The Experts below are selected from a list of 159 Experts worldwide ranked by ideXlab platform

Athanasios D. Panagopoulos - One of the best experts on this subject based on the ideXlab platform.

  • Cloud Attenuation Statistics Prediction From Ka-Band to Optical Frequencies: Integrated Liquid Water Content Field Synthesizer
    IEEE Transactions on Antennas and Propagation, 2017
    Co-Authors: Nikolaos K. Lyras, Charilaos I. Kourogiorgas, Athanasios D. Panagopoulos
    Abstract:

    The impact of cloud impairments on satellite links is increasing with the employment of higher frequency bands. In this paper, a Model for predicting cloud attenuation statistics for satellite communication systems operating from Ka-band to optical range is presented. The cloud attenuation must be accurately quantified for the reliable design of satellite communication systems. A Stochastic Dynamic Model for the generation of integrated liquid water content (ILWC) fields is proposed. The Model is based on the Stochastic differential equations and incorporates the spatial and temporal behavior of ILWC. Classifying the cloud types based on the cloud vertical extent and using the microphysical properties of clouds, the well-known Mie scattering theory and the global statistics for ILWC by International Telecommunications Union-Radio (ITU-R), a unified space-time Model for the prediction of induced attenuation due to clouds for frequencies above Ka-band up to optical range is presented. The proposed Model is tested in terms of first order statistics, compared first with ITU-R P.840-6 Model and then with data obtained in the literature, showing encouraging results. Moreover, the probability of cloud occurrence for optical satellite single and site diversity system is calculated. Finally, the limitations and the applicability of the proposed Model are discussed.

  • a rain attenuation Stochastic Dynamic Model for leo satellite systems above 10 ghz
    IEEE Transactions on Vehicular Technology, 2015
    Co-Authors: Charilaos I. Kourogiorgas, Athanasios D. Panagopoulos
    Abstract:

    In this paper, a new rain-attenuation Stochastic Dynamic channel Model for low Earth orbit (LEO) satellite links operating above 10 GHz is proposed, taking into account the time dependence of elevation angle and its impact on rain-attenuation Dynamics. The new synthesizer is based on the first-order Stochastic differential equations (SDEs) and extends the well-known Maseng–Bakken (M–B) Model for fixed satellite communication links. Moreover, an analytical closed-form expression of the rain-attenuation Dynamic parameter is derived and used in the proposed synthesizer. The new channel Model is validated in terms of the LEO-slant-path rain-attenuation exceedance probability. Finally, a new analytical Model for the calculation of fade-slope conditional exceedance probability is presented, which is then validated with accurate simulations. The new Models are directly applicable for the evaluation and design of fade mitigation techniques (FMTs) in LEO satellite systems operating at frequencies above 10 GHz.

  • satellite and terrestrial links rain attenuation time series generator for heavy rain climatic regions
    IEEE Transactions on Antennas and Propagation, 2013
    Co-Authors: S A Kanellopoulos, Charilaos I. Kourogiorgas, Athanasios D. Panagopoulos, J D Kanellopoulos
    Abstract:

    A new Stochastic Dynamic Model for the generation of rain attenuation time series for fixed satellite and Line-of-sight (LOS) terrestrial links operating above 10 GHz is presented. The Model's concept originate from the classic Maseng-Bakken (M-B) approach apart that it generates Gamma distributed rain attenuation time-series and not lognormal as in M-B approach. Gamma-distributed links are typical at heavy rain climatic regions where the new Model is expected to perform better than the M-B. The comparison with experimental results in terms of exceedance probability is very encouraging.

  • short term rain attenuation frequency scaling for satellite up link power control applications
    IEEE Transactions on Antennas and Propagation, 2013
    Co-Authors: Georgios A Karagiannis, Athanasios D. Panagopoulos, J D Kanellopoulos
    Abstract:

    In this paper, a novel Stochastic Dynamic Model for the short-term frequency scaling of rain attenuation is presented. The Model captures the Dynamic characteristics of the instantaneous frequency scaling factor and provides the means to incorporate them in simultaneous rain attenuation time series generation, as well as in analytical calculations. Moreover, an analytical framework is proposed for rain attenuation prediction at a given frequency based on the rain attenuation measured at another frequency. The proposed Model can be used for the timely activation of an open-loop up-link power control scheme in broadband satellite communication networks operating at frequencies above 10 GHz. It is applied to simulated rain attenuation data that have been obtained using the Synthetic Storm Technique on rain rate experimental data. Finally, it is shown how the new Model improves the performance of an up-link power control scheme in terms of system availability.

  • multidimensional rain attenuation Stochastic Dynamic Modeling application to earth space diversity systems
    IEEE Transactions on Antennas and Propagation, 2012
    Co-Authors: Georgios A Karagiannis, Athanasios D. Panagopoulos, J D Kanellopoulos
    Abstract:

    A Stochastic Dynamic Model for the induced rain attenuation on multiple radio links is presented in this paper. The Model is considered as a generalization of the well-known and well-accepted Maseng–Bakken Model in $n$ -dimensions. It incorporates the spatial and time behavior of the rain attenuation phenomena and provides an analytical expression for the transition probability distribution. It consists of a system of Stochastic differential equations (SDEs), which, except for the solid mathematical formulation of the correlated rain attenuation Stochastic processes, constitutes the general framework for the calculation of other statistical quantities useful for the radio system designers. The long-term statistics and the Dynamic properties of rain attenuation are used for the parameterization of the Model, without the constraint of any built-in assumptions of the rain field. Finally, the proposed Model is used for the generation of correlated rain attenuation time series on multiple satellite communication slant paths and especially to diversity schemes, including site and orbital (angle) diversity. The derived results from the Model are tested with respect to experimental long-term statistics for various geometries with very encouraging results. The limitations and the ranges of applicability of the Model for Earth–space diversity systems are reported, and the sensitivity of the Model on the crucial parameters is discussed.

J D Kanellopoulos - One of the best experts on this subject based on the ideXlab platform.

  • satellite and terrestrial links rain attenuation time series generator for heavy rain climatic regions
    IEEE Transactions on Antennas and Propagation, 2013
    Co-Authors: S A Kanellopoulos, Charilaos I. Kourogiorgas, Athanasios D. Panagopoulos, J D Kanellopoulos
    Abstract:

    A new Stochastic Dynamic Model for the generation of rain attenuation time series for fixed satellite and Line-of-sight (LOS) terrestrial links operating above 10 GHz is presented. The Model's concept originate from the classic Maseng-Bakken (M-B) approach apart that it generates Gamma distributed rain attenuation time-series and not lognormal as in M-B approach. Gamma-distributed links are typical at heavy rain climatic regions where the new Model is expected to perform better than the M-B. The comparison with experimental results in terms of exceedance probability is very encouraging.

  • short term rain attenuation frequency scaling for satellite up link power control applications
    IEEE Transactions on Antennas and Propagation, 2013
    Co-Authors: Georgios A Karagiannis, Athanasios D. Panagopoulos, J D Kanellopoulos
    Abstract:

    In this paper, a novel Stochastic Dynamic Model for the short-term frequency scaling of rain attenuation is presented. The Model captures the Dynamic characteristics of the instantaneous frequency scaling factor and provides the means to incorporate them in simultaneous rain attenuation time series generation, as well as in analytical calculations. Moreover, an analytical framework is proposed for rain attenuation prediction at a given frequency based on the rain attenuation measured at another frequency. The proposed Model can be used for the timely activation of an open-loop up-link power control scheme in broadband satellite communication networks operating at frequencies above 10 GHz. It is applied to simulated rain attenuation data that have been obtained using the Synthetic Storm Technique on rain rate experimental data. Finally, it is shown how the new Model improves the performance of an up-link power control scheme in terms of system availability.

  • multidimensional rain attenuation Stochastic Dynamic Modeling application to earth space diversity systems
    IEEE Transactions on Antennas and Propagation, 2012
    Co-Authors: Georgios A Karagiannis, Athanasios D. Panagopoulos, J D Kanellopoulos
    Abstract:

    A Stochastic Dynamic Model for the induced rain attenuation on multiple radio links is presented in this paper. The Model is considered as a generalization of the well-known and well-accepted Maseng–Bakken Model in $n$ -dimensions. It incorporates the spatial and time behavior of the rain attenuation phenomena and provides an analytical expression for the transition probability distribution. It consists of a system of Stochastic differential equations (SDEs), which, except for the solid mathematical formulation of the correlated rain attenuation Stochastic processes, constitutes the general framework for the calculation of other statistical quantities useful for the radio system designers. The long-term statistics and the Dynamic properties of rain attenuation are used for the parameterization of the Model, without the constraint of any built-in assumptions of the rain field. Finally, the proposed Model is used for the generation of correlated rain attenuation time series on multiple satellite communication slant paths and especially to diversity schemes, including site and orbital (angle) diversity. The derived results from the Model are tested with respect to experimental long-term statistics for various geometries with very encouraging results. The limitations and the ranges of applicability of the Model for Earth–space diversity systems are reported, and the sensitivity of the Model on the crucial parameters is discussed.

David Zilberman - One of the best experts on this subject based on the ideXlab platform.

  • innovation subsidies versus consumer subsidies a real options analysis of solar energy
    Energy Policy, 2016
    Co-Authors: Kiran Torani, Gordon C Rausser, David Zilberman
    Abstract:

    Abstract Given the interest in the commercialization of affordable, clean energy technologies, we examine the prospects of solar photovoltaics (PV). We consider the question of how to transition to a meaningful percentage of solar energy in a sustainable manner and which policies are most effective in accelerating adoption. This paper develops a Stochastic Dynamic Model of the adoption of solar PV in the residential and commercial sector under two sources of uncertainty – the price of electricity and cost of solar. The analytic results suggest that a high rate of innovation may delay adoption of a new technology if the consumer has rational price expectations. We simulate the Model across alternative rates technological change, electricity prices, subsidies and carbon taxes. It is shown that there will be a displacement of incumbent technologies and a widespread shift towards solar PV in under 30 years – and that this can occur without consumer incentives and carbon pricing. We show that these policies have a modest impact in accelerating adoption, and that they may not be an effective part of climate policy. Instead, results demonstrate that further technological change is the crucial determinant and main driver of adoption. Further, results indicate that subsidies and taxes become increasingly ineffective with higher rates of technological change.

  • a Model of investment under uncertainty modern irrigation technology and emerging markets in water
    Social Science Research Network, 2002
    Co-Authors: Janis M Carey, David Zilberman
    Abstract:

    This article develops a Stochastic Dynamic Model of irrigation technology adoption. It predicts that farms will not invest in modern technologies unless the expected present value of investment exceeds the cost by a potentially large hurdle rate. The article also demonstrates that, contrary to common belief, water markets can delay adoption. The introduction of a market should induce farms with abundant (scarce) water supplies to adopt earlier (later) than they would otherwise. This article was motivated by evidence that, contrary to NPV predictions, farms wait until random events such as drought drive returns significantly above costs before investing in modern irrigation technologies.

  • a Model of investment under uncertainty modern irrigation technology and emerging markets in water
    American Journal of Agricultural Economics, 2002
    Co-Authors: Janis M Carey, David Zilberman
    Abstract:

    This article develops a Stochastic Dynamic Model of irrigation technology adoption. It predicts that farms will not invest in modern technologies unless the expected present value of investment exceeds the cost by a potentially large hurdle rate. The article also demonstrates that, contrary to common belief, water markets can delay adoption. The introduction of a market should induce farms with abundant (scarce) water supplies to adopt earlier (later) than they would otherwise. This article was motivated by evidence that, contrary to NPV predictions, farms wait until random events such as drought drive returns significantly above costs before investing in modern irrigation technologies. Copyright 2002, Oxford University Press.

Charilaos I. Kourogiorgas - One of the best experts on this subject based on the ideXlab platform.

  • Cloud Attenuation Statistics Prediction From Ka-Band to Optical Frequencies: Integrated Liquid Water Content Field Synthesizer
    IEEE Transactions on Antennas and Propagation, 2017
    Co-Authors: Nikolaos K. Lyras, Charilaos I. Kourogiorgas, Athanasios D. Panagopoulos
    Abstract:

    The impact of cloud impairments on satellite links is increasing with the employment of higher frequency bands. In this paper, a Model for predicting cloud attenuation statistics for satellite communication systems operating from Ka-band to optical range is presented. The cloud attenuation must be accurately quantified for the reliable design of satellite communication systems. A Stochastic Dynamic Model for the generation of integrated liquid water content (ILWC) fields is proposed. The Model is based on the Stochastic differential equations and incorporates the spatial and temporal behavior of ILWC. Classifying the cloud types based on the cloud vertical extent and using the microphysical properties of clouds, the well-known Mie scattering theory and the global statistics for ILWC by International Telecommunications Union-Radio (ITU-R), a unified space-time Model for the prediction of induced attenuation due to clouds for frequencies above Ka-band up to optical range is presented. The proposed Model is tested in terms of first order statistics, compared first with ITU-R P.840-6 Model and then with data obtained in the literature, showing encouraging results. Moreover, the probability of cloud occurrence for optical satellite single and site diversity system is calculated. Finally, the limitations and the applicability of the proposed Model are discussed.

  • a rain attenuation Stochastic Dynamic Model for leo satellite systems above 10 ghz
    IEEE Transactions on Vehicular Technology, 2015
    Co-Authors: Charilaos I. Kourogiorgas, Athanasios D. Panagopoulos
    Abstract:

    In this paper, a new rain-attenuation Stochastic Dynamic channel Model for low Earth orbit (LEO) satellite links operating above 10 GHz is proposed, taking into account the time dependence of elevation angle and its impact on rain-attenuation Dynamics. The new synthesizer is based on the first-order Stochastic differential equations (SDEs) and extends the well-known Maseng–Bakken (M–B) Model for fixed satellite communication links. Moreover, an analytical closed-form expression of the rain-attenuation Dynamic parameter is derived and used in the proposed synthesizer. The new channel Model is validated in terms of the LEO-slant-path rain-attenuation exceedance probability. Finally, a new analytical Model for the calculation of fade-slope conditional exceedance probability is presented, which is then validated with accurate simulations. The new Models are directly applicable for the evaluation and design of fade mitigation techniques (FMTs) in LEO satellite systems operating at frequencies above 10 GHz.

  • satellite and terrestrial links rain attenuation time series generator for heavy rain climatic regions
    IEEE Transactions on Antennas and Propagation, 2013
    Co-Authors: S A Kanellopoulos, Charilaos I. Kourogiorgas, Athanasios D. Panagopoulos, J D Kanellopoulos
    Abstract:

    A new Stochastic Dynamic Model for the generation of rain attenuation time series for fixed satellite and Line-of-sight (LOS) terrestrial links operating above 10 GHz is presented. The Model's concept originate from the classic Maseng-Bakken (M-B) approach apart that it generates Gamma distributed rain attenuation time-series and not lognormal as in M-B approach. Gamma-distributed links are typical at heavy rain climatic regions where the new Model is expected to perform better than the M-B. The comparison with experimental results in terms of exceedance probability is very encouraging.

Zidong Wang - One of the best experts on this subject based on the ideXlab platform.

  • Modeling throughput of emergency departments via time series an expectation maximization algorithm
    ACM Transactions on Management Information Systems, 2013
    Co-Authors: Zidong Wang, Xiaohui Liu, Julie Eatock, Sally Mcclean, Dongmei Liu, Terry Young
    Abstract:

    In this article, the expectation maximization (EM) algorithm is applied for Modeling the throughput of emergency departments via available time-series data. The Dynamics of emergency department throughput is developed and evaluated, for the first time, as a Stochastic Dynamic Model that consists of the noisy measurement and first-order autoregressive (AR) Stochastic Dynamic process. By using the EM algorithm, the Model parameters, the actual throughput, as well as the noise intensity, can be identified simultaneously. Four real-world time series collected from an emergency department in West London are employed to demonstrate the effectiveness of the introduced algorithm. Several quantitative indices are proposed to evaluate the inferred Models. The simulation shows that the identified Model fits the data very well.

  • Time Series Modeling of Nano-Gold Immunochromatographic Assay via Expectation Maximization Algorithm
    IEEE Transactions on Biomedical Engineering, 2013
    Co-Authors: Nianyin Zeng, Zidong Wang, Yurong Li, Min Du
    Abstract:

    In this paper, the expectation maximization (EM) algorithm is applied to the Modeling of the nano-gold immunochromatographic assay (nano-GICA) via available time series of the measured signal intensities of the test and control lines. The Model for the nano-GICA is developed as the Stochastic Dynamic Model that consists of a first-order autoregressive Stochastic Dynamic process and a noisy measurement. By using the EM algorithm, the Model parameters, the actual signal intensities of the test and control lines, as well as the noise intensity can be identified simultaneously. Three different time series data sets concerning the target concentrations are employed to demonstrate the effectiveness of the introduced algorithm. Several indices are also proposed to evaluate the inferred Models. It is shown that the Model fits the data very well.

  • Stochastic Dynamic Modeling of short gene expression time series data
    IEEE Transactions on Nanobioscience, 2008
    Co-Authors: Zidong Wang, Fuwen Yang, Stephen Swift, Allan Tucker, Xiaohui Liu
    Abstract:

    In this paper, the expectation maximization (EM) algorithm is applied for Modeling the gene regulatory network from gene time-series data. The gene regulatory network is viewed as a Stochastic Dynamic Model, which consists of the noisy gene measurement from microarray and the gene regulation first-order autoregressive (AR) Stochastic Dynamic process. By using the EM algorithm, both the Model parameters and the actual values of the gene expression levels can be identified simultaneously. Moreover, the algorithm can deal with the sparse parameter identification and the noisy data in an efficient way. It is also shown that the EM algorithm can handle the microarray gene expression data with large number of variables but a small number of observations. The gene expression Stochastic Dynamic Models for four real-world gene expression data sets are constructed to demonstrate the advantages of the introduced algorithm. Several indices are proposed to evaluate the Models of inferred gene regulatory networks, and the relevant biological properties are discussed.