Ensembles of decision trees based on imprecise probabilities and uncertainty measures

In this paper, we present an experimental comparison among different strategies for combining decision trees built by means of imprecise probabilities and uncertainty measures. It has been proven that the combination or fusion of the information obtained from several classifiers can improve the final process of the classification. We use previously developed schemes, known as Bagging and Boosting, along with a new one based on the variation of the root node via the information rank of each feature of the class variable. To this end, we applied two different approaches to deal with missing data and continuous variables. We use a set of tests on the performance of the methods analyzed here, to show that, with the appropriate approach, the Boosting scheme constitutes an excellent way to combine this type of decision tree. It should be noted that it provides good results, even compared with a standard Random Forest classifier, a successful procedure very commonly used in the literature.     

Variable Structure Control with chattering elimination and guaranteed stability for a generalized T-S model

In this paper, a fuzzy based Variable Structure Control (VSC) with guaranteed stability is presented. The main objective is to obtain an improved performance of highly non-linear unstable systems. The main contribution of this work is that, firstly, new functions for chattering reduction and error convergence without sacrificing invariant properties are proposed, which is considered the main drawback of the VSC control. Secondly, the global stability of the controlled system is guaranteed.The well known weighting parameters approach, is used in this paper to optimize local and global approximation and modeling capability of T-S fuzzy model.A one link robot is chosen as a nonlinear unstable system to evaluate the robustness, effectiveness and remarkable performance of optimization approach and the high accuracy obtained in approximating nonlinear systems in comparison with the original T-S model. Simulation results indicate the potential and generality of the algorithm. The application of the proposed FLC-VSC shows that both alleviation of chattering and robust performance are achieved with the proposed FLC-VSC controller. The effectiveness of the proposed controller is proven infront of disturbances and noise effects.     

A document is known by the company it keeps: neighborhood consensus for short text categorization

During the last decades the Web has become the greatest repository of digital information. In order to organize all this information, several text categorization methods have been developed, achieving accurate results in most cases and in very different domains. Due to the recent usage of Internet as communication media, short texts such as news, tweets, blogs, and product reviews are more common every day. In this context, there are two main challenges; on the one hand, the length of these documents is short, and therefore, the word frequencies are not informative enough, making text categorization even more difficult than usual. On the other hand, topics are changing constantly at a fast rate, causing the lack of adequate amounts of training data. In order to deal with these two problems we consider a text classification method that is supported on the idea that similar documents may belong to the same category. Mainly, we propose a neighborhood consensus classification method that classifies documents by considering their own information as well as information about the category assigned to other similar documents from the same target collection. In particular, the short texts we used in our evaluation are news titles with an average of 8 words. Experimental results are encouraging; they indicate that leveraging information from similar documents helped to improve classification accuracy and that the proposed method is especially useful when labeled training resources are limited.     

Coreference resolution: an empirical study based on SemEval-2010 shared Task 1

This paper presents an empirical evaluation of coreference resolution that covers several interrelated dimensions. The main goal is to complete the comparative analysis from the SemEval-2010 task on Coreference Resolution in Multiple Languages. To do so, the study restricts the number of languages and systems involved, but extends and deepens the analysis of the system outputs, including a more qualitative discussion. The paper compares three automatic coreference resolution systems for three languages (English, Catalan and Spanish) in four evaluation settings, and using four evaluation measures. Given that our main goal is not to provide a comparison between resolution algorithms, these are merely used as tools to shed light on the different conditions under which coreference resolution is evaluated. Although the dimensions are strongly interdependent, making it very difficult to extract general principles, the study reveals a series of interesting issues in relation to coreference resolution: the portability of systems across languages, the influence of the type and quality of input annotations, and the behavior of the scoring measures.     

Privacy-enhanced architecture for smart metering

The recent deployment of smart grids promises to bring numerous advantages in terms of energy consumption reduction in both homes and businesses. A more transparent and instantaneous measurement of electricity consumption through smart meters utilization leads to an enhancement in the ability of monitoring, controlling and predicting energy usage. Nevertheless, it also has associated drawbacks related to the privacy of customers, since such management might reveal their personal habits, which electrical appliances they are using at each moment, whether they are at home or not, etc. In this work, we present a privacy-enhanced architecture for smart metering aimed at tackling this threat by means of encrypting individual measurements while allowing the electricity supplier to access the aggregation of the corresponding decrypted values.     

Advance human–machine interface automatic evaluation

The need for accessibility evaluation tools is motivated by several endogenous and exogenous reasons coming from the end user (the designer and the developer) and companies releasing information systems. Existing evaluation tools mainly concentrate on examining the code of Web pages: Web pages more and more frequently contain non-HTML parts that entirely escape from being treated by existing techniques. This is the case of the advanced human–machine interface (AHMI), a piece of software programmed in C/C++, used for controlling the advanced flight management system in the aircraft cockpit. Studying this new user interface (UI) requires a structured approach to evaluate and validate AHMI designs. The goal in this work is to develop an evaluation tool to automate the process of evaluating the AHMI. The method addresses: support of multiple bases of guidelines (accessibility or usability or both) on-demand (partial or total evaluation), with different levels of details (a presentation for developers and for those responsible for certifying accessibility). The method goes a step toward the automatic evaluation of UI containing non-HTML parts.     

Evaluation of messaging middleware for high-performance cloud computing

Cloud computing is posing several challenges, such as security, fault tolerance, access interface singularity, and network constraints, both in terms of latency and bandwidth. In this scenario, the performance of communications depends both on the network fabric and its efficient support in virtualized environments, which ultimately determines the overall system performance. To solve the current network constraints in cloud services, their providers are deploying high-speed networks, such as 10 Gigabit Ethernet. This paper presents an evaluation of high-performance computing message-passing middleware on a cloud computing infrastructure, Amazon EC2 cluster compute instances, equipped with 10 Gigabit Ethernet. The analysis of the experimental results, confronted with a similar testbed, has shown the significant impact that virtualized environments still have on communication performance, which demands more efficient communication middleware support to get over the current cloud network limitations.     

Downstream environmental effects of dam operations: Changes in habitat quality for native fish species

Hydropeaking dam operation and water extractions for irrigation have been broadly stated as alterations to natural flow regimes, which have also been noticed in the Biobío Watershed, in Central Chile, since 1996. In the Biobío River, most of native fish species are endemic and very little is known about them. Their ecological and social values have never been estimated, and there is lack of information about their habitat preferences. Furthermore, changes on fish habitat availability due to natural and/or man‐made causes have not been evaluated. In this study, eight native fish species, in a representative reach of the Biobío River, were studied and their preferred habitats were surveyed and characterized. A hydrodynamic model was built and linked to the fish habitat simulation model CASiMiR. Fuzzy rules and fuzzy sets were developed for describing habitat preference of the native fish species. CASiMiR was then used to simulate how physical habitat conditions vary due to flow control (i.e. upstream dams). Results show how overall habitat quality, expressed as weighted usable area (WUA) and hydraulic habitat suitability (HHS), changes and fluctuates due to the dam operation and how the daily hydropeaking is influencing quantity, quality and location of different habitats. The study suggests that the analysed fish are highly susceptible to flow control, as dams are currently operated, and fish habitat improvement suggestions are proposed. Copyright © 2010 John Wiley & Sons, Ltd.