Abstract
Line-following robots can recognize and follow a line drawn on a surface. Their operating principles have elements that could be used in the development of numerous autonomous technologies, with applications in education and industry. This class of robots usually represent the first contact students have with educational robotics, being used to develop students' logic thinking and programming skills. The cost of robotic platforms is still prohibitive in low-budget schools and universities, which makes almost impossible having a platform for each small group of students in a classroom, harming the learning process. This work proposes a 3D web-based open-source simulator for Pololu's 3Pi line-following robots, making such technology more accessible and available even for distance learning courses. The developed software simulates the robot's physical structure, behavior, and operations-as being able to read surfaces-, enabling the user to observe the robot following the line as the code commands. The simulator was validated based on experiments that included motion analysis and time measurements of pre-stablished tasks so that its execution could be more coherently based on what happens in reality.

Abstract
This paper proposes the linear frequency cepstral coefficients as highly discriminative features for anomaly detection in ball bearings using vibration sensor data. These features are based on cepstral analysis and are capable of encoding the patterns of a spectral magnitude profile. Incipient damages on bearings can grow rapidly under normal use resulting in vibration and harsh noise. If left undetected, this damage will worsen, leading to high maintenance costs or even injury. Multiple interferences in an industrial environment contaminate the signal, making it a challenge to correctly identify the bearings' condition. Many studies have attempted to overcome this issue at the signal level. However, the discriminative capacity of the current vibration signal features is still vulnerable to interference, which motivates this work. In order to demonstrate the benefits of these features, we (1) show that they are computationally efficient and suitable for real-time incremental training; (2) conduct discriminative analysis by evaluating the separability performance and comparing it with the state of the art; and (3) test the robustness of the proposed features under noise interference, which is ideal for use in the harsh operating conditions of industrial machinery. The data was obtained from a laboratory workbench setting that reproduces bearing fault scenarios. Results show that the proposed features are fast, competitive when compared to state-of-the-art features, and resilient to high levels of interference. Despite the higher performance when using the quadratic model, the proposed features remain highly discriminative when used with several other discriminant function.

Abstract
The objective of the present study was to investigate the influence of demineralization solution on the optical properties of chicken femoral samples. Biomaterials based on bone have gained importance in clinical applications due to their properties as better osseointegration and biocompatibility. Biomateriais (bone substitute) are essentials to auxiliary in treatment of diseases related to bones such as bone density disorder, low bone mineral mass and the deterioration of bone tissue. Our data shows that integrating sphere technique permits to determinate significant difference in optical properties between healthy and demineralized samples. In this work, the optical properties of bone samples from chicken femur have been measured over the wavelength range 700–1000 nm.

Abstract
We hear more and more about autonomous vehicles, however, where are we heading with automation? Recently, we have heard about some crashes of autonomous vehicles, which have occurred during trials. Therefore, can this technology be trusted? Equally important, what kind of moral and ethical questions are behind the decisions that a vehicle like this must make? Who should be saved if someone must die, in a car accident? The elderly, or perhaps younger people? Executives or the homeless? People who follow traffic rules, or is that not relevant? This article will start by reviewing some of the ethical questions that have already been raised and results found within the public domain. Then the article proceeds by discussing our survey, administered in Portugal, with 111 answers. For situations which would seemingly lead to an obvious consensus and to a 100% agreement on the matter, we found this to not be the case, as our survey never achieved such polarized results. For example, even when confronted with saving pet animals or children, there was still a split in the choice made (albeit pending heavily towards saving the children). This goes to show how people are different and make different choices in life. Are we superior to animals and do we have a greater right to life than pets? Of course, this is debatable, according to differing values and cultures. Therefore, it follows that much debate should ensue as to how to program autonomous vehicles to behave - in case the loss of life (in whatever form) is at stake. Automation, as such, is thus leading us down ambiguous avenues where grey areas abound and we may simply not know what is best all of the time. Automation is thus making us work harder at being human beings and is bringing us to new levels of rationality - where emotions should also play a big part. The spontaneity and intuitiveness of human decision-making being taken out of the equation (when an accident occurs without automated cars that is how we think) makes many pre-meditated decisions uncertain and unpopular. Profoundly humane issues, which are often culture specific, are thus yet to be discussed.

Abstract
In this paper, demand-side management (DSM) is performed through demand response aggregators (DRAs) in an uncertain environment within zonal price market framework. The proposed scheme aims to allow cross-border electricity trading and optimize interconnections usage as well as to obtain optimum DR volume from the perspective of the Market Coupling Operator (MCO). The market consists of several zonal price markets as Nominated Electricity Market Operators (NEMO) who run their day-ahead and balancing market internally and communicate the information to the MCO to provide the cooperation with other NEMOs. To this end, a stochastic two-stage model is formulated in which the total operation cost from MCO's viewpoint is minimized. Accordingly, the model aims to consider day-ahead decisions in the first stage and balancing decisions in the second stage. Furthermore, the intermittent nature of renewable sources generation is handled by scenario generation with Monte-Carlo Simulation (MCS) method. NEMOs are physically connected as radial network. Therefore, all relative network constraints are taken into account as a linear power flow for radial networks. The results of the implementation of the proposed model demonstrate the effectiveness of various DR biddings on hourly DR volume, hourly DR cost and power exchange between different NEMOS. © 2019 IEEE.

Abstract
This study proposes a novel multi-agent method for electric vehicle (EV) owners who will take part in the electricity market. Each EV is considered as an agent, and all the EVs have vehicle-to-grid capability. These agents aim to minimise the charging cost and to increase the privacy of EV owners due to omitting the aggregator role in the system. Each agent has two independent decision cores for buying and selling energy. These cores are developed based on a reinforcement learning (RL) algorithm, i.e. Q-learning algorithm, due to its high efficiency and appropriate performance in multi-agent methods. Based on the proposed method, agents can buy and sell energy with the cost minimisation goal, while they should always have enough energy for the trip, considering the uncertain behaviours of EV owners. Numeric simulations on an illustrative example with one agent and a testing system with 500 agents demonstrate the effectiveness of the proposed method.