19,056 research outputs found

    Evaluation of Psychoacoustic Sound Parameters for Sonification

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    Sonification designers have little theory or experimental evidence to guide the design of data-to-sound mappings. Many mappings use acoustic representations of data values which do not correspond with the listener's perception of how that data value should sound during sonification. This research evaluates data-to-sound mappings that are based on psychoacoustic sensations, in an attempt to move towards using data-to-sound mappings that are aligned with the listener's perception of the data value's auditory connotations. Multiple psychoacoustic parameters were evaluated over two experiments, which were designed in the context of a domain-specific problem - detecting the level of focus of an astronomical image through auditory display. Recommendations for designing sonification systems with psychoacoustic sound parameters are presented based on our results

    Surface profile prediction and analysis applied to turning process

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    An approach for the prediction of surface profile in turning process using Radial Basis Function (RBF) neural networks is presented. The input parameters of the RBF networks are cutting speed, depth of cut and feed rate. The output parameters are Fast Fourier Transform (FFT) vector of surface profile for the prediction of surface profile. The RBF networks are trained with adaptive optimal training parameters related to cutting parameters and predict surface profile using the corresponding optimal network topology for each new cutting condition. A very good performance of surface profile prediction, in terms of agreement with experimental data, was achieved with high accuracy, low cost and high speed. It is found that the RBF networks have the advantage over Back Propagation (BP) neural networks. Furthermore, a new group of training and testing data were also used to analyse the influence of tool wear and chip formation on prediction accuracy using RBF neural networks

    Audio-based Roughness Sensing and Tactile Feedback for Haptic Perception in Telepresence

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    Haptic perception is highly important for immersive teleoperation of robots, especially for accomplishing manipulation tasks. We propose a low-cost haptic sensing and rendering system, which is capable of detecting and displaying surface roughness. As the robot fingertip moves across a surface of interest, two microphones capture sound coupled directly through the fingertip and through the air, respectively. A learning-based detector system analyzes the data in real time and gives roughness estimates with both high temporal resolution and low latency. Finally, an audio-based vibrational actuator displays the result to the human operator. We demonstrate the effectiveness of our system through lab experiments and our winning entry in the ANA Avatar XPRIZE competition finals, where briefly trained judges solved a roughness-based selection task even without additional vision feedback. We publish our dataset used for training and evaluation together with our trained models to enable reproducibility of results.Comment: IEEE International Conference on Systems, Man, and Cybernetics (SMC), Honolulu, Hawaii, USA, October 202

    Individual differences in aesthetic preferences for multi-sensorial stimulation

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    The aim of the current project was to investigate aesthetics in multi-sensorial stimulation and to explore individual differences in the process. We measured the aesthetics of Interactive Objects (IOs) which are three-dimensional objects with electronic components that exhibit an autonomous behaviour when handled: e.g., vibrating, playing a sound, or lighting-up. The Q-sorting procedure of Q-methodology was applied. Data were analysed by following the Qmulti protocol. The results suggested that overall participants preferred IOs that (i) vibrate, (ii) have rough surface texture, and (iii) are round. No particular preference emerged about the size of the IOs. When making aesthetic judgment, participants paid more attention to the behaviour variable of the IOs than the size, contour or surface texture. In addition, three clusters of participants were identified, suggesting that individual differences existed in the aesthetics of IOs. Without proper consideration of potential individual differences, aesthetic scholars may face the risk of having significant effects masked by individual differences. Only by paying attention to this issue can more meaningful findings be generated to contribute to the field of aesthetics

    Investigating Perceptual Congruence Between Data and Display Dimensions in Sonification

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    The relationships between sounds and their perceived meaning and connotations are complex, making auditory perception an important factor to consider when designing sonification systems. Listeners often have a mental model of how a data variable should sound during sonification and this model is not considered in most data:sound mappings. This can lead to mappings that are difficult to use and can cause confusion. To investigate this issue, we conducted a magnitude estimation experiment to map how roughness, noise and pitch relate to the perceived magnitude of stress, error and danger. These parameters were chosen due to previous findings which suggest perceptual congruency between these auditory sensations and conceptual variables. Results from this experiment show that polarity and scaling preference are dependent on the data:sound mapping. This work provides polarity and scaling values that may be directly utilised by sonification designers to improve auditory displays in areas such as accessible and mobile computing, process-monitoring and biofeedback

    Preliminary Investigation of the Frictional Response of Reptilian Shed Skin

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    Developing deterministic surfaces relies on controlling the structure of the rubbing interface so that not only the surface is of optimized topography, but also is able to self-adjust its tribological behaviour according to the evolution of sliding conditions. In seeking inspirations for such designs, many engineers are turning toward the biological world to correlate surface structure to functional behavior of bio-analogues. From a tribological point of view, squamate reptiles offer diverse examples where surface texturing, submicron and nano-scale features, achieve frictional regulation. In this paper, we study the frictional response of shed skin obtained from a snake (Python regius). The study employed a specially designed tribo-acoustic probe capable of measuring the coefficient of friction and detecting the acoustical behavior of the skin in vivo. The results confirm the anisotropy of the frictional response of snakes. The coefficient of friction depends on the direction of sliding: the value in forward motion is lower than that in the backward direction. In addition it is shown that the anisotropy of the frictional response may stem from profile asymmetry of the individual fibril structures present within the ventral scales of the reptil

    Heat conduction tuning using the wave nature of phonons

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    The world communicates to our senses of vision, hearing and touch in the language of waves, as the light, sound, and even heat essentially consist of microscopic vibrations of different media. The wave nature of light and sound has been extensively investigated over the past century and is now widely used in modern technology. But the wave nature of heat has been the subject of mostly theoretical studies, as its experimental demonstration, let alone practical use, remains challenging due to the extremely short wavelengths of these waves. Here we show a possibility to use the wave nature of heat for thermal conductivity tuning via spatial short-range order in phononic crystal nanostructures. Our experimental and theoretical results suggest that interference of thermal phonons occurs in strictly periodic nanostructures and slows the propagation of heat. This finding broadens the methodology of heat transfer engineering by expanding its territory to the wave nature of heat

    DNS of Laminar to Turbulent Transition on NACA 0012 Airfoil with Sand Grain Roughness

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    The Lattice-Boltzmann-based solver PowerFLOW is used to perform direct numerical simulations of the transitional flow over an airfoil at Reynolds number equal to 0.657 million. The leading edge of the airfoil is covered with sand particles, represented by polyhedra, to mimic the grit used in experiments. The sensitivity of the laminar to turbulent transition to the size of these particles, grid resolution, spanwise length is evaluated and rectangular trips are also tested

    To “Sketch-a-Scratch”

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    A surface can be harsh and raspy, or smooth and silky, and everything in between. We are used to sense these features with our fingertips as well as with our eyes and ears: the exploration of a surface is a multisensory experience. Tools, too, are often employed in the interaction with surfaces, since they augment our manipulation capabilities. “Sketch-a-Scratch” is a tool for the multisensory exploration and sketching of surface textures. The user’s actions drive a physical sound model of real materials’ response to interactions such as scraping, rubbing or rolling. Moreover, different input signals can be converted into 2D visual surface profiles, thus enabling to experience them visually, aurally and haptically
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