Abstract

Abstract
Melanoma is considered the deadliest type of skin cancer and in the last decade, the incidence rate has increased substantially. However, automatic melanoma classification has been widely used to aid the detection of lesions as well as prevent eventual death. Therefore, in this paper we decided to investigate how an attention mechanism combined with a classical backbone network would affect the classification of melanomas. This mechanism is known as triplet attention, a lightweight method that allows to capture cross-domain interactions. This characteristic helps to acquire rich discriminative feature representations. The different experiments demonstrate the effectiveness of the model in five different datasets. The model was evaluated based on sensitivity, specificity, accuracy, and F1-Score. Even though it is a simple method, this attention mechanism shows that its application could be beneficial in classification tasks.

Abstract
Energy efficiency and indoor air quality are frequently-two conflicting objectives when establishing the air change rate (ACH) of a dwelling. In Europe, the northern countries have a clear focus on energy conservation, leading to an obvious awareness of the importance of airtightness, which translates into a high level of regulation and implementation. Meanwhile, the southern counterparts experience a more com-plex challenge by having predominantly passive ventilation strategies and milder climates, which often results in a more permissive approach. This work proposes an innovative labelling methodology to classify the performance of naturally ventilated dwellings. A representative sample of a southern European national built stock is used in a stochastic process to create a pool of 43,200 unique dwellings. The simulation period refers to a month of the typical heating season in the southern European mild conditions. The results test the labelling methodology. With feature selection, ACH limits, and a labelling strategy, dwellings classify according to their ability to provide adequate ACHs. The terrain was the best splitter of the dataset from the applied categorical variables. Regarding continuous variables, the airtightness was the one explaining most of the variability of the outputted ACHs, followed by the floor area. From the best performing dwellings labelled as compliant (Com), the average airtightness level was 5.3 h(-1), with 4.9 h(-1) and 5.8 h(-1) in rural and urban locations.

Abstract
The new education paradigm derived from industry 4.0 indicates that personalised and engaging learning models should be applied to train employees so they can know the related concepts of this industry, have the necessary skills to perform adequately their tasks and correctly use the technologies and tools. This paper presents a qualitative analysis of existing frameworks for training through Serious Games. By analysing the frameworks identified in a previously conducted literature review, this paper shows the frameworks' dimensions, objectives, and trends. Gaps regarding the planned adaptation of Serious Games by the studied frameworks and the lack of relationship between learning outcomes and professional competencies were also presented. © 2022 Elsevier B.V.. All rights reserved.

Abstract
A 3D real-Time quality inspection platform that specifically focus on automotive cast iron parts was developed for the industry and is presented in this work. It is supported by a cloud-based platform, which combines recent software and hardware advances to deal with large amounts of information related to the acquisition process and the computational power needed to execute the computer vision platform algorithms (e.g., point cloud filtering, alignment, and comparison). This platform introduces changes in the current workflow through the inspection process digitalization. Indeed, it promotes the reduction of human-related inspection errors, as well as ergonomic issues, while simultaneously making available a solution for the automatic gathering and storing of data in a cloud-like environment, for further access and advanced data analytics.

Abstract
This paper proposes a roadmap to integrate existing educational web applications into the ecosystem based on a learning management system. To achieve this integration, applications must support the Learning Tools Interoperability specification in the role of tool provider. The paper starts with an overview of the evolution of this specification, emphasizing the main features of the current stable version. Then, it proposes a set of design goals and milestones to guide the adaptation process. The proposed roadmap was validated with existing applications. This paper reports on the challenges faced to apply it in these concrete cases.