How to install OpenCV in Microsoft Visual Studio 2017
How to install OpenCV in Microsoft Visual Studio 2017 is created by AKElevon.
Steps to install OpenCV in Microsoft Visual Studio 2017
Step 1: Install Visual Studio 2017
Step 2: Install OpenCV
Step 3: Include OpenCV to system path
• Go to Advanced System Settings --) Environment Variables --)System Variables --) Path
• Click on ‘Edit’. Now, click ‘New’ to add new environment variable.
• Copy and paste the path of bin folder inside OpenCV package.
• Press OK and exit the environment variable.
Step 4: Create a new empty console application
Step 5: Include OpenCV in Visual Studio
• Change the Debug environment to x64.
• Inside Properties of the project, then CC++ --)General. Copy the path to include folder of opencv and paste it inside Additional Include Directories. Then, click Apply.
• Go to linker --) General. Copy the path to folder containing opencv lib files and paste it inside Additional Library Directories. Then, click Apply.
• Go to Input. Edit Additional Dependencies and paste the the files end with d.lib file’s name.
• Exit the Properties by clicking OK.
Step 6:
• Move .dll files from bin to System32
Step 7: Test the code
=====================================================
Application:
-----) Install OpenCV in MSVS 2017
=====================================================
Software Used:
------) Microsoft Visual Studio 2017
======================================================
Components:
• Microsoft Visual Studio 2017
======================================================
Other Projects:
Four Way Traffic Light System Using Arduino Simple Version
------ https://youtu.be/mJ0ANveFoZ8
C# Window form Button and Text Box
------ hhttps://youtu.be/EqHBA7lSOeg
=====================================================
AKElevon also Support (If you have any question or you can get help about any project Mail me) and Work in Following Fields.
=====Mail programmer74432@gmail.com====
1- 8051 related Projects
2- Image Processing Using Matlab
3- Electronics Projects
4- Machine Learning
5- Deep Learning using Matlab
6- Arduino Projects
7- Python and C++ --Window Form
8- C# Window Form
9- PLC Projects
10- Computer Vision using C++
11- OpenCV using C++
Bytronic Industrial Control Simulation Using LogixPro
Bytronic Industrial Control Simulation Using LogixPro is created by AKElevon. The bytronic industrial control trainer is a system that was designed to represent a typical industrial process automation system. Its objective is to ensure the assembly of plastic rings and aluminum pegs. It is made up of 2 conveyor system. The conveyors are of two types; chain conveyor and a belt conveyor. The chain conveyor processes the pegs and rings up the upper sort area.
=====================================================
Application:
-----) Automatic Assembly System
=====================================================
Software Used:
------) Logix Pro
======================================================
Components:
• Logix Pro
======================================================
Other Projects:
Four Way Traffic Light System Using Arduino Simple Version
------ https://youtu.be/mJ0ANveFoZ8
C# Window form Button and Text Box
------ hhttps://youtu.be/EqHBA7lSOeg
=====================================================
AKElevon also Support (If you have any question or you can get help about any project Mail me) and Work in Following Fields.
=====Mail programmer74432@gmail.com====
1- 8051 related Projects
2- Image Processing Using Matlab
3- Electronics Projects
4- Machine Learning
5- Deep Learning using Matlab
6- Arduino Projects
7- Python and C++ --Window Form--
8- C# Window Form
9- PLC Projects
Four Way Traffic Light System with Counter Using Arduino
Video:
Description:
We can use 2bit decoder IC's for LED's to reduce usage of Arduino Pins. We can also use 4bit Up/Down Counter for Seven Segment. We use its Down Counter mode. We can use BCD Decoder IC's to decode input bits into Seven segment inputs.=====================================================
Application:
-----) To control Traffic
=====================================================
Software Used:
------) For Arduino Programming ***Arduino IDE****
------) For Simulation ***Proteus***
======================================================
Components:
- · Arduino UNO
- · Seven Segments Common Anode
- · LED’s (Red, Green, Blue/Yellow)
- · 4555 IC’s (2 to 4bit Decoder)
- · 74191 IC’s (4bit Up/Down Counter)
- · 7447 BCD Decoder IC’s
Code:
//Four
Way Traffic Light System With 3Bit Counter Using Arduino UNO
const int south_B1
= 0;
const int south_B2
= 1;
const int east_B1
= 2;
const int east_B2
= 3;
const int west_B1
= 4;
const int west_B2
= 5;
const int north_B1
= 6;
const int north_B2
= 7;
const int clk1 =
11; //Pulse For Timer1/Counter
of North
const int clk2 =
9; //Pulse For
Timer2/Counter of East
const int clk3 =
10; //Pulse For
Timer2/Counter of West
const int clk4 =
8; //Pulse For
Timer2/Counter of South
void setup() {
// put your
setup code here, to run once:
pinMode(north_B1, OUTPUT);
pinMode(east_B1, OUTPUT);
pinMode(west_B1, OUTPUT);
pinMode(south_B1, OUTPUT);
pinMode(north_B2, OUTPUT);
pinMode(east_B2, OUTPUT);
pinMode(west_B2, OUTPUT);
pinMode(south_B2, OUTPUT);
pinMode(clk1, OUTPUT);
pinMode(clk2, OUTPUT);
pinMode(clk3, OUTPUT);
pinMode(clk4, OUTPUT);
update(LOW, LOW, LOW, LOW, LOW, HIGH,
HIGH, LOW);
count(0);
delay(990);
update(LOW, LOW, LOW, LOW, LOW, HIGH,
HIGH, LOW);
count(0);
delay(990);
update(LOW, LOW, LOW, HIGH, HIGH, LOW,
LOW, LOW);
count(1);
delay(990);
update(LOW, LOW, LOW, HIGH, HIGH, LOW,
LOW, LOW);
count(1);
delay(990);
update(LOW, HIGH, HIGH, LOW, LOW, LOW,
LOW, LOW);
count(2);
delay(990);
update(LOW, HIGH, HIGH, LOW, LOW, LOW,
LOW, LOW);
count(2);
delay(990);
update(HIGH, LOW, LOW, LOW, LOW, LOW,
LOW, HIGH);
count(3);
delay(990);
update(HIGH, LOW, LOW, LOW, LOW, LOW,
LOW, HIGH);
count(3);
delay(990);
}
void loop() {
// put your
main code here, to run repeatedly:
update(LOW, LOW, LOW, LOW, LOW, HIGH,
HIGH, LOW);
count(3);
delay(990);
update(LOW, LOW, LOW, LOW, LOW, HIGH,
HIGH, LOW);
count(3);
delay(990);
update(LOW, LOW, LOW, HIGH, HIGH, LOW,
LOW, LOW);
count(3);
delay(990);
update(LOW, LOW, LOW, HIGH, HIGH, LOW,
LOW, LOW);
count(3);
delay(990);
update(LOW, HIGH, HIGH, LOW, LOW, LOW,
LOW, LOW);
count(3);
delay(990);
update(LOW, HIGH, HIGH, LOW, LOW, LOW,
LOW, LOW);
count(3);
delay(990);
update(HIGH, LOW, LOW, LOW, LOW, LOW,
LOW, HIGH);
count(3);
delay(990);
update(HIGH, LOW, LOW, LOW, LOW, LOW,
LOW, HIGH);
count(3);
delay(990);
}
void update(boolean x1, boolean x2, boolean x3, boolean x4, boolean x5, boolean x6, boolean x7, boolean x8)
{
digitalWrite(north_B1, x1);
digitalWrite(north_B2, x2);
digitalWrite(east_B1, x3);
digitalWrite(east_B2, x4);
digitalWrite(west_B1, x5);
digitalWrite(west_B2, x6);
digitalWrite(south_B1, x7);
digitalWrite(south_B2, x8);
}
void count(int tec)
{
if (tec == 0)
{
digitalWrite(clk1, LOW);
digitalWrite(clk2, LOW);
digitalWrite(clk3, LOW);
digitalWrite(clk4, LOW);
delay(10);
digitalWrite(clk1, HIGH);
digitalWrite(clk2, LOW);
digitalWrite(clk3, LOW);
digitalWrite(clk4, LOW);
}
else if (tec == 1)
{
digitalWrite(clk1, LOW);
digitalWrite(clk2, LOW);
digitalWrite(clk3, LOW);
digitalWrite(clk4, LOW);
delay(10);
digitalWrite(clk1, HIGH);
digitalWrite(clk2, LOW);
digitalWrite(clk3, LOW);
digitalWrite(clk4, HIGH);
}
else if (tec == 2)
{
digitalWrite(clk1, LOW);
digitalWrite(clk2, LOW);
digitalWrite(clk3, LOW);
digitalWrite(clk4,
LOW);
delay(10);
digitalWrite(clk1, HIGH);
digitalWrite(clk2, LOW);
digitalWrite(clk3, HIGH);
digitalWrite(clk4, HIGH);
}
else
{
digitalWrite(clk1, LOW);
digitalWrite(clk2, LOW);
digitalWrite(clk3, LOW);
digitalWrite(clk4, LOW);
delay(10);
digitalWrite(clk1, HIGH);
digitalWrite(clk2, HIGH);
digitalWrite(clk3, HIGH);
digitalWrite(clk4, HIGH);
}
}
======================================================
Other Projects:
Four Way Traffic Light System Using Arduino Simple Version
------ https://youtu.be/mJ0ANveFoZ8
Four Way Traffic Light System DLD Project
------ https://youtu.be/Sso0yG1Leq4
=====================================================
AKElevon also Support (If you have any question or you can get help about any project Mail me) and Work in Following Fields.
=====Mail programmer74432@gmail.com====
1- 8051 related Projects
2- Image Processing Using Matlab
3- Electronics Projects
4- Machine Learning
5- Deep Learning
6- Arduino Projects
7- Python and C++ --Window Form--
DC Motor Speed Control using Potentiometer
YouTube Video:
7-DC Motor Speed Control using Potentiometer is created by AKElevon. We read analog output of potentiometer and Observe DC motor speed.
=====================================================
Application:
-----) Intensity of LED
-----) Speed of Motor
=====================================================
Software Used:
------) For Arduino Programming ***Arduino IDE****
------) For Simulation ***Proteus***
------) For Breadboard Diagram ***Fritzing***
======================================================
Feature of Tutorial:
----- RGB LED's Interfacing with Arduino
======================================================
Other Projects:
Four Way Traffic Light System Using Arduino Simple Version
------ https://youtu.be/mJ0ANveFoZ8
Four Way Traffic Light System DLD Project
------ https://youtu.be/Sso0yG1Leq4
=====================================================
AKElevon also Support (If you have any question or you can get help about any project Mail me) and Work in Following Fields.
=====Mail programmer74432@gmail.com====
1- 8051 related Projects
2- Image Processing Using Matlab
3- Electronics Projects
4- Machine Learning
5- Deep Learning
6- Arduino Projects
7- Python and C++ --Window Form--
Build a Controllable RGB LED
YouTube Video:
3-Build a Controllable RGB LED is created by AKElevon. We control RGB LED. We can change Color of RGB LED by selecting Input. We can use Arduino UNO and RGB LED for this tutorial.
=====================================================
Application:
-----) Intensity of LED
-----) Speed of Motor
=====================================================
Software Used:
------) For Arduino Programming ***Arduino IDE****
------) For Simulation ***Proteus***
------) For Breadboard Diagram ***Fritzing***
======================================================
Feature of Tutorial:
----- RGB LED's Interfacing with Arduino
======================================================
Other Projects:
Four Way Traffic Light System Using Arduino Simple Version
------ https://youtu.be/mJ0ANveFoZ8
Four Way Traffic Light System DLD Project
------ https://youtu.be/Sso0yG1Leq4
=====================================================
AKElevon also Support (If you have any question or you can get help about any project Mail me) and Work in Following Fields.
=====Mail programmer74432@gmail.com====
1- 8051 related Projects
2- Image Processing Using Matlab
3- Electronics Projects
4- Machine Learning
5- Deep Learning
6- Arduino Projects
7- Python and C++ --Window Form--
Four Bit Counter Using Shift Register with Arduino
Four Bit Counter Using Shift Register with Arduino is created by AKElevon. We build a simple Four Bit Counter Using Shift Register with Arduino. We can use Arduino UNO, 2 to 4 bit Decoder IC, 8 bit Shift Register and 2 digit 7 Segment for this project.
=====================================================
Software Used:
------) For Arduino Programming ***Arduino IDE****
------) For Simulation ***Proteus***
======================================================
Feature of Project:
----- Bluetooth Controlled
----- Android App
======================================================
Other Projects:
Four Way Traffic Light System Using Arduino Simple Version
------ https://youtu.be/mJ0ANveFoZ8
Four Way Traffic Light System DLD Project
------ https://youtu.be/Sso0yG1Leq4
=====================================================
AKElevon also Support "If you have any question or you can get help about any project Contact me whats-app no given below" and Work in Following Fields.
=====Whatsapp no +923206508366====
1- 8051 related Projects
2- Image Processing Using Matlab
3- Electronics Projects
4- Machine Learning
5- Deep Learning
6- Arduino Projects
7- Python and C++ --Window Form--
Introduction to Robotics
BACKGROUND
The history of industrial automation is characterized by periods of rapid change in
popular methods. Either as a cause or, perhaps, an effect, such periods of change in
automation techniques seem closely tied to world economics. Use of the industrial
robot, which became identifiable as a unique device in the 1960s, along with
computer-aided design (CAD) systems and computer-aided manufacturing (CAM)
systems, characterizes the latest trends in the automation of the manufacturing
process. These technologies are leading industrial automation through another
transition, the scope of which is stifi unknown.
In North America, there was much adoption of robotic equipment in the early
1980s, followed by a brief pull-back in the late 1980s. Since that time, the market has
been growing, although it is subject to economic swings, as are all markets. The number of robots being installed per year in the major
industrial regions of the world. Note that Japan reports numbers somewhat differently
from the way that other regions do: they count some machines as robots
that in other parts of the world are not considered robots (rather, they would be
simply considered "factory machines"). Hence, the numbers reported for Japanare
somewhat inflated.
A major reason for the growth in the use of industrial robots is their declining
cost. Through the decade of the 1990s, robot prices dropped
while human labor costs increased. Also, robots are not just getting cheaper, they
are becoming more effective—faster, more accurate, more flexible. If we factor
these quality adjustments into the numbers, the cost of using robots is dropping even
faster than their price tag is. As robots become more cost effective at their jobs,
and as human labor continues to become more expensive, more and more industrial
jobs become candidates for robotic automation. This is the single most important
trend propelling growth of the industrial robot market. A secondary trend is that,
economics aside, as robots become more capable they become able to do more and
more tasks that might be dangerous or impossible for human workers to perform.
The applications that industrial robots perform are gradually getting more
sophisticated, but it is stifi the case that, in the year 2000, approximately 78%
of the robots installed in the US were welding or material-handling robots.
A more challenging domain, assembly by industrial robot, accounted for 10% of
installations.
This book focuses on the mechanics and control of the most important form
of the industrial robot, the mechanical manipulator. Exactly what constitutes an
industrial robot is sometimes debated. Devices such as that shown in are
always included, while numerically controlled (NC) milling machines are usually
not. The distinction lies somewhere in the sophistication of the programmability of
the device—if a mechanical device can be programmed to perform a wide variety
of applications, it is probably an industrial robot. Machines which are for the most
part limited to one class of task are considered fixed automation. For the purposes
of this text, the distinctions need not be debated; most material is of a basic nature
that applies to a wide variety of programmable machines.
By and large, the study of the mechanics and control of manipulators is
not a new science, but merely a collection of topics taken from "classical" fields.
Mechanical engineering contributes methodologies for the study of machines in
static and dynamic situations. Mathematics supplies tools for describing spatial
motions and other attributes of manipulators. Control theory provides tools for
designing and evaluating algorithms to realize desired motions or force applications.
Electrical-engineering techniques are brought to bear in the design of sensors
and interfaces for industrial robots, and computer science contributes a basis for
programming these devices to perform a desired task.
THE MECHANICS AND CONTROL OF MECHANICAL MANIPULATORS
The following sections introduce some terminology and briefly preview each of the
topics that will be covered in the text.
Description of position and orientation
In the study of robotics, we are constantly concerned with the location of objects in
three-dimensional space. These objects are the links of the manipulator, the parts
and tools with which it deals, and other objects in the manipulator's environment.
At a crude but important level, these objects are described by just two attributes:
position and orientation. Naturally, one topic of immediate interest is the manner
in which we represent these quantities and manipulate them mathematically.
In order to describe the position and orientation of a body in space, we wifi
always attach a coordinate system, or frame, rigidly to the object. We then proceed
to describe the position and orientation of this frame with respect to some reference
coordinate system. Any frame can serve as a reference system within which to express the
position and orientation of a body, so we often think of transforming or changing
the description of these attributes of a body from one frame to another. Chapter 2
discusses conventions and methodologies for dealing with the description of position
and orientation and the mathematics of manipulating these quantities with respect
to various coordinate systems.
Developing good skifis concerning the description of position and rotation of
rigid bodies is highly useful even in fields outside of robotics.
Forward kinematics of manipulators
Kinematics is the science of motion that treats motion without regard to the forces
which cause it. Within the science of kinematics, one studies position, velocity, acceleration, and all higher order derivatives of the position variables (with respect
to time or any other variable(s)). Hence, the study of the kinematics of manipulators
refers to all the geometrical and time-based properties of the motion.
Manipulators consist of nearly rigid links, which are connected by joints that
allow relative motion of neighboring links. These joints are usually instrumented
with position sensors, which allow the relative position of neighboring links to be
measured. In the case of rotary or revolute joints, these displacements are called
joint angles. Some manipulators contain sliding (or prismatic) joints, in which the
relative displacement between links is a translation, sometimes called the joint
offset.
The number of degrees of freedom that a manipulator possesses is the number
of independent position variables that would have to be specified in order to locate
all parts of the mechanism. This is a general term used for any mechanism. For
example, a four-bar linkage has only one degree of freedom (even though there
are three moving members). In the case of typical industrial robots, because a
manipulator is usually an open kinematic chain, and because each joint position is
usually defined with a single variable, the number of joints equals the number of
degrees of freedom.
At the free end of the chain of links that make up the manipulator is the endeffector.
Depending on the intended application of the robot, the end-effector could
be a gripper, a welding torch, an electromagnet, or another device. We generally
describe the position of the manipulator by giving a description of the tool frame,
which is attached to the end-effector, relative to the base frame, which is attached
to the nonmoving base of the manipulator. A very basic problem in the study of mechanical manipulation is called forward
kinematics. This is the static geometrical problem of computing the position and
orientation of the end-effector of the manipulator. Specifically, given a set of joint angles, the forward kinematic problem is to compute the position and orientation of
the tool frame relative to the base frame. Sometimes, we think of this as changing
the representation of manipulator position from a joint space description into a
Cartesian space description.
Introduction to artificial intelligence
"Artificial intelligence" is the ability of machines to do things
that people would say require intelligence. Artificial intelligence (AI)
research is an attempt to discover and describe aspects of human intelligence
that can be simulated by machines. For example, at present
there are machines that can do the following things:
1. Play games of strategy (e.g., Chess, Checkers, Poker) and
(in Checkers) learn to play better than people.
2. Learn to recognize visual or auditory patterns.
3. Find proofs for mathematical theorems.
4. Solve certain, well-formulated kinds of problems.
5. Process information expressed in human languages.
The extent to which machines (usually computers) can do these
things independently of people is still limited; machines currently exhibit
in their behavior only rudimentary levels of intelligence. Even so, the
possibility exists that machines can be made to show behavior indicative
of intelligence, comparable or even superior to that of humans.'
Alternatively, AI research may be viewed as an attempt to develop
a mathematical theory to describe the abilities and actions of things
(natural or man-made) exhibiting "intelligent" behavior, and serve as a
calculus for the design of intelligent machines. As yet there is no "mathematical
theory of intelligence," and researchers dispute whether there
ever will be.
This book serves as an introduction to research on machines that display intelligent behavior. Such machines some fimes
will be called "artificial intelligence's," "intelligent machines," or "mechanical
intelligence's."
The inclination in this book is toward the first viewpoint of AI research,
without forsaking the second. Since AI research is still in its
infancy, it is therefore prudent to withhold estimation of its future. It is
best to begin with a summation of present knowledge, considering such
questions as:
1. What is known .about natural intelligence?
2. When can we justifiably call a machine intelligent?
3. How and to what extent do machines currently simulate intelligence
or display intelligent behavior?
4. How might machines eventually simulate intelligence?
5. How can machines and their behavior be described mathematically?
6. What uses could be made of intelligent machines?
Each of these questions will be explored in some detail in this
book. The first and second questions are covered in this chapter. It is
hoped that the six questions are covered individually in enough detail
so that the reader will be guided to broader study if he is so inclined.
For parts of this book, some knowledge of mathematics (especially sets,
functions, and logic) is presupposed, though much of the book is understandable
without it.
TURING'S TEST
A basic goal of AI research is to construct a machine that exhibits
the behavior associated with human intelligence, that is, comparable to
the intelligence of a human being. It is not required that the
machine use the same underlying mechanisms (whatever they are) that
are used in human cognition, nor is it required that the
machine go through stages of development or learning such as those
through which people progress.
The classic experiment proposed for determining whether a machine
possesses intelligence on a human level is known as Turing's test (after
A. M. Turing, who pioneered research in computer logic, undecidability theory, and artificial intelligence). This experiment has yet to be performed
seriously, since no machine yet displays enough intelligent
behavior to be able to do well in the test. Still, Turing's test is the basic
paradigm for much successful work and for many experiments in
machine intelligence, from the Samuel's Checkers Player to "semanticinformation
processing" programs such as Colby's PARRY or Raphael's.
Basically, Turing's test consists of presenting a human being, A,
with a typewriter-like or TV-like terminal, which he can use to converse
with two unknown (to him) sources, B and C ). The
interrogator A is told that one terminal is controlled by a machine and
that the other terminal is controlled by a human being whom A has
never met. A is to guess which of B and C is the machine and which is
the person. If A cannot distinguish one from the other with significantly
better than 50% accuracy, and if this result continues to hold no matter
what people are involved in the experiment, the machine is said to
simulate human intelligence.
Some comments on Turing's test are in order. First, the nature
of Turing's test is such that it does not permit the interrogator A to observe
the physical natures of B and C; rather, it permits him only to
observe their "intellectual behavior," that is, their ability to communicate
with formal symbols and to "think abstractly." So, while the test
does not enable A to be prejudiced by the physical nature of either
B or C, neither does it give a way to compare those aspects of an
entity's behavior that reflect its ability to act non abstractly in the real
world-that is, to be ·intelligent in its performance of concrete operations
on objects. Can the machine, for example, fry an egg or clean
a house?
Second, one possible achievement of AI research would be to produce
a complete description of a machine that can successfully pass
Turing's test, or to find a proof that no machine can pass it. The complete
description must be of a machine that can actually be constructed.
A proof that there is no such constructive machine (it might say, e.g.,
"The number of parts in such a machine must be greater than the
number of electrons in the universe.") is consequently to be regarded
as a proof of the "no machine" alternative.
Third, it may be that more than one type of machine can pass
Turing's test. In this case, AI research has a secondary problem of
creating a general description of all machines that will successfully pass
Turing's test.
Fourth, if a machine passes Turing's test, it means in effect that
there is at least one machine that can learn to solve problems as well as
a human being. This would lead to asking if a constructive machine can
be described which would be capable of learning to solve not only those
problems that people can usually solve, but also those that people create
but can only rarely solve. That is, is it possible to build mechanical
intelligence's that are superior to human intelligence?
It is not yet possible to give a definite answer to any of these
questions. Some evidence exists that AI research may eventually attain
at least the goal of a machine that passes Turing's test.
It is clear that the intellectual capabilities of a human being are
directly related to the functioning of his brain, which appears to be a
finite structure of cells. Moreover, people have succeeded in constructing
machines that can "learn" to produce solutions to certain specific
intellectual problems,· which are superior to the solutions people can
produce. The most notable example is Samuel's Checkers Player, which
has learned to play a better game of Checkers than its designer, and
which currently plays at a championship level.
Software And Hardware II
Output Devices
Once data are processed, output devices translate the language of bits into a form
humans can understand. Output devices are divided into two basic categories: those
that produce hard copy, including printers and plotters; and those that produce
soft (digital) copy, including monitors (the most commonly used output device).
Soft copy is also produced by speakers that produce speech, sound, or music.
Secondary Storage Devices
The memory we have discussed so far is temporary or volatile. To save your work
permanently, you need secondary storage devices. Magnetic disk and magnetic tape
and optical disks are used as secondary storage media. Magnetic media (disk,
diskette, tape, and high-capacity Zip disks) store data and programs as magnetic spots or electromagnetic charges. High-capacity optical disks (compact disks [CDs]
or digital video disks [DVDs]) store data as pits and lands burned into a plastic disk.
Solid-state memory devices include flash memory cards used in notebooks, memory
sticks, and very compact key chain devices; these devices have no moving parts,
are very small, and have a high capacity. USB flash drives have a huge capacity for
information.
SOFTWARE
Software refers to the programs—the step-by-step instructions that tell the hardware
what to do. Without software, hardware is useless. Software falls into two general categories:
system software and application software.
System Software
System software consists of programs that let the computer manage its resources.
The most important piece of system software is the operating system. The operating
system is a group of programs that manage and organize resources of the computer.
It controls the hardware, manages basic input and output operations, keeps track
of your files saved on disk and in memory, and directs communication between
the CPU and other pieces of hardware. It coordinates how other programs work
with the hardware and with each other. Operating systems also provide the user
interface—that is, the way the user communicates with the computer. For example,
Windows provides a graphical user interface, pictures or icons that you click on with
a mouse. When the computer is turned on, the operating system is booted or loaded
into the computer’s RAM. No other program can work until the operating system is
booted.
Application Software
Application software allows you to apply computer technology to a task you need
done. There are application packages for many needs.
Word-processing software allows you to enter text for a paper, report, letter, or
memo. Once the text is entered, you can format it, that is, make it look the way you
want it to look. You can change the size, style, and face of the type. In addition, margins
and justification can be set to any specifications. Style checkers can help you
with spelling and grammar. Word-processing software also includes thesauri, headers
and footers, index generators, and outlining features.
Electronic spreadsheets allow you to process numerical data. Organized into
rows and columns intersecting to form cells, spreadsheets make doing arithmetic
almost fun. You enter the values you want processed and the formula that tells the
software how to process them and the answer appears. If you made a mistake entering
a value, just change it and the answer is automatically recalculated. Spreadsheet
software also allows you to create graphs easily—just by indicating what cells you
want graphed. Electronic health records (EHRs) can use spreadsheets to graph a
series of a patient’s blood values over time.
Database management software permits you to manage large quantities of data
in an organized fashion. Information in a database is organized in tables. The database
management software makes it easy to enter data, edit data, sort or organize
data, search for data that meets a particular criterion, and retrieve data. Once the
structure of the table is defined and the data entered, that data can be used for a
variety of purposes without being retyped. Eye-pleasing, businesslike reports can
easily be generated by simply defining their structure.
There are also specialized software packages used in specific fields such as medicine.
For example, there are specialized accounting programs used in medical
offices. Microsoft is considering developing a new software package for the health
care industry. Communications software includes Web browsers, such as Internet Explorer.
These programs allow you to connect your computer to other computers in a
network.
Software And Hardware
Hardware
The physical components of a computer are called hardware. Pieces of hardware may
be categorized according to the functions each performs: input, process, output, and
storage. As you recall, inside the computer, all data are represented by the binary
digits (bits) 1 (one) and 0 (zero). To translate data into 1s and 0s is to digitize.
Input Devices
Input devices function to take data that people understand and translate those data
into a form that the computer can process. Input devices may be divided into two
categories: keyboards and direct-entry devices.
Direct-entry devices include pointing devices, scanning devices, smart and optical
cards, speech and vision input, touch screens, sensors, and human-biology input
devices.
The pointing device with which you are most familiar is the mouse, which you
can use to position the insertion point on the screen, or make a choice from a
menu. Other pointing devices are variations of the mouse. Light pens, digitizing
tablets, and pen-based systems allow you to use a pen or stylus to enter data. The
marks you make or letters you write are digitized.
Most scanning devices digitize data by shining a light on an image and measuring
the reflection. Bar-code scanners read the universal product codes; optical mark
recognition devices can recognize a mark on paper; optical character recognition
devices can recognize letters. Special scanning equipment called magnetic ink character
recognition (MICR) is used by banks to read the numbers at the bottoms of
checks. You are familiar with fax machines, which scan images, digitize them, and
send them over telecommunication lines. Some scanning devices, called image
scanners, scan and digitize whole pages of text and graphics. One scanning device of
particular interest to those with impaired eyesight is the Kurzweil scanner—hardware
and software—which scans printed text and reads it aloud to the user.
Radio frequency identification (RFID) tags (input devices) are now used to
identify anything from the family dog to the sponge the surgeon left in your body, by
sending out radio waves. One medical insurance company is conducting a two-year
trial with chronically ill patients who will have an RFID the size of a grain of rice
implanted. The RFID will contain their medical histories. It transmits 30 feet without
the person’s knowledge. In 2006, one U.S. company implanted chips in two of
its employees “as a way of controlling access to a room where it holds security video
footage for government agencies and police.” Several different kinds of cards are used as input devices: your automated teller
machine (ATM) card or charge card contains a small amount of data in the magnetic stripe. A smart card can hold more data and contains a microprocessor. Smart cards
have been used as debit cards. Several states now use smart cards as driver’s licenses.
The card includes a biometric identifier and may include other personal information
as well. Privacy advocates fear that there is so much information on the cards that they
can become a target for identity thieves. An optical card holds about two thousand
pages. The optical card may be used to hold your entire medical history, including
test results and X-rays. If you are hospitalized in an emergency, the card—small
enough to carry in your wallet—would make this information immediately available.
Vision input systems are currently being developed and refined. A computer
uses a camera to digitize images and stores them. The computer “sees” by having the
camera take a picture of an object. The digitized image of this object is then compared
to images in storage. This technology can be used in adaptive devices, such as
in glasses that help Alzheimer’s patients. The glasses include a database of names
and faces; a camera sees a face, and if it “recognizes” the face, it gives the wearer the
name of the subject.
Speech input systems allow you to talk to your computer, and the computer
processes the words as data and commands. A speech-recognition system contains a
dictionary of digital patterns of words. You say a word and the speech-recognition
system digitizes the word and compares the word to the words in its dictionary. If it
recognizes the word, the command is executed. There are speech dictation packages
tailored to specific professions. A system geared toward medicine would
include an extensive vocabulary of digitized medical terms and would allow the
creation of patient records and medical reports. This system can be used as an
input device by physicians who, in turn, can dictate notes, even while, for example,
operating. Speech recognition is also especially beneficial as an enabling technology,
allowing those who do not have the use of their hands to use computers. In
English, many phrases and words sound the same, for example, hyphenate and -8
(hyphen eight). Speech-recognition software allows mistakes such as these to be
corrected by talking. The newest speech-recognition software does not need training
and gets “smarter” as you use it. It looks at context to get homophones (to, too,
two) correct. Of particular interest to health professionals are input devices called sensors.
A sensor is a device that collects data directly from the environment and sends those
data to a computer. Sensors are used to collect patient information for clinical
monitoring systems, including physiological, arrhythmia, pulmonary, and obstetrical/
neonatal systems. In critical care units, monitoring systems make nurses aware of
any change in a patient’s condition immediately. They detect the smallest change in
temperature, blood pressure, respiration, or any other physiological measurement.
The newest kinds of input devices are called human-biology input devices. They
allow you to use your body as an input device. They include biometrics, which are
being used in security systems to protect data from unauthorized access. Biometrics
identify people by their body parts. Biometrics include fingerprints, hand prints,
face recognition, and iris scans. Once thought to be almost 100 percent accurate,
biometric identification systems are now recognized as far from perfect. Line-of-sight input allows the user to look at a keyboard displayed on a screen
and indicate the character selected by looking at it. Implanted chips have allowed
locked-in stroke patients (a syndrome caused by stroke where a person cannot
respond, although he or she knows what is going on) to communicate with a computer
by focusing brain waves (brain wave input); this is experimental; research is
continuing.
Processing Hardware and Memory
Once data are digitized, they are processed. Processing hardware is the brain of the
computer. Located on the main circuit board (or motherboard), the processor or
system unit contains the central processing unit (CPU) and memory. The CPU has
two parts: the arithmetic-logic unit, which performs arithmetic operations and logical
operations of comparing; and the control unit, which directs the operation of
the computer in accordance with the program’s instructions.
The CPU works closely with memory. The instructions of the program being
executed must be in memory for processing to take place. Memory is also located
on chips on the main circuit board. The part of memory where current work is temporarily
stored during processing is called random-access memory (RAM). It is temporary
and volatile. The other part of memory is called read-only memory (ROM)
or firmware; it contains basic start-up instructions, which are burned into a chip at
the factory; you cannot change the contents of ROM.
Many computers have open architecture that allows you to add devices. The system
board contains expansion slots, into which you can plug expansion boards for
additional hardware. The board has sockets on the outside, called ports. You can
plug a cable from your new device into the port. The significance of open architecture
is the fact that it enables you to add any hardware and software interfaces to
your existing computer system. This means you can not only expand the memory of
your computer but also add devices that make your computer more amenable to
uses in medicine. Expansion boards also allow the use of virtual reality simulators,
which help in teaching certain procedures.
