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The Human Brain And Pattern Recognition Biology Essay

Artificial Intelligence is a branch of computer science that seeks to create a computer system capable of sensing the world around it, understanding conversations, learning, reasoning, and reaching decisions, just as would a human.

The ability to create intelligent machines has intrigued humans since ancient times, and today with the advent of the computer and 50 years of research into AI programming techniques, the dream of smart machines is becoming a reality. Researchers are creating systems which can mimic human thought, understand speech, beat the best human chess player, and countless other feats never before possible. Find out how the military is applying AI logic to its hi-tech systems, and how in the near future Artificial Intelligence may impact our lives.

HUMAN BRAIN:

The brain is a remarkable structure that defines who we are as individual and how we experience the world. Recent advances in neuron imaging have allowed researchers to look inside the brain, providing vivid pictures of its subcomponents and their associated functions. The gross structure of the brain is familiar to most. The outer layer of the forebrain constitutes the familiar wrinkled tissue that is the cerebral cortex, or just cortex. The large folds in the cortex called gyri

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http://www.thebigview.com/mind/brain.html

The human brain is the size of a large grapefruit and weighs 1 – 1.5 kg. The outer visible layer, the cortex, is part of the cerebrum. It comprises two halves, or hemispheres, of highly wrinkled grey matter. The grey matter consists of the cell bodies of neurons, whereas the subjacent white matter consists of nerve fibres (axons) that constitute long distance connections between neurons. The two hemispheres are separated by a deep grove, the longitudinal cerebral fissure. They are connected at the base by the corpus callosum, a thick layer of nerve fibres. At the outer sides of the hemispheres there is another deep grove, the lateral fissure or lateral sulcus, which divides the frontal and parietal lobes from the temporal lobes. Developmentally, the brain can be divided into three main divisions, the hindbrain, midbrain, and forebrain.

HINDBRAIN:

The area of the brain comprising thepons, medulla and cerebellum. The hindbrain functions collectively to co-ordinate motor activity, posture, equilibrium and sleep patterns and regulate unconscious but essential functions, such as breathing and blood circulation.

MIDBRAIN:

The midbrain is the least differentiated and the smallest segment of the brainstem and can be divided into three portions: a medial segment, which includes DA manufacturing neurons and which represents the anterior continuation of the reticular formation (described below); the most recently evolved ventral segment through which pass descending cortical fibbers; and the tectum which is dorsally located and includes the superior (visual) and inferior (auditory) colliculi. Located between and below the ventral segment and the DA producing tegmentum is the substantia nigra which manufactures Dopamine. However, the most obvious structure of the midbrain is the pinkish colored "red nucleus", which receives descending motor fibers from the frontal lobe and gives rise to the rubrospinal tract which facilitates flexor muscle tone.

http://www.mhhe.com/socscience/intro/ibank/ibank/0012lll.jpg

When you look at an object, electrical signals travel via the optic nerves to an area in your brain called the thalamus. This then sends the information to the visual cortex, where it is examined in detail. Different parts of the visual cortex simultaneously process the colour, shape, movement and depth of the object. Other parts of the cortex put this information together to give you a complete picture of the object.

FOREBRAIN:

The forebrain, also known as the prosencephalon, is the largest section of the brain. It is separated into two hemispheres, called the lower diencephalon and the upper telencephalon, that are each split into four lobes: parietal, temporal, occipital and frontal. Most sensory and associative processing occurs in the forebrain, including voluntary and involuntary motor control, emotion, cognition and language.

HOW DOES BRAIN WORK?

Your brain is the hub of your nervous system. It is made up of 100 billion nerve cells - about the same as the number of trees in the Amazon rainforest. Each cell is connected to around 10,000 others. So the total number of connections in your brain is the same as the number of leaves in the rainforest about 1000 trillion.

NEURONS:

A neuron is a cell specialized to conduct electrochemical impulses called nerve impulses or action potentials.

Link to a page describing these.

All neurons outside the central nervous system (and many within it) conduct impulses along hairlike cytoplasmic extensions, the nerve fibbers or axons. (The diagram represents a motor neuron with most of its axon omitted.) The axons connecting your spinal cord to your foot can be as much as 1 m long (although only a few micrometers in diameter).

Axons grow out of the cell body, which houses the nucleus as well as other organelles such as the endoplasmic reticulum. The length of some axons is so great that it is remarkable that the cell body controls them all the way to their tip. There is a steady transport of cell components (e.g., vesicles, mitochondria) from the cell body along the entire length of the axon. This flow is driven by kinesins moving along the many microtubules in the cytoplasm within the axon. Even so, it may take 2 weeks or longer for material synthesized in the cell body to reach the axon terminals in your big toe.

In many neurons, nerve impulses are generated in short branched fibbers called dendrites and also in the cell body. The impulses are then conducted along the axon, which usually branches several times close to its end.

Many axons are covered with a glistening fatty sheath, the myelin sheath. It is the greatly-expanded plasma membrane of an accessory cell, the Schwann cell. Schwann cells are spaced at regular intervals along the axon. Their plasma membrane is wrapped around and around the axon forming the myelin sheath.

Where the sheath of one Schwann cell meets that of the next, the axon is unprotected. This region, the node of Ranvier, plays an important part in the propagation of the nerve impulse.

Type of Neurons

There are three major classes of neurons.

Sensory neurons

These run from the various types of stimulus receptors, e.g.,

touch

odor

taste

sound

vision

To the central nervous system (CNS), the brain and spinal cord.

The cell bodies of the sensory neurons leading to the spinal cord are located in clusters, the dorsal root ganglia (DRG), next to the spinal cord. Their axon extends in both directions: a peripheral axon to receptors at the periphery and a central axon passing into the spinal cord. The latter axon usually terminates at an interneuron.

PATTERN RECOGNITION:

Pattern recognition is a process that taking in raw data and making an action based on the category of the pattern. When a program makes observations of some kind, it is often programmed to compare what it sees with a pattern. For example, a vision program may try to match a pattern of eyes and a nose in a scene in order to find a face. More complex patterns, e.g. in a natural language text, in a chess position, or in the history of some event are also studied. These more complex patterns require quite different methods than do the simple patterns that have been studied the most.

Computer vision is the ability to recognize patterns in an image and to separate objects from background as quickly as the human brain. In the 1990s military technology initially developed to analyze spy-satellite images found its way into commercial applications, including monitors for assembly lines, digital cameras, and automotive imaging systems. Another pursuit in artificial intelligence research is natural language processing, the ability to interpret and generate human languages. In this area, as in others related to artificial intelligence research, commercial applications have been delayed as improvements in hardware, the computing power of the machines themselves have not kept pace with the increasing complexity of software.

EXAMPLE:

Imagine you went to a friend’s house today and you’re in your friend’s kitchen. You see a chair and sit down on that chair.

How do you know it’s safe to sit on that chair?

But even more interestingly, how do you know it’s a chair in the first instance?

Your brain worked out the pattern, didn’t it?

It figured out, that if the chair looked like a chair, then it must be a chair.

The chair you picked may be orange, and you’ve never sat in an orange chair before, but hey the brain still sees it as a chair.

And even if the chair didn’t have four legs. Even if it had just one central beam, your brain still sees the chair as a chair.

This is the simplicity of patterning

You see the chair. You sit on it.

A five-month old baby sees it.

And slams into it. Bumps into it. Stares at it.

And isn’t sure what to do with it.

The patterns are clear in your brain. The patterns aren’t that clear in the brain of that baby.

Applications

These are pattern recognition systems with various applications. Some of the most important and currently in use are:

Weather report: To classify all the meteorological data according to different patterns, with the knowledge we have different situations that can allows us to create predictive maps automatically.

Recognition of handwritten characters or machine is one of the most popular utilities pattern recognition systems since the writing symbols are readily identifiable.

Voice recognition: An analysis of the voice signal is now used in many applications; a clear example is the computer telemarketers.

Applications in medicine: Analysis of biorhythms, detection of irregularities in x-ray images, detection of infected cells, skin tags.

Fingerprint Recognition: used and known by most, through fingerprints are all identifiable and programs that detect and classify the matches, it’s easy matching.

Face Recognition: used to tell attendees at an event or simply to detect a smile and there are different cameras on the market with this option available.

Interpretation of aerial photographs and satellite: very useful for military or civilian proposals, such as agriculture, geology, geography, urban planning.

Voice Recognition:

Speech recognition is the aptitude of a computer, converting the words of the human you to a binary code understandable by the computer. Most people have the idea that speech recognition is based on a computer that has a sort of electronic ear, this actually serves more as a translator, which converts our language, in a machine understandable. Such features enhance user experiences.

The voice recognition works on many levels. As an outgrowth of the concept, voice recognition, is the team's attempt to identify the person talking to you, based on the unique tone of his voice. Therefore, we can say that speech recognition is one of the new technologies that allow us to input commands and data to the computer, as well as other input interfaces such as keyboard, mouse or touch screen, etc.

This interface opens many doors for computer applications, which are used on a daily basis. It gives us a new way to interact with our team, while reducing the time required for data entry. For example, if your cell phone has voice recognition software, you can make calls without dialling, only saying the name of the person you wish to call. This feature is even more productive, than speed dial, and that the version that is in the market for voice dialing is pretty limited. However, voice recognition has made great strides in the military industry and health, which has given way to automation of many processes.

Speech recognition has come a long way since a technology is used only in complex industrial machines, to become a tool, found in many elements of everyday life. Advances in speech recognition are related to the development of faster computers, which demonstrates that the emergence of advanced voice recognition, the sun is only a matter of time. The advancement of speech recognition in engineering laboratories for specialized applications came in the 1970’s; this system was a continuous survey, which means that humans do not need to pause between words. As it developed, this technology has been gaining ground in the mass market.

The first industry that used voice recognition software as a commercial application was the healthcare industry. Initially, doctors thought that this technology could replace the traditional medical transcription. This idea was not very successful, because doctors are so eager, preferring not to be bothered with the use of these programs also do not trust a computer, critical transcripts, which are cooked to perfection by humans.

However, advances in computer technology, made possible the use of speech recognition, in items like phones, cars and personal computers. The voice recognition adds a level of simplicity for all users who put so much responsibility in this system as the health industry. After all, no life is at stake, if the voice recognition system to your cell phone, dials a wrong number. With the aggressive campaigns of companies like Microsoft and its Vista operating system, and other mobile operating systems, the voice recognition technology is being slowly absorbed by the modern lifestyle.

CONCLUSION:

Voice recognition still has many drawbacks and limitations. These flaws are based on artificial intelligence deficiencies. This technology acts as a translator of certain commands, as computers cannot filter the context or purpose of the orders. At the same time, language processing is easier said than done. The reality is that computers, it is difficult to process multiple sentences and recognize commands easily. Most speech recognition software must be configured to work correctly, this should suit your voice, so you can recognize the orders and commands you dictated. However, it is expected that in future the voice recognition software, an integral part of computers, not only industries but also within our homes. Voice dialling is just a hint of what the voice recognition can do on mobile devices. Because laptops fall into the category of mobile devices, and as such, are becoming smaller, it can predict the spread of voice recognition technology for these devices to improve productivity and our way of life. Need weather update? You can talk to your cell phone, and this will be willing to give this information.

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