The Sound Monad: A Philosophical Perspective on Sound Design

Abstract This article aims at sketching a philosophical theory of sound based on the perspective of sound designers: unique agents blurring the boundaries between engineering, music, acoustics and sound-based art. After having introduced the general framing in Section 1, focusing on a short history of the theory and practice of sound design, in Section 2 we propose a reading of sound as monad. We derive such intuition from the technology of digital sampling of audio signals, based on the decomposition of complex sound waves in a number of elementary sinusoidal waves. Thus, in Section 3, we attempt at grounding the resulting "sound-atom" on Leibniz's notion of monad, intended both as a "simple substance without parts" and as a "nucleus of forces in statu possibilitatis." The insight is resumed and further discussed in Section 4, where we draw our conclusions by demonstrating the fitness of such framing with regards to the standpoint of sound design, while accounting for the work of sound artists Carsten Nicolai and Ryoji Ikeda

A snapshot of the city: cultural transfer through a language learning app

This paper describes how a web app could be useful to promote cultural transfer and incidental learning of Italian as a Second Language (L2) on the university campus of Forlì (University of Bologna). The app, named Forliviamo, aims to present and promote the city of Forlì and the local culture to international students and tourists and, at the same time, to support them through the incidental learning of Italian. After giving an overall description of the app, it will be explained how cultural identity is transmitted in terms of both promoting local gastronomy, traditional events, iconic places of the city and fostering the incidental learning of Italian. Special attention will be paid to the strategies adopted to facilitate the users' approach to language and culture

Interaction in an asynchronous online course:a synthesis of quantitative predictors

The effectiveness and potential of asynchronous online courses hinge on sustained, purposeful interaction. And while many factors affecting interaction have been uncovered by prior literature, there are few accounts of the relative importance of these factors when studied in the same online course. In this paper, we develop a literature-informed model of six predictors on the likelihood that a note receives a reply. We corroborate earlier findings (such as the impact of the date that the note was posted), but also obtain one contradictory result (that reading ease does not appear to be a significant predictor). We offer hypotheses for our findings, suggest future directions for this type of research, and offer educational implications

When learning Italian as a Second Language, tourism and technology go hand in hand

[EN] This paper aims to describe the development of CALL-ER, an application for mobile devices, produced within the CALL-ER project (Context-Aware Language Learning in Emilia Romagna). An ever-increasing availability of applications for language learning that meet the different learning needs of users, as well as the ubiquitous wireless communication, led applications for mobile devices to become gradually more context-aware. This means that language is acquired by users through the direct experience with the local context where they are. An example in this regard is represented by the CALL-ER mobile application, that supports mobility students through the incidental learning of Italian language and culture in the city of Forlì. We will begin this contribution with an outline of the theoretical underpinnings that supported the project and a presentation of the project itself. We will then present the first stage of the project, during which the application was developed before its first testing. At this point, an overall description of the application will be given. A special attention will be paid throughout this paper both to how language learning has been conceived through experiential tourism and to the multimodality of the contents.Cervini, C.; Zingaro, A. (2021). When learning Italian as a Second Language, tourism and technology go hand in hand. En 7th International Conference on Higher Education Advances (HEAd'21). Editorial Universitat Politècnica de València. 341-349. https://doi.org/10.4995/HEAd21.2021.12961OCS34134

Discontinuous Galerkin finite element investigation on the fully-compressible Navier–Stokes equations for microscale shock-channels

Microfluidics is a multidisciplinary area founding applications in several fields such as the aerospace industry. Microelectromechanical systems (MEMS) are mainly adopted for flow control, micropower generation and for life support and environmental control for space applications. Microflows are modeled relying on both a continuum and molecular approach. In this paper, the compressible Navier–Stokes (CNS) equations have been adopted to solve a two-dimensional unsteady flow for a viscous micro shock-channel problem. In microflows context, as for the most gas dynamics applications, the CNS equations are usually discretized in space using finite volume method (FVM). In the present paper, the PDEs are discretized with the nodal discontinuous Galerkin finite element method (DG–FEM) in order to understand how the method performs at microscale level for compressible flows. Validation is performed through a benchmark test problem for microscale applications. The error norms, order of accuracy and computational cost are investigated in a grid refinement study, showing a good agreement and increasing accuracy with reference data as the mesh is refined. The effects of different explicit Runge–Kutta schemes and of different time step sizes have also been studied. We found that the choice of the temporal scheme does not really affect the accuracy of the numerical results

Student Low Achievement Prediction

In this paper, we propose a method for assessing the risk of low achievement in primary and secondary school. We train three machine learning models with data collected by the Italian Ministry of Education through the INVALSI large-scale assessment tests. We compare the results of the trained models and evaluate the effectiveness of the solutions in terms of performance and interpretability. We test our methods on data collected in end-of-primary school mathematics tests to predict the risk of low achievement at the end of compulsory schooling (5 years later). The promising results of our approach suggest that it is possible to generalise the methodology for other school systems and for different teaching subject

Low-achievement risk assessment with machine learning

In this work, we propose a method for assessing the risk of low-achievement in secondary school with data collected from the Italian ministry of education. Low-achievement is a phenomenon whereby a student, despite completing his or her education, does not reach the level of competence expected by the school system. We train three machine learning models on a large, real dataset through the INVALSI large-scale assessment tests and compare the results in terms of predictive and descriptive performance. We exploit data collected in end-of-primary school mathematics tests to predict the risk of low-achievement at the end of compulsory schooling (5 years later). The promising results of our approach suggest that it is possible to generalise the methodology for other school systems and for different teaching subjects

Multimodal Side-Tuning for Document Classification

In this paper, we propose to exploit the side-tuning framework for multimodal document classification. Side-tuning is a methodology for network adaptation recently introduced to solve some of the problems related to previous approaches. Thanks to this technique it is actually possible to overcome model rigidity and catastrophic forgetting of transfer learning by fine-tuning. The proposed solution uses off-the-shelf deep learning architectures leveraging the side-tuning framework to combine a base model with a tandem of two side networks. We show that side-tuning can be successfully employed also when different data sources are considered, e.g. text and images in document classification. The experimental results show that this approach pushes further the limit for document classification accuracy with respect to the state of the art.Comment: 2020 25th International Conference on Pattern Recognition (ICPR