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The textbook is primarily written for senior undergraduate and post graduate students studying in areas of computer science and engineering, and electrical engineering. However, as the subject covers various interdisciplinary areas, the book is also expected to be of interest to a larger readership in Science and Engineering. It has a comprehensive and balanced coverage of theory and applications of computer vision with a textbook approach providing worked out examples, and exercises. It covers theory and applications of some relatively recent advancements in technology such as on colour processing, deep learning techniques for processing images and videos, document processing, biometry, content based image retrieval, etc. It also delves with theories and processing in non-optical imaging systems, such as range or depth imaging, medical imaging and remote sensing imaging.
We derive boundary conditions for two-dimensional parallel and non-parallel flows at the interface of a homogeneous and isotropic porous medium and an overlying fluid layer by solving a macroscopic closure problem based on the asymptotic solution to the generalised transport equations (GTE) in the interfacial region. We obtained jump boundary conditions at the effective sharp surface dividing the homogeneous fluid and porous layers for either the Darcy or the Darcy–Brinkman equations. We discuss the choice of the location of the dividing surface and propose choices which reduce the distance with the GTE solutions. We propose an ad hoc expression of the permeability distribution within the interfacial region which enables us to preserve the invariance of the fluid-side-averaged velocity profile with respect to the radius $r_0$ of the averaging volume. Solutions to the GTE, equipped with the proposed permeability distribution, compare favourably with the averaged solutions to the pore-scale simulations when the interfacial thickness $\delta$ is adjusted to $r_0$. Numerical tests for parallel and non-parallel flows using the obtained jump boundary conditions or the generalised transport equations show quantitative agreement with the GTE solutions, with experiments and pore-scale simulations. The proposed model of mass and momentum transport is predictive, requiring solely information on the bulk porosity and permeability and the location of the solid matrix of the porous medium. Our results suggest that the Brinkman corrections may be avoided if the ratio $a=\delta /\delta _B$ of the thickness $\delta$ of the interfacial region to the Brinkman penetration depth $\delta _B$ is large enough, as the Brinkman sub-layer is entirely contained within the interfacial region in that case. Our formulation has been extended to anisotropic porous media and can be easily dealt with for three-dimensional configurations.
To quantify the impact of patient- and unit-level risk adjustment on infant hospital-onset bacteremia (HOB) standardized infection ratio (SIR) ranking.
Design:
A retrospective, multicenter cohort study.
Setting and participants:
Infants admitted to 284 neonatal intensive care units (NICUs) in the United States between 2016 and 2021.
Methods:
Expected HOB rates and SIRs were calculated using four adjustment strategies: birthweight (model 1), birthweight and postnatal age (model 2), birthweight and NICU complexity (model 3), and birthweight, postnatal age, and NICU complexity (model 4). Sites were ranked according to the unadjusted HOB rate, and these rankings were compared to rankings based on the four adjusted SIR models.
Results:
Compared to unadjusted HOB rate ranking (smallest to largest), the number and proportion of NICUs that left the fourth quartile (worst-performing) following adjustments were as follows: adjusted for birthweight (16, 22.5%), birthweight and postnatal age (19, 26.8%), birthweight and NICU complexity (22, 31.0%), birthweight, postnatal age and NICU complexity (23, 32.4%). Comparing NICUs that moved into the better-performing quartiles after birthweight adjustment to those that remained in the better-performing quartiles regardless of adjustment, the median percentage of low birthweight infants was 17.1% (Interquartile Range (IQR): 15.8, 19.2) vs 8.7% (IQR: 4.8, 12.6); and the median percentage of infants who died was 2.2% (IQR: 1.8, 3.1) vs 0.5% (IQR: 0.01, 12.0), respectively.
Conclusion:
Adjusting for patient and unit-level complexity moved one-third of NICUs in the worst-performing quartile into a better-performing quartile. Risk adjustment may allow for a more accurate comparison across units with varying levels of patient acuity and complexity.
Inspired by work of Andrews and Newman [‘Partitions and the minimal excludant’, Ann. Comb.23 (2019), 249–254] on the minimal excludant or ‘mex’ of partitions, we define four new classes of minimal excludants for overpartitions and establish relations to certain functions due to Ramanujan.
Understanding how the adult human brain learns novel categories is an important problem in neuroscience. Drift-diffusion models are popular in such contexts for their ability to mimic the underlying neural mechanisms. One such model for gradual longitudinal learning was recently developed in Paulon et al. (J Am Stat Assoc 116:1114–1127, 2021). In practice, category response accuracies are often the only reliable measure recorded by behavioral scientists to describe human learning. Category response accuracies are, however, often the only reliable measure recorded by behavioral scientists to describe human learning. To our knowledge, however, drift-diffusion models for such scenarios have never been considered in the literature before. To address this gap, in this article, we build carefully on Paulon et al. (J Am Stat Assoc 116:1114–1127, 2021), but now with latent response times integrated out, to derive a novel biologically interpretable class of ‘inverse-probit’ categorical probability models for observed categories alone. However, this new marginal model presents significant identifiability and inferential challenges not encountered originally for the joint model in Paulon et al. (J Am Stat Assoc 116:1114–1127, 2021). We address these new challenges using a novel projection-based approach with a symmetry-preserving identifiability constraint that allows us to work with conjugate priors in an unconstrained space. We adapt the model for group and individual-level inference in longitudinal settings. Building again on the model’s latent variable representation, we design an efficient Markov chain Monte Carlo algorithm for posterior computation. We evaluate the empirical performance of the method through simulation experiments. The practical efficacy of the method is illustrated in applications to longitudinal tone learning studies.
This comprehensive textbook combines the theoretical principles of engineering hydrology together with their practical applications, using modern industry-standard software. The textbook is written by the combination of a practitioner of water resources engineering with over 30 years of professional experience and a highly respected academic and recognized world authority in hydrology. Examples are drawn from global case studies, with exercises available online. The book begins with a review of the necessary mathematics and statistical hydrology. The underlying principles of the geographic information systems are discussed. In addition to topics covering fundamental concepts, separate chapters are devoted to reservoir operations, water resources management, climate change, and various methods of optimizing hydrologic models for calibration and validation. This textbook will prove to be indispensable for advanced students in civil, environmental, and agricultural engineering, preparing them to confidently join the industrial sector. It will also be an indispensable reference textbook for practicing engineers, bringing them up to date with modern techniques in applied hydrology.
Introduces an abridged history of hydrology and provides a brief discussion of hydrologic science and engineering, hydrologic system, hydrologic processes, hydrologic modeling, hydrologic models, and hydrologic data sources.
Deals with watershed geomorphology and characteristics, including hierarchical structure of a draiange basin, morphological parameters, hypsometry, stream order, Horton’s laws, stream power, longitudinal stream profile, hydraulic geometry, drainage density, drainage pattern, lag time, and time of concentration.
Geographic information systems (GIS) are discussed encompassing data base management, geodatabase, data structure of geographic features, topologic data structure, geographic data model, type of data models, Earth datum, map projection, map scale, geoprocessing and geovisualization, delineation of drainage areas and streams, and derivation of hydrologic parameters using GIS.
Hydrologic modeling with particular focus on model calibration. Beginning with a short discussion of hydrologic models, the chapter goes on to discussing model calibration through optimization, goodness-of-fit indices, measures of model performance, optimization methods, model validation, and sensitivity analysis. The chapter is concluded with a discussion of optimization models included in HEC-HMS.
Describes channel routing, including governing equations, characteristics of flood wave movement, channel routing methods, modified Puls, Muskingum, Lag and K, and Muskingum-Cunge methods of channel routing, selection of a routing mehod, comparison of hydrologic and hyraulic methods of routing, and channel routing in HEC-HMS.
Covers erosion process, types of erosion, estimation of erosion using universal and modified universal soil loss equations, sediemnt yield and its determination, temporal distribution of sedienmnt yiled, sediemnt loads in channels, sediemnt transport, sediemnt properties, fall velocity, sediemnt transport functions, sediment routing, reservoir sedimentation, and erosion and sedimentation modeling in HEC-HMS.
Many design problems, such as urban drainage and channel sizing require only peak discharge which is often estimated by the rational method which is described by presenting the rational method equation, the rational coefficient, drainage area, characteristic time, implications of the method, modified rational method and implications, and applications.
Groundwater and baseflow covering aquifers and their properties, gaining and losing streams, governing equations for groundwater flow, baseflow separation, baseflow models, parameter estimation, exponential decay and linear reservoir model.
Deals with rainfall measurements and models, methods of rainfall measurement, types of rainfall, rainfall statistics, spatial and temporal distributions of rainfall, NRCS type curves, Huff curves, annual maxima and partial duration series, design storms, frequency analysis, intensity–duration–frequency relationships, depth-area relation, temporal distribution of design rainfall, probable maximum precipitation, gridded rainfall, and design of rain gauge network.
One of the main physically- based methods for overland flow and channel flow modeling is the kinematic wave method. Kinematic wave models, including kinemtic wave equations for channel flow and overland flow, analytical solutions, numerical solutions, distinguishing features of kinemtic wave model, and implementation of kinematic wave model in HEC-HMS are discussed.
Unit hydrograph models dealing with the representaion of a watershd as linear time invariant system, response function and convolution, unit hydrograph characteristics, unit hydrograph derivation, synthetic unit hydrographs, gamma distribution, Snyder, NRCS, and Clark unit hydrograph models, instantaneous unit hydrographs, instantaneous unit hydrograph models, parameter estimation, and application of unit hydrographs and instantaneous unit hydrographs, S-hydrographs.