Abstract
The paper presents a Cloud-based architecture for Ubiquitous and Cloud Manufacturing as a multilayer communicational architecture designated as the Communicational Architecture. It is characterised as (a) rich client interfaces (Rich Internet Application) with sufficient interaction to allow user agility and competence, (b) multimodal, for multiple client device classes support and (c) communicational to allow pragmatics, where human-to-human real interaction is completely supported. The main innovative part of this architecture is sustained by a semiotic framework organised on three main logical levels: (a) device level, which allows the user `to use' pragmatics with the system, (b) application level which results for a set of tools which allows users pragmatics-based interaction and (c) application server level that implements the Pragmatics renderer,a pragmatics supporting engine that supports all pragmatics services. The Pragmatics renderer works as a communication enabler, and consists of a set of integrated collaboration technology that makes the bridge between the user/devices and the `system'. A federated or community cloud is developed using a particular cloud REST ful Application Programming Interface that supports (cloud) services registration, composition and governance (pragmatics services behaves as SaaS in the cloud).

Abstract
Information is a crucial asset to successful internationalization, as it allows to reduce risks and uncertainty and to facilitate international expansion. Information about foreign markets and activities can be obtained by companies from internal or external sources, and in formal or informal ways. Industrial business associations (IBAs) are one of the external information sources. Due to their resource constraints, small and medium enterprises (SMEs) tend to highly depend on the services and information of IBAs to expand their business overseas. However, to improve their role in supporting SME internationalization, one important development is for IBAs to evolve towards more collaborative networks, by sharing more organized and valued information with their associates, but also by fostering information flows and more collaborations between them. This paper contributes to this view by synthetizing current data and information sources to support SME internationalization, based on a literature review, on interviews with Portuguese IBAs, and on expert opinion. An innovative aspect is to present a first instantiation of a socio-semantic model, opening paths for further developments in this area, and contributing to the community of Collaborative Networks. © IFIP International Federation for Information Processing 2017.

Abstract
We build on a long-standing tradition in astronomical adaptive optics (AO) of specifying performance metrics and error budgets using linear systems modeling in the spatial-frequency domain. Our goal is to provide a comprehensive tool for the calculation of error budgets in terms of residual temporally filtered phase power spectral densities and variances. In addition, the fast simulation of AO-corrected point spread functions (PSFs) provided by this method can be used as inputs for simulations of science observations with next-generation instruments and telescopes, in particular to predict post-coronagraphic contrast improvements for planet finder systems. We extend the previous results presented in Correia and Teixeira [J. Opt. Soc. Am. A 31, 2763 (2014)] to the closed-loop case with predictive controllers and generalize the analytical modeling of Rigaut et al. [Proc. SPIE 3353, 1038 (1998)], Flicker [Technical Report (W. M. Keck Observatory, 2007)], and Jolissaint [J. Eur. Opt. Soc. 5, 10055 (2010)]. We follow closely the developments of Ellerbroek [J. Opt. Soc. Am. A 22, 310 (2005)] and propose the synthesis of a distributed Kalman filter to mitigate both aniso-servo-lag and aliasing errors while minimizing the overall residual variance. We discuss applications to (i) analytic AO-corrected PSF modeling in the spatial-frequency domain, (ii) post-coronagraphic contrast enhancement, (iii) filter optimization for real-time wavefront reconstruction, and (iv) PSF reconstruction from system telemetry. Under perfect knowledge of wind velocities, we show that ~60 nm rms error reduction can be achieved with the distributed Kalman filter embodying antialiasing reconstructors on 10 m class high-order AO systems, leading to contrast improvement factors of up to three orders of magnitude at few ?/D separations (~1 - 5?/D) for a 0 magnitude star and reaching close to one order of magnitude for a 12 magnitude star.

Abstract
Urban metabolism accounts of total annual energy, water, and other resource flows are increasingly available for a variety of world cities. For local decision makers, however, it may be important to understand the variations of resource consumption within the city. Given the difficulty of gathering suburban resource consumption data for many cities, this article investigates the potential of statistical downscaling methods to estimate local resource consumption using socioeconomic or other data sources. We evaluate six classes of downscaling methods: ratio-based normalization; linear regression (both internally and externally calibrated); linear regression with spatial autocorrelation; multilevel linear regression; and a basic Bayesian analysis. The methods were applied to domestic energy consumption in London, UK, and our results show that it is possible to downscale aggregate resource consumption to smaller geographies with an average absolute prediction error of around 20%; however, performance varies widely by method, geography size, and fuel type. We also show how mapping these results can quickly identify districts with noteworthy resource consumption profiles. Further work should explore the design of local data collection strategies to enhance these methods and apply the techniques to other urban resources such as water or waste.

Abstract
Sidescan sonars have seen wide deployment in underwater imaging. They can be used to image the seabed to a rather acceptable resolution from a few centimeters to 10 centimeters. Yet, sonar images are still of a substantially lower visual quality as they suffer from quite a few problems, e.g., acoustic shadows that vary according to vehicle heading and sonar grazing angle, speckle noise, geometric deformation due to ping variation and speed of vehicle carrying the sonar, etc. Landmark detection in sidescan sonar images is vital to find objects and locations of interest that are useful in various underwater operations. The objective of this work is proposing novel landmark detection methods for this class of images. Cubic smoothing spline fitted to the across-track signals is proposed as a method to detect the objects and their shadows. To cover a large area, experimental data has been acquired during missions performed in Melenara Bay (Las Palmas/Spain) using autonomous underwater vehicles (AUVs) equipped with Klein 3500 sidescan sonar. The AUVs have been deployed in two missions (one mission performed each day) and a total of 25 large-resolution images have been acquired. The AUV generated 12 parallel path images in the first mission and 13 parallel path images in the second mission with an angle of 70 degrees between the direction of mission #1 and mission #2. This difference in the directions of the two missions was necessary to ensure different acoustic shadows between the two sets of images, each set being generated from a different mission. Results show that the proposed methods are powerful in detecting landmarks from these challenging images.

Abstract
Demands for underwater communication systems are increasing due to the ongoing expansion of human activities in underwater environments such as environmental monitoring, underwater exploration, offshore oil field exploration and monitoring, port security, and tactical surveillance. As such, there is a serious requirement to improve the performance of underwater communication systems in order to effectively use the equipment and the resources. The high cost, lack of flexibility, and operational disadvantages of wireline (particularly optical fiber) systems to provide real-time communication in underwater applications become restrictive for many cases. This triggers the growing demand for underwater wireless links. Acoustic communications suffer from a very small available bandwidth, very low celerity, and large latencies due to the low propagation speed. Underwater wireless optical communications (UWOC) which are able to achieve data rates of hundreds of Mbps (even up to Gbps) for short ranges, typically several tens of meters, appear as an attractive alternative or complementary solution to long-range acoustic communications. In fact, water is relatively transparent to light in the visible band of the spectrum and absorption takes its minimum value in the blue-green spectral range (450 nm-550 nm) [1,2]. Thanks to the ability of providing unprecedentedly high-rate data transmission, the UWOC technology enables the establishment of high-speed and reliable links for underwater missions employing robotics or autonomous underwater vehicles (AUVs), for instance. In addition, it is highly energy efficient, compared to the traditional technique of acoustic communication, and also has much less impact on marine animal life (see Figure 11.1) [3,4]. In particular, it is harmless to the cetaceans and coral. © 2017 by Taylor & Francis Group, LLC.