Analysis of Fade Dynamics in Site Diversity System in Slovenia

Prediction of Joint Rain Attenuation Statistics Induced on Earth–Satellite Multiple Site Diversity Systems Using Gaussian Copula

IEEE Antennas and Wireless Propagation Letters ◽

10.1109/lawp.2016.2557960 ◽

2017 ◽

Vol 16 ◽

pp. 95-98 ◽

Cited By ~ 4

Author(s):

Arsim Kelmendi ◽

Charilaos Kourogiorgas ◽

Andrej Hrovat ◽

Athanasios D. Panagopoulos ◽

Gorazd Kandus ◽

...

Keyword(s):

Earth Satellite ◽

Rain Attenuation ◽

Gaussian Copula ◽

Multiple Site ◽

Diversity Systems ◽

Site Diversity

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Observation of Site Diversity Gain Dependency on Separation Distance Using an Attenuation-Dependent Logarithmic Model in a Tropical Region

IEEE Access ◽

10.1109/access.2021.3056183 ◽

2021 ◽

Vol 9 ◽

pp. 33994-34006

Author(s):

Fazdliana Samat ◽

Mandeep Jit Singh ◽

Aduwati Sali ◽

P. M. Kalaivaanan

Keyword(s):

Separation Distance ◽

Diversity Gain ◽

Tropical Region ◽

Logarithmic Model ◽

Site Diversity

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Evaluation of the Gaussian copula prediction method for joint rain attenuation statistics in Earth-satellite site diversity systems

2016 International Conference on Broadband Communications for Next Generation Networks and Multimedia Applications (CoBCom) ◽

10.1109/cobcom.2016.7593491 ◽

2016 ◽

Author(s):

Arsim Kelmendi ◽

Gorazd Kandus ◽

Ales Svigelj ◽

Andrej Vilhar ◽

Andrej Hrovat ◽

...

Keyword(s):

Prediction Method ◽

Earth Satellite ◽

Rain Attenuation ◽

Gaussian Copula ◽

Diversity Systems ◽

Site Diversity

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A fixed network design for site diversity enhanced wireless access

Gateway to 21st Century Communications Village. VTC 1999-Fall. IEEE VTS 50th Vehicular Technology Conference (Cat. No.99CH36324) ◽

10.1109/vetecf.1999.798592 ◽

2005 ◽

Cited By ~ 4

Author(s):

M. Meinesz ◽

F. Schoute ◽

J.-D. Bakker

Keyword(s):

Network Design ◽

Wireless Access ◽

Site Diversity ◽

Fixed Network

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Field-theoretic density estimation for biological sequence space with applications to 5′ splice site diversity and aneuploidy in cancer

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2025782118 ◽

2021 ◽

Vol 118 (40) ◽

pp. e2025782118

Author(s):

Wei-Chia Chen ◽

Juannan Zhou ◽

Jason M. Sheltzer ◽

Justin B. Kinney ◽

David M. McCandlish

Keyword(s):

Probability Distribution ◽

Maximum Entropy ◽

Density Estimation ◽

Sequence Space ◽

Chromosomal Abnormalities ◽

Fundamental Problem ◽

Probability Distributions ◽

Biological Sequence ◽

Point Estimates ◽

Site Diversity

Density estimation in sequence space is a fundamental problem in machine learning that is also of great importance in computational biology. Due to the discrete nature and large dimensionality of sequence space, how best to estimate such probability distributions from a sample of observed sequences remains unclear. One common strategy for addressing this problem is to estimate the probability distribution using maximum entropy (i.e., calculating point estimates for some set of correlations based on the observed sequences and predicting the probability distribution that is as uniform as possible while still matching these point estimates). Building on recent advances in Bayesian field-theoretic density estimation, we present a generalization of this maximum entropy approach that provides greater expressivity in regions of sequence space where data are plentiful while still maintaining a conservative maximum entropy character in regions of sequence space where data are sparse or absent. In particular, we define a family of priors for probability distributions over sequence space with a single hyperparameter that controls the expected magnitude of higher-order correlations. This family of priors then results in a corresponding one-dimensional family of maximum a posteriori estimates that interpolate smoothly between the maximum entropy estimate and the observed sample frequencies. To demonstrate the power of this method, we use it to explore the high-dimensional geometry of the distribution of 5′ splice sites found in the human genome and to understand patterns of chromosomal abnormalities across human cancers.

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The effect of life-history and mode of inheritance on neutral genetic variability

Genetics Research ◽

10.1017/s0016672301004979 ◽

2001 ◽

Vol 77 (2) ◽

pp. 153-166 ◽

Cited By ~ 114

Author(s):

BRIAN CHARLESWORTH

Keyword(s):

Sequence Variation ◽

Adult Mortality ◽

Structured Populations ◽

Human Populations ◽

Effective Population ◽

Transmission Modes ◽

Population Sizes ◽

Age Structured ◽

Infinite Sites Model ◽

Site Diversity

Formulae for the effective population sizes of autosomal, X-linked, Y-linked and maternally transmitted loci in age-structured populations are developed. The approximations used here predict both asymptotic rates of increase in probabilities of identity, and equilibrium levels of neutral nucleotide site diversity under the infinite-sites model. The applications of the results to the interpretation of data on DNA sequence variation in Drosophila, plant, and human populations are discussed. It is concluded that sex differences in demographic parameters such as adult mortality rates generally have small effects on the relative effective population sizes of loci with different modes of inheritance, whereas differences between the sexes in variance in reproductive success can have major effects, either increasing or reducing the effective population size for X-linked loci relative to autosomal or Y-linked loci. These effects need to be accounted for when trying to understand data on patterns of sequence variation for genes with different transmission modes.

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