Search results for "Data analysis."

Open data from the first and second observing runs of advanced LIGO and advanced Virgo

2021

Abbot, Rich, et al. (Virgo and MAGIC Collaboration)

Fast simulation of muons produced at the SHiP experiment using Generative Adversarial Networks

2019

This paper presents a fast approach to simulating muons produced in interactions of the SPS proton beams with the target of the SHiP experiment. The SHiP experiment will be able to search for new long-lived particles produced in a 400~GeV$/c$ SPS proton beam dump and which travel distances between fifty metres and tens of kilometers. The SHiP detector needs to operate under ultra-low background conditions and requires large simulated samples of muon induced background processes. Through the use of Generative Adversarial Networks it is possible to emulate the simulation of the interaction of 400~GeV$/c$ proton beams with the SHiP target, an otherwise computationally intensive process. For th…

40 years of time geography: from the conceptual framework to the GI Science contributions

2011

International audience; Social scientists studying the effects of space on human behavior usually consider the time dimension as an external factor. Activities are analyzed in an aggregate sense such that the process of individual decision-making is depicted as the single case of "the average individual." In order to link efficiently space and time dimensions, Torsten Hägerstrand defined in 1970's the concept of Time Geography and thereby founded the school of Swedish geography. His conceptual framework was destined to change the course of history in the social sciences. After 40 years, this success has transcended scientific boundaries. In this paper, we propose to review the evolution of …

Anaconda, qualitative data analysis software for Catalyse

2013

Issues in synthetic data generation for advanced manufacturing

2017

To have any chance of application in real world, advanced manufacturing research in data analytics needs to explore and prove itself with real-world manufacturing data. Limited access to real-world data largely contrasts with the need for data of varied types and larger quantity for research. Use of virtual data is a promising approach to make up for the lack of access. This paper explores the issues, identifies challenges, and suggests requirements and desirable features in the generation of virtual data. These issues, requirements, and features can be used by researchers to build virtual data generators and gain experience that will provide data to data scientists while avoiding known or …

Event generation and statistical sampling for physics with deep generative models and a density information buffer

2021

Simulating nature and in particular processes in particle physics require expensive computations and sometimes would take much longer than scientists can afford. Here, we explore ways to a solution for this problem by investigating recent advances in generative modeling and present a study for the generation of events from a physical process with deep generative models. The simulation of physical processes requires not only the production of physical events, but to also ensure that these events occur with the correct frequencies. We investigate the feasibility of learning the event generation and the frequency of occurrence with several generative machine learning models to produce events l…

Effect of thyroid function on assisted reproduction outcomes in euthyroid infertile women: A single center retrospective data analysis and a systemat…

2022

BackgroundThe influence of thyroid-stimulating hormone (TSH) on gestational outcomes have been studied and checked whether differing TSH levels are relevant on human reproduction outcomes. International guidelines recommend TSH values <2.5 mIU/L in women trying to conceive, since values above this level are related to a higher frequency of adverse reproductive outcomes. This study aimed to evaluate whether TSH values correlate with different gestational outcomes in euthyroid infertile women without autoimmune thyroid disease.MethodsA retrospective cohort study was conducted involving 256 women who underwent in vitro fertilization (IVF) treatment. The participants were divided into tw…

Precise measurement of the top quark mass in dilepton decays using optimized neutrino weighting

2016

We measure the top quark mass in dilepton final states of top-antitop events in proton-antiproton collisions at sqrt(s) = 1.96 TeV, using data corresponding to an integrated luminosity of 9.7 fb^-1 at the Fermilab Tevatron Collider. The analysis features a comprehensive optimization of the neutrino weighting method to minimize the statistical uncertainties. We also improve the calibration of jet energies using the calibration determined in top-antitop to lepton+jets events, which reduces the otherwise limiting systematic uncertainty from the jet energy scale. The measured top quark mass is mt = 173.32 +/- 1.36(stat) +/- 0.85(syst) GeV.

Platform for efficient and secure data collection and exploitation in intelligent vehicular networks

2016

Nowadays, automotive area is witnessing a tremendous evolution due to the increasing growth in communication technologies, environmental sensing & perception aptitudes, and storage & processing capacities that we can find in recent vehicles. Indeed, a car is being a kind of intelligent mobile agent able to perceive its environment, sense and process data using on-board systems and interact with other vehicles or existing infrastructure. These advancements stimulate the development of several kinds of applications to enhance driving safety and efficiency and make traveling more comfortable. However, developing such advanced applications relies heavily on the quality of the data and therefore…

The Role of Big Data in Addressing Societal Challenges: A Systematic Mapping Study

2019

Part 2: Big Data Analytics; International audience; Big data has recently become the focus of academic and corporate investigation due to its high potential in generating business and social value. We have done a systematic mapping of the literature related to big data and its applications leading to social change through the lens of social innovation. The search strategy initially resulted in 593 papers, and after applying inclusion exclusion criteria a total of 156 papers were mapped; 59% of which were identified as empirical studies. This mapping investigated the publication frequency of the studies, research approach and contributions, research areas and article distribution per journal…