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The Raspberry Pi has become a computing phenomenon. This single-board miniature
computer, first released in February 2012 by the Raspberry Pi Foundation, has grown into
a series of nearly a dozen models that have sold a total of more than 10 million units in
five years.
Inexpensive to buy and to run, Raspberry Pi computeRS are great for enthusiasts,
good for games, and fun for children. Raspberry Pi computeRS are also terrific in the
classroom, enabling you to put on each desk an easily-manageable computer on which
students can do everything from learning Internet use and essential office software skills,
through grasping programming basics in an easy-to-learn format, to performing full-on
programming in Python, Java, C, and other languages. Better yet, you can install all the
software needed for those activities automatically alongside the operating system.
標簽：
Deploying
Classroom
Raspberry
the
Pi
in
上傳時間：
2020-06-06
上傳用戶：shancjb
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Over the past few decades there has been an exponential growth in service robots
and smart home technologies, which has led to the development of exciting new
products in our daily lives. Service robots can be used to provide domestic aid for
the elderly and disabled, serving various functions ranging from cleaning to enter-
tainment. Service robots are divided by functions, such as personal robots, field
robots, security robots, healthcare robots, medical robots, rehabilitation robots and
entertainment robots. A smart home appears “intelligent” because its embedded
computeRS can monitor so many aspects of the daily lives of householders. For
example, the refrigerator may be able to monitor its contents, suggest healthy alter-
natives and order groceries. Also, the smart home system may be able to clean the
house and water the plants.
標簽：
Robotics
Service
Digital
within
Home
the
上傳時間：
2020-06-06
上傳用戶：shancjb
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This book was written by Michael Margolis with Nick Weldin to help you explore the
amazing things you can do with Arduino.
Arduino is a family of microcontrollers (tiny computeRS) and a software creation envi-
ronment that makes it easy for you to create programs (called sketches) that can interact
with the physical world. Things you make with Arduino can sense and respond to
touch, sound, position, heat, and light. This type of technology, often referred to as
physical computing, is used in all kinds of things, from the iPhone to automobile elec-
tronics systems. Arduino makes it possible for anyone—even people with no program-
ming or electronics experience—to use this rich and complex technology.
標簽：
Cookbook
Arduino
上傳時間：
2020-06-09
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Simulation is experimentation with models. For system design, research, and edu-
cation, simulations must not only construct and modify many different models but
also store and access a large volume of results. That is practical only with models
programmed on computeRS [1,2]
標簽：
Dynamic-System
Simulation
上傳時間：
2020-06-10
上傳用戶：shancjb
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Striking developments have taken place since 1980 in feedback control theory. The subject has be-
come both more rigorous and more applicable. The rigor is not for its own sake, but rather that even
in an engineering discipline rigor can lead to clarity and to methodical solutions to problems. The
applicability is a consequence both of new problem formulations and new mathematical solutions
to these problems. Moreover, computeRS and software have changed the way engineering design is
done. These developments suggest a fresh presentation of the subject, one that exploits these new
developments while emphasizing their connection with classical control.
標簽：
Feedback
Control
Theory
上傳時間：
2020-06-10
上傳用戶：shancjb
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Modern information technologies and the advent of machines powered by artificial
intelligence (AI) have already strongly influenced the world of work in the 21st century.
computeRS, algorithms and software simplify everyday tasks, and it is impossible
to imagine how most of our life could be managed without them. However, is it
also impossible to imagine how most process steps could be managed without
human force? The information economy characterised by exponential growth
replaces the mass production industry based on economy of scales
標簽：
AI-and-Robotics-IBA-GEI-April
2017
上傳時間：
2020-06-10
上傳用戶：shancjb
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We’re living through exciting times. The landscape of what computeRS can do is
changing by the week. Tasks that only a few years ago were thought to require
higher cognition are getting solved by machines at near-superhuman levels of per-
formance. Tasks such as describing a photographic image with a sentence in idiom-
atic English, playing complex strategy game, and diagnosing a tumor from a
radiological scan are all approachable now by a computer. Even more impressively,
computeRS acquire the ability to solve such tasks through examples, rather than
human-encoded of handcrafted rules.
標簽：
Deep-Learning-with-PyTorch
上傳時間：
2020-06-10
上傳用戶：shancjb
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Artificial Intelligence (AI) has undoubtedly been one of the most important buz-
zwords over the past years. The goal in AI is to design algorithms that transform com-
puters into “intelligent” agents. By intelligence here we do not necessarily mean an
extraordinary level of smartness shown by superhuman; it rather often involves very
basic problems that humans solve very frequently in their day-to-day life. This can
be as simple as recognizing faces in an image, driving a car, playing a board game, or
reading (and understanding) an article in a newspaper. The intelligent behaviour ex-
hibited by humans when “reading” is one of the main goals for a subfield of AI called
Natural Language Processing (NLP). Natural language 1 is one of the most complex
tools used by humans for a wide range of reasons, for instance to communicate with
others, to express thoughts, feelings and ideas, to ask questions, or to give instruc-
tions. Therefore, it is crucial for computeRS to possess the ability to use the same tool
in order to effectively interact with humans.
標簽：
Embeddings
Processing
Language
Natural
in
上傳時間：
2020-06-10
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Computer science as an academic discipline began in the 1960’s. Emphasis was on
programming languages, compilers, operating systems, and the mathematical theory that
supported these areas. Courses in theoretical computer science covered finite automata,
regular expressions, context-free languages, and computability. In the 1970’s, the study
of algorithms was added as an important component of theory. The emphasis was on
making computeRS useful. Today, a fundamental change is taking place and the focus is
more on a wealth of applications. There are many reasons for this change. The merging
of computing and communications has played an important role. The enhanced ability
to observe, collect, and store data in the natural sciences, in commerce, and in other
fields calls for a change in our understanding of data and how to handle it in the modern
setting. The emergence of the web and social networks as central aspects of daily life
presents both opportunities and challenges for theory.
標簽：
Foundations
Science
Data
of
上傳時間：
2020-06-10
上傳用戶：shancjb
