scholarly journals Automatic identification of outliers in Hubble Space Telescope galaxy images

2021 ◽  
Author(s):  
Lior Shamir
Keyword(s):  
Learning Algorithm ◽  
Hubble Space Telescope ◽  
Automatic Identification ◽  
Machine Learning Algorithm ◽  
Computer Algorithms ◽  
Large Collection ◽  
Space Telescope ◽  
The Past ◽  
Manual Search ◽  
Astronomical Databases

Abstract Rare extragalactic objects can carry substantial information about the past, present, and future universe. Given the size of astronomical databases in the information era it can be assumed that very many outlier galaxies are included in existing and future astronomical databases. However, manual search for these objects is impractical due to the required labor, and therefore the ability to detect such objects largely depends on computer algorithms. This paper describes an unsupervised machine learning algorithm for automatic detection of outlier galaxy images, and its application to several Hubble Space Telescope fields. The algorithm does not require training, and therefore is not dependent on the preparation of clean training sets. The application of the algorithm to a large collection of galaxies detected a variety of outlier galaxy images. The algorithm is not perfect in the sense that not all objects detected by the algorithm are indeed considered outliers, but it reduces the dataset by two orders of magnitude to allow practical manual identification. The catalogue contains 147 objects that would be very difficult to identify without using automation.

scholarly journals CAN A MACHINE LEARNING ALGORITHM IDENTIFY SARS-COV-2 VARIANTS BASED ON CONVENTIONAL rRT-PCR? PROOF OF CONCEPT

2021 ◽  
Author(s):  
jorge cabrera Alvargonzalez ◽  
Ana Larranaga Janeiro ◽  
Sonia Perez ◽  
Javier Martinez Torres ◽  
Lucia martinez lamas ◽  
...  
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Supervised Classification ◽  
Learning Algorithm ◽  
Support Vector ◽  
Classification Algorithms ◽  
Machine Learning Algorithm ◽  
Proof Of Concept ◽  
The Past ◽  
Number Of Cycles

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been and remains one of the major challenges humanity has faced thus far. Over the past few months, large amounts of information have been collected that are only now beginning to be assimilated. In the present work, the existence of residual information in the massive numbers of rRT-PCRs that tested positive out of the almost half a million tests that were performed during the pandemic is investigated. This residual information is believed to be highly related to a pattern in the number of cycles that are necessary to detect positive samples as such. Thus, a database of more than 20,000 positive samples was collected, and two supervised classification algorithms (a support vector machine and a neural network) were trained to temporally locate each sample based solely and exclusively on the number of cycles determined in the rRT-PCR of each individual. Finally, the results obtained from the classification show how the appearance of each wave is coincident with the surge of each of the variants present in the region of Galicia (Spain) during the development of the SARS-CoV-2 pandemic and clearly identified with the classification algorithm.

scholarly journals Measuring proper motions of galactic dwarf galaxies with Hubble Space Telescope

2007 ◽  
Vol 3 (S248) ◽  
pp. 244-247 ◽  
Author(s):  
S. Piatek ◽  
C. Pryor
Keyword(s):  
Research Group ◽  
Dwarf Galaxies ◽  
Hubble Space Telescope ◽  
Proper Motions ◽  
Future Directions ◽  
Space Telescope ◽  
The Past ◽  
Scientific Justification ◽  
Satellite Galaxies ◽  
Using Data

AbstractOver the past several years, our research group has been measuring proper motions for nearby dwarf satellite galaxies using data taken with the Hubble Space Telescope. In order to measure proper motions with an expected size of several tens of milliarcseconds per century using a time baseline of 2-4 years, our work required that positions of stars and QSOs be measured to an accuracy of ~0.25 mas (~0.005 pixel). This contribution reviews the scientific justification of this work and our methodology. It concludes with a few general results and future directions.

scholarly journals ONLINE LEARNING FOR IMAGE PROCESSING IN NETWORKED SETTING

2017 ◽  
Vol 10 (13) ◽  
pp. 284
Author(s):  
Ankush Rai ◽  
Jagadeesh Kannan R
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Online Learning ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
The Past ◽  
Slow Development ◽  
Online Learning Algorithm

In the past decade development of machine learning algorithm for network settings has witnessed little advancements owing to slow development of technologies for improving bandwidth and latency.  In this study we present a novel online learning algorithm for network based computational operations in image processing setting

scholarly journals Distances to Planetary Nebulae

1989 ◽  
Vol 131 ◽  
pp. 65-72
Author(s):  
Julie H. Lutz
Keyword(s):  
Hubble Space Telescope ◽  
Planetary Nebulae ◽  
Significant Progress ◽  
Space Telescope ◽  
The Past ◽  
New Methods ◽  
Work Done

Finding distances to planetary nebulae remains a frustrating undertaking, but significant progress has been made over the past several years. This review covers primarily work done on distances since 1980, with some references to earlier papers. Some interesting new methods have been tried recently and some methods that have been used for years have been refined. Missions such as the Hubble Space Telescope and Hipparcos may provide new data on distances. Advances in ground-based telescopes and instruments will make possible new studies of distances.

scholarly journals Visions of Nature's Planet Foundry: Images of Circumstellar Disks

2004 ◽  
Vol 202 ◽  
pp. 291-299
Author(s):  
Karl Stapelfeldt
Keyword(s):  
Hubble Space Telescope ◽  
Planetary Systems ◽  
Circumstellar Disks ◽  
Space Telescope ◽  
The Past ◽  
Disk Structure

As the number of detected extrasolar planetary systems has steadily grown over the past five years, so too has the number of circumstellar disks with resolved images. In this contribution, I take stock of the current inventory of disk images at various wavelengths; summarize the results of a new disk imaging survey conducted with the Hubble Space Telescope; review the major inferences that can be drawn about disk structure from the extant images; and suggest areas for future progress.

scholarly journals Lessons Learned from the Hubble Space Telescope (HST) Contamination Control Program

2007 ◽  
Vol 50 (1) ◽  
pp. 44-60
Author(s):  
Patricia Hansen ◽  
Jacqueline Townsend ◽  
Randy Hedgeland
Keyword(s):  
Hubble Space Telescope ◽  
Control Program ◽  
Scientific Data ◽  
Lessons Learned ◽  
Space Telescope ◽  
Contamination Control ◽  
The Past ◽  
Integration Program ◽  
New Generation

Over the past two decades, the Hubble Space Telescope (HST) contamination control program has evolved from a ground-based integration program to a space-based science-sustaining program. The contamination controls from new-generation scientific instruments and orbital replacement units were incorporated into the HST contamination control program to maintain scientific capability over the life of the telescope. Long-term, on-orbit scientific data have shown that the contamination controls implemented for the instruments, servicing mission activities (Orbiter, astronauts, and mission), and on-orbit operations successfully protected the HST from contamination and the instruments from self-contamination.

Machine Learning Algorithm Based Bandwidth Prediction for Internet Usage

2020 ◽  
Vol 17 (8) ◽  
pp. 3749-3753
Author(s):  
J. Rajaram ◽  
M. Nalini ◽  
N. Vadivelan
Keyword(s):  
Machine Learning ◽  
At Risk ◽  
Learning Algorithm ◽  
Arima Model ◽  
Internet Usage ◽  
Machine Learning Algorithm ◽  
Framework Structure ◽  
The Past ◽  
Basic Activity ◽  
Time Plan

The applicability of framework structure and affiliation arranging recognize a basic activity in the bandwidth prediction. The procedure for predicting the framework use is to see the basic transmission limit with respect to future periods. This prediction helps with utilizing the techniques workplaces in the saint way. Thinking about the fundamental cost of bandwidth, at top hours of a framework traffic we can follow an amazing sort of plan to purchase. In this paper, the past use data of FWDR organize centers is at risk to univariate direct time plan ARIMA model after precise change is used to calculate necessary bandwidth limit concerning future needs. The anticipated data is veered from the obvious data gained from a for all intents and purposes indistinguishable framework and the foreseen data has been viewed as inside ten percent MAPE. This design reduction the MAPE by eleven point seventy-one percentage and fifteen point forty-two percent of self-rulingly when stood separated from the non-able changed ARIMA model at ninety-nine percent CI. The outcome show that the suitably changed ARIMA design has improved show when meandered from non-intentionally changed ARIMA model. Increasingly significant dataset can be passed on with season alterations and thought of expanded length groupings, for dynamically unequivocal and longer term needs.

scholarly journals The Dynamics Of Galactic Globular Cluster

2008 ◽  
Vol 4 (S252) ◽  
pp. 269-270
Author(s):  
Chen Ding
Keyword(s):  
Globular Cluster ◽  
Proper Motion ◽  
Velocity Dispersion ◽  
Hubble Space Telescope ◽  
Space Velocity ◽  
Space Telescope ◽  
Dispersion Profile ◽  
The Past ◽  
Internal Velocity

AbstractWe have used the Hubble Space Telescope (HST) to measure proper motion of the globular cluster NGC 6656 (M22) with respect to the background bulge stars and its internal velocity dispersion profile. With the space velocity of (Π, Θ, W) = (184±3, 209±14, 132±15) km s−1, we also calculate the orbit of the cluster. The central velocity dispersion in both components of the proper motion of cluster stars is 16.99 km s−1. We derive the mass-to-ration (M/L)∼1.7 which is relatively higher than the past works.

scholarly journals Fire incidents visualization and pattern recognition using machine learning algorithms

2021 ◽  
Vol 22 (3) ◽  
pp. 1427
Author(s):  
Jonardo R. Asor ◽  
Jefferson L. Lerios ◽  
Sherwin B. Sapin ◽  
Jocelyn O. Padallan ◽  
Chester Alexis C. Buama
Keyword(s):  
Machine Learning ◽  
Pattern Recognition ◽  
Learning Algorithm ◽  
The Philippines ◽  
Machine Learning Algorithms ◽  
Machine Learning Algorithm ◽  
Fire Occurrence ◽  
The Past ◽  
Fire Incident ◽  
Analyze Data

A fire incident is a devastating event that can be avoided with enough knowledge on how and when it may occur. For the past years, fire incidents have become a big problem for the Philippines, since it affects the socio-economic growth of the country. Machine learning algorithm is a well-known technique to predict and analyze data. It can also be used to recognize pattern and develop models for artificial intelligence. Pattern recognition through machine learning algorithm is already established and have proven itself accurate in different fields such as education, crime, health and many others including fire incidents. This paper aims to develop a model for recognizing patterns of fire incidents in the province of Laguna, Philippines implementing a machine learning algorithm. With the foregoing project, it is found out that a recurrent neural network shows an astonishing result in terms of pattern recognition. Further, it is also found that Calamba City is the most vulnerable area in case of fire occurrence in the Province of Laguna.

scholarly journals The Invisible Universe

2012 ◽  
Vol 16 (1 and 2) ◽  
pp. 255-259
Author(s):  
Michael Rowan-Robinson
Keyword(s):  
Milky Way ◽  
Hubble Space Telescope ◽  
Space Telescope ◽  
X Ray ◽  
The Past ◽  
Night Sky ◽  
William Herschel ◽  
The Universe ◽  
Optical Telescopes ◽  
The Invisible

With our own eyes we can see the night sky of the stars, planets and the Milky Way, the arena of pre-telescopic astronomy. Modern optical telescopes have opened up the universe of galaxies and we are familiar with the superb images of the Hubble Space Telescope. But with the invisible wavelengths of radio, infrared and X-ray, a very different universe comes into view. The astronomy of the invisible wavelengths was inaugurated by William Herschel in 1800 but developed very slowly over the next 160 years. The past fifty years have seen an explosion in our understanding of this strange world.

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