الصفحة 2
الصفحة 2
Harmonic Analysis and Applications
John J. Benedetto has had a profound influence not only on the direction of harmonic analysis and its applications, but also on the entire community of people involved in the field. This self-contained volume in honor of John covers a wide range of topics in harmonic analysis and related areas, including weighted-norm inequalities, frame theory, wavelet theory, time-frequency analysis, and sampling theory. The invited chapters pay tribute to John’s many achievements and express an appreciation for both the mathematical and personal inspiration he has given to so many students, coauthors, and colleagues. Although the scope of the book is broad, chapters are clustered by topic to provide authoritative expositions that will be of lasting interest.
Handbook of neurochemistry and molecular neurobiology : Development and Aging Changes in the Nervous System
In the animal nervous system, a very high metabolic turnover, fragile but steep ionic gradients, and morphological and structural constraints - dictated by the necessity for prompt neuronal transmission of electrical impulses and necessary plasticity - result in a highly fragile organ system. Here, we address a small sampling of major constituents of neural function at the cellular and molecular level that play important roles in development and aging, two endogenous processes that embody features of allostasis or the dynamic shifts in set points for specific homeostatic mechanisms associated with development and aging. These chapters stress the dynamic features of neuronal responses to internal (developmental) cues or the more harmful external events (injury and disease) in a modern perspective.
Handbook of Multilevel Analysis
Multilevel analysis is the statistical analysis of hierarchically and non-hierarchically nested data. The simplest example is clustered data, such as a sample of students clustered within schools. Multilevel data are especially prevalent in the social and behavioral sciences and in the bio-medical sciences. The models used for this type of data are linear and nonlinear regression models that account for observed and unobserved heterogeneity at the various levels in the data. This book presents the state of the art in multilevel analysis, with an emphasis on more advanced topics. These topics are discussed conceptually, analyzed mathematically, and illustrated by empirical examples. The authors of the chapters are the leading experts in the field.
Geostatistics for environmental applications ; Proceedings of the Fifth European Conference on geostatistics for environmental applications
Once applied only to problems of mining-reserves assessment or petroleum-reservoir characterization, geostatistics is now being used in an increasingly large number of disciplines in environmental sciences. On the one hand, it enables the analysis and handling, in a rigorous probabilistic framework of the issues of spatial and temporal interpolation of continuous or categorical environmental variables. On the other hand, the methodology is also used to design and optimize sampling campaigns. "Geostatistics for Environmental Applications" contains forty selected contributions covering the latest progress in a broad spectrum of fields including air quality, climatology, ecology, groundwater hydrology, surface hydrology, oceanography, soil contamination, epidemiology and health, natural hazards, and remote sensing.
Frontiers in Statistical Quality Control 8
The proportion of nonconforming meters in a lot has traditionally defined lot quality for utility meter sampling inspection purposes. However, lot quality is usually measured on the basis of two criteria for such products: the proportion of nonc- forming packages in the lot and the lot mean quantity.
Foundations and applications of sensor management
Foundations and Applications of Sensor Management presents the emerging theory of sensor management with applications to real-world examples such as landmine detection, adaptive signal and image sampling, multi-target tracking, and radar waveform scheduling.
Forest Inventory : Methodology and Applications
This book has been developed as a forest inventory textbook for students and can also serve as a handbook for practical foresters. The book is divided into four sections. The first section deals mostly with sampling issues. First, we present the basic sampling designs at a fairly non-technical mathematical level. In addition, we present some more advanced sampling issues often needed in forest inventory. Those include for instance problems with systematic sampling, and methods for sampling vegetation or rare populations. Forest inventory also includes issues that are unique to forestry, like problems in measuring sample plots in the field, or utilising sample tree measurements. These issues include highly sophisticated methodology, but we try to present these also such that forestry students can grasp the ideas behind them. Each method is presented with examples. For foresters who need more details, references are given to more advanced scientific papers and books in the fields of statistics and biometrics.
Fetal compromise in labor
Sixty years ago, the purpose of introducing electronic fetal heart rate monitoring (EFM) was to reduce the incidence of intrapartum stillbirth. However, by the early 1980s, with falling stillbirth rates, fetal blood sampling had been widely abandoned, as many considered that EFM was sufficient on its own. Unfortunately, while the sensitivity of EFM for the detection of potential fetal compromise is high, specificity is low, and there is a high false positive rate which has been associated with a rising cesarean section rate. The authors suggest that EFM is considered and analyzed as a classic screening test and not a diagnostic test. Furthermore, it requires contextualization with other risk factors to achieve improved performance. A new proposed metric, the Fetal Reserve Index, takes into account additional risk factors and has demonstrated significantly improved performance metrics. It is going through the phases of further development, evaluation, and wider clinical implementation.
Econometric Analysis of Count Data
The book provides graduate students and researchers with an up-to-date survey of statistical and econometric techniques for the analysis of count data, with a focus on conditional distribution models. Proper count data probability models allow for rich inferences, both with respect to the stochastic count process that generated the data, and with respect to predicting the distribution of outcomes. The book starts with a presentation of the benchmark Poisson regression model. Alternative models address unobserved heterogeneity, state dependence, selectivity, endogeneity, underreporting, and clustered sampling. Testing and estimation is discussed from frequentist and Bayesian perspectives. Finally, applications are reviewed in fields such as economics, marketing, sociology, demography, and health sciences. The fifth edition contains several new topics, including copula functions, Poisson regression for non-counts, additional semi-parametric methods, and discrete factor models. Other sections have been reorganized, rewritten, and extended.
Dynamic Regression Models for Survival Data
This book studies and applies modern flexible regression models for survival data with a special focus on extensions of the Cox model and alternative models with the aim of describing time-varying effects of explanatory variables.
Drug safety evaluation : Methods and protocols
Focuses on the most recent advances in the field of drug safety evaluation. Divided into seven parts, chapters detail specific aspects related to the experimental design of preclinical studies conducted to support the safety of pediatric and combination drugs, necropsy and histopathology evaluation, mass spectrometry imaging, genetic toxicology protocols including the Pig-a mutation assay, safety pharmacology methods such as automatization of patch-clamp procedures, target safety assessment for investigative toxicology, screening assays for developmental toxicology, and methods to characterize novel translational safety biomarkers like microRNAs. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting to avoid known pitfalls.
Discrete-time Sliding Mode Control : A Multirate Output Feedback Approach
Sliding mode control is a simple and yet robust control technique, where the system states are made to confine to a selected subset. With the increasing use of computers and discrete-time samplers in controller implementation in the recent past, discrete-time systems and computer based control have become important topics. This monograph presents an output feedback sliding mode control philosophy which can be applied to almost all controllable and observable systems, while at the same time being simple enough as not to tax the computer too much. It is shown that the solution can be found in the synergy of the multirate output sampling concept and the concept of discrete-time sliding mode control.
Digital Signal Processing with Field Programmable Gate Arrays
Field-Programmable Gate Arrays (FPGAs) are revolutionizing digital signal processing as novel FPGA families are replacing ASICs and PDSPs for front-end digital signal processing algorithms. So the efficient implementation of these algorithms is critical and is the main goal of this book. It starts with an overview of today's FPGA technology, devices, and tools for designing state-of-the-art DSP systems. A case study in the first chapter is the basis for more than 40 design examples throughout. The following chapters deal with computer arithmetic concepts, theory and the implementation of FIR and IIR filters, multirate digital signal processing systems, DFT and FFT algorithms, advanced algorithms with high future potential, and adaptive filters. Each chapter contains exercises. The VERILOG source code and a glossary are given in the appendices. This edition has a new chapter on microprocessors, new sections on special functions using MAC calls, intellectual property core design and arbitrary sampling rate converters, and over 100 new exercises.
Digital Signal Processing for Measurement Systems : Theory and Applications
Digital Signal Processing for Measurement Systems: Theory and Applications covers the theoretical as well as the practical issues which form the basis of the modern DSP-based instruments and measurement methods. It covers the basics of DSP theory before discussing the critical aspects of DSP unique to measurement science. Includes important topics, for example, problems that arise when sampling periodic signals and the relationship between the sampling rate and the SNR
Design and Analysis of Simulation Experiments
This is an advanced expository book on statistical methods for the Design and Analysis of Simulation Experiments (DASE). Though the book focuses on DASE for discrete-event simulation (such as queuing and inventory simulations), it also discusses DASE for deterministic simulation (such as engineering and physics simulations). The text presents both classic and modern statistical designs. Classic designs (e.g., fractional factorials) assume only a few factors with a few values per factor. The resulting input/output data of the simulation experiment are analyzed through low-order polynomials, which are linear regression (meta)models. Modern designs allow many more factors, possible with many values per factor. These designs include group screening (e.g., Sequential Bifurcation, SB) and space filling designs (e.g., Latin Hypercube Sampling, LHS). The data resulting from these modern designs may be analyzed through low-order polynomials for group screening and various metamodel types (e.g., Kriging) for LHS.
Design and analysis of randomized algorithms : Introduction to design paradigms
Randomness is a powerful phenomenon that can be harnessed to solve various problems in all areas of computer science. Randomized algorithms are often more efficient, simpler and, surprisingly, also more reliable than their deterministic counterparts. Computing tasks exist that require billions of years of computer work when solved using the fastest known deterministic algorithms, but they can be solved using randomized algorithms in a few minutes with negligible error probabilities. Introducing the fascinating world of randomness, this book systematically teaches the main algorithm design paradigms – foiling an adversary, abundance of witnesses, fingerprinting, amplification, and random sampling, etc. – while also providing a deep insight into the nature of success in randomization. Taking sufficient time to present motivations and to develop the reader's intuition, while being rigorous throughout, this text is a very effective and efficient introduction to this exciting field.
Deep learning and computer vision in remote sensing-I
In the last few years, huge amounts of progress have been made regarding remote sensing in the field of computer vision. This success and progress is mostly due to the effectiveness of deep learning (DL) algorithms. In addition, the remote sensing community has shifted its attention to DL, and DL algorithms have been used to achieve significant success in many image analysis tasks. However, with regard to remote sensing, a number of challenges caused by difficulties in data acquisition and annotation have not been fully solved yet. This reprint is a collection of novel developments in the field of remote sensing using computer vision, deep learning, and artificial intelligence. The articles published involve fundamental theoretical analyses as well as those demonstrating their application to real-world problems.
Data collection in fragile states : Innovations from Africa and beyond
This book addresses an urgent issue on which little organized information exists. It reflects experience in Africa but is highly relevant to other fragile states as well. —Constantine Michalopoulos, John Hopkins University, USA and former Director of Economic Policy and Co-ordination at the World Bank
Cosmic Ray Neutron Sensing : Estimation of Agricultural Crop Biomass Water Equivalent
Provides methods for the estimation of Biomass Water Equivalent (BEW), an essential step for improving the accuracy of area-wide soil moisture by cosmic-ray neutron sensors (CRNS). Three techniques are explained in detail: (i) traditional in-situ destructive sampling, (ii) satellite based remote sensing of plant surfaces, and (iii) biomass estimation via the use of the CRNS itself. The advantages and disadvantages of each method are discussed along with step by step instructions on proper procedures and implementation.
Cooperative Bug Isolation : Winning Thesis of the 2005 ACM Doctoral Dissertation Competition
Efforts to understand and predict the behavior of software date back to the earliest days of computer programming,over half a century ago. In the intervening decades, the need for effective methods of understanding software has only increased; so- ware has spread to become the underpinning of much of modern society, and the potentially disastrous consequences of broken or poorly understood software have become all too apparent.
