Abstract
With the recent liberalization of electricity markets, market players need to decide whether to and how to participate in each electricity market type that is available to them. The search for the best opportunities to sell or buy the required energy is, however, not an easy task. Moreover, the changes that electricity markets are constantly suffering make this an highly dynamic environment, with huge associated unpredictability. Decision support tools become, therefore, essential for market players to be able to take the best advantage from market participation. This paper proposes a methodology to estimate the expected prices of bilateral contracts based on the analysis of contracts' historic log. The proposed method is based on the application of a clustering methodology that groups the historic contracts according to their prices' similarity. The optimal number of groups is automatically calculated taking into account the preference for the balance between the estimation error and the number of groups. The centroids of each cluster are used to define a dynamic fuzzy variable that approximates the tendency of contracts' history. The resulting fuzzy variable allows estimating expected prices for contracts instantaneously and approximating missing values in the historic contracts log.

Abstract
A study on the influence of titanium on the diffusion kinetics of erbium in lithium niobate is presented. An empirical linear relation between the diffusion coefficient of erbium and the initial film thickness of titanium was obtained from secondary ion mass spectrometry data. An improvement in the diffusion coefficient by a factor of two was measured for a 200-nm titanium film. Furthermore, the erbium and titanium codiffusion process not only enhances the diffusion of erbium, leading to smaller diffusion time, but also improves the device visibility for further fabrication procedures. This letter is envisioned to clarify in a quantitative way the process of simultaneous codiffusion of erbium and titanium ions into lithium niobate, which has been studied by several authors; nevertheless, no definitive conclusion can be found in the literature.

Abstract
This paper presents a local search, based on a new neighborhood for the job-shop scheduling problem, and its application within a biased random-key genetic algorithm. Schedules are constructed by decoding the chromosome supplied by the genetic algorithm with a procedure that generates active schedules. After an initial schedule is obtained, a local search heuristic, based on an extension of the 1956 graphical method of Akers, is applied to improve the solution. The new heuristic is tested on a set of 205 standard instances taken from the job-shop scheduling literature and compared with results obtained by other approaches. The new algorithm improved the best-known solution values for 57 instances.

Abstract
Natural user interfaces are becoming widespread as a focus of research in human-computer interaction. Gestural interaction is an important part of this field, but generally done by mimicry. This raises concerns such as the necessity of creating abstractions for non-imitable commands and the difficulty of finding gestures that are meaningful for a worldwide audience. Cultural backgrounds impart different meanings to gestures. In this research , we explore the concept of allowing individuals to interact with computer systems using gesture from the individual’s own culture, focusing on a software engineering approach to support this idea. The aim is to leverage the rich semantics of non-mimicry cultural gestures to expand gestural interaction to support abstract commands for instructions that do not have a matching gestural imitation. This approach also holds the potential to support the learning of gestural commands, by linking them to the cultural background of each user. The proposed software engineering approach demonstrates the feasibility of planning applications with commands in mind, not specific gestures, separating concerns between gestural identification (which can include cultural background elements) and actual commands.

Abstract
Linear Meld is a concurrent forward-chaining linear logic programming language where logical facts can be asserted and retracted in a structured way. In Linear Meld, a program is seen as a database of logical facts and a set of derivation rules. The database of facts is partitioned by the nodes of a graph structure which leads to parallelism when nodes are executed simultaneously. Due to the foundations on linear logic, rules can retract facts in a declarative and structured fashion, leading to more expressive programs. We present the design and implementation of the virtual machine that we implemented to run Linear Meld on multicores, with particular focus on thread management, code organization, fact indexing, rule execution, and database organization for efficient fact insertion, lookup and deletion. Our results show that the virtual machine is capable of scaling programs with up to 16 threads and also exhibits interesting scalar performance results due to our indexing optimizations.

Abstract