Abstract
The Network-on-Chip (NoC) architecture is an interconnect network with a good performance and scalability potential. Thus, it comes as no surprise that NoCs are among the most popular interconnect mediums in nowadays available many-core platforms. Over the years, the real-time community has been attempting to make NoCs amenable to the real-time analysis. One such approach advocates to employ virtual channels. Virtual channels are hardware resources that can be used as an infrastructure to facilitate flit-level preemptions between communication traffic flows. This gives the possibility to implement priority-preemptive arbitration policies in routers, which is a promising step towards deriving real-time guarantees for NoC traffic. So far, various aspects of priority-preemptive NoCs were studied, such as arbitration, priority assignment, routing, and workload mapping. Due to a potentially large solution space, the majority of available techniques are heuristic-centric, that is, either pure heuristics, or heuristic-based search strategies are used. Such approaches may lead to an inefficient use of hardware resources, and may cause a resource over-provisioning as well as unnecessarily high design-cost expenses. Motivated by this reality, we take a different approach, and propose an integer linear program to solve the problems of priority assignment and routing of NoC traffic. The proposed method finds optimal routes and priorities, but also allows to reduce the search space (and the computation time) by fixing either priorities or routes, and derive optimal values for remaining parameters. This framework is used to experimentally evaluate both the scalability of the proposed method, as well as the efficiency of existing priority assignment and routing techniques.

Abstract
To ensure software quality, we can use static and dynamic analysis techniques. Both have advantages and disadvantages and should be used together to improve their performance. In this paper, we present a strategy for applying a set of mutation operators for software testing, which represents a dynamic technique, based on the difficulty an automated static analyzer has on detecting their modeled faults. In other words, we investigated which sets of faults, represented by mutation operators, an automated static analyzer was able to recognize and prioritize the mutation testing considering only the set of mutation operators whose set of faults are difficult to be detected by such static analyzer. We compare our set of mutation operators with others, and the statical analysis shows no difference in the mutation score and costs regarding the number of generated and equivalent mutants among the different strategies. Nevertheless, we consider our proposal attractive once it uses operators with lower overlapping with faults detected by the automated static analyzer we have used.

Abstract
The aim of this work was to investigate the potential of Fourier transform infrared spectroscopy (FTIR) to detect and predict the bacterial load of salmon fillets (Salmo salar) stored at 3, 8 and 30 degrees C under three packaging conditions: air packaging (AP) and two modified atmospheres constituted by a mixture of 50%N-2/40%CO2/10%O-2 with lemon juice (MAPL) and without lemon juice (MAP). Fresh salmon samples were periodically examined for total viable counts (TVC), specific spoilage organisms (SSO) counts, pH, FTIR and sensory assessment of freshness. Principal components analysis (PCA) allowed identification of the wavenumbers potentially correlated with the spoilage process. Linear discriminant analysis (LDA) of infrared spectral data was performed to support sensory data and to accurately identify samples freshness. The effect of the packaging atmospheres was assessed by microbial enumeration and LDA was used to determine sample packaging from the measured infrared spectra. It was verified that modified atmospheres can decrease significantly the bacterial load of fresh salmon. Lemon juice combined with MAP showed a more pronounced delay in the growth of Brochothrix thermosphacta, Photobacterium phosphoreum, psychrotrophs and H2S producers. Partial least squares regression (PLS-R) allowed estimates of TVC and psychrotrophs, lactic acid bacteria, molds and yeasts, Brochothrix thermosphacta, Enterobacteriaceae, Pseudomonas spp. and H2S producer counts from the infrared spectral data: For TVC, the root mean square error of prediction (RMSEP) value was 0.78 log cfu g(-1) for an external set of samples. According to the results, FTIR can be used as a reliable, accurate and fast method for real time freshness evaluation of salmon fillets stored under different temperatures and packaging atmospheres.

Abstract

Abstract
One of the most common ways of collecting ocean data is to deploy sensors from the surface, allowing to understand the variation of water properties with depth. Autonomous vertical profilers are robotic vehicles that replace human operators in this task. They form a particular class of autonomous underwater vehicles that move predominantly along the vertical axis, typically with reduced control on the horizontal axis. This paper describes a propeller driven autonomous underwater profiler, optimized for shallow waters. The vehicle has no fins or other control surfaces, and uses four independent thrusters to provide both vertical and horizontal motion, including hovering in the water column. The paper describes the main subsystems, including the hardware implementation, the software structure, and the motion controllers, with experimental data from the first trials. © 2017 Marine Technology Society.

Abstract
Entropy and compression have been used to distinguish fetuses at risk of hypoxia from their healthy counterparts through the analysis of Fetal Heart Rate (FHR). Low correlation that was observed between these two approaches suggests that they capture different complexity features. This study aims at characterizing the complexity of FHR features captured by entropy and compression, using as reference international guidelines. Single and multi-scale approaches were considered in the computation of entropy and compression. The following physiologic-based features were considered: FHR baseline; percentage of abnormal long (% abLTV) and short (% abSTV) term variability; average short term variability; and, number of acceleration and decelerations. All of the features were computed on a set of 68 intrapartum FHR tracings, divided as normal, mildly, and moderately-severely acidemic born fetuses. The correlation between entropy/compression features and the physiologic-based features was assessed. There were correlations between compressions and accelerations and decelerations, but neither accelerations nor decelerations were significantly correlated with entropies. The % abSTV was significantly correlated with entropies (ranging between 0.54 and 0.62), and to a higher extent with compression (ranging between 0.80 and 0.94). Distinction between groups was clearer in the lower scales using entropy and in the higher scales using compression. Entropy and compression are complementary complexity measures.