Abstract
Workplace innovation (WPI) plays an important role at the institutional level, enabling firms to improve their competitive advantage. However, it remains an under-researched theme. The purpose of this paper is to extend current knowledge of the mechanisms that facilitate innovations in the workplace, identifying the main determinants that leverage WPI, based on a systematic literature review (SLR). An SLR has been carried out in order to determine the main determinants of WPI. The main topics are analyzed, and then the determinants derived inductively. WPI is depicted as a wide array of topics (38) that may be clustered around five different determinants that are transverse and intertwined. This research contributes by filling the gap regarding WPI. It combines five main determinants and provides important insights into possible avenues for the research of WPI.

Abstract

Abstract
Web 2.0 has allowed collaboration, interaction and sharing of information online, such as online review platforms. Consequently, these short and straightforward opinions have increasingly proved to be essential sources of information not only for consumers but also for companies, as they represent the consumer's sincere evaluation, free from any kind of bias. In this sense, there should be an interest in the analysis and monitoring of online reviews by companies, as the result of these actions may provide guidelines to readjust their strategy, support decision-making and ensure the satisfaction of their consumers. To generate useful information to assist decision-making and strategies' implementation by retailers in the Municipality of Porto, online reviews from the GoogleMyBusiness platform were organised, classified, and analysed. 9945 online reviews were extracted, directed to 246 retail adaptations of the Municipality of Porto, from 2017 to 2020, which were later classified by the polarity of sentiment (positive, negative, neutral, or mixed). Sentiment analysis was conducted, combined with statistical tests and frequency distribution tables to discover relevant information for retailers. With sentiment analysis, retailers can understand their consumers and their behaviour to adapt their strategies and make the right decisions to ensure their customers' satisfaction. With the results obtained, this study proves that it is possible to extract useful information from online reviews and reveals that it is still an area of little interest for retailers in the Municipality of Porto.

Abstract
The fusion of data from different sensors often requires that an accurate geometric transformation between the sensors is known. The procedure by which these transformations are estimated is known as sensor calibration. The vast majority of calibration approaches focus on specific pairwise combinations of sensor modalities, unsuitable to calibrate robotic systems containing multiple sensors of varied modalities. This paper presents a novel calibration methodology which is applicable to multi-sensor, multi-modal robotic systems. The approach formulates the calibration as an extended optimization problem, in which the poses of the calibration patterns are also estimated. It makes use of a topological representation of the coordinate frames in the system, in order to recalculate the poses of the sensors throughout the optimization. Sensor poses are retrieved from the combination of geometric transformations which are atomic, in the sense that they are indivisible. As such, we refer to this approach as ATOM - Atomic Transformations Optimization Method. This makes the approach applicable to different calibration problems, such as sensor to sensor, sensor in motion, or sensor to coordinate frame. Additionally, the proposed approach provides advanced functionalities, integrated into ROS, designed to support the several stages of a complete calibration procedure. Results covering several robotic platforms and a large spectrum of calibration problems show that the methodology is in fact general, and achieves calibrations which are as accurate as the ones provided by state of the art methods designed to operate only for specific combinations of pairwise modalities.

Abstract
Currently, there has been a great development of the wind energy market, which is accompanied by an increase in the number of wind farms at sea, the offshore wind farms. Therefore, it is crucial to ensure that efficiency in energy production is maximum and that the levelized cost of energy (LCOE) is minimal. In this paper, a mixed-integer linear programming model (MILP) is proposed to find the best wind farm layout taking into account the wake effect in order to maximize energy production. The design of an offshore wind farm located at the North Sea is considered as a case study, contemplating three situations regarding the number of wind turbines to be installed and to determine the best positioning of them in order to maximize energy production, taking into account the wake effect and the lowest LCOE. © 2022, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

Abstract