Review: Audio anecdotes: tools, tips and techniques for digital audio

Audio Anecdotes is the first in a series of three books covering creating, recording, processing, and analyzing sound and music, also touching on the opportunities presented by digital media and computing. This first book divides into eight chapters and twenty-five essays addressing measurement, perception, recording, synthesis, signal processing, computer techniques, computer tools, and human experience. Co-editor Ken Greenebaum notes that after being frustrated and disappointed with the lack of resources available to understand digital (and previously analog) media, his intention was “to create the book I wished for then and that I still want today” (p. xi). The editors note that “articles take a variety of forms: introductions, essays, in-depth technical explorations, presentations of tools and techniques, and post-mortem analysis” (p. xiv). With the variety of authors that have contributed, particularly those coming from beyond the academy and those drawing on personal experience, readers are encouraged to learn about the contributors’ backgrounds before reading each section

Synthesis of Minimal Error Control Software

Software implementations of controllers for physical systems are at the core of many embedded systems. The design of controllers uses the theory of dynamical systems to construct a mathematical control law that ensures that the controlled system has certain properties, such as asymptotic convergence to an equilibrium point, while optimizing some performance criteria. However, owing to quantization errors arising from the use of fixed-point arithmetic, the implementation of this control law can only guarantee practical stability: under the actions of the implementation, the trajectories of the controlled system converge to a bounded set around the equilibrium point, and the size of the bounded set is proportional to the error in the implementation. The problem of verifying whether a controller implementation achieves practical stability for a given bounded set has been studied before. In this paper, we change the emphasis from verification to automatic synthesis. Using synthesis, the need for formal verification can be considerably reduced thereby reducing the design time as well as design cost of embedded control software. We give a methodology and a tool to synthesize embedded control software that is Pareto optimal w.r.t. both performance criteria and practical stability regions. Our technique is a combination of static analysis to estimate quantization errors for specific controller implementations and stochastic local search over the space of possible controllers using particle swarm optimization. The effectiveness of our technique is illustrated using examples of various standard control systems: in most examples, we achieve controllers with close LQR-LQG performance but with implementation errors, hence regions of practical stability, several times as small.Comment: 18 pages, 2 figure

The digital code driven autonomous synthesis of ibuprofen automated in a 3D-printer-based robot

An automated synthesis robot was constructed by modifying an open source 3D printing platform. The resulting automated system was used to 3D print reaction vessels (reactionware) of differing internal volumes using polypropylene feedstock via a fused deposition modeling 3D printing approach and subsequently make use of these fabricated vessels to synthesize the nonsteroidal anti-inflammatory drug ibuprofen via a consecutive one-pot three-step approach. The synthesis of ibuprofen could be achieved on different scales simply by adjusting the parameters in the robot control software. The software for controlling the synthesis robot was written in the python programming language and hard-coded for the synthesis of ibuprofen by the method described, opening possibilities for the sharing of validated synthetic ‘programs’ which can run on similar low cost, user-constructed robotic platforms towards an ‘open-source’ regime in the area of chemical synthesis

A zero-cost, real-time, Windows signal laboratory

This paper introduces a Windows-based signal capture, display, and waveform synthesis package called “Win-eLab”. The software is able to run on a conventional desktop or laptop with no additional hardware, and can perform real-time Fourier analysis on audio-frequency signals. This paper is intended as an introduction to Win-eLab, aimed at motivating further use of it in both teaching and self-directed learning contexts. The use of the software to familiarize students with the concept of “laboratory” instrumentation is discussed, as well as the usefulness of a simultaneous time-domain/frequency-domain display for understanding signals, particularly in signal processing and communications systems courses. It is anticipated that applications may extend beyond electrical & electronic engineering – for example, as an aid to understanding mechanical vibrations, acoustics, and in other discipline areas

A software tool for simulating practical chemistry

A software package has been written to allow a user to build and manipulate a simple chemistry experiment. Using a toolbox of equipment the apparatus can be interactively designed and the necessary chemicals added from a database. Selection of the appropriate physical and reaction conditions allows the experiment to be run both in real and virtual time, snapshots of the experiment being stored for subsequent modification and replay. The structure of the reaction data file allows any reaction to be designed with yields and both forward and backward reaction rates. Thus, the user has the opportunity to experiment with the best apparatus layout, reactant composition and physical conditions in order to achieve an optimal result. Some extensions of the current software are discussed

Synthesis of Attributed Feature Models From Product Descriptions: Foundations

Feature modeling is a widely used formalism to characterize a set of products (also called configurations). As a manual elaboration is a long and arduous task, numerous techniques have been proposed to reverse engineer feature models from various kinds of artefacts. But none of them synthesize feature attributes (or constraints over attributes) despite the practical relevance of attributes for documenting the different values across a range of products. In this report, we develop an algorithm for synthesizing attributed feature models given a set of product descriptions. We present sound, complete, and parametrizable techniques for computing all possible hierarchies, feature groups, placements of feature attributes, domain values, and constraints. We perform a complexity analysis w.r.t. number of features, attributes, configurations, and domain size. We also evaluate the scalability of our synthesis procedure using randomized configuration matrices. This report is a first step that aims to describe the foundations for synthesizing attributed feature models