Abstract
Exploring the seas and the oceans is essential for industrial and environmental applications. Given the fact that the seas cover 72% of the surface of the Earth and are home to 90% of all life found on it, underwater imaging has become an active research area in recent years. Due to the high absorption of electromagnetic waves by water, sonar is currently the exemplary choice used in underwater imaging. Yet, underwater images acquired with sonars suffer from various degradations, since the sound signal is affected by the environment and the sonar parameters and geometry. This work proposes an enhancement method that aims at getting close to natural underwater images. The enhanced images can be used in further applications related to seabed mapping and underwater computer vision. The enhancement aims at reducing the echo-decay and some effects of the receiver gain.

Abstract
The work described in this paper is part of the development of a framework to support the joint execution of cooperative missions by a group of vehicles, in a simulated, augmented, or real environment. Such a framework brings forward the need for formal languages in which to specify the vehicles that compose a team, the scenario in which they will operate, and the mission to be performed. This paper introduces the Scenario Description Language (SDL) and the Team Description Language (TDL), two Extensible Markup Language based dialects that compose the static components necessary for representing scenario and mission knowledge. SDL provides a specification of physical scenario and global operational constraints, while TDL defines the team of vehicles, as well as team-specific operational restrictions. The dialects were defined using Extensible Markup Language schemas, with all required information being integrated in the definitions. An interface was developed and incorporated into the framework, allowing for the creation and edition of SDL and TDL files. Once the information is specified, it can be used in the framework, thus facilitating environment and team specification and deployment. A survey answered by practitioners and researchers shows that the satisfaction with SDL+TDL is elevated (the overall evaluation of SDL+TDL achieved a score of 4 out of 5, with 81%/78.6% of the answers 4); in addition, the usability of the interface was evaluated, achieving a score of 86.7 in the System Usability Scale survey. These results imply that SDL+TDL is flexible enough to represent scenarios and teams, through a user-friendly interface.

Abstract
This paper presents an integrated cognitive robotics system for industrial kitting operations in a modern factory setting. The robot system combines low-level robot control and execution monitoring with automated mission and task planning, and a logistics planner which communicates with the factory's manufacturing execution system. The system has been implemented and tested on a series of automotive kitting problems, where collections of parts are picked from a warehouse and delivered to the production line. The system has been empirically evaluated and the complete framework shown to be successful at assembling kits in a small factory environment.

Abstract
This paper presents a new technique for providing the analysis and comparison of wiretap codes in the small blocklength regime over the binary erasure wiretap channel. A major result is the development of Monte Carlo strategies for quantifying a code's equivocation, which mirrors techniques used to analyze forward error correcting codes. For this paper, we limit our analysis to coset-based wiretap codes, and give preferred strategies for calculating and/or estimating the equivocation in order of preference. We also make several comparisons of different code families. Our results indicate that there are security advantages to using algebraic codes for applications that require small to medium blocklengths. © 2017 IEEE.

Abstract
This paper aims to develop grasping and manipulation capability along with autonomous navigation and localization in a wheelchair-mounted robotic arm to serve patients. Since the human daily environment is dynamically varied, it is not possible to enable the robot to know all the objects that would be grasped. We present an approach to enable the robot to detect, grasp and manipulate unknown objects. We propose an approach to construct the local reference frame that can estimate the object pose for detecting the grasp pose of an object. The main objective of this paper is to present the grasping and manipulation approach along with a navigating and localization method that can be performed in the human daily environment. A grid map and a match algorithm is used to enable the wheelchair to localize itself using a low-power computer. The experimental results show that the robot can manipulate multiple objects and can localize itself with great accuracy.

Abstract
This study presents a new function-based modulation control technique for modular multilevel converters (MMCs). The main contribution of this study is the formulation of two new modulation functions for the required switching signals of the MMC's upper and lower sub-modules, respectively. The output and circulating current equations of the converter are employed to attain the arm's currents which are utilised for the proposed modulation functions, which have two important features: (i) it is much less complex compared to the existing control methods of MMC; and (ii) the proposed controller can be regulated properly to deal with parameter variations in a bid to ensure stable and accurate performance. In this controller, the MMC output current magnitude and phase angle required for special active and reactive power sharing can be easily applied to the modulation functions. Also, the equivalent capacitors of upper and lower sub-modules are discussed based on the proposed modulation functions. Finally, simulations are performed in Matlab/Simulink environment to evaluate the performance of the proposed control technique in both the dynamic conditions of load as well as varying parameters.