Bridging logic and kernel machines

We propose a general framework to incorporate first-order logic (FOL) clauses, that are thought of as an abstract and partial representation of the environment, into kernel machines that learn within a semi-supervised scheme. We rely on a multi-task learning scheme where each task is associated with a unary predicate defined on the feature space, while higher level abstract representations consist of FOL clauses made of those predicates. We re-use the kernel machine mathematical apparatus to solve the problem as primal optimization of a function composed of the loss on the supervised examples, the regularization term, and a penalty term deriving from forcing real-valued constraints deriving from the predicates. Unlike for classic kernel machines, however, depending on the logic clauses, the overall function to be optimized is not convex anymore. An important contribution is to show that while tackling the optimization by classic numerical schemes is likely to be hopeless, a stage-based learning scheme, in which we start learning the supervised examples until convergence is reached, and then continue by forcing the logic clauses is a viable direction to attack the problem. Some promising experimental results are given on artificial learning tasks and on the automatic tagging of bibtex entries to emphasize the comparison with plain kernel machines.     

Learning extended FSA from software: An empirical assessment

A number of techniques that infer finite state automata from execution traces have been used to support test and analysis activities. Some of these techniques can produce automata that integrate information about the data-flow, that is, they also represent how data values affect the operations executed by programs.The integration of information about operation sequences and data values into a unique model is indeed conceptually useful to accurately represent the behavior of a program. However, it is still unclear whether handling heterogeneous types of information, such as operation sequences and data values, necessarily produces higher quality models or not.In this paper, we present an empirical comparative study between techniques that infer simple automata and techniques that infer automata extended with information about data-flow. We investigate the effectiveness of these techniques when applied to traces with different levels of sparseness, produced by different software systems. To the best of our knowledge this is the first work that quantifies both the effect of adding data-flow information within automata and the effectiveness of the techniques when varying sparseness of traces.     

To lock, or not to lock: That is the question

Mechanisms to control concurrent access over project artefacts are needed to execute the software development process in an organized way. These mechanisms are implemented by concurrency control policies in version control systems that may inhibit (i.e. ‘to lock’) or allow (i.e., ‘not to lock’) parallel development. This work presents a novel approach named Orion that analyzes the project's historical changes and suggests the most appropriate concurrency control policy for each software element. This suggestion aims at minimizing conflict situations and thus improving the productivity of the development team. In addition, it identifies critical elements that do not work well with any of these policies and are candidates to refactoring. We evaluated Orion through two experimental studies and the results, which indicated it was effective, led us to a prototype implementation. Apart from the Orion approach this paper also presents the planning, execution, and analysis stages of the evaluation, and details of prototype internals.     

Fracture toughness characterization of materials under multiaxial loading

The novel concept of generalized fracture toughness characterization of brittle materials subjected to multiaxial loadings is presented. The theory emphasizes the fracture process as the result of the opening action of the crack surfaces. The generalized fracture toughness values describing the failure events due to combined loading systems lie on a Fracture Envelope characteristic for a given material. The Cartesian equation of the Envelope in the K ₁ K ₂plane is specified by the conventional fracture toughness K _1cand Poisson's ratio . A Griffith-type fracture criterion permits the prediction of crack propagation onset and crack growth direction.

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Résumé L'article présente le nouveau concept de la force de rupture généralisée qui caractérise les matériaux fragiles sujets à sollicitations multiaxiales. La théorie met en évidence que le phénomène de rupture est le résultat de l'action de déplacement symétrique des surfaces de la fissure. Le lieu des valeurs de la force de rupture généralisée qui décrivent les événements de rupture dûs à conditions de sollicitations combinées est l'Enveloppe de Rupture caracteristique pour un matériel particulier. L'équation Cartésienne de l'Enveloppe dans le plan K ₁ K ₂est specifiée par la force de rupture conventionelle K _1cet par le rapport de Poisson . Un critère de rupture du type Griffith permet la determination de l'amorçage et la direction d'accroissement de la fissure.

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Operated for United States Department of Energy, Contract DE-AC-12-65SN00052.     

Modeling of gold microbeams as strain and pressure sensors for characterizing MEMS packages

This work presents the modeling of gold microbeams for characterizing Micro-electro-mechanical systems (MEMS) packages in terms of both strains induced to the MEMS devices and hermetic sealing capability. The proposed test structures are based on arrays of rectangular-shaped clamped-free and clamped–clamped beams, to be realized with a film of electroplated gold by surface micromachining technology. The resonant frequency of the microbeams is modeled by FEM simulations as a function of substrate deformations, which could be induced by the package. Clamped–clamped bridges show a linear change of the square of the resonant frequency in case of in-plane deformations, in fairly good agreement with an approximate analytical model. Cantilever beams are modeled as variable capacitors to detect out-of-plane deformations. Finally, an analytical model to study cantilever beams as resonators for detecting pressure changes is discussed and compared with preliminary experimental results, showing an impact on the quality factor in a range from 10^?2 mbar to 1?bar.     

Gene regulatory networks reconstruction from time series datasets using genetic programming: a comparison between tree-based and graph-based approaches

Genetic programming researchers have shown a growing interest in the study of gene regulatory networks in the last few years. Our team has also contributed to the field, by defining two systems for the automatic reverse engineering of gene regulatory networks called GRNGen and GeNet. In this paper, we revise this work by describing in detail the two approaches and empirically comparing them. The results we report, and in particular the fact that GeNet can be used on large networks while GRNGen cannot, encourage us to pursue the study of GeNet in the future. We conclude the paper by discussing the main research directions that we are planning to investigate to improve GeNet.     

Temporal contexts: Effective text classification in evolving document collections

The management of a huge and growing amount of information available nowadays makes Automatic Document Classification (ADC), besides crucial, a very challenging task. Furthermore, the dynamics inherent to classification problems, mainly on the Web, make this task even more challenging. Despite this fact, the actual impact of such temporal evolution on ADC is still poorly understood in the literature. In this context, this work concerns to evaluate, characterize and exploit the temporal evolution to improve ADC techniques. As first contribution we highlight the proposal of a pragmatical methodology for evaluating the temporal evolution in ADC domains. Through this methodology, we can identify measurable factors associated to ADC models degradation over time. Going a step further, based on such analyzes, we propose effective and efficient strategies to make current techniques more robust to natural shifts over time. We present a strategy, named temporal context selection, for selecting portions of the training set that minimize those factors. Our second contribution consists of proposing a general algorithm, called Chronos, for determining such contexts. By instantiating Chronos, we are able to reduce uncertainty and improve the overall classification accuracy. Empirical evaluations of heuristic instantiations of the algorithm, named WindowsChronos and FilterChronos, on two real document collections demonstrate the usefulness of our proposal. Comparing them against state-of-the-art ADC algorithms shows that selecting temporal contexts allows improvements on the classification accuracy up to 10%. Finally, we highlight the applicability and the generality of our proposal in practice, pointing out this study as a promising research direction.     

Construction of baselines for VoIP traffic management on open MANs

In the last century, owing to the constant evolution of technologies telecommunication networks have become increasingly robust, being able to support multiple services. These services are part of the heterogeneous network traffic that can be carried through the Internet. Many of these services, including VoIP, are latency sensitive. In other words, this means that their quality depends directly on the network quality of service. Since users tend to become more sensitive with the instability and unavailability of the network, it is important to improve traffic management. A particular type of data that could be used to improve VoIP traffic management is the Internet Protocol Detail Record (IPDR). IPDRs are tickets created by all VoIP call attempts which contain a group of information related to the call history. Because of its full range of information, IPDRs can be used to create VoIP traffic baselines. This paper presents the development of baselines based on IPDRs to support VoIP traffic management in open‐access Metropolitan Area Networks (MAN). Copyright © 2013 John Wiley & Sons, Ltd.     

Building a bridge between performance management,radical innovation,and innovation networks: A systematic literature review

Research on performance management (PM) of networks and radical innovation has largely developed along two isolated paths. On the one hand, a growing body of knowledge addresses the use of performance management systems in the context of networks (notably for production and incremental innovation). On the other hand, radical innovation scholars have shown how innovation initiatives that are more uncertain demand the use of new approaches (e.g., new project management routines or different evaluative tools for portfolios). Some scholars even suggest that traditional PM may suppress radical innovation. Our study takes a different approach. It aims to bridge radical innovation and network performance management through a systematic review of the literature. Here, we adopt a hybrid approach that combines bibliometrics with content analysis. Whereas the literature often separates the issues of network performance management and radical innovation, our contribution expands the theory of network management and radical innovation by developing a conceptual framework based on these concepts, thus combining them. We also offer suggestions for further research on this approach. Our framework suggests that overall, the performance management of radical innovation networks presents different features (e.g., recursive rather than linear) and constructs (e.g., openness and unintended performance) from those of innovation network management.