Nano tech can bring a big changes in biology, materials science, chemistry and daily life.
Futurist predictions mixed on nanotechnology .
http://www.nanowerk.com/news/newsid=1190.php
Nanotechnology, shortened to "nanotech", is the study of the controlling of matter on an atomic and molecular scale. Generally nanotechnology deals with structures of the size 100 nanometers or smaller in at least one dimension, and involves developing materials or devices within that size. Nanotechnology is very diverse, ranging from extensions of conventional device physics to completely new approaches based upon molecular self-assembly, from developing new materials with dimensions on the nanoscale to investigating whether we can directly control matter on the atomic scale.
There has been much debate on the future implications of nanotechnology. Nanotechnology has the potential to create many new materials and devices with a vast range of applications, such as in medicine, electronics and energy production. On the other hand, nanotechnology raises many of the same issues as with any introduction of new technology, including concerns about the toxicity and environmental impact of nanomaterials,[1] and their potential effects on global economics, as well as speculation about various doomsday scenarios. These concerns have led to a debate among advocacy groups and governments on whether special regulation of nanotechnology is warranted.
http://en.wikipedia.org/wiki/Nanotechnology
Sunday, October 25, 2009
Friday, October 23, 2009
Turing machine
Many computer scienc estudents know the Turing machine from computing theory course. You use Turing machine to prove your algorithm.
A Turing machine is a theoretical device that manipulates symbols contained on a strip of tape. Despite its simplicity, a Turing machine can be adapted to simulate the logic of any computer algorithm, and is particularly useful in explaining the functions of a CPU inside of a computer.
For definition of turing machine, see wiki:
http://en.wikipedia.org/wiki/Turing_machine
Turing machines, first described by Alan Turing in (Turing 1937), are simple abstract computational devices intended to help investigate the extent and limitations of what can be computed.
Turing, writing before the invention of the modern digital computer, was interested in the question of what it means to be computable. Intuitively a task is computable if one can specify a sequence of instructions which when followed will result in the completion of the task. Such a set of instructions is called an effective procedure, or algorithm, for the task. This intuition must be made precise by defining the capabilities of the device that is to carry out the instructions. Devices with different capabilities may be able to complete different instruction sets, and therefore may result in different classes of computable tasks (see the entry on computability and complexity).
Turing proposed a class of devices that came to be known as Turing machines. These devices lead to a formal notion of computation that we will call Turing-computability.
The proposition that Turing's notion captures exactly the intuitive idea of effective procedure is called the Church-Turing thesis. This proposition, being a claim about the relationship between a formal concept and intuition, is not provable, though it would be refuted by an intuitively acceptable algorithm for a task that is not Turing-computable. That no such counterexample has been found, together with the fact that Turing-computability is equivalent to independently defined notions of computability based on alternative foundations, such as recursive functions and abacus machines, indicates that there is at least something natural about this notion of computability.
Turing machines are not physical objects but mathematical ones. We require neither soldering irons nor silicon chips to build one. The architecture is simply described, and the actions that may be carried out by the machine are simple and unambiguously specified. Turing recognized that it is not necessary to talk about how the machine carries out its actions, but merely to take as given the twin ideas that the machine can carry out the specified actions, and that those actions may be uniquely described.
http://plato.stanford.edu/entries/turing-machine/
A Turing machine is a theoretical device that manipulates symbols contained on a strip of tape. Despite its simplicity, a Turing machine can be adapted to simulate the logic of any computer algorithm, and is particularly useful in explaining the functions of a CPU inside of a computer.
For definition of turing machine, see wiki:
http://en.wikipedia.org/wiki/Turing_machine
Turing machines, first described by Alan Turing in (Turing 1937), are simple abstract computational devices intended to help investigate the extent and limitations of what can be computed.
Turing, writing before the invention of the modern digital computer, was interested in the question of what it means to be computable. Intuitively a task is computable if one can specify a sequence of instructions which when followed will result in the completion of the task. Such a set of instructions is called an effective procedure, or algorithm, for the task. This intuition must be made precise by defining the capabilities of the device that is to carry out the instructions. Devices with different capabilities may be able to complete different instruction sets, and therefore may result in different classes of computable tasks (see the entry on computability and complexity).
Turing proposed a class of devices that came to be known as Turing machines. These devices lead to a formal notion of computation that we will call Turing-computability.
The proposition that Turing's notion captures exactly the intuitive idea of effective procedure is called the Church-Turing thesis. This proposition, being a claim about the relationship between a formal concept and intuition, is not provable, though it would be refuted by an intuitively acceptable algorithm for a task that is not Turing-computable. That no such counterexample has been found, together with the fact that Turing-computability is equivalent to independently defined notions of computability based on alternative foundations, such as recursive functions and abacus machines, indicates that there is at least something natural about this notion of computability.
Turing machines are not physical objects but mathematical ones. We require neither soldering irons nor silicon chips to build one. The architecture is simply described, and the actions that may be carried out by the machine are simple and unambiguously specified. Turing recognized that it is not necessary to talk about how the machine carries out its actions, but merely to take as given the twin ideas that the machine can carry out the specified actions, and that those actions may be uniquely described.
http://plato.stanford.edu/entries/turing-machine/
Future cars-electric cars
What is electric car ?
It is a vehicle with electric pwoer, electric control system and electric propulsion. Don't need any gasoline and no polution.
More info from wiki page:
http://en.wikipedia.org/wiki/Electric_car
It is a vehicle with electric pwoer, electric control system and electric propulsion. Don't need any gasoline and no polution.
More info from wiki page:
http://en.wikipedia.org/wiki/Electric_car
Online video edit
I just found this company acquired by Google does online edit video.
Don't need to buy expensive software like Adobe Premiere and Apple FInal cur pro. Use this one is enough to edit your personal veideo.
http://www.omnisio.com/
Don't need to buy expensive software like Adobe Premiere and Apple FInal cur pro. Use this one is enough to edit your personal veideo.
http://www.omnisio.com/
Cloud computing and data center
Distribute computing almost the same as cloud computing. Store data in the remote server. Access the data from any computer in the network. You don't need to bring your disk and storage media with you any time.
Cloud computing is the provision of dynamically scalable and often virtualized resources as a service over the Internet on a utility basis.[1][2] Users need not have knowledge of, expertise in, or control over the technology infrastructure in the "cloud" that supports them.[3] Cloud computing services often provide common business applications online that are accessed from a web browser, while the software and data are stored on the servers.
More info from wiki page: http://en.wikipedia.org/wiki/Cloud_computing
References:
1. "Cloud Computing: Clash of the clouds". The Economist. 2009-10-15. Retrieved
2009-11-03.
2. Distinguishing Cloud Computing from Utility Computing,
http://www.ebizq.net/blogs/saasweek/2008/03/distinguishing_cloud_computing/
3. Gartner Says Cloud Computing Will Be As Influential As E-business,
http://www.gartner.com/it/page.jsp?id=707508
Cloud computing is the provision of dynamically scalable and often virtualized resources as a service over the Internet on a utility basis.[1][2] Users need not have knowledge of, expertise in, or control over the technology infrastructure in the "cloud" that supports them.[3] Cloud computing services often provide common business applications online that are accessed from a web browser, while the software and data are stored on the servers.
More info from wiki page: http://en.wikipedia.org/wiki/Cloud_computing
References:
1. "Cloud Computing: Clash of the clouds". The Economist. 2009-10-15. Retrieved
2009-11-03.
2. Distinguishing Cloud Computing from Utility Computing,
http://www.ebizq.net/blogs/saasweek/2008/03/distinguishing_cloud_computing/
3. Gartner Says Cloud Computing Will Be As Influential As E-business,
http://www.gartner.com/it/page.jsp?id=707508
Thursday, October 8, 2009
Algorithms and Computer Science Maths
I have all the algorithms discussions here. A lot of people know these Algorithms in their class.
Algorithms:
1. Shortest Path : Dijkestra, Bellmanford.
2. Minum Spanning tree: Prim's
3. B+ Tree
4. R+ tree
5. Hashing
6. Their implementation
7. Complexity
Algorithms:
1. Shortest Path : Dijkestra, Bellmanford.
2. Minum Spanning tree: Prim's
3. B+ Tree
4. R+ tree
5. Hashing
6. Their implementation
7. Complexity
Subscribe to:
Posts (Atom)