scholarly journals Analysis of Long-Term Single-Site Observations of the Pulsating DB White Dwarf GD 358

2002 ◽  
Vol 185 ◽  
pp. 382-383
Author(s):  
P.A. Bradley
Keyword(s):  
Fourier Transform ◽  
White Dwarf ◽  
Time Scale ◽  
Single Site ◽  
Difference Frequency ◽  
Data Sets ◽  
Period Range ◽  
Whole Earth

The pulsating DB white dwarf GD 358 was observed by the Whole Earth Telescope (WET) in 1990, 1994, and 2000. While these observing runs revealed a wealth of pulsation modes, they constitute only three “snapshots” of the behavior of this star. These “snapshots” show that GD 358 has a series of l = 1 modes present in the period range of 420 to 810 seconds, with numerous Fourier Transform peaks at the sums and differences of the l = 1 mode frequencies. In addition, the amplitudes of the l = 1 modes and the sum and difference frequency peaks (which I also call “combination peaks” in this paper) are different in each WET run. These data are not sufficient to determine the time scale of the amplitude changes and whether additional l = 1 modes might be present. For this, we need more frequent data sets, although not necessarily WET data.

scholarly journals The Pulsating White Dwarf L19-2

1995 ◽  
Vol 155 ◽  
pp. 441-442
Author(s):  
Denis J. Sullivan
Keyword(s):  
Fine Structure ◽  
White Dwarf ◽  
Single Site ◽  
Fine Structure Splitting ◽  
Structure Splitting ◽  
The One ◽  
Whole Earth

AbstractPrevious studies of the southern DAV white dwarf L19-2 have revealed that it pulsates non-radially in at least five modes with periods ~ 102 s and amplitudes less than 10 mmag. All of these modes showed fine structure splitting, but the one-day aliases resulting from the gaps in the single-site data made identification of the various frequencies, at best, difficult. Recent observations of L19-2 obtained from Mt. John (NZ) are presented, along with a discussion of the prospects for a Whole Earth Telescope run on this object scheduled for 1995.

Wet Observations of the DAV G185–32

2003 ◽  
Vol 12 (1) ◽  
Author(s):  
B. G. Castanheira ◽  
S.O. Kepler ◽  
P. Moskalik ◽  
S. J. Kleinman ◽  
A.E. Sansom ◽  
...  
Keyword(s):  
Fourier Transform ◽  
White Dwarf ◽  
Whole Earth

AbstractThe pulsating DAV white dwarf G185-32 was observed with the Whole Earth Telescope in 1992, during XCov8. We briefly report on the weighted Fourier transform of the data obtained.

scholarly journals White Dwarf.Org - Establishing a Permanent Endowment for the Whole Earth Telescope

2003 ◽  
Vol 12 (2) ◽  
Author(s):  
Travis S. Metcalfe
Keyword(s):  
White Dwarf ◽  
Fund Raising ◽  
Current Status ◽  
Dwarf Stars ◽  
Non Profit ◽  
White Dwarf Stars ◽  
Funding Sources ◽  
Governmental Funding ◽  
Whole Earth

AbstractWhite Dwarf Research Corporation is a non-profit organization dedicated to scientific research and public education on topics relevant to white dwarf stars. It was founded in 1999 in Austin, Texas to help fulfill the need for an alternative research center where scarce funding dollars could be used more efficiently, and to provide a direct link between astronomers who study white dwarf stars and the general public. Due to its administrative simplicity, WDRC can facilitate the funding of multi-institutional and international collaborations, provide seamless grant portability, minimize overhead rates, and actively seek non-governmental funding sources. I describe the motivation for, and current status of, one of the long-term goals of WDRC: to establish a permanent endowment for the operation of the Whole Earth Telescope. I pay particular attention to fund-raising efforts through the website at http://WhiteDwarf.org/donate/.

scholarly journals Analysis of Long-Term Single-Site Observations of The Pulsating DB White Dwarf GD 358

2004 ◽  
Vol 193 ◽  
pp. 506-510
Author(s):  
P.A. Bradley
Keyword(s):  
White Dwarf ◽  
Single Site ◽  
Change Over Time ◽  
Almost All ◽  
Over Time

AbstractWe briefly describe the analysis of single-site data collected from 1982 to 1992 for the pulsating DB white dwarf GD 358. We show that the amplitudes of almost all of the l = 1 modes change over time, and some of the l = 1 modes disappear for months at a time. We also find a new mode at k = 19, with a frequency of ~1173μHz.

scholarly journals A detection of the evolutionary time scale of the DA white dwarf G117 - B15A with the Whole Earth Telescope

1991 ◽  
Vol 378 ◽  
pp. L45 ◽  
Author(s):  
S. O. Kepler ◽  
D. E. Winget ◽  
R. E. Nather ◽  
P. A. Bradley ◽  
A. D. Grauer ◽  
...  
Keyword(s):  
White Dwarf ◽  
Time Scale ◽  
Evolutionary Time ◽  
Evolutionary Time Scale ◽  
Whole Earth

The long-term instability of the new generation hydrogen masers

2020 ◽  
pp. 35-38
Author(s):  
S.I. Donchenko ◽  
I.Y. Blinov ◽  
I.B. Norets ◽  
Y.F. Smirnov ◽  
A.A. Belyaev ◽  
...  
Keyword(s):  
Time Scale ◽  
Frequency Difference ◽  
Clock Frequency ◽  
Quantum Frequency ◽  
Frequency Standards ◽  
Quantum Frequency Standards ◽  
New Generation ◽  
Atomic Time

The latest changes in the algorithm for the formation of the international atomic time scale TAI are reported in terms of estimating the weights of the clocks involved in the formation of TAI. Studies of the characteristics of the long-term instability of new-generation hydrogen masers based on processing the results of the clock frequency difference with respect to TAI are performed. It has been confirmed that at present, new-generation hydrogen masers show significantly less long-term instability in comparison with quantum frequency standards ofsimilar and other types.

Asian Americans and Pacific Islanders: Employment Issues in the United States

2011 ◽  
Vol 9 (1-2) ◽  
pp. 58-69
Author(s):  
Marlene Kim
Keyword(s):  
United States ◽  
Asian Americans ◽  
The United States ◽  
Current Data ◽  
Pacific Islanders ◽  
Native Hawaiians ◽  
Data Sets ◽  
High Poverty ◽  
Unemployment Rates

Asian Americans and Pacific Islanders (AAPIs) in the United States face problems of discrimination, the glass ceiling, and very high long-term unemployment rates. As a diverse population, although some Asian Americans are more successful than average, others, like those from Southeast Asia and Native Hawaiians and Pacific Islanders (NHPIs), work in low-paying jobs and suffer from high poverty rates, high unemployment rates, and low earnings. Collecting more detailed and additional data from employers, oversampling AAPIs in current data sets, making administrative data available to researchers, providing more resources for research on AAPIs, and enforcing nondiscrimination laws and affirmative action mandates would assist this population.

Human Activity Recognition using Fourier Transform Inspired Deep Learning Combination Model

2019 ◽  
Vol 9 (1) ◽  
pp. 16-31
Author(s):  
Kyungkoo Jun
Keyword(s):  
Fourier Transform ◽  
Deep Learning ◽  
Short Term Memory ◽  
Window Size ◽  
Sensor Data ◽  
Data Sets ◽  
Data Set ◽  
Proposed Model ◽  
Testing Data ◽  
Labeling Scheme

Background & Objective: This paper proposes a Fourier transform inspired method to classify human activities from time series sensor data. Methods: Our method begins by decomposing 1D input signal into 2D patterns, which is motivated by the Fourier conversion. The decomposition is helped by Long Short-Term Memory (LSTM) which captures the temporal dependency from the signal and then produces encoded sequences. The sequences, once arranged into the 2D array, can represent the fingerprints of the signals. The benefit of such transformation is that we can exploit the recent advances of the deep learning models for the image classification such as Convolutional Neural Network (CNN). Results: The proposed model, as a result, is the combination of LSTM and CNN. We evaluate the model over two data sets. For the first data set, which is more standardized than the other, our model outperforms previous works or at least equal. In the case of the second data set, we devise the schemes to generate training and testing data by changing the parameters of the window size, the sliding size, and the labeling scheme. Conclusion: The evaluation results show that the accuracy is over 95% for some cases. We also analyze the effect of the parameters on the performance.

Epidemiological Evidence that Maternal Influenza Contributes to the Aetiology of Schizophrenia

1993 ◽  
Vol 163 (4) ◽  
pp. 522-534 ◽  
Author(s):  
W. Adams ◽  
R. E. Kendell ◽  
E. H. Hare ◽  
P. Munk-Jørgensen
Keyword(s):  
Data Sets ◽  
Time Lags ◽  
Epidemiological Evidence ◽  
Intrauterine Development ◽  
Increased Risk ◽  
Schizophrenic Patients ◽  
The Relationship ◽  
Monthly Incidence ◽  
Maternal Influenza

The epidemiological evidence that the offspring of women exposed to influenza in pregnancy are at increased risk of schizophrenia is conflicting. In an attempt to clarify the issue we explored the relationship between the monthly incidence of influenza (and measles) in the general population and the distribution of birth dates of three large series of schizophrenic patients - 16 960 Scottish patients born in 1932–60; 22 021 English patients born in 1921–60; and 18 723 Danish patients born in 1911–65. Exposure to the 1957 epidemic of A2 influenza in midpregnancy was associated with an increased incidence of schizophrenia, at least in females, in all three data sets. We also confirmed the previous report of a statistically significant long-term relationship between patients' birth dates and outbreaks of influenza in the English series, with time lags of - 2 and - 3 months (the sixth and seventh months of pregnancy). Despite several other negative studies by ourselves and others we conclude that these relationships are probably both genuine and causal; and that maternal influenza during the middle third of intrauterine development, or something closely associated with it, is implicated in the aetiology of some cases of schizophrenia.

scholarly journals A Novel LSTM Model with Interaction Dual Attention for Radar Echo Extrapolation

2021 ◽  
Vol 13 (2) ◽  
pp. 164
Author(s):  
Chuyao Luo ◽  
Xutao Li ◽  
Yongliang Wen ◽  
Yunming Ye ◽  
Xiaofeng Zhang
Keyword(s):  
Short Term Memory ◽  
Weather Forecast ◽  
Vital Role ◽  
Data Sets ◽  
Short Term ◽  
Learning Techniques ◽  
Radar Echo ◽  
Hidden States ◽  
Better Than

The task of precipitation nowcasting is significant in the operational weather forecast. The radar echo map extrapolation plays a vital role in this task. Recently, deep learning techniques such as Convolutional Recurrent Neural Network (ConvRNN) models have been designed to solve the task. These models, albeit performing much better than conventional optical flow based approaches, suffer from a common problem of underestimating the high echo value parts. The drawback is fatal to precipitation nowcasting, as the parts often lead to heavy rains that may cause natural disasters. In this paper, we propose a novel interaction dual attention long short-term memory (IDA-LSTM) model to address the drawback. In the method, an interaction framework is developed for the ConvRNN unit to fully exploit the short-term context information by constructing a serial of coupled convolutions on the input and hidden states. Moreover, a dual attention mechanism on channels and positions is developed to recall the forgotten information in the long term. Comprehensive experiments have been conducted on CIKM AnalytiCup 2017 data sets, and the results show the effectiveness of the IDA-LSTM in addressing the underestimation drawback. The extrapolation performance of IDA-LSTM is superior to that of the state-of-the-art methods.

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