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The article takes Boethius’s theory of musical harmony as a starting point, in particular studying the collective dimension embedded in this concept. The dynamics of contact and interdetermination, between humans and other-than-human, are explored and understood as factors co-involved in the possibility of common living. The role of the notions of ecology and economy in rereading the concept of harmony provided by Boethius’s theory is also reviewed. The text then explores a site-specific work that experiments with these issues through the creation of an acousmatic patch that is superimposed onto a broken ecology, showing how this serves as an agent for a reharmonisation of a drought-ravaged river. The article concludes by addressing the implications that a territorially situated musical approach might represent for recovery of the broken link between humans and the other-than-human.
Machine listening takes place through sonification. Sound is treated as data by a computer that listens by deconstructing and reconstructing sound. To better explore the aesthetic, relational and ontological aspects of machine listening, this article reflects upon the Fourier analysis, which is vital for machine learning algorithms. It then outlines the listening modes articulated by French composer Pierre Schaeffer and updates them for the new material conditions of contemporary listening. It proposes that a new mode, identified while working with sonification, be added to Schaeffer’s classic array. It explores non-human listening among machines that listen with other concerns beyond the human need to interpret content. Thus, this article makes a particular strategic move: it centres around machine listening, which enables computers to perform analyses of a soundscape, and resynthesis, a mode of sonification that treats sound as data, to reintroduce the ‘sound object’ nature of resynthesised sounds. It looks at sonification through discourse analysis and media archaeology, and gives importance to experiments in art that privilege sensorial and affective dimensions often ignored by scientific approaches. It proposes that thinking about machine listening through sonification can assist in developing sensibilities that are more responsive to the present sonic ecologies between human and non-human listeners.
While mathematics and technologic systems have been intrinsically developed with purposes of representing and computing problems with a human-centric orientation, they nonetheless can be considered to have non-human agency. Drawing on anthropology and architecture studies, this article argues that the human-based logics underpinning mathematics and technologies does not delimit them as human entities, and that they can exhibit influential capacities when engaged with during processes of artistic making. This idea is demonstrated through the development of a visitor-interactive audiovisual artwork. The software environments IanniX and Max were actants in the experimental process of sonifying hyperbolic paraboloid (hypar) planes, as well as the mathematic equations themselves. This article discusses how mathematic and technologic agency affected the development of three hypar models used in the piece, as well as an initial unused version. It also discusses how hardware interface objects influenced human-computer interaction design. The article will interest scholars of technologic agency and practitioners interested in converting three-dimensional planes into sound or creating interactive exhibition technology.
This article presents the concept of a ‘haptic aurality’ in soundscape composition, an aesthetic and perceptual model derived from visual art theory, media studies and phenomenology that extends the haptic beyond its common association to vibroacoustic phenomena in the sonic arts. Included in this framework are both the standard haptic arguments, from psychology and engineering, including notions of kinaesthesia and proprioception, and varied definitions of the haptic as a not necessarily tactile mode of knowing touch that involves synaesthesia, transmodal perception and philosophical notions of sensory dedifferentiation. In adapting this survey of sometimes contradictory accounts of the haptic as parameters for compositional analysis and application, the article simultaneously creates novel engagements between soundscape composition and acousmatic practice.
This article analyses the author’s modular synthesis practice through the lens of Simondonian philosophy, arguing that modular synthesis represents a dynamic example of technical ontogenesis in artistic practice. With its emphasis on technical becoming, Gilbert Simondon’s philosophy of technology provides a detailed framework for the analysis of modular synthesis patching. Following a practice-based methodology, the article references two ‘think-aloud’ videos filmed of the author patching on two modular synthesis systems. Tracing the genesis of sound sources throughout each session, aspects of Simondonian technical invention are analysed with respect to this creative practice. As these patches concretise, an increasingly saturated associated milieu is shown to emerge as the driving force behind technical invention. Seeking resolutions between incompatibilities arising between the internal milieu of a sound source and the external milieu of the modular system, the analysis reveals the appearance of metastable states within the ontogenesis of each patch. By detailing the various forms of recurrent causality in these patches, this article reveals how modular synthesis practice can serve as the site for the co-evolution of musical ideas and technical objects; a theatre of individuation that is both more-than-human in its evolutionary potential, and more-than-music in its practical application.
This article critiques the anthropocentric tendencies in machine listening practices and narratives, developing alternative concepts and methods to explore the more-than-human potential of these technologies through the framework of sonic fiction. Situating machine listening within the contemporary soundscape of dataveillance, the research examines post-anthropocentric threads that emerge at the intersection of datafication, subjectivation and animalisation. Theory and practice interweave in the composition of a music piece, The Spiral, enabling generative feedback between concept, sensation and technique. Specifically, the research investigates the figure of a mollusc bio-sensor between science fact and fable, as the (im)possible locus of musicality. This emergent methodology also offers new insights for other sound art and music practices aiming to pluralise what listening might be.
Seth Kim Cohen’s notion of non-cochlear sound art explores the idea of more-than-music, reframing sonic listening, shifting away from the aesthetic and towards the conceptual, reducing ‘the value of sonic pleasure in favor of a broader set of philosophical, social, political, and historical concerns’. While this notion holds academic and artistic merit, it does not acknowledge similar explorations in sound art within disabled and d/Deaf communities and developments within disability aesthetics. Works within the disability arts that fit into Kim-Cohen’s non-cochlear sound art were created prior to the publication of his 2009 text In the Blink of an Ear: Toward a Non-Cochlear Sound Art and have continued to develop since. This article discusses Kim-Cohen’s non-cochlear sound and asks the reader to view it alongside discussions of disability aesthetics and sound art works by Hard of Hearing (HoH) and d/Deaf artists. In doing so, it illustrates how disability art and aesthetics are inherently conceptual and sociopolitical and have not only been forgotten in discussion of non-cochlear sound art, but have also carved their own path.
Biomimicry shifts focus away from anthropocentric design approaches and encourages practitioners to develop a sensitivity to the interconnectedness of natural systems and their resultant potentiality as musical forms. Embracing the concepts of biomimicry necessitates a perspectival transformation from human authorship towards a reciprocal partnership with nature that stresses sustainable technological innovation in artistic expression. The need to solve design challenges in harmony with a broader ecological context means that biomimicry represents a new form of environmentally attuned sonic practice that is both communicative and interpretative of systems operating outside everyday human experience. This research employs the biomimetic process to unravel and respond to issues related to the development of form and structure at the locus of compositional practice. Furthermore, it utilises these insights to generate new knowledge through the activities of this practice and the novel insights apprehended through the triangulation of science, nature and music. Finally, it uses biomimicry to impact the compositional trajectory practically, extending beyond metaphor or representation, and offers a glimpse into realms that are more than music, more than human.
The global race to build the world's first quantum computer has attracted enormous investment from government and industry, and it attracts a growing pool of talent. As with many cutting-edge technologies, the optimal implementation is not yet settled. This important textbook describes four of the most advanced platforms for quantum computing: nuclear magnetic resonance, quantum optics, trapped ions, and superconducting systems. The fundamental physical concepts underpinning the practical implementation of quantum computing are reviewed, followed by a balanced analysis of the strengths and weaknesses inherent to each type of hardware. The text includes more than 80 carefully designed exercises with worked solutions available to instructors, applied problems from key scenarios, and suggestions for further reading, facilitating a practical and expansive learning experience. Suitable for senior undergraduate and graduate students in physics, engineering, and computer science, Building Quantum Computers is an invaluable resource for this emerging field.
In developing countries, a significant amount of natural gas is used for household water heating, accounting for roughly 50% of total usage. Legacy systems, typified by large water heaters, operate inefficiently by continuously maintaining a large volume of water at a constant temperature, irrespective of demand. With dwindling domestic gas reserves and rising demand, this increases dependence on expensive energy imports.
We introduce a novel Internet of Things (IoT)-inspired solution to understand and predict water usage patterns and only activate the water heater when there’s a predicted demand. This retrofit system is maintenance-free and uses a rechargeable battery powered by a thermoelectric generator (TEG), which capitalizes on the temperature difference between the heater and its environment for electricity. Our study shows a notable 70% reduction in natural gas consumption compared to traditional systems. Our solution offers a sustainable and efficient method for water heating, addressing the challenges of depleting gas reserves and rising energy costs.
We present plingo, an extension of the answer set programming (ASP) system clingo that incorporates various probabilistic reasoning modes. Plingo is based on $\textit{Lpmln}^{\pm }$, a simple variant of the probabilistic language Lpmln, which follows a weighted scheme derived from Markov logic. This choice is motivated by the fact that the main probabilistic reasoning modes can be mapped onto enumeration and optimization problems and that $\textit{Lpmln}^{\pm }$ may serve as a middle-ground formalism connecting to other probabilistic approaches. Plingo offers three alternative frontends, for Lpmln, P-log, and ProbLog. These input languages and reasoning modes are implemented by means of clingo’s multi-shot and theory-solving capabilities. In this way, the core of plingo is an implementation of $\textit{Lpmln}^{\pm }$ in terms of modern ASP technology. On top of that, plingo implements a new approximation technique based on a recent method for answer set enumeration in the order of optimality. Additionally, in this work, we introduce a novel translation from $\textit{Lpmln}^{\pm }$ to ProbLog. This leads to a new solving method in plingo where the input program is translated and a ProbLog solver is executed. Our empirical evaluation shows that the different solving approaches of plingo are complementary and that plingo performs similarly to other probabilistic reasoning systems.
Data irregularities, namely small disjuncts, class skew, imbalance, and outliers significantly affect the performance of classifiers. Another challenge posed to classifiers is when new unlabelled data have different characteristics than the training data; this change is termed as a data shift. In this paper, we focus on identifying small disjuncts and dataset shift using the supervised classifier, sequential ellipsoidal partitioning classifier (SEP-C). This method iteratively partitions the dataset into minimum-volume ellipsoids that contain points of the same label, based on the idea of Reduced Convex Hulls. By allowing an ellipsoid that contains points of one label to contain a few points of the other, such small disjuncts may be identified. Similarly, if new points are accommodated only by expanding one or more of the ellipsoids, then shifts in data can be identified. Small disjuncts are distribution-based irregularities that may be considered as being rare but more error-prone than large disjuncts. Eliminating small disjuncts by removal or pruning is seen to affect the learning of the classifier adversely. Dataset shifts have been identified using Bayesian methods, use of confidence scores, and thresholds—these require prior knowledge of the distributions or heuristics. SEP-C is agnostic of the underlying data distributions, uses a single hyperparameter, and as ellipsoidal partitions are generated, well-known statistical tests can be performed to detect shifts in data; it is also applicable as a supervised classifier when the datasets are highly skewed and imbalanced. We demonstrate the performance of SEP-C with UCI, MNIST handwritten digit image, and synthetically generated datasets.