The question of whether or not soil hydraulic parameters of dualpermeability models (DPM) can be properly identified by inverse analysis of preferential water flow data has not been resolved to date. We applied a DPM based on two coupled Richards’ equations to compare the performance of inverse and forward simulations of laboratory preferential flow data. Infiltration and drainage experiments w...

Though concurrent design and construction has been lauded for reducing the time of the total processes, such an approach may make projects more uncertain and complex than those where a sequential design and construction process is used. The main sources of risk are iterative cycles that result from errors and changes introduced during the execution of concurrent design and construction. Such cy...

Work with the discrete sequence production (DSP) task has provided a substantial literature on discrete sequencing skill over the last decades. The purpose of the current article is to provide a comprehensive overview of this literature and of the theoretical progress that it has prompted. We start with a description of the DSP task and the phenomena that are typically observed with it. Then we...

We present a Bayesian nonparametric framework for multilevel clustering which utilizes grouplevel context information to simultaneously discover low-dimensional structures of the group contents and partitions groups into clusters. Using the Dirichlet process as the building block, our model constructs a product base-measure with a nested structure to accommodate content and context observations...

The assembly process of aeronautical panel usually involves numerous parts and subprocesses. Thus a large number of Finite Element Analysis (FEA) runs are required to construct its compliant Deviation Propagation Model (DPM), when using the traditional compliant assembly variation analysis methods such as the Method of Influence Coefficients and the Linear Contact method. In this paper, an effi...

Disease progression modeling (DPM) of Alzheimer's disease (AD) aims at revealing long term pathological trajectories from short term clinical data. Along with the ability of providing a data-driven description of the natural evolution of the pathology, DPM has the potential of representing a valuable clinical instrument for automatic diagnosis, by explicitly describing the biomarker transition ...

The purpose of this chapter is to present the design, analysis, and simulation of a wide class of algorithms that can be used for online parameter identification of continuous-time plants. The online identification procedure involves the following three steps. Step 1. Lump the unknown parameters in a vector θ∗ and express them in the form of the parametric model SPM, DPM, B-SPM, or B-DPM. Step ...

This paper presents an algorithm for finding the maximum a posteriori (MAP) clustering in a class of univariate product partition models. While the number of possible clusterings of n observations grows according to the Bell exponential number, the dynamic programming algorithm presented here exploits properties of the model to provide an O(n2) search. Hence, the algorithm can be used to find t...

Digital programmable metasurfaces (DPMs) can dynamically modulate electromagnetic waves in space, time, and frequency domains with powerful capabilities. In contrast, joint radar communication (JRC) is an important avenue to use the universally intelligently. Hence, combining DPM JRC may produce a promising way achieve universal intelligent terminals. Herein, mechanism of extremely flexible bas...

Labile memory is thought to be held in the brain as persistent neural network activity. However, it is not known how biologically relevant memory circuits are organized and operate. Labile and persistent appetitive memory in Drosophila requires output after training from the α'β' subset of mushroom body (MB) neurons and from a pair of modulatory dorsal paired medial (DPM) neurons. DPM neurons i...