We present an algorithm based on multi-layer transformers for identifying Adverse Drug Reactions (ADR) in social media data. Our model relies on the properties of the problem and the characteristics of contextual word embeddings to extract two views
from documents. Then a classifier is trained on each view to label a set of unlabeled documents to be used as an initializer for a new classifier in the other view. Finally, the initialized classifier in each view is further trained using the initial training examples. We evaluated our model in the largest publicly available ADR dataset. The experiments testify that our model significantly outperforms the transformer-based models pretrained on domain-specific data.
In deployment, systems that use speech as input must make use of automated transcriptions. Yet, typically when these systems are evaluated, gold transcriptions are assumed. We explicitly examine the impact of transcription errors on the downstream pe
rformance of a multi-modal system on three related tasks from three datasets: emotion, sarcasm, and personality detection. We include three separate transcription tools and show that while all automated transcriptions propagate errors that substantially impact downstream performance, the open-source tools fair worse than the paid tool, though not always straightforwardly, and word error rates do not correlate well with downstream performance. We further find that the inclusion of audio features partially mitigates transcription errors, but that a naive usage of a multi-task setup does not.
Theoretical studies and experimental measurements have
proved the existence of magnetic moments of the neutral
neutrino particle, so that its participation in
the electromagnetic interactions in the nature cannot be
neglected. The problem of the solar neutrino (Decreasing
the solar neutrino bundle, which arrived to the earth) was
one of the an understandable issues in the neutrino physics.
Increasing data rate in optical communication systems leads to nonlinear electromagnet phenomenon in optical signal along fiber, and causes distortion in it.Thefiber dispersion is a linear phenomenon that causes difficulties toachieve high bit rate a
nd distance product.The limiting of nonlinear effects requireslow input power level, but this induces lowsignal to noise ratio. So, we search another solutions.
This paper studies Split Step Fourier Transform Algorithm (SSFTM) used to solve partial differential nonlinear Schrödinger equation (NLSE).Then, we use it for simulating optical signal propagating in fiber by using MATLAB program, and designing fiber optic block could add it to MATLAB Simulink Library. Finally ,in this paper, we achieved results for selecting important parameters in single mode fiber for high bit rate, for improving bit error rate and Qcoefficient.
The toxic effect of some insecticides (Amitraz, Amitraz + summer oil,
Abamectin, Abamectin + summer oil) and plant extracts (Melia azedarach L.,
M. azedarach + summer oil, Schinus molle L., S. molle + summer oil) were
tested on the predator of pea
r psyllae insect Anthocoris nemoralis F. and the
parasite Trechnites psyllae R. in the Mokhtaria research station, agricultural
research center at Homs during the season 2011.
