Symmetry reductions for model checking of concurrent dynamic software

Symmetry reduction techniques exploit symmetries that occur during the execution of a system in order to minimize its state space for efficient verification of temporal logic properties. This paper presents a framework for concisely defining and evaluating symmetry reductions currently used in software model checking, involving heap objects and processes. An on-the-fly state space exploration algorithm combining both techniques will also be presented. Second, the relation between symmetry and partial-order reductions is investigated, showing how ones strengths can be used to compensate for the others weaknesses. The symmetry reductions presented here were implemented in the dSPIN model-checking tool. We also performed a number of experiments that show significant progress in reducing the cost of finite-state software verification.     

Extracting Multilingual Lexicons from Parallel Corpora

The paper describes our recent developments in automatic extraction of translation equivalents from parallel corpora. We describe three increasingly complex algorithms: a simple baseline iterative method, and two non-iterative more elaborated versions. While the baseline algorithm is mainly described for illustrative purposes, the non-iterative algorithms outline the use of different working hypotheses which may be motivated by different kinds of applications and to some extent by the languages concerned. The first two algorithms rely on cross-lingual POS preservation, while with the third one POS invariance is not an extraction condition. The evaluation of the algorithms was conducted on three different corpora and several pairs of languages.     

Using a Computer Driven PID Regulator for Controlling the Vacuum Pump of a Mechanical Milking Machine

Conventional vacuum control in a milking system is accomplished by using a vacuum pump, sized for the maximum air flows into the milking system, running at a full speed. The difference between the pump capacity and the necessary flow of air is compensated by allowing air to enter the system through a regulator. The solution presented in this paper uses a VFD （variable frequency driver） in order to drive the vacuum pump at a controlled speed, so that the air removed equals the air entering the milking system. The VFD technology is able to adjust the rate of air removal from the milking system, by changing the speed of the vacuum pump motor. The VFD is controlled by a computer using a virtual instrument in order to emulate a PID （proportion integration differentiation） regulator. The tests aimed to evaluate the vacuum regulator characteristics and vacuum stability. A statistical analysis of the experimental results was performed and it showed that there was a significant difference between the experimental results obtained for the two methods of vacuum regulation （with vacuum regulator and VFD controller respectively）. The experimental results proved that the used of the VFD controller led to a higher vacuum stability in terms of the error between the set vacuum value and the achieved values.     

Making Predictions of Global Warming Impacts Using a Semantic Web Tool that Simulates Fuzzy Cognitive Maps

Computational Economics - One of the most important environmental problems of our era is Global Warming (GW), which derives its roots mainly from anthropogenic activities and is expected to cause...     

Faster synchronization in P systems

In the field of molecular computing, in particular P systems, synchronization is an important requirement for composing or sequentially linking together congenial P system activities. We provide a deterministic algorithm to the Firing Squad Synchronization Problem, for digraph-based P systems, which runs in 3e + 11 steps, where e is the eccentricity of the general. Our algorithm uses a convenient framework, called simple P modules, which embraces the essential features of several popular types of P systems.     

Result diversification in social image retrieval: a benchmarking framework

This article addresses the diversification of image retrieval results in the context of image retrieval from social media. It proposes a benchmarking framework together with an annotated dataset and discusses the results achieved during the related task run in the MediaEval 2013 benchmark. 38 multimedia diversification systems, varying from graph-based representations, re-ranking, optimization approaches, data clustering to hybrid approaches that included a human in the loop, and their results are described and analyzed in this text. A comparison of the use of expert vs. crowdsourcing annotations shows that crowdsourcing results have a slightly lower inter-rater agreement but results are comparable at a much lower cost than expert annotators. Multimodal approaches have best results in terms of cluster recall. Manual approaches can lead to high precision but often lower diversity. With this detailed results analysis we give future insights into diversity in image retrieval and also for preparing new evaluation campaigns in related areas.     

An empirical study on green practices of mobile phone users

Given the market’s saturation with smartphones and the increased power needs that these have as compared with older feature phones, the users’ green practices and behavior is emerging as an important research topic. The environmental aspects and general awareness issues are not addressed in this study; however, the limited battery life of smartphones is a decisive factor that shapes the users’ behavior, practices and preferences. As such, the users need to follow green practices and carefully assess the energy related characteristics (speed, screen size, weight, and price) that they value the most in a smartphone, to maximize their experience. Based on our previous work that gathered relevant data from 313 users, we extended the analysis in order to examine the user battery life and charging practices, buying habits, green practices and preferences. To that end, we used quantitative statistics and Fuzzy Decision Tree analysis to propose relevant Fuzzy Decision Rules that can classify the results and profile the users.     

Synthesis and characterisation of nanostructured silica-powellite-HAP composites

Well-defined calcium molybdate (CaMoO₄) and hydroxyapatite (HAP) nanocrystals were developed by thermal treatment on the surface of a SiO₂–CaO–P₂O₅–MoO₃ amorphous precursor synthesised at room-temperature by sol–gel route. The structural and morphological characterisaions were performed by several techniques: energy dispersive X-ray spectroscopy, thermal analyses (DTA/TGA), X-ray diffraction (XRD), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy, electron paramagnetic resonance. Complementary, Fourier transform infrared and Raman spectroscopies provided a clear picture regarding the short range order structure, emphasising beside the CaMoO₄ phase development, the presence of HAP nanocrystals. The vibrational spectroscopic techniques proved to be valuable tools for evidencing very small HAP nanocrystallites that cannot be clearly observed by XRD and TEM analyses.     

Spectroscopic behavior of some a(3)b type tetrapyrrolic complexes in several organic solvents and micellar media

The paper presents spectral studies of some unsymmetrical A(3)B tetrapyrrolic, porphyrin-type complexes with Cu(II) and Zn(II) in different solvents and micellar media aimed at estimating their properties in connection with the living cell. The results indicate that the position of the absorption and emission peaks is mostly influenced by the central metal ion and less by the environmental polarity or the peripheric substituents of the porphyrinic core. The comparison between the overall absorption and emission spectra of the compounds in methanol or cyclohexane vs. direct and reverse Triton X micellar systems, respectively, suggests for all compounds the localization at the interface between the polyethylene oxide chains and the tert-octyl-phenyl etheric residue of the Triton X-100 molecules. These findings could be important when testing the compounds embedded in liposomes or other delivery systems to the targeted cell.     

Context-adaptive pre-processing scheme for robust speech recognition in fast-varying noise environment

Based on the observation that dissimilar speech enhancement algorithms perform differently for different types of interference and noise conditions, we propose a context-adaptive speech pre-processing scheme, which performs adaptive selection of the most advantageous speech enhancement algorithm for each condition. The selection process is based on an unsupervised clustering of the acoustic feature space and a subsequent mapping function that identifies the most appropriate speech enhancement channel for each audio input, corresponding to unknown environmental conditions. Experiments performed on the MoveOn motorcycle speech and noise database validate the practical value of the proposed scheme for speech enhancement and demonstrate a significant improvement in terms of speech recognition accuracy, when compared to the one of the best performing individual speech enhancement algorithm. This is expressed as accuracy gain of 3.3% in terms of word recognition rate. The advance offered in the present work reaches beyond the specifics of the present application, and can be beneficial to spoken interfaces operating in fast-varying noise environments.