Abstract
In this paper, we consider the single machine earliness/tardiness scheduling problem with different release dates and no unforced idle time. The problem is decomposed into weighted earliness and weighted tardiness subproblems. Lower bounding procedures are proposed for each of these subproblems, and the lower bound for the original problem is the sum of the lower bounds for the two subproblems. The lower bounds and several version, of a branch-and-bound algorithm are then tested on a set of randomly generated problems, and instances with up to 30 jobs are solved to optimality. To the best of our knowledge, this is the first exact approach for the early/tardy scheduling problem with release dates and no unforced idle time.

Abstract
This paper is concerned with design considerations and tradeoffs involved in the power electronics development for light electric vehicles. A review of propulsion system design, power conversion structure and control is presented. A three-phase squirrel-cage induction motor is used as propulsion system for an electric scooter. The motor is controlled at different operating conditions by means of a simple scalar control using a low cost controller board developed for light electric vehicles used in local areas. Experimental results show that the proposed digital controller is able to follow the reference speed with a suitable dynamics for the electric scooter.

Abstract
In this paper, a new operational strategy regarding islanding operation is presented exploiting Distributed Generation for islanding; purposes. The presence of DG may be used to enhance reliability to final consumers by providing an alternative power source when there is an interruption in the upstream network. The feasibility of this type of operation in distribution networks is analyzed in a case study by analyzing the behavior of different generating units and protection settings.

Abstract
A dispatch rule and a greedy procedure are presented for the single machine earliness/tardiness scheduling problem with no idle time and compared with the best of the existing dispatch rules. Both dispatch rules use a lookahead parameter that had previously been set at a fixed value. We develop functions that map some instance statistics into appropriate values for that parameter. We also consider the use of dominance rules to improve the solutions obtained by the heuristics. The computational results show that the function-based versions of the heuristics outperform their fixed value counterparts and that the use of the dominance rules can indeed improve solution quality with little additional computational effort.

Abstract
The emergence of micro-generation as a technically sound alternative has lead, in recent times, to the concept of microgrid, a network of LV consumers and producers able to export electric energy in some circumstances and also to work in a isolated way in emergency situations. Research work about the organization of microgrids, control devices, functionalities and other technical and economic aspects is presently being carried out, in order to establish a consistent technical framework to support the concept. Among other aspects, the effect of microgrids in the reliability of the distribution network has been pointed out as an important advantage, due to the ability of isolated operation in emergency situations. In order to address this topic, the present paper identifies the situations where the existence of a microgrid may reduce the interruption rate and time and thus improve the reliability indices of the distribution network. The relevant expressions necessary to quantify the reliability are also presented. An illustrative example is included, where the global influence of the microgrid in reliability is commented.

Abstract
Thin-Layer Chromatography images are used to detect and identify the presence of specific oligosaccharides, expressed by the existence, at different positions, of bands in the gel image. 1D gaussian deconvolution, commonly used for band detection, does not produce good results due to the large curvature observed in the bands. To overcome this uncertainty on the band position, we propose a novel feature extraction methodology that allows an accurate modeling of curved bands. The features are used to classify the data into two different classes, to differentiate normal from pathologic cases. The paper presents the developed methodology together with the analysis and discussion of the results.