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Digital sound synthesis has long been approached using standard digital filtering techniques. Newer synthesis strategies, however, make use of physical descriptions of musical instruments, and allow for much more realistic and complex sound production and thereby synthesis becomes a problem of simulation. This book has a special focus on time domain finite difference methods presented within an audio framework. It covers time series and difference operators, and basic tools for the construction and analysis of finite difference schemes, including frequency-domain and energy-based methods, with special attention paid to problems inherent to sound synthesis. Various basic lumped systems and excitation mechanisms are covered, followed by a look at the 1D wave equation, linear bar and string vibration, acoustic tube modelling, and linear membrane and plate vibration. Various advanced topics, such as the nonlinear vibration of strings and plates, are given an elaborate treatment. Key features: Includes a historical overview of digital sound synthesis techniques, highlighting the links between the various physical modelling methodologies. A pedagogical presentation containing over 150 problems and programming exercises, and numerous figures and diagrams, and code fragments in the MATLAB® programming language helps the reader with limited experience of numerical methods reach an understanding of this subject. Offers a complete treatment of all of the major families of musical instruments, including certain audio effects. Numerical Sound Synthesis is suitable for audio and software engineers, and researchers in digital audio, sound synthesis and more general musical acoustics. Graduate students in electrical engineering, mechanical engineering or computer science, working on the more technical side of digital audio and sound synthesis, will also find this book of interest.

\"The hidden history of the pocket calculator -- a device that ushered in modern mathematics, helped build the atomic bomb, and went with us to the moon -- and the mathematicians, designers, and inventors who brought it to life.\" -- back cover

Across the millennia, and across a range of disciplines, there has been a widespread desire to connect, or translate between, the senses in a manner that is meaningful, rather than arbitrary. Early examples were often inspired by the vivid, yet mostly idiosyncratic, crossmodal matches expressed by synaesthetes, often exploited for aesthetic purposes by writers, artists, and composers. A separate approach comes from those academic commentators who have attempted to translate between structurally similar dimensions of perceptual experience (such as pitch and colour). However, neither approach has succeeded in delivering consensually agreed crossmodal matches. As such, an alternative approach to sensory translation is needed. In this narrative historical review, focusing on the translation between audition and vision, we attempt to shed light on the topic by addressing the following three questions: (1) How is the topic of sensory translation related to synaesthesia, multisensory integration, and crossmodal associations? (2) Are there common processing mechanisms across the senses that can help to guarantee the success of sensory translation, or, rather, is mapping among the senses mediated by allegedly universal (e.g., amodal) stimulus dimensions? (3) Is the term ‘translation’ in the context of cross-sensory mappings used metaphorically or literally? Given the general mechanisms and concepts discussed throughout the review, the answers we come to regarding the nature of audio-visual translation are likely to apply to the translation between other perhaps less-frequently studied modality pairings as well.

The process by which Palaeolithic Europe was transformed from a Neanderthal-dominated region to one occupied exclusively by Homo sapiens has proven challenging to diagnose. A blurred chronology has made it difficult to determine when Neanderthals disappeared and whether modern humans overlapped with them. Italy is a crucial region because here we can identify not only Late Mousterian industries, assumed to be associated with Neanderthals, but also early Upper Palaeolithic industries linked with the appearance of early H. sapiens , such as the Uluzzian and the Aurignacian. Here, we present a chronometric dataset of 105 new determinations (74 radiocarbon and 31 luminescence ages) from four key southern Italian sites: Cavallo, Castelcivita, Cala, and Oscurusciuto. We built Bayesian-based chronometric models incorporating these results alongside the relative stratigraphic sequences at each site. The results suggest; 1) that the disappearance of Neanderthals probably pre-dated the appearance of early modern humans in the region and; 2) that there was a partial overlap in the chronology of the Uluzzian and Protoaurignacian, suggesting that these industries may have been produced by different human groups in Europe. Here, the authors present 74 radiocarbon and 31 luminescence age determinations from four sites in southern Italy. They use these data to suggest that Neanderthal disappearance in the region predated the appearance of early modern humans, a previously unclear chronology

Drawing on documentary sources and 114 interviews with market participants, this and a companion article discuss the development and use in finance of the Gaussian copula family of models, which are employed to estimate the probability distribution of losses on a pool of loans or bonds, and which were centrally involved in the credit crisis. This article, which explores how and why the Gaussian copula family developed in the way it did, employs the concept of 'evaluation culture', a set of practices, preferences and beliefs concerning how to determine the economic value of financial instruments that is shared by members of multiple organizations. We identify an evaluation culture, dominant within the derivatives departments of investment banks, which we call the 'culture of no-arbitrage modelling', and explore its relation to the development of Gaussian copula models. The article suggests that two themes from the science and technology studies literature on models (modelling as 'impure' bricolage, and modelling as articulating with heterogeneous objectives and constraints) help elucidate the history of Gaussian copula models in finance.

The problem of assimilating biased and inaccurate observations into inadequate models of the physical systems from which the observations were taken is common in the petroleum and groundwater fields. When large amounts of data are assimilated without accounting for model error and observation bias, predictions tend to be both overconfident and incorrect. In this paper, we propose a workflow for calibration of imperfect models to biased observations that involves model construction, model calibration, model criticism and model improvement. Model criticism is based on computation of model diagnostics which provide an indication of the validity of assumptions. During the model improvement step, we advocate identification of additional physically motivated parameters based on examination of data mismatch after calibration and addition of bias correction terms. If model diagnostics indicates the presence of residual model error after parameters have been added, then we advocate estimation of a “total” observation error covariance matrix, whose purpose is to reduce weighting of observations that cannot be matched because of deficiency of the model. Although the target applications of this methodology are in the subsurface, we illustrate the approach with two simplified examples involving prediction of the future velocity of fall of a sphere from models calibrated to a short-time series of biased measurements with independent additive random noise. The models into which the data are assimilated contain model errors due to neglect of physical processes and neglect of uncertainty in parameters. In every case, the estimated total error covariance is larger than the true observation covariance implying that the observations need not be matched to the accuracy of the measuring instrument. Predictions are much improved when all model improvement steps were taken.

The Internet of Things (IoT) connects various medical devices that enable remote monitoring, which can improve patient outcomes and help healthcare providers deliver precise diagnoses and better service to patients. However, IoT-based healthcare management systems face significant challenges in data security, such as maintaining a triad of confidentiality, integrity, and availability (CIA) and securing data transmission. This paper proposes a novel AdaBoost support vector machine (ASVM) based on the grey wolf optimization and international data encryption algorithm (ASVM-based GWO-IDEA) to secure medical data in an IoT-enabled healthcare system. The primary objective of this work was to prevent possible cyberattacks, unauthorized access, and tampering with the security of such healthcare systems. The proposed scheme encodes the healthcare data before transmitting them, protecting them from unauthorized access and other network vulnerabilities. The scheme was implemented in Python, and its efficiency was evaluated using a Kaggle-based public healthcare dataset. The performance of the model/scheme was evaluated with existing strategies in the context of effective security parameters, such as the confidentiality rate and throughput. When using the suggested methodology, the data transmission process was improved and achieved a high throughput of 97.86%, an improved resource utilization degree of 98.45%, and a high efficiency of 93.45% during data transmission.

Jurassic sedimentary sequences suitable for nuclear waste storage in northern Germany consist of organic-lean claystone and were uplifted to < 100 m depth in the Hils Syncline area (southern Lower Saxony Basin). This Hils Syncline, showcasing a northwestward increase in thermal maturity, facilitates the study of shale petrophysical properties influenced by burial history. This study introduces a 3D-thermally calibrated numerical model of the Hils Syncline area to analyze its geodynamic evolution and maturity variations. It provides new vitrinite reflectance and sonic velocity data for modeling calibration and erosion estimation. The Hils Syncline area has undergone continuous subsidence, interrupted by a Cretaceous uplift documented by an erosional unconformity. During the latest Early Cretaceous, Jurassic rocks underwent maximum burial reaching up to several thousand meters depth and temperatures up to 160 °C in the northwest. The Late Cretaceous inversion caused stronger erosion towards the northwest removing up to 3300 m of sediment compared to about 1300 m in the south, according to vitrinite reflectance-based estimations. Numerical modeling results along the study area indicate decreasing porosity and permeability northwestward with increasing thermal maturity. Porosity and vertical permeability decreased to 5–14% and 2.8 × 10 –23 to 1.5 × 10 –19 m 2 [1 mD = 10 −15 m 2 ], respectively, while vertical thermal conductivity increased to 1.30–2.12 (W/m/K). These trends of porosity/permeability and thermal conductivity with burial align with sonic velocity and published experimental porosity data, except for the thermally most mature region (Haddessen). This anomaly is tentatively attributed here to localized overpressure generation in the Posidonia Shale during maximum burial, affecting both the underlying Pliensbachian and overlying Doggerian units. Graphical abstract 3D numerical model of the Hils Syncline and surrounding area revealing that a northwestward increase in maximum burial resulted in higher temperatures and varying maturity levels. While most locations align well with calibration data (i.e. measured vitrinite reflectance and porosity), discrepancies arise in the Haddessen/Bensen area. The mismatch between porosity, vitrinite reflectance, and sonic velocity response indicates local overpressure in the northernmost region mainly during the Cretaceous. It was likely caused by gas generation in the Posidonia Shale affecting nearby Lower and Middle Jurassic units.

Computer simulations have conventionally been understood to be either extensions of formal methods such as mathematical models or as special cases of empirical practices such as experiments. Here, I argue that computer simulations are best understood as instruments. Understanding them as such can better elucidate their actual role as well as their potential epistemic standing in relation to science and other scientific methods, practices and devices.