Discount Computers

Whilst our lives have become dependent on computers, our bodies
haven’t quite accepted the idea. Every day computer users
complain of blurred vision, tired eyes, gritty eyes and
headaches. Many start to wear eye glasses and blame their
computers. Others are convinced that their computer has caused
their Myopia (nearsightedness) to worsen. High tech employees
worry about radiation from the computer screen. Can the computer
lead to irreversible eye damage?

The good news is that extensive eye care health research in
Israel and in North America has shown conclusively and
repeatedly that computers do not cause eye disease. Nor has it
been shown that intensive computer work can lead to or effect
myopia in high tech workers. (The situation with children is
slightly more controversial but this will be discussed in
another article) However there is no doubt that computers can
lead to many temporary eye problems most of which can be solved
by simple changes in work pattern.

The sooner any symptoms begin, for instance within half an hour
of commencing work, the more likely it is that there is a
specific problem. Developing tired eyes after eight hours of non
stop intensive visual activity is normal though. Try running the
New York, London or Jerusalem marathons and see if your legs get
tired.

The following are some simple tips to prevent eye strain and to
enhance your eye health care for many years to come.

Have your eyes and vision checked at least once a year. Any
minor vision problem will be aggravated by computer use. If you
wear glasses or contact lenses, be sure they are appropriate for
computer use and for the distance between you and your computer.

Be sure to rest your eyes regularly, especially if you are new
to computers. Remember the 20:20 rule. Every 20 minutes, look in
to the distance for 20 seconds. Continuous use of any part of
the body, including your eyes, will inevitably lead to fatigue.

Your computer should be at a comfortable distance (about
30-40cm) and the top of the screen should be facing you and
slightly below eye level. Adjust your desk or chair so that this
is the case. Our eyes are designed to point forwards and
downwards when looking at near objects, e.g. when reading.
Looking upwards or sideways at your computer will rapidly lead
to eye strain.

Hang any material you are copying at the same distance and as
close to the screen as possible. Use a manuscript holder. This
will prevent constant refocusing to differing distances and
directions.

Minimise glare from your computer screen due to reflections from
lights or windows. This can be done by adjusting the direction
of your screen or by attaching a glare reduction filter. Your
pupil changes in size according to the brightness of the screen
and excessive movement of the pupil caused by multiple
reflections can cause headaches. Bright sunlight from a window
behind your screen will have a similar effect. Glare also causes
you to screw up your eyes, which if prolonged, will lead to
headaches. However make sure your desk and key board are
sufficiently illuminated.

Occasional use of artificial tear eye drops (as recommended by
your eye doctor) can help dry eyes symptoms. We tend to blink
less when concentrating intently, and when looking straight
ahead much of the eye is exposed leading to increased tear
evaporation and dry eyes. Remember to blink more.

Keep your computer screen clean. Dust and fingerprints can
reduce clarity.

Poor quality computer screens can lead to eye strain. Low
resolution, low pixel numbers and high contrast colors can put
an extra strain on the eyes when reading from a screen. The
Refresh Rate of a computer is a measure of how often the display
unit refreshes or redraws the picture per second. In the past
rates of 60Hz were acceptable, but flickering of the screen was
evident at this rate causing headaches. It is now recommended
that the rate should not be less than 70Hz and most new monitors
are 75-85 Hz.

Sensible use of your computer will reduce headaches and eye
discomfort, and increase productivity.

About the author:
Dr Andrew Fink MD FRCOphth is a practising Eye Surgeon in Tel
Aviv, Israel. Originally from England he specialises in Laser
Vision Correction, and Cataract Surgery. He is medical adviser
to Healthylens.com, an on line discount contact lens service.
(http://www.healthylens.com)

There are so many types of digital camera printer on offer that
finding the right one for your personal and business needs can
be a very daunting task. However, there are a few main points to
consider when choosing a digital camera printer that will help
make the process a little easier.

It isn’t necessary to have a high-resolution digital camera
printer to make great pictures. The higher the printer
resolution you use, the more pixels you’ll need in your original
image file to produce a decent size print with your digital
camera printer. The actual file size (in pixels) of the image
from your camera, divided by the printer resolution (in dots per
inch), determines the final print size. So, if the image file
size is 1,478 x 1,280 pixels, and you print the file at 163 dpi
with your digital camera printer, the final print size will be 9
x 7.8 inches.

If your digital camera printer resolution is 300 dpi, then you
will have a higher resolution with more dots per inch laid down
on the paper but a smaller print size. It is therefore important
to ensure that you have the image file size to support the
resolution of your digital camera printer.

The price of a digital camera printer is lowering whilst the
quality is increasing. If you choose the right digital camera
printer you can have your own photo lab, greeting card designing
and sign making department with just your digital camera, some
software and a printer.

The aim of having a digital camera printer is to produce
photographic prints that look as close to real photographic
prints as possible. This type of digital camera printer was once
very expensive to buy and run, but technological advancements
and competitive pricing have made them much more accessible to
the average buyer. Ink-jet printers are now available that can
produce excellent prints and a near photo-quality printer is
much easier to find for people with a small budget. You will
probably want to have a digital camera printer with a scanning
feature built-in. If you want to produce same-size scans of
photos you don’t need scan resolutions higher than 300 samples
per inch for the scanner.

Your digital camera printer should also have the same interface
that you already have on your computer. So if you have USB, then
get a digital camera printer with USB, a Firewire printer if you
have Firewire or a SCSI printer if you have SCSI. There should
be no need to buy a digital camera printer that requires a
different interface to the one you already have on your computer
or it will cost you more to upgrade if necessary.

About the author:
Steve Gargin is the administrator of
http://digital-camera-reviews.helper-guru.com/camera-digital-phot
ography-wedding/index.html which is a great website dedicated to
giving free advice on Digital Cameras.

The Artificial Intelligence community sought to understand human
intelligence by building computer programs, which exhibited
intelligent behavior. Intelligence was perceived to be a problem
solving ability. Most human problems appeared to have reasoned,
rather than mathematical, solutions. The diagnosis of a disease
could hardly be calculated. If a patient had a group of
symptoms, then she had a particular disease. But, such reasoning
required prior knowledge. The programs needed to have the
“knowledge” that the disease exhibited a particular group of
symptoms. For the AI community, that vague knowledge residing in
the minds of “Experts” was superior to text book knowledge. So
they called the programs, which solved such problems, Expert
Systems.

Expert Systems managed goal oriented problem solving tasks
including diagnosis, planning, scheduling, configuration and
design. One method of knowledge representation was through “If,
then…” rules. When the “If” part of a rule was satisfied, then
the “Then” part of the rule was concluded. These became rule
based Expert Systems. But knowledge was sometimes factual and at
other times, vague. Factual knowledge had clear cause to effect
relationships, where clear conclusions could be drawn from
concrete rules. Pain was one symptom of a disease. If the
disease always exhibited pain, then pain pointed to the disease.
But vague and judgmental knowledge was called heuristic
knowledge. It was more of an art. The pain symptom could not
mechanically point to diseases, which occasionally exhibited
pain. Uncertainty did not yield concrete answers.

The AI community tried to solve this problem by suggesting a
statistical, or heuristic analysis of uncertainty. The
possibilities were represented by real numbers or by sets of
real-valued vectors. The vectors were evaluated by means of
different “fuzzy” concepts. The components of the measurements
were listed, giving the basis of the numerical values.
Variations were combined, using methods for computing
combination of variances. The combined uncertainty and its
components were expressed in the form of “standard deviations.”
Uncertainty was given a mathematical expression, which was
hardly useful in the diagnosis of a disease.

The human mind did not compute mathematical relationships to
assess uncertainty. The mind knew that a particular symptom
pointed to a possibility, because it used intuition, a process
of elimination, to instantly identify patterns. Vague
information was powerfully useful to an elimination process,
since they eliminated many other possibilities. If the patient
lacked pain, all diseases, which always exhibited pain, could be
eliminated. Diseases, which sometimes exhibited pain were
retained. Further symptoms helped identification from a greatly
reduced database. A selection was easier from a smaller group.
Uncertainty could be powerfully useful for an elimination
process.

Intuition was an algorithm, which evaluated the whole database,
eliminating every context that did not fit. This algorithm has
powered Expert Systems which acted speedily to recognize a
disease, identify a case law or diagnose the problems of a
complex machine. It was instant, holistic, and logical. If
several parallel answers could be presented, as in the multiple
parameters of a power plant, recognition was instant. For the
mind, where millions of parameters were simultaneously
presented, real time pattern recognition was practical. And
elimination was the key, which could conclusively handle
uncertainty, without resort to abstruse calculations.

About the author:
Abraham Thomas is the author of The Intuitive Algorithm, a book,
which suggests that intuition is a pattern recognition
algorithm. The ebook version is available at
http://www.intuition.co.in. The book may be purchased only in
India. The website, provides a free movie and a walk through to
explain the ideas.