Abstract
This paper presents a methodology for the optimal placement and sizing of reactive power compensation devices in a distribution system (DS) with distributed generation. Quasi-static time series is embedded in an optimization method based on a genetic algorithm to adequately represent the uncertainty introduced by solar photovoltaic generation and electricity demand and its effect on DS operation. From the analysis of a typical DS, the reactive power compensation rating power results in an increment of 24.9% when compared to the classical genetic algorithm model. However, the incorporation of quasi-static time series analysis entails an increase of 26.8% on the computational time required.

Abstract

Abstract
To study how emotions affect people in expressive writing, scientists require tools to aid them in their research. The researchers at M-BW use an Experiment Management System, called HandSpy to store and analyze the hand-written productions of participants. The input is stored as digital ink and then displayed on a web-based interface. To assist the project, HandSpy integrates with new sources of information to help researchers visualize the link between psychophysiological data and written input. The newly acquired data is synchronized with the existing burst-pause interval model and represented on the user interface of the platform together with the already existing information.

Abstract

Abstract
The Internet of Things (IoT) is rapidly becoming an integral component of the industrial market in areas such as automation and analytics, giving rise to what is termed as the Industrial IoT (IIoT). The IIoT promises innovative business models in various industrial domains by providing ubiquitous connectivity, efficient data analytics tools, and better decision support systems for a better market competitiveness. However, IIoT deployments are vulnerable to a variety of security threats at various levels of the connectivity and communications infrastructure. The complex nature of the IIoT infrastructure means that availability, confidentiality and integrity are difficult to guarantee, leading to a potential distrust in the network operations and concerns of loss of critical infrastructure, compromised safety of network end-users and privacy breaches on sensitive information. This work attempts to look at the requirements currently specified for a secure IIoT ecosystem in industry standards, such as Industrial Internet Consortium (IIC) and OpenFog Consortium, and to what extent current IIoT connectivity protocols and platforms hold up to the standards with regard to security and privacy. The paper also discusses possible future research directions to enhance the security, privacy and safety of the IIoT.

Abstract
Nowadays, industrial robots are still commonly programmed using essentially off-line tools, such as is the case of structured languages or simulated environments. This is a very time-consuming process, which necessarily requires the presence of an experienced programmer with technical knowledge of the set-up to be used, as well as a concept and a complete definition of the details associated with the operations. Moreover, considering some industrial applications such as coating, painting, and polishing, which commonly require the presence of highly skilled shop floor operators, the translation of this human craftsmanship into robot language using the available programming tools is still a very difficult task. In this regard, this paper presents a programming by demonstration solution, that allows a skilled shop floor operator to directly teach the industrial robot. The proposed system is based on the 6D Mimic innovative solution, endowed with an IMU sensor as to enable the system to tolerate temporary occlusions of the 6D Marker. Results show that, in the event of an occlusion, a reliable and highly accurate pose estimation is achieved using the IMU data. Furthermore, the selected IMU was a low-cost model, to not severely increase the 6D Mimic cost, despite lowering the quality of the readings. Even in these conditions, the developed algorithm was able to produce high-quality estimations during short time occlusions.