Data Structures Using C

The strengthening of reinforced concrete (RC) structures using advanced fibre-reinforced polymer (FRP) composites, and in particular the behaviour of FRP-strengthened RC structures is a topic which ha

Special Edition Using Visual C++ 6 focuses on making you productive with Visual C++ as quickly as possible. Because of its straightforward approach, this book is able to progress into more advanced t

Discusses the opportunities and risks for the U.S. in using intelligence data for environmental purposes.

This book is a customized version in Taiwan, and the content is extracted from Chapters 1 to 15 of the book "Introduction to Python Programming and Data Structures, Global Edition, 3rd edition".-- --For introductory courses in Python Programming.A fundamentals first approach to programming helps students create efficient, elegant code.Introduction to Python Programming and Data Structures introduces students to basic programming concepts using a fundamentals-first approach that prepares students to learn object-oriented programming and advanced Python programming. This approach presents programming concepts and techniques that include control statements, loops, functions, and arrays before designing custom classes. Students learn basic logic and programming concepts prior to moving into object-oriented and GUI programming. The content incorporates a wide variety of problems with various levels of difficulty and covers many application areas to engage and motivate students.For a list of

Much of the statistical information currently produced by federal statistical agencies - information about economic, social, and physical well-being that is essential for the functioning of modern society - comes from sample surveys. In recent years, there has been a proliferation of data from other sources, including data collected by government agencies while administering programs, satellite and sensor data, private-sector data such as electronic health records and credit card transaction data, and massive amounts of data available on the internet. How can these data sources be used to enhance the information currently collected on surveys, and to provide new frontiers for producing information and statistics to benefit American society? Toward a 21st Century National Data Infrastructure: Enhancing Survey Programs by Using Multiple Data Sources, the second report in a series funded by the National Science Foundation, discusses how use of multiple data sources can improve the quality

Chunyan Li is a course instructor with many years of experience in teaching about time series analysis. His book is essential for students and researchers in oceanography and other subjects in the Earth sciences, looking for a complete coverage of the theory and practice of time series data analysis using MATLAB. This textbook covers the topic's core theory in depth, and provides numerous instructional examples, many drawn directly from the author's own teaching experience, using data files, examples, and exercises. The book explores many concepts, including time; distance on Earth; wind, current, and wave data formats; finding a subset of ship-based data along planned or random transects; error propagation; Taylor series expansion for error estimates; the least squares method; base functions and linear independence of base functions; tidal harmonic analysis; Fourier series and the generalized Fourier transform; filtering techniques: sampling theorems: finite sampling effects; wavelet

Using data science in order to solve a problem requires a scientific mindset more than coding skills. Data Science for Supply Chain Forecasting, Second Edition contends that a true scientific method w

Basic Statistics with R: Reaching Decisions with Data, First Edition, provides readers with an understanding of the processes at work in using data for results. The work begins with data collection an

How to use data as a tool for empowerment rather than oppression. Big data can be used for good--from tracking disease to exposing human rights violations--and for bad--implementing surveillance and c

Drawing on examples from across the social and behavioral sciences, Statistics with R: Solving Problems Using Real-World Data introduces foundational statistics concepts with beginner-friendly R progr

Large-scale data analytics using machine learning (ML) underpins many modern data-driven applications. ML systems provide means of specifying and executing these ML workloads in an efficient and scala

?Learn how to use Python and its structures, how to install Python, and which tools are best suited for data analyst work. This book provides you with a handy reference and tutorial on topics ranging

This book provides an in-depth analysis of the role of foreign-owned banks for credit growth, financial stability and economic growth in the post-communist European countries. Using data covering 20 c

A comprehensive compilation of the available experimental and theoretical vibrational data for organometallic compounds and its role in evaluating the structures, bonding, and properties of these key

Almost 50 years have passed since the famous papers of Hugo Rietveld from the late sixties where he describes a method for the refinement of crystal structures from neutron powder diffraction data. So

Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner platform. Whether you are brand new to data science or working on your ten

This book bridges the current quantitative and qualitative text analyses, using grammar as a crucial source of investigation. Taking data from Czech, an inflected language, in which the most optimal c

This book presents the statistical analysis of compositional data using the log-ratio approach. It includes a wide range of classical and robust statistical methods adapted for compositional data anal

This book helps students and scholars get started on the exciting journey of using visual data in social research. It covers the many uses a researcher can make of images, from creating images as a pa

This book tackles the challenges of how to make sense of qualitative data. It offers students and researchers a hands-on guide to the practicalities of coding, comparing data, and using computer-assis

This unique book addresses the statistical modelling and analysis of microbiome data using cutting-edge R software. It includes real-world data from the authors’ research and from the public domain, a

This book uses institutional data to examine and analyze the current governance structures of Multilateral Financial Institutions (MFIs) with the ultimate goal of reforming MFI governance models to be

Panel Data Econometrics with R provides a tutorial for using R in the field of panel data econometrics. Illustrated throughout with examples in econometrics, political science, agriculture and epidemi

Malware Data Science explains how to identify, analyze, and classify large-scale malware using machine learning and data visualization.Security has become a "big data" problem. The growth rate of malw

Using a general approach, this book supports the student to enable mastery of the methods of analysis of isostatic and hyperstatic structures. To show the performance of the methods of analysis of the

This book contains the most complete description of the geologic and geophysical data of the structure of Arctic Basin including structures of the earth’s crust, crustal and acoustic basement, a

This book provides an in-depth understanding of big data challenges to digital forensic investigations, also known as big digital forensic data. It also develops the basis of using data mining in big

The Study Guide and Selected Solutions Manual as written specifically to assist students using General, Organic, and Biological Chemistry: Structures of Life. It contains learning objectives, cha

Direct from Microsoft, this Exam Ref is the official study guide for the new Microsoft 70-779 Analyzing and Visualizing Data by Using Microsoft Excel certification exam. Exam Ref 70-779 Anal

This book provides an in-depth understanding of big data challenges to digital forensic investigations, also known as big digital forensic data. It also develops the basis of using data mining in big

This book is written to address the issues relating to data gathering, data warehousing, and data analysis, all of which are useful when working with large amounts of data. Using practical examples of

Predictive Analytics has revolutionised marketing practice. It involves using many techniques from data mining, statistics, modelling, machine learning and artificial intelligence, to analyse current

Functional languages help developers support concurrency by encouraging immutable data structures that can be passed between threads without having to worry about a shared state, all while avoiding si

The design of tall buildings structures involves several rather complex design activities, including data capture, modelling, conceptual design, and structural analysis and detailing. While traditiona

Analyze your biostatistics data with JMP! Trevor Bihl's Biostatistics Using JMP: A Practical Guide provides a practical introduction on using JMP, the interactive statistical discovery software, to so

Learn Docker "infrastructure as code" technology to define a system for performing standard but non-trivial data tasks on medium- to large-scale data sets, using Jupyter as the master controller.It is

Rao presents an easy to use quick reference to basic design data on polymer resin, machine, part, and process and shows how to apply this data to solve practical problems, using examples with calc

Cybermetric Techniques to Evaluate Organizations Using Web-Based Data proposes a complete and multifaceted analysis model, integrating quantitative and qualitative measures (extracted from web usabili

This introductory guide provides a clear detailed explanation of how to present data in tables and graphs using the popular software application SPSS. Using practical examples the book is simple to us

Real-world data sets are messy and complicated. Written for students in social science and public management, this authoritative but approachable guide describes all the tools needed to collect data and prepare it for analysis. Offering detailed, step-by-step instructions, it covers collection of many different types of data including web files, APIs, and maps; data cleaning; data formatting; the integration of different sources into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming no prior knowledge of R and Python, the author introduces programming concepts gradually, using real data sets that provide the reader with practical, functional experience.