Abstract
Unmanned Aerial Vehicles (UAVs) are a key ingredient in the industry and in warehouse logistics digital transformation process, providing the ability to perform automatic cyclic counting and real-time inventory, localize hard-to-find items and reach narrow storage areas. The use of UAVs poses new challenges, such as indoor autonomous localization and navigation, collision avoidance and automated UAV fleet management. This paper addresses the development of a vision-based Graph-SLAM approach for UAV indoor localization without predefined warehouse markers positions. A framework is proposed and developed to support different commercial UAV platforms, allowing the estimation in real-time of the UAV position and attitude. Indoor experimental tests were carried out in order to evaluate the performance of the developed method, comparing the results obtained with an approach based on the pre-mapped markers position indoor localization method.

Abstract
Researchers have to ensure that their projects comply with Research Data Management (RDM) requirements. Consequently, the main funding agencies require Data Management Plans (DMPs) for grant applications. So, institutions are investing in RDM tools and implementing RDM workflows in order to support their researchers. In this context, we propose a collaborative DMP-building method that involves researchers, data stewards and other parties if required. This method was applied as part of an RDM workflow in research groups across several scientific domains. We describe it as a systematic approach and illustrate it through a set of case studies. We also address the DMP monitoring process during the life cycle of projects. The feedback from the researchers highlighted the advantages of creating DMPs and their growing need. So, there is motivation to improve the DMP support process according to the machine-actionable DMPs concept and to the best practices in each scientific community.

Abstract
Significant developments on semiconductor technology have captured the electronic industry and paved the way for dominating household appliances market. Typical loads in this market generally have nonlinear voltage current characteristics. Therefore, highly-integrated power-electronic based electrical equipment in the demand side has caused harmonic pollution, which is one of the most important power quality problems in distribution system operation. To address this issue, there have been significantly great attempts to keep total harmonic distortion (THD) and total demand distortion (TDD) levels within International standard limits defined by IEEE 519 and IEC 61000. On the other hand, load shifting has recently drawn special attention of power grid planners to improve system performance substantially in the smart grid paradigm. In this study, the real harmonic measurements of residential appliances (both linear and nonlinear) are carried out in the Smart Home Laboratory in Yildiz Technical University, Istanbul, Turkey. Different load profiles are then created with a high accuracy based on the measured voltage and current, active, reactive and apparent power. Also, three case studies are considered to investigate the impacts of load shifting strategies on power quality requirements in terms of satisfying the relevant standards. As a result, it is shown that the TDD value decreases below nearly 8% limitation by mitigating the harmonic distortion and the TDD index, which indicates the harmonic distortion effect on the system regarding the desired standard limits of IEEE.

Abstract
As life expectancy grows and the population requirements for satisfactory health and wellness levels increases, there is a clear opportunity for the incorporation of alternative techniques and tools for promoting health and preventing disease. One of these tools, is the use of thermal water-based treatments, commonly known as thermalism, as tools to trigger patients’ overall wellness. Despite the collective assumption of the effects of thermalism, there is little to no scientific evidence of these treatments, thus impairing the potential of this activity to become more widespread in society. Thus, with this paper, we present a conceptual model for a non-invasive sensing system based on wearables that can monitor a set of patients’ biomarkers which will serve as the basis for the validation of the effects of thermalism. This system will also serve as a management and operation control tool for thermal SPA managers and technical directors.

Abstract
This paper presents a methodology for the optimization of bilateral point-to-point power transactions between prosumers/electricity consumers, taking into account the physical constraints of the power grid, aiming to minimize the total cost of electricity expenditures. As a resolution strategy, the optimization problem is divided into two stages. The first consists of a purely energy problem, in which prosumers/consumers establish energy exchanges in an efficient manner, in order to obtain an adequate balance between demand and total system generation. The second stage is physical, in which the grid constraints are modeled, such as maximum line loading and bus voltage level. A 14-bar system with 19 peers (agents) that also considers the possibility of switching with an external grid, which can be another set of peers, another energy community, or simply the grid under the responsibility of the local utility, is modeled for the evaluation of the proposed methodology. The proposed method proved to be effective because it achieved results where the operation of the electric grid is feasible.

Abstract
Robotics competitions are environments that foster teamwork, AI, and technology development by encouraging students, researchers, and academics to test their solutions against each other. These competitions often challenge the competitors' prototypes with tasks specifically designed to benchmark them with the current optimal solutions. During the prototype stages of a robot, the development costs and time spent are often higher than other stages, as changes in the prototype are frequent. Simulation is often used to reduce these variables as it allows flexibility in all development stages before transitioning to the real scenario. However, a digital twin can be used to increase even further flexibility and effectiveness. Digital twins are virtual representations of real assets, providing replication and prediction of real scenario events, and real-time monitoring of the real object. Thus, this paper presents the development of a digital twin of an automatic guided vehicle (AGV) to the Robot@Factory Lite competition and the tests performed to validate the approach.