Graphene acoustic transducers based on electromagnetic interactions

All ingredients of the previous chapters are combined in order to build a gauge invariant theory of the interactions among the elementary particles. We start with a unified model of the weak and the electromagnetic interactions. The gauge symmetry is spontaneously broken through the BEH mechanism and we identify the resulting BEH boson. Then we describe the theory known as quantum chromodynamics (QCD), a gauge theory of the strong interactions. We present the property of confinement which explains why the quarks and the gluons cannot be extracted out of the protons and neutrons to form free particles. The last section contains a comparison of the theoretical predictions based on this theory with the experimental results. The agreement between theory and experiment is spectacular.

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Categorizing Touch-Input Locations from Touchscreen Device Interfaces via On-Board Mechano-Acoustic Transducers

Applied Sciences ◽

10.3390/app11114834 ◽

2021 ◽

Vol 11 (11) ◽

pp. 4834

Author(s):

Kai Ren Teo ◽

Balamurali B T ◽

Jianying Zhou ◽

Jer-Ming Chen

Keyword(s):

User Interaction ◽

Data Access ◽

Machine Learning Techniques ◽

Acoustic Features ◽

Touch Input ◽

Acoustic Transducers ◽

Learning Techniques ◽

Access Controls ◽

Input Location ◽

Mitigation Methods

Many mobile electronics devices, including smartphones and tablets, require the user to interact physically with the device via tapping the touchscreen. Conveniently, these compact devices are also equipped with high-precision transducers such as accelerometers and microphones, integrated mechanically and designed on-board to support a range of user functionalities. However, unintended access to these transducer signals (bypassing normal on-board data access controls) may allow sensitive user interaction information to be detected and thereby exploited. In this study, we show that acoustic features extracted from the on-board microphone signals, supported with accelerometer and gyroscope signals, may be used together with machine learning techniques to successfully determine the user’s touch input location on a touchscreen: our ensemble model, namely the random forest model, predicts touch input location with up to 86% accuracy in a realistic scenario. Accordingly, we present the approach and techniques used, the performance of the model developed, and also discuss limitations and possible mitigation methods to thwart possible exploitation of such unintended signal channels.

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Soft photon theorem in the small negative cosmological constant limit

Journal of High Energy Physics ◽

10.1007/jhep08(2021)105 ◽

2021 ◽

Vol 2021 (8) ◽

Author(s):

Nabamita Banerjee ◽

Karan Fernandes ◽

Arpita Mitra

Keyword(s):

Cosmological Constant ◽

Tree Level ◽

Leading Order ◽

Asymptotically Flat ◽

Soft Factor ◽

Flat Spacetime ◽

Electromagnetic Interactions ◽

Flat Spacetimes ◽

Perturbative Corrections ◽

Soft Factors

Abstract We study the effect of electromagnetic interactions on the classical soft theorems on an asymptotically AdS background in 4 spacetime dimensions, in the limit of a small cosmological constant or equivalently a large AdS radius l. This identifies 1/l2 perturbative corrections to the known asymptotically flat spacetime leading and subleading soft factors. Our analysis is only valid to leading order in 1/l2. The leading soft factor can be expected to be universal and holds beyond tree level. This allows us to derive a 1/l2 corrected Ward identity, following the known equivalence between large gauge Ward identities and soft theorems in asymptotically flat spacetimes.

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