1. A computer-implemented method comprising:
simulating user behavior pertaining to a specified future time period,
wherein the simulating is based on an observed user behavior, and
wherein the simulating produces first simulated data;
selecting an item of a plurality of items during the specified future time period based on the first simulated data; and
presenting the item to a user.
2. The computer-implemented method of claim 1, wherein the observed user behavior comprises a number of times the plurality of items have been viewed by a plurality of users and the number of times each item of the plurality of items has been clicked.
3. The computer-implemented method of claim 1, wherein the step of simulating user behavior further comprises:
calculating a probability that a particular item of the plurality of items will maximize a performance metric;
selecting the particular item based on the probability;
recording, in connection with the particular item at the first simulated data, a hypothetical view; and
recording, in connection with the particular item at second simulated data, a value based on a probability that a user of the plurality of users would click on the particular item.
4. The computer-implemented method of claim 3, wherein the probability is based on the observed user behavior and the first and second simulated data.
5. The computer-implemented method of claim 2, wherein the value based on a probability that a user of the plurality of users would click on the particular item comprises:
a division of a total number of clicks observed for the particular item by a total number of times the particular item has been selected;
wherein the total number of times the particular item has been selected is based on the first simulated data and the observed user behavior.
6. The computer-implemented method of claim 1, wherein the first simulated data comprises percentages of times each item of the plurality of items was selected in the step of simulating user behavior.
7. The computer-implemented method of claim 6, wherein the percentages comprise the probability that each item of the plurality of items will be presented to the user during the specified future time period.
8. A computer-implemented method comprising:
generating a plan for presenting an item from a plurality of items to a user;
wherein the plan is based on a simulation of user behavior pertaining to a specified future time period;
wherein the simulation comprises a function measuring a potential that presenting the item will maximize a performance metric; and
presenting, to the user, the item selected from the plurality of items according to the plan.
9. The computer-implemented method of claim 8, wherein the performance metric comprises a click-through rate, a total number of page views over time, or a measure of overall user experience.
10. The computer-implemented method of claim 8,
wherein the function measuring a potential that presenting the item will maximize a performance metric further comprises calculating a priority corresponding to the item; and
wherein the priority comprises a measure of a current estimated click rate pertaining to the item and a measure of the probability that the current estimated click rate will improve.
11. The computer-implemented method of claim 8, further comprising the steps of:
presenting, to the user, the item selected according to the plan after the simulation of user behavior pertaining to a specified future time period.
12. The computer-implemented method of claim 8, further comprising the steps of:
presenting, to the user, the item selected according to the plan during the simulation of user behavior pertaining to a specified future time period.
13. The computer-implemented method of claim 8, wherein the simulation of user behavior pertains to users of a portal page on the internet.
14. The computer-implemented method of claim 8, wherein the simulation of user behavior is based on a solution to the Bayesian multi-armed bandit problem.
15. A machine-readable volatile or non-volatile medium carrying one or more sequences of instructions, wherein execution of the one or more sequences of instructions by one or more processors causes the one or more processors to perform the steps of:
simulating user behavior pertaining to a specified future time period,
wherein the simulating is based on an observed user behavior, and
wherein the simulating produces first simulated data;
selecting an item of a plurality of items during the specified future time period based on the first simulated data; and
presenting the item to a user.
16. The machine-readable volatile or non-volatile medium of claim 15, wherein the observed user behavior comprises a number of times the plurality of items have been viewed by a plurality of users and the number of times each item of the plurality of items has been clicked.
17. The machine-readable volatile or non-volatile medium of claim 15, wherein the step of simulating user behavior further comprises:
calculating a probability that a particular item of the plurality of items will maximize a performance metric;
selecting the particular item based on the probability;
recording, in connection with the particular item at the first simulated data, a hypothetical view; and
recording, in connection with the particular item at second simulated data, a value based on a probability that a user of the plurality of users would click on the particular item.
18. The machine-readable volatile or non-volatile medium of claim 17, wherein the probability is based on the observed user behavior and the first and second simulated data.
19. The machine-readable volatile or non-volatile medium of claim 16, wherein the value based on a probability that a user of the plurality of users would click on the particular item comprises:
a division of a total number of clicks observed for the particular item by a total number of times the particular item has been selected;
wherein the total number of times the particular item has been selected is based on the first simulated data and the observed user behavior.
20. The machine-readable volatile or non-volatile medium of claim 15, wherein the first simulated data comprises percentages of times each item of the plurality of items was selected in the step of simulating user behavior.
21. The machine-readable volatile or non-volatile medium of claim 20, wherein the percentages comprise the probability that each item of the plurality of items will be presented to the user during the specified future time period.
22. A machine-readable volatile or non-volatile medium carrying one or more sequences of instructions, wherein execution of the one or more sequences of instructions by one or more processors causes the one or more processors to perform the steps of:
generating a plan for presenting an item from a plurality of items to a user;
wherein the plan is based on a simulation of user behavior pertaining to a specified future time period;
wherein the simulation comprises a function measuring a potential that presenting the item will maximize a performance metric; and
presenting, to the user, the item selected from the plurality of items according to the plan.
23. The machine-readable volatile or non-volatile medium of claim 22, wherein the performance metric comprises a click-through rate, a total number of page views over time, or a measure of overall user experience.
24. The machine-readable volatile or non-volatile medium of claim 22,
wherein the function measuring a potential that presenting the item will maximize a performance metric further comprises calculating a priority corresponding to the item; and
wherein the priority comprises a measure of a current estimated click rate pertaining to the item and a measure of the probability that the current estimated click rate will improve.
25. The machine-readable volatile or non-volatile medium of claim 22, further comprising the steps of:
presenting, to the user, the item selected according to the plan after the simulation of user behavior pertaining to a specified future time period.
26. The machine-readable volatile or non-volatile medium of claim 22, further comprising the steps of:
presenting, to the user, the item selected according to the plan during the simulation of user behavior pertaining to a specified future time period.
27. The machine-readable volatile or non-volatile medium of claim 22, wherein the simulation of user behavior pertains to users of a portal page on the internet.
28. The machine-readable volatile or non-volatile medium of claim 22, wherein the simulation of user behavior is based on a solution to the Bayesian multi-armed bandit problem.
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 composite gas separation module, comprising:
a) a porous metal substrate;
b) a porous anodic aluminum oxide layer, wherein the porous anodic aluminum oxide layer overlies the porous metal substrate; and
c) a dense gas-selective membrane, wherein the dense gas-selective membrane overlies the porous anodic aluminum oxide layer.
2. The composite gas separation module of claim 1 wherein the porous metal substrate is stainless steel.
3. The composite gas separation module of claim 1 wherein the porous metal substrate is an alloy containing chromium and nickel.
4. The composite gas separation module of claim 3 wherein the alloy further contains molybdenum.
5-17. (canceled)
18. The composite gas separation module of claim 1 wherein the dense gas-selective membrane is a dense hydrogen-selective membrane.
19. The composite gas separation module of claim 18 wherein the dense hydrogen-selective membrane includes palladium or an alloy thereof.
20. A composite filter, comprising:
a) a porous non-aluminum metal substrate; and
b) a porous anodic aluminum oxide layer, wherein the porous anodic aluminum oxide layer overlies the porous non-aluminum metal substrate, and wherein the porous anodic aluminum oxide layer defines pores extending from a first side of the porous anodic aluminum oxide layer through the porous anodic aluminum oxide layer to a second side of the porous anodic aluminum oxide layer.
21. The composite filter of claim 20 wherein the porous non-aluminum metal substrate is stainless steel.
22. The composite filter of claim 20 wherein the porous non-aluminum metal substrate is an alloy containing chromium and nickel.
23. The composite filter of claim 20 wherein the alloy further contains molybdenum.
24-27. (canceled)
28. The composite filter of claim 20 wherein the porous non-aluminum metal substrate defines pores having an first mean pore diameter, wherein the porous anodic aluminum oxide layer defines pores having a second mean pore diameter, and wherein the first mean pore diameter is less than the first mean pore diameter.
29. The composite filter of claim 28 wherein the first mean pore diameter is less than half of the first mean pore diameter.
30-31. (canceled)
32. A method for fabricating a composite gas separation module, comprising:
a) applying a porous anodic aluminum oxide layer over a porous metal substrate; and
b) applying a dense gas-selective membrane over the porous anodic aluminum oxide layer, thereby forming the composite gas separation module.
33. The method of claim 32 wherein applying a porous anodic aluminum oxide layer over a porous metal substrate includes applying an aluminum metal layer over the porous metal substrate.
34. The method of claim 33 wherein the porous metal substrate is a porous non-aluminum metal substrate.
35-49. (canceled)
50. The method of claim 32 wherein applying a porous anodic aluminum oxide layer over a porous metal substrate includes:
a) applying an aluminum metal layer over the porous metal substrate;
b) oxidizing the aluminum metal layer by anodic oxidation, thereby forming a first anodic aluminum oxide layer;
c) removing at least a portion of the first anodic aluminum oxide layer, thereby forming a template, wherein the template includes unoxidized aluminum metal; and
d) oxidizing the aluminum metal of the template by anodic oxidation, thereby forming the porous anodic aluminum oxide layer.
51. (canceled)
52. The method of claim 32 wherein the gas-selective membrane is a hydrogen-selective membrane.
53-57. (canceled)
58. A method for fabricating a composite filter, comprising:
a) applying an aluminum metal layer over a porous non-aluminum metal substrate;
b) oxidizing the aluminum metal layer by anodic oxidation, thereby forming a first anodic aluminum oxide layer;
c) removing at least a portion of the first anodic aluminum oxide layer, thereby forming a template, wherein the template includes unoxidized aluminum metal; and
d) oxidizing the aluminum metal of the template by anodic. oxidation, thereby forming a porous anodic aluminum oxide layer.
59. The method of claim 58 wherein the porous anodic aluminum oxide layer includes non-porous anodic aluminum oxide and further comprising removing at least a portion of the non-porous anodic aluminum oxide from the porous anodic aluminum oxide layer.
60. A method for selectively separating hydrogen gas from a hydrogen gas-containing gaseous stream, comprising:
directing the hydrogen gas-containing gaseous stream to a composite gas separation module, wherein the composite gas separation module includes:
a) a porous metal substrate;
b) a porous anodic aluminum oxide layer, wherein the porous anodic aluminum oxide layer overlies the porous metal substrate; and
c) a dense hydrogen-selective membrane, wherein the dense hydrogen-selective membrane overlies the porous anodic aluminum oxide layer;
whereby hydrogen gas is at least partially partitioned from the gaseous stream by passing through the dense hydrogen-selective membrane.
61. The method of claim 60 further comprising the step of reacting hydrogen gas-producing reactants to produce the gaseous stream.
62. The method of claim 60 wherein the porous metal substrate defines pores having an first mean pore diameter, wherein the porous anodic aluminum oxide layer defines pores having a second mean pore diameter, and wherein the second mean pore diameter is less than the first mean pore diameter.
63-67. (canceled)
68. The method of claim 62 wherein the dense hydrogen-selective membrane includes palladium or an alloy thereof.
69. The method of claim 33 further including annealing the aluminum metal layer in an atmosphere comprising an inert gas and hydrogen gas.
70-71. (canceled)