Abstract
In this poster, we are addressing the topic of "system's evaluation" from the point of view of assessing the usability of a gamified experience with 20 teenagers aged 15-17 years. The currently tested experience was ideally designed for children 9-10 years. In order to adapt the application to teenagers, we tested it with 20 targeted users. In this poster, we share the results and encourage a discussion among the researchers about how to adapt the gamified experience designed for children to a teenage audience.

Abstract
Charging performance of Plug-in Hybrid Electric Vehicles (PHEVs) under various charging approaches brings new challenges for the distribution grid, such as feeder overloading and increment of loss. In this paper, the impact of charging PHEVs on the load profile is evaluated considering Demand Response (DR) programs in order to minimize the impact of charging PHEVs on load profile. In the proposed DR strategy, all consumers can determine and control their loads. Also, the proposed DR strategy can satisfy the function of reducing peak with regard to different PHEV penetration, while preserving consumer comfort levels. For performing DR programs, time of use and real time pricing models are used to evaluate the impacts of charging of PHEVs on distribution system operations. A 33-node test feeder has been studied to assess different penetration schemes of PHEVs including 11.3%, 35% and 45% PHEV penetration in residential loads. Moreover, uncertainties associated with PHEV charging performances are handled with Monte Carlo simulation. Results validate that the amount of peak loss, and Peak to Average Ratio (PAR) increase owing to PHEVs penetration growth. Also, the results illustrate that scheduling for the operation of PHEVs with DR program reduces the distribution losses and PAR.

Abstract
The multirotor UAVs are being integrated into a wide range of application scenarios due to maneuverability in 3D, versatility and reasonable payload of sensors. One of the application scenarios is the inspection of structures where the human intervention is difficult or unsafe and the UAV can provide an improvement of the collected data. At the same time introduce challenges due to low altitude missions and also the fact of being manually operated without line of sight. In order to overcome these issues, this paper presents a LiDAR-based realtime collision avoidance algorithm, denoted by Escape Elliptical Search Point with the ability to be integrated into autonomous and manned modes of operation. The algorithm was validated in a simulation environment developed in Gazebo and also in a mixed environment composed by a real robot in an outdoor scenario and simulated obstacle and LiDAR.

Abstract
The integration of renewable energy sources (RESs) cannot be postponed given the several techno-economic and environmental factors. However, the intermittent nature of RESs brings several challenges because such sources introduce significant operational variability and uncertainty in the system. Framed in this context a new stochastic mathematical planning model is proposed considering the placement and sizing of energy storage systems and reactive power sources that altogether enable high penetration of RESs. The model employs a linearized AC model, balancing well accuracy with computational burden. The model is tested on a standard distribution network system. Numerical results show that the simultaneous integration of energy storage systems and reactive power sources largely leads to a substantially increased penetration of RESs in distribution systems. Furthermore, dramatic reductions in losses, system costs and emissions are observed. Results analysis also reveal the positive contribution of such a planning on the overall voltage stability in the system.

Abstract
Burden reduction is a key issue in modern public administrations' and businesses' agendas. Compliance with mandatory regulations can have a direct impact on a country's economic performance, growth, and development. Research in this area, contributes to a better understanding of the implications and context of administrative burden, and increases the efficiency of the strategies adopted to reduce it. The goal of this study is to undertake a review of the current state of the art on Administrative Burden Reduction (ABR), in order to gain a deeper insight about the subject, identify current gaps, and better plan for future research. A total of 122 papers were identified as relevant, out of a pool of 742 papers retrieved from the current literature. The relevant papers were analyzed across four dimensions: methodology, type and focus, and targeted stakeholders. Three key gaps were identified and discussed in relation to: citizen orientated services and burden reduction; empirical research and post-initiative re-evaluation; and, the role of stakeholders, interest groups and end-users in driving ABR. Lastly a conceptual framework model and next steps are proposed.

Abstract
The container loading problem (CLP) is a real-world driven, combinatorial optimisation problem that addresses the maximisation of space usage in cargo transport units. The research conducted on this problem failed to fulfill the real needs of the transportation industry, owing to the inadequate representation of practical-relevant constraints. The dynamic stability of cargo is one of the most important practical constraints. It has been addressed in the literature in an over-simplified way which does not translate to real-world stability. This paper proposes a physics simulation tool based on a physics engine, which can be used to translate real-world stability into the CLP. To validate the tool, a set of benchmark tests is proposed and the results obtained with the physics simulation tool are compared to the state-of-the-art simulation engineering software Abaqus Unified FEA. Analytical calculations have been also conducted, and it was also possible to conclude that the tool proposed is a valid alternative.