Abstract
Matrix converters feature low switching loss, small electromagnetic interference filter, and the potential for achieving high power density. With the employment of wide-bandgap devices, such as silicon carbide devices, the converter performance can be further improved. For a safe operation of matrix converters, an overvoltage protection circuit is necessary to limit the voltage stress of the devices during fault conditions. Due to the high switching speed of silicon carbide devices, the topology and layout design of the overvoltage protection circuit is critical to ensure fast and robust protection for the devices. In this article, a detachable overvoltage protection circuit is designed for each phase leg of the matrix converter. The topology and hardware layout design are elaborated. A 15-kW full silicon carbide implemented matrix converter is built, and the designed overvoltage protection circuits are employed and tested.

Abstract
Pollutant emissions from passenger cars give rise to harmful effects on human health and the environment. Predicting traffic flow is a challenging problem, but essential to understand what factors influence car traffic and what measures should be taken to reduce carbon dioxide emissions. In this work, we developed a predictive model to forecast traffic flow in several locations in the city of Porto for 24 h later, i.e., the next day at the same time. We trained a XGBoost Regressor with multi-modal data from 2018 and 2019 obtained from traffic and weather sensors of the city of Porto and the geographic location of several points of interest. The proposed model achieved a mean absolute error, mean square error, Spearman's rank correlation coefficient, and Pearson correlation coefficient equal to 80.59, 65395, 0.9162, and 0.7816, respectively, when tested on the test set. The developed model makes it possible to analyse which areas of the city of Porto will have more traffic the next day and take measures to optimise this increasing flow of cars. One of the ideas present in the literature is to develop intelligent traffic lights that change their timers according to the expected traffic in the area. This system could help decrease the levels of carbon dioxide emitted and therefore decrease its harmful effects on the health of the population and the environment.

Abstract
This research aims to highlight the major domains of and address the most prominent topics in the Total Quality Management (TQM) field in the service sector. Although there are numerous studies related to TQM, systematic quantitative reviews on TQM in services are scarce. The objective of this paper is to present a thorough analysis of the current mostly discussed issues related to the use of TQM in services by conducting a bibliometric analysis of the extant literature on TQM collected from Web of Science and Scopus databases. The findings indicate that TQM implementation is not a fading topic. The studies in the field of 'TQM use in services' are growing and becoming more intensive. TQM-related practices are gaining more attention while the TQM implementation framework is still under development. Healthcare is the most researched industry. Top management commitment/leadership is a critical construct and managers should be aware of the obstacle caused by lacking it. TQM professionals and managers in the service sector can benefit from this paper by having a sketch of the latest and most prominent academic findings and thus gaining insights on techniques that fit into TQM implementation. For academic professionals, several research avenues are pointed out.

Abstract

Abstract
The financial planning of distribution systems usually includes the prediction of annual mandatory investments, concerning the resources that the DSO is compelled to allocate as a result of new network connections, required by new consumers or new energy producers. This paper presents a methodology to estimate the mandatory investments that the DSO should do in the distribution network. These estimations are based on historical data, load growth expectations and various socioeconomic indices. However, the available database contains very few annual investment examples (one aggregated value per year since 2002) compared to the large number of variables (potential inputs), which is a factor of regression overfitting. Thus, the applicable regression techniques are restrained to simple but efficient models. This paper describes a new methodology to identify the most suitable estimation models. The implemented application automatically builds, selects, and tests estimation models resulting from combinations of input variables. The final forecast is provided by a committee of models. Results obtained so far confirm the feasibility of the adopted methodology.

Abstract
This paper presents a new stochastic mixed-integer second-order cone programming model to solve the problem of optimal operation of distribution systems considering network reconfiguration, voltage control devices, dispatchable and nondispatchable distributed generators (DGs), and the possibility of closed-loop topology operation. The decision variables are the active and reactive power generation of DGs, the tap position of substations' (SS) on-load tap changers and voltage regulators, the number of switchable capacitor banks in operation, and the operational statuses of sectionalizing and tie switches. The proposed formulation considers the minimization of (i) the cost of the energy purchased from the distribution SSs and dispatchable DGs, (ii) greenhouse gas emissions, (iii) technical energy losses, and (iv) the number of basic loops formed in the network. Tests are carried out using the 33-node system and the results demonstrate the effectiveness of the proposed formulation. The benefits provided by the presented approach include reduced operational costs and greenhouse gas emissions mitigation.