scholarly journals Spectrum Fitting Code for LAMOST ExtraGAlactic Surveys (LEGAS)

2009 ◽  
Vol 5 (S262) ◽  
pp. 295-298
Author(s):  
Xu Kong ◽  
Shanshan Su
Keyword(s):  
Optical Fibers ◽  
State Of The Art ◽  
Spectral Synthesis ◽  
Quality Data ◽  
Data Bases ◽  
High Quality Data ◽  
New Era ◽  
Extragalactic Surveys ◽  
Spectrum Fitting ◽  
Very High

AbstractThe study of stellar populations in galaxies is entering a new era with the availability of large and high-quality data bases of both observed galactic spectra and state-of-the-art evolutionary synthesis models. The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) has a 4m primary, and a 5 degree field of view, accommodate as many as 4000 optical fibers. It can obtain the spectra of objects as faint as down to B = 20.5 mag with an exposure of 1.5 hour, promising a very high spectrum acquiring rate of ten-thousands of spectra per night. In this talk, we introduce the progress of the LAMOST project, its surveys and show the spectral synthesis code that we are developing for the LAMOST ExtraGAlactic Surveys (LEGAS).

scholarly journals R factors in Rietveld analysis: How good is good enough?

2006 ◽  
Vol 21 (1) ◽  
pp. 67-70 ◽  
Author(s):  
Brian H. Toby
Keyword(s):  
Rietveld Analysis ◽  
Poor Quality ◽  
Quality Data ◽  
High Quality ◽  
High Quality Data ◽  
Poor Quality Data ◽  
Error Index ◽  
R Factors ◽  
Very High

The definitions for important Rietveld error indices are defined and discussed. It is shown that while smaller error index values indicate a better fit of a model to the data, wrong models with poor quality data may exhibit smaller values error index values than some superb models with very high quality data.

scholarly journals Intuition-Enabled Machine Learning Beats the Competition When Joint Human-Robot Teams Perform Inorganic Chemical Experiments

2019 ◽  
Author(s):  
Leroy Cronin ◽  
Vasilios Duros ◽  
Jonathan Grizou ◽  
Abhishek Sharma ◽  
Hessam Mehr ◽  
...  
Keyword(s):  
Self Assembly ◽  
State Of The Art ◽  
Chemical Space ◽  
Autonomous Systems ◽  
Quality Data ◽  
High Quality Data ◽  
Current State ◽  
Robot Teams ◽  
Substantial Progress ◽  
Inorganic Chemical

<div> <p>Traditionally, chemists have relied on years of training and accumulated experience in order to discover new molecules. But the space of possible molecules so vast, only a limited exploration with the traditional methods can be ever possible. This means that many opportunities for the discovery of interesting phenomena have been missed, and in addition, the inherent variability of these phenomena can make them difficult to control and understand. The current state-of-the-art is moving towards the development of automated and eventually fully autonomous systems coupled with in-line analytics and decision-making algorithms. Yet even these, despite the substantial progress achieved recently, still cannot easily tackle large combinatorial spaces as they are limited by the lack of high-quality data. Herein, we explore the utility of active learning methods for exploring the chemical space by comparing collaboration between human experimenters with an algorithm-based search, against their performance individually to probe the self-assembly and crystallization of the polyoxometalate cluster Na<sub>6</sub>[Mo<sub>120</sub>Ce<sub>6</sub>O<sub>366</sub>H<sub>12</sub>(H<sub>2</sub>O)<sub>78</sub>]·200H<sub>2</sub>O (<b>1</b>). We show that the robot-human teams are able to increase the prediction accuracy to 75.6±1.8%, from 71.8±0.3% with the algorithm alone and 66.3±1.8% from only the human experimenters demonstrating that human-robot teams beat robots or humans working alone.</p> </div>

scholarly journals New model atmosphere analyses of cool white dwarfs: a revised luminosity function and constraints on the age of the Galaxy

1997 ◽  
Vol 189 ◽  
pp. 429-432
Author(s):  
S.K. Leggett ◽  
P. Bergeron ◽  
Maria Teresa Ruiz
Keyword(s):  
White Dwarfs ◽  
Luminosity Function ◽  
State Of The Art ◽  
Model Atmosphere ◽  
Quality Data ◽  
High Quality Data ◽  
The Galaxy ◽  
Effective Temperatures ◽  
Cool White Dwarfs ◽  
Turn Over

We have obtained new photometric and spectroscopic data for a large sample of cool white dwarfs. These data have been analysed with state-of-the-art model atmospheres and effective temperatures and atmospheric compositions have been determined (Bergeron, Ruiz & Leggett 1997). Radii and masses have also been obtained for those stars with accurate parallax measurements. These high quality data and models allow us to produce an improved cool white dwarf luminosity function based on the Liebert, Dahn & Monet (1988) proper motion sample. The turn-over seen at the faint end of this luminosity function, combined with theoretical cooling sequences, enable us to constrain the age of the local region of the Galaxy.

scholarly journals Monitoring the TROPOMI-SWIR module instrument stability using desert sites

2021 ◽  
Author(s):  
Tim A. van Kempen ◽  
Filippo Oggionni ◽  
Richard M. van Hees
Keyword(s):  
Quality Data ◽  
Light Sources ◽  
High Quality ◽  
High Quality Data ◽  
Signal Stability ◽  
Independent Validation ◽  
Internal Calibration ◽  
Global Coverage ◽  
Operational Data ◽  
Very High

Abstract. Since its launch in 2017, the TROPOMI instrument on S-5P has provided very high quality data using daily global coverage for a number of key atmospheric trace gasses. Over its first 1,000 days in operations, the SWIR module has been very stable and the continuously monitored calibration has remained of high quality. This calibration relies on a combination of extensive pre-launch and post-launch measurements, complemented by regular monitoring of internal light sources and background measurements. In this paper we present a method and results for independent validation of the SWIR module calibration and instrument stability by examining the signal stability of a sample of 23 pseudo-invariant calibration desert sites. The data covers over two years of operational data. With a Lambertian surface assumption, the results show that the SWIR module has little to no instrument degradation down to an accuracy of about 0.3 % per year, validating results obtained from the internal calibration suite. The method presented here will be used as ongoing validation of the SWIR calibration.

scholarly journals Fasting during Ramadan in people with chronic kidney disease: a review of the literature

2019 ◽  
Vol 10 ◽  
pp. 204201881988901 ◽  
Author(s):  
Shahzaib Ahmad ◽  
Tahseen A. Chowdhury
Keyword(s):  
Chronic Kidney Disease ◽  
High Risk ◽  
Kidney Disease ◽  
Quality Data ◽  
High Quality Data ◽  
Ramadan Fasting ◽  
Ckd Stage ◽  
Stage 1 ◽  
Very High ◽  
Geographical Locations

Chronic kidney disease (CKD) is common among Muslim patients, and many such patients are keen to fast during the month of Ramadan. Fasting for prolonged periods may be deleterious for patients with CKD, but the changing season of fasting means that the duration of fast is very variable between geographical locations. There is, furthermore, a paucity of evidence to guide patients and clinicians in management of fasting in people with CKD. In this article, we aim to review the available evidence for patients with CKD and fasting, including haemodialysis and renal transplantation. We suggest that all patients with CKD should be deemed high risk or very high risk for fasting. We conclude, however, that patients with stable mild/moderate CKD (stage 1–3) may be able to fast providing they are carefully monitored and counselled. We also suggest that patients with stable renal transplants may also be able to fast, providing they are monitored carefully by their transplant team. Patients on haemodialysis or peritoneal dialysis should not be encouraged to fast, but if they do so, they will need careful weekly monitoring. There is an urgent need for high-quality data for patients with CKD who plan to fast over Ramadan, to enable more guidance to be developed for this vulnerable group of patients.

scholarly journals Prisma the Instruments

1993 ◽  
Vol 137 ◽  
pp. 672-674
Author(s):  
Andrew Jones
Keyword(s):  
High Resolution ◽  
Stellar Structure ◽  
Quality Data ◽  
The Sun ◽  
Calibration Point ◽  
High Quality ◽  
High Quality Data ◽  
X Ray ◽  
Very High ◽  
Selection Of

Our understanding of Solar structure has increased dramatically in the last couple of decades thanks mainly to the opening of new windows of observation providing high quality data to theoreticians with access to powerful computing facilities. Two of the new windows were UV and X-ray images of the Sun, allowing a detailed view of the upper solar atmosphere, and the development of very high resolution spectrometers allowing us to exploit the solar oscillations to probe the internal structure of the Sun. It is the goal of PRISMA to extend these techniques to other stars, which using the Sun as a calibration point will allow us to explore stellar structure and evolution in ways not possible now.In this poster I will present a possible selection of instruments able to achieve this goal, and explain some of the rationale in their design. A more general overview is presented by T. Appouchaux also in these proceedings. It must be stressed that these are not the definitive instruments to be flown on PRISMA, but rather result from a study to show the feasibility of such a mission. Should PRISMA be chosen as the next ESA medium sized mission, an ‘Announcement of Opportunity’ wiH be issued by ESA and the responses of all people interested in constructing the instrument will be considered.

scholarly journals Dialog State Tracking with Reinforced Data Augmentation

2020 ◽  
Vol 34 (05) ◽  
pp. 9474-9481
Author(s):  
Yichun Yin ◽  
Lifeng Shang ◽  
Xin Jiang ◽  
Xiao Chen ◽  
Qun Liu
Keyword(s):  
Data Augmentation ◽  
State Of The Art ◽  
The State ◽  
Training Data ◽  
Quality Data ◽  
Specific Context ◽  
High Quality ◽  
High Quality Data ◽  
Fine Grained ◽  
State Tracking

Neural dialog state trackers are generally limited due to the lack of quantity and diversity of annotated training data. In this paper, we address this difficulty by proposing a reinforcement learning (RL) based framework for data augmentation that can generate high-quality data to improve the neural state tracker. Specifically, we introduce a novel contextual bandit generator to learn fine-grained augmentation policies that can generate new effective instances by choosing suitable replacements for specific context. Moreover, by alternately learning between the generator and the state tracker, we can keep refining the generative policies to generate more high-quality training data for neural state tracker. Experimental results on the WoZ and MultiWoZ (restaurant) datasets demonstrate that the proposed framework significantly improves the performance over the state-of-the-art models, especially with limited training data.

scholarly journals Efficient Optomechanical Mode-Shape Mapping of Micromechanical Devices

Micromachines ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 880
Author(s):  
David Hoch ◽  
Kevin-Jeremy Haas ◽  
Leopold Moller ◽  
Timo Sommer ◽  
Pedro Soubelet ◽  
...  
Keyword(s):  
State Of The Art ◽  
Phase Lock Loop ◽  
Quality Data ◽  
High Quality Data ◽  
Silicon Nitride Membrane ◽  
Individual Contributions ◽  
Alternative Approaches ◽  
Shape Mapping ◽  
Degenerate Modes ◽  
Micromechanical Devices

Visualizing eigenmodes is crucial in understanding the behavior of state-of-the-art micromechanical devices. We demonstrate a method to optically map multiple modes of mechanical structures simultaneously. The fast and robust method, based on a modified phase-lock loop, is demonstrated on a silicon nitride membrane and shown to outperform three alternative approaches. Line traces and two-dimensional maps of different modes are acquired. The high quality data enables us to determine the weights of individual contributions in superpositions of degenerate modes.

scholarly journals Intuition-Enabled Machine Learning Beats the Competition When Joint Human-Robot Teams Perform Inorganic Chemical Experiments

2019 ◽  
Author(s):  
Leroy Cronin ◽  
Vasilios Duros ◽  
Jonathan Grizou ◽  
Abhishek Sharma ◽  
Hessam Mehr ◽  
...  
Keyword(s):  
Self Assembly ◽  
State Of The Art ◽  
Chemical Space ◽  
Autonomous Systems ◽  
Quality Data ◽  
High Quality Data ◽  
Current State ◽  
Robot Teams ◽  
Substantial Progress ◽  
Inorganic Chemical

<div> <p>Traditionally, chemists have relied on years of training and accumulated experience in order to discover new molecules. But the space of possible molecules so vast, only a limited exploration with the traditional methods can be ever possible. This means that many opportunities for the discovery of interesting phenomena have been missed, and in addition, the inherent variability of these phenomena can make them difficult to control and understand. The current state-of-the-art is moving towards the development of automated and eventually fully autonomous systems coupled with in-line analytics and decision-making algorithms. Yet even these, despite the substantial progress achieved recently, still cannot easily tackle large combinatorial spaces as they are limited by the lack of high-quality data. Herein, we explore the utility of active learning methods for exploring the chemical space by comparing collaboration between human experimenters with an algorithm-based search, against their performance individually to probe the self-assembly and crystallization of the polyoxometalate cluster Na<sub>6</sub>[Mo<sub>120</sub>Ce<sub>6</sub>O<sub>366</sub>H<sub>12</sub>(H<sub>2</sub>O)<sub>78</sub>]·200H<sub>2</sub>O (<b>1</b>). We show that the robot-human teams are able to increase the prediction accuracy to 75.6±1.8%, from 71.8±0.3% with the algorithm alone and 66.3±1.8% from only the human experimenters demonstrating that human-robot teams beat robots or humans working alone.</p> </div>

scholarly journals The state of the art in helioseismic ground-based experiments

1997 ◽  
Vol 181 ◽  
pp. 15-29
Author(s):  
Pere L. Pallé
Keyword(s):  
Solar Cycle ◽  
State Of The Art ◽  
Quality Data ◽  
Direct Impact ◽  
High Quality ◽  
High Quality Data ◽  
The Past ◽  
Long Time ◽  
Inversion Techniques ◽  
And Inversion

The new results obtained from the observation of solar oscillations over the past decade, have a direct impact on our knowledge of the Sun's interior. As a consequence, a great interest in helioseismology has arisen and is reflected in the development of new observational projects as well as new analyse and inversion techniques. In this review we will describe the present ground-based observational programmes, which, unlike the space ones, are mostly designed to produce high quality data over very long time spans (up to solar cycle time scales). The characteristics of the various observational programmes, single-site and network, will be described together with their performances, the main results obtained up to now, and some other logistical aspects.

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