Unsupervised learning models-based CRM anomaly detection using GPU

Deep learning models have improved several business intelligence tools like Customer relationship Management(CRM) systems. However, those models have increased the need for advanced computational capacity and infrastructure. Modern accelerators are starting to have floating-point precision arithmetic problems generated by highly streamlined systems, powered by the need to process an ever-increasing volume of data and increasingly complex models to attend to the necessity to identify customer data that allow consolidating products or services. We focus on CRM anomalies detection using GPU(Graphics Processor Unit) because they are a relevant source of money drain for organizations and directly affect the relationship between clients and suppliers. Our results present the combination of deep learning models with a computational structure that could access by organizations, but with a combination that reduces the number of features that achieve answers to CRM system.#AnáliticaDeDatosLos modelos de aprendizaje profundo han mejorado varias herramientas de inteligencia empresarial, como los sistemas de gestión de relaciones con el cliente (CRM). Sin embargo, esos modelos han aumentado la necesidad de infraestructura y capacidad computacional avanzada. Los aceleradores modernos están comenzando a tener problemas aritméticos de precisión de punto flotante generados por sistemas altamente optimizados, impulsados ​​por la necesidad de procesar un volumen cada vez mayor de datos y modelos cada vez más complejos para atender la necesidad de identificar datos de clientes que permitan consolidar productos o servicios. . Nos enfocamos en la detección de anomalías de CRM utilizando GPU (Graphics Processor Unit) porque son una fuente relevante de drenaje de dinero para las organizaciones y afectan directamente la relación entre clientes y proveedores. Nuestros resultados presentan la combinación de modelos de aprendizaje profundo con una estructura computacional a la que podrían acceder las organizaciones, pero con una combinación que reduce la cantidad de funcionalidades que logran respuestas al sistema CRM

Un análisis de la pobreza en Colombia basado en aprendizaje automático

El articulo analiza la pobreza en Colombia utilizando herramientas de aprendizaje automático supervisado a partir de los datos de Hogares, Personas y Vivienda del DANE para el periodo 2016 a 2019. Se examina la percepción de factores que influyen en la pobreza teniendo en cuenta las especificidades estructurales que conforman la medición de la pobreza, como la salud, el trabajo y la educación. El aporte de esta investigación es comparar el Índice de pobreza multidimensional con los factores relevantes de la situación de pobreza mediante el uso de herramientas aprendizaje automático. Los hallazgos revelan que el algoritmo XGBoost identifica los indicadores que causan la pobreza y permite proponer un marco de trabajo para lucha contra la pobreza. Palabras Clave: Aprendizaje automático, Medición y análisis de la pobreza, construcción de modelos y estimación, cambios tecnológicos.#BrechaDigitalThe article analyzes poverty in Colombia using supervised machine learning tools from DANE’s date of Households, People, and Housing for 2016 to 2019. The article examines the perception of factors that influence poverty, considering the structural specificities that make up the poverty measurement, such as health, work, and education. The contribution of this research is to compare the Multidimensional Poverty Index with the factors that are relevant to the poverty situation using machine learning tools. The findings reveal that the XGBoost algorithm identifies indicators that cause poverty and allows proposing a framework to fight poverty. Keywords: Machine Learning, Measurement and Analysis of Poverty, Computational Techniques; Simulation Modeling, Model Construction and Estimation, Technologica

Large-Angle Proton-Nucleus Elastic Scattering

This work was supported by the National Science Foundation Grants NSF PHY 78-22774 A03, NSF PHY 81-14339, and by Indiana Universit

Sperm DNA integrity in relation to exposure to environmental perfluoroalkyl substances – A study of spouses of pregnant women in three geographical regions.

Perfluoroalkyl substances (PFASs) can interfere with male reproductive function, but evidence in humansis limited. Six hundred four fertilemen(199 from Greenland, 197 from Poland and 208 from Ukraine) wereenrolled in the study. We measured four PFASs in serum (PFOS, PFOA, PFNA and PFHxS) and concurrentDNA damage in spermatozoa by sperm chromatin structure assay (SCSA) and in situ terminal deoxynucleotidyltransferase dUTP nick-end labeling (TUNEL) assay, apoptotic markers in semen (Fas-receptorand Bcl-xL), and reproductive hormones in serum. No association between PFASs and SCSA, apoptoticmarkers or reproductive hormones emerged.Weobserved a slight increase in SHBG and TUNEL-positivitywith increased PFOA exposure in men from Greenland. Thus, consistent evidence that PFAS exposureinterferes with sperm DNA fragmentation, apoptosis or reproductive hormones was not found

0+ → 0- Excitations in 16-O with 200 MeV Proton Inelastic Scattering

This research was sponsored by the National Science Foundation Grant NSF PHY-931478

Quantum Monte Carlo Calculations of Pion Scattering from Li

We show that the neutron and proton transition densities predicted by recent quantum Monte Carlo calculations for A=6,7 nuclei are consistent with pion scattering from 6Li and 7Li at energies near the Delta resonance. This has provided a microscopic understanding of the enhancement factors for quadrople excitations, which were needed to describe pion inelastic scattering within the nuclear shell model of Cohen and Kurath.Comment: 10 pages, REVTeX, 3 postscript figures; added calculation of elastic and inelastic pion scattering from 6Li at multiple energie

Atomic Parity Nonconservation: Electroweak Parameters and Nuclear Structure

There have been suggestions to measure atomic parity nonconservation (PNC) along an isotopic chain, by taking ratios of observables in order to cancel complicated atomic structure effects. Precise atomic PNC measurements could make a significant contribution to tests of the Standard Model at the level of one loop radiative corrections. However, the results also depend upon certain features of nuclear structure, such as the spatial distribution of neutrons in the nucleus. To examine the sensitivity to nuclear structure, we consider the case of Pb isotopes using various recent relativistic and non-relativistic nuclear model calculations. Contributions from nucleon internal weak structure are included, but found to be fairly negligible. The spread among present models in predicted sizes of nuclear structure effects may preclude using Pb isotope ratios to test the Standard Model at better than a one percent level, unless there are adequate independent tests of the nuclear models by various alternative strong and electroweak nuclear probes. On the other hand, sufficiently accurate atomic PNC experiments would provide a unique method to measure neutron distributions in heavy nuclei.Comment: 44 pages, INT Preprint DOE/ER/40561-050-INT92-00-1

Congenital deficiency reveals critical role of ISG15 in skin homeostasis

Ulcerating skin lesions are manifestations of human ISG15 deficiency, a type I interferonopathy. However, chronic inflammation may not be their exclusive cause. We describe two siblings with recurrent skin ulcers that healed with scar formation upon corticosteroid treatment. Both had a homozygous nonsense mutation in the ISG15 gene, leading to unstable ISG15 protein lacking the functional domain. We characterized ISG15(-/-) dermal fibroblasts, HaCaT keratinocytes, and human induced pluripotent stem cell-derived vascular endothelial cells. ISG15-deficient cells exhibited the expected hyperinflammatory phenotype, but also dysregulated expression of molecules critical for connective tissue and epidermis integrity, including reduced collagens and adhesion molecules, but increased matrix metalloproteinases. ISG15(-/-) fibroblasts exhibited elevated ROS levels and reduced ROS scavenger expression. As opposed to hyperinflammation, defective collagen and integrin synthesis was not rescued by conjugation-deficient ISG15. Cell migration was retarded in ISG15(-/-) fibroblasts and HaCaT keratinocytes, but normalized under ruxolitinib treatment. Desmosome density was reduced in an ISG15(-/-) 3D epidermis model. Additionally, there were loose architecture and reduced collagen and desmoglein expression, which could be reversed by treatment with ruxolitinib/doxycycline/TGF-beta 1. These results reveal critical roles of ISG15 in maintaining cell migration and epidermis and connective tissue homeostasis, whereby the latter likely requires its conjugation to yet unidentified targets

Microscopic calculations of medium effects for 200-MeV (p,p') reactions

We examine the quality of a G-matrix calculation of the effective nucleon-nucleon (NN) interaction for the prediction of the cross section and analyzing power for 200-MeV (p,p') reactions that populate natural parity states in $^{16}$O, $^{28}$Si, and $^{40}$Ca. This calculation is based on a one-boson-exchange model of the free NN force that reproduces NN observables well. The G-matrix includes the effects of Pauli blocking, nuclear binding, and strong relativistic mean-field potentials. The implications of adjustments to the effective mass ansatz to improve the quality of the approximation at momenta above the Fermi level will be discussed, along with the general quality of agreement to a variety of (p,p') transitions.Comment: 36 pages, TeX, 18 figure