DETAILED ACTION
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 .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Examiner's Note.
Examiner has cited particular paragraphs and/or columns and line numbers and/or figures in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant, in preparing the responses, to fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner.
The Examiner notes that it has been held that a recitation that a structural element is "adapted to", “configured to”, “capable of”, “arranged to”, “intended to”, "so as" or “operable to” perform a function does not limit the claim to a particular structure and thus only requires the ability to so perform the function. (See In re Hutchison, 69 USPQ 138. See also, MPEP 2111.04) As such, under the broadest reasonable interpretation of the claims and the prior art, the recitations of "adapted to", “configured to”, “capable of”, “arranged to”, “intended to”, "so as" or “operable to” will be deemed met by an element in the prior art capable of performing the function recited in connection with "adapted to", “configured to”, “capable of”, “arranged to”, “intended to”, "so as" or “operable to”.
The Examiner has cited particular paragraphs or columns and line numbers in the references applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings of the art and are applied to specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested of the applicant in preparing responses, to fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner. SEE MPEP 2141.02 [R-07.2015] VI. PRIOR ART MUST BE CONSIDERED IN ITS ENTIRETY, INCLUDING DISCLOSURES THAT TEACH AWAY FROM THE CLAIMS: A prior art reference must be considered in its entirety, i.e., as a whole, including portions that would lead away from the claimed invention. W.L. Gore & Associates, Inc. v. Garlock, Inc., 721 F.2d 1540, 220 USPQ 303 (Fed. Cir. 1983), cert, denied, 469 U.S. 851 (1984). See also MPEP §2123.
Specification objections
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Claim Objections
Claim 25 is objected to because of the following informalities: The term “to be” is not a positive limitation inasmuch as the term is in future tense and implies a change in condition in the future. This does not serve to limit the structure in the present tense. Appropriate correction is required.
Claim 14 is objected to because of the following informalities: typographical error (according to claim 1[[1]]3). Appropriate correction is required.
Reference of prior art
Carvalho et al. (US 20200309810, NEURAL NETWORK SYSTEM WHOSE TRAINING IS BASED ON A COMBINATION OF MODEL AND FLIGHT INFORMATION FOR ESTIMATION OF AIRCRAFT AIR DATA).
Higgins et al. (US 20180348250, FLIGHT PARAMETER PREDICTION USING NEURAL NETWORKS).
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 2, 5, 6, 8-12 and 17-19 are rejected under 35 U.S.C. 102 (a)(1), (a)(2) as being anticipated by Carvalho.
Re claim 1 Referring to the figures and the Detailed Description, Carvalho discloses:
An aircraft (100) comprising: an air data estimator (¶ 0004, figs. 1-3) comprising a machine learning model having been trained to predict air data parameter values from input values (¶ 0004, 0052, figs. 1-3); the air data estimator (106) operable in real time on input values, where the input values are sensor data only from sensors internal to the aircraft (100) or data derived from such sensor data (¶ 0022, 0055, figs. 1-3).
Re claim 2 Referring to the figures and the Detailed Description, Carvalho discloses:
The aircraft (100) according to claim 1, comprising a flight control system and wherein the input values comprise values from the flight control system comprising control surface position (¶ 0044, and Bank Angle (Phi) inherently caused by control surface ¶ 0073).
static pressure values (¶ 0013).
Re claim 5 Referring to the figures and the Detailed Description, Carvalho discloses:
The aircraft (100) according to claim[[s]] 1, comprising a digital engine control unit (108) and wherein the input values comprise engine data from the digital engine control unit (108) (¶ 0062, Full Authority Digital Engine Control (FADEC).
Re claim 6 Referring to the figures and the Detailed Description, Carvalho discloses:
The aircraft (100) according to claim[[s]] 1, comprising a vehicle management system (110), and wherein the input values comprise mass and/or centre of gravity of the aircraft (100) determined by the vehicle management system (¶ 0057, 0071).
Re claim 8 Referring to the figures and the Detailed Description, Carvalho discloses:
The aircraft (100) according to claim[[s]] 1, comprising a navigation sub system and inertial measurement unit, which provides attitude data of the aircraft (100) within the input values (¶ 0020, 0059, 0060, … Global Positioning System and an Inertial Navigation System).
Re claim 9 Referring to the figures and the Detailed Description, Carvalho, as modified above, discloses: The aircraft (100) according to claim 8, wherein the navigation sub system and inertial measurement unit provides manoeuvre rates within the input values (¶ 0059-0061).
Re claim 10 Referring to the figures and the Detailed Description, Carvalho discloses: The aircraft (100) according to claim 9, wherein the navigation sub system and inertial measurement unit provides acceleration of the aircraft (100) within the input values (¶ 0059-0061).
Re claim 11 Referring to the figures and the Detailed Description, Carvalho discloses:: The aircraft (100) according to claim[[s]]_1 wherein the air data parameter values comprise any one or more of: angle of attack, sideslip, dynamic pressure, static pressure (¶ 0013).
Re claim 12 Referring to the figures and the Detailed Description, Carvalho discloses:: The aircraft (100) according to claim 1 wherein the air data parameter values comprise static pressure and dynamic pressure and wherein the aircraft comprises an output parameter calculator configured to compute altitude of the aircraft (100) and airspeed of the aircraft (100) from the static pressure and dynamic pressure parameter values predicted by the air data estimator (¶ 0013, 0060, 0067).
Re claim 17 Referring to the figures and the Detailed Description, Carvalho discloses: A method performed in an aircraft (100), the method comprising: using an air data estimator (106) comprising a machine learning model to predict air data parameter values from input values in real time; where the input values are sensor data only from sensors internal to the aircraft (100) or data derived from such sensor data.
(Claim 17 is similar in scope to Claim 1; therefore, Claim 17 is rejected under the same rationale as Claim 1).
Re claim 18 Referring to the figures and the Detailed Description, Carvalho discloses: The method according to claim 17 wherein the input values comprise: engine data (¶ 0062), control surface position (¶ 0044, and Bank Angle (Phi) inherently caused by control surface ¶ 0073), static pressure (¶ 0013), mass (¶ 0057), centre of gravity (¶ 0071), attitudes (¶ 0063), manoeuvre rates (¶ 0059-0061)., accelerations (¶ 0059-0061)..
Re claim 19 Referring to the figures and the Detailed Description, Carvalho discloses: The method according to claim 18 comprising concatenating the input values into a vector and inputting the vector to the machine learning model (¶ 0061).
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.
Claim(s) 13-16, 20, 21, 24 and 25 is/are rejected under 35 U.S.C. 103 as being unpatentable over Carvalho and further in view of Higgins.
Re claim 13 Referring to the figures and the Detailed Description, Carvalho discloses: The aircraft (100) according to any preceding claim 1 wherein the machine learning model is a neural network comprising an input layer (¶ 0032),
However Carvalho fails to teach as disclosed by Higgins: an output layer and a maximum of two internal layers (¶ 0017, 0028).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to add the Higgins teachings of an output layer and a maximum of two internal layers into the Carvalho, to obtain the best performance of the neural network.
Re claim 14 Referring to the figures and the Detailed Description, Carvalho, as modified above, discloses: The aircraft (100) according to claim 1[[1]]3 wherein the neural network is a feed forward neural network without recurrence (Higgins ¶ 0017).
Re claim 15 Referring to the figures and the Detailed Description, Carvalho, as modified above, discloses: The aircraft (100) according to any of claim[[s]] 14 wherein the neural network is implemented using hardware circuitry comprising a graphics processing unit or parallel processing device (Higgins ¶ 0045).
Re claim 16 Referring to the figures and the Detailed Description, Carvalho, as modified above, discloses: The aircraft (100) of claim 1 wherein the machine learning model has been trained using labelled training data computed by randomly selecting values from a flight envelope of the aircraft and using the selected values to simulate the input values (Higgins ¶ 0045).
Re claim 20 Referring to the figures and the Detailed Description, Carvalho fails to teach as disclosed by Higgins: The method according to 19 comprising normalizing the vector before inputting the vector to the machine learning model (¶ 0032).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to add the Higgins teachings of normalizing the vector before inputting the vector to the machine learning model into the Carvalho, to adjust values measured on different scales to a common scale.
Re claim 21 Referring to the figures and the Detailed Description, Carvalho, as modified above, discloses: The method according to claim[[s]] 20 comprising unnormalizing output values output from the machine learning model (Carvalho 0032, Higgins ¶ 0017).
Re claim 24 Referring to the figures and the Detailed Description, Carvalho, as modified above, discloses: A computer-implemented method of training an air data estimator to predict values of air data parameters of an aircraft (100), the method comprising: using supervised training to train a neural network in the air data estimator, the supervised training using training data pairs, each training data pair comprising ground truth values of the air data parameters selected from a flight envelope of the aircraft (100), and corresponding simulated values from avionics in the aircraft (100), the simulated values computed using stored empirical data about engines of the aircraft and empirical data about the aircraft (100) obtained from wind tunnel testing, and rules of computational fluid dynamics.
(Claim 24 is similar in scope to Claims 1 and 17 and their dependent claims; therefore, Claim 24 is rejected under the same rationale as Claims 1 and 17 and their dependent claims).
Re claim 25 Referring to the figures and the Detailed Description, Carvalho, as modified above, discloses: The computer-implemented method of claim 24 wherein the neural network comprises a plurality of neural networks one for each parameter to be predicted (Higgins ¶0028, … various neural networks to be used as one for each parameter to be predicted).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MEDHAT BADAWI whose telephone number is (571)270-5983. The examiner can normally be reached on Mon-Fri during office hours. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, JOSHUA MICHENER can be reached on 571-272-1467. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MEDHAT BADAWI/Primary Examiner, Art Unit 3642
