Abstract
This paper addresses the allocation of electrical losses in distribution networks with embedded generation, in a liberalized environment. The nonlinear nature of the issue, the loss changes due to voltage variation and, specially, the contribution of embedded generation to loss variation are considered. The proposed method is based on tracing the real and imaginary parts of the currents and has two steps. First, the losses in the distribution network, in the absence of embedded generation, are allocated to the consumers (or their providers). Second, the variations in the losses that result from the influence of embedded generation are allocated to the generatorsi These variations are a measure of the avoided or added costs related to losses. In the allocation process, made in a branch basis, both real and reactive powers are considered. The methodology presented in this paper can be used to evaluate embedded generation incentives or to design tariffs for the use of the distribution network.

Abstract
This paper presents and proposes a new approach to achieve robust speed estimation in induction motor sensorless control. The estimation method is based on a reduced-order Extended Kalman Filter (EKF), instead of a full order EKF. The EKF algorithm uses a reduced-order statespace model structure that is discretized in a particular and innovative way proposed in this paper. With this model structure, only the rotor flux components are estimated, besides the rotor speed itself. Important practical aspects and new improvements are introduced that enable us to reduce the execution time of the algorithm without difficulties related to the tuning of covariance matrices, since the number of elements to be adjusted is reduced.

Abstract
In this paper we propose a method for grouping and summarizing large sets of association rules according to the items contained in each rule. We use hierarchical clustering to partition the initial rule set into thematically coherent subsets. This enables the summarization of the rule set by adequately choosing a representative rule for each subset, and helps in the interactive exploration of the rule model by the user. We define the requirements of our approach, and formally show the adequacy of the chosen approach to our aims. Rule clusters can also be used to infer novel interest measures for the rules. Such measures are based on the lexicon of the rules and are complementary to measures based on statistical properties, such as confidence, lift and conviction. We show examples of the application of the proposed techniques.

Abstract
Although ontology has gained wide attention in the area of information systems, a criticism typical of the early days is still rehearsed here and there. Roughly, this criticism says: general ontologies are not suited for real applications. We believe this is the result of a misunderstanding of the role of general ontologies since, we claim, even foundational ontologies (the most general and formal ontologies) have a crucial role in building reusable, adaptable and transparent application systems. We support this view by showing how foundational ontologies can be used in the manufacturing control area. Our approach (partially presented here through an example) provides a domain-specific ontology which is explicitly designed for applications, theoretically organized by a foundational ontology, driven by the application field for all intents and purposes, suitable for communication across different applications.

Abstract
An optical fiber sensing system, for monitoring oxygen aiming in vivo nuclear magnetic resonance (NMR) applications is presented. Oxygen detection is based on the dynamic quenching of the fluorescence of a ruthenium complex trapped in the porous structure of a sol-gel silica film. Oxygen concentration is determined by phase-modulation fluorometry. Preliminary results concerning the characterization of doped sol-gel thin films deposited by dip coating in glass slides and in optical fiber probes are presented. Four different probe configurations are tested and compared. Best results are obtained with a fiber taper configuration which shows reproducibility and best excitation efficiency. This structure is fully characterized and some considerations regarding optimal fiber optical sensing probes for 02 detection are addressed.

Abstract
In this paper we describe random start local search and tabu search for solving a multi-item, multi-machine discrete lot sizing and scheduling problem with sequence dependent changeover costs. We present two construction heuristics with a random component; one of them is purely random and another is based on the linear programming relaxation of the mixed integer programming model. They are used to generate initial solutions for random start local search and tabu search. We also propose two ways of exploring the neighborhoods, one based on a random subset of the neighborhood, and another based on exploring the whole neighborhood. Construction and improvement methods were combined on random start local search and tabu search, leading to a total of eight different methods. We present results of extensive computer experiments for analyzing the performance of all methods and their comparison with branch-and-bound, and conclude with some remarks on the different approaches to the problem.