1. A method of categorizing network traffic content comprising:
receiving, via a network interface device, network traffic content from a network in a network traffic content categorization module;
performing, through execution of instructions on a processor, analysis on the network traffic content within the network traffic content categorization module according to at least one analysis technique to obtain at least one categorization of the network traffic content and a probability of accuracy of each obtained network traffic categorization, the at least one analysis performed as a function of a database of known categorization properties of network traffic content;
storing, on a data storage device, by the network traffic content categorization module, a representation of the categorization, a representation of the probability of accuracy of each obtained network traffic categorization, and data derived from the network traffic content;
providing a view of the stored representation of the categorization including the probability of accuracy of each obtained network traffic categorization; and
receiving input verifying an accuracy of the stored representation of the categorization.
2. The method of claim 1, further comprising:
categorizing subsequently received network traffic content according to the at least one analysis technique as a function of the stored representation of the categorization.
3. The method of claim 1, wherein storing the representation of the categorization and data derived from the network traffic content includes storing the representation in the database of known categorization properties of network traffic content.
4. The method of claim 1, wherein the network traffic content comprises text-based chat messages.
5. The method of claim 4, wherein the text-based chat messages are instant messages.
6. The method of claim 1, wherein the network traffic content comprises content received over a network according to the Hypertext Transport Protocol and an email protocol.
7. The method of claim 1, wherein performing analysis on the network traffic content includes performing at least one of an internal link analysis, an external link analysis, a meta tag analysis, and a token analysis.
8. The method of claim 1, wherein the network traffic content categorization module receives a copy of the network traffic content to build a database of categorized network traffic content and a network traffic content screening module screens network traffic content destined for users according to the database of categorized network traffic content.
9. A method of screening network traffic content comprising:
receiving, via a network interface device, network traffic content from a network in a network traffic content screening module;
performing, through execution of instructions on a processor, analysis on the network traffic content within the network traffic content screening module according to at least one analysis technique to obtain at least one categorization of the network traffic content and a probability of accuracy of each obtained network traffic categorization, the at least one analysis performed as a function of a database of known categorization properties of network traffic content;
determining, through execution of instructions on a processor, based on the at least one categorization of the network traffic content, whether the network traffic content is undesirable content;
when the network traffic content is undesirable content, preventing the undesirable content from reaching its destination; and
otherwise allowing the network traffic content to pass;
storing, on a data storage device, by the network traffic content categorization module, a representation of the categorization, a representation of the probability of accuracy of each obtained network traffic categorization, and data derived from the network traffic content;
providing a view of the stored representation of the categorization including the probability of accuracy of each obtained network traffic categorization; and
receiving input verifying an accuracy of the stored representation of the categorization.
10. The method of claim 9, further comprising:
passing a copy of the network traffic content to a network traffic content categorization module to build a database of known network traffic content categorizations according to the at least one categorization.
11. The method of claim 9, wherein the network traffic content comprises text-based chat messages.
12. The method of claim 11, wherein the text-based chat messages are instant messages.
13. The method of claim 9, wherein the network traffic content comprises content received over a network according to the Hypertext Transport Protocol and an email protocol.
14. The method of claim 9, wherein performing analysis on the network traffic content includes performing at least one of an internal link analysis, an external link analysis, a meta tag analysis, and a token analysis.
15. A non-transitory machine-readable storage medium, with instructions thereon which when executed by a processor of a machine, causes the machine to screen network traffic content by:
receiving network traffic content in a network traffic content screening module;
performing analysis on the network traffic content within the network traffic content screening module according to at least one analysis technique to obtain at least one categorization of the network traffic content and a probability of accuracy of each obtained network traffic categorization, the at least one analysis performed as a function of a database of known categorization properties of network traffic content;
determining, based on the at least one categorization of the network traffic content, whether the network traffic content is undesirable content;
when the network traffic content is undesirable content, preventing the undesirable content from reaching its destination; and
otherwise allowing the network traffic content to pass;
storing, on a data storage device, by the network traffic content categorization module, a representation of the categorization, a representation of the probability of accuracy of each obtained network traffic categorization, and data derived from the network traffic content;
providing a view of the stored representation of the categorization including the probability of accuracy of each obtained network traffic categorization; and
receiving input verifying an accuracy of the stored representation of the categorization.
16. The non-transitory machine-readable storage medium of claim 15, wherein the instructions when further executed, cause the machine to:
pass a copy of the network traffic content to a network traffic content categorization module to build a database of known network traffic content categorizations according to the at least one categorization.
17. The non-transitory machine-readable storage medium of claim 15, wherein the network traffic content comprises text-based chat messages.
18. The non-transitory machine-readable storage medium of claim 15, wherein the network traffic content comprises content received over a network according to the Hypertext Transport Protocol and an email protocol.
19. The non-transitory machine-readable storage medium of claim 15, wherein performing analysis on the network traffic content includes performing at least one of an internal link analysis, an external link analysis, a meta tag analysis, and a token analysis.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A method for removably installing a flowing water turbine system, said method comprising the steps of:
floating said water turbine system to a desired operating location;
coupling a buoy to said water turbine system;
transmitting a signal from said buoy to said water turbine system;
filling a tank in response to said signal; and
submerging said water turbine system to a desired depth.
2. The method of removably installing a flowing water turbine system of claim 1, said method further comprising the steps of:
placing a mooring in a desired location; and
coupling a first cable to said mooring.
3. The method of removably installing a flowing water turbine system of claim 2, said method further comprising the steps of:
removably coupling said first cable to said water turbine system; and
coupling a second cable between said buoy and said first cable.
4. The method of removably installing a flowing water turbine system of claim 3 wherein said second cable is operably coupled to said water turbine system.
5. The method of removably installing a flowing water turbine system of claim 4 wherein said signal is transmitted through said second cable.
6. A method of operating a flowing water turbine system, said method comprising the steps of:
determining the water depth having a desired water current speed;
transmitting a first signal from a flotation device in response to said current speed determination;
adjusting the buoyancy of a water turbine system in response to said first signal;
changing the depth of operation of said water turbine system in response to said buoyancy adjustment; and
transmitting electrical power from said water turbine system.
7. The method of operating a flowing water turbine system of claim 6, said method further comprising the steps of:
determining a first condition that requires servicing of said water turbine system;
transmitting a second signal from said flotation device to said water turbine system; and
removing water from a tank in said water turbine system in response to said second signal.