Abstract
This paper presents an architecture that supports Quality of Service (QoS) in an Arrowhead-compliant System of Systems (SoS). The Arrowhead Framework supports local cloud functionalities for automation applications, provided by means of a Service Oriented Architecture (SOA), by offering a number of services that ease application development. On such applications the QoS guarantees are required for service fruition, and are themselves requested as services from the framework. To fulfil this objective we start by describing the Arrowhead architecture and the components needed to dynamically in run-time negotiate a system configuration that guarantees the QoS requirements between application services.

Abstract
The blooming of different cloud data management infrastructures has turned multistore systems to a major topic in the nowadays cloud landscape. In this demonstration, we present a Cloud Multidatastore Query Language (CloudMdsQL), and its query engine. CloudMdsQL is a functional SQL-like language, capable of querying multiple heterogeneous data stores (relational and NoSQL) within a single query that may contain embedded invocations to each data store's native query interface. The major innovation is that a CloudMdsQL query can exploit the full power of local data stores, by simply allowing some local data store native queries (e.g. a breadth-first search query against a graph database) to be called as functions, and at the same time be optimized. Within our demonstration, we focus on two use cases each involving four diverse data stores (graph, document, relational, and key-value) with its corresponding CloudMdsQL queries. The query execution flows are visualized by an embedded real-time monitoring subsystem. The users can also try out different ad-hoc queries, not necessarily in the context of the use cases.

Abstract
Online recommender systems often deal with continuous, potentially fast and unbounded ows of data. Ensemble methods for recommender systems have been used in the past in batch algorithms, however they have never been studied with incremental algorithms, that are capable of processing those data streams on the y. We propose online bagging, using an incremental matrix factorization algorithm for positiveonly data streams. Using prequential evaluation, we show that bagging is able to improve accuracy more than 20% over the baseline with small computational overhead.

Abstract
A great variety of human gesture recognition methods exist in the literature, yet there is still a lack of solutions to encompass some of the challenges imposed by real life scenarios. In this document, a gesture recognition for robotic search and rescue missions in the high seas is presented. Themethod aims to identify shipwrecked people by recognizing the hand waving gesture sign. We introduce a novelmotion descriptor, through which high recognition accuracy can be achieved even for low resolution images. The method can be simultaneously applied to rigid object characterization, hence object and gesture recognition can be performed simultaneously. The descriptor has a simple implementation and is invariant to scale and gesture speed. Tests, preformed on a maritime dataset of thermal images, proved the descriptor ability to reach a meaningful representation for very low resolution objects. Recognition rates with 96.3% of accuracy were achieved.

Abstract
The capability of relatively high-speed short-range communications of Autonomous Underwater Vehicles (AUVs) in underwater scenarios, for example, for communication between vehicles or when the AUV is approaching a docking station for downloading of data gathered during a survey mission, is becoming a relevant application in the context of sea exploration and mining. In this paper the analysis of the J-pole antenna and two of its configurations namely Super J-pole and Collinear J-pole antennas are presented, aimed at improving the propagation distance and data rates when such antennas are installed on AUV for onward usage in underwater communications. The performance of these three antennas is assessed through simulation in fresh and sea water, operating in the High Frequency (HF) band. These antennas are compared in terms of bandwidth and directivity which are important elements in the transmission and reception of electromagnetic signals. The results obtained show that these antennas will be desirable both for improved data rates and propagation distance in fresh and sea water. The antennas were designed with FEKO electromagnetic simulation software.

Abstract
Declarative programming has been hailed as a promising approach to parallel programming since it makes it easier to reason about programs while hiding the implementation details of parallelism from the programmer. However, its advantage is also its disadvantage as it leaves the programmer with no straightforward way to optimize programs for performance. In this paper, we introduce Coordinated Linear Meld (CLM), a concurrent forward-chaining linear logic programming language, with a declarative way to coordinate the execution of parallel programs allowing the programmer to specify arbitrary scheduling and data partitioning policies. Our approach allows the programmer to write graph-based declarative programs and then optionally to use coordination to fine-tune parallel performance. In this paper we specify the set of coordination facts, discuss their implementation in a parallel virtual machine, and show-through example-how they can be used to optimize parallel execution. We compare the performance of CLM programs against the original uncoordinated Linear Meld and several other frameworks.