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Spatial Information Technology for Sustainable Development Goals
This textbook aims to develop a scientific knowledge base on spatial information technology to communicate the United Nations' Sustainable Development Goals (SDGs) among students, researchers, professionals and laymen.The book improves understanding of the spatial database and explains how to extract information from this for planning purposes.To enhance the knowledge of geoscientists and environmentalists, the book describes the basic fundamental concepts to advance techniques for spatial data management and analysis and discusses the methodology.The Geographic Information System (GIS), remote sensing and Global Positioning System (GPS) are presented in an integrated manner for the planning of resources and infrastructure.The management of these systems is discussed in a very lucid way to develop the reader's skills.The proper procedure for map making and spatial analysis are included along with case studies to the reader.Where thefirst part of the book discusses the conceptual background, the second part deals with case studies using these applications in different disciplines.The presented case studies include land use, agriculture, flood, watershed characterization and infrastructure assessment for the Sustainable Development Goals.
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Supply Chain Finance : Mechanisms, Risk Analytics, and Technology
As global supply chains become more complex, the need for expertise in their financial aspects grows.This book aims to equip students and professionals with the knowledge to navigate these complexities, ensuring efficient and resilient financial supply chain operations.It provides an in-depth exploration into the intricate and constantly evolving realm of supply chain finance.By merging key concepts, major mechanisms, hands-on risk analytics, and the latest technology trends, this book offers a seamless and comprehensive examination of the topic, grounded in the author's twenty years of academic research and hands-on experience.Students in supply chain management will gain a thorough understanding of the financial elements that are integral to modern supply chains, including the importance of liquidity, the role of financial institutions, and the optimization of cash flows within the supply chain ecosystem.Definitions will be used throughout the text to elucidate financial terminology that may be unfamiliar to management students.The instructor’s manual will include PowerPoint slides, exercises, and quizzes to assess student comprehension and progress. This textbook will serve as the primary resource for understanding the financial dimensions of supply chains.
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Management Consultants' Acceptance of Internet Technology : An Empirical Study of the Determinants of Web Analytics Technology Acceptance
The Internet continues to offer businesses new tools to enhance infrastructure-and new Web analytics technology (WAT) is helping organizations aggregate and integrate online user behavior data for management operations and strategic planning.This research study developed a model based on unified theory of acceptance use of technology (UTAUT) premises to provide empirical evidence to support management consultants' acceptance of WAT.The study sought input from almost three hundred management consultants, and the results show a positive correlation among the determinants, including effort expectations, performance expectations, social influence, facilitating conditions, and behavioral intentions.In fact, performance expectancy, effort expectancy, social influence, and facilitating conditions can predict sixty-two percent of the behavior intention of management consultants to accept WAT...
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Data Analytics & Visualization All-in-One For Dummies
Install data analytics into your brain with this comprehensive introduction Data Analytics & Visualization All-in-One For Dummies collects the essential information on mining, organizing, and communicating data, all in one place.Clocking in at around 850 pages, this tome of a reference delivers eight books in one, so you can build a solid foundation of knowledge in data wrangling.Data analytics professionals are highly sought after these days, and this book will put you on the path to becoming one.You’ll learn all about sources of data like data lakes, and you’ll discover how to extract data using tools like Microsoft Power BI, organize the data in Microsoft Excel, and visually present the data in a way that makes sense using a Tableau.You’ll even get an intro to the Python, R, and SQL coding needed to take your data skills to a new level.With this Dummies guide, you’ll be well on your way to becoming a priceless data jockey. Mine data from data sourcesOrganize and analyze data Use data to tell a story with TableauExpand your know-how with Python and R New and novice data analysts will love this All-in-One reference on how to make sense of data.Get ready to watch as your career in data takes off.
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What is spatial visualization ability?
Spatial visualization ability refers to the capacity to mentally manipulate and comprehend spatial relationships between objects. Individuals with strong spatial visualization skills can easily visualize and understand how objects relate to each other in space, such as rotating or manipulating shapes in their mind. This ability is crucial in various fields such as engineering, architecture, and mathematics, as it allows individuals to solve complex problems and understand spatial concepts more effectively. Improving spatial visualization ability can enhance problem-solving skills and overall cognitive performance.
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Is spatial visualization important for engineers?
Yes, spatial visualization is important for engineers as it allows them to mentally manipulate and understand complex 3D objects and structures. Engineers often need to design and analyze various components and systems, and spatial visualization skills help them to conceptualize and communicate their ideas effectively. Whether it's designing a new product, creating blueprints for a building, or solving complex problems, spatial visualization is a crucial skill that allows engineers to think critically and innovate in their field.
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Can one improve their spatial visualization skills?
Yes, it is possible to improve spatial visualization skills through practice and training. Engaging in activities such as puzzles, building models, and playing spatial reasoning games can help develop these skills. Additionally, practicing mental rotation exercises and regularly challenging oneself with spatial tasks can also contribute to improvement. With consistent effort and dedication, individuals can enhance their spatial visualization abilities over time.
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What are problems with spatial visualization skills?
Some problems with spatial visualization skills include difficulty in understanding and interpreting maps, graphs, and diagrams. Individuals with poor spatial visualization skills may struggle with tasks such as navigating through unfamiliar environments, understanding 3D objects, and mentally rotating objects. This can impact their performance in subjects such as math, science, and engineering, as well as in everyday activities such as driving and assembling furniture. Additionally, poor spatial visualization skills can lead to frustration and decreased confidence in one's abilities.
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Spatial Analysis with R : Statistics, Visualization, and Computational Methods
In the five years since the publication of the first edition of Spatial Analysis: Statistics, Visualization, and Computational Methods, many new developments have taken shape regarding the implementation of new tools and methods for spatial analysis with R.The use and growth of artificial intelligence, machine learning and deep learning algorithms with a spatial perspective, and the interdisciplinary use of spatial analysis are all covered in this second edition along with traditional statistical methods and algorithms to provide a concept-based problem-solving learning approach to mastering practical spatial analysis.Spatial Analysis with R: Statistics, Visualization, and Computational Methods, Second Edition provides a balance between concepts and practicums of spatial statistics with a comprehensive coverage of the most important approaches to understand spatial data, analyze spatial relationships and patterns, and predict spatial processes.New in the Second Edition: Includes new practical exercises and worked-out examples using R Presents a wide range of hands-on spatial analysis worktables and lab exercises All chapters are revised and include new illustrations of different concepts using data from environmental and social sciences Expanded material on spatiotemporal methods, visual analytics methods, data science, and computational methods Explains big data, data management, and data miningThis second edition of an established textbook, with new datasets, insights, excellent illustrations, and numerous examples with R, is perfect for senior undergraduate and first-year graduate students in geography and the geosciences.
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Spatial Statistics and Geostatistics : Theory and Applications for Geographic Information Science and Technology
"Ideal for anyone who wishes to gain a practical understanding of spatial statistics and geostatistics.Difficult concepts are well explained and supported by excellent examples in R code, allowing readers to see how each of the methods is implemented in practice"- Professor Tao Cheng, University College LondonFocusing specifically on spatial statistics and including components for ArcGIS, R, SAS and WinBUGS, this book illustrates the use of basic spatial statistics and geostatistics, as well as the spatial filtering techniques used in all relevant programs and software.It explains and demonstrates techniques in:spatial samplingspatial autocorrelationlocal statisticsspatial interpolation in two-dimensionsadvanced topics including Bayesian methods, Monte Carlo simulation, error and uncertainty.It is a systematic overview of the fundamental spatial statistical methods used by applied researchers in geography, environmental science, health and epidemiology, population and demography, and planning.A companion website includes digital R code for implementing the analyses in specific chapters and relevant data sets to run the R codes.
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Spatial Epidemiological Approaches in Disease Mapping and Analysis
Containing method descriptions and step-by-step procedures, the Spatial Epidemiological Approaches in Disease Mapping and Analysis equips readers with skills to prepare health-related data in the proper format, process these data using relevant functions and software, and display the results as mapped or statistical summaries.Describing the wide range of available methods and key GIS concepts for spatial epidemiology, this book illustrates the utilities of the software using real-world data.Additional topics include geographic data models, address matching, geostatistical analysis, universal kriging, point pattern analysis, kernel density, spatio-temporal display, and disease surveillance.
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Crime Mapping and Spatial Data Analysis using R
Crime mapping and analysis sit at the intersection of geocomputation, data visualisation and cartography, spatial statistics, environmental criminology, and crime analysis.This book brings together relevant knowledge from these fields into a practical, hands-on guide, providing a useful introduction and reference material for topics in crime mapping, the geography of crime, environmental criminology, and crime analysis.It can be used by students, practitioners, and academics alike, whether to develop a university course, to support further training and development, or to hone skills in self-teaching R and crime mapping and spatial data analysis.It is not an advanced statistics textbook, but rather an applied guide and later useful reference books, intended to be read and for readers to practice the learnings from each chapter in sequence.In the first part of this volume we introduce key concepts for geographic analysis and representation and provide the reader with the foundations needed to visualise spatial crime data.We then introduce a series of tools to study spatial homogeneity and dependence.A key focus in this section is how to visualise and detect local clusters of crime and repeat victimisation.The final chapters introduce the use of basic spatial models, which account for the distribution of crime across space.In terms of spatial data analysis the focus of the book is on spatial point pattern analysis and lattice or area data analysis.
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What is the function of spatial visualization ability?
Spatial visualization ability allows individuals to mentally manipulate and understand spatial relationships between objects. This ability is crucial in fields such as engineering, architecture, and design, where individuals need to visualize and manipulate complex 3D objects and structures. It also plays a key role in tasks such as navigation, map reading, and understanding geometric concepts. Overall, spatial visualization ability is important for problem-solving, creativity, and understanding the physical world.
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What are the differences between routing, forwarding, switching, and bridging in network and communication technology?
Routing involves determining the best path for data packets to travel from the source to the destination network. Forwarding is the process of sending data packets from one network device to another based on the destination address. Switching involves directing data packets within a single network based on MAC addresses. Bridging connects two different network segments at the data link layer, allowing communication between devices on separate networks. Each of these processes plays a crucial role in ensuring efficient and reliable communication within a network.
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Should I learn wood technology or carpentry technology?
The decision between learning wood technology or carpentry technology depends on your interests and career goals. Wood technology focuses on the science and engineering of wood materials, including processing, preservation, and utilization. This field is more research and industry-oriented, with opportunities in manufacturing, product development, and quality control. On the other hand, carpentry technology is more hands-on and practical, focusing on the skills and techniques needed for construction and woodworking projects. If you are more interested in the technical and scientific aspects of wood, then wood technology may be the better choice. However, if you enjoy working with your hands and want to pursue a career in construction or woodworking, then carpentry technology may be the better fit for you.
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Is induction technology more durable than ceramic glass technology?
Induction technology is generally considered more durable than ceramic glass technology. This is because induction cooktops are made with a tough glass-ceramic material that can withstand high temperatures and is less prone to scratches and cracks. Additionally, induction cooktops have fewer parts that can wear out over time compared to ceramic glass cooktops, making them more reliable in the long run. Overall, induction technology is known for its durability and longevity compared to ceramic glass technology.
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