DETAILED ACTION
This Office Action is sent in response to Applicant’s Communication received 5/17/2024 for application number 18/667,151.
Claims 1-20 are pending.
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 .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Independent claim 1 (representative of independent claim 11) recites:
A method, comprising: collecting data associated with an evolutionary diffusion process; aggregating steps of the evolutionary diffusion process to define windows that each include a respective set of steps; using the steps in the windows to create a model that models changes between intermediate steps of the evolutionary diffusion process, and a final step of the evolutionary diffusion process; using the model to synthesize data samples associated with the intermediate steps; and using the synthesized data samples to train the model.
(2A, prong 1) The underlined portions of the claim recite an abstract idea, specifically a mental process and mathematical calculations. A human can observe and write down data associated with an evolutionary diffusion process (i.e. observe over time a natural degradation process) and then mentally divide the data into windows and steps. For creating the model of the diffusion process, synthesizing data samples, and training the mode, the broadest reasonable interpretation of these limitations are mathematical calculations because the specification states these steps are performed using a series of mathematical calculations (see paragraphs 93-103 and 112-121).
(2A, prong 2) This judicial exception is not integrated into a practical application. The claims recite the additional elements of (a) generic computer hardware (the computer-readable medium in claim 11). Element (a) is a mere instruction to apply the exception because this element only adds generic computer hardware after-the-fact to the abstract idea. Even when all of the additional elements are considered in ordered combination with the recited abstract idea, the claim as a whole does not integrate the abstract idea into a practical application because the claim as a whole only adds mere instructions to apply the exception to the mental process and mathematical calculations.
(2B) The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Element (a) is a mere instruction to apply the exception as explained above. Even when all of the additional elements are considered in ordered combination with the recited abstract idea, the claim as a whole does not amount to significantly more than the abstract idea itself because the claim as a whole only adds mere instructions to apply the exception to the mental process and mathematical calculations.
For dependent claims 2-4 and 12-14, these claims add to the mental process: humans can observe progressively degrading natural processes and create real observation data.
For dependent claims 5-7 and 15-17, these claims add to the mathematical calculations: these claims further limit the mathematical models in the claim.
For dependent claims 8-10 and 18-20, these claims add to the mental process: humans can determine a window size schedule with constant size and make a judgment balancing the smoothness of window transition with minimizing a number of steps.
Claim Rejections - 35 USC § 102
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 (i.e., changing from AIA to pre-AIA ) 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.
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.
Claim(s) 1-9 and 11-19 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Zhang et al., An Interpretable Latent Denoising Diffusion Probabilistic Model for Fault Diagnosis Under Limited Data (NPL [U], see Notice of References Cited).
In reference to claim 1, Zhang discloses a method, comprising: collecting data associated with an evolutionary diffusion process (real-world mechanical data is collected associated with degrading mechanical components, pages 10358-59); aggregating steps of the evolutionary diffusion process to define windows that each include a respective set of steps (divided according to variance schedule, pages 10355-57); using the steps in the windows to create a model that models changes between intermediate steps of the evolutionary diffusion process, and a final step of the evolutionary diffusion process (model is trained on the real data, pages 10356-59 and Algorithm 1); using the model to synthesize data samples associated with the intermediate steps; and using the synthesized data samples to train the model (further training performed by sampling and generating synthesized data, pages 10356-59 and Algorithm 1).
In reference to claim 2, Zhang discloses the method as recited in claim 1, wherein the evolutionary diffusion process comprises a process in which the data progressively degrades, or improves, at each of the steps of the evolutionary diffusion process (mechanical parts progressively degrade, pages 10358-59).
In reference to claim 3, Zhang discloses the method as recited in claim 1, wherein the data comprises real, rather than synthesized, data (real mechanical data, pages 10358-59).
In reference to claim 4, Zhang discloses the method as recited in claim 1, wherein degradations in the data occur as a natural part of the evolutionary diffusion process, and the degradations are not synthesized (real mechanical data, pages 10358-59).
In reference to claim 5, Zhang discloses the method as recited in claim 1, wherein the model comprises a diffusion model operable to increase, and decrease, degradation of input data provided to the model (forward and reverse diffusion, see fig. 1 and pages 10355).
In reference to claim 6, Zhang discloses the method as recited in claim 1, wherein the model is also trained using one or more features, and outputs of one or more data models (model also trained with features and outputs of variational autoencoder, pages 10356-59 and Algorithm 1).
In reference to claim 7, Zhang discloses the method as recited in claim 6, wherein the one or more data models comprise a parametric data model, and/or a non-parametric data model (parametric, pages 10356-59 and Algorithm 1).
In reference to claim 8, Zhang discloses the method as recited in claim 1, wherein a schedule is used to determine respective sizes of the windows (divided according to variance schedule, pages 10355-57).
In reference to claim 9, Zhang discloses the method as recited in claim 8, where the schedule comprises one of: a constant window schedule; or a window decay schedule that comprises either an exponential window decay schedule or a linear window decay schedule (constant, page 10356, or linear, page 10360).
In reference to claim 11, this claim is directed to a non-transitory computer-readable medium associated with the method claimed in claim 1 and is therefore rejected under a similar rationale.
In reference to claim 12, this claim is directed to a non-transitory computer-readable medium associated with the method claimed in claim 2 and is therefore rejected under a similar rationale.
In reference to claim 13, this claim is directed to a non-transitory computer-readable medium associated with the method claimed in claim 3 and is therefore rejected under a similar rationale.
In reference to claim 14, this claim is directed to a non-transitory computer-readable medium associated with the method claimed in claim 4 and is therefore rejected under a similar rationale.
In reference to claim 15, this claim is directed to a non-transitory computer-readable medium associated with the method claimed in claim 5 and is therefore rejected under a similar rationale.
In reference to claim 16, this claim is directed to a non-transitory computer-readable medium associated with the method claimed in claim 6 and is therefore rejected under a similar rationale.
In reference to claim 17, this claim is directed to a non-transitory computer-readable medium associated with the method claimed in claim 7 and is therefore rejected under a similar rationale.
In reference to claim 18, this claim is directed to a non-transitory computer-readable medium associated with the method claimed in claim 8 and is therefore rejected under a similar rationale.
In reference to claim 19, this claim is directed to a non-transitory computer-readable medium associated with the method claimed in claim 9 and is therefore rejected under a similar rationale.
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 10 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al., An Interpretable Latent Denoising Diffusion Probabilistic Model for Fault Diagnosis Under Limited Data (NPL [U], see Notice of References Cited) as applied to claims 1 and 11 above, and in further view of Wang et al., Learning to Schedule in Diffusion Probabilistic Models (NPL [V], see Notice of References Cited).
In reference to claim 10, Zhang does not explicitly teach the method as recited in claim 1, wherein sizes of the windows are based on a balancing of a relative smoothness between window transitions, and keeping a number of initial steps of the evolutionary diffusion process as low as possible.
Wang teaches the method as recited in claim 1, wherein sizes of the windows are based on a balancing of a relative smoothness between window transitions, and keeping a number of initial steps of the evolutionary diffusion process as low as possible (see pages 2480-83: window size is learned to balance minimizing number of steps versus smoothness, i.e. quality from full sequence).
It would have been obvious to one of ordinary skill in art, having the teachings of Zhang and Wang before the earliest effective filing date, to modify the fixed schedule of Zhang to include the learned schedule of Wang.
One of ordinary skill in the art would have been motivated to modify the schedule of Zhang to include the learned schedule of Wang because it improves performance of the diffusion network (Wang, page 2486).
In reference to claim 20, this claim is directed to a non-transitory computer-readable medium associated with the method claimed in claim 10 and is therefore rejected under a similar rationale.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. NPLs [W] and [X], teach diffusion models with quantum states.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Andrew T. Chiusano whose telephone number is (571)272-5231. The examiner can normally be reached M-F, 10am-6pm.
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/ANDREW T CHIUSANO/ Primary Examiner, Art Unit 2144
