Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
The amendments filed May 8, 2026 have been entered. Claims 1-20 remain pending in this application. Claims 1, 9, and 17 have been amended.
Response to Arguments
Applicant argues in the correspondence filed May 8, 2026, on pages 9-10, that Grgich fails to teach generating a plurality of subsets of the set of satellite signals, wherein each subset excludes satellite signals from a satellite of the plurality of satellites.
In response, Examiner agrees with this notion and as a result, regarding the respective limitations in claims 1, 9, and 17, new grounds of rejection are made under Grgich in view of Vanderwerf et al. (US 20030117317 A1), citing
Vanderwerf; para. 23, “Step 260 of the present invention is like step 60, except that a plurality of sub-sub-solutions, Δrnm(n=1, 2 . . . N; m=1, 2 . . . N; n≠m) are calculated with each based on a respective sub-subset of the N sub-solutions. As explained above, each sub-sub-group contains the same satellites as each sub-group (N−1) except that it also excludes one other additional satellite.”, and
Vanderwerf; para. 36, “Having determined the solution separation parameters, processor 16 executes step 90 in the '737 patent and determines if a failure has occurred. If a failure occurs, this information is transferred to step 290 as shown by arrow 292. Step 290 involves a determination of which of the satellites is the one that failed.”
Vanderwerf; Fig. 2, where the sub-sub-group forming technique described in step 260 allows for satellite failure isolation and exclusion in step 290.
Applicant argues that Grgich fails to teach performing a remedial action with regards to a satellite of the plurality of satellites associated with the identified satellite signal, with the reasoning that removing outlier observation data does not amount to performing a remedial action with regards to a particular satellite associated with a corrupted satellite signal.
In response, Examiner asserts that Grgich does teach performing a remedial action with regards to a satellite of the plurality of satellites associated with the identified satellite signal, citing
para. 65, “Note that if the method 200 identifies data from one or more sources (e.g., satellites, base stations) as erroneous, the method 200 may include flagging or otherwise providing notification that said sources may be ‘unhealthy’. Further, the method 200 may disregard or weight differently observations from these sources.”,
noting that removing outlier or erroneous observation data associated with a particular satellite amounts to a remedial action with regards to a satellite of a plurality of satellites associated with an identified satellite signal.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 4-6, 8-9, 12-14, 16-17, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Grgich et al. (US 20190187298 A1), hereinafter Grgich, in view of Vanderwerf et al. (US 20030117317 A1), hereinafter Vanderwerf.
Regarding claim 1, Grgich teaches a method, comprising:
receiving a set of satellite signals comprising a satellite signal from each of a plurality of satellites, wherein each satellite signal is captured by a location sensor of a client device (para. 32, “A method 200 for reduced-outlier satellite positioning includes receiving satellite positioning observations S210, generating a first receiver position estimate S220, and generating an outlier-reduced second receiver position estimate S230, as shown in FIG. 3.”; para. 34, “S210 includes receiving satellite positioning observations. S210 functions to receive [at a mobile receiver or at any other computer system] satellite data that can be used to calculate the position of the mobile receiver [potentially along with correction data]. […] Navigation satellite carrier signals received in Step S210 may include GPS signals, GLONASS signals, Galileo signals, SBAS signals and/or any other suitable navigation signal transmitted by a satellite.),
generating a plurality of subsets of the set of satellite signals (para. 57, “Alternatively, in this technique, S230 may include calculating posterior residual variances for a number of set-reduced observations [i.e., different subsets of the whole set of observations] and choosing the reduced set with the lowest variance.”; para. 65, “Note that if the method 200 identifies data from one or more sources [e.g., satellites, base stations] as erroneous, the method 200 may include flagging or otherwise providing notification that said sources may be ‘unhealthy’. Further, the method 200 may disregard or weight differently observations from these sources.”),
computing a sensor location measurement based on each of the plurality of subsets of the set of satellite signals, computing an accuracy score for each of the sensor location measurements based on a corresponding subset of satellite signals, identifying a satellite signal of the set of satellite signals as inaccurate based on the accuracy scores for the sensor location measurements corresponding to subsets of satellite signals that include the identified satellite signal (para. 14, “The systems and methods of the present disclosure are directed to the removal of inaccurate observation data in satellite positioning techniques, in turn increasing accuracy, efficiency, and/or any other metric of positioning performance [e.g., accuracy of corrections data].”; para. 54, “In a second implementation of an invention embodiment, S230 includes generating an outlier-reduced second receiver position estimate using the variance threshold technique described in this section. Note that the term ‘variance threshold technique’ is here coined to refer to exactly the technique described herein [any similarity in name to other techniques is purely coincidental].”; Examiner is construing a variance value to represent an accuracy score of a sensor location measurement), and
responsive to identifying the satellite signal as inaccurate, performing a remedial action with regards to the identified satellite signal (para. 57, “Alternatively, in this technique, S230 may include calculating posterior residual variances for a number of set-reduced observations [i.e., different subsets of the whole set of observations] and choosing the reduced set with the lowest variance.”; para. 65, “Note that if the method 200 identifies data from one or more sources [e.g., satellites, base stations] as erroneous, the method 200 may include flagging or otherwise providing notification that said sources may be ‘unhealthy’. Further, the method 200 may disregard or weight differently observations from these sources.”), but fails to teach
generating a plurality of subsets of the set of satellite signals, wherein each subset excludes satellite signals from a satellite of the plurality of satellites.
However, Vanderwerf teaches
generating a plurality of subsets of the set of satellite signals, wherein each subset excludes satellite signals from a satellite of the plurality of satellites (para. 23, “Step 260 of the present invention is like step 60, except that a plurality of sub-sub-solutions, Δrnm(n=1, 2 . . . N; m=1, 2 . . . N; n≠m) are calculated with each based on a respective sub-subset of the N sub-solutions. As explained above, each sub-sub-group contains the same satellites as each sub-group (N−1) except that it also excludes one other additional satellite.”; para. 36, “Having determined the solution separation parameters, processor 16 executes step 90 in the '737 patent and determines if a failure has occurred. If a failure occurs, this information is transferred to step 290 as shown by arrow 292. Step 290 involves a determination of which of the satellites is the one that failed.”; Fig. 2, where the sub-sub-group forming technique described in step 260 allows for satellite failure isolation and exclusion in step 290).
Grgich and Vanderwerf are considered to be analogous to the claimed invention because they are in the same field of GNSS satellite error detection and correction. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Grgich with the teachings of Vanderwerf with the motivation of being able to effectively isolate an erroneous satellite in order to take a remedial action associated with said satellite.
Regarding claims 4, 12, and 20, Grgich in view of Vanderwerf teaches the method of claim 1, the non-transitory computer-readable storage medium of claim 9, and the computer system of claim 17 respectively, wherein performing the remedial action comprises:
disregarding, for locating the client device, signals from the satellite associated with the identified satellite signal for a time period (Grgich; para. 14, “The systems and methods of the present disclosure are directed to the removal of inaccurate observation data in satellite positioning techniques, in turn increasing accuracy, efficiency, and/or any other metric of positioning performance [e.g., accuracy of corrections data].”; para. 45, “The position estimate of S220 is preferably calculated by any number of prediction and update steps based on the observations received in S210. For example, S210 may include receiving observations at different times, and S220 may include generating a position estimate using all of those observations and a previous position estimate.”; para. 54, “In a second implementation of an invention embodiment, S230 includes generating an outlier-reduced second receiver position estimate using the variance threshold technique described in this section. Note that the term ‘variance threshold technique’ is here coined to refer to exactly the technique described herein [any similarity in name to other techniques is purely coincidental].”).
Regarding claims 5 and 13, Grgich in view of Vanderwerf teaches the method of claim 1 and the non-transitory computer-readable storage medium of claim 9 respectively, further comprising:
determining a location of the client device based on a subset of the plurality of satellite signals that excludes the identified satellite signal (Grgich; para. 14, “The systems and methods of the present disclosure are directed to the removal of inaccurate observation data in satellite positioning techniques, in turn increasing accuracy, efficiency, and/or any other metric of positioning performance [e.g., accuracy of corrections data].”; para. 34, “S210 includes receiving satellite positioning observations. S210 functions to receive [at a mobile receiver or at any other computer system] satellite data that can be used to calculate the position of the mobile receiver [potentially along with correction data].”; para. 54, “In a second implementation of an invention embodiment, S230 includes generating an outlier-reduced second receiver position estimate using the variance threshold technique described in this section. Note that the term ‘variance threshold technique’ is here coined to refer to exactly the technique described herein [any similarity in name to other techniques is purely coincidental].”).
Regarding claims 6 and 14, Grgich in view of Vanderwerf teaches the method of claim 5 and the non-transitory computer-readable storage medium of claim 13 respectively, wherein performing the remedial action comprises:
disregarding, for locating the client device, signals from the satellite associated with the identified satellite signal until the client device is a threshold distance away from the determined location of the client device (Grgich; para. 55, “In the variance threshold technique, the posterior residual, posterior residual covariance, and posterior residual variance are calculated as in the scaled residual technique. However, in this technique, the posterior residual variances are examined directly. If one or more posterior residual variances is outside of a threshold range, this is an indication that outliers may be present in the observation data.”).
Regarding claims 8 and 16, Grgich in view of Vanderwerf teaches the method of claim 1 and the non-transitory computer-readable storage medium of claim 9 respectively, wherein identifying the satellite signal based on the accuracy scores comprises:
identifying a sensor location measurement with an accuracy score indicating that the sensor location measurement is accurate (Grgich; para. 14, “The systems and methods of the present disclosure are directed to the removal of inaccurate observation data in satellite positioning techniques, in turn increasing accuracy, efficiency, and/or any other metric of positioning performance [e.g., accuracy of corrections data].”), and
identifying the satellite signal excluded from the subset of satellite signals corresponding to the identified sensor location measurement (Grgich; para. 47, “While techniques for removing or weighting measurement outliers exist in the prior art (as well as analysis of solution or measurement quality based on residuals), S230 includes specific techniques that may more efficiently mitigate the effect of outliers than existing techniques. For example, while techniques exist for mitigating for a single outlier at a time, the techniques of S230 may lend themselves to identifying and/or mitigating for multiple outliers in parallel.”).
Regarding claim 9, Grgich teaches a non-transitory computer-readable storage medium comprising stored instructions executable by a processor (para. 67, “The instructions are preferably executed by computer-executable components preferably integrated with a system for outlier-reduced processing of satellite position data. The computer-readable medium can be stored on any suitable computer-readable media such as RAMs, ROMs, flash memory, EEPROMs, optical devices [CD or DVD], hard drives, floppy drives, or any suitable device. The computer-executable component is preferably a general or application specific processor, but any suitable dedicated hardware or hardware/firmware combination device can alternatively or additionally execute the instructions.”), the instructions executable to perform operations comprising:
receiving a set of satellite signals comprising a satellite signal from each of a plurality of satellites, wherein each satellite signal is captured by a location sensor of a client device (para. 32, “A method 200 for reduced-outlier satellite positioning includes receiving satellite positioning observations S210, generating a first receiver position estimate S220, and generating an outlier-reduced second receiver position estimate S230, as shown in FIG. 3.”; para. 34, “S210 includes receiving satellite positioning observations. S210 functions to receive [at a mobile receiver or at any other computer system] satellite data that can be used to calculate the position of the mobile receiver [potentially along with correction data]. […] Navigation satellite carrier signals received in Step S210 may include GPS signals, GLONASS signals, Galileo signals, SBAS signals and/or any other suitable navigation signal transmitted by a satellite.),
generating a plurality of subsets of the set of satellite signals (para. 57, “Alternatively, in this technique, S230 may include calculating posterior residual variances for a number of set-reduced observations [i.e., different subsets of the whole set of observations] and choosing the reduced set with the lowest variance.”; para. 65, “Note that if the method 200 identifies data from one or more sources [e.g., satellites, base stations] as erroneous, the method 200 may include flagging or otherwise providing notification that said sources may be ‘unhealthy’. Further, the method 200 may disregard or weight differently observations from these sources.”),
computing a sensor location measurement based on each of the plurality of subsets of the set of satellite signals, computing an accuracy score for each of the sensor location measurements based on a corresponding subset of satellite signals, identifying a satellite signal of the set of satellite signals as inaccurate based on the accuracy scores for the sensor location measurements corresponding to subsets of satellite signals that include the identified satellite signal (para. 14, “The systems and methods of the present disclosure are directed to the removal of inaccurate observation data in satellite positioning techniques, in turn increasing accuracy, efficiency, and/or any other metric of positioning performance [e.g., accuracy of corrections data].”; para. 54, “In a second implementation of an invention embodiment, S230 includes generating an outlier-reduced second receiver position estimate using the variance threshold technique described in this section. Note that the term ‘variance threshold technique’ is here coined to refer to exactly the technique described herein [any similarity in name to other techniques is purely coincidental].”; Examiner is construing a variance value to represent an accuracy score of a sensor location measurement), and
responsive to identifying the satellite signal as inaccurate, performing a remedial action with regards to the identified satellite signal (para. 57, “Alternatively, in this technique, S230 may include calculating posterior residual variances for a number of set-reduced observations [i.e., different subsets of the whole set of observations] and choosing the reduced set with the lowest variance.”; para. 65, “Note that if the method 200 identifies data from one or more sources [e.g., satellites, base stations] as erroneous, the method 200 may include flagging or otherwise providing notification that said sources may be ‘unhealthy’. Further, the method 200 may disregard or weight differently observations from these sources.”), but fails to teach
generating a plurality of subsets of the set of satellite signals, wherein each subset excludes satellite signals from a satellite of the plurality of satellites.
However, Vanderwerf teaches
generating a plurality of subsets of the set of satellite signals, wherein each subset excludes satellite signals from a satellite of the plurality of satellites (para. 23, “Step 260 of the present invention is like step 60, except that a plurality of sub-sub-solutions, Δrnm(n=1, 2 . . . N; m=1, 2 . . . N; n≠m) are calculated with each based on a respective sub-subset of the N sub-solutions. As explained above, each sub-sub-group contains the same satellites as each sub-group (N−1) except that it also excludes one other additional satellite.”; para. 36, “Having determined the solution separation parameters, processor 16 executes step 90 in the '737 patent and determines if a failure has occurred. If a failure occurs, this information is transferred to step 290 as shown by arrow 292. Step 290 involves a determination of which of the satellites is the one that failed.”; Fig. 2, where the sub-sub-group forming technique described in step 260 allows for satellite failure isolation and exclusion in step 290).
Grgich and Vanderwerf are considered to be analogous to the claimed invention because they are in the same field of GNSS satellite error detection and correction. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Grgich with the teachings of Vanderwerf with the motivation of being able to effectively isolate an erroneous satellite in order to take a remedial action associated with said satellite.
Regarding claim 17, Grgich teaches a computer system comprising:
at least one processor, non-transitory computer-readable storage medium comprising stored instructions executable by a processor (para. 67, “The instructions are preferably executed by computer-executable components preferably integrated with a system for outlier-reduced processing of satellite position data. The computer-readable medium can be stored on any suitable computer-readable media such as RAMs, ROMs, flash memory, EEPROMs, optical devices [CD or DVD], hard drives, floppy drives, or any suitable device. The computer-executable component is preferably a general or application specific processor, but any suitable dedicated hardware or hardware/firmware combination device can alternatively or additionally execute the instructions.”), the instructions executable to perform operations comprising:
receiving a set of satellite signals comprising a satellite signal from each of a plurality of satellites, wherein each satellite signal is captured by a location sensor of a client device (para. 32, “A method 200 for reduced-outlier satellite positioning includes receiving satellite positioning observations S210, generating a first receiver position estimate S220, and generating an outlier-reduced second receiver position estimate S230, as shown in FIG. 3.”; para. 34, “S210 includes receiving satellite positioning observations. S210 functions to receive [at a mobile receiver or at any other computer system] satellite data that can be used to calculate the position of the mobile receiver [potentially along with correction data]. […] Navigation satellite carrier signals received in Step S210 may include GPS signals, GLONASS signals, Galileo signals, SBAS signals and/or any other suitable navigation signal transmitted by a satellite.),
generating a plurality of subsets of the set of satellite signals (para. 57, “Alternatively, in this technique, S230 may include calculating posterior residual variances for a number of set-reduced observations [i.e., different subsets of the whole set of observations] and choosing the reduced set with the lowest variance.”; para. 65, “Note that if the method 200 identifies data from one or more sources [e.g., satellites, base stations] as erroneous, the method 200 may include flagging or otherwise providing notification that said sources may be ‘unhealthy’. Further, the method 200 may disregard or weight differently observations from these sources.”),
computing a sensor location measurement based on each of the plurality of subsets of the set of satellite signals, computing an accuracy score for each of the sensor location measurements based on a corresponding subset of satellite signals, identifying a satellite signal of the set of satellite signals as inaccurate based on the accuracy scores for the sensor location measurements corresponding to subsets of satellite signals that include the identified satellite signal (para. 14, “The systems and methods of the present disclosure are directed to the removal of inaccurate observation data in satellite positioning techniques, in turn increasing accuracy, efficiency, and/or any other metric of positioning performance [e.g., accuracy of corrections data].”; para. 54, “In a second implementation of an invention embodiment, S230 includes generating an outlier-reduced second receiver position estimate using the variance threshold technique described in this section. Note that the term ‘variance threshold technique’ is here coined to refer to exactly the technique described herein [any similarity in name to other techniques is purely coincidental].”; Examiner is construing a variance value to represent an accuracy score of a sensor location measurement), and
responsive to identifying the satellite signal as inaccurate, performing a remedial action with regards to the identified satellite signal (para. 57, “Alternatively, in this technique, S230 may include calculating posterior residual variances for a number of set-reduced observations [i.e., different subsets of the whole set of observations] and choosing the reduced set with the lowest variance.”; para. 65, “Note that if the method 200 identifies data from one or more sources [e.g., satellites, base stations] as erroneous, the method 200 may include flagging or otherwise providing notification that said sources may be ‘unhealthy’. Further, the method 200 may disregard or weight differently observations from these sources.”), but fails to teach
generating a plurality of subsets of the set of satellite signals, wherein each subset excludes satellite signals from a satellite of the plurality of satellites.
However, Vanderwerf teaches
generating a plurality of subsets of the set of satellite signals, wherein each subset excludes satellite signals from a satellite of the plurality of satellites (para. 23, “Step 260 of the present invention is like step 60, except that a plurality of sub-sub-solutions, Δrnm(n=1, 2 . . . N; m=1, 2 . . . N; n≠m) are calculated with each based on a respective sub-subset of the N sub-solutions. As explained above, each sub-sub-group contains the same satellites as each sub-group (N−1) except that it also excludes one other additional satellite.”; para. 36, “Having determined the solution separation parameters, processor 16 executes step 90 in the '737 patent and determines if a failure has occurred. If a failure occurs, this information is transferred to step 290 as shown by arrow 292. Step 290 involves a determination of which of the satellites is the one that failed.”; Fig. 2, where the sub-sub-group forming technique described in step 260 allows for satellite failure isolation and exclusion in step 290).
Grgich and Vanderwerf are considered to be analogous to the claimed invention because they are in the same field of GNSS satellite error detection and correction. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Grgich with the teachings of Vanderwerf with the motivation of being able to effectively isolate an erroneous satellite in order to take a remedial action associated with said satellite.
Claims 2, 7, 10, 15, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Grgich in view of Vanderwerf and further in view of Werner et al. (US 20240402279 A1), hereinafter Werner.
Regarding claims 2, 10, and 18, Grgich in view of Vanderwerf teaches the method of claim 1, the non-transitory computer-readable storage medium of claim 9, and the computer system of claim 17 respectively, but fails to teach wherein computing the accuracy scores for the sensor location measurements comprises:
computing an accuracy score for a sensor location measurement based on a corresponding VIO location measurement.
However, Werner teaches
computing an accuracy score for a sensor location measurement based on a corresponding VIO location measurement (para. 265, “Combining GNSS signals with visual inertial odometry [VIO] measurements can enhance the accuracy and robustness of positioning and navigation in certain scenarios, particularly when GNSS signals are degraded or unavailable. This combination is often referred to as sensor fusion or sensor integration.”; para. 271, “ A fusion algorithm can assign weights or confidences to the GNSS and VIO measurements based on their reliability and accuracy. The weights can be dynamically adjusted based on the quality of the signals, the presence of signal obstructions, or the accuracy of the VIO system.”).
Grgich, Vanderwerf, and Werner are considered to be analogous to the claimed invention because they are in the same field of geospatial positioning. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Grgich in view of Vanderwerf with the teachings of Werner with the motivation of increasing positioning accuracy.
Regarding claims 7 and 15, Grgich in view of Vanderwerf teaches the method of claim 1 and the non-transitory computer-readable storage medium of claim 9 respectively, but fails to teach wherein performing the remedial action comprises:
capturing VIO data by the client device for locating the client device.
However, Werner teaches
capturing VIO data by the client device for locating the client device (para. 82, “By combining the visual information from the camera with the inertial measurements from the IMU, VIO can provide robust and accurate estimates of the camera and thus mobile device's motion, even in challenging conditions where only one sensor may not be sufficient. The integration of visual and inertial data enhances the system's ability to track objects, estimate their trajectory, and navigate in complex environments.”).
Grgich, Vanderwerf, and Werner are considered to be analogous to the claimed invention because they are in the same field of geospatial positioning. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Grgich in view of Vanderwerf with the teachings of Werner with the motivation of increasing positioning accuracy.
Claims 3, 11, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Grgich in view of Vanderwerf and further in view of Ledvina et al. (US 20250164648 A1), hereinafter Ledvina.
Regarding claims 3, 11, and 19, Grgich in view of Vanderwerf teaches the method of claim 1, the non-transitory computer-readable storage medium of claim 9, and the computer system of claim 17 respectively, but fails to teach wherein computing the accuracy scores for the sensor location measurements comprises:
applying a machine-learning model to the subset of satellite signals corresponding to a sensor location measurement,
wherein the machine-learning model is trained based on historical data to generate an accuracy score for a set of satellite signals based on the satellite signals.
However, Ledvina teaches
applying a machine-learning model to the subset of satellite signals corresponding to a sensor location measurement (para. 16, “The machine learning model is trained based on comparisons between the GNSS position estimates and reference positioning system estimates at respective times, together with parameter(s) indicating a position of the device relative to one or more GNSS satellites of the GNSS positioning system at the respective times that the measurements were captured.”),
wherein the machine-learning model is trained based on historical data to generate an accuracy score for a set of satellite signals based on the satellite signals (para. 37, “Another class of interactions may be the download of machine learning model(s), for specific areas. For example, these machine learning model(s) may be downloaded after the position of the electronic device 102 has been determined at a coarse level [e.g., a predefined level of accuracy].”; para. 53, “Residual error computation(s) 406 may be determined by comparing the GNSS receiver computations 402 with the reference device computations 404 [e.g., as provided by the reference device]. Moreover, these location errors may be stored as part of the training/testing data [e.g., within a database] that is used to generate the machine learning model 412 as discussed below with respect to FIG. 4B.”).
Grgich, Vanderwerf, and Ledvina are considered to be analogous to the claimed invention because they are in the same field of geospatial positioning. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Grgich in view of Vanderwerf with the teachings of Ledvina with the motivation of iteratively increasing positioning accuracy.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ERIC K HODAC whose telephone number is (571) 270-0123. The examiner can normally be reached M-Th 8-6.
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/ERIC K HODAC/Examiner, Art Unit 3648
/OLUMIDE AJIBADE AKONAI/Primary Examiner, Art Unit 3648
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