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AuthorAlouini, Mohamed-Slim (1140)Ooi, Boon S. (276)Ng, Tien Khee (222)Salama, Khaled N. (213)Bajic, Vladimir B. (209)View MoreDepartment

Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division (6072)

Electrical Engineering Program (2996)Physical Sciences and Engineering (PSE) Division (1197)Applied Mathematics and Computational Science Program (1138)Computer Science Program (1019)View MoreJournalIEEE Transactions on Wireless Communications (108)IEEE Transactions on Communications (96)Scientific Reports (77)IEEE Transactions on Vehicular Technology (68)IEEE Access (66)View MoreKAUST Acknowledged Support UnitOffice of Sponsored Research (OSR) (19)Supercomputing Laboratory (19)Office of Sponsored Research (11)Technology Innovation Center (10)OSR (9)View MoreKAUST Grant NumberBAS/1/1614-01-01 (66)OSR-2015-CRG4-2582 (49)BAS/1/1606-01-01 (25)BAS/1/1664-01-01 (23)URF/1/1976-02 (21)View MorePatent StatusPublished Application (117)Granted Patent (32)PublisherInstitute of Electrical and Electronics Engineers (IEEE) (2251)Springer Nature (630)Elsevier BV (591)Wiley (268)Association for Computing Machinery (ACM) (155)View MoreSubjectoutage probability (35)Optimization (34)Interference (33)Signal to noise ratio (32)MIMO (31)View MoreTypeArticle (3408)Conference Paper (1866)Poster (238)Preprint (168)Patent (149)View MoreYear (Issue Date)2019 (592)2018 (898)2017 (900)2016 (771)2015 (742)View MoreItem AvailabilityOpen Access (3217)Metadata Only (2678)Embargoed (177)

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Dimension-independent likelihood-informed MCMC

Cui, Tiangang; Law, Kody; Marzouk, Youssef M. (Journal of Computational Physics, Elsevier BV, 2015-10-08) [Article]

Many Bayesian inference problems require exploring the posterior distribution of high-dimensional parameters that represent the discretization of an underlying function. This work introduces a family of Markov chain Monte Carlo (MCMC) samplers that can adapt to the particular structure of a posterior distribution over functions. Two distinct lines of research intersect in the methods developed here. First, we introduce a general class of operator-weighted proposal distributions that are well defined on function space, such that the performance of the resulting MCMC samplers is independent of the discretization of the function. Second, by exploiting local Hessian information and any associated low-dimensional structure in the change from prior to posterior distributions, we develop an inhomogeneous discretization scheme for the Langevin stochastic differential equation that yields operator-weighted proposals adapted to the non-Gaussian structure of the posterior. The resulting dimension-independent and likelihood-informed (DILI) MCMC samplers may be useful for a large class of high-dimensional problems where the target probability measure has a density with respect to a Gaussian reference measure. Two nonlinear inverse problems are used to demonstrate the efficiency of these DILI samplers: an elliptic PDE coefficient inverse problem and path reconstruction in a conditioned diffusion.

Spectral analysis in thin tubes with axial heterogeneities

Ferreira, Rita; Mascarenhas, M. Luísa; Piatnitski, Andrey (Portugaliae Mathematica, European Mathematical Publishing House, 2015) [Article]

In this paper, we present the 3D-1D asymptotic analysis of the Dirichlet spectral problem associated with an elliptic operator with axial periodic heterogeneities. We extend to the 3D-1D case previous 3D-2D results (see [10]) and we analyze the special case where the scale of thickness is much smaller than the scale of the heterogeneities and the planar coefficient has a unique global minimum in the periodic cell. These results are of great relevance in the comprehension of the wave propagation in nanowires showing axial heterogeneities (see [17]).

Different Power Adaption Methods on Fluctuating Two-Ray Fading Channels

Zhao, Hui; Liu, Zhedong; Alouini, Mohamed-Slim (IEEE Wireless Communications Letters, Institute of Electrical and Electronics Engineers (IEEE), 2018-11-14) [Article]

In this letter, we consider a typical scenario where the transmitter employs different power adaption methods, including the optimal rate and power algorithm, optimal rate adaption, channel inversion and truncated channel inversion, to enhance the ergodic capacity (EC) with an average transmit power constraint over fluctuating two-way fading channels. In
particular, we derive exact closed-form expressions for the EC under different power adaption methods, as well as correspond-
ing asymptotic formulas for the EC valid in the high signal-to- noise ratio (SNR) region. Finally, we compare the performance
of the EC under different power adaption methods, and this also validates the accuracy of our derived expressions for the exact
and asymptotic EC.

Ranking-based Method for News Stance Detection

Zhang, Qiang; Yilmaz, Emine; Liang, Shangsong (Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18, Association for Computing Machinery (ACM), 2018-04-18) [Conference Paper]

A valuable step towards news veracity assessment is to understand stance from different information sources, and the process is known as the stance detection. Specifically, the stance detection is to detect four kinds of stances (

Homogenization of the stochastic Navier–Stokes equation with a stochastic slip boundary condition

Bessaih, Hakima; Maris, Razvan Florian (Applicable Analysis, Informa UK Limited, 2015-11-02) [Article]

The two-dimensional Navier–Stokes equation in a perforated domain with a dynamical slip boundary condition is considered. We assume that the dynamic is driven by a stochastic perturbation on the interior of the domain and another stochastic perturbation on the boundaries of the holes. We consider a scaling (ᵋ for the viscosity and 1 for the density) that will lead to a time-dependent limit problem. However, the noncritical scaling (ᵋ, β > 1) is considered in front of the nonlinear term. The homogenized system in the limit is obtained as a Darcy’s law with memory with two permeabilities and an extra term that is due to the stochastic perturbation on the boundary of the holes. The nonhomogeneity on the boundary contains a stochastic part that yields in the limit an additional term in the Darcy’s law. We use the two-scale convergence method after extending the solution with 0 inside the holes to pass to the limit. By Itô stochastic calculus, we get uniform estimates on the solution in appropriate spaces. Due to the stochastic integral, the pressure that appears in the variational formulation does not have enough regularity in time. This fact made us rely only on the variational formulation for the passage to the limit on the solution. We obtain a variational formulation for the limit that is solution of a Stokes system with two pressures. This two-scale limit gives rise to three cell problems, two of them give the permeabilities while the third one gives an extra term in the Darcy’s law due to the stochastic perturbation on the boundary of the holes.

Ferrite LTCC based phased array antennas

Ghaffar, Farhan A.; Nafe, Ahmed A.; Shamim, Atif (2016 IEEE International Symposium on Antennas and Propagation (APSURSI), Institute of Electrical and Electronics Engineers (IEEE), 2016-11-02) [Conference Paper]

Two phased array antennas realized in multilayer ferrite LTCC technology are presented in this paper. The use of embedded bias windings in these designs allows the negation of external magnets which are conventionally employed with bulk ferrite medium. This reduces the required magnetostatic field strength by 90% as compared to the traditional designs. The phase shifters are implemented using the SIW technology. One of the designs is operated in the half mode waveguide topology while the other design is based on standard full mode waveguide operation. The two phase shifter designs are integrated with two element patch antenna array and slotted SIW array respectively. The array designs demonstrate a beam steering of 30° and ±19° respectively for a current excitation of 200 mA. The designs, due to their small factor can be easily integrated in modern communication systems which is not possible in the case of bulk ferrite based designs.

An improved Density-Based Approach to Spatio–Textual Clustering on Social Media

Nguyen, Minh D.; Shin, Won-Yong (IEEE Access, Institute of Electrical and Electronics Engineers (IEEE), 2019-03-04) [Article]

Density-based spatial clustering of applications with noise (DBSCAN) is the most commonly used density-based clustering algorithm but may not be sufficient when the input data type is heterogeneous in terms of textual description. When we aim to discover clusters of geo-tagged records relevant to a particular point of interest (POI) on social media, examining only one type of input data (e.g., the tweets relevant to a POI) may draw an incomplete picture of clusters due to noisy regions. To overcome this problem, we introduce DBSTexC , a newly defined density-based clustering algorithm using spatio-textual information on social media (e.g., Twitter). We first characterize the POI-relevant and POI-irrelevant geo-tagged tweets as the texts that include and do not include a POI name or its semantically coherent variations, respectively. By leveraging the proportion of the POI-relevant and POI-irrelevant tweets, the proposed algorithm demonstrates much higher clustering performance than the DBSCAN case in terms of F1 score and its variants. While DBSTexC performs exactly as DBSCAN with the textually homogeneous inputs, it far outperforms DBSCAN with the textually heterogeneous inputs. Furthermore, to further improve the clustering quality by fully capturing the geographic distribution of geo-tagged points, we present fuzzy DBSTexC ( F-DBSTexC ), an extension of DBSTexC , which incorporates the notion of fuzzy clustering into the DBSTexC . We then demonstrate the consistent superiority of F-DBSTexC over the original DBSTexC via intensive experiments. The computational complexity of our algorithms is also analytically and numerically shown.

A Posteriori Error Analysis for Evolution Nonlinear Schrödinger Equations up to the Critical Exponent

Katsaounis, Theodoros; Kyza, Irene (SIAM Journal on Numerical Analysis, Society for Industrial & Applied Mathematics (SIAM), 2018-05-17) [Article]

We provide a posteriori error estimates in the L([0, T]; L(?))-norm for relaxation time discrete and fully discrete schemes for a class of evolution nonlinear Schrödinger equations up to the critical exponent. In particular for the discretization in time we use the relaxation Crank–Nicolson-type scheme introduced by Besse in [SIAM J. Numer. Anal., 42 (2004), pp. 934–952]. The space discretization consists of finite element spaces that are allowed to change between time steps. The estimates are obtained using the reconstruction technique. Through this technique the problem is converted to a perturbation of the original partial differential equation and this makes it possible to use nonlinear stability arguments as in the continuous problem. Our analysis includes as special cases the cubic and quintic nonlinear Schrödinger equations in one spatial dimension and the cubic nonlinear Schrödinger equation in two spatial dimensions. Numerical results illustrate that the estimates are indeed of optimal order of convergence.

665 Nail lesions in 30 old inbred mouse strains

Linn, S.C.; Mustonen, A.M.; Silva, K.A.; Kennedy, V.E.; Sundberg, B.A.; Bechtold, L.S.; Cusolito, L.R.; Alghamdi, S.; Hoehndorf, Robert; Schofield, P.N.; Sundberg, J.P. (Journal of Investigative Dermatology, Elsevier BV, 2018-04-19) [Poster]

Parametrizing coarse grained models for molecular systems at equilibrium

Kalligiannaki, Evangelia; Chazirakis, A.; Tsourtis, A.; Katsoulakis, M. A.; Plecháč, P.; Harmandaris, V. (The European Physical Journal Special Topics, Springer Nature, 2016-10-18) [Article]

Hierarchical coarse graining of atomistic molecular systems at equilibrium has been an intensive research topic over the last few decades. In this work we (a) review theoretical and numerical aspects of different parametrization methods (structural-based, force matching and relative entropy) to derive the effective interaction potential between coarse-grained particles. All methods approximate the many body potential of mean force; resulting, however, in different optimization problems. (b) We also use a reformulation of the force matching method by introducing a generalized force matching condition for the local mean force in the sense that allows the approximation of the potential of mean force under both linear and non-linear coarse graining mappings (E. Kalligiannaki, et al., J. Chem. Phys. 2015). We apply and compare these methods to: (a) a benchmark system of two isolated methane molecules; (b) methane liquid; (c) water; and (d) an alkane fluid. Differences between the effective interactions, derived from the various methods, are found that depend on the actual system under study. The results further reveal the relation of the various methods and the sensitivities that may arise in the implementation of numerical methods used in each case.

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