Marcio Guedes Correa, Gabrielle Delorence Di Santo
Este estudo bibliográfico pretende estabelecer um panorama sobre as práticas utilizadas na música adaptativa para trilhas sonoras de videogames. A música adaptativa, diferentemente das trilhas sonoras-musicais estáticas tradicionais, ajusta-se em tempo real para refletir os eventos, os ambientes e as ações do jogador no jogo, criando uma experiência auditiva personalizada. Os principais métodos discutidos incluem re-sequenciamento horizontal, camadas verticais e mixagem dinâmica, cada um permitindo transições perfeitas e variações de tom, ritmo e harmonia. Essas técnicas são complementadas por processos algorítmicos para adaptar elementos musicais, como andamento, timbre e leitmotivs, a diversos cenários de jogo. A abordagem teórica enfatiza a interação entre o áudio diegético e não diegético, bem como a integração do design centrado no usuário para garantir a interação intuitiva entre a música e a mecânica do jogo. O trabalho também aborda os desafios para alcançar a coerência em narrativas não lineares, mostrando como as estratégias adaptativas contribuem para a profundidade emocional e o alinhamento narrativo.
Elaheh Azadi Marand, Amir Sheikhahmadi, Moharram Challenger
et al.
Recommender systems (RSs) are fundamental tools that address data redundancy and serve as intelligent supplements for tasks such as data retrieval and refinement by analyzing user behavior. Nowadays, RSs are utilized in various domains, ranging from filtering web news based on user preferences to recommending movies, music, books, and articles in e-commerce. Additionally, these systems are extensively employed to facilitate software engineering activities, including modeling. Modeling environments are enriched with RSs that assist in building models by providing recommendations based on previous solutions to similar problems within the same domain. Consequently, there is growing research interest in approaches that aid the modeling process. This paper presents a systematic literature review (SLR) that analyzes how recommender systems techniques are used to suggest UML diagrams, as well as the role of UML diagrams in describing recommender systems. In addition, it discusses methods for evaluating primary studies, the challenges that primary studies have addressed, and the domains of study that primary studies have targeted (based on an analysis of 4789 papers). We believe this study will guide researchers and professionals in identifying recommender system techniques for generating UML diagram suggestions and understanding the overall purpose of using UML diagrams. Furthermore, it may contribute to a broader understanding of the research process and inspire future research on recommender system techniques within other modeling languages. The results show that 45% of the studies use content-based techniques to suggest UML diagrams, with 77% of the recommendations being structural diagrams (such as class diagrams). On the other hand, to design the components of the proposed approaches (recommender systems), behavioral diagrams are generally used (53% on average), focusing on knowledge-based techniques (28% on average). Finally, the study shows that researchers use content-based (38%) and knowledge-based (41%) techniques to recommend design models. The analysis revealed that the following challenges were identified: 19 studies dealt with the cold start problem, 20 studies with sparsity issues, 11 studies with scalability concerns, 3 studies with diversity challenges, and 12 studies with other types of challenges.
The article presents a hitherto unknown letter of Paul Siefert, written in Amsterdam in December 1608. Based on its contents and other source documentation, a timeline of Siefert’s activities up to 1611 has been detailed, including the events surrounding the competition for the post of organist of St. Mary’s Church in Gdańsk. The study concludes with hypotheses concerning the composer’s education before 1607.
SF Luthfie Arguby Purnomo, SF Lukfianka Sanjaya Purnama, Robith Khoiril Umam
et al.
In Indonesia, to strengthen the memorization and comprehension of holy Qur’anic verses among youth, short verses are often adapted into senandung (chanting). This phenomenon is of academic urgency to study as it involves issues of preserving the accuracy and sacredness of the transadapted verses while simultaneously lyricizing them into songs. We argue that this specific transadaptation deserves a new term as a point of departure. We called it transnuancing, a portmanteau of translation and nuancing. To support the claim, we formulated the research questions: 1) what is transnuancing? 2) what are the characteristics of transnuancing? To address the questions, we employed the theories of transadaptation by Purnomo et al. (2022), musical nuance by Roholt (2014), sonic theology by Beck (2021), Maclean, Bryant, and Bradley (1987), and paraphrasing by Gorleé (2005) with analysis techniques by Spradley (2016) in a qualitative design context. Theoretical triangulation was implemented to ensure the data’s validity. The findings indicate that to preserve the accuracy and sacredness of the transadapted verses in Javanese and Indonesian, the translators pay close attention to the nuances of the translation. We classified the nuancing into semantic, aesthetic, and contextual nuancing. Through semantic nuancing, the translation is taken from official translations of the Qur’an. Through aesthetic nuancing, background music or a genre considered solemn was selected to accompany the translation. Through contextual nuancing, the context surrounding the translation was considered. Future studies could investigate the parameterization of the nuancing to determine their numerical weights by involving audience receptions. Through this parameterization process, assessment rubrics that include nuancing as one of the elements could be designed.
Abstract Endowing flexible and adaptable fiber devices with light-emitting capabilities has the potential to revolutionize the current design philosophy of intelligent, wearable interactive devices. However, significant challenges remain in developing fiber devices when it comes to achieving uniform and customizable light effects while utilizing lightweight hardware. Here, we introduce a mass-produced, wearable, and interactive photochromic fiber that provides uniform multicolored light control. We designed independent waveguides inside the fiber to maintain total internal reflection of light as it traverses the fiber. The impact of excessive light leakage on the overall illuminance can be reduced by utilizing the saturable absorption effect of fluorescent materials to ensure light emission uniformity along the transmission direction. In addition, we coupled various fluorescent composite materials inside the fiber to achieve artificially controllable spectral radiation of multiple color systems in a single fiber. We prepared fibers on mass-produced kilometer-long using the thermal drawing method. The fibers can be directly integrated into daily wearable devices or clothing in various patterns and combined with other signal input components to control and display patterns as needed. This work provides a new perspective and inspiration to the existing field of fiber display interaction, paving the way for future human–machine integration.
Priya Silverstein, Colin Elman, Amanda Montoya
et al.
Abstract Journal editors have a large amount of power to advance open science in their respective fields by incentivising and mandating open policies and practices at their journals. The Data PASS Journal Editors Discussion Interface (JEDI, an online community for social science journal editors: www.dpjedi.org ) has collated several resources on embedding open science in journal editing ( www.dpjedi.org/resources ). However, it can be overwhelming as an editor new to open science practices to know where to start. For this reason, we created a guide for journal editors on how to get started with open science. The guide outlines steps that editors can take to implement open policies and practices within their journal, and goes through the what, why, how, and worries of each policy and practice. This manuscript introduces and summarizes the guide (full guide: https://doi.org/10.31219/osf.io/hstcx ).
A well agreed discourse in music perception research is that affective response can be generated by music when a tendency in the music is delayed or inhibited. There is a consensus that this tendency is statistically driven, derived from exposure to culturally situated musical idioms. By presenting a neural-network inspired spreading activation model (SAM) this paper argues that the nature of the tendency is worthy of further investigation. SAM organises the music stream perceived by the listener continuously into segments such that a match with an existing ‘mental representation’ (node) is found, which is then linked to the node for the previously segmented part of the music stream, with the link between these nodes strengthening and consolidating with exposure. The currently activated segment (the music being sounded) will prime the best matching (strongest linked) node available, generating expectancy. Expectancy is defined as the most strongly primed segment, and emerges dynamically through experience with environmental and musical contexts, rather than schematic or prototypical means. Expectancy is the specific exemplar instance that the activated (currently sounding) segment of music and contextual factors prime. This hypothesis of veridical dominance has implications for enduring aspects of music expectancy theory: (1) individual experiences matter in the formation of expectations; (2) expectations are a dynamic process, that change and are updated with experience; (3) context plays a critical role in expectancy; and (4) schema, prototypes and statistical accounts of expectation should be treated as convenient approximations of underlying cognitive processes.
BackgroundThe recent COVID-19 pandemic has contributed to the emergence of several technologies for infectious disease management. Although much focus has been placed on contact-tracing apps, another promising new tactic is proximity tracing, which focuses on health-related behavior and can be used for primary prevention. Underpinned by theories on behavioral design, a proximity-detection system can be devised that provides a user with immediate nudges to maintain physical distance from others. However, the practical feasibility of proximity detection during an infectious disease outbreak has not been sufficiently investigated.
ObjectiveWe aimed to evaluate the feasibility of using a wearable device to nudge for distance and to gather important insights about how functionality and interaction are experienced by users. The results of this study can guide future research and design efforts in this emerging technology.
MethodsIn this retrospective case study, a wearable proximity-detection technology was used in a workplace for 6 weeks during the production of a music competition. The purpose of the technology was to nudge users to maintain their physical distance using auditory feedback. We used a mixed methods sequential approach, including interviews (n=8) and a survey (n=30), to compile the experiences of using wearable technology in a real-life setting.
ResultsWe generated themes from qualitative analysis based on data from interviews and open-text survey responses. The quantitative data were subsequently integrated into these themes: feasibility (implementation and acceptance—establishing a shared problem; distance tags in context—strategy, environment, and activities; understanding and learning; and accomplishing the purpose) and design aspects (a purposefully annoying device; timing, tone, and proximity; and additional functions).
ConclusionsThis empirical study reports on the feasibility of using wearable technology based on proximity detection to nudge individuals to maintain physical distance in the workplace. The technology supports attention to distance, but the usability of this approach is dependent on the context and situation. In certain situations, the audio signal is frustrating, but most users agree that it needs to be annoying to ensure sufficient behavioral adaption. We proposed a dual nudge that involves vibration followed by sound. There are indications that the technology also facilitates learning how to maintain a greater distance from others, and that this behavior can persist beyond the context of technology use. This study demonstrates that the key value of this technology is that it places the user in control and enables immediate action when the distance to others is not maintained. This study provides insights into the emerging field of personal and wearable technologies used for primary prevention during infectious disease outbreaks. Future research is needed to evaluate the preventive effect on transmission and investigate behavioral changes in detail and in relation to different forms of feedback.
Guitar Textural Analysis is an analytical proposal devised for the composition for the guitar that exposes the relations between the textural structure and the technical procedures used in the instrumental performance. The Guitar Textural Proposals (GTPs) are the specific configurations extracted in this analytical process. In the present work, the focus remains on recognizing parsimonious movements between GTPs, that is, minimal distinctions between patterns of use of the instrument combined with respective textural configurations. Parsimoniousness is defined in the context of Developing Variation, Neo-Riemannian Theory, and Partitional Analysis. Previous works by Fabio Adour and authors Sérgio Freire and Pedro Cambraia present perspectives on the relation between texture and guitar performance. Leo Brouwer’s series of progressive pieces Études Simples is adopted as a reference. The work results in a proposal for a ordered network of technical-textural configurations connected by parsimonious relations.
<h4>Relevance</h4>Popularity-based approaches are widely adopted in music recommendation systems, both in industry and research. These approaches recommend to the target user what is currently popular among all users of the system. However, as the popularity distribution of music items typically is a long-tail distribution, popularity-based approaches to music recommendation fall short in satisfying listeners that have specialized music preferences far away from the global music mainstream. Addressing this gap, the contribution of this article is three-fold.<h4>Definition of mainstreaminess measures</h4>First, we provide several quantitative measures describing the proximity of a user's music preference to the music mainstream. Assuming that there is a difference between the global music mainstream and a country-specific one, we define the measures at two levels: relating a listener's music preferences to the global music preferences of all users, or relating them to music preferences of the user's country. To quantify such music preferences, we define a music item's popularity in terms of artist playcounts (APC) and artist listener counts (ALC). Moreover, we adopt a distribution-based and a rank-based approach as means to decrease bias towards the head of the long-tail distribution. This eventually results in a framework of 6 measures to quantify music mainstream.<h4>Differences between countries with respect to music mainstream</h4>Second, we perform in-depth quantitative and qualitative studies of music mainstream in that we (i) analyze differences between countries in terms of their level of mainstreaminess, (ii) uncover both positive and negative outliers (substantially higher and lower country-specific popularity, respectively, compared to the global mainstream), analyzing these with a mixed-methods approach, and (iii) investigate differences between countries in terms of listening preferences related to popular music artists. We conduct our studies and experiments using the standardized LFM-1b dataset, from which we analyze about 800,000,000 listening events shared by about 53,000 users (from 47 countries) of the music streaming platform Last.fm. We show that there are substantial country-specific differences in listeners' music consumption behavior with respect to the most popular artists listened to.<h4>Rating prediction experiments</h4>Third, we demonstrate the applicability of our study results to improve music recommendation systems. To this end, we conduct rating prediction experiments in which we tailor recommendations to a user's level of preference for the music mainstream using the proposed 6 mainstreaminess measures: defined by a distribution-based or rank-based approach, defined on a global level or on a country level (for the user's country), and for APC or ALC. Our approach roughly equals a hybrid recommendation approach in which a demographic filtering strategy is implemented before collaborative filtering is performed. Results suggest that, in terms of rating prediction accuracy, each of the presented mainstreaminess definitions has its merits.
The article reflects on the representational character of sound recording and on a particular use ethnomusicologists make of it. By means of the revision of bibliography generated in different disciplines and of the criticism of a series of preconceptions, a definition of sound recording is outlined, which relates it to the scientific, aesthetic, ideological and technological forces that govern the generation of other types of documents and the production of knowledge in general. Also, the conditioning role the Archive institution has in the creation, storage-classification, study and edition of sound recording is highlighted.