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Detection and Analysis of Microorganisms by Mass Spectrometry
In the human body, there are millions of living microorganisms involved in protecting the body from invaders, helping digestion and regulating moods, but there are also harmful pathogens that cause infectious diseases. For instance, the coronavirus (COVID-19) has caused considerable loss of life since its outbreak. Comprehensive analysis and characterization of microbes is of significant importance to understand the function and role of microorganisms, and rapid detection and identification of unknown pathogens are essential in early diagnosis, treatment monitoring and personalized medicine. Mass spectrometry is a technique to ionize molecules and detect the mass-to-charge ratio of the gener...
Foundations of Time Series Analysis and Prediction Theory
Foundations of time series for researchers and students This volume provides a mathematical foundation for time seriesanalysis and prediction theory using the idea of regression and thegeometry of Hilbert spaces. It presents an overview of the tools oftime series data analysis, a detailed structural analysis ofstationary processes through various reparameterizations employingtechniques from prediction theory, digital signal processing, andlinear algebra. The author emphasizes the foundation and structureof time series and backs up this coverage with theory andapplication. End-of-chapter exercises provide reinforcement for self-study andappendices covering multivariate distributions and Bayes...
Current Catalog
First multi-year cumulation covers six years: 1965-70.
Statistical Computing with R
Computational statistics and statistical computing are two areas that employ computational, graphical, and numerical approaches to solve statistical problems, making the versatile R language an ideal computing environment for these fields. One of the first books on these topics to feature R, Statistical Computing with R covers the traditional core material of computational statistics, with an emphasis on using the R language via an examples-based approach. Suitable for an introductory course in computational statistics or for self-study, it includes R code for all examples and R notes to help explain the R programming concepts. After an overview of computational statistics and an introductio...
Computational Botany
This book discusses innovative methods for mining information from images of plants, especially leaves, and highlights the diagnostic features that can be implemented in fully automatic systems for identifying plant species. Adopting a multidisciplinary approach, it explores the problem of plant species identification, covering both the concepts of taxonomy and morphology. It then provides an overview of morphometrics, including the historical background and the main steps in the morphometric analysis of leaves together with a number of applications. The core of the book focuses on novel diagnostic methods for plant species identification developed from a computer scientist’s perspective. ...
Rugged Free Energy Landscapes
This collection of lectures and tutorial reviews focuses on the common computational approaches in use to unravel the static and dynamical behaviour of complex physical systems at the interface of physics, chemistry and biology. Prominent consideration is given to rugged free-energy landscapes. The authors aim to provide a common basis and technical language for the (computational) technology transfer between the fields and systems considered.
An Agglomeration Of Experiments With Mixture Methodology Volume – I
The book contains selected published research papers present in the literature since late fifties. The authors of the papers are eminent academicians, planners and scientists of repute in their respective areas. In the section on Introduction to Design of Experiments, the short overview is given on design of experiment, its optimality & efficiency criteria. Introduction to Mixture Problem: Design and its Construction, this section contains the basic concept and models for mixture problem, and also contains the construction of designs and its test criteria for mixture problems. Mixture experiments are generally conducted in different branches of agricultural and industrial research where it i...
Optimal Crossover Designs
This monograph presents a comprehensive and up-to-date account of the developments in optimality aspects of crossover designs. Crossover designs are immensely useful in various areas of human investigation including agriculture, animal nutrition, clinical trials, pharmaceutical studies, biological assays, weather modification experiments, sensory evaluation of food products and learning experiments. Research on the optimality aspects of crossover designs has developed only in the last three decades, and it has now emerged as a potential field for further investigation. This book is the first comprehensive treatise on this subject. It covers optimal crossover designs at length by consolidating vast amounts of material from the literature, and includes many recent and deep results. It is expected that this book will not only provide a one-stop reference for the available results, but also encourage further research in this area of substantial practical relevance.
Supervised Classification of Thermal High-Resolution Infrared Images: A case study for the diagnosis of RaynaudÕs Phenomenon
In many classification problems, relevant features are unknown a priori. Therefore, many candidate features are introduced to represent the phenomenon. Unfortunately, it is often true that most of these are either partially or completely redundant to the target. Thus, when the size of the dataset is large, an important primary step in the classification task is to remove the unwanted features. In this framework, this study proposes a new subset selection algorithm, called JSS+E (Jackknifed Stepwise Selection with Exhaustive search), in order to improve the stepwise selection procedure. The procedure is applied, in a supervised classification approach, for the differential diagnosis of Raynaud's Phenomenon, on the basis of functional infrared (IR) imaging data. The results discussed for a dataset collected at ITAB laboratory in Chieti, allow to refine the experimental protocol in a completely new non-invasive way.
