Process optimization in the self-reacting friction stir welding of aluminum 6061-T6

Self-reacting friction stir welding (SR-FSW), also called bobbin-tool friction stir welding (BT-FSW), is a solid state welding process similar to friction stir welding (FSW) except that the tool has two opposing shoulders instead of the shoulder and a backing plate found in FSW. The tool configuration results in greater heat input and a symmetrical weld macrostructure. A significant amount of information has been published in the literature concerning traditional FSW while little has been published about SR-FSW. An optimization experiment was performed using a factorial design to evaluate the effect of process parameters on the weld temperature, surface and internal quality, and mechanical properties of self-reacting friction stir welded aluminum alloy 6061-T6 butt joints. The parameters evaluated were tool rotational speed, traverse speed, and tool plunge force. A correlation between weld temperature, defect formation (specifically galling and void formation), and mechanical properties was found. Optimum parameters were determined for the welding of 8-mm-thick 6061-T6 plate.     

Optimization of biochemical systems through mathematical programming: Methods and applications

In this work we present a general (mono and multiobjective) optimization framework for the technological improvement of biochemical systems. The starting point of the method is a mathematical model in ordinary differential equations (ODEs) of the investigated system, based on qualitative biological knowledge and quantitative experimental data. In the method we take advantage of the special structural features of a family of ODEs called power-law models to reduce the computational complexity of the optimization program. In this way, the genetic manipulation of a biochemical system to meet a certain biotechnological goal can be expressed as an optimization program with some desired properties such as linearity or convexity.The general method of optimization is presented and discussed in its linear and geometric programming versions. We furthermore illustrate the use of the method by several real case studies. We conclude that the technological improvement of microorganisms can be afforded using the combination of mathematical modelling and optimization. The systematic nature of this approach facilitates the redesign of biochemical systems and makes this a predictive exercise rather than a trial-and-error procedure.     

Sensor data integration for indoor human tracking

A human tracking system based on the integration of the measurements from an inertial motion capture system and a UWB (Ultra-Wide Band) location system has been developed. On the one hand, the rotational measurements from the inertial system are used to track precisely all limbs of the body of the human. On the other hand, the translational measurements from both systems are combined by three different fusion algorithms (a Kalman filter, a particle filter and a combination of both) in order to obtain a precise global localization of the human in the environment. Several experiments have been performed to compare their accuracy and computational efficiency.     

Light-weight salient foreground detection for embedded smart cameras

An embedded smart camera is a stand-alone unit that not only captures images, but also includes a processor, memory and communication interface. Battery-powered, embedded smart cameras introduce many additional challenges since they have very limited resources, such as energy, processing power and memory. Computer vision algorithms running on these camera boards should be light-weight and efficient. Considering the memory requirements of an algorithm and its portability to an embedded processor should be an integral part of the algorithm design in addition to the accuracy requirements. This paper presents a light-weight and efficient background modeling and foreground detection algorithm that is highly robust against lighting variations and non-static backgrounds including scenes with swaying trees, water fountains and rain. Compared to many traditional methods, the memory requirement for the data saved for each pixel is very small in the proposed algorithm. Moreover, the number of memory accesses and instructions are adaptive, and are decreased depending on the amount of activity in the scene. Each pixel is treated differently based on its history, and instead of requiring the same number of memory accesses and instructions for every pixel, we require less instructions for stable background pixels. The plot of the number of unstable pixels at each frame also serves as a tool to find the video portions with high activity. The proposed method selectively updates the background model with an automatically adaptive rate, thus can adapt to rapid changes. As opposed to traditional methods, pixels are not always treated individually, and information about neighbors is incorporated into decision making. The results obtained with nine challenging outdoor and indoor sequences are presented, and compared with the results of different state-of-the-art background subtraction methods. The ROC curves and memory comparison of different background subtraction methods are also provided. The experimental results demonstrate the success of the proposed light-weight salient foreground detection method.     

Line planning on tree networks with applications to the Quito Trolebús system

We discuss an optimization model for the line planning problem in public transport in order to minimize operation costs while guaranteeing a certain level of quality of service, in terms of available transport capacity. We analyze the computational complexity of this problem for tree network topologies as well as several categories of line operations that are important for the Quito Trolebús system. In practice, these instances can be solved quite well, and significant optimization potentials can be demonstrated.     

Shape-sensitive MLS deformation

This work presents methods for deforming meshes in a shape-sensitive way using Moving Least Squares (MLS) optimization. It extends an approach for deforming space (Cuno et al. in Proceedings of the 27th Computer Graphics International Conference, pp. 115–122, 2007) by showing how custom distance metrics may be used to achieve deformations which preserve the overall mesh shape. Several variant formulations are discussed and demonstrated, including the use of geodesic distances, distances constrained to paths contained in the mesh, the use of skeletons, and a reformulation of the MLS scheme which makes it possible to affect the bending behavior of the deformation. Finally, aspects of the implementation of these techniques in parallel architectures such as GPUs (graphics processing units) are described and compared with CPU-only implementations.     

Real-time collaboration of virtual laboratories through the Internet

Web-based learning environments are becoming increasingly popular in higher education. One of the most important web-learning resources is the virtual laboratory (VL), which gives students an easy way for training and learning through the Internet. Moreover, on-line collaborative communication represents a practical method to transmit the knowledge and experience from the teacher to students overcoming physical distance and isolation. Considering these facts, the authors of this document have developed a new dynamic collaborative e-learning system which combines the main advantages of virtual laboratories and collaborative learning practices. In this system, the virtual laboratories are based on Java applets which have embedded simulations developed in Easy Java Simulations (EJS), an open-source tool for teachers who do not need complex programming skills. The collaborative e-learning is based on a real-time synchronized communication among these Java applets. Therefore, this original approach provides a new tool which integrates virtual laboratories inside a synchronous collaborative e-learning framework. This paper describes the main features of this system and its successful application in a distance education environment among different universities from Spain.     

Arity and alternation: a proper hierarchy in higher order logics

We study the effect of simultaneously bounding the maximal-arity of the higher-order variables and the alternation of quantifiers in higher-order logics, as to their expressive power on finite structures (or relational databases). Let $\mathit{AA}^i(r,m)$ be the class of (i?+?1)-th order logic formulae where all quantifiers are grouped together at the beginning of the formulae, forming m alternating blocks of consecutive existential and universal quantifiers, and such that the maximal-arity (a generalization of the concept of arity, not just the maximal of the arities of the quantified variables) of the higher-order variables is bounded by r. Note that, the order of the quantifiers in the prefix may be mixed. We show that, for every i?≥?1, the resulting $\mathit{AA}^i(r,m)$ hierarchy of formulae of (i?+?1)-th order logic is proper. This extends a result by Makowsky and Pnueli who proved that the same hierarchy in second-order logic is proper. In both cases the strategy used to prove the results consists in considering formulae which, represented as finite structures, satisfy themselves. As the well known diagonalization argument applies here, this gives rise, for each order i and each level of the $\mathit{AA}^i(r,m)$ hierarchy of arity and alternation, to a class of formulae which is not definable in that level, but which is definable in a higher level of the same hierarchy. We then use a similar argument to prove that the classes of $\Sigma^i_m \cup \Pi^i_m$ formulae in which the higher-order variables of all orders up to i?+?1 have maximal-arity at most r, also induce a proper hierarchy in each higher-order logic of order i?≥?3. It is not known whether the correspondent hierarchy in second-order logic is proper. Using the concept of finite model truth definitions introduced by M. Mostowski, we give a sufficient condition for that to be the case.     

From a Conceptual Framework for Agents and Objects to a Multi-Agent System Modeling Language

In this paper we propose a multi-agent system modeling language (MAS-ML) that extends UML (Unified Modeling Language) based on structural and dynamic properties presented in a conceptual framework (metamodel) called Taming Agents and Objects (TAO). Our focus is the adaptation according to TAO concepts of the static Class diagram and the interaction Sequence diagram proposed by UML. These two diagrams have been chosen because they are the most commonly used and because it is possible to use them to illustrate both the structural and dynamic aspects of TAO metamodel. We propose a conservative extension of the UML metamodel, which includes agent-related notions that are part of the TAO conceptual framework while preserving all object-related concepts, which constitute the UML metamodel. The main difference between our approach and the others presented in the literature is the clear definition and representation of the elements that compose MASs and their corresponding behavior. In order to extend UML with TAO non-object concepts, it is not possible to use only the three basic extensions mechanisms provided by UML and new metaclasses and stereotypes have been created and associated with the UML metamodel.