Author: claimsbot

1. A method for communicating in a wireless network including a plurality of nodes, comprising:
partitioning each periodic announcement cycle of a communication schedule into a set of time slots, including a set of management time slots, a set of beacon time slots, and a set of superframe time slots;
broadcasting management frames during the management slot, wherein the management frames specify beacons;
broadcasting the beacons during the beacon-slots, wherein the beacons specify superframe; and
transmitting the superframes during the superframe time slots.
2. The method of claim 1, wherein the network includes a plurality of star networks, and wherein each star network includes a central parent node and a plurality of leaf nodes, and wherein the central nodes are a wired backbone.
3. The method of claim 2, wherein a particular leaf node simultaneously has multiple central parent nodes.
4. The method of claim 1, wherein the leaf nodes include sensors, and the central nodes aggregate data acquired by the sensors.
5. The method of claim 1, wherein the transmitting uses frequency channel hopping.
6. The method of claim 1, wherein the network includes mobile nodes.
7. The method of claim 1, wherein the broadcasting and transmitting uses an announcement channel.
8. The method of claim 1, wherein the transmitting uses a channel that is different than the announcement channel.
9. The method of claim 1, wherein a time length of the announcement cycle can vary in different parts of the network.
10. The method of claim 1, wherein the time slots are selected and reserved using a distributed process.
11. The method of claim 1, wherein a time length of the announcement cycle varies dynamically.
12. The method of claim 1, wherein the nodes start transmitting the superframes simultaneously after a last beacon time slot in the announcement cycle, and the nodes use different channels or a channel hopping sequence.
13. The method of claim 1, wherein the superframes have different sizes.
14. The method of claim 1, wherein the beacon includes a field for specifying a size of superframe time slots.
15. The method of claim 1, wherein the beacon includes a field for specifying a channel index for the superframes.
16. The method of claim 1, wherein the beacon includes a field for beacon payload data.
17. The method of claim 1, wherein the management frames include a Beacon-Slot Request, which is used by a particular node to announce an intention to reserve and use a particular beacon time slot.
18. The method of claim 17, wherein the management frames include a Beacon-Slot Response frame, which is used to indicate that the intention to use and reserve will cause a problem for the network.
19. The method of claim 1, wherein the superframe time slot includes guaranteed time slots (GTS) for transmitting GTS frames, and wherein in the GTS frames include additional data frames.
20. The method of claim 1, wherein the superframe includes an indication whether the superframe is to be acknowledges immediately after being received.
21. The method of claim 1, wherein the network has a mesh topology for communicating with the nodes via multiple hops.
22. The method of claim 1, wherein resource of the network are allocated in a distributed manner.
23. The method of claim 22, wherein the resources include time and frequencies.

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 generating an object-oriented model from a vocabulary, the method comprising the operations of:
(a) receiving the vocabulary comprising terms and sentential forms, each of the terms comprising a word or phrase representing a concept, each of the sentential forms comprising a prepositional statement representing a fact type and including at least one placeholder, the placeholder being specified by a term;
(b) automatically creating a first class for each of the terms in the vocabulary;
(c) making a classification superclass to be a superclass for each of the first classes, wherein the classification superclass is a subclass of a fact superclass, wherein the fact superclass is a superclass whose instances are facts, such that each instance of the first class represents a fact that a thing is classified to be an instance of the concept represented by the corresponding term rather than representing an instance of the concept, and wherein the classification superclass is a superclass whose instances are classifications;
(d) automatically creating a second class for each sentential form in the vocabulary;
(e) making the fact superclass to be a superclass for each of the second classes, wherein the fact superclass is a superclass whose instances are facts, such that each instance of the second class represents a fact that is an instance of the fact type represented by the corresponding sentential form; and
wherein acts (a)-(e) are performed so as to limit the granularity of encapsulation of information in each of the first classes and the second classes to no larger than the representation of a single fact.
2. The method of claim 1 further comprising:
(f) creating a package; and,
(g) making each of the classes created in operations (b) and (d) to be a member of the package.
3. The method of claim 1 wherein operation (b) comprises: associating the first class with a name, the name including, as at least a portion of the name, the term for which the first class is created.
4. The method of claim 1 wherein operation (b) comprises:
creating an attribute in the first class, the value of the attribute in an instance of the first class representing a thing being classified.
5. The method of claim 1 wherein operation (d) comprises:
associating each of the second classes with a name, the name including, as at least a portion of the name, the sentential form for which the second class is created.
6. The method of claim 2 wherein the vocabulary has a name and wherein the method further comprises:
associating the package with a name based on the name of the vocabulary.
7. The method of claim 1 further comprising:
creating a thing superclass whose instances are representations of things;
creating the fact superclass class whose instances are representations of facts;
making the fact superclass to be a subclass of the thing superclass;
creating the classification superclass whose instances are representations of classifications;
making the classification superclass to be a subclass of the fact superclass;
creating a text superclass whose instances are representations of texts; and
making the text superclass to be a subclass of the thing superclass.
8. The method of claim 1 wherein, for each placeholder of each sentential form in the vocabulary, operation (d) comprises the operation of:
creating an attribute for the placeholder within the class created for the corresponding sentential form.
9. The method of claim 8 wherein the operation of creating an attribute for the placeholder includes the operation of:
assigning a name to the attribute using the text of the term specified for the placeholder.
10. The method of claim 8 wherein the operation of creating an attribute for the placeholder further includes the operation of:
setting the type of the attribute to be a general type representing a thing, the thing being the subject of facts expressed by the vocabulary.
11. An article of manufacture comprising:
a machine-accessible medium including data that, when accessed by a machine, causes the machine to perform operations comprising:
(a) receiving a vocabulary comprising terms and sentential forms, each of the terms comprising a word or phrase representing a concept, each of the sentential forms comprising a prepositional statement representing a fact type and including at least one placeholder, the placeholder being specified by a term;
(b) automatically creating a first class for each of the terms in the vocabulary;
(c) making a classification superclass to be a superclass for each of the first classes, wherein the classification superclass is a subclass of a fact superclass, such that each instance of the first class represents a fact that a thing is classified to be an instance of the concept represented by the corresponding term rather than representing an instance of the concept, and wherein the classification superclass is a superclass whose instances are classifications;
(d) automatically creating a second class for each sentential form in the vocabulary;
(e) making the fact superclass to be a superclass for each of the second classes, wherein the fact superclass is a superclass whose instances are facts, such that each instance of the second class represents a fact that is an instance of the fact type represented by the corresponding sentential form; and
wherein acts (a)-(e) are performed such that the granularity of encapsulation of information in each of the first classes and the second classes is no larger than the representation of a single fact.
12. The article of manufacture of claim 11 wherein the data further comprise data that, when accessed by the machine, cause the machine to perform operations comprising:
(f) creating a package; and,
(g) making each of the classes created in operations (b) and (d) to be a member of the package.
13. The article of manufacture of claim 11 wherein the data causing the machine to perform the operation (b) comprise data that, when accessed by the machine, cause the machine to perform operations comprising:
associating the first class with a name, the name including, as at least a portion of the name, the term for which the first class is created.
14. The article of manufacture of claim 11 wherein the data causing the machine to perform the operation (b) comprise data that, when accessed by the machine, cause the machine to perform operations comprising:
creating an attribute in the first class, the value of the attribute in an instance of the first class representing a thing being classified.
15. The article of manufacture of claim 11 wherein the data causing the machine to perform the operation (d) comprise data that, when accessed by the machine, cause the machine to perform operations comprising:
associating each of the second classes with a name, the name including, as at least a portion of the name, the sentential form for which the second class is created.
16. The article of manufacture of claim 12 wherein the vocabulary has a name and wherein the data further comprise data that, when accessed by the machine, cause the machine to perform operations comprising:
associating the package with a name based on the name of the vocabulary.
17. The article of manufacture of claim 11 wherein the data further comprise data that, when accessed by the machine, cause the machine to perform operations comprising:
creating a thing superclass whose instances are representations of things;
creating a the fact superclass whose instances are representations of facts;
making the fact superclass to be a subclass of the thing superclass;
creating the classification superclass whose instances are representations of classifications;
making the classification superclass to be a subclass of the fact superclass;
creating a text superclass whose instances are representations of texts; and
making the text superclass to be a subclass of the first general class.
18. The article of manufacture of claim 11 wherein the data causing the machine to perform the operation (c) comprise data that, when accessed by the machine, cause the machine to perform operations comprising:
for each placeholder of each sentential form in the vocabulary, creating an attribute for the placeholder within the class created for the corresponding sentential form.
19. The article of manufacture of claim 18 wherein the data causing the machine to perform the operation of creating an attribute for the placeholder comprise data that, when accessed by the machine, cause the machine to perform operations comprising:
assigning a name to the attribute using the text of the term specified for the placeholder.
20. The article of manufacture of claim 18 wherein the data causing the machine to perform the operation of creating an attribute for the placeholder further comprise data that, when accessed by the machine, cause the machine to perform operations comprising:
setting the type of the attribute to be a general type representing a thing, the thing being the subject of facts expressed by the vocabulary.
21. A system comprising:
a processor; and
a memory coupled to the processor, the memory containing instructions that, when executed by the processor, cause the processor to:
(a) receive a vocabulary comprising terms and sentential forms, each of the terms comprising a word or phrase representing a concept, each of the sentential forms comprising a prepositional statement representing a fact type and including at least one placeholder, the placeholder being specified by a term;
(b) automatically create a first class for each of the terms in the vocabulary;
(c) cause a classification superclass to be a superclass for each of the first classes, wherein the classification superclass is a subclass of a fact superclass, such that each instance of the first class represents a fact that a thing is classified to be an instance of the concept represented by the corresponding term rather than representing an instance of the concept, and wherein the classification superclass is a superclass whose instances are classifications;
(d) automatically create a second class for each sentential form in the vocabulary;
(e) cause the fact superclass to be a superclass for each of the second classes, wherein the fact superclass is a superclass whose instances are facts, such that each instance of the second class represents a fact that is an instance of the fact type represented by the corresponding sentential form; and
wherein acts (a)-(e) are performed such that the granularity of encapsulation of information in each of the first classes and the second classes is no larger than the representation of a single fact.
22. The system of claim 21 wherein the instructions further comprise instructions that, when executed by the processor, cause the processor to:
(e) create a package; and,
(f) make each of the classes created in (b) and (d) to be a member of the package.
23. The system of claim 21 wherein the instructions causing the processor to create a first class for each of the terms in the vocabulary comprise instructions that, when executed by the processor, cause the processor to:
associate each of the first classes with a name, the name including, as at least a portion of the name, the term for which the first class is created.
24. The system of claim 21 wherein the instructions causing the processor to create a first class for each of the terms in the vocabulary comprise instructions that, when executed by the processor, cause the processor to:
create an attribute in the first class, the value of the attribute in an instance of the first class representing a thing being classified.
25. The system of claim 21 wherein the instructions causing the processor to create a second class for each sentential form in the vocabulary comprise instructions that, when executed by the processor, cause the processor to:
associate the second class with a name, the name including, as at least a portion of the name, the sentential form for which the second class is created.
26. The system of claim 22 wherein the vocabulary has a name and wherein the instructions further comprise instructions that, when executed by the processor, cause the processor to:
associate the package with a name based on the name of the vocabulary.
27. The system of claim 21 wherein the instructions further comprise instructions that, when executed by the processor, cause the processor to:
create a thing superclass whose instances are representations of things;
create the fact superclass whose instances are representations of facts;
make fact superclass to be a subclass of the thing superclass;
create the classification superclass whose instances are representations of classifications;
make the classification superclass to be a subclass of the fact superclass;
create a text superclass whose instances are representations of texts; and
make text superclass to be a subclass of the thing superclass.
28. The system of claim 21 wherein the instructions causing the processor to create a second class for each of the sentential forms in the vocabulary comprise instructions that, when executed by the processor, cause the processor to:
for each placeholder of each sentential form in the vocabulary, create an attribute for the placeholder within the class created for the corresponding sentential form.
29. The system of claim 28 wherein the instructions causing the processor to create an attribute for the placeholder comprise instructions that, when executed by the processor, cause the processor to:
assign a name to the attribute using the text of the term specified for the placeholder.
30. The system of claim 28 wherein the instructions causing the processor to create an attribute for the placeholder further comprise instructions that, when executed by the processor, cause the processor to:
set the type of the attribute to be a general type representing a thing, the thing being the subject of facts expressed by the vocabulary.

1. A method of adapting a Class II game to provide play characteristics of a Class III game, the method comprising:
simulating a plurality of plays of the Class III game in a computer to obtain, frequencies of occurrence of at least one Class III award;
simulating a plurality of plays of the Class II game in a computer to obtain frequencies of occurrence of at least one Class II outcome;
selecting a Class III award;
obtaining, from the Class III game simulation, relative frequencies of occurrences of main and special sequences that yield the selected Class III award;
selecting a Class II outcome that has a similar frequency of occurrence to selected Class III award;
defining an award for the selected Class II outcome according to the selected Class III award;
randomly selecting a main or a special sequence that yields the selected Class III award when the selected Class II outcome occurs during play of the Class II game, wherein randomly selecting the main or special sequence comprises weighting the random selection according to the obtained relative frequencies of occurrence of the main and special sequences; and
providing a display corresponding with a display that would have been displayed if the player had been playing the Class III game and had won the selected Class III award according to the selected sequence.
2. A method of adapting a Class II game to provide play characteristics of a Class III game, the method comprising:
simulating a plurality of plays of the Class III game in a computer to obtain frequencies of occurrence of at least one Class III award;
simulating a plurality of plays of the Class II game in a computer to obtain frequencies of occurrence of at least one Class II outcome;
grouping the Class III awards according to ranges of awards;
selecting a Class III award;
obtaining, from the Class III game simulation, relative frequencies of occurrences of main and special sequences that yield awards in the Class III award group that includes the selected Class III award;
selecting a Class II outcome that has a similar frequency of occurrence to the selected Class III award;
defining an award for the selected Class II outcome according to awards in the Class III award group that includes the selected Class III award;
randomly selecting a main or a special sequence that yields an award in the Class III award group that includes the selected Class III award when the selected Class II outcome occurs during play of the Class II game, wherein randomly selecting the main or special sequence comprises weighting the random selection according to the obtained relative frequencies of occurrence of the main and special sequences; and providing a display corresponding with a display that would have been displayed if the player had been playing the Class III game and had won the given Class III award according to the selected sequence.
3. A method of adapting a Class II game to provide play characteristics of a Class III game, the method comprising:
simulating a plurality of plays of the Class III game in a computer to obtain frequencies of occurrence of a plurality of Class III awards;
simulating a plurality of plays of the Class II game in a computer to obtain frequencies of occurrence of at least one Class II outcome;
grouping the Class III awards according to ranges of awards;
selectin a Class III award;
selecting a Class II outcome that has a similar frequency of occurrence to the selected Class III award;
defining an award for the selected Class II outcome according to the selected Class III award, wherein defining an award for the selected Class II outcome comprises defining an award according to awards in the Class III award group that includes the selected Class III award;
running a second simulation of a plurality of plays of the Class II game in a computer using the defined awards of the selected Class II outcomes; and
adjusting the defined awards of the Class II outcomes according to any differences between awards awarded in the second simulation of the Class II game and awards awarded in the simulation of the Class III game.
4. A computer system configured to a Class II carne to characteristics of a Class III game, the computer system comprising:
one or more memories;
one or more processors communicatively coupled with the one or more memories, the one or more processors configured to:
simulate a plurality of plays of the Class III game in a computer to obtain frequencies of occurrence of at least one Class III award;
simulate a plurality of plays of the Class II game in a computer to obtain frequencies of occurrence of at least one Class II outcome;
select a Class III award;
obtain, from the Class III game simulation, relative frequencies of occurrences of main and special sequences that yield the selected Class III award;
select a Class II outcome that has a similar frequency of occurrence to the selected Class III award;
randomly select a main or a special sequence that yields the selected Class III award when the selected Class II outcome occurs during play of the Class II game, wherein randomly selecting the main or special sequence comprises weighting the random selection according to the obtained relative frequencies of occurrence of the main and special sequences; and
define an award for the selected Class II outcome according to the selected Class III award.
5. A computer program product for adapting a Class II game to provide play characteristics of a Class III game, the computer program product comprising:
a non-transitory computer-readable medium comprising:
code for simulating a plurality of plays of the Class III game in a computer to obtain frequencies of occurrence of at least one Class III award;
code for simulating a plurality of plays of the Class II game in a computer to obtain frequencies of occurrence of at least one Class II outcome;
code for grouping the Class III awards according to ranges of awards;
code for selecting a Class III award;
code for obtaining, from the Class III game simulation, relative frequencies of occurrences of main and special sequences that yield awards in a Class III award group that includes the selected Class III award;
code for selecting a Class II outcome that has a similar frequency of occurrence to the selected Class III award;
code for defining an award for the selected Class II outcome according to awards in the Class III award group that include the selected Class III award;
code for randomly selecting a main or a special sequence that yields an award in the Class III award group that includes the selected Class III award when the selected Class II outcome occurs during play of the Class II game, wherein randomly selecting the main or special sequence comprises weighting the random selection according to the obtained relative frequencies of occurrence of the main and special sequences; and
code for providing a display corresponding with a display that would have been displayed if the player had been playing the Class III game and had won the given Class III award according to the selected sequence.
6. A computer program product for adapting a Class II game to provide play characteristics of a Class III game, the computer program product comprising:
a non-transitory computer-readable medium comprising:
code for simulating a plurality of plays of the Class III game in a computer

to obtain frequencies of occurrence of at least one Class III award;
code for simulating a plurality of plays of the Class II game in a computer

to obtain frequencies of occurrence of at least one Class II outcome;
code for grouping the Class III awards according to ranges of awards;
code for selecting a Class III award;
code for selecting a Class II outcome that has a similar frequency of occurrence to the selected Class III award; and
code for defining an award for the selected Class II outcome according to awards in the Class III award group that include the selected Class III award;
code for running a second simulation of a plurality of plays of the Class II game in a computer using the defined awards of the selected Class II outcomes; and
code for adjusting the defined awards of the Class II outcomes according to any differences between awards awarded in the second simulation of the Class II game and awards awarded in the simulation of the Class III game.
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 film scanner for reading an image formed on a film, said film scanner comprising:
an imaging device that senses a part of said image to generate an image signal;
a transport table that supports said film;
a stepper motor that moves said transport table in a predetermined direction, so that said imaging device can sense the whole of said image, said stepper motor being driven in steps; and
an image signal reading processor that reads said image signal in synchronization with movement of said transport table, said image signal reading processor reading at one or both of a first timing where said stepper motor stops at a rotational angle position of a step and a second timing where said stepper motor temporarily stops at least at one rotational angle position during a step.
2. A film scanner according to claim 1, wherein said second timing is a temporary stopping at a rotational angle position of half of a step.
3. A film scanner according to claim 1, wherein said image signal reading processor reads said image signal only at said first timing of said stepper motor at the time of a pre-scan of the film and reads said image signal at each of said first timing and said second timing at the time of a main-scan of the film.
4. A film scanner according to claim 1, wherein said stepper motor is temporarily stopped at a point of time of overshoot caused when driven by said step and said second timing is the timing of the temporary stopping due to said overshoot.
5. A film scanner according to claim 4, wherein the rotational angle position of the state of temporary stopping of said stepper motor at the time of overshoot is a predetermined rotational angle position in the middle of said step.
6. A film scanner according to claim 1, wherein said transport table is provided detachably with a film holder for holding said film, a position of said film holder to said transport table being changed to switch said image to be scanned.
7. A film scanner according to claim 1, further comprising a rack provided at said transport table along said predetermined direction, and a pinion attached to an output shaft of said stepper motor to engage with said rack.
8. A film scanner according to claim 1, further comprising an image signal rearranging processor rearranges said image signals read at said first and second timings in order, so that arranged mage signals of the correct order are obtained.
9. A film scanner provided with an imaging device for performing a main-scan of a film on which an image is formed to scan said image and a scanning mechanism for moving the film in a sub-scan direction perpendicular to said main-scan direction with respect to said imaging device, characterized in that said scanning mechanism is provided with a transport table for supporting said film and transporting it in said sub-scan direction, a transport mechanism for making said transport table move in said sub-scan direction, and an image signal reading processor for reading an image signal of said film obtained by said imaging device in synchronization with movement of said transport table, said transport mechanism is provided with a stepper motor serving as a source of drive power and driven in required steps, and said image signal reading processor is configured to read said image signal at one or both of a first timing where said stepper motor stops at a rotational angle position of a step and a second timing where it temporarily stops at least at one rotational angle position during a step.