Thursday, July 9, 2009

Test Completed.

OK. This test Blog completes here.
The tasks remaining in remaving it to the finakl stage are:
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Wednesday, July 8, 2009

Headless Horseman!

The headless horseman has appeared in many forms of literature throughout history and throughout the world. Many countries have their own unique version of the legend in which some form of the headless horseman appears. In the United States, various states have their own version of a headless horseman tale; Texas' version of the legend, written by Thomas Mayne Reid in 1865 or 1866, tells of ghosts of beheaded horse thieves, who roam the countryside.

The more noted and recognizable headless horseman of today imitates the one that appears in Washington Irving's short story, which was published in 1820. The story is set in America, within a 1790's Dutch settlement that residents nicknamed “Sleepy Hollow”. Its protagonist is a schoolteacher named Ichabod Crane, whose apparent demise results from a meeting with the horseman. The horseman himself is allegedly a Hessian soldier from the Revolutionary War who was decapitated by a cannonball and now roams Sleepy Hollow on the back of his horse, with his severed head resting upon the pommel of his saddle. He is therefore also called the 'Galloping Hessian'. The Horseman is said to be incapable of crossing the covered bridge at the town entrance (a possible reference to the belief that ghosts cannot cross water), although he is shown throwing his head across a river to strike down Ichabod Crane. Ichabod's fate is left ambiguous; some of the background characters allege that he has been "carried off" by the Horseman, while others suggest that he has been frightened out of the county by the ghost and by the prospect of facing his landlord, later to become a lawyer in Philadelphia. It is implied later that the Horseman was in fact Brom Bones, Ichabod's rival for the hand in marriage of the local beauty Katrina van Tassel, who imitated the legend of the Galloping Hessian on purpose to kill or frighten away his competitor. The fact that a shattered pumpkin is found beside Ichabod's abandoned hat supports this, in that the pumpkin may easily have been used to simulate the Horseman's severed head. Intriguingly, there is no mention of a severed head in the story heard by Ichabod, though it is prominent in his own encounter with the horseman.


The legend of the Headless Horseman begins in Sleepy Hollow, New York. The Horseman was a Hessian of unknown rank; one of many such hired to suppress the American Revolutionary War. During the war, the Horseman was one of 548 Hessians killed in a battle for Chatterton Hill, wherein his head was severed by a cannonball. He was buried in a graveyard outside a church. Thereafter he appears as a ghost, who presents to nightly travelers an actual danger (rather than the largely harmless fright produced by the majority of ghosts), presumably of decapitation
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  • A version referred to as a "darklord" appears in the Ravenloft campaign setting for the Dungeons & Dragons roleplaying game; it overlays itself on random stretches of barren road and hunts for lone travelers with the assistance of several of the heads of previous victims.
  • In A Hollow Sleep by Chris Ebert, the Horseman is given an identity of "Heinrich Luneberg" and his origins are explored. The story is told from his perspective.
  • In the Beetleborgs Metallix episode "Headless Over Heels," the Headless Horseman accuses Wolfgang of stealing his head. When he arrives in Charterville looking for his head, he attempts to find it or take one of the other monsters' heads in exchange. It is revealed that Little Ghoul had his head, and was using it as a bowling ball. Upon its return, bolts were attached to the head to keep it from falling off again.
  • Dark Shadows (1966)

Neural network

There is no precise agreed-upon definition among researchers as to what a neural network is, but most would agree that it involves a network of simple processing elements (neurons), which can exhibit complex global behavior, determined by the connections between the processing elements and element parameters. The original inspiration for the technique was from examination of the central nervous system and the neurons (and their axons, dendrites and synapses) which constitute one of its most significant information processing elements (see Neuroscience). In a neural network model, simple nodes (called variously "neurons", "neurodes", "PEs" ("processing elements") or "units") are connected together to form a network of nodes — hence the term "neural network." While a neural network does not have to be adaptive per se, its practical use comes with algorithms designed to alter the strength (weights) of the connections in the network to produce a desired signal flow.

These networks are also similar to the biological neural networks in the sense that functions are performed collectively and in parallel by the units, rather than there being a clear delineation of subtasks to which various units are assigned (see also connectionism). Currently, the term Artificial Neural Network (ANN) tends to refer mostly to neural network models employed in statistics, cognitive psychology and artificial intelligence. Neural network models designed with emulation of the central nervous system (CNS) in mind are a subject of theoretical neuroscience (computational neuroscience).

In modern software implementations of artificial neural networks the approach inspired by biology has more or less been abandoned for a more practical approach based on statistics and signal processing. In some of these systems neural networks, or parts of neural networks (such as artificial neurons) are used as components in larger systems that combine both adaptive and non-adaptive elements. While the more general approach of such adaptive systems is more suitable for real-world problem solving, it has far less to do with the traditional artificial intelligence connectionist models. What they do, however, have in common is the principle of non-linear, distributed, parallel and local processing and adaptation.


Neural network models in artificial intelligence are usually referred to as artificial neural networks (ANNs); these are essentially simple mathematical models defining a function  f : X \rightarrow Y . Each type of ANN model corresponds to a class of such functions.

The network in artificial neural network

The word network in the term 'artificial neural network' arises because the function f(x) is defined as a composition of other functions gi(x), which can further be defined as a composition of other functions. This can be conveniently represented as a network structure, with arrows depicting the dependencies between variables. A widely used type of composition is the nonlinear weighted sum, where f (x) = K \left(\sum_i w_i g_i(x)\right) , where K is some predefined function, such as the hyperbolic tangent. It will be convenient for the following to refer to a collection of functions gi as simply a vector g = (g_1, g_2, \ldots, g_n).

Saturday, July 4, 2009

Kash Lagaa: No Smoking (2007)

Kash Lagaa: No Smoking
Genre: Sufi

Zindagi Hai Kash Laga 2
Hasrato Ki Raakh Uda
Yeh Jahan Pani Hai
Bulbula Hai Pani Hai
Bulbulon Pe Rukna Kya
Paniyon Mein Bheta Ja Bheta Ja

Kash Laga
Kash Laga
Kash Laga
Kash Laga

Jalti Hai Tanhaiyan
Kati Hai Raat Raat Jag Jag Ke
Udti Hai Chingariyan
Gucche Hai Lal Lal Gili Aag Ke
Oh Khilti Hai Jaise Jalte
Jugnu Ho Beliyon Mein
Aakhein Lagi Ho Jaise

Do Din Ka Aag Hai Yeh
Sara Jahan Dhua

Do Din Ki Zindagi Mein
Dono Jahan Ka Dhua

Yeh Jahan Pani Hai
Bulbula Hai Pani Hai
Bulbulon Pe Rukna Kya
Paniyon Mein Bheta Ja Bheta Ja

Kash Laga
Kash Laga
Kash Laga
Kash Laga

Chohti Hui Bastiyan
Jata Hoon Bar Bar Ghom Ghoom Ke
Milte Nahi Woh Nishaan
Chode The Dahliz Chom Chom Ke

Jo Aaye Chad Jayenge
Jungle Ki Kyariya Hain
Pagdandiyon Per Milna Do Din Ki Yaariyan Hai
Kya Jane Kaun Jaye Pari Se Pari Aye
Hum Bhi Katar Mein Hai
Jab Bhi Sawari Aaye

Yeh Jahan Pani Hai
Bulbula Hai Pani Hai
Bulbulon Pe Rukna Kya
Paniyon Mein Bheta Ja Bheta Ja

Kash Laga
Kash Laga
Kash Laga
Kash Laga