Abstract
The objective of coalition formation is to partition the agent set that gives the highest utility to the system. Over the past three decades, the process of coalition formation has been applied to various real-life applications where agents need to form efficient groups to accomplish a task. This article presents a study of the state-of-the-art approaches on the applications of coalition formation. In particular, it surveys the algorithmic approaches for optimizing the system's welfare. The algorithms are then analyzed based on a framework that consists of two dimensions: (i) the features of the problem environment, which gives an overview of the complexity level of the environment, and (ii) the features of the problem solver, which gives an overview of the solution quality. Our study analyses the approaches in terms of the framework mentioned above, justifies the use of the approaches in a particular problem setting, presents guidance to choose the right algorithmic approach for a problem at hand, and classifies the state-of-the-art approaches according to their basic working principles. This article also presents possible future directions of work to the research community. This study shows that theoretical models need more research before they can be deployed in the real world.

Abstract
O mundo pós-COVID-19 é claramente mais digital do que no passado e cursos como o Mestrado em Negócio Electrónico (MNE) são relevantes para capacitar os profissionais do nosso país para pensarem as actividades realizadas on-line ou suportadas em algum momento no digital. Esta revista apresenta trabalhos de investigadores-júnior realizados no contexto da unidade curricular Metodologias de Investigação e Comunicação Científica, que contam com a orientação de professores/investigadores-senior da escola de Ciências Empresariais (ISCAP) do Politécnico do Porto e de outras escolas/faculdades do ensino superior em Portugal.

Abstract
Football is one of the most popular sports in the world, so the perception of the game and the prediction of results is of general interest to fans, coaches, media and gamblers. Although predicting football results is a very complex task, the football betting business has grown over time. The unpredictability of football results and the growing betting business justify the development of prediction models to support gamblers. In this article, we develop machine learning methods that take multiple statistics of previous matches and attributes of players from both teams as inputs to predict the outcome of football matches. Several prediction models were tested, with the experimental results showing encouraging performance in terms of the profit margin of football bets. © 2022 Elsevier B.V.. All rights reserved.

Abstract
The advance of technology in the automotive industry brought several new functionalities providing more efficiency and safety. This, however, has one important concern: the development has become more complex. AMALTHEA is a framework for automotive system design and development in a model-based development fashion. It includes several features, including testing, software design, simulation and traceability. This paper presents ongoing work to integrate GPU tracing in the AMALTHEA standard format for tracing execution events, thus enabling platform heterogeneity to be supported in the tracing model. © 2022, Ada-Europe. All rights reserved.

Abstract

Abstract
The use of virtual reality technologies for data visualization and analysis has been an emerging topic of research in the past years. However, one type of data has been left neglected, the point cloud. While some strides have been made in the visualization and analysis of point clouds in immersive environments, these have yet to be used for direct manipulation interactions. It is hypothesized that as with other types of data, bringing direct interactions and 3D visualization to point clouds may increase the ease of performing basic handling tasks. An immersive application for virtual reality HMDs was developed in Unity to help research this hypothesis. It is capable of parsing classified point cloud files with extracted objects and representing them in a virtual environment. Several editing tools were also developed, designed with the HMD controllers in mind. The end result allows the user to perform basic transformative tasks to the point cloud with an ease of use and intuitive feeling unmatched by the traditional desktop-based tools. © 2021 Owner/Author.