Source-free Active Domain Adaptation for Diabetic Retinopathy Grading Based on Ultra-wide-field Fundus Image

Domain adaptation (DA) has been widely applied in the diabetic retinopathy (DR) grading of unannotated ultra-wide-field (UWF) fundus images, which can transfer annotated knowledge from labeled color fundus images. However, suffering from huge domain gaps and complex real-world scenarios, the DR grading performance of most mainstream DA is far from that of clinical diagnosis. To tackle this, we propose a novel source-free active domain adaptation (SFADA) in this paper. Specifically, we focus on DR grading problem itself and propose to generate features of color fundus images with continuously evolving relationships of DRs, actively select a few valuable UWF fundus images for labeling with local representation matching, and adapt model on UWF fundus images with DR lesion prototypes. Notably, the SFADA also takes data privacy and computational efficiency into consideration. Extensive experimental results demonstrate that our proposed SFADA achieves state-of-the-art DR grading performance, increasing accuracy by 20.9% and quadratic weighted kappa by 18.63% compared with baseline and reaching 85.36% and 92.38% respectively. These investigations show that the potential of our approach for real clinical practice is promising

Learning with worked-out problems in Manufacturing Technology: The effects of instructional explanations and self-explanation prompts on acquired knowledge acquisition, near and far transfer performance

In the present research, two different explanatory approaches – namely, instructional explanation and self-explanation prompts – were applied in worked-out-problem-based learning (learning with worked-out problems) in a computer-assisted instructional environment in the domain of manufacturing technology. This research aims at comparing the effects of both explanatory approaches on topic knowledge acquisition, near transfer performance, and far transfer performance. Additionally, this research also attempts to examine the impact of topic interest on the aforementioned variables, in addition to the relationships between topic interest, mental effort, and learning outcomes. A total of 76 second-year students were randomly assigned to experimental and control groups. The pre- and post-tests were used to measure topic knowledge acquisition, near-transfer performance, and far-transfer performance, whereas topic interest and mental effort were measured by means of Topic Interest Questionnaire and NASA Task Load Index (NASA-TLX) respectively. The analysis outcomes revealed that the self-explanation prompts approach was significantly superior to the instructional-explanation approach in terms of topic knowledge acquisition and near transfer performance. In addition, the results demonstrated that the impact of topic interest was significantly noticeable on far transfer tasks, but not on topic knowledge acquisition and near transfer tasks. On the other hand, the relationship between mental effort investment and test performance was not statistically significant. Finally, an equivocal relationship, which varied depending on the treatment conditions, was discovered between topic interest, mental effort, and test performance. (DIPF/orig.)In der vorliegenden Untersuchung wurden zwei unterschiedliche Lehrmethoden – instruktionale Erklärung und Aufforderung zur Selbsterklärung – angewandt auf das Lernen mit Lösungsbeispielen in einer computergestützten Lernumgebung, die thematisch im Bereich der Fertigungstechnik angesiedelt ist. Die computergestützte Lernumgebung bestand aus einer vom Autor erstellten Lernsoftware, die mit Macromedia Authorware entworfen und entwickelt wurde. Hauptziel der Studie war ein Vergleich der Effekte beider Lehrmethoden auf die Aneignung von Sachwissen sowie die Leistung beim nahen und weiten Transfer. Außerdem wurden die Auswirkungen von Gegenstandsinteresse auf die zuvor genannten Kriterien untersucht und die Beziehungen zwischen Gegenstandsinteresse, mentaler Anstrengung und Lernergebnissen. Insgesamt wurden 76 Studierende im zweiten Jahr ihres Studiums an der Fakultät für Technische Bildung, Universität Tun Hussein Onn Malaysia (UTHM), nach dem Zufallsprinzip in drei Gruppen aufgeteilt: Selbsterklärungsaufforderung (SE: n = 25), instruktionale Erklärung (IE: n = 25) und Kontrollgruppe (n = 26). Mit Pre- und Post-Tests wurden die Aneignung von Sachwissen sowie die nahe und weite Transferleistung erhoben. Gegenstandsinteresse und mentale Anstrengung wurden mit dem Topic Interest–Fragebogen und dem NASA-TLX gemessen. Das Statistik-Paket für die Sozialwissenschaften (SPSS) wurde verwendet, um die Hypothesen an den gesammelten Daten zu prüfen. Die Hypothesenprüfung erfolgte mittels quantitativ statistischer Auswertungsverfahren (Korrelation, Varianzanalyse). (DIPF/Orig.

A knowledge-based framework to facilitate E-training implementation

Dissertação para obtenção do Grau de Mestre em Engenharia Eletrotécnica e de ComputadoresNowadays, there is an evident increase of the custom-made products or solutions demands with the objective to better fits to customer needs and profiles. Aligned with this, research in e-learning domain is focused in developing systems able to dynamically readjust their contents to respond to learners’ profiles demands. On the other hand, there is also an increase of e-learning developers which even not being from pedagogical curricula, as research engineers, needs to prepare e-learning programmes about their prototypes or products developed. This thesis presents a knowledge-based framework with the purpose to support the creation of e-learning materials, which would be easily adapted for an effective generation of custom-made e-learning courses or programmes. It embraces solutions for knowledge management, namely extraction from text & formalization and methodologies for collaborative e-learning courses development, where main objective is to enable multiple organizations to actively participate on its production. This also pursues the challenge of promoting the development of competencies, which would result from an efficient knowledge-transfer from research to industry

On Evidence-based Risk Management in Requirements Engineering

Background: The sensitivity of Requirements Engineering (RE) to the context makes it difficult to efficiently control problems therein, thus, hampering an effective risk management devoted to allow for early corrective or even preventive measures. Problem: There is still little empirical knowledge about context-specific RE phenomena which would be necessary for an effective context- sensitive risk management in RE. Goal: We propose and validate an evidence-based approach to assess risks in RE using cross-company data about problems, causes and effects. Research Method: We use survey data from 228 companies and build a probabilistic network that supports the forecast of context-specific RE phenomena. We implement this approach using spreadsheets to support a light-weight risk assessment. Results: Our results from an initial validation in 6 companies strengthen our confidence that the approach increases the awareness for individual risk factors in RE, and the feedback further allows for disseminating our approach into practice.Comment: 20 pages, submitted to 10th Software Quality Days conference, 201