Influences of Weighting Techniques on TOPSIS-based Network Slice Selection Function

2019 ◽  
Author(s):  
Zoran S. Bojkovic ◽  
Bojan M. Bakmaz ◽  
Miodrag R. Bakmaz
Keyword(s):  
Selection Function

scholarly journals A complete search for redshift z ≳ 6.5 quasars in the VIKING survey

2020 ◽  
Vol 501 (2) ◽  
pp. 1663-1676
Author(s):  
R Barnett ◽  
S J Warren ◽  
N J G Cross ◽  
D J Mortlock ◽  
X Fan ◽  
...  
Keyword(s):  
Model Comparison ◽  
High Redshift ◽  
Detailed Comparison ◽  
Selection Function ◽  
Data Set ◽  
Bayesian Model Comparison ◽  
Fitting Method ◽  
Complete Search ◽  
Potential Contaminant ◽  
Ranked List

ABSTRACT We present the results of a new, deeper, and complete search for high-redshift 6.5 < z < 9.3 quasars over 977 deg2 of the VISTA Kilo-Degree Infrared Galaxy (VIKING) survey. This exploits a new list-driven data set providing photometry in all bands Z, Y, J, H, Ks, for all sources detected by VIKING in J. We use the Bayesian model comparison (BMC) selection method of Mortlock et al., producing a ranked list of just 21 candidates. The sources ranked 1, 2, 3, and 5 are the four known z > 6.5 quasars in this field. Additional observations of the other 17 candidates, primarily DESI Legacy Survey photometry and ESO FORS2 spectroscopy, confirm that none is a quasar. This is the first complete sample from the VIKING survey, and we provide the computed selection function. We include a detailed comparison of the BMC method against two other selection methods: colour cuts and minimum-χ2 SED fitting. We find that: (i) BMC produces eight times fewer false positives than colour cuts, while also reaching 0.3 mag deeper, (ii) the minimum-χ2 SED-fitting method is extremely efficient but reaches 0.7 mag less deep than the BMC method, and selects only one of the four known quasars. We show that BMC candidates, rejected because their photometric SEDs have high χ2 values, include bright examples of galaxies with very strong [O iii] λλ4959,5007 emission in the Y band, identified in fainter surveys by Matsuoka et al. This is a potential contaminant population in Euclid searches for faint z > 7 quasars, not previously accounted for, and that requires better characterization.

scholarly journals Radio continuum size evolution of star-forming galaxies over 0.35 < z < 2.25

2019 ◽  
Vol 625 ◽  
pp. A114 ◽  
Author(s):  
E. F. Jiménez-Andrade ◽  
B. Magnelli ◽  
A. Karim ◽  
G. Zamorani ◽  
M. Bondi ◽  
...  
Keyword(s):  
Star Formation ◽  
Formation Rate ◽  
Gaussian Model ◽  
Cosmic Time ◽  
Radio Continuum ◽  
Continuum Emission ◽  
Selection Function ◽  
Star Forming ◽  
Size Evolution ◽  
Galaxy Population

To better constrain the physical mechanisms driving star formation, we present the first systematic study of the radio continuum size evolution of star-forming galaxies (SFGs) over the redshift range 0.35 <  z <  2.25. We use the VLA COSMOS 3 GHz map (noise rms = 2.3 μJy beam−1, θbeam = 0.75 arcsec) to construct a mass-complete sample of 3184 radio-selected SFGs that reside on and above the main sequence (MS) of SFGs. We constrain the overall extent of star formation activity in galaxies by applying a 2D Gaussian model to their radio continuum emission. Extensive Monte Carlo simulations are used to validate the robustness of our measurements and characterize the selection function. We find no clear dependence between the radio size and stellar mass, M⋆, of SFGs with 10.5 ≲ log(M⋆/M⊙) ≲ 11.5. Our analysis suggests that MS galaxies are preferentially extended, while SFGs above the MS are always compact. The median effective radius of SFGs on (above) the MS of Reff = 1.5 ± 0.2 (1.0 ± 0.2) kpc remains nearly constant with cosmic time; a parametrization of the form Reff ∝ (1 + z)α yields a shallow slope of only α = −0.26 ± 0.08 (0.12 ± 0.14) for SFGs on (above) the MS. The size of the stellar component of galaxies is larger than the extent of the radio continuum emission by a factor ∼2 (1.3) at z = 0.5 (2), indicating star formation is enhanced at small radii. The galactic-averaged star formation rate surface density (ΣSFR) scales with the distance to the MS, except for a fraction of MS galaxies (≲10%) that harbor starburst-like ΣSFR. These “hidden” starbursts might have experienced a compaction phase due to disk instability and/or a merger-driven burst of star formation, which may or may not significantly offset a galaxy from the MS. We thus propose to use ΣSFR and distance to the MS in conjunction to better identify the galaxy population undergoing a starbursting phase.

scholarly journals Estimating a resource selection function with line transect sampling

2002 ◽  
Vol 6 (4) ◽  
pp. 213-228 ◽  
Author(s):  
Bryan F. J. Manly
Keyword(s):  
Resource Selection ◽  
Probability Function ◽  
Resource Selection Function ◽  
Line Transect ◽  
Selection Function ◽  
Line Transect Sampling ◽  
Selection Probability ◽  
Transect Sampling ◽  
Conditional Maximum ◽  
Habitat Variables

A resource selection probability function is a function that gives the prob- ability that a resource unit (e.g., a plot of land) that is described by a set of habitat variables X1 to Xp will be used by an animal or group of animals in a certain period of time. The estimation of a resource selection function is usually based on the comparison of a sample of resource units used by an animal with a sample of the resource units that were available for use, with both samples being assumed to be effectively randomly selected from the relevant populations. In this paper the possibility of using a modified sampling scheme is examined, with the used units obtained by line transect sampling. A logistic regression type of model is proposed, with estimation by conditional maximum likelihood. A simulation study indicates that the proposed method should be useful in practice.

Improving recommender systems’ performance on cold-start users and controversial items by a new similarity model

2016 ◽  
Vol 12 (2) ◽  
pp. 126-149 ◽  
Author(s):  
Masoud Mansoury ◽  
Mehdi Shajari
Keyword(s):  
Real World ◽  
Design Methodology ◽  
Cold Start ◽  
Selection Function ◽  
Data Sets ◽  
Real World Data ◽  
Content Type ◽  
User Similarity ◽  
Active User ◽  
Similarity Model

Purpose This paper aims to improve the recommendations performance for cold-start users and controversial items. Collaborative filtering (CF) generates recommendations on the basis of similarity between users. It uses the opinions of similar users to generate the recommendation for an active user. As a similarity model or a neighbor selection function is the key element for effectiveness of CF, many variations of CF are proposed. However, these methods are not very effective, especially for users who provide few ratings (i.e. cold-start users). Design/methodology/approach A new user similarity model is proposed that focuses on improving recommendations performance for cold-start users and controversial items. To show the validity of the authors’ similarity model, they conducted some experiments and showed the effectiveness of this model in calculating similarity values between users even when only few ratings are available. In addition, the authors applied their user similarity model to a recommender system and analyzed its results. Findings Experiments on two real-world data sets are implemented and compared with some other CF techniques. The results show that the authors’ approach outperforms previous CF techniques in coverage metric while preserves accuracy for cold-start users and controversial items. Originality/value In the proposed approach, the conditions in which CF is unable to generate accurate recommendations are addressed. These conditions affect CF performance adversely, especially in the cold-start users’ condition. The authors show that their similarity model overcomes CF weaknesses effectively and improve its performance even in the cold users’ condition.

scholarly journals The XXL Survey

2018 ◽  
Vol 620 ◽  
pp. A18 ◽  
Author(s):  
C. H. A. Logan ◽  
B. J. Maughan ◽  
M. N. Bremer ◽  
P. Giles ◽  
M. Birkinshaw ◽  
...  
Keyword(s):  
Angular Resolution ◽  
False Positive Rate ◽  
High Sensitivity ◽  
Point Sources ◽  
Selection Function ◽  
X Rays ◽  
Cluster Emission ◽  
X Ray ◽  
Wide Range ◽  
Function Modelling

Context. The XMM-XXL survey has used observations from the XMM-Newton observatory to detect clusters of galaxies over a wide range in mass and redshift. The moderate PSF (FWHM ~ 6″ on-axis) of XMM-Newton means that point sources within or projected onto a cluster may not be separated from the cluster emission, leading to enhanced luminosities and affecting the selection function of the cluster survey. Aims. We present the results of short Chandra observations of 21 galaxy clusters and cluster candidates at redshifts z > 1 detected in the XMM-XXL survey in X-rays or selected in the optical and infra-red. Methods. With the superior angular resolution of Chandra, we investigate whether there are any point sources within the cluster region that were not detected by the XMM-XXL analysis pipeline, and whether any point sources were misclassified as distant clusters. Results. Of the 14 X-ray selected clusters, 9 are free from significant point source contamination, either having no previously unresolved sources detected by Chandra or with less than about 10% of the reported XXL cluster flux being resolved into point sources. Of the other five sources, one is significantly contaminated by previously unresolved AGN, and four appear to be AGN misclassified as clusters. All but one of these cases are in the subset of less secure X-ray selected cluster detections and the false positive rate is consistent with that expected from the XXL selection function modelling. We also considered a further seven optically selected cluster candidates associated with faint XXL sources that were not classed as clusters. Of these, three were shown to be AGN by Chandra, one is a cluster whose XXL survey flux was highly contaminated by unresolved AGN, while three appear to be uncontaminated clusters. By decontaminating and vetting these distant clusters, we provide a pure sample of clusters at redshift z > 1 for deeper follow-up observations, and demonstrate the utility of using Chandra snapshots to test for AGN in surveys with high sensitivity but poor angular resolution.

scholarly journals Local disc model in view of Gaia DR1 and RAVE data

2018 ◽  
Vol 620 ◽  
pp. A71 ◽  
Author(s):  
K. Sysoliatina ◽  
A. Just ◽  
I. Koutsouridou ◽  
E. K. Grebel ◽  
G. Kordopatis ◽  
...  
Keyword(s):  
Main Sequence ◽  
Galactic Plane ◽  
Formation Rate ◽  
Velocity Distribution Function ◽  
Initial Mass Function ◽  
Selection Function ◽  
Thin Disc ◽  
Disc Model ◽  
Starting Point ◽  
Data Release

Aims. We test the performance of the semi-analytic self-consistent Just-Jahreiß disc model (JJ model) with the astrometric data from the Tycho-Gaia Astrometric Solution (TGAS) sub-catalogue of the first Gaia data release (Gaia DR1), as well as the radial velocities from the fifth data release of the Radial Velocity Experiment survey (RAVE DR5). Methods. We used a sample of 19 746 thin-disc stars from the TGAS×RAVE cross-match selected in a local solar cylinder of 300 pc radius and 1 kpc height below the Galactic plane. Based on the JJ model, we simulated this sample via the forward modelling technique. First, we converted the predicted vertical density laws of the thin-disc populations into a mock sample. For this we used the Modules and Experiments in Stellar Astrophysics (MESA) Isochrones and Stellar Tracks (MIST), a star formation rate (SFR) that decreased after a peak at 10 Gyr ago, and a three-slope broken power-law initial mass function (IMF). Then the obtained mock populations were reddened with a 3D dust map and were subjected to the selection criteria corresponding to the RAVE and TGAS observational limitations as well as to additional cuts applied to the data sample. We calculated the quantities of interest separately at different heights above the Galactic plane, taking the distance error effects in horizontal and vertical directions into account separately. Results. The simulated vertical number density profile agrees well with the data. An underestimation of the stellar numbers begins at ∼800 pc from the Galactic plane, which is expected as the possible influence of populations from |z| > 1 kpc is ignored during the modelling. The lower main sequence (LMS) is found to be thinner and under-populated by 3.6% relative to the observations. The corresponding deficits for the upper main sequence (UMS) and red giant branch (RGB) are 6% and 34.7%, respectively. However, the intrinsic uncertainty related to the choice of stellar isochrones is ∼10% in the total stellar number. The vertical velocity distribution function f(|W|) simulated for the whole cylinder agrees to within 1σ with the data. This marginal agreement arises because the dynamically cold populations at heights < 200 pc from the Galactic plane are underestimated. We also find that the model gives a fully realistic representation of the vertical gradient in stellar populations when studying the Hess diagrams for different horizontal slices. We also checked and confirm the consistency of our results with the newly available second Gaia data release (DR2). Conclusions. Based on these results and considering the uncertainties in the data selection as well as the sensitivity of the simulations to the sample selection function, we conclude that the fiducial JJ model confidently reproduces the vertical trends in the thin-disc stellar population properties. Thus, it can serve as a starting point for the future extension of the JJ model to other Galactocentric distances.

scholarly journals When and why performance goals predict exploitation behaviors: An achievement goal complex analysis of the selection function of assessment

2018 ◽  
Vol 43 (2) ◽  
pp. 266-284 ◽  
Author(s):  
Nicolas Sommet ◽  
David Nguyen ◽  
Kevin Fahrni ◽  
Martin Jobin ◽  
Ha-Phong Nguyen ◽  
...  
Keyword(s):  
Complex Analysis ◽  
Achievement Goal ◽  
Performance Goals ◽  
Selection Function

scholarly journals Using decades of spawning data and hydraulic models to construct a temperature dependent resource selection function for management of an endangered salmonid

2021 ◽  
Author(s):  
Peter N Dudley ◽  
Sara N John ◽  
Miles E Daniels ◽  
Eric M. Danner
Keyword(s):  
Water Temperature ◽  
Environmental Variables ◽  
Resource Selection ◽  
Oncorhynchus Tshawytscha ◽  
Linear Models ◽  
Low Cost ◽  
Hydraulic Modeling ◽  
Selection Function ◽  
Spawning Habitat ◽  
Increasing Temperature

In North America, impassable, man-made barriers block access to salmonid spawning habitat and require costly restoration efforts in the remaining habitats. Evaluating restored spawning habitat quality requires information on salmon water velocity and depth preferences, which may vary in relation to other variables (e.g. water temperature). We demonstrate a generalizable, low cost method to gather and analyze this data by combining aerial redd surveys of winter-run Chinook salmon (Oncorhynchus tshawytscha), 2D hydraulic modeling, and generalized linear models to calculate spawning resource selection functions (RSFs). Our method permits the examination of interactions between environmental variables on habitat selection, which are frequently treated as independent. Our methods resulted in a RSF that shows interactions between both velocity and depth preference with changing temperature. Preferred depth increased and preferred velocity decreased with increasing temperature. Spawning RSFs for environmental variables may change as other environmental conditions (i.e. water temperature) change, thus it is importance to account for potential interactions when using or producing RSFs.

scholarly journals Effects of the selection function on metallicity trends in spectroscopic surveys of the Milky Way

2017 ◽  
Vol 606 ◽  
pp. A97 ◽  
Author(s):  
G. Nandakumar ◽  
M. Schultheis ◽  
M. Hayden ◽  
A. Rojas-Arriagada ◽  
G. Kordopatis ◽  
...  
Keyword(s):  
Stellar Population ◽  
Milky Way ◽  
Target Selection ◽  
Selection Function ◽  
Population Synthesis ◽  
Sample Distribution ◽  
Stellar Population Synthesis ◽  
Source Sample ◽  
Correction Terms ◽  
Metallicity Distribution

Context. Large spectroscopic Galactic surveys imply a selection function in the way they performed their target selection. Aims. We investigate here the effect of the selection function on the metallicity distribution function (MDF) and on the vertical metallicity gradient by studying similar lines of sight using four different spectroscopic surveys (APOGEE, LAMOST, RAVE, and Gaia-ESO), which have different targeting strategies and therefore different selection functions. Methods. We use common fields between the spectroscopic surveys of APOGEE, LAMOST, RAVE (ALR) and APOGEE, RAVE, Gaia-ESO (AGR) and use two stellar population synthesis models, GALAXIA and TRILEGAL, to create mock fields for each survey. We apply the selection function in the form of colour and magnitude cuts of the respective survey to the mock fields to replicate the observed source sample. We make a basic comparison between the models to check which best reproduces the observed sample distribution. We carry out a quantitative comparison between the synthetic MDF from the mock catalogues using both models to understand the effect of the selection function on the MDF and on the vertical metallicity gradient. Results. Using both models, we find a negligible effect of the selection function on the MDF for APOGEE, LAMOST, and RAVE. We find a negligible selection function effect on the vertical metallicity gradients as well, though GALAXIA and TRILEGAL have steeper and shallower slopes, respectively, than the observed gradient. After applying correction terms on the metallicities of RAVE and LAMOST with respect to our reference APOGEE sample, our observed vertical metallicity gradients between the four surveys are consistent within 1σ. We also find consistent gradient for the combined sample of all surveys in ALR and AGR. We estimated a mean vertical metallicity gradient of − 0.241 ± 0.028 dex kpc-1. There is a significant scatter in the estimated gradients in the literature, but our estimates are within their ranges. Conclusions. We have shown that there is a negligible selection function effect on the MDF and the vertical metallicity gradients for APOGEE, RAVE, and LAMOST using two stellar population synthesis models. Therefore, it is indeed possible to combine common fields of different surveys in studies using MDF and metallicity gradients provided their metallicities are brought to the same scale.

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