Author: claimsbot

1. A protective layer thermal transfer film, comprising: at least a release layer, and
a protective layer, formed on one surface of a substrate film;
the release layer being formed from at least a silicone-modified resin and silicone oil.
2. The protective layer thermal transfer film of claim 1, wherein the protective layer contains at least a peeling layer, the peeling layer is formed from an aqueous coating solution.
3. The protective layer thermal transfer film of claim 1 or claim 2, wherein the silicone oil is polyether-modified silicone oil.
4. The protective layer thermal transfer film of claim 1, wherein the silicone oil has a viscosity of 500 mm2s or less (25\xb0 C.).
5. The protective layer thermal transfer film of claim 2, wherein the peeling layer comprises at least a water-based resin and silica particles; the silica particles being set to 90% by weight or less as solids.
6. The protective layer thermal transfer film of claim 1, wherein a heat sublimable color material layer andor a heat meltable color material layer are formed on one face of the substrate file together with the thermally transferable protective layer.

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 of displaying a cursor, comprising:
obtaining a cursor image indication, indicative of a cursor image;
obtaining an ancillary image indication, indicative of an ancillary image, based on the cursor image indication;
forming a composite image indication indicative of a composite image containing both the cursor image and the ancillary image, a location at which the ancillary image is located being based on a location at which the cursor image is located; and,

displaying the composite image.
2. The method of claim 1 wherein obtaining a cursor indication comprises:
obtaining a cursor AND-mask.
3. The method of claim 2 wherein obtaining an ancillary image indication comprises:
obtaining an ALPHA-mask based on the cursor AND-mask.
4. The method of claim 3 wherein the cursor AND-mask comprises a bitmap having dimensions similar to dimensions of a bitmap defining the cursor image, and wherein each bit defines whether a display by a corresponding pixel is visible or non-visible.
5. The method of claim 4 wherein obtaining an ALPHA-mask comprises:
enlarging the AND-mask to include a border;
translating values in the AND-mask bitmap from visible values corresponding to a visible portion of the cursor image to translucent values; and
repositioning the translucent values within the enlarged AND-mask by a desired offset value.
6. The method of claim 5 wherein repositioning comprises:
repositioning the translucent values by a predetermined offset value.
7. The method of claim 5 wherein the repositioning step comprises:
obtaining the desired offset value based on a dynamically changing variable; and
repositioning the translucent values based on the obtained offset value.
8. The method of claim 7 wherein obtaining the desired offset value comprises:
obtaining the desired offset value based on a displayed position of the cursor image.
9. The method of claim 8 wherein obtaining the desired offset value comprises:
obtaining the desired offset value based on a displayed position of the cursor image and a time of day.
10. The method of claim 7 wherein obtaining the desired offset value comprises:
obtaining the desired offset value based on data associated with an image underlying a displayed position of the cursor image.
11. The method of claim 7 wherein obtaining the desired offset value comprises:
obtaining the desired offset value based on an operator input from a pointing device.
12. The method of claim 7 wherein obtaining the desired offset value comprises:
obtaining the desired offset value based on a size dimension of the cursor image.
13. The method of claim 3 wherein the displaying step comprises:
blending the ancillary image to a display screen based on the ALPHA-mask; and
blending the cursor image to the display screen based on the cursor AND-mask.
14. The method of claim 13 wherein blending the ancillary image and blending the cursor image are performed by blending a composite image, including an ancillary image component and a cursor image component, to the display screen.
15. The method of claim 13 wherein blending the ancillary image and blending the cursor image each comprise:
blending the ancillary image and the cursor image to a temporary bitmap; and
copying the contents of the temporary bitmap to the display screen.
16. The method of claim 3 wherein the displaying step comprises:
blending the ancillary image to a display screen according to a function having a first term corresponding to a portion of the ancillary image displayed and a second term corresponding to a portion of an underlying image displayed.
17. The method of claim 3 and further comprising:
softening the ALPHA-mask.
18. The method of claim 17 wherein the softening step comprises:
filtering the ALPHA-mask with an averaging filter a desired number of times.
19. The method of claim 18 wherein the desired number of times is based on data associated with an image underlying a displayed position of the cursor image.
20. The method of claim 1 wherein the ancillary image appears as a shadow of the cursor image.
21. The method of claim 1 wherein the ancillary image appears as an image formed by light impinging on a surface after passing through the cursor image.
22. A computer readable medium containing instructions which, when executed by a computer cause the computer to perform steps of:
obtaining a cursor image indication, indicative of a cursor image;
obtaining an ancillary image indication, indicative of an ancillary image, based on the cursor image indication;
forming a composite image indication indicative of a composite image containing both the cursor image and the ancillary image,
a location at which the ancillary image is located being based on a location at which the cursor image is located; and displaying the composite image.
23. The computer readable medium of claim 22 wherein obtaining a cursor indication comprises:
obtaining a cursor AND-mask.
24. The computer readable medium of claim 22, further comprising:
wherein obtaining a cursor image indication comprises obtaining a cursor AND-mask; and
wherein obtaining an ancillary image indication comprises obtaining an ALPHA-mask based on the cursor AND-mask.
25. The computer readable medium of claim 24 wherein the cursor AND-mask comprises a bitmap having dimensions similar to dimensions of a bitmap defining the cursor image, and wherein each bit defines whether a display by a corresponding pixel is visible or non-visible.
26. The computer readable medium of claim 25 wherein obtaining an ALPHA-mask comprises:
enlarging the AND-mask to include a border;
translating values in the AND-mask bitmap from visible values corresponding to a visible portion of the cursor image to translucent values; and
repositioning the translucent values within the enlarged AND-mask by a desired offset value.
27. The computer readable medium of claim 26 wherein repositioning comprises:
repositioning the translucent values by a predetermined offset value.
28. The computer readable medium of claim 26 wherein the repositioning step comprises:
obtaining the desired offset value based on a dynamically changing variable; and
repositioning the translucent values based on the obtained offset value.
29. The computer readable medium of claim 28 wherein obtaining the desired offset value comprises:
obtaining the desired offset value based on a displayed position of the cursor image.
30. The computer readable medium of claim 29 wherein obtaining the desired offset value comprises:
obtaining the desired offset value based on a displayed position of the cursor image and a time of day.
31. The computer readable medium of claim 28 wherein obtaining the desired offset value comprises:
obtaining the desired offset value based on data associated with an image underlying a displayed position of the cursor image.
32. The computer readable medium of claim 28 wherein obtaining the desired offset value comprises:
obtaining the desired offset value based on an operator input from a pointing device.
33. The computer readable medium of claim 26 wherein repositioning comprises:
obtaining the desired offset value based on dimensions of the cursor image.
34. The computer readable medium of claim 24 wherein the displaying step comprises:
blending the ancillary image to a display screen based on the ALPHA-mask; and
blending the cursor image to the display screen based on the cursor AND-mask.
35. The computer readable medium of claim 34 wherein blending the ancillary image and blending the cursor image are performed by blending a composite image, including an ancillary image component and a cursor image component, to the display screen.
36. The computer readable medium of claim 24 wherein the displaying step comprises:
blending the ancillary image to a display screen using according to a function having a first term corresponding to a portion of the ancillary image displayed and a second term corresponding to a portion of an underlying image displayed.
37. The computer readable medium of claim 24 and further comprising:
softening the ALPHA-mask.
38. The computer readable medium of claim 37 wherein the softening step comprises:
filtering the ALPHA-mask with an averaging filter a desired number of times.
39. The computer readable medium of claim 38 wherein the desired number of times is based on data associated with an image underlying a displayed position of the cursor image.

1. A computer-implemented method of automatically generating a story, comprising:
selecting a theme of said story;
examining elements of said theme and instantiating said theme;
using said theme to select and control other aspects of the story generation, including a plot of said story which employs knowledge-generated characteristics, relationships, and events.
2. The computer-implemented method according to claim 1, further comprising inputting said elements of said theme into a stage, said stage being a collection of elements of said story and their interrelationships.
3. The computer-implemented method according to claim 1, further comprising inputting said elements into a simulation engine to play out a series of events over time, thereby to generate a plot, said plot including characters, their characteristics, and their respective interactions, and a history of events and their temporal relationships, said simulation engine including a predetermined randomness such that random elements from said databases are selected.
4. The computer-implemented method according to claim 1, further comprising inputting said elements into a simulation engine to play out a series of events over time.
5. The computer-implemented method according to claim 1, further comprising generating a plot.
6. The computer-implemented method according to claim 5, wherein said plot comprises characters, their characteristics, and their respective interactions, and a history of events and their temporal relationships.
7. The computer-implemented method according to claim 5, wherein said simulation engine comprises a predetermined randomness such that random elements from said databases are selected.
8. The computer-implemented method according to claim 5, wherein said plot comprises at least one of characters, their characteristics, and their respective interactions, and a history of events and their temporal relationships.
9. The method according to claim 1 further comprising:
developing a scenario, including a plurality of activities, based on said plot generated, such that details of said activities are developed and bridged.
10. The method according to claim 9, wherein said scenarios are in a formal, logic based language independent of a spoken language, said method further comprising:
inputting said scenarios into a natural language generator such that said scenarios are converted from said logic-based language to a natural language, said natural language being a spoken language understandable by a human reader, said conversion from said logic-based language to said natural language influencing at least one of story grammars, literary constraints, words, phrases, and sentence structure used in said scenario.
11. A signal-bearing medium tangibly embodying a program of machine-readable instructions executable by a digital processing apparatus to perform a method of story generation, said method comprising:
selecting a theme of said story;
examining elements of said theme and instantiating said theme;
using said theme to select and control other aspects of the story generation, including a plot of said story which employs knowledge-generated characteristics, relationships, and events.
12. A computer-implemented method of automatically generating a story, comprising:
inputting elements of a story into a simulation engine to play out a series of events over time, thereby to generate a plot, said plot including at least one of characters, their characteristics, and their respective interactions, and a history of events and their temporal relationships.

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 computer implemented context method, comprising:
Establishing a communication link with an application,
Identifying each of one or more layers of context analyzed by said application using said communication link,
Assigning a context quotient to the application and determining which context layers should be included in a packet of data forwarded to the application based on a number of context layers analyzed by the application, and
Creating and sending a packet containing information only from the identified context layers to the application.
2. The method of claim 1, wherein an application is selected from the group consisting of Accounting application, Alliance management application, Asset management application, Brand management application, Budgetingfinancial planning application, Business intelligence application, Call management application, Cash management application, Channel management application, Commodity risk management application, Content management application, Contract management application, Credit-risk management application, Customer relationship management application, Data integration application, Demand chain application, Decision support application, Document management application, Email management application, Employee relationship management application, Energy risk management application, Executive dashboard application, Expense report processing application, Fleet management application, Fraud management application, Freight management application, Human capital management application, Human resource management application, Incentive management application, Innovation management application, Insurance management application, Intellectual property management application, Intelligent storage application, Interest rate risk management application, Investor relationship management application, Knowledge management application, Learning management application, Location management application, Maintenance management application, Material requirement planning application, Metrics application, Online analytical processing application, Ontology management application, Partner relationship management application, Payroll application, Performance management application, Price optimization application, Exchange application, Process management application, Product life-cycle management application, Project management application, Project portfolio management application, Revenue management application, Risk management application, Risk simulation application, Sales force automation application, Scorecard application, Sensor grid application, Service management application, Six-sigma quality management application, Strategic planning application, Supply chain application, Supplier relationship management application, Support chain application, Taxonomy development application, Technology chain application, Unstructured data management application, Visitor (web site) relationship management application, Weather risk management application, Workforce management application, Yield management application and combinations thereof.
3. The method of claim 1, wherein a layer of context is selected from the group consisting of Physical, Tactical, Instant, Organization, Mission, Social Environment and combinations thereof.
4. A context aware system, comprising a machine with a processor having circuitry to execute instructions; a storage device available to said processor with sequences of instructions stored therein, which when executed cause the processor to:
Establish a communication link with an application,
Identify each of one or more aspects of context analyzed by said application by completing a test of said application using said communication link,
Determine which aspects of context should be included in a packet of data forwarded to the application based on a result of the test, and
Create and send a packet containing data only from the identified aspects of context to the application
where a machine is selected from the group consisting of phone, personal digital assistant, computer and combinations thereof.
5. The system of claim 4, wherein an application is selected from the group consisting of Accounting application, Alliance management application, Asset management application, Brand management application, Budgetingfinancial planning application, Business intelligence application, Call management application, Cash management application, Channel management application, Commodity risk management application, Content management application, Contract management application, Credit-risk management application, Customer relationship management application, Data integration application, Demand chain application, Decision support application, Document management application, Email management application, Employee relationship management application, Energy risk management application, Executive dashboard application, Expense report processing application, Fleet management application, Fraud management application, Freight management application, Human capital management application, Human resource management application, Incentive management application, Innovation management application, Insurance management application, Intellectual property management application, Intelligent storage application, Interest rate risk management application, Investor relationship management application, Knowledge management application, Learning management application, Location management application, Maintenance management application, Material requirement planning application, Metrics application, Online analytical processing application, Ontology management application, Partner relationship management application, Payroll application, Performance management application, Price optimization application, Exchange application, Process management application, Product life-cycle management application, Project management application, Project portfolio management application, Revenue management application, Risk management application, Risk simulation application, Sales force automation application, Scorecard application, Sensor grid application, Service management application, Six-sigma quality management application, Strategic planning application, Supply chain application, Supplier relationship management application, Support chain application, Taxonomy development application, Technology chain application, Unstructured data management application, Visitor (web site) relationship management application, Weather risk management application, Workforce management application, Yield management application and combinations thereof.
6. The system of claim 4, wherein an aspect of context is selected from the group consisting of Physical Status, Tactical Situation, Instant Impact, Organization, Mission Measure, Social Environment and combinations thereof.
7. A program storage device readable by a machine with a processor, tangibly embodying a program of instructions executable by at least one machine with a processor to perform a context method, comprising:
Establish a communication link with an application,
Identify each of one or more aspects of context analyzed by said application by completing a test of said application using said communication link,
Determine which aspects of context should be included in a packet of data forwarded to the application based on a result of the test, and
Create and send a packet containing data only from the identified aspects of context to the application.
8. The program storage device of claim 7, wherein an application is selected from the group consisting of Accounting application, Alliance management application, Asset management application, Brand management application, Budgetingfinancial planning application, Business intelligence application, Call management application, Cash management application, Channel management application, Commodity risk management application, Content management application, Contract management application, Credit-risk management application, Customer relationship management application, Data integration application, Demand chain application, Decision support application, Document management application, Email management application, Employee relationship management application, Energy risk management application, Executive dashboard application, Expense report processing application, Fleet management application, Fraud management application, Freight management application, Human capital management application, Human resource management application, Incentive management application, Innovation management application, Insurance management application, Intellectual property management application, Intelligent storage application, Interest rate risk management application, Investor relationship management application, Knowledge management application, Learning management application, Location management application, Maintenance management application, Material requirement planning application, Metrics application, Online analytical processing application, Ontology management application, Partner relationship management application, Payroll application, Performance management application, Price optimization application, Exchange application, Process management application, Product life-cycle management application, Project management application, Project portfolio management application, Revenue management application, Risk management application, Risk simulation application, Sales force automation application, Scorecard application, Sensor grid application, Service management application, Six-sigma quality management application, Strategic planning application, Supply chain application, Supplier relationship management application, Support chain application, Taxonomy development application, Technology chain application, Unstructured data management application, Visitor (web site) relationship management application, Weather risk management application, Workforce management application, Yield management application and combinations thereof.
9. The program storage device of claim 7, wherein an aspect of context is selected from the group consisting of Physical Status, Tactical Situation, Instant Impact, Organization, Mission Impact, Social Environment and combinations thereof.