System and method for a dynamic professional syllabus

• US 20020018066A1
• Filed: 07/05/2001
• Published: 02/14/2002
• Est. Priority Date: 07/05/2000
• Status: Abandoned Application

• Current Assignee: Amos Vizer
• Original Assignee: Amos Vizer
• Inventors: Vizer, Amos
• Application Number:
  US09/897,959
• Publication Number:
  US 20020018066A1
• Time in Patent Office: Days
• US Class Current: 345/428
• CPC Class Codes: G06T 17/20 Finite element generation, e.g. wire-frame surface description, tesselation
• CPC Class Codes: G09B 7/00 Electrically-operated teaching apparatus or devices working with questions and answers mechanically operated G09B3/00; computing arrangements G06F
• CPC Class Codes: G09B 9/00 Simulators for teaching or training purposes for the use of weapons F41; computing aspects G06; protocols for games, networked simulations or virtual reality H04L67/131

Abstract

The present invention relates to an integrated professional information server and, in particular, it concerns a inter or intra-net system to coordinate professional learning, organization, information, and communication needs, generate and communicate a syllabus containing a program of missions. Exercises strengthen a professional'"'"'s proficiency and knowledge in at least one topic. Preferentially the syllabus automatically presents at least one trainee with appropriate exercises, controls support materials, and tracks progress. An on-line real time graphical simulation algorithm facilitates simulations of real localities.

Claims

1. A system for generating a syllabus for a trainee, the system comprising:

a) a database containing at least one topic and at least one topic attribute;

b) a processor in communication with said data base, said processor designed and configured to generate the syllabus based on said topic and topic attribute;

c) an input interface capable of communicating with said processor; and

d) an output interface capable of communicating with said processor.

2. The system of claim 1, wherein said input interface further includes at least one tool selected from the group consisting of a scenario builder, a device builder, a virtual instructor builder, a terrain builder, an import export algorithm and a certification tool.

3. The system of claim 1, wherein said database further stores trainee data and the syllabus is further based on said trainee data.

4. The system of claim 3, wherein said processor receives trainee performance data from training equipment, evaluates trainee performance and updates said database.

5. The system of claim 4, wherein said evaluation of performance is available to the trainee.

6. The system of claim 5, wherein said evaluation of performance includes an option to replay said exercise.

7. The system of claim 4, wherein said evaluation of performance is reported to an administrative user.

8. The system of claim 3, wherein said input interface includes at least one interface selected from the group consisting of a personal computer, formatted evaluations, an output channel of a training simulator, a medical database, a psychological database, a data collection device of a vehicle, a device measuring the performance of a vehicle, a voice communication device, an automated test reader, a personal digital assistant, a recording device, a scanner, and an e-mail message.

9. The system of claim 3, wherein said input interface serves at least one purpose selected from the group consisting of to edit said topic, to edit said topic attribute, to enter information pertaining to a budget, to edit information pertaining to resource availability, and to edit information pertaining to scheduling.

10. The system of claim 3, wherein said output interface serves at least one purpose selected from the group consisting of presenting a training exercise, presenting a training session program, presenting orders for a required resource, reporting progress, reporting budget information, and reporting schedule information.

11. The system of claim 3, wherein the syllabus includes a briefing.

12. The system of claim 3, wherein said trainee data includes at least one member of the group consisting of psychological data, an exercise previously completed by the trainee, time required by the trainee to complete said already completed exercise, previous experience of the trainee, and schedule information pertinent to the trainee.

13. The system of claim 1, wherein the syllabus contains a crew exercise, said crew exercise including a plurality of trainees.

14. The system of claim 13, wherein said plurality of trainees uses a plurality of output interfaces communicating via a network.

15. The system of claim 14, wherein the syllabus includes a mission and said plurality of input interfaces, said plurality of output interfaces and said network further serve to coordinate said mission.

16. The system of claim 1, wherein said database further stores at least one data item selected from the group consisting of a data library, a tutorial, a tip, a memo and a test.

17. The system of claim 16, wherein said memo requires reception verification by an intended recipient.

18. The system of claim 16, wherein said database further includes information pertinent to the trainee.

19. The system of claim 18, wherein said processor further pushes data to said output interface at an appropriate time.

20. The system of claim 1, wherein said attribute of said topic consist of at least one attribute selected from the group consisting of a topic level, an order in which said topics are to be covered, an exercise to train said topic, a prerequisite to performing said exercise, an estimated time needed by a typical trainee to complete said exercise, a resource required for said exercise, a resource availability, a budget information, a requisite for successful completion of said topic, and a requisite for successful completion of said exercise.

21. The system of claim 1, wherein said processor is a personal computer.

22. The system of claim 1, wherein said output interface consists of at least one interface selected from the group consisting of a video viewer, a training simulator, a training simulator control channel, voice instructions, a communication channel of a training vehicle, a control channel of a training vehicle, a printer, a personal digital assistant, an e-mail message, and a personal computer.

23. The system of claim 1, wherein the syllabus includes a program for a class, said class comprising a plurality of trainees.

24. The system of claim 1, further comprising:

e) a communication network in communication with said processor; and

f) a communication device in communication with said communication network to be used for at least one purpose selected from the group consisting of said data input interface, said output interface.

25. The system of claim 24, wherein said communication network is selected from the group consisting of the Internet, a cellular communication network, a telephone network, a computer network, a radio transmitter and receiver network and interconnected fax machines.

27. The method of claim 26, further comprising the steps of:

d) inputting trainee data; and

e) updating the syllabus based on said trainee data.

28. The method of claim 27, wherein data is provided using at least one interface selected from the group consisting of a personal computer, formatted evaluations, an output channel of a training simulator, a medical database, a psychological database, a data collection device of a vehicle, a device measuring the performance of a vehicle, an automated test reader, a personal digital assistant, a recording device, a scanner, and an e-mail message.

29. The method of claim 27, wherein said trainee data includes trainee progress communicated to said database by training equipment.

30. The method of claim 27, wherein the syllabus includes a program for a class comprising a plurality of trainees.

31. The method of claim 27, wherein the step of providing said database includes at least one of sub-step selected from the group consisting of editing said topic, editing said topic attribute, entering information pertaining to a budget, editing information pertaining to resource availability, and editing information pertaining to scheduling.

32. The method of claim 27, wherein the step of outputting the syllabus includes at least one step selected from the group consisting of presenting a training exercise, presenting a training session program, presenting orders for a required resource, reporting progress, reporting budget information, presenting a crew exercise and reporting schedule information.

33. The method of claim 27, wherein said trainee data includes at least one member of the group consisting of psychological data, an exercise previously completed by the trainee, time required by the trainee to complete said already completed exercise, previous experience of the trainee, and schedule information pertinent to the trainee.

34. The method of claim 32, wherein said crew exercise is performed by a plurality of trainees using a plurality of input interfaces said input interfaces interconnected by a network.

35. The method of claim 26, further comprising the step:

d) providing information pertinent to the syllabus.

36. The method of claim 26, wherein said attribute of said topic consists of at least one attribute selected from the group consisting of a topic level, an order in which topics are to be covered, an exercise for training said topic, a prerequisite for performing said exercise, an estimated time to complete said exercise, a resource required for said exercise, a resource availability, a requisites for successful completion of said topic, and a requisite for successful completion of said exercise.

37. The method of claim 26, wherein the syllabus is generated by a personal computer.

38. The method of claim 26, wherein said output is provided by at least one interface selected from the group consisting of a video viewer, a training simulator program, a training simulator control channel, voice instructions, a communication channels of a vehicle, control channels of a training vehicle, and a printer.

39. The method of claim 26, wherein the syllabus includes a flight training exercise.

40. The method of claim 26, further comprising the steps of:

e) providing a communication network in communication with said processor; and

f) providing communication devices in communication with said communication network to be used for at least one purpose selected from the group consisting of inputting trainee data, inputting topic data, inputting attribute data and said step of outputting the syllabus.

41. The method of claim 40, wherein said communication network is selected from the group consisting of the Internet, a cellular communication network, a telephone network, a computer network, a radio transmitter and receiver network and interconnected fax machines.

26. A method for generating a syllabus for a trainee, the method comprising the steps of:

a) providing a database containing at least one topic and at least one topic attribute;

b) generating the syllabus based on said topic and topic attribute in said database; and

c) outputting the syllabus.

42. A method of adaptive real time triangulation for progressive meshing of a domain based on a geometrical data set, the method comprising the steps of:

a) generating an optimal unstructured map based on the geometrical data;

b) storing said optimal unstructured map; and

C) constructing a polygon mesh in a section of the domain at a required level of detail based on said optimal unstructured map.

43. The method of claim 42, further comprising the step of:

d) modifying a location in said polygon mesh to meet a required level of detail.

44. The method of claim 43, wherein said steps of generating, storing and constructing are performed off-line and said step of modifying is performed repeatedly on-line according to need.

45. The method of claim 43, wherein said step of modifying a location in said polygon mesh includes at least one sub-step selected from the group consisting of splitting a polygon and reducing a plurality of polygons.

46. The method of claim 44, wherein for said step of splitting a polygon, the height of new vertices is assigned by at least one technique selected from the group consisting of kridging from known heights on said optimum unstructured map, interpolation of heights of said optimum unstructured map, interpolation of heights in said polygon mesh, hierarchical subdivision, and conditional random simulation.

47. The method of claim 44, wherein said splitting and said reduction of polygons is by the Rottger-Hiedrich algorithm.

48. The method of claim 42, wherein said geometric data is ground level data.

49. The method of claim 42, wherein said geometric data is digitized from a graphic image.

50. The method of claim 42, further comprising the step of:

d) rendering an image.

51. The method of claim 50, wherein said image is for use by a flight simulator.

52. The method of claim 42, wherein said step of generating an optimal unstructured map includes the sub-step of fitting a set of best-fit curves to the geometrical data.

53. The method of claim 52, wherein said set of best-fit curves are a set of splines.

54. The method of claim 52, wherein said step of generating an optimal unstructured map further includes the sub-step of creating a set of control points from said set of best-fit curves.

55. The method of claim 54, wherein said best-fit curves are Bezier splines;

and said control points correspond to said set of Bezier splines.

56. The method of claim 42, wherein said step of generating an optimal unstructured map includes the sub-steps of:

i) breaking the domain into zones; and

ii) generating an optimal unstructured map in at least one of said zones.

57. The method of claim 56, wherein said zones are divided such that each zone has a consistent variance structure.

58. The method of claim 42, wherein said step of generating an optimal unstructured map includes the sub-step of sampling the geometrical data and wherein said optimal unstructured map is generated from said sample of said geometric data.

59. The method of claim 58, wherein a size of said sample of said geometric data is chosen based on scale of variance of the geometrical data.

60. The method of claim 42, wherein said step of generating an optimal unstructured map includes the sub-step of analyzing the scale of variance of the geometrical data.

61. The method of claim 60, wherein said analysis of scale of variance includes at least one analysis selected from the group including a Fourier analysis and spatial-statistical analysis.

62. The method of claim 61, wherein said variance structure is described by at least one characteristic selected from the list including a spectrum, a variogram, a covariogram, a fractal, and indicator statistics.

63. The method of claim 61, wherein conditional random simulation is used for at least one purpose selected from the group consisting of to simulate data in a location where the geometrical data is inadequate for said generation of said optimal unstructured map, to fill in data in a location where said optimal unstructured map is insufficient for said construction of said polygon mesh and to fill in data when modifying said polygon mesh in a location where said optimal unstructured map and said polygon mesh are insufficient for said required level of detail.

64. The method of claim 42, wherein said step of constructing a polygon mesh includes the step of triangulation.

65. The method of claim 64, wherein said step of triangulation is Delaunay triangulation.

66. The method of claim 42, wherein said step of constructing a polygon mesh includes the sub-step of simplifying at least one map selected from the group consisting of said optimal unstructured map and said polygon mesh.

68. The method of claim 67, wherein said sub-step of joining is by stitching.

69. The method of claim 67, wherein said geometric map is an optimal unstructured map.

70. The method of claim 67, wherein said sub-step of dividing the domain into sub-domains is accomplished by employing at least one attribute selected from the group consisting of variance and required level of detail.

67. A method of adaptive real time triangulation for progressive meshing of a domain based on a geometrical data set, the method comprising the steps of:

a) storing a geometric map of the domain;

b) constructing a polygon mesh in a section of the domain at a required level of detail based on said geometric map including the sub-steps of;

i) dividing the domain into a plurality of sub-domains;

ii) constructing a plurality of polygon sub-meshes, each polygon sub-mesh of said plurality of polygon sub-meshes being in one sub-domain of said plurality of sub-domains, each said polygon sub-mesh being based on said geometric map.

iii) joining a first sub-mesh of said plurality of sub-meshes to a second sub-mesh of said plurality of sub-meshes where said first sub-mesh and said second sub-mesh share a common boundary.

71. A system to progressively mesh a domain using adaptive real time triangulation comprising:

a) a processor designed and configured for;

i) generating an optimal unstructured map of the domain based on geometric data;

ii) constructing a polygon mesh of a portion of the domain at a required level of detail based on said optimal unstructured map; and

iii) modifying said polygon mesh to meet a new required level of detail

b) an input interface capable of communicating with said processor and designed and configured for inputting said geometric data;

c) a database capable of communicating with said processor and designed and configured for storing said optimal unstructured map and said polygon mesh; and

d) an output interface capable of communicating with said processor and designed and configured for outputting said polygon mesh.

72. The system of claim 71, wherein said processor is further designed and configured for breaking the domain into a plurality of sub-domains;

generating a sub-mesh in each sub-domain and joining said sub-meshes.

73. The system of claim 71, wherein said processor is further designed and configured to analyze variance of said geometric data.

74. The system of claim 71, wherein said processor is further designed and configured to simplify at least one mesh selected from the group comprising said optimal unstructured map and said polygon mesh.

75. The system of claim 71, wherein said processor is further designed and configured to select sample of points from said geometric data.

76. The system of claim 71, wherein said processor is further designed and configured to fill in the geometrical data with simulated data in a location in the domain by conditional random simulation.

77. The system of claim 71, wherein said input interface includes a digitizer to manufacture said geometric data from a graphic image.

78. The system of claim 71, wherein said output interface is a flight simulator which uses said polygon mesh to render an image.