Instituto Politécnico Nacional

About: Instituto Politécnico Nacional is a education organization based out in Mexico City, Mexico. It is known for research contribution in the topics: Population & Context (language use). The organization has 43351 authors who have published 63315 publications receiving 938532 citations. The organization is also known as: Instituto Politécnico Nacional & Instituto Politecnico Nacional.

Gaia Early Data Release 3 - Photometric content and validation

Abstract: Context. Gaia Early Data Release 3 (Gaia EDR3) contains astrometry and photometry results for about 1.8 billion sources based on observations collected by the European Space Agency Gaia satellite during the first 34 months of its operational phase.Aims. In this paper, we focus on the photometric content, describing the input data, the algorithms, the processing, and the validation of the results. Particular attention is given to the quality of the data and to a number of features that users may need to take into account to make the best use of the Gaia EDR3 catalogue.Methods. The processing broadly followed the same procedure as for Gaia DR2, but with significant improvements in several aspects of the blue and red photometer (BP and RP) preprocessing and in the photometric calibration process. In particular, the treatment of the BP and RP background has been updated to include a better estimation of the local background, and the detection of crowding effects has been used to exclude affected data from the calibrations. The photometric calibration models have also been updated to account for flux loss over the whole magnitude range. Significant improvements in the modelling and calibration of the Gaia point and line spread functions have also helped to reduce a number of instrumental effects that were still present in DR2. Results. Gaia EDR3 contains 1.806 billion sources with G -band photometry and 1.540 billion sources with G BP and G RP photometry. The median uncertainty in the G -band photometry, as measured from the standard deviation of the internally calibrated mean photometry for a given source, is 0.2 mmag at magnitude G = 10–14, 0.8 mmag at G ≈ 17, and 2.6 mmag at G ≈ 19. The significant magnitude term found in the Gaia DR2 photometry is no longer visible, and overall there are no trends larger than 1 mmag mag−1 . Using one passband over the whole colour and magnitude range leaves no systematics above the 1% level in magnitude in any of the bands, and a larger systematic is present for a very small sample of bright and blue sources. A detailed description of the residual systematic effects is provided. Overall the quality of the calibrated mean photometry in Gaia EDR3 is superior with respect to DR2 for all bands.

Extended gamma-ray sources around pulsars constrain the origin of the positron flux at Earth

Abstract: The unexpectedly high flux of cosmic-ray positrons detected at Earth may originate from nearby astrophysical sources, dark matter, or unknown processes of cosmic-ray secondary production. We report the detection, using the High-Altitude Water Cherenkov Observatory (HAWC), of extended tera–electron volt gamma-ray emission coincident with the locations of two nearby middle-aged pulsars (Geminga and PSR B0656+14). The HAWC observations demonstrate that these pulsars are indeed local sources of accelerated leptons, but the measured tera–electron volt emission profile constrains the diffusion of particles away from these sources to be much slower than previously assumed. We demonstrate that the leptons emitted by these objects are therefore unlikely to be the origin of the excess positrons, which may have a more exotic origin.

Sentiment Analysis Is a Big Suitcase

Abstract: Although most works approach it as a simple categorization problem, sentiment analysis is actually a suitcase research problem that requires tackling many natural language processing (NLP) tasks The expression “sentiment analysis” itself is a big suitcase (like many others related to affective computing, such as emotion recognition or opinion mining) that all of us use to encapsulate our jumbled idea about how our minds convey emotions and opinions through natural language The authors address the composite nature of the problem via a three-layer structure inspired by the “jumping NLP curves” paradigm In particular, they argue that there are (at least) 15 NLP problems that need to be solved to achieve human-like performance in sentiment analysis

Exact histogram specification

Abstract: While in the continuous case, statistical models of histogram equalization/specification would yield exact results, their discrete counterparts fail. This is due to the fact that the cumulative distribution functions one deals with are not exactly invertible. Otherwise stated, exact histogram specification for discrete images is an ill-posed problem. Invertible cumulative distribution functions are obtained by translating the problem in a K-dimensional space and further inducing a strict ordering among image pixels. The proposed ordering refines the natural one. Experimental results and statistical models of the induced ordering are presented and several applications are discussed: image enhancement, normalization, watermarking, etc.