Abstract
Clustering of source code is a technique that can help improve feedback in automated program assessment. Grouping code submissions that contain similar mistakes can, for instance, facilitate the identification of students' difficulties to provide targeted feedback. Moreover, solutions with similar functionality but possibly different coding styles or progress levels can allow personalized feedback to students stuck at some point based on a more developed source code or even detect potential cases of plagiarism. However, existing clustering approaches for source code are mostly inadequate for automated feedback generation or assessment systems in programming education. They either give too much emphasis to syntactical program features, rely on expensive computations over pairs of programs, or require previously collected data. This paper introduces an online approach and implemented tool-AsanasCluster-to cluster source code submissions to programming assignments. The proposed approach relies on program attributes extracted from semantic graph representations of source code, including control and data flow features. The obtained feature vector values are fed into an incremental k-means model. Such a model aims to determine the closest cluster of solutions, as they enter the system, timely, considering clustering is an intermediate step for feedback generation in automated assessment. We have conducted a twofold evaluation of the tool to assess (1) its runtime performance and (2) its precision in separating different algorithmic strategies. To this end, we have applied our clustering approach on a public dataset of real submissions from undergraduate students to programming assignments, measuring the runtimes for the distinct tasks involved: building a model, identifying the closest cluster to a new observation, and recalculating partitions. As for the precision, we partition two groups of programs collected from GitHub. One group contains implementations of two searching algorithms, while the other has implementations of several sorting algorithms. AsanasCluster matches and, in some cases, improves the state-of-the-art clustering tools in terms of runtime performance and precision in identifying different algorithmic strategies. It does so without requiring the execution of the code. Moreover, it is able to start the clustering process from a dataset with only two submissions and continuously partition the observations as they enter the system.

Abstract
The eDNA autonomous biosampler results from a line of research aimed at developing systems for sampling and collecting marine biological data, and for collecting environmental DNA. Environmental DNA is a tool that has been increasingly used in the biological monitoring of aquatic environments, as it is a non-invasive method with very promising results when it comes to assessing biological diversity. In this sense, the automation of this method has the potential to greatly increase the temporal and spatial resolution of current biological monitoring programs in aquatic environments. The system has been developed in a partnership between research teams at the Centre for Robotics and Autonomous Systems (CRAS - INESC TEC) and CIIMAR and has been tested in multiple operational scenarios, including the Arctic, where it was attached to the AUV IRIS.

Abstract
Geophysical studies on the lunar surface have, in the past, used various methods that contribute not only towards the knowledge of the lunar subsurface but also contribute towards the design of future lunar missions, namely those that will, in the near future, take humans to the Moon’s surface. This work analyzes a specific set of ground penetrating radar (GPR) data, collected during the Chang’E-4 mission of the Chinese Space Agency, using theYutu-2 rover within the von Kármán crater, on the far-side of the Moon. From this dataset two electrical parameters were estimated. The approach uses the backscatter of the electromagnetic wavefield in order to obtain estimates of the real component of the complex relative permittivity as well as the electrical resistivity. © 2024 International Multidisciplinary Scientific Geoconference. All rights reserved.

Abstract
The Ambient Assisted Living (AAL) systems are human-centered and designed to prioritize the needs of elderly individuals, providing them with assistance in case of emergencies or unexpected situations. These systems involve caregivers or selected individuals who can be alerted and provide the necessary help when needed. To ensure effective assistance, it is crucial for caregivers to understand the reasons behind alarm triggers and the nature of the danger. This is where an explainability module comes into play. In this paper, we introduce an explainability module that offers visual explanations for the fall detection module. Our framework involves generating anchor boxes using the K-means algorithm to optimize object detection and using YOLOv8 for image inference. Additionally, we employ two well-known XAI (Explainable Artificial Intelligence) algorithms, LIME (Local Interpretable Model) and Grad-CAM (Gradient-weighted Class Activation Mapping), to provide visual explanations.

Abstract

Abstract
This paper explores the internationalisation of small and medium-sized firms (SMEs) in Africa and Latin America. A total of 97 papers covering the period between 1995 and 2017 were analysed, providing a unique comparative perspective of the internationalisation of SMEs. The analysis of the papers revealed the following six main topics: international networking; financing, export promotion; internationalisation strategies; resources and business environment/context; e-business, e-commerce; and barriers to internationalisation. The topic 'internationalisation strategies' is the most researched topic both regarding the internationalisation of both African and Latin American SMEs. However, while the studies on Latin American SMEs focus on rapid internationalisation, international entrepreneurship orientation and export performance, the studies on African SMEs focus on supply performance, international behaviour, internationalisation process, knowledge and key-selection of foreign markets. This provides a clear perspective on how SMEs of those two emerging continents deal with the intricacies of internationalisation.