Expertise is perceived from both sound and body movement in musical performance

Music is a rich form of nonverbal communication, in which the movements that expert musicians make during performance can influence the perception of expressive and structural features of the music. Whether the actual skill of a musician is perceivable from vision of movement was examined. In Experiment 1, musicians and non-musicians rated performances by novice, intermediate and expert clarinettists from point-light animations of their movements, sound recordings, or both. Performances by clarinettists of more advanced skill level were rated significantly higher from vision of movements, although this effect was stronger when sound was also presented. In Experiment 2, movements and sound from the novice and expert clarinettists' performances were switched for half the presentations, and were matched for the rest. Ratings of novice music were significantly higher when presented with expert movements, although the opposite was not found for expert sound presented with novice movements. No perceptual effect of raters' own level of musicianship was found in either experiment. These results suggest that expertise is perceivable from vision of musicians' body movements, although perception of skill from sound is dominant. The results from Experiment 2 further indicate a cross-modal effect of vision and audition on the perception of musical expertise. © 2012 Elsevier B.V.

Predicting organic acid concentration from UV/vis spectrometry measurements - A comparison of machine learning techniques

The concentration of organic acids in anaerobic digesters is one of the most critical parameters for monitoring and advanced control of anaerobic digestion processes. Thus, a reliable online-measurement system is absolutely necessary. A novel approach to obtaining these measurements indirectly and online using UV/vis spectroscopic probes, in conjunction with powerful pattern recognition methods, is presented in this paper. An UV/vis spectroscopic probe from S::CAN is used in combination with a custom-built dilution system to monitor the absorption of fully fermented sludge at a spectrum from 200 to 750 nm. Advanced pattern recognition methods are then used to map the non-linear relationship between measured absorption spectra to laboratory measurements of organic acid concentrations. Linear discriminant analysis, generalized discriminant analysis (GerDA), support vector machines (SVM), relevance vector machines, random forest and neural networks are investigated for this purpose and their performance compared. To validate the approach, online measurements have been taken at a full-scale 1.3-MW industrial biogas plant. Results show that whereas some of the methods considered do not yield satisfactory results, accurate prediction of organic acid concentration ranges can be obtained with both GerDA and SVM-based classifiers, with classification rates in excess of 87% achieved on test data.

Kinematic Analysis and Dimensional Synthesis of Exechon Parallel Kinematic Machine for Large Volume Machining

A parallel kinematic machine (PKM) topology can only give its best performance when its geometrical parameters are optimized. In this paper, dimensional synthesis of a newly developed PKM is presented for the first time. An optimization method is developed with the objective to maximize both workspace volume and global dexterity of the PKM. Results show that the method can effectively identify design parameter changes under different weighted objectives. The PKM with optimized dimensions has a large workspace to footprint ratio and a large well-conditioned workspace, hence justifies its suitability for large volume machining.

Cognitive and task-related EEG correlates of arithmetic performance in adolescents

Cognitive and neurophysiological correlates of arithmetic calculation, concepts, and applications were examined in 41 adolescents, ages 12-15 years. Psychological and task-related EEG measures which correctly distinguished children who scored low vs. high (using a median split) in each arithmetic subarea were interpreted as indicative of processes involved. Calculation was related to visual-motor sequencing, spatial visualization, theta activity measured during visual-perceptual and verbal tasks at right- and left-hemisphere locations, and right-hemisphere alpha activity measured during a verbal task. Performance on arithmetic word problems was related to spatial visualization and perception, vocabulary, and right-hemisphere alpha activity measured during a verbal task. Results suggest a complex interplay of spatial and sequential operations in arithmetic performance, consistent with processing model concepts of lateralized brain function.

IO Performance Prediction in Consolidated Virtualized Environments

We propose a trace-driven approach to predict the performance degradation of disk request response times due to storage device contention in consolidated virtualized environments. Our performance model evaluates a queueing network with fair share scheduling using trace-driven simulation. The model parameters can be deduced from measurements obtained inside Virtual Machines (VMs) from a system where a single VM accesses a remote storage server. The parameterized model can then be used to predict the effect of storage contention when multiple VMs are consolidated on the same virtualized server. The model parameter estimation relies on a search technique that tries to estimate the splitting and merging of blocks at the the Virtual Machine Monitor (VMM) level in the case of multiple competing VMs. Simulation experiments based on traces of the Postmark and FFSB disk benchmarks show that our model is able to accurately predict the impact of workload consolidation on VM disk IO response times.

Perceptual investigation of image placement with Ambisonics for non-centred listeners

Ambisonics is a scalable spatial audio technique that attempts to present a sound scene to listeners over as large an area as possi- ble. A localisation experiment was carried out to investigate the performance of a first and third order system at three listening positions - one in the centre and two off-centre. The test used a reverse target-pointer adjustment method to determine the error, both signed and absolute, for each combination of listening posi- tion and system. The signed error was used to indicate the direc- tion and magnitude of the shifts in panning angle introduced for the off-centre listening positions. The absolute error was used as a measure of the performance of the listening position and systems combinations for a comparison of their overall performance. A comparison was made between the degree of image shifting be- tween the two systems and the robustness of their off-centre per- formance.

Validation of an ultra high performance liquid chromatography-tandem mass spectrometry method for detection and quantitation of 19 endocrine disruptors in milk

An endocrine disruptor (ED) is an exogenous compound that interferes with the body's endocrine system. Exposure to EDs may result in adverse health effects such as infertility and cancer. EDs are composed of a vast group of chemicals including compounds of natural origin such as phytoestrogens or mycotoxins and a wide range of man-made chemicals such as pesticides. Synthetic compounds may find their way into the food chain where a number of them can biomagnify. Additionally, processing activities and food contact materials may add further to the already existing pool of food contaminants. Thus, our diet is considered to be one of the main exposure routes to EDs. Some precautionary legislation has already been introduced to control production and/or application of some persistent organic pollutants with ED characteristics. However, newly emerging EDs with bioaccumulative properties have recently been reported to appear at lower tiers of the food chain but have not been monitored at the grander scale. Milk and dairy products are a major component of our diet, thus it is important to monitor them for EDs. However, most methods developed to date are devoted to one group of compounds at a time. The UHPLC-MS/MS method described here has been validated according to EC decision 2002/657/EC and allows simultaneous extraction, detection, quantitation and confirmation of 19 EDs in milk. The method calibration range is between 0.50 and 20.0 μg kg with coefficients of determination above 0.99 for all analytes. Precision varied from 4.7% to 23.4% in repeatability and reproducibility studies. Established CCα and CCβ values (0.11-0.67 μg kg) facilitate fast, reliable, quantitative and confirmatory analysis of sub μg kg levels of a range of EDs in milk.

Machine Learning for Predictive Maintenance: A Multiple Classifiers Approach

In this paper a multiple classifier machine learning methodology for Predictive Maintenance (PdM) is presented. PdM is a prominent strategy for dealing with maintenance issues given the increasing need to minimize downtime and associated costs. One of the challenges with PdM is generating so called ’health factors’ or quantitative indicators of the status of a system associated with a given maintenance issue, and determining their relationship to operating costs and failure risk. The proposed PdM methodology allows dynamical decision rules to be adopted for maintenance management and can be used with high-dimensional and censored data problems. This is achieved by training multiple classification modules with different prediction horizons to provide different performance trade-offs in terms of frequency of unexpected breaks and unexploited lifetime and then employing this information in an operating cost based maintenance decision system to minimise expected costs. The effectiveness of the methodology is demonstrated using a simulated example and a benchmark semiconductor manufacturing maintenance problem.

Effect of fretting on fatigue performance of Ti-1023 titanium alloy

The plain fatigue and fretting fatigue tests of Ti-1023 titanium alloy were performed using a high-frequency push-pull fatigue testing machine. Both σmax versus number of cycles to failure curves were obtained for comparative analysis of the fretting effect on fatigue performance of the titanium alloy. Meanwhile, by analyzing the fracture of plain fatigue and fretting fatigue, the fretting scar and the fretting debris observed by scanning electron microscopy (SEM), the mechanism of fretting fatigue failure of Ti-1023 titanium alloy is discussed. The fretting fatigue strength of Ti-1023 titanium alloy is 175 MPa under 10 MPa contact pressure, which is 21% of plain fatigue strength (836 MPa). Under fretting condition, the Ti-1023 titanium alloy fatigue fracture failure occurs in a shorter fatigue life. When it comes to σmax versus number of cycles to failure curves, data points in the range of 106–107 cycles under plain fatigue condition moved to the range of 105–106 under fretting fatigue condition. The integrity of the fatigue specimen surface was seriously damaged under the effect of fretting. With the alternating stress loaded on specimen, the stress concentrated on the surface of fretting area, which brought earlier the initiation and propagation of crack.

DFIG Machine Design for Maximizing Power Output Based on Surrogate Optimization Algorithm

This paper presents a surrogate-model based optimization of a doubly-fed induction generator (DFIG) machine winding design for maximizing power yield. Based on site-specific wind profile data and the machine’s previous operational performance, the DFIG’s stator and rotor windings are optimized to match the maximum efficiency with operating conditions for rewinding purposes. The particle swarm optimization (PSO)-based surrogate optimization techniques are used in conjunction with the finite element method (FEM) to optimize the machine design utilizing the limited available information for the site-specific wind profile and generator operating conditions. A response surface method in the surrogate model is developed to formulate the design objectives and constraints. Besides, the machine tests and efficiency calculations follow IEEE standard 112-B. Numerical and experimental results validate the effectiveness of the proposed technologies.

Movement and Perceptual Strategies to Intercept Virtual Sound Sources

To intercept a moving object, one needs to be in the right place at the right time. In order to do this, it is necessary to pick up and use perceptual information that specifies the time to arrival of an object at an interception point. In the present study, we examined the ability to intercept a laterally moving virtual sound object by controlling the displacement of a sliding handle and tested whether and how the interaural time difference (ITD) could be the main source of perceptual information for successfully intercepting the virtual object. The results revealed that in order to accomplish the task, one might need to vary the duration of the movement, control the hand velocity and time to reach the peak velocity (speed coupling), while the adjustment of movement initiation did not facilitate performance. Furthermore, the overall performance was more successful when subjects employed a time-to-contact (tau) coupling strategy. This result shows that prospective information is available in sound for guiding goal-directed actions.

The idea, the machine, and the art: word and image in the 21st century

Taking in recent advances in neuroscience and digital technology, Gander and Garland assess the state of the inter-arts in America and the Western world, exploring and questioning the primacy of affect in an increasingly hypertextual everyday environment. In this analysis they signal a move beyond W. J. T. Mitchell’s coinage of the ‘imagetext’ to an approach that centres the reader-viewer in a recognition, after John Dewey, of ‘art as experience’. New thinking in cognitive and computer sciences about the relationship between the body and the mind challenges any established definitions of ‘embodiment’, ‘materiality’, ‘virtuality’ and even ‘intelligence, they argue, whilst ‘Extended Mind Theory’, they note, marries our cognitive processes with the material forms with which we engage, confirming and complicating Marshall McLuhan’s insight, decades ago, that ‘all media are “extensions of man”’. In this chapter, Gander and Garland open paths and suggest directions into understandings and critical interpretations of new and emerging imagetext worlds and experiences.

Elastodynamic Modeling and Analysis for an Exechon Parallel Kinematic Machine

As a newly invented parallel kinematic machine (PKM), Exechon has attracted intensive attention from both academic and industrial fields due to its conceptual high performance. Nevertheless, the dynamic behaviors of Exechon PKM have not been thoroughly investigated because of its structural and kinematic complexities. To identify the dynamic characteristics of Exechon PKM, an elastodynamic model is proposed with the substructure synthesis technique in this paper. The Exechon PKM is divided into a moving platform subsystem, a fixed base subsystem and three limb subsystems according to its structural features. Differential equations of motion for the limb subsystem are derived through finite element (FE) formulations by modeling the complex limb structure as a spatial beam with corresponding geometric cross sections. Meanwhile, revolute, universal, and spherical joints are simplified into virtual lumped springs associated with equivalent stiffnesses and mass at their geometric centers. Differential equations of motion for the moving platform are derived with Newton's second law after treating the platform as a rigid body due to its comparatively high rigidity. After introducing the deformation compatibility conditions between the platform and the limbs, governing differential equations of motion for Exechon PKM are derived. The solution to characteristic equations leads to natural frequencies and corresponding modal shapes of the PKM at any typical configuration. In order to predict the dynamic behaviors in a quick manner, an algorithm is proposed to numerically compute the distributions of natural frequencies throughout the workspace. Simulation results reveal that the lower natural frequencies are strongly position-dependent and distributed axial-symmetrically due to the structure symmetry of the limbs. At the last stage, a parametric analysis is carried out to identify the effects of structural, dimensional, and stiffness parameters on the system's dynamic characteristics with the purpose of providing useful information for optimal design and performance improvement of the Exechon PKM. The elastodynamic modeling methodology and dynamic analysis procedure can be well extended to other overconstrained PKMs with minor modifications.