Simplified method measures changes in tensile yield strength using least number of specimens

Simplified method determines yield strength due to heat treat, irradiation or mechanical treatment. Each specimen in a group of specimens is tested for yield stress point, subjected to heat treat or irradiation, and retested for new yield stress point which is a measure of change in material

Polyphonic music transcription using note onset and offset detection

In this paper, an approach for polyphonic music transcription based on joint multiple-F0 estimation and note onset/offset detection is proposed. For preprocessing, the resonator time-frequency image of the input music signal is extracted and noise suppression is performed. A pitch salience function is extracted for each frame along with tuning and inharmonicity parameters. For onset detection, late fusion is employed by combining a novel spectral flux-based feature which incorporates pitch tuning information and a novel salience function-based descriptor. For each segment defined by two onsets, an overlapping partial treatment procedure is used and a pitch set score function is proposed. A note offset detection procedure is also proposed using HMMs trained on MIDI data. The system was trained on piano chords and tested on classic and jazz recordings from the RWC database. Improved transcription results are reported compared to state-of-the-art approaches

Multiple-F0 estimation of piano sounds exploiting spectral structure and temporal evolution

This paper proposes a system for multiple fundamental frequency estimation of piano sounds using pitch candidate selection rules which employ spectral structure and temporal evolution. As a time-frequency representation, the Resonator Time-Frequency Image of the input signal is employed, a noise suppression model is used, and a spectral whitening procedure is performed. In addition, a spectral flux-based onset detector is employed in order to select the steady-state region of the produced sound. In the multiple-F0 estimation stage, tuning and inharmonicity parameters are extracted and a pitch salience function is proposed. Pitch presence tests are performed utilizing information from the spectral structure of pitch candidates, aiming to suppress errors occurring at multiples and sub-multiples of the true pitches. A novel feature for the estimation of harmonically related pitches is proposed, based on the common amplitude modulation assumption. Experiments are performed on the MAPS database using 8784 piano samples of classical, jazz, and random chords with polyphony levels between 1 and 6. The proposed system is computationally inexpensive, being able to perform multiple-F0 estimation experiments in realtime. Experimental results indicate that the proposed system outperforms state-of-the-art approaches for the aforementioned task in a statistically significant manner. Index Terms: multiple-F0 estimation, resonator timefrequency image, common amplitude modulatio

A temporally-constrained convolutive probabilistic model for pitch detection

A method for pitch detection which models the temporal evolution of musical sounds is presented in this paper. The proposed model is based on shift-invariant probabilistic latent component analysis, constrained by a hidden Markov model. The time-frequency representation of a produced musical note can be expressed by the model as a temporal sequence of spectral templates which can also be shifted over log-frequency. Thus, this approach can be effectively used for pitch detection in music signals that contain amplitude and frequency modulations. Experiments were performed using extracted sequences of spectral templates on monophonic music excerpts, where the proposed model outperforms a non-temporally constrained convolutive model for pitch detection. Finally, future directions are given for multipitch extensions of the proposed model

Not so social media: Twitter use in the conference sector

This research forms part of a larger project funded by Meeting Professionals International (MPI) focusing on the future of business events . In this paper we investigate the motivations for social media use within a professional event context. Twitter was tracked before during and after seven conferences and from this the top tweeters and organisers were identified. Fifteen interviews were conducted into both the organisational strategy and individual motivations for tweeting and were analysed alongside interviews with five social media experts. The research highlights several potential areas of conflict. Social media use tends to focus on broadcasting information rather than encouraging dialogue. People only tweet if they gain personal or individual professional value from doing so and event organisers need a deeper understanding of what that value is. Monitoring social media to gain customer insights and develop a more responsive customer service strategy is not yet happening although it is recognised as a necessity. The silent majority (passives) need to be better understood and catered for through social media use. Overall this sector, which successfully creates social interactions offline appears to be failing to do so online. A more strategic and resourced approach to social media is needed if its potential is to be achieved

Multiple-instrument polyphonic music transcription using a convolutive probabilistic model

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DScent Final Report

DScent was a joint project between five UK universities combining research theories in the disciplines of computational inference, forensic psychology and expert decision-making in the area of counter-terrorism. This document discusses the work carried out by Leeds Metropolitan University which covers the research, design and development work of an investigator support system in the area of deception using artificial intelligence. For the purposes of data generation along with system and hypothesis testing the project team devised two closed world games, the Cutting Corners Board Game and the Location Based Game. DScentTrail presents the investigator with a ‘scent trail’ of a suspect’s behaviour over time, allowing the investigator to present multiple challenges to a suspect from which they may prove the suspect guilty outright or receive cognitive or emotional clues of deception (Ekman 2002; Ekman & Frank 1993; Ekman & Yuille 1989; Hocking & Leathers 1980; Knapp & Comadena 1979). A scent trail is a collection of ordered, relevant behavioural information over time for a suspect. There are links into a neural network, which attempts to identify deceptive behavioural patterns of individuals. Preliminary work was carried out on a behavioural based AI module which would work separately alongside the neural network, with both identifying deception before integrating their results to update DScentTrail. Unfortunately the data that was necessary to design such a system was not provided and therefore, this section of research only reached its preliminary stages. To date research has shown that there are no specific patterns of deceptive behaviour that are consistent in all people, across all situations (Zuckerman 1981). DScentTrail is a decision support system, incorporating artificial intelligence (AI), which is intended to be used by investigators and attempts to find ways around the problem stated by Zuckerman above

DScentTrail: A new way of viewing deception

The DScentTrail System has been created to support and demonstrate research theories in the joint disciplines of computational inference, forensic psychology and expert decision-making in the area of counter-terrorism. DScentTrail is a decision support system, incorporating artificial intelligence, and is intended to be used by investigators. The investigator is presented with a visual representation of a suspect‟s behaviour over time, allowing them to present multiple challenges from which they may prove the suspect guilty outright or receive cognitive or emotional clues of deception. There are links into a neural network, which attempts to identify deceptive behaviour of individuals; the results are fed back into DScentTrail hence giving further enrichment to the information available to the investigator

Moduli Corrections to Gauge and Gravitational Couplings in four dimensional Superstrings

We study one-loop, moduli-dependent corrections to gauge and gravitational couplings in supersymmetric vacua of the heterotic string. By exploiting their relation to the integrability condition for the associated CP-odd couplings, we derive general expressions for them, both for $(2,2)$ and $(2,0)$ models, in terms of tree level four-point functions in the internal $N=2$ superconformal theory. The $(2,2)$ case, in particular symmetric orbifolds, is discussed in detail.Comment: 19 page

The Temperament Police: The Truth, the Ground Truth, and Nothing but the Truth

The tuning system of a keyboard instrument is chosen so that frequently used musical intervals sound as consonant as possible. Temperament refers to the compromise arising from the fact that not all intervals can be maximally consonant simultaneously. Recent work showed that it is possible to estimate temperament from audio recordings with no prior knowledge of the musical score, using a conservative (high precision, low recall) automatic transcription algorithm followed by frequency estimation using quadratic interpolation and bias correction from the log magnitude spectrum. In this paper we develop a harpsichord-specific transcription system to analyse over 500 recordings of solo harpsichord music for which the temperament is specified on the CD sleeve notes. We compare the measured temperaments with the annotations and discuss the differences between temperament as a theoretical construct and as a practical issue for professional performers and tuners. The implications are that ground truth is not always scientific truth, and that content-based analysis has an important role in the study of historical performance practice. 1