1. An optical apparatus comprising at least one light source generating at least one input beam, at least one Flexible Reflective Analog Modulator (FRAM), said FRAM generally comprising a flexible reflective member attached to a substrate by at least one leg extending outwardly therefrom, an electrode on said substrate and an electrode on said flexible reflective member thus forming a set of electrodes for applying an actuation voltage thereon, the optical apparatus further comprising an illumination optics comprising at least one lens, said lens focusing said input beam to produce at least one focused beam, said focused beam comprising a beam waist, said FRAM having a FRAM position either in front of, behind or at said beam waist and a FRAM orientation such that said focused beam is divergently reflected by said flexible reflective member of said FRAM to produce at least one reflected beam therefrom.
2. The optical apparatus as claimed in claim 1, wherein said light source comprises a laser.
3. The optical apparatus as claimed in claim 1, wherein said FRAM has a FRAM position in front of said beam waist.
4. The optical apparatus as claimed in claim 1, wherein said FRAM has a FRAM position behind said beam waist.
5. The optical apparatus as claimed in claim 1, wherein said FRAM has a FRAM position at said beam waist.
6. The optical apparatus as claimed in claim 1, wherein said FRAM, having a flexible reflective member, includes a natural FRAM curvature in the absence of an applied actuation voltage defined by a natural curvature of said flexible reflective member.
7. The optical apparatus as claimed in claim 6, wherein said FRAM has a variable FRAM curvature adjusted about said natural FRAM curvature by a range of actuation voltages applied thereon.
8. The optical apparatus as claimed in claim 7, wherein said reflected beam from said FRAM has a variable reflected beam divergence which depends on said variable FRAM curvature thereof, and thus on said range of actuation voltages applied thereon.
9. The optical apparatus as claimed in claim 8, wherein said range of actuation voltages can be determined and applied to each said FRAM individually, each said FRAM thus operating independently.
10. A light intensity modulator comprising:
an optical apparatus for variably modifying a divergence of at least one reflected beam comprising at least one light source generating at least one input beam, at least one Flexible Reflective Analog Modulator (FRAM), said FRAM generally comprising a flexible reflective member attached to a substrate by at least one leg extending outwardly therefrom, an electrode on said substrate and an electrode on said flexible reflective member thus forming a set of electrodes for applying an actuation voltage thereon, said FRAM having a natural FRAM curvature in the absence of an actuation voltage applied thereon defined by a natural curvature of said flexible reflective member, and a variable FRAM curvature adjusted by a range of actuation voltages applied thereon, said optical apparatus further comprising an illumination optics comprising at least one lens, said lens focusing said input beam to produce at least one focused beam, said focused beam comprising a beam waist, said FRAM having a FRAM position either in front of, behind or at said beam waist and a FRAM orientation such that said focused beam is reflected by said flexible reflective member of said FRAM to produce at least one reflected beam therefrom, said reflected beam reflected by said FRAM having a variable reflected beam divergence dependent on the FRAM position and the variable FRAM curvature of said FRAM, and thus on the range of actuation voltages applied thereon;
a conversion optics for converting the variable reflected beam divergence of said reflected beam into a variable reflected beam intensity.
11. The light intensity modulator as claimed in claim 10, wherein said light source comprises a laser.
12. The light intensity modulator as claimed in claim 10, wherein said FRAM has a FRAM position in front of said beam waist.
13. The light intensity modulator as claimed in claim 10, wherein said FRAM has a FRAM position behind said beam waist.
14. The light intensity modulator as claimed in claim 10, wherein said FRAM has a FRAM position at said beam waist.
15. The light intensity modulator as claimed in claim 10, wherein said range of actuation voltages can be determined and applied to each said FRAM individually, each said FRAM thus being an independently operated FRAM.
16. The light intensity modulator as claimed in claim 10, wherein said conversion optics comprises either Cassegrain optics, Schlieren optics, mask arrangements combined with optics, or any combination thereof.
17. The light intensity modulator as claimed in claim 10, comprising an electronic driver performing all FRAM driving functions required for the proper operation of said FRAM.
18. The light intensity modulator as claimed in claim 17, wherein said FRAM driving functions comprise light modulation data processing.
19. The light intensity modulator as claimed in claim 17, wherein said FRAM driving functions comprise digital-to-analog data conversion.
20. The light intensity modulator as claimed in claim 17, wherein said FRAM driving functions comprise actuation voltage amplification.
21. The light intensity modulator as claimed, in claim 17, wherein said FRAM driving functions comprise coarse and fine offset generation.
22. The light intensity modulator as claimed in claim 17, wherein said range of actuation voltages are applied using at least one actuation voltage waveform constructed to minimize the response time of said FRAM.
23. The light intensity modulator as claimed in claim 22, wherein said actuation voltage waveform comprises either an exponentially varying voltage waveform, a decreasing or increasing electrostatic pressure ramp waveform, a two-step function actuation waveform, an accelerated two-step actuation waveform, a filtered step function waveform, or any combination thereof.
24. The light intensity modulator as claimed in claim 22, wherein said FRAM driving functions comprise actuation voltage waveform shaping.
25. The light intensity modulator as claimed in claim 10, comprising a plurality of FRAMs organized in at least one FRAM array, said FRAM array comprising at least two FRAMs.
26. The light intensity modulator as claimed in claim 25, wherein said FRAM array comprises at least one linear FRAM array.
27. The light intensity modulator as claimed in claim 26, wherein said illumination optics is configured to address said linear FRAM array.
28. The light intensity modulator as claimed in claim 27, wherein said illumination optics comprise either a microlens array, a diffraction grating, an optics for generating a focused beam comprising cylindrical wavefronts, or any combination thereof.
29. The light intensity modulator as claimed in claim 27, wherein said range of actuation voltages can be determined and applied to each said FRAM individually, each said FRAM thus being an independently operated FRAM.
30. The light intensity modulator as claimed in claim 29, wherein each linear FRAM array of independently operated FRAMs produces at least one line of variable intensity light dots.
31. An image projector comprising:
an optical apparatus for variably modifying the divergence of at least one reflected beam comprising at least one light source generating at least one input beam, a plurality of independently operated Flexible Reflective Analog Modulators (FRAMs) organized in at least one linear FRAM array, said linear FRAM array comprising at least one FRAM, each said FRAM generally comprising a flexible reflective member attached to a flat substrate by at least one leg extending outwardly therefrom, an electrode on said substrate and an electrode on said flexible reflective member thus forming a set of electrodes for applying an actuation voltage thereon, each said FRAM having a natural FRAM curvature in the absence of an actuation voltage applied thereon defined by a natural curvature of said respective flexible reflective member and a variable FRAM curvature adjusted by a range of actuation voltages applied thereon, said optical apparatus further comprising an illumination optics configured to address said linear FRAM array, said illumination optics focusing said input beam to produce at least one focused beam, said focused beam comprising a beam waist, said FRAM array having a FRAM array position either in front of, behind or at said beam waist and a FRAM array orientation such that said focused beam is reflected by said flexible reflective members of said FRAMs of said FRAM array to produce a plurality of reflected beams therefrom, each said reflected beam reflected by a respective FRAM of said FRAM array having a variable reflected beam divergence dependent on the respective FRAM position and the variable FRAM curvature of said respective FRAM, and thus on the range of actuation voltages applied thereon;
a conversion optics for converting the variable reflected beam divergence of each said reflected beam into a variable reflected beam intensity, said linear FRAM array of independently operated FRAMs thus producing at least one line of variable intensity light dots;
a scanning mechanism coupled to a projection optics, said scanning mechanism scanning through said at least one line of variable intensity light dots in a scanning direction perpendicular thereto, thus projecting, in conjunction with said projection optics, a bidimensional image.
32. The image projector as claimed in claim 31, wherein said light source comprises a laser.
33. The image projector as claimed in claim 31, wherein each said FRAM has a FRAM position in front of said beam waist.
34. The image projector as claimed in claim 31, wherein each said FRAM has a FRAM position behind said beam waist.
35. The image projector as claimed in claim 31, wherein each said FRAM has a FRAM position at said beam waist.
36. The image projector as claimed in claim 31, wherein said illumination optics comprises either a microlens array, a diffraction grating, an optics for generating a focused beam comprising cylindrical wavefronts, or any combination thereof.
37. The image projector as claimed in claim 31, wherein said conversion optics comprises either Cassegrain optics, Schlieren optics, mask arrangements combined with optics, or any combination thereof.
38. The image projector as claimed in claim 31, comprising an electronic driver performing all FRAM driving functions required for the proper operation of said FRAMs.
39. The image projector as claimed in claim 38, wherein said FRAM driving functions comprise light modulation data processing.
40. The image projector as claimed in claim 38, wherein said FRAM driving functions comprise digital-to-analog data conversion.
41. The image projector as claimed in claim 38, wherein said FRAM driving functions comprise actuation voltage amplification.
42. The image projector as claimed in claim 38, wherein said FRAM driving functions comprise coarse and fine offset generation.
43. The image projector as claimed in claim 38, wherein said range of voltages is applied using at least one actuation voltage waveform constructed to minimize the response time of said FRAMs.
44. The image projector as claimed in claim 43, wherein said actuation voltage waveform comprises either an exponentially varying voltage waveform, a decreasing or increasing electrostatic pressure ramp waveform, a two-step function actuation waveform, an accelerated two-step actuation waveform, a filtered step function waveform, or any combination thereof.
45. The image projector as claimed in claim 43, wherein said FRAM driving functions also comprise actuation voltage waveform shaping.
46. The image projector as claimed in claim 31, wherein said at least one light source comprises at least two laser light sources, said laser light sources operating at different wavelengths, each said laser light source illuminating a respective said linear FRAM array, each said respective linear FRAM array generating a respective line of said variable intensity light dots, said lines of variable intensity light dots being combined to form a multicoloured line of variable intensity light dots to be directed toward said scanning mechanism and said projection optics to produce a bidimensional multicolour image.
47. The image projector as claimed in claim 46, wherein said wavelengths represent additive colours.
48. The image projector as claimed in claim 47, wherein said additive colours comprise red, green and blue.
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 method of generating a feature planning granularity metric for use in project planning of a proposed project having characteristics represented by a plurality of project estimation fields having one or more project estimation constraint fields, the method comprising:
receiving via a computer processor a plurality of project estimation constraint metrics corresponding to respective project estimation constraint fields of the proposed project for use in generating a metric indicative of a feature planning granularity characteristic;
obtaining via the computer processor a reference class of project data of a plurality of historical reference projects, the data for each historical reference project comprising:
a metric representing cumulative identified features relative to a planned effort of the scope of the reference project for one or more points of time during the course of the reference project; and
a feature completion progress schedule for completed registered features and a corresponding amount of planned effort contributed by each respective registered feature to the planned effort of the scope of the reference project;
applying via the computer processor the project estimation constraint metrics in reference class forecasting on the reference class of project data, to generate a metric representing estimated cumulative identified features relative to a scope of the proposed project for one or more points of time during the course of the proposed project, wherein the estimated cumulative identified features have a cumulative effort larger than the effort of the scope of the proposed project; and
providing via the computer processor the metric representing estimated cumulative identified features relative to the effort of the scope of the proposed project, for use in project planning as the feature planning granularity characteristic.
2. The method of claim 1 wherein the effort of the scope of the proposed project and the planned effort of the scope of each historical reference project is measured in a baseline unit of full-time-equivalent-person-days.
3. The method of claim 1 wherein the project estimation constraint fields comprise at least one field of the group consisting of project scope, project duration, project cost, project resources, project success rate, and predictive model accuracy.
4. The method of claim 1 wherein the proposed project is a partially completed project.
5. The method of claim 1 wherein applying the project estimation constraint metrics in reference class forecasting comprises applying a logistic model to the reference class of project data to generate a feature identification progress schedule.
6. The method of claim 5 wherein applying the logistic model comprises using a regression technique to obtain parameter determination equations having as independent variables the project estimation constraint fields.
7. A computer implemented method of generating a feature completion progress schedule for use in project estimation of a proposed project having characteristics represented by a plurality of project estimation fields having one or more project estimation constraint fields, the method comprising:
receiving via a computer processor a plurality of project estimation constraint metrics comprising at least a metric indicative of a feature planning granularity characteristic expressed as a number of cumulative identified features relative to an effort of a scope of the proposed project;
obtaining via the computer processor a reference class of project data of a plurality of historical reference projects, the data for each historical reference project comprising:
a metric representing cumulative identified features relative to a planned effort of the scope of the reference project, wherein the cumulative identified features have a cumulative effort larger than the planned effort of the scope of the reference project; and
a feature completion progress schedule for completed registered features and a corresponding amount of planned effort contributed by each respective registered feature to the planned effort of the scope of the reference project;
applying via the computer processor the project estimation constraint metrics in reference class forecasting on the reference class of project data, to generate a feature completion progress schedule for the proposed project; and
providing via the computer processor the feature completion progress schedule for use in project estimation.
8. The method of claim 7 wherein the effort of the scope of the proposed project and the planned effort of the scope of each historical reference project is measured in a baseline unit of full-time-equivalent-person-days.
9. The method of claim 7 wherein the project estimation constraint fields further comprise at least one field of the group consisting of project scope, project duration, project cost, project resources, project success rate, and predictive model accuracy.
10. The method of claim 7 wherein the proposed project is a partially completed project having an original planned effort of scope, and wherein the metric indicative of the feature planning granularity characteristic is the number of cumulative identified features of the partially completed project relative to the original planned effort of scope.
11. The method of claim 7 wherein applying the project estimation constraint metrics in reference class forecasting comprises applying a logistic model using a regression technique to obtain parameter determination equations having as independent variables the project estimation constraint fields.
12. A computer implemented system for generating a feature planning granularity metric for use in project planning of a proposed project having characteristics represented by a plurality of project estimation fields having one or more project estimation constraint fields, the system comprising:
a client input interface operative to receive a plurality of project estimation constraint metrics corresponding to respective project estimation constraint fields of the proposed project for use in generating a metric indicative of a feature planning granularity characteristic;
a data repository operative to obtain a reference class of project data of a plurality of historical reference projects, the data for each historical reference project comprising:
a metric representing cumulative identified features relative to a planned effort of the scope of the reference project for one or more points of time during the course of the reference project; and
a feature completion progress schedule for completed registered features and a corresponding amount of planned effort contributed by each respective registered feature to the planned effort of the scope of the reference project;
a data analyzer in signal communication with the client input interface and the data repository, the data analyzer being operative to apply the project estimation constraint metrics in reference class forecasting on the reference class of project data, to generate a metric representing estimated cumulative identified features relative to a scope of the proposed project for one or more points of time during the course of the proposed project, wherein the estimated cumulative identified features have a cumulative effort larger than the effort of the scope of the proposed project; and
a client output interface in signal communication with the data analyzer and operative to provide the metric representing estimated cumulative identified features relative to the effort of the scope of the proposed project, for use in project planning as the feature planning granularity characteristic.
13. The system of claim 12 wherein the effort of the scope of the proposed project and the planned effort of the scope of each historical reference project is measured in a baseline unit of full-time-equivalent-person-days.
14. The system of claim 12 wherein the project estimation constraint fields comprise at least one field of the group consisting of project scope, project duration, project cost, project resources, project success rate, and predictive model accuracy.
15. The system of claim 12 wherein the proposed project is a partially completed project.
16. The system of claim 12 wherein applying the project estimation constraint metrics in reference class forecasting comprises applying a logistic model to the reference class of project data to generate a feature identification progress schedule.
17. The system of claim 16 wherein applying the logistic model comprises using a regression technique to obtain parameter determination equations having as independent variables the project estimation constraint fields.
18. A computer implemented system for generating a feature completion progress schedule for use in project estimation of a proposed project having characteristics represented by a plurality of project estimation fields having one or more project estimation constraint fields, the system comprising:
a client input interface operative to receive a plurality of project estimation constraint metrics comprising at least a metric indicative of a feature planning granularity characteristic expressed as a number of cumulative identified features relative to an effort of a scope of the proposed project;
a data repository operative to obtain a reference class of project data of a plurality of historical reference projects, the data for each historical reference project comprising:
a metric representing cumulative identified features relative to a planned effort of the scope of the reference project, wherein the cumulative identified features have a cumulative effort larger than the planned effort of the scope of the reference project; and
a feature completion progress schedule for completed registered features and a corresponding amount of planned effort contributed by each respective registered feature to the planned effort of the scope of the reference project;
a data analyzer in signal communication with the client input interface and the data repository, the data analyzer being operative to apply the project estimation constraint metrics in reference class forecasting on the reference class of project data, to generate a feature completion progress schedule for the proposed project; and
a client output interface in signal communication with the data analyzer and operative to provide the feature completion progress schedule for use in project estimation.
19. The system of claim 18 wherein the effort of the scope of the proposed project and the planned effort of the scope of each historical reference project is measured in a baseline unit of full-time-equivalent-person-days.
20. The system of claim 18 wherein the project estimation constraint fields further comprise at least one field of the group consisting of project scope, project duration, project cost, project resources, project success rate, and predictive model accuracy.
21. The system of claim 18 wherein the proposed project is a partially completed project having an original planned effort of scope, and wherein the metric indicative of the feature planning granularity characteristic is the number of cumulative identified features of the partially completed project relative to the original planned effort of scope.
22. The system of claim 18 wherein applying the project estimation constraint metrics in reference class forecasting comprises applying a logistic model using a regression technique to obtain parameter determination equations having as independent variables the project estimation constraint fields.