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Sensor technologies play a large part in modern life, as they are
present in things like security systems, digital cameras,
smartphones, and motion sensors. While these devices are always
evolving, research is being done to further develop this technology
to help detect and analyze threats, perform in-depth inspections,
and perform tracking services. Optoelectronics in Machine
Vision-Based Theories and Applications provides innovative insights
on theories and applications of optoelectronics in machine
vision-based systems. It also covers topics such as applications of
unmanned aerial vehicle, autonomous and mobile robots, medical
scanning, industrial applications, agriculture, and structural
health monitoring. This publication is a vital reference source for
engineers, technology developers, academicians, researchers, and
advanced-level students seeking emerging research on sensor
technologies and machine vision.
As technology continues to develop, certain innovations are
beginning to cover a wide range of applications, specifically
mobile robotic systems. The boundaries between the various
automation methods and their implementations are not strictly
defined, with overlaps occurring. Specificity is required regarding
the research and development of android systems and how they
pertain to modern science. Control and Signal Processing
Applications for Mobile and Aerial Robotic Systems is a pivotal
reference source that provides vital research on the current state
of control and signal processing of portable robotic designs. While
highlighting topics such as digital systems, control theory, and
mathematical methods, this publication explores original inquiry
contributions and the instrumentation of mechanical systems in the
industrial and scientific fields. This book is ideally designed for
technicians, engineers, industry specialists, researchers,
academicians, and students seeking current research on today's
execution of mobile robotic schemes.
In this book, the authors focus on efficient ways to program
instrumentation and automation systems using LabVIEW (TM), a system
design platform and development environment commonly used for data
acquisition, instrument control, and industrial automation on a
variety of operating systems. Starting with the concepts of data
flow and concurrent programming, the authors go on to address the
development of state machines, event programming and consumer
producer systems. Chapters cover the following topics: Introduction
to LabVIEW (TM), debugging tools, structures, SubVIs, structures -
LabVIEW (TM) features, organizing front panel and block diagram,
using software resources, using hardware resources, implementing
test machines with a basic architecture, controlling the user
interface, error handling, responding to the user interactions, the
ATM review project, communication between loops at different rates,
preventing race conditions, advanced use of software resources, and
real-time programming. This book helps undergraduate and graduate
students learn how to identify the most suitable design patterns
depending on the application, and how to implement them in
conjunction with data acquisition and instrumentation control
systems. It is also a helpful resource for engineers and scientists
who want to implement binary files to record data, control the user
interface and implement efficient ways of programming.
This book constitutes the refereed proceedings of the 17th
Ibero-American Conference on Artificial Intelligence, IBERAMIA
2022, held in Cartagena de Indias, Colombia, in November 2022. The
33 full and 4 short papers presented were carefully reviewed and
selected from 67 submissions. The papers are organized in the
following topical sections: applications of AI; ethics and smart
city; green and sustainable AI; machine learning; natural language
processing; robotics and computer vision; simulation and
forecasting.
As technology continues to develop, certain innovations are
beginning to cover a wide range of applications, specifically
mobile robotic systems. The boundaries between the various
automation methods and their implementations are not strictly
defined, with overlaps occurring. Specificity is required regarding
the research and development of android systems and how they
pertain to modern science. Control and Signal Processing
Applications for Mobile and Aerial Robotic Systems is a pivotal
reference source that provides vital research on the current state
of control and signal processing of portable robotic designs. While
highlighting topics such as digital systems, control theory, and
mathematical methods, this publication explores original inquiry
contributions and the instrumentation of mechanical systems in the
industrial and scientific fields. This book is ideally designed for
technicians, engineers, industry specialists, researchers,
academicians, and students seeking current research on today's
execution of mobile robotic schemes.
A practical guide to getting the most out of Excel, using it for
data preparation, applying machine learning models (including cloud
services) and understanding the outcome of the data analysis. Key
Features Use Microsoft's product Excel to build advanced
forecasting models using varied examples Cover range of machine
learning tasks such as data mining, data analytics, smart
visualization, and more Derive data-driven techniques using Excel
plugins and APIs without much code required Book DescriptionWe have
made huge progress in teaching computers to perform difficult
tasks, especially those that are repetitive and time-consuming for
humans. Excel users, of all levels, can feel left behind by this
innovation wave. The truth is that a large amount of the work
needed to develop and use a machine learning model can be done in
Excel. The book starts by giving a general introduction to machine
learning, making every concept clear and understandable. Then, it
shows every step of a machine learning project, from data
collection, reading from different data sources, developing models,
and visualizing the results using Excel features and offerings. In
every chapter, there are several examples and hands-on exercises
that will show the reader how to combine Excel functions, add-ins,
and connections to databases and to cloud services to reach the
desired goal: building a full data analysis flow. Different machine
learning models are shown, tailored to the type of data to be
analyzed. At the end of the book, the reader is presented with some
advanced use cases using Automated Machine Learning, and artificial
neural network, which simplifies the analysis task and represents
the future of machine learning. What you will learn Use Excel to
preview and cleanse datasets Understand correlations between
variables and optimize the input to machine learning models Use and
evaluate different machine learning models from Excel Understand
the use of different visualizations Learn the basic concepts and
calculations to understand how artificial neural networks work
Learn how to connect Excel to the Microsoft Azure cloud Get beyond
proof of concepts and build fully functional data analysis flows
Who this book is forThis book is for data analysis, machine
learning enthusiasts, project managers, and someone who doesn't
want to code much for performing core tasks of machine learning.
Each example will help you perform end-to-end smart analytics.
Working knowledge of Excel is required.
Sensor technologies play a large part in modern life, as they are
present in things like security systems, digital cameras,
smartphones, and motion sensors. While these devices are always
evolving, research is being done to further develop this technology
to help detect and analyze threats, perform in-depth inspections,
and perform tracking services. Optoelectronics in Machine
Vision-Based Theories and Applications provides innovative insights
on theories and applications of optoelectronics in machine
vision-based systems. It also covers topics such as applications of
unmanned aerial vehicle, autonomous and mobile robots, medical
scanning, industrial applications, agriculture, and structural
health monitoring. This publication is a vital reference source for
engineers, technology developers, academicians, researchers, and
advanced-level students seeking emerging research on sensor
technologies and machine vision.
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