Abstract
This paper presents the work performed in the implementation of an underwater simulation environment for the development of an autonomous underwater vehicle for the exploration of flooded underground tunnels. In particular, the implementation of a laser based structured light system, multibeam sonar and other robot details were addressed. The simulation was used as a relevant tool in order to study and specify the robot multiple sensors characteristics and placement in order to adequately survey a realistic environment. A detailed description of the research and development work is presented along with the analysis of obtained results and the benefits this work brings to the project. © 2017 IEEE.

Abstract
Innovation is a widely studied field. It is extremely important for any organization wishing to achieve and maintain a competitive advantage in the market, even though assessing the impacts of innovation represents a challenge due to the difficulty of isolating and measuring it. Furthermore, healthcare institutions are facing an increasing need for innovation in order to become competitive and offer new treatments for patients. Surprisingly, little is known about the nature of innovativeness in healthcare organizations and its relationship with performance. The aim of this research is to analyze whether the several types of innovation influence the relevant measures of performance in healthcare institutions, researching empirically the innovativeness-performance relationship. The study is based on a quantitative analysis on 34 Portuguese hospitals, collecting detailed information about the innovation portfolio of each one. Factor analysis and hypothesis testing were applied. Moreover, the hospitals were classified by type of property and geographical region they belong to, and statistical comparative tests were performed to test the existence of statistical differences. It was found that organizational innovation is correlated with process innovation and service innovation. Furthermore, service and process innovations influence operational performance. However, we cannot conclude that innovation in healthcare units has an overall impact on their financial performance. The results of this study may help hospital administrators to make better decisions with regard to their innovation policy design.

Abstract
The feasibility of measuring arsenic and selenium contents in a single nail clipping was investigated using a small-focus portable X-ray fluorescence (XRF) instrument with monochromatic excitation beams. Nail clipping phantoms supplemented with arsenic and selenium to produce materials with 0, 5, 10, 15, and 20 mu g/g were used for calibration purposes. In total, 10 different clippings were analyzed at two different measurement positions. Energy spectra were fit with detection peaks for arsenic K-alpha, selenium K-alpha, arsenic K-beta, selenium K-beta, and bromine K-alpha characteristic X-rays. Data analysis was performed under two distinct conditions of fitting constraint. Calibration lines were established from the amplitude of each of the arsenic and selenium peaks as a function of the elemental contents in the clippings. The slopes of the four calibration lines were consistent between the two conditions of analysis. The calculated minimum detection limit (MDL) of the method, when considering the Ka peak only, ranged from 0.210 +/- 0.002 mu g/g selenium under one condition of analysis to 0.777 +/- 0.009 mu g/g selenium under another. Compared with previous portable XRF nail clipping studies, MDLs were substantially improved for both arsenic and selenium. The new measurement technique had the additional benefits of being short in duration (similar to 3 min) and requiring only a single nail clipping. The mass of the individual clipping used did not appear to play a major role in signal strength, but positioning of the clipping is important.

Abstract
Model-based methodologies, supported by automatic generation, have been proposed as a solution to reduce software development costs. In the case of interactive computing systems specific challenges arise. On the one hand, a high level of automation requires the use of detailed models, which is contrary to the iterative development process, based on the progressive refinement of user interface mockups, typical of user centered development processes. On the other hand, layered software architectures imply a distinction between the models used in the business logic and in the user interface, raising consistency problems between the models at each level. This article proposes a tool supported approach to user interface generation directly from the architectural models of the business logic. In many situations, user interfaces provide similar features inside a specific domain. The identification of the application domain is thus a key factor in supporting the automation of the generation process. © 2017 Association for Computing Machinery.

Abstract
In recent years, safer and more reliable biometric methods have been developed. Apart from the need for enhanced security, the media and entertainment sectors have also been applying biometrics in the emerging market of user-adaptable objects/systems to make these systems more user-friendly. However, the complexity of some state-of-the-art biometric systems (e.g., iris recognition) or their high false rejection rate (e.g., fingerprint recognition) is neither compatible with the simple hardware architecture required by reduced-size devices nor the new trend of implementing smart objects within the dynamic market of the Internet of Things (IoT). It was recently shown that an individual can be recognized by extracting features from their electrocardiogram (ECG). However, most current ECG-based biometric algorithms are computationally demanding and/or rely on relatively large (several seconds) ECG samples, which are incompatible with the aforementioned application fields. Here, we present a computationally low-cost method (patent pending), including simple mathematical operations, for identifying a person using only three ECG morphology-based characteristics from a single heartbeat. The algorithm was trained/tested using ECG signals of different duration from the Physionet database on more than 60 different training/test datasets. The proposed method achieved maximal averaged accuracy of 97.450% in distinguishing each subject from a ten-subject set and false acceptance and rejection rates (FAR and FRR) of 5.710 +/- 1.900% and 3.440 +/- 1.980%, respectively, placing Beat-ID in a very competitive position in terms of the FRR/FAR among state-of-the-art methods. Furthermore, the proposed method can identify a person using an average of 1.020 heartbeats. It therefore has FRR/FAR behavior similar to obtaining a fingerprint, yet it is simpler and requires less expensive hardware. This method targets low-computational/energy-cost scenarios, such as tiny wearable devices (e.g., a smart object that automatically adapts its configuration to the user). A hardware proof-of concept implementation is presented as an annex to this paper.

Abstract