Introduction to Mathematical Methods in Bioinformatics
This book looks at the mathematical foundations of the models currently in use. This book is unique in the sense that it looks at the mathematical foundations of the models, which are crucial for correct interpretation of the outputs of the models.
Introduction to materials science for engineers
Provides balanced, current treatment of the full spectrum of engineering materials, covering all the physical properties, applications and relevant properties associated with engineering materials. It explores all of the major categories of materials while also offering detailed examinations of a wide range of new materials with high-tech applications.
Introduction to malnutrition among children
Malnutrition refers to when a person's diet does not provide enough nutrients or the right balance of nutrients for optimal health. Causes of Malnutrition To help understand the causes of malnutrition, UNICEF developed a conceptual framework which remains a useful tool to help understand the causes of malnutrition. Acute malnutrition among children is consistently increasing even though overall malnutrition levels in Syria remain below emergency levels...
Introduction to Machine Learning with Applications in Information Security
Provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications. The book is accessible and doesn't prove theorems, or dwell on mathematical theory. The goal is to present topics at an intuitive level, with just enough detail to clarify the underlying concepts. The book covers core classic machine learning topics in depth, including Hidden Markov Models (HMM), Support Vector Machines (SVM), and clustering. Additional machine learning topics include k-Nearest Neighbor (k-NN), boosting, Random Forests, and Linear Discriminant Analysis (LDA). The fundamental deep learning topics of backpropagation, Convolutional Neural Networks (CNN), Multilayer Perceptrons (MLP), and Recurrent Neural Networks (RNN) are covered in depth. A broad range of advanced deep learning architectures are also presented, including Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), Extreme Learning Machines (ELM), Residual Networks (ResNet), Deep Belief Networks (DBN), Bidirectional Encoder Representations from Transformers (BERT), and Word2Vec.
Introduction to Logic and Theory of Knowledge : Lectures 1906/07
This course on logic and theory of knowledge fell exactly midway between the publication of the Logical Investigations in 1900-01 and Ideas I in 1913. It constitutes a summation and consolidation of Husserl’s logico-scientific, epistemological, and epistemo-phenomenological investigations of the preceding years and an important step in the journey from the descriptivo-psychological elucidation of pure logic in the Logical Investigations to the transcendental phenomenology of the absolute consciousness of the objective correlates constituting themselves in its acts in Ideas I. In this course Husserl began developing his transcendental phenomenology as the genuine realization of what had only been realized in fragmentary form in the Logical Investigations.
Introduction to Lie Algebras
This book provides an elementary introduction to Lie algebras. It starts with basic concepts. A section on low-dimensional Lie algebras provides readers with experience of some useful examples. This is followed by a discussion of solvable Lie algebras and a strategy towards a classification of finite-dimensional complex Lie algebras. The next chapters cover Engel's theorem, Lie's theorem and Cartan's criteria and introduce some representation theory. The root-space decomposition of a semisimple Lie algebra is discussed, and the classical Lie algebras studied in detail. The authors also classify root systems, and give an outline of Serre's construction of complex semisimple Lie algebras. An overview of further directions then concludes the book and shows the high degree to which Lie algebras influence present-day mathematics.The only prerequisite is some linear algebra and an appendix summarizes the main facts that are needed. The treatment is kept as simple as possible with no attempt at full generality.
Introduction to Ion Beam Biotechnology
It presents treatment of modern ion beam biotechnology and with respect to applications of ion beam bombardment of living cellular material in the hybrid field of ion beam physics and biology.Key Topics include: – Ion beam formation – Ion implantation fundamentals – Interaction between energetic ions and biological organisms – Reaction processes of ion implanted biological small molecules – Damage and repair of ion-bombarded DNA – Cell damage due to ion bombardment – Biological effects of ion implantation – Fundamentals of ion-bombardment-induced genetic variation – Ion beam mutation breeding of crops – Ion beam mutation breeding of microbes – Ion beam induced gene transfer – Ion beam induced synthesis of organic molecules – Single-ion bombardment mutation of cells
Introduction to Intelligent Construction Technology of Transportation Infrastructure
Expounds on the related technologies of intelligent transportation infrastructure construction. Based on the essential characteristics of intelligent construction, "perception, analysis, decision-making, and execution," the basic structure of intelligent construction technology (ICT) is established. With the integration of engineering construction technologies, the analyses of the essence of intelligent algorithms and the feasibility of Artificial Intelligence (AI) are provided. The book introduces the essential characteristics of Big Data and the Internet of Things and their relationship with engineering construction. On this basis, the feasibility and implementation plan of intelligent technology applications in design, construction, and maintenance are analyzed and demonstrated with engineering examples.
Introduction to information retrieval
Teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science.
Introduction to Geometric Computing
The geometric ideas in computer science, mathematics, engineering, and physics have considerable overlap and students in each of these disciplines will eventually encounter geometric computing problems. The topic is traditionally taught in mathematics departments via geometry courses, and in computer science through computer graphics modules. This text isolates the fundamental topics affecting these disciplines and lies at the intersection of classical geometry and modern computing.
Introduction to Genetic Algorithms
This book is designed to provide an in-depth knowledge on the basic operational features and characteristics of Genetic Algorithms. The various operators and techniques given in the book are pertinent to carry out Genetic Algorithm Research Projects. The book also explores the different types are Genetic Algorithms available with their importance. Implementation of Genetic Algorithm concept has been performed using the universal language C/C++ and the discussion also extends to Genetic Algorithm MATLAB Toolbox. Few Genetic Algorithm problems are programmed using MATLAB and the simulated results are given for the ready reference of the reader. The applications of Genetic Algorithms in Machine learning, Mechanical Engineering, Electrical Engineering, Civil Engineering, Data Mining, Image Processing, and VLSI are dealt to make the readers understand where the concept can be applied.
Introduction to Fuzzy Logic using MATLAB
Fuzzy Logic, at present is a hot topic, among academicians as well various programmers. This book is provided to give a broad, in-depth overview of the field of Fuzzy Logic. The basic principles of Fuzzy Logic are discussed in detail with various solved examples. The different approaches and solutions to the problems given in the book are well balanced and pertinent to the Fuzzy Logic research projects. The applications of Fuzzy Logic are also dealt to make the readers understand the concept of Fuzzy Logic. The solutions to the problems are programmed using MATLAB 6.0 and the simulated results are given. The MATLAB Fuzzy Logic toolbox is provided for easy reference.
Introduction to food chemistry
Bridges this gap in the relevant literature, as it employs the latest pedagogical theories in textbook writing to present the subject to students with broad range of cognitive skills. This book presents specific learning objectives for each chapter and is self-contained so students will not need to search for essential information outside the textbook. This new edition has been expanded to include chapters on sweeteners, glass transition, amino acids, proteins for major food commodities and food additives. All of the original chapters have been updated and expanded to include new research and technologies.
Introduction to Focused Ion Beams : Instrumentation, Theory, Techniques and Practice
Introduction to Focused Ion Beams is geared towards techniques and applications. The first portion of this book introduces the basics of FIB instrumentation, milling, and deposition capabilities. The chapter dedicated to ion-solid interactions is presented so that the FIB user can understand which parameters will influence FIB milling behavior. The remainder of the book focuses on how to prepare and analyze samples using FIB and related tools, and presents specific applications and techniques of the uses of FIB milling, deposition, and dual platform techniques. This is the only text that discusses and presents the theory directly related to applications and the only one that discusses the vast applications and techniques used in FIBs and Dual platform instruments.
Introduction to finite element analysis : A textbook for engineering students
Covers the basic concepts and applications of finite element analysis. It is specifically aimed at introducing this advanced topic to undergraduate-level engineering students and practicing engineers in a lucid manner. It also introduces a structural and heat transfer analysis software FEASTSMT which has wide applications in civil, mechanical, nuclear and automobile engineering domains.
Introduction to Epigenetics
This textbook leads the reader from basic concepts of chromatin structure and function and RNA mechanisms to the understanding of epigenetics, imprinting, regeneration and reprogramming. The textbook treats epigenetic phenomena in animals, as well as plants.
Introduction to Engineering Statistics and Six Sigma : Statistical Quality Control and Design of Experiments and Systems
Introduction to Engineering Statistics and Six Sigma contains precise descriptions of all of the many related methods and details case studies showing how they have been applied in engineering and business to achieve millions of dollars of savings. Specifically, the methods introduced include many kinds of design of experiments (DOE) and statistical process control (SPC) charting approaches, failure mode and effects analysis (FMEA), formal optimization, genetic algorithms, gauge reproducibility and repeatability (R&R), linear regression, neural nets, simulation, quality function deployment (QFD) and Taguchi methods. A major goal of the book is to help the reader to determine exactly which methods to apply in which situation and to predict how and when the methods might not be effective.
Introduction to Empirical Processes and Semiparametric Inference
This book provides a self-contained, linear, and unified introduction to empirical processes and semiparametric inference. These powerful research techniques are surprisingly useful for developing methods of statistical inference for complex models and in understanding the properties of such methods. The targeted audience includes statisticians, biostatisticians, and other researchers with a background in mathematical statistics who have an interest in learning about and doing research in empirical processes and semiparametric inference but who would like to have a friendly and gradual introduction to the area. The book can be used either as a research reference or as a textbook. The level of the book is suitable for a second year graduate course in statistics or biostatistics, provided the students have had a year of graduate level mathematical statistics and a semester of probability.
Introduction to Drug Disposition and Pharmacokinetics
The application of knowledge of drug disposition, and skills in pharmacokinetics, are crucial to the development of new drugs and to a better understanding of how to achieve maximum benefit from existing ones. The book takes the reader from basic concepts to a point where those who wish to will be able to perform pharmacokinetic calculations and be ready to read more advanced texts and research papers.
Introduction to Discrete Event Systems
Introduction to Discrete Event Systems is a comprehensive introduction to the field of discrete event systems, offering a breadth of coverage that makes the material accessible to readers of varied backgrounds. The book emphasizes a unified modeling framework that transcends specific application areas, linking the following topics in a coherent manner: language and automata theory, supervisory control, Petri net theory, Markov chains and queueing theory, discrete-event simulation, and concurrent estimation techniques



















