7 Deadly sins of Email…Deadly Sins#1

Do you want to receive lots of spam email? Do you want to be more likely to get viruses in email? Do you want complete strangers to have easy access to your email address? Do you like reading messages that are full of < < < < at the start of every message?

If you can answer ‘yes’ to all of the above, then don’t read any further. On the other hand, if you want to avoid some deadly sins that cause unnecessary grief with email, read on. After you’ve read it – spread the message.

DEADLY SIN #1 – FORWARDING ALL THOSE WARNINGS

You’ve no doubt seen them. Tell everyone you know about a telephone scam, or a nasty virus or even those that promise you prize money from Bill Gates. So far, I haven’t come across one message that is genuine, they are usually a hoax or misguided, or both. Sometimes they claim to have originated in some health department, or the police, or Microsoft/Symantec etc. Still all hoaxes.

Watch out for the virus warnings that tell you to delete a file on your computer too. It’s most likely to be a useful system file that you end up deleting!

Add to this sin, the amazing photographs that get sent around, like the giant cat or the shark leaping out of the water to grab a man dangling from a helicopter. Most of these are faked photographs.

Generally, all you are doing is adding to the clogged up mail system.

What if you think it might be true?

Check it out first. These sites will usually have information about messages that are circulated so freely. Copy and paste a phrase or the title from the message (try more than one option if you don’t get a result) into the search facility on the site.

Dual Core Processor

Definition

Seeing the technical difficulties in cranking higher clock speed out of the present single core processors, dual core architecture has started to establish itself as the answer to the development of future processors. With the release of AMD dual core opteron and Intel Pentium Extreme edition 840, the month of April 2005 officially marks the beginning of dual core endeavors for both companies.

The transition from a single core to dual core architecture was triggered by a couple of factors. According to Moore’s Law, the number of transistors (complexity) on a microprocessor doubles approximately every 18 months. The latest 2 MB Prescott core possesses more than 160 million transistors; breaking the 200 million mark is just a matter of time. Transistor count is one of the reasons that drive the industry toward the dual core architecture. Instead of using the available astronomically high transistor counts to design a new, more complex single core processor that would offer higher performance than the present offerings, chip makers have decided to put these transistors to use in producing two identical yet independent cores and combining them in to a single package.

To them, this is actually a far better use of the available transistors, and in return should give the consumers more value for their money. Besides, with the single core’s thermal envelope being pushed to its limit and severe current leakage issues that have hit the silicon manufacturing industry ever since the transition to 90 nm chip fabrication, it’s extremely difficult for chip makers (particulary Intel) to squeeze more clock speed out of the present single core design. Pushing for higher clock speeds is not a feasible option at present because of transistor current leakage. And adding more features into the core will increase the complexity of the design and make it harder to manage. These are the factors that have made the dual core option the more viable alternative in making full use of the amount of transistors available.

What is a dual core processor?
A dual core processor is a CPU with two separate cores on the same die, each with its own cache. It’s the equivalent of getting two microprocessors in one. In a single-core or traditional processor the CPU is fed strings of instructions it must order, execute, then selectively store in its cache for quick retrieval. When data outside the cache is required, it is retrieved through the system bus from random access memory (RAM) or from storage devices. Accessing these slows down performance to the maximum speed the bus, RAM or storage device will allow, which is far slower than the speed of the CPU. The situation is compounded when multi-tasking. In this case the processor must switch back and forth between two or more sets of data streams and programs. CPU resources are depleted and performance suffers.

In a dual core processor each core handles incoming data strings simultaneously to improve efficiency. Just as two heads are better than one, so are two hands. Now when one is executing the other can be accessing the system bus or executing its own code. Adding to this favorable scenario, both AMD and Intel’s dual-core flagships are 64-bit.
To utilize a dual core processor, the operating system must be able to recognize multi-threading and the software must have simultaneous multi-threadi0ng technology (SMT) written into its code. SMT enables parallel multi-threading wherein the cores are served multi-threaded instructions in parallel. Without SMT the software will only recognize one core. Adobe Photoshop is an example of SMT-aware software. SMT is also used with multi-processor systems common to servers.

An attractive value of dual core processors is that they do not require a new motherboard, but can be used in existing boards that feature the correct socket. For the average user the difference in performance will be most noticeable in multi-tasking until more software is SMT aware. Servers running multiple dual core processors will see an appreciable increase in performance.

Face Recognition Technology

Definition
Humans are very good at recognizing faces and if computers complex patterns. Even a passage of time doesn’t affect this capability and therefore it would help become as robust as humans in face recognition. Machine recognition of human faces from still or video images has attracted a great deal of attention in the psychology, image processing, pattern recognition, neural science, computer security, and computer vision communities. Face recognition is probably one of the most non-intrusive and user-friendly biometric authentication methods currently available; a screensaver equipped with face recognition technology can automatically unlock the screen whenever the authorized user approaches the computer.

Face is an important part of who we are and how people identify us. It is arguably a person’s most unique physical characteristic. While humans have had the innate ability to recognize and distinguish different faces for millions of years, computers are just now catching up.
Visionics, a company based in New Jersey, is one of many developers of facial recognition technology. The twist to its particular software, FaceIt, is that it can pick someone’s face out of a crowd, extract that face from the rest of the scene and compare it to a database full of stored images. In order for this software to work, it has to know what a basic face looks like. Facial recognition software is designed to pinpoint a face and measure its features. Each face has certain distinguishable landmarks, which make up the different facial features. These landmarks are referred to as nodal points. There are about 80 nodal points on a human face. Here are a few of the nodal points that are measured by the software:

Distance between eyes
” Width of nose
” Depth of eye sockets
” Cheekbones
” Jaw line
” Chin

These nodal points are measured to create a numerical code, a string of numbers that represents the face in a database. This code is called a faceprint. Only 14 to 22 nodal points are needed for the FaceIt software to complete the recognition process.

Software

Facial recognition software falls into a larger group of technologies known as biometrics. Biometrics uses biological information to verify identity. The basic idea behind biometrics is that our bodies contain unique properties that can be used to distinguish us from others. Besides facial recognition, biometric authentication methods also include:

” Fingerprint scan
” Retina scan
” Voice identification

Facial recognition methods generally involve a series of steps that serve to capture, analyze and compare a face to a database of stored images. The basic processes used by the FaceIt system to capture and compare images are:
Detection – When the system is attached to a video surveillance system, the recognition software searches the field of view of a video camera for faces. If there is a face in the view, it is detected within a fraction of a second. A multi-scale algorithm is used to search for faces in low resolution. The system switches to a high-resolution search only after a head-like shape is detected.
2. Alignment – Once a face is detected, the system determines the head’s position, size and pose. A face needs to be turned at least 35 degrees toward the camera for the system to register it.
3. Normalization -The image of the head is scaled and rotated so that it can be registered and mapped into an appropriate size and pose. Normalization is performed regardless of the head’s location and distance from the camera. Light does not impact the normalization process.
4. Representation – The system translates the facial data into a unique code. This coding process allows for easier comparison of the newly acquired facial data to stored facial data.
5. Matching – The newly acquired facial data is compared to the stored data and (ideally) linked to at least one stored facial representation.