Abstract
This paper presents a C++ application programming interface for a co-evolutionary algorithm for solution and scenario generation in stochastic problems. Based on a two-space biased random-key genetic algorithm, it involves two types of populations that are mutually impacted by the fitness calculations. In the solution population, high-quality solutions evolve, representing first-stage decisions evaluated by their performance in the face of the scenario population. The scenario population ultimately generates a diverse set of scenarios regarding their impact on the solutions. This application allows the straightforward implementation of this algorithm, where the user needs only to define the problem-dependent decoding procedure and may adjust the risk profile of the decision-maker. This paper presents the co-evolutionary algorithm and structures the interface. We also present some experiments that validate the impact of relevant features of the application.

Abstract
Synthetic data consists of artificially generated data. When data are scarce, or of poor quality, synthetic data can be used, for example, to improve the performance of machine learning models. Generative adversarial networks (GANs) are a state-of-the-art deep generative models that can generate novel synthetic samples that follow the underlying data distribution of the original dataset. Reviews on synthetic data generation and on GANs have already been written. However, none in the relevant literature, to the best of our knowledge, has explicitly combined these two topics. This survey aims to fill this gap and provide useful material to new researchers in this field. That is, we aim to provide a survey that combines synthetic data generation and GANs, and that can act as a good and strong starting point for new researchers in the field, so that they have a general overview of the key contributions and useful references. We have conducted a review of the state-of-the-art by querying four major databases: Web of Sciences (WoS), Scopus, IEEE Xplore, and ACM Digital Library. This allowed us to gain insights into the most relevant authors, the most relevant scientific journals in the area, the most cited papers, the most significant research areas, the most important institutions, and the most relevant GAN architectures. GANs were thoroughly reviewed, as well as their most common training problems, their most important breakthroughs, and a focus on GAN architectures for tabular data. Further, the main algorithms for generating synthetic data, their applications and our thoughts on these methods are also expressed. Finally, we reviewed the main techniques for evaluating the quality of synthetic data (especially tabular data) and provided a schematic overview of the information presented in this paper.

Abstract

Abstract
The complexity of systems continues to increase rapidly, especially due to the multi-level integration of subsystems from different domains into cyber-physical systems. This results in special challenges for the efficient verification and validation (V&V) of these systems with regard to their requirements and properties. In order to tackle the new challenges and improve the quality assurance processes, the V&V workflows have to be documented and analyzed. In this paper, a novel approach for the workflow modelling of V&V activities is presented. The generic approach is tailorable to different industrial domains and their specific constraints, V&V methods, and toolchains. The outcomes comprise a dedicated modelling notation (VVML) and tool-support using the modelling framework Enterprise Architect for the efficient documentation and implementation of workflows in the use cases. The solution enables the design of re-usable workflow assets such as V&V activities and artifacts that are exchanged between workflows. This work is part of the large scale European research project VALU3S that deals with the improvement and evaluation of V&V processes in different technical domains, focusing on safety, cybersecurity, and privacy properties.

Abstract
Mobile ticketing services allow urban transport passengers to travel in a convenient and easy way, enhancing their travelling experience. In recent years several mobile ticketing services have started to be developed and launched, but there is still a lot to be done in terms of its effectiveness, efficiency and innovation. This paper presents a micro-location mobile ticketing solution based on Near Field Communication (NFC) and Bluetooth Low Energy (BLE) technologies, called Anda. This solution is based on a check-in/be-out scheme and requires the minimum intervention from the passenger. It is really innovative in the urban transport field, as it takes advantage of BLE technology not usually used for this purpose, it is based on a concept of post-billing with a fare optimization algorithm associated and it allows the micro-location of passengers throughout their journeys. This paper details the architecture of the solution and its mode of operation. It also presents the evaluation methodology that was followed during the pilot trial that took place in the Metropolitan Area of Porto (AMP), Portugal, during one year with 140 real passengers. A set of design lessons were identified as a result of the field tests and materialized in five mobile ticketing design dimensions, constituting important contributions to the design of future mobile ticketing services. Anda was commercially deployed in the AMP in 2018 and is used by thousands of passengers every day.

Abstract
A significant advancement regarding the electrification of transportation has occurred in recent years due to technological developments, environmental concerns, and geopolitical issues in the energy areas all over the world. In this study, a new concept for the integration of rail-based public transportation systems with electric vehicle (EV) parking lots operated by a park and ride strategy is propounded, including also renewable resources based energy production. In the proposed structure, the charging power demand of the EV parking lot is supplied by different charging strategies considering the existing unused energy infrastructure capacity and the regenerative braking energy of the railway system, altogether. Here, the design of a photovoltaic (PV) based carport type renewable energy production unit is also realized in the existing local parking area. The development of an optimal energy management system to effectively manage these inputs is realized and the uncertainties pertaining to EVs' demand are also taken into account. To demonstrate its efficacy, the concept is tested considering a bench of case studies and comprehensive results are obtained.