Abstract

Abstract
Demand response (DR) programs offer tremendous opportunities to those who have concerns about the future of energy. Since the DR strategies facilitate new technologies to take part in the power systems, the idea of spreading of electric vehicles (EVs) attracts researchers around the world. In this study, an optimal energy management strategy for EV parking lots considering peak load reduction based DR programs is built in stochastic programming framework, denoted by EV parking lot energy management (EV-PLEM). The proposed EV-PLEM aims to maximize the load factor during the daily operation of an EV parking lot taking into account the uncertain behavior of EVs, such as arrival and departure times together with the stochasticity of the remaining state-of-energy of EVs when they reach the parking lot. A set of case studies is conducted to validate the effectiveness of the suggested EV-PLEM concept, and credible results and useful findings are reported for the cases in which the EV-PLEM is implemented.

Abstract
The analysis of the intern anatomy of wood samples for species identification is a complex task that only experts can perform accurately. Since there are not many experts in the world and their training can last decades, there is great interest in developing automatic processes to extract high-level information from microscopic wood images. The purpose of this work was to develop algorithms that could provide meaningful information for the classification process. The work focuses on hardwoods, which have a very diverse anatomy including many different features. The ray width is one of such features, with high diagnostic value, which is visible on the tangential section. A modified distance function for the DBSCAN algorithm was developed to identify clusters that represent rays, in order to count the number of cells in width. To test both the segmentation and the modified DBSCAN algorithms, 20 images were manually segmented, obtaining an average Jaccard index of 0.66 for the segmentation and an average index M=0.78 for the clustering task. The final ray count had an accuracy of 0.91. © 2019, Springer Nature Switzerland AG.

Abstract
Nowadays, workers and students preparing for a career are aware that they must constantly update their skills in order to fulfil both the market’s and companies’ demands. The environment is packed with technologies that help us by optimizing our tasks on a daily basis. However, the majority of opinions can agree that these tools may have a bigger impact on the labour market than it was ever expected. What is the future of jobs as we know them, and what impact will future technology innovations have on society? Lots of factors enter the picture when this particular topic is discussed – including the economy in general, productivity rates, salaries and expenses, people’s stress and satisfaction levels, among others. To achieve this study’s main purpose, questionnaires were distributed, which were the basis for the creation of a hypothetical model that represents our understanding of the subject considering the sample’s feedback. This study also advances our view concerning the literature review and the opinions of those surveyed, aiming to provide a strong and consistent theory of what the market labour will be; that is, which jobs are likely to lose practice, which ones may subsist, and which activities might grow with the circumstances’ influence. © 2019, Springer Nature Switzerland AG.

Abstract
Mobility is an essential part of modern society and of the actual panorama of mobility and accessibility, including Public Transportation Systems (PTS), needs to be rethink and adapted, regarding the social and technological evolutions, enhancing a healthier, environmentally sustainable, economic viable and equitable transportation for all the population. This paper describes the actual mobility attributes, through mentioning diverse case studies, and technological features/requirements towards presenting a solution to achieve the redefinition of mobility systems, i.e. allowing to enhance integrated mobility options, from the Public Transport (PT) modes through the soft modes enclosure, supported by a technological system that could manage and support the efficient use of such mobility options - that is designated as Flexible on Demand Transport Services (FDTS). The involvement and commitment of all the stakeholders in the mobility process as well as the municipal support, and the policy makers in general is essential to fully adopt the mobility framework dynamics and implement the future mobility of the intermodal system and of the MaaS integration.

Abstract
This paper addresses a framework for expansion planning of an active distribution network (ADS) that supplies its downward active microgrids (AMGs) and it participates in the upward wholesale market to sell its surplus electricity. The proposed novel model considers the impact of coordinated and uncoordinated bidding of AMGs and demand response providers (DRPs) on the optimal expansion planning. The problem has six sources of uncertainty: upward electricity market prices, AMGs location and time of installation, AMGs power generation/consumption, ADS intermittent power generations, DRP biddings, and the ADS system contingencies. The model uses the conditional value at risk (CVaR) criterion in order to handle the trading risks of ADS with the wholesale market. The proposed formulation integrates the deterministic and stochastic parameters of the risk-based expansion planning of ADS that is rare in the literature on this field. The introduced method uses a four-stage optimisation algorithm that uses genetic algorithm, CPLEX and DICOPT solvers. The proposed method is applied to the 18-bus and 33-bus test systems to assess the proposed algorithm. The proposed method reduces the aggregated expansion planning costs for the 18-bus and 33-bus system about 44.04% and 11.82% with respect to the uncoordinated bidding of AMGs/DRPs costs, respectively.