scholarly journals The Time Scale Calculus Approach to the Geodesic Problem in 3D Dynamic Data Sets

2013 ◽  
Vol 18 (3) ◽  
pp. 421-427
Author(s):  
Sibel Atmaca ◽  
Ömer Akgüller
Keyword(s):  
Time Scale ◽  
Data Sets ◽  
Dynamic Data ◽  
Time Scale Calculus ◽  
Geodesic Problem

scholarly journals When to Spray: a Time-Scale Calculus Approach to Controlling the Impact of West Nile Virus

2009 ◽  
Vol 14 (2) ◽  
Author(s):  
Diana Thomas ◽  
Marion Weedermann ◽  
Lora Billings ◽  
Joan Hoffacker ◽  
Robert A. Washington-Allen
Keyword(s):  
West Nile Virus ◽  
Time Scale ◽  
West Nile ◽  
Time Scale Calculus ◽  
The Impact

scholarly journals Dynamic Fractional Inequalities Amplified on Time Scale Calculus Revealing Coalition of Discreteness and Continuity

2018 ◽  
Vol 2 (4) ◽  
pp. 25
Author(s):  
Muhammad Sahir
Keyword(s):  
Time Scale ◽  
Extended Form ◽  
Time Scale Calculus ◽  
Dynamic Time ◽  
Radon’S Inequality

In this paper, we present a generalization of Radon’s inequality on dynamic time scale calculus, which is widely studied by many authors and an intrinsic inequality. Further, we present the classical Bergström’s inequality and refinement of Nesbitt’s inequality unified on dynamic time scale calculus in extended form.

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.

Exploration and synthesis of dynamic data sets in telecom network applications

2003 ◽  
Author(s):  
Ch. Ykman-Couvreur ◽  
J. Lambrecht ◽  
D. Verkest ◽  
F. Catthoor ◽  
H. De Man
Keyword(s):  
Data Sets ◽  
Dynamic Data ◽  
Network Applications ◽  
Telecom Network

scholarly journals Consensus of classical and fractional inequalities having congruity on time scale calculus

2019 ◽  
Vol 27 (1) ◽  
pp. 57-69
Author(s):  
Muhammad Jibril Shahab Sahir
Keyword(s):  
Time Scales ◽  
Time Scale ◽  
Hölder’S Inequality ◽  
Fractional Integrals ◽  
Power Mean ◽  
Extended Form ◽  
Hölder's Inequality ◽  
Time Scale Calculus ◽  
Power Mean Inequality ◽  
Radon’S Inequality

Abstract In this paper, we find accordance of some classical inequalities and fractional dynamic inequalities. We find inequalities such as Radon’s inequality, Bergström’s inequality, Rogers-Hölder’s inequality, Cauchy-Schwarz’s inequality, the weighted power mean inequality and Schlömilch’s inequality in generalized and extended form by using the Riemann-Liouville fractional integrals on time scales.

scholarly journals Metannot: A succinct data structure for compression of colors in dynamic de Bruijn graphs

2017 ◽  
Author(s):  
Harun Mustafa ◽  
André Kahles ◽  
Mikhail Karasikov ◽  
Gunnar Rätsch
Keyword(s):  
Data Structure ◽  
High Throughput Sequencing ◽  
Sequence Data ◽  
Data Sets ◽  
Sequencing Data ◽  
Dynamic Data ◽  
De Bruijn Graphs ◽  
Dna And Rna ◽  
Succinct Data Structure ◽  
Dynamic Data Structure

AbstractMuch of the DNA and RNA sequencing data available is in the form of high-throughput sequencing (HTS) reads and is currently unindexed by established sequence search databases. Recent succinct data structures for indexing both reference sequences and HTS data, along with associated metadata, have been based on either hashing or graph models, but many of these structures are static in nature, and thus, not well-suited as backends for dynamic databases.We propose a parallel construction method for and novel application of the wavelet trie as a dynamic data structure for compressing and indexing graph metadata. By developing an algorithm for merging wavelet tries, we are able to construct large tries in parallel by merging smaller tries constructed concurrently from batches of data.When compared against general compression algorithms and those developed specifically for graph colors (VARI and Rainbowfish), our method achieves compression ratios superior to gzip and VARI, converging to compression ratios of 6.5% to 2% on data sets constructed from over 600 virus genomes.While marginally worse than compression by bzip2 or Rainbowfish, this structure allows for both fast extension and query. We also found that additionally encoding graph topology metadata improved compression ratios, particularly on data sets consisting of several mutually-exclusive reference genomes.It was also observed that the compression ratio of wavelet tries grew sublinearly with the density of the annotation matrices.This work is a significant step towards implementing a dynamic data structure for indexing large annotated sequence data sets that supports fast query and update operations. At the time of writing, no established standard tool has filled this niche.

scholarly journals Multiple isotopic models using various kinetic fractionation coefficients to estimateδ18O of leaf water

2018 ◽  
Author(s):  
Yonge Zhang ◽  
Xinxiao Yu ◽  
Lihua Chen ◽  
Guodong Jia
Keyword(s):  
Steady State ◽  
Time Scale ◽  
Model Performance ◽  
Special Care ◽  
Leaf Water ◽  
Data Sets ◽  
Kinetic Fractionation ◽  
Improved Model ◽  
Material Exchange ◽  
Good Agreement

AbstractInvestigation ofδ18O of leaf water may improve our understanding of the evapotranspiration partitioning and material exchange between the inside and outside of leaves. In this study,δ18O of bulk leaf water (δL,b) was estimated by both isotopic–steady–state (ISS) and non–steady–state (NSS) assumptions considering the Péclet effect. Specifically, we carefully modified kinetic fractionation coefficients (αk). The results showed that the Péclet effect is required to predictδL,b. On the diel time scale, both NSS assumption + Péclet effect (NSS + P) and ISS assumption + Péclet effect (ISS + P) using modifiedαk(αk–modified) forδL,bshowed a good agreement with observedδL,b(p> 0.05). When using previously proposedαk, however, both NSS + P and ISS + P were not reliable estimators ofδL,b(p< 0.05). On a longer time scale (days), estimates of daily meanδL,bfrom ISS + P outperformed the estimates from NSS + P when using the sameαkvalues. Also, the employment ofαk–modifiedimproved model performance in predicting daily meanδL,bcompared to the use of previously proposedαk. Clearly, special care must be taken concerningαkwhen using isotopic models to estimateδL,b.HighlightFor hourly and daily mean data sets, the employment of modified kinetic fractionation coefficients significantly improved model performance forδ18O of bulk leaf water.

scholarly journals Some Dynamic Inequalities via Diamond Integrals for Function of Several Variables

2021 ◽  
Vol 5 (4) ◽  
pp. 207
Author(s):  
Muhammad Bilal ◽  
Khuram Ali Khan ◽  
Hijaz Ahmad ◽  
Ammara Nosheen ◽  
Khalid Mahmood Awan ◽  
...  
Keyword(s):  
Time Scales ◽  
Time Scale ◽  
Jensen’S Inequality ◽  
Hardy Type Inequalities ◽  
Hardy Type ◽  
Several Variables ◽  
Time Scale Calculus ◽  
Special Cases ◽  
Function Of Several Variables ◽  
New Inequalities

In this paper, Jensen’s inequality and Fubini’s Theorem are extended for the function of several variables via diamond integrals of time scale calculus. These extensions are used to generalize Hardy-type inequalities with general kernels via diamond integrals for the function of several variables. Some Hardy Hilbert and Polya Knop type inequalities are also discussed as special cases. Classical and new inequalities are deduced from the main results using special kernels and particular time scales.

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