Abstract
Causality tracking mechanisms, such as vector clocks and version vectors, rely on mappings from globally unique identifiers to integer counters. In a system with a well known set of entities these ids can be preconfigured and given distinct positions in a vector or distinct names in a mapping. Id management is more problematic in dynamic systems, with large and highly variable number of entities, being worsened when network partitions occur. Present solutions for causality tracking are not appropriate to these increasingly common scenarios. In this paper we introduce Interval Tree Clocks, a novel causality tracking mechanism that can be used in scenarios with a dynamic number of entities, allowing a completely decentralized creation of processes/replicas without need for global identifiers or global coordination. The mechanism has a variable size representation that adapts automatically to the number of existing entities, growing or shrinking appropriately. The representation is so compact that the mechanism can even be considered for scenarios with a fixed number of entities, which makes it a general substitute for vector clocks and version vectors.

Abstract
This paper presents a new classification approach to deal with class imbalance in TLC patterns, which is due to the huge difference between the number of normal and pathological cases as a consequence of the rarity of LSD diseases. The proposed architecture is formed by two decision stages: the first is implemented by a one-class classifier aiming at recognizing most of the normal samples; the second stage is a hierarchical classifier which deals with the remaining outliers that are expected to contain the pathological cases and a small percentage of normal samples. We have also evaluated this architecture by a forest of classifiers, using the majority voting as a, rule to generate the final classification. The results that were obtained proved that this approach is able to overcome some of the difficulties associated with class imbalance.

Abstract
In this paper, we present beam search heuristics for the single machine early/tardy scheduling problem with job-independent penalties, and no machine idle time. These heuristics include priority and detailed classic beam search algorithms, as well as filtered and recovering procedures. Three dispatching rules are considered as evaluation functions, in order to analyse the effect of different rules on the performance of the beam search heuristics. The computational results show that the performance of the beam search procedures does improve with the quality of the dispatching rule. The detailed and recovering algorithms clearly Outperform the best existing heuristic, and the improvement is particularly higher for the more difficult instances. The detailed beam search algorithm provides the best performance, and is recommended for small to medium size instances. For larger instances, however, this algorithm requires excessive computation times. The recovering beam search procedure is computationally more efficient, and is then the heuristic of choice for medium to large instances.

Abstract
Battery-powered electric vehicle appear to be one of the viable solutions for the growing concerns for environmental protection and the fast rate of depletion of world fuel oil supply. This type of vehicle can become a viable alternative to the internal combustion engine only if they are able to meet certain reliability, safety, performance, and cost criteria. In addition, this type of electrical vehicles have serious disadvantages because of the limitation on cruising range imposed by weight, capacity of the electric accumulators and long recharging time. Improvement of efficiency of induction motor traction drives is an important issue in pure electric vehicles to improve the running distance on one charge. In this paper, the authors evaluate a loss-minimization algorithm (LMA) by considering their influence on the performance of the vehicle. The evaluation of the proposed LMA is demonstrated experimentally under different operating conditions of the vehicle.

Abstract
Ontologies are a technological key factor regarding the knowledge management domain. This paper presents a graphical-based knowledge representation approach using concept maps towards creating a formal work organization ontology, which was translated into a Content Management System in order to manage the work design information. Some aspects related with the advantages of visual approaches for collaborative development of ontologies are discussed.

Abstract
This paper describes a mathematical model and the developed solution algorithm to solve an integrated active/reactive dispatch while retaining competitive aspects. The main drive for this research was the recognition that the introduction of competitive mechanisms lead to a certain extent to a decoupling between active and reactive power scheduling. Aiming at remarrying them, the developed approach includes an initial bid based uniform price active power auction run by the Market Operator, followed by a technical validity analysis run by the System Operator. If necessary, the System Operator uses adjustment bids to recover the technical feasibility of the dispatch. These bids are presented both by the demand and by generators meaning that demand can play an important role in increasing the liquidity of this specific market. This approach also includes capacitor banks and transformer taps leading to a combinatorial problem solved using Simulated Annealing. Finally, the paper includes results from a case study based on the IEEE 24 Bus Test System to illustrate the interest of this type of approaches.