Abstract
In this work we propose a method for maximization of the efficiency of an underwater wireless power transfer system that has to cope with load changes, quality factor and coupling coefficient deviations. By means of 3D electromagnetic simulation and numerical computation, parameter analysis is accomplished using different compensation methods, namely series-series, series-parallel and parallel-parallel. Moreover, a linear load profile is assessed as a proof of concept applicable to more complex load behaviours. For this linear load variation a maximum measured average efficiency of 82% was obtained throughout the entire battery state of charge. Electronics and full system considerations are also presented. Finally, a good agreement between theoretical predictions of the proposed method, simulation assessment and measurement results was verified.

Abstract
The radiation characteristics of a dipole antenna when immersed in both fresh and seawater are assessed through simulation and experimental work. Simulations show that the antenna's bandwidth and radiation pattern change with the properties of the medium where it is placed, namely the conductivity of the medium. Two dipoles antennas with current baluns were built and tested experimentally in freshwater. The tests included the measurement of the insertion loss between two identical dipole antennas and their radiation pattern. The results obtained show a good agreement between the simulation and experimental results.

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
This paper focuses on the design of high quality spiral resonators for maximising wireless power transfer efficiency between an AUV and an underwater docking station. By using 3D electromagnetic simulations and numerical analysis, the relevant parameters for quality factor computation are extracted. The impact of different variables on a spiral resonator's quality factor is assessed, allowing to conclude on the optimum design parameters to achieve optimum efficiency on the power transmission through magnetic coupling. This work will contribute to enable the development future AUV wireless charging systems, which will allow for an improvement of AUV's range and endurance while ensuring lower operational costs. © 2016 IEEE.

Abstract
The use of high efficiency resonant coupling wireless power systems for subsea operations is here considered for the charging of autonomous underwater vehicles. In this paper, two architectures based on two different inductors are analysed for their potential as resonant wireless power couplers. Both systems were designed and optimised through electromagnetic 3D simulations, upon which two prototypes were constructed and measured. Efficiencies as high as 75% for distances up to 5 cm were achieved on experimental testing.

Abstract
Context recognition is an indispensable functionality of context-aware applications that deals with automatic determination and inference of contextual information from a set of observations captured by sensors. It enables developing applications that can respond and adapt to user's situations. Thus much attention has been paid to developing innovative context recognition capabilities into context-aware systems. However, some existing studies rely on wearable sensors for context recognition and this practice has limited the incorporation of contexts into practical applications. Additionally, contexts are usually provided as low-level data, which are not suitable for more advanced mobile applications. This article explores and evaluates the use of smartphone's built-in sensors and classification algorithms for context recognition. To realize this goal, labeled sensor data were collected as training and test datasets from volunteers' smartphones while performing daily activities. Time series features were then extracted from the collected data, summarizing user's contexts with 50% overlapping slide windows. Context recognition is achieved by inducing a set of classifiers with the extracted features. Using cross validation, experimental results show that instance-based learners and decision trees are best suitable for smart phone -based context recognition, achieving over 90% recognition accuracy. Nevertheless, using leave one -subject-out validation, the performance drops to 79%. The results also show that smartphone's orientation and rotation data can be used to recognize user contexts. Furthermore, using data from multiple sensors, our results indicate improvement in context recognition performance between 1.5% and 5%. To demonstrate its applicability, the context recognition system has been incorporated into a mobile application to support context-aware personalized media recommendations.