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RECONSTRUCTION OF AN INTERFACE BETWEEN THE FLUID AND PIEZOELECTRIC SOLID BY ACOUSTIC MEASUREMENTS
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| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Siam Journal On Applied Mathematics |
| Volume / Edisi | : | 83 (No. 5) |
| Halaman | : | 2073-2095 |
| Abstrak | : | In this paper, we consider an inverse interaction scattering problem of recovering an interface between the fluid and piezoelectric solid from acoustic measurements. First, the well posedness of the interaction model is shown in associated function spaces by the variational method. Then new uniqueness results are proved for the inverse problem by taking far-field data at one fixed frequency, based on a uniform a priori estimate of the solutions of the interaction model. With these results, the factorization method is then justified to reconstruct the shape and location of the interface between the fluid and piezoelectric solid. Finally, we investigate an associated interior transmission eigenvalue problem, and show that the set of interior transmission eigenvalues is at most discrete and with no finite accumulation point under a natural assumption on physical coefficients |
ARSIP BELANDA DI MASA REVOLUSI INDONESIA
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Berita Arsip Nasional RI |
| Volume / Edisi | : | -/16, DESEMBER (No. 16) |
| Halaman | : | 5-8 |
| Abstrak | : | - |
DERIVATION AND STABILITY ANALYSIS OF A MACROSCOPIC MULTILANE MODEL FOR TRAFFIC FLOW
| Pengarang | : | Puppo, Gabriella,Herty Michael,Piu, Matteo |
| Nama Majalah/Jurnal | : | Siam Journal On Applied Mathematics |
| Volume / Edisi | : | 83 (No. 5) |
| Halaman | : | 2052-2072 |
| Abstrak | : | The mathematical modeling and the stability analysis of multilane traffic in the macroscopic scale is considered. We propose a new first order model derived from microscopic dy namics with lane changing, leading to a coupled system of hyperbolic balance laws. The macroscopic limit is derived without assuming ad hoc space and time scalings. The analysis of the stability of the equilibria of the model is discussed. The proposed numerical tests confirm the theoretical findings between the macroscopic and microscopic modeling, and the results of the stability analysis. |
ARSIP DAN NILAI GUNANYA
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Berita Arsip Nasional RI |
| Volume / Edisi | : | -/16, DESEMBER (No. 16) |
| Halaman | : | 1-4 |
| Abstrak | : | - |
A Tuning-free Robust and Efficient Approach to High-dimensional Regression
| Pengarang | : | Lan Wang |
| Nama Majalah/Jurnal | : | Journal of the American Statistical Association |
| Volume / Edisi | : | 115 (No. 532) |
| Halaman | : | 1700-1714 |
| Abstrak | : | We introduce a novel approach for high-dimensional regression with theoretical guarantees. The new procedure overcomes the challenge of tuning parameter selection of Lasso and possesses several appealing properties. It uses an easily simulated tuning parameter that automatically adapts to both the unknown random error distribution and the correlation structure of the design matrix. It is robust with substantial efficiency gain for heavy-tailed random errors while maintaining high efficiency for normal random errors. Comparing with other alternative robust regression procedures, it also enjoys the property of being equivariant when the response variable undergoes a scale transformation. Computationally, it can be efficiently solved via linear programming. Theoretically, under weak conditions on the random error distribution, we establish a finite-sample error bound with a near-oracle rate for the new estimator with the simulated tuning parameter. Our results make useful contributions to mending the gap between the practice and theory of Lasso and its variants. We also prove that further improvement in efficiency can be achieved by a second-stage enhancement with some light tuning. Our simulation results demonstrate that the proposed methods often outperform cross-validated Lasso in various settings. |
Template Independent Component Analysis: Targeted and Reliable Estimation of Subject-level Brain Networks Using Big Data Population Priors
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Journal of the American Statistical Association |
| Volume / Edisi | : | 115 (No. 531) |
| Halaman | : | 1151-1177 |
| Abstrak | : | Large brain imaging databases contain a wealth of information on brain organization in the populations they target, and on individual variability. While such databases have been used to study group-level features of populations directly, they are currently underutilized as a resource to inform single-subject analysis. Here, we propose leveraging the information contained in large functional magnetic resonance imaging (fMRI) databases by establishing population priors to employ in an empirical Bayesian framework. We focus on estimation of brain networks as source signals in independent component analysis (ICA). We formulate a hierarchical “template” ICA model where source signals—including known population brain networks and subject-specific signals—are represented as latent variables. For estimation, we derive an expectation–maximization (EM) algorithm having an explicit solution. However, as this solution is computationally intractable, we also consider an approximate subspace algorithm and a faster two-stage approach. Through extensive simulation studies, we assess performance of both methods and compare with dual regression, a popular but ad-hoc method. The two proposed algorithms have similar performance, and both dramatically outperform dual regression. We also conduct a reliability study utilizing the Human Connectome Project and find that template ICA achieves substantially better performance than dual regression, achieving 75–250% higher intra-subject reliability. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement. |
Estimating the Effects of Fine Particulate Matter on 432 Cardiovascular Diseases Using Multi-Outcome Regression With Tree-Structured Shrinkage
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Journal of the American Statistical Association |
| Volume / Edisi | : | 115 (No. 532) |
| Halaman | : | 1689-1699 |
| Abstrak | : | The positive relationship between airborne fine particulate matter (PM2.5) and cardiovascular disease (CVD) is established. Little is known about effect size heterogeneity across distinct CVD outcomes. We conducted a multi-outcome case-crossover study of Medicare beneficiaries aged >65 years residing in the mainland USA from 2000 through 2012. The exposure was two-day average PM2.5 in each individual’s residential zipcode. The outcomes were hospitalization for 432 distinct CVDs defined by the International Classification of Diseases, Revision 9. Our dataset included almost 24 million CVD hospitalizations. We analyzed the data using multi-outcome regression with tree-structured shrinkage (MOReTreeS), a novel method that enables: (1) borrowing of strength across outcomes; (2) data-driven discovery of outcome groups that are similarly affected by the exposure; (3) estimation of a single effect for each group. MOReTreeS grouped 420 outcomes together; for this group, the odds ratio [OR] for hospitalization associated with a 10 μg m− 3 increase in PM2.5 was 1.011 (95% credible interval [CI] = 1.011–1.012). The model identified congestive heart failure as having the strongest positive association with PM2.5 (OR = 1.019; 95%CI = 1.017–1.022). Some outcomes exhibited negative associations with PM2.5, including aortic dissection, subarachnoid and intracerebral hemorrhage, abdominal aneurysm, and essential hypertension; further research is needed to understand these counterintuitive findings. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement. |
SIMILARITY SUPPRESSES CYCLICITY: WHY SIMILAR COMPETITORS FORM HIERARCHIES
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Siam Journal On Applied Mathematics |
| Volume / Edisi | : | 83 (No. 5) |
| Halaman | : | 2027-2051 |
| Abstrak | : | Competitive systems can exhibit both hierarchical (transitive) and cyclic (intransi tive) structures. Despite theoretical interest in cyclic competition, which offers richer dynamics and occupies a larger subset of the scope of possible competitive systems, most real-world systems are predominantly transitive. Why? Here, we introduce a generic mechanism that promotes transitivity, even when there is ample room for cyclicity. We demonstrate that, if competitive outcomes depend smoothly on competitor attributes, then similar competitors compete transitively. We quantify the rate of convergence to transitivity given the similarity of the competitors and the smoothness of the performance function. Thus, we prove the adage regarding apples and oranges. Similar objects admit well-ordered comparisons; diverse objects may not. |
DATA-DRIVEN BASIS FOR RECONSTRUCTING THE CONTRASTIN INVERSE SCATTERING: PICARD CRITERION, REGULARITY, REGULARIZATION, AND STABILITY
| Pengarang | : | Meng, Shixu |
| Nama Majalah/Jurnal | : | Siam Journal On Applied Mathematics |
| Volume / Edisi | : | 83 (No. 5) |
| Halaman | : | 2003-2026 |
| Abstrak | : | We consider the inverse medium scattering of reconstructing the medium contrast using Born data, including the full-aperture, limited-aperture, and multifrequency data. We propose data-driven basis functions for these inverse problems based on the generalized prolate spheroidal wave functions and related eigenfunctions. Such data-driven eigenfunctions are eigenfunctions of a Fourier integral operator; they remarkably extend analytically to the whole space, are doubly orthogonal, and are complete in the class of band-limited functions. We first establish a Picard criterion for reconstructing the contrast using the data-driven basis, where the reconstruction formula can also be understood from the viewpoint of data processing and analytic extrapolation. Another salient feature associated with the generalized prolate spheroidal wave functions is that the data driven basis for a disk is also a basis for a Sturm-Liouville differential operator. With the help of Sturm-Liouville theory, we estimate the L2 approximation error for a spectral cutoff approximation of Hs functions. This yields a spectral cutoff regularization strategy for noisy data and an explicit stability estimate for contrast in Hs (0 < s < 1/2) in the full-aperture case. In the limited-aperture and multifrequency cases, we also obtain spectral cutoff regularization strategies for noisy data and stability estimates for a class of contrast. |
ANALYSIS OF A REACTION-DIFFUSION SIR EPIDEMIC MODEL WITH NONCOMPLIANT BEHAVIOR
| Pengarang | : | Parkinson, Christian,Wang, Weinan |
| Nama Majalah/Jurnal | : | Siam Journal On Applied Mathematics |
| Volume / Edisi | : | 83 (No. 5) |
| Halaman | : | 1969-2002 |
| Abstrak | : | Recent work by public health experts suggests that incorporating human behavior is crucial in faithfully modeling an epidemic. We present a reaction-diffusion partial differential equation SIR-type population model for an epidemic including behavioral concerns. In our model, the disease spreads via mass action, as is customary in compartmental models. However, drawing from social contagion theory, we assume that as the disease spreads and prevention measures are enacted, noncompliance with prevention measures also spreads throughout the population. We prove global existence of classical solutions of our model, and then perform \scrR 0-type analysis and determine asymptotic behavior of the model in different parameter regimes. Finally, we simulate the model and discuss the new facets which distinguish our model from basic SIR-type models. |