Religious/secular discourses and practices of good sex

This article focuses on the triangulation of sexuality, religion and secularity in Dutch society by analysing two contemporary case studies. We focus on sexual experiences and practices rather than sexual identities to further understand the constructions of what constitutes 'good' sex. The empirical research is situated in the Netherlands, where the binary of religion and sexual regulation versus secularity and sexual freedom has been dominant in both public and political discourse for a long time. Exploring sexual practices and narratives as central to the constitution of both religious and secular selves, we noted these to be fluctuating, inconsistent and subject to discourses. Our first case study discusses sexual experiences of non-heterosexual Protestant women, whereas the second explores the frequently considered 'neutral' notions of secularity in sexual education. Applying insights from both religious studies and queer studies, we bring the empirical study of sexuality together with the theoretical debates about the conceptualisation of the secular and the religious in contemporary Western Europe.This comparative approach to sexuality not only undermines the culturally presumed exclusive opposition of the secular and the religious but it also provides new empirical contributions for understanding the interactions between sexual practices and sexual discourses

In their own words: using text analysis to identify musicologists' attitudes towards technology

A widely distributed online survey gathered quantitative and qualitative data relating to the use of technology in the research practices of musicologists. This survey builds on existing work in the digital humanities and provides insights into the specific nature of musicology in relation to use and perceptions of technology. Analysis of the data (n=621) notes the preferences in resource format and the digital skills of the survey participants. The themes of comments on rewards, benefits, frustrations, risks, and limitations are explored using an h-point approach derived from applied linguistics. It is suggested that the research practices of musicologists reflect wider existing research into the digital humanities, and that efforts should be made into supporting development of their digital skills and providing usable, useful and reliable software created with a ‘musicology-centred’ design approach. This software should support online access to high quality digital resources (image, text, sound) which are comprehensive and discoverable, and can be shared, reused and manipulated at a micro- and macro level

Comment on Huron and Veltman: Does a Cognitive Approach to Medieval Mode Make Sense?

This commentary examines Huron and Veltman’s article from the perspective of historical musicology. The following issues are discussed: • The authors regard modes as conceptual categories of the medieval listener, which seems unlikely on historical and theoretical grounds. • Pitch class profiles are not a good way of capturing the melodic nature of the modes. • The diatonic rather than the chromatic scale should be employed as the reference pitch system for the modes. • The tentative explanation of the transition from modality to tonality ignores the fundamental differences between modes and keys, and the role of polyphony in this supposed transition. The article’s methodology, to apply quantitative methods to problems of historical musicology, is fundamentally sound, and suggestions are made in this commentary as to how its shortcomings can be amended by reformulating research questions and redesigning methods

Hooked on Music Information Retrieval

This article provides a reply to 'Lure(d) into listening: The potential of cognition-based music information retrieval,' in which Henkjan Honing discusses the potential impact of his proposed Listen, Lure & Locate project on Music Information Retrieval (MIR). Honing presents some critical remarks on data-oriented approaches in MIR, which we endorse. To place these remarks in context, we first give a brief overview of the state of the art of MIR research. Then we present a series of arguments that show why purely data-oriented approaches are unlikely to take MIR research and applications to a more advanced level. Next, we propose our view on MIR research, in which the modelling of musical knowledge has a central role. Finally, we elaborate on the ideas in Honing's paper from a MIR perspective in this paper and propose some additions to the Listen, Lure & Locate project

Opponent modelling in the game of tron using reinforcement learning

In this paper we propose the use of vision grids as state representation to learn to play the game Tron using neural networks and reinforcement learning. This approach speeds up learning by significantly reducing the number of unique states. Furthermore, we introduce a novel opponent modelling technique, which is used to predict the opponent’s next move. The learned model of the opponent is subsequently used in Monte-Carlo roll-outs, in which the game is simulated n-steps ahead in order to determine the expected value of conducting a certain action. Finally, we compare the performance using two different activation functions in the multi-layer perceptron, namely the sigmoid and exponential linear unit (Elu). The results show that the Elu activation function outperforms the sigmoid activation function in most cases. Furthermore, vision grids significantly increase learning speed and in most cases this also increases the agent’s performance compared to when the full grid is used as state representation. Finally, the opponent modelling technique allows the agent to learn a predictive model of the opponent’s actions, which in combination with Monte-Carlo roll-outs significantly increases the agent’s performance

Sampled Policy Gradient for Learning to Play the Game Agar.io

In this paper, a new offline actor-critic learning algorithm is introduced: Sampled Policy Gradient (SPG). SPG samples in the action space to calculate an approximated policy gradient by using the critic to evaluate the samples. This sampling allows SPG to search the action-Q-value space more globally than deterministic policy gradient (DPG), enabling it to theoretically avoid more local optima. SPG is compared to Q-learning and the actor-critic algorithms CACLA and DPG in a pellet collection task and a self play environment in the game Agar.io. The online game Agar.io has become massively popular on the internet due to intuitive game design and the ability to instantly compete against players around the world. From the point of view of artificial intelligence this game is also very intriguing: The game has a continuous input and action space and allows to have diverse agents with complex strategies compete against each other. The experimental results show that Q-Learning and CACLA outperform a pre-programmed greedy bot in the pellet collection task, but all algorithms fail to outperform this bot in a fighting scenario. The SPG algorithm is analyzed to have great extendability through offline exploration and it matches DPG in performance even in its basic form without extensive sampling

Towards Automated Processing of Folk Song Recordings

Folk music is closely related to the musical culture of a specific nation or region. Even though folk songs have been passed down mainly by oral tradition, most musicologists study the relation between folk songs on the basis of symbolic music descriptions, which are obtained by transcribing recorded tunes into a score-like representation. Due to the complexity of audio recordings, once having the transcriptions, the original recorded tunes are often no longer used in the actual folk song research even though they still may contain valuable information. In this paper, we present various techniques for making audio recordings more easily accessible for music researchers. In particular, we show how one can use synchronization techniques to automatically segment and annotate the recorded songs. The processed audio recordings can then be made accessible along with a symbolic transcript by means of suitable visualization, searching, and navigation interfaces to assist folk song researchers to conduct large scale investigations comprising the audio material