João Paulo Almeida

Abstract
The automotive industry deals with complex processes. Becoming aware of the importance of agile management they are contributing to a creative fusion known as leagile. However, this concept needs further study and investigation. This work presents a systematic literature review on Lean Agile implementation in the automotive industry. Thirty-three publications were reviewed and characterized according to the year of publication, country of origin, industrial sector, used tools and their contributions to the automotive sector. The results show that 50% of the articles were published after 2018. The countries with the most publications are India, Portugal, and United Kingdom. The most cited tools are Value Stream Mapping (VSM), Just in Time (JIT) and 5S (23%). This study confirms the growing use of leagile in the automotive industry and the growing potential for research development in the area.

Abstract
The present study brings forward a simulation-based study of the production process of a Portuguese bakery. The main goal is to analyse different production processes and propose improvements, through the use of discrete event simulation. A relevant set of data was collected, and four productive processes were selected to be modelled using Simio software (Simulation Modelling based on Intelligent Objects). The analysis of the developed models highlighted the need for improvements and different scenarios were created to this purpose. Among the obtained results, it was found that the adoption of mixed production scenarios allowed the increase of the production level while maintaining the current existing resources. In conclusion, this study highlighted the ability of the simulation technique to analyse manufacturing processes, throughout the creation of different scenarios, providing insights on the production process optimising the companies' productive performance.

Abstract
[No abstract available]

Abstract
Storytelling is a powerful marketing tool that can be used to attract the audience's attention and influence behavior. However, this investigation seeks to understand more deeply the importance of written narratives in the marketing field. In this sense, the objective of this article is to explore similarities and identify patterns, phases or stages, variables, indicators, and respective relationships (models) to help marketers to create storytelling. In the analogy of the visual methodology analytical process, this literature review created a selection of the sample and developed content to structure storytelling within the marketing framework. Through the analysis of 78 papers published in the Web of Science main collection, this research finds out three clusters: marketing cluster, content cluster, and context cluster. Our results indicate that, in marketing, storytelling elicits brand identification, awareness, and customer engagement, as well as it helps with self-expression, a sense of belonging, and a perception of the value of the product or brand. We find some variables, indicators, and respective relationships (models) that can be used in storytelling in the marketing field to improve value awareness. This review also allowed us to identify factors related to the structuring of marketing storytelling. And we found three key elements of the story construct that are transversal: content, classification, and character. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
The evolution of technology and the increasing connectivity between devices lead to an increased risk of cyberattacks. Good protection systems, such as Intrusion Detection System (IDS) and Intrusion Prevention System (IPS), are essential in trying to prevent, detect and counter most of the attacks. However, the increasing creativity and type of attacks raise the need for more resources and processing power for the protection systems which, in turn, requires horizontal scalability to keep up with the massive companies' network infrastructure and with the complexity of attacks. Technologies like machine learning, show promising results and can be of added value in the detection and prevention of attacks in real-time. But good algorithms and tools are not enough. They require reliable and solid datasets to be able to effectively train the protection systems. The development of a good dataset requires horizontal-scalable, robust, modular and fault-tolerance systems, so that the analyses may be done also in real-time. This paper describes an architecture for horizontal-scaling capture architecture, able to collect packets from multiple sources and prepared for real-time analysis. It depends on multiple modular nodes with specific roles to support different algorithms and tools.