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Irina Semenova

Publications and source records attributed to Irina Semenova.

4 recordsLinked to original sources

Construction and Performance of the Barrel Electromagnetic Calorimeter for the GlueX Experiment

The barrel calorimeter is part of the new spectrometer installed in Hall D at Jefferson Lab for the GlueX experiment. The calorimeter was installed in 2013, commissioned in 2014 and has been operating routinely since early 2015. The detector configuration, associated Monte Carlo simulations, calibration and operational performance are described herein. The calorimeter records the time and energy deposited by charged and neutral particles created by a multi-GeV photon beam. It is constructed as a lead and scintillating-fiber calorimeter and read out with 3840 large-area silicon photomultiplier arrays. Particles impinge on the detector over a wide range of angles, from normal incidence at 90 degrees down to 11.5 degrees, which defines a geometry that is fairly unique among calorimeters. The response of the calorimeter has been measured during a running experiment and performs as expected for electromagnetic showers below 2.5 GeV. We characterize the performance of the BCAL using the energy resolution integrated over typical angular distributions for $π^0$ and $η$ production of $σ_E/E$=5.2\%/$\sqrt{E(\rm{GeV})} \oplus$ 3.6\% and a timing resolution of $σ$\,=\,150\,ps at 1\,GeV.

physics.ins-det↗

About the survey of propagandistic messages in contemporary social media

This paper presents the research results that have identified a set of characteristic parameters of propagandistic messages. Later these parameters can be used in the algorithm creating special user-oriented propagandistic messages to improve distribution and assimilation of information by users.

cs.SI↗

Analytical model of misinformation of a social network node

This paper presents the research of the influence of cognitive, behavioral, representational factors on the susceptibility of the participants in social networks to misinformation, as well as on the activity of the nodes in this regard. The importance of this research consists of method of blocking the propaganda. This is very important because when people involuntarily acquire information some of them experience an undesired change in their social attitude. Such phenomena typically lead towards the information warfare. A model was developed during this research for calculating the level of misinformation of the social network participant (network node) based on the model of iterative learning process.

cs.SI↗