Increased attention to the relationships between affect and learning has led to the development of machine-learned models that are able to identify students’ affective states in computerized learning environments. Data for these affect detectors have been collected from multiple modalities including physical sensors, dialogue logs, and logs of students’ interactions with the learning environmen...

Although gamma ray showers are muon-poor, they still produce a number of muons sufficient to make the sources observed by GeV and TeV telescopes observable also in muons. For sources with hard gamma ray spectra there is a relative ‘enhancement’ of muons from gamma ray primaries as compared to that from nucleon primaries. All shower gamma rays above the photoproduction threshold contribute to th...

Although gamma ray showers are muon-poor, they still produce a number of muons suucient to make the sources observed by GeV and TeV telescopes observable also in muons. For sources with hard gamma ray spectra there is a relativèenhancement' of muons from gamma ray primaries as compared to that from nucleon primaries. All shower gamma rays above the photo-production threshold contribute to the n...

this paper addresses the signal processing principles in passive bistatic radar (pbr) systems. in this case, the detection problem in the presence of system noise, clutter/multipath, direct signal and interfering target signals is investigated. to this light, two types of detectors are studied. in the first one, which is based on intuitive sense, we examine two detectors. in the second type det...

Extremely sensitive detectors are necessary for deep full-sky survey of distant extragalactic sources in the submillimeter-wave region by the cryogenically cooled telescope at the International Space Station (project Submillimetron). Detection of faint sources needs wide-band continuum observation using direct detectors (bolometers) not restricted by the quantum noise of indirect heterodyne rec...

Learning object detectors requires massive amounts of labeled training samples from the specific data source of interest. This is impractical when dealing with many different sources (e.g., in camera networks), or constantly changing ones such as mobile cameras (e.g., in robotics or driving assistant systems). In this paper, we address the problem of self-learning detectors in an autonomous man...

Consider a large collection of similar gravitational wave sources. If we cannot resolve the individual signals produced by these sources and know only their statistical properties, the signals form a stochastic background. We group stochastic backgrounds into the following two classes: those for which the individual sources have (i) average redshift z ≫ 1 and (ii) average redshift z ∼ 1. Typica...

Parallel to the development and optimization of high-power EUV sources for lithography, the realization of low-cost EUV sources for at-wavelength metrology is strongly required. These sources are important tools for the characterization of EUV mirrors and masks, for the determination of thin film transmission (EUV filters), for research on resist materials, and for the calibration of EUV detect...

Background: Estimating dosimetric parameters for small fields under non-reference conditions leads to significant errors if done based on conventional protocols used for large fields in reference conditions. Hence, further correction factors have been introduced to take into account the influence of spectral quality changes when various detectors are used in non-reference conditions at differen...