Abstract
This review is focused on microstructured optical fiber sensors developed in recent years for liquid RI sensing. The review is divided into three parts: the first section introduces a general view of the most relevant refractometric sensors that have been reported over the last thirty years. Section 2 discusses several microstructured optical fiber designs, namely, suspended-core fiber, photonic crystal fiber, large-core air-clad photonic crystal fiber, and others. This part is also divided into two main groups: the interferometric-based and resonance-based configurations. The sensing methods rely either on full/selective filling of the microstructured fiber air holes with a liquid analyte or by simply immersing the sensing fiber into the liquid analyte. The sensitivities and resolutions are tabled at the end of this section followed by a brief discussion of the obtained results. The last section concludes with some remarks about the microstructured fiber-based configurations developed for RI sensing and their potential for future applications. © 2014 by the authors.

Abstract
We characterize the secrecy level of communication under Uncoordinated Frequency Hopping, a spread spectrum scheme where a transmitter and a receiver randomly hop through a set of frequencies with the goal of deceiving an adversary. In our work, the goal of the legitimate parties is to land on a given frequency without the adversary eavesdroppers doing so, therefore being able to communicate securely in that period, that may be used for secret-key exchange. We also consider the effect on secrecy of the availability of friendly jammers that can be used to obstruct eavesdroppers by causing them interference. Our results show that tuning the number of frequencies and adding friendly jammers are effective countermeasures against eavesdroppers.

Abstract
Several concurrent applications running on a sensor network may cause a node to transmit packets at distinct periods, which increases the radio-switching rate and has significant impact in terms of the overall energy consumption. We propose to batch the transmissions together by defining a harmonizing period to align the transmissions from multiple applications at periodic boundaries. This harmonizing period is then leveraged to design a distributed protocol called Network-Harmonized Scheduling (NHS) that coordinates transmissions across nodes and provides real-time guarantees in a multi-hop network. Categories and Subject Descriptors-C. 3 [Computer Systems Organization]: Special-purpose and Application-Based Systems: Real-time and embedded systems

Abstract
This work draws upon the theoretical foundations of Special Education for People with Disability, Environmental Education and the Human Computer Interaction (HCI), from the Activity Theory perspective, to propose the MusicPaint software. Initially, the design considerations of MusicPaint are presented. Then, its pilot use by seven students with disability is described. From the qualitative and quantitative evidence of performance that was gathered, the key findings are presented and discussed. Despite the limited number of participants in the experimental validation scenarios, the findings reveal the potentiality of the MusicPaint to enhance the accessibility of students with disability to Environmental Education opportunities, contributing to the HCI-based enhancement of accessibility in the educational settings. © 2014 Springer International Publishing.

Abstract
In this paper we address the problem of musical genre recognition for a dancing robot with embedded microphones capable of distinguishing the genre of a musical piece while moving in a real-world scenario. For this purpose, we assess and compare two state-of-the-art musical genre recognition systems, based on Support Vector Machines and Markov Models, in the context of different real-world acoustic environments. In addition, we compare different preprocessing robot audition variants (single channel and separated signal from multiple channels) and test different acoustic models, learned a priori, to tackle multiple noise conditions of increasing complexity in the presence of noises of different natures (e.g., robot motion, speech). The results with six different musical genres suggest improved results, in the order of 43.6pp for the most complex conditions, when recurring to Sound Source Separation and acoustic models trained in similar conditions to the testing scenarios. A robot dance demonstration session confirms the applicability of the proposed integration for genre-adaptive dancing robots in real-world noisy environments.

Abstract