical grids. Forecasting accurately the PV power has been recognized as a way to ease this problem. This work addresses now-casting of PV power with Extreme Learning Machines (ELMs) without exogenous inputs. Wavelet decomposition and multi-resolution analysis is the most effective way to achieve high accuracy for 5 min-ahead forecast up to 70% greater than the persistence model. A neural network evaluation algorithm based on multiple initializations and incremental hidden nodes is applied and ELMs performance and computation efficiency is evaluated versus Time Delay Neural Networks (TDNNs) for time and time-frequency domain forecasting.

Abstract
The introduction of smart end-users is a vital point towards the smart grid vision. In this respect, smart households have drawn significant attention recently. Home energy management systems (HEMS) in smart households and transformer energy management units have different objectives that can sometimes be conflicting. Thus, a novel interactive optimum operating strategy that considers all possible aspects in each smart household together with internal bi-directional power flows within the household structure from economic (minimization of household daily electricity usage costs) and technical (avoidance of transformer overloading) perspective is proposed in this study. To the best knowledge of the authors, this is the first study in the literature combining all of the possible operational possibilities in HEMS of smart households together with internal household bi-directional power flows and the technical limitations of a transformer unit serving a neighborhood of smart households under a mixed-integer linear programming (MILP) framework.