Abstract
In this paper we describe the participation of InfoLab in the patient-centred information retrieval task of the CLEF eHealth 2016 lab. We analyse the performance of several query expansion strategies using difierent sources of terms and difierent methods to select the terms to be added to the original query. One of the strategies uses pseudo relevance feedback for term selection. The other strategies use external sources such as Wikipedia articles and definitions from the UMLS Metathesaurus for term selection. In the end, readability metrics such as SMOG, FOG and Flesch-Kincaid were used to re-rank the documents retrieved using the expanded queries. As the relevance and readability assessments are not available we can't make any conclusion regarding the results of our approaches.

Abstract
Many fields of engineering, science and finance use models that are developed and validated in high-level languages such as MATLAB. However, when moving to environments with resource constraints or portability challenges, these models often have to be rewritten in lower-level languages such as C. Doing so manually is costly and error-prone, but automated approaches tend to generate code that can be substantially less efficient than the handwritten equivalents. Additionally, it is usually difficult to read and improve code generated by these tools. In this paper, we describe how we improved our MATLAB-to-C compiler, based on the MATISSE framework, to be able to compete with handwritten C code. We describe our new IR and the most important optimizations that we use in order to obtain acceptable performance. We also analyze multiple C code versions to identify where the generated code is slower than the handwritten code and identify a few key improvements to generate code capable of outperforming handwritten C. We evaluate the new version of our compiler using a set of benchmarks, including the Disparity benchmark, from the San Diego Vision Benchmark Suite, on a desktop computer and on an embedded device. The achieved results clearly show the efficiency of the current version of the compiler. Copyright is held by the owner/author(s). Publication rights licensed to ACM.

Abstract
In a growing number of domains, such as health-care and transportation, several independent systems, forming a heterogeneous and distributed system of systems, are involved in the provisioning of end-to-end services to users. Testing such systems, running over interconnected mobile and cloud-based platforms, is particularly important and challenging, with little support being provided by current tools. In order to assess the current state of the practice regarding the testing of distributed and heterogeneous systems (DHS) and identify opportunities and priorities for research and innovation initiatives, we conducted an exploratory survey that was responded by 147 software testing professionals that attended industry-oriented software testing conferences, and present the main results in this paper. The survey allowed us to assess the relevance of DHS in software testing practice, the most important features to be tested in DHS, the current status of test automation and tool sourcing for testing DHS, and the most desired features in test automation solutions for DHS. We expect that the results presented in the paper are of interest to researchers, tool vendors and service providers in this field.

Abstract
This paper discusses about a proposed solution to the obstacle avoidance problem in multi-robot systems when applied to active target tracking. It is explained how a nonlinear model predictive formation control (NMPFC) previously proposed solves this problem of fixed and moving obstacle avoidance. First, an approach is presented which uses potential functions as terms of the NMPFC. These terms penalize the proximity with mates and obstacles. A strategy to avoid singularity problems with the potential functions using a modified A* path planning algorithm was then introduced. Results with simulations and experiments with real robots are presented and discussed demonstrating the efficiency of the proposed approach.

Abstract

Abstract
There are several sources of error affecting the accuracy of underwater ranging using acoustic signals. These errors have a direct impact in the performance of Long Baseline (LBL) navigation system. This paper presents the results of experiments designed to characterize the most significant sources of errors in acoustic ranging. For the experiments, we use a set of acoustic devices and compare distances given by GPS differences with and acoustic ranges. We describe the experimental procedure and we process the results to provide a qualitative and quantitative analysis of the errors.