Integrating transformers with graph representation learning has emerged as a research focal point. However, recent studies showed that positional encoding in Transformers does not capture enough structural information...
详细信息
Popularized by Arnold Schoenberg in the mid-20th century, the method of twelve-tone composition produces musical compositions based on one or more orderings of the equal-tempered chromatic scale. The work of twelve-to...
详细信息
Recycling obsolete electronic devices (E-waste) is a dangerous task for human workers. Automated E-waste recycling is an area of great interest but challenging for current robotic applications. We focus on the problem...
详细信息
Driven by technological advancements in generative AI and the shortage of data professionals in the European labour market, a growing interest in data science education has led to the development of numerous data scie...
详细信息
ISBN:
(数字)9798331539498
ISBN:
(纸本)9798331539504
Driven by technological advancements in generative AI and the shortage of data professionals in the European labour market, a growing interest in data science education has led to the development of numerous data science curricula. However, a standardized competency framework for data scientists has not yet been established. Moreover, data scientists have shifted from a generalist approach to focusing on specialised roles within the data ecosystem. As a result, data science curricula have become more specialised, often including a comprehensive introductory phase followed by in-depth studies in specific areas. However, many students struggle to combine the diverse competencies and knowledge elements a data science degree teaches. To address this challenge, this research project focuses on developing a data science framework that identifies interdependencies between competencies and knowledge elements, enabling students to choose personalized learning paths based on their individual goals and prior knowledge. This paper introduces a competency network to create personalized learning paths for an introductory data science course. It will be based on professionally logical interdependencies, which will be evaluated and optimised through the analysis of expert interviews. The goal is to positively impact students' self-efficacy, motivation, and learning outcomes by providing a structured and adaptable learning experience.
Argumentation Frameworks (AFs) are used, in the field of Artificial Intelligence, to evaluate the justification state of conflicting information, thus allowing the development of automatic reasoning techniques and sys...
详细信息
In this paper, an asymmetrical novel 4D system with a bounded function of exponential form, which can exhibit chaotic and hyperchoatic behaviors has been proposed. By calculating Lyapunov exponents and bifurcation dia...
详细信息
The paper proposes a time-fractional modified model of thermal wave propagation in ferroelectrics. To solve the initial-boundary value problem for a partial differential equation numerically, an implicit computational...
详细信息
In this work we propose a formal system for fuzzy algebraic reasoning. The sequent calculus we define is based on two kinds of propositions, capturing equality and existence of terms as members of a fuzzy set. We prov...
详细信息
Social assistive robots enhance social interaction and well-being by providing companionship and support. Emotional Intelligence in these robots refers to their ability to identify, understand, and respond to human em...
详细信息
Gaussian processes (GPs) serve as powerful surrogate models in optimisation by providing a flexible data-driven framework for representing complex fitness landscapes. We provide an analysis of realisations drawn from ...
详细信息
暂无评论