Evaluation of the salt leaching method for the production of ethylene propylene diene monomer rubber foams

The thermomechanical behavior of ethylene propylene diene monomer (EPDM) foams produced with the salt leaching method has been investigated and compared with the behavior of EPDM foams obtained from conventional blowing agents. Moreover, the salt-leaching process has been optimized to minimize salt residues and the influence of different parameters (such as average particle size and particle size distribution) has been investigated. Scanning electron microscopy and density measurements highlighted that salt-leaching leads to the formation of open-cell porosity with cell dimensions of around 60 to 80 μm, while foams obtained with the two traditional foaming agents lead to closed-cell porosity. Compression set values indicate that the behavior of the foams produced with salt leaching are more similar to the unfoamed rubber, characterized by higher elasticity and low residual deformation. Two theoretical models were successfully applied to the compression curves (Mooney-Rivlin and Exponential-Logarithmic) and they highlighted the effect of foaming on the properties of EPDM rubber and in particular the higher chain extensibility obtained through the salt leaching foaming method.     

Output feedback of Markov jump linear systems with no mode observation: An automotive throttle application

The note presents an output feedback control strategy for Markov jump linear systems with no mode observation. Based on minimizing a finite‐time quadratic cost, we derive an algorithm that generates output feedback gains that satisfy a necessary optimality condition. These gains can be computed off‐line relying only on the initial condition of the system. This result expands a previous one from the literature that considered state‐feedback only. To illustrate the usefulness of the approach, real‐time laboratory experiments were performed to control an automotive electronic throttle valve subject to Markov‐driven voltage fluctuations. Copyright © 2015 John Wiley & Sons, Ltd.     

Comparing and experimenting machine learning techniques for code smell detection

Several code smell detection tools have been developed providing different results, because smells can be subjectively interpreted, and hence detected, in different ways. In this paper, we perform the largest experiment of applying machine learning algorithms to code smells to the best of our knowledge. We experiment 16 different machine-learning algorithms on four code smells (Data Class, Large Class, Feature Envy, Long Method) and 74 software systems, with 1986 manually validated code smell samples. We found that all algorithms achieved high performances in the cross-validation data set, yet the highest performances were obtained by J48 and Random Forest, while the worst performance were achieved by support vector machines. However, the lower prevalence of code smells, i.e., imbalanced data, in the entire data set caused varying performances that need to be addressed in the future studies. We conclude that the application of machine learning to the detection of these code smells can provide high accuracy (>96 %), and only a hundred training examples are needed to reach at least 95 % accuracy.     

Some results on disturbance attenuation for Hamiltonian systems via direct discrete‐time design

The disturbance attenuation and robust disturbance attenuation problems for Hamiltonian systems in the discrete‐time setting are considered and some new results are presented. The new results are derived utilizing the recently presented dissipativity equality obtained by adding the dissipation rate function to the classical dissipativity inequality. A selection of the dissipation rate function yields new results. These results include a condition on the dissipation structure of the system to achieve the desired disturbance attenuation level and gives direct construction of optimal control laws for any desired disturbance attenuation level. The results remove the need to solve Hamilton–Jacobi–Isaacs inequalities. Copyright © 2014 John Wiley & Sons, Ltd.     

An autonomic approach for P2P/cloud collaborative environments

The rise of Cloud Computing has progressively dimmed the interest in volunteer and peer-to-peer computing, in general. However, efficient and cost-effective large scale distributed collaborative environments cannot be achieved leveraging upon the Cloud alone. In this paper, we propose a novel hybrid P2P/cloud approach where components and protocols are autonomically configured according to specific target goals, such as cost-effectiveness, reliability and availability. The proposed approach is based on the Networked Autonomic Machine (NAM) framework, which allows distributed system designers to include different kinds of cost and performance constraints. As an example, we show how the NAM-based approach can be used to design collaborative storage systems, enabling the definition of an autonomic policy to decide, according to cost minimization and data availability goals, how to part data chunks among peer nodes and Cloud, based on the local perception of the P2P network.     

Workflows for Heliophysics

In this paper we describe how we have introduced workflows into the working practices of a community for whom the concept of workflows is very new, namely the heliophysics community. Heliophysics is a branch of astrophysics which studies the Sun and the interactions between the Sun and the planets, by tracking solar events as they travel throughout the Solar system. Heliophysics produces two major challenges for workflow technology. Firstly it is a systems science where research is currently developed by many different communities who need reliable data models and metadata to be able to work together. Thus it has major challenges in the semantics of workflows. Secondly, the problem of time is critical in heliophysics; the workflows must take account of the propagation of events outwards from the sun. They have to address the four dimensional nature of space and time in terms of the indexing of data. We discuss how we have built an environment for Heliophysics workflows building on and extending the Taverna workflow system and utilising the myExperiment site for sharing workflows. We also describe how we have integrated the workflows into the existing practices of the communities involved in Heliophysics by developing a web portal which can hide the technical details from the users, who can concentrate on the data from their scientific point of view rather than on the methods used to integrate and process the data. This work has been developed in the EU Framework 7 project HELIO, and is being disseminated to the worldwide Heliophysics community, since Heliophysics requires integration of effort on a global scale.     

oDect: an RFID‐based object detection API to support applications development on mobile devices

The RFID technology is becoming ever more popular in the development of ubiquitous computing applications. A full exploitation of the RFID potential requires the study and implementation of human–computer interaction (HCI) modalities to be able to support wide usability by the target audience. This implies the need for programming methodologies specifically dedicated to support the easy and efficient prototyping of applications to have feedback from early tests with users. On the basis of our field‐working experience, we have designed oDect, a high‐level language and platform‐independent application programming interface (API), ad hoc designed to meet the needs of typical applications for mobile devices (smart phones and PDAs). oDect aims at allowing application developers to create their prototypes focusing on the needs of the final users, without having to care about the low‐level software that interacts with the RFID hardware. Further, in an end‐user developing (EUD) approach, oDect provides specific support for the application end‐user herself to cope with typical problems of RFID applications in detecting objects. We describe in detail the features of the API and discuss the findings of a test with four programmers, where we analyse and evaluate the use of the API in four sample applications. We also present results of an end‐user test, which investigated strengths and weaknesses of the territorial agenda (TA) concept. The TA is an RFID‐based citizen guide that aids—through time‐ and location‐based reminders—users in their daily activities in a city. The TA directly exploits EUD features of oDect, in particular concerning the possibility of linking detected objects with custom actions. Copyright © 2008 John Wiley & Sons, Ltd.     

VirtuE: a formal model of virtual enterprises for information markets

A vital part of a modern economy is an information market. In this market, information products are being traded in countless ways. Information is bought, modified, integrated, incorporated into other products, and then sold again. Often, the manufacturing of an information product requires the collaboration of several participants. A virtual enterprise is a community of business entities that collaborate on the manufacturing of complex products. This collaboration is often ad hoc, for a specific product only, after which the virtual enterprise may dismantle. The virtual enterprise paradigm is particularly appealing for modeling collaborations for manufacturing information products, and in this paper we present a new model, called VirtuE, for modeling such activities. VirtuE has three principal components. First, it defines a distributed infrastructure with concepts such as members, products, inventories, and production plans. Second, it defines transactions among members, to enable collaborative production of complex products. Finally, it provides means for the instrumentation of enterprises, to measure their performance and to govern their behavior.