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 .
Claim Objections
Claim 6 is objected to because of the following informalities:
Regarding claim 6, Applicant is advised to spell out “loess”.
Appropriate correction is required.
Allowable Subject Matter
Claims 3 and 4 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
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.
(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, 16, 19, 20 are rejected under 35 U.S.C. 102 (a) (1) as being anticipated by ALBADAWI et al. US 2018/0132731 (hereinafter ALBADAWI).
Regarding claim 1, ALBADAWI teaches: a computer-implemented method of creating a model configured to predict behavior of a real-world system, the method comprising, by a processor:
receiving, in memory, input and output data for the real-world system (Fig. 1B, [0051] - - receive a set of measurements);
subdividing the input and output data received into a plurality of subsets in accordance with a criterion (Fig. 1B, [0052] - - 3 subsets; [0032] - - divide the dataset into three subsets);
for each subset of the plurality, fitting a regression model to data of the subset (Fig. 1B, [0052] - - “determine a first regression representation using a first subset from the set of measurements, a second regression representation using a second subset from the set of measurements, and a third regression representation using a third subset from the set of measurements”);
for each data point in each subset of the plurality of subsets, assigning a respective weight to the data point for each regression model ([0041] - - each regression model or representation may be assigned a weight); and
generating the model configured to predict the behavior of the real-world system by calculating a weighted average of each regression model using the assigned respective weights ([0041] - - “blood pressure determination component 110 may be configured to determine a weighted average of the first blood pressure indication 154, the second blood pressure indication 160, and the third blood pressure indication 164”).
Claim 19 is substantially similar to claim 1 and is rejected for the same reasons and rationale as above.
Claim 20 is substantially similar to claim 1 and is rejected for the same reasons and rationale as above.
Regarding claim 16, ALBADAWI teaches all the limitations of the base claims as outlined above.
ALBADAWI further teaches: the real-world system comprises at least one of a manufacturing system, a chemical system, a modeling system, an engineering system, a logistical system, a power system, or any combination thereof ([0005] - - human blood pressure is a chemical system).
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.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over ALBADAWI et al. US 2018/0132731 (hereinafter ALBADAWI) in view of Faddoul et al. US 2013/0282627 (hereinafter Faddoul).
Regarding claim 2, ALBADAWI teaches all the limitations of the base claims as outlined above.
But ALBADAWI does not explicitly teach:
iteratively subdividing the input and output data to form a tree, wherein each subset of the plurality of subsets is a leaf of the tree.
However, Faddoul teaches:
iteratively subdividing the input and output data to form a tree, wherein each subset of the plurality of subsets is a leaf of the tree (Fig. 2 [0007], [0030] - - iteratively splitting data, leaf of the DT (decision tree)).
ALBADAWI and Faddoul are analogous art because they are from the same field of endeavor. They all relate to models.
Therefore before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by ALBADAWI, and incorporating iteratively splitting data, as taught by Faddoul.
One of ordinary skill in the art would have been motivated to do this modification in order to improve model prediction accuracy, as suggested by Faddoul ([0046]).
Claims 5 are rejected under 35 U.S.C. 103 as being unpatentable over ALBADAWI et al. US 2018/0132731 (hereinafter ALBADAWI) in view of Prasad Datta et al. US 2020/0257896 (hereinafter PASZEK).
Regarding claim 5, ALBADAWI teaches all the limitations of the base claims as outlined above.
But ALBADAWI does not explicitly teach:
the criterion is a mean-squared error.
However, PASZEK teaches:
the criterion is a mean-squared error ([0031] - - data are grouped based on the mean square error).
ALBADAWI and PASZEK are analogous art because they are from the same field of endeavor. They all relate to predicting.
Therefore before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by ALBADAWI, and incorporating grouping data based on mean square error, as taught by PASZEK.
One of ordinary skill in the art would have been motivated to do this modification in order to improve data analysis, as suggested by PASZEK ([0031]).
Claims 6 are rejected under 35 U.S.C. 103 as being unpatentable over ALBADAWI et al. US 2018/0132731 (hereinafter ALBADAWI) in view of Prasad Datta et al. US 2019/0244287 (hereinafter Datta).
Regarding claim 6, ALBADAWI teaches all the limitations of the base claims as outlined above.
But ALBADAWI does not explicitly teach:
each weight is assigned based on a weighting scheme inherited from loess regression.
However, Datta teaches:
each weight is assigned based on a weighting scheme inherited from loess regression ([0026] - - LOESS model is a locally weighted polynomial regression).
ALBADAWI and Datta are analogous art because they are from the same field of endeavor. They all relate to models.
Therefore before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by ALBADAWI, and incorporating LOESS, as taught by Datta.
One of ordinary skill in the art would have been motivated to do this modification in order to improve modeling, as suggested by Datta ([0026]).
Claims 7 are rejected under 35 U.S.C. 103 as being unpatentable over ALBADAWI et al. US 2018/0132731 (hereinafter ALBADAWI) in view of Johannesson et al. US 2019/0244287 (hereinafter Johannesson).
Regarding claim 7, ALBADAWI teaches all the limitations of the base claims as outlined above.
But ALBADAWI does not explicitly teach:
a given regression model is a cross-validated linear regression model..
However, Johannesson teaches:
a given regression model is a cross-validated linear regression model. ([0123] - - a cross-validated linear regression model).
ALBADAWI and Johannesson are analogous art because they are from the same field of endeavor. They all relate to models.
Therefore before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by ALBADAWI, and incorporating a cross-validated linear regression model, as taught by Johannesson.
One of ordinary skill in the art would have been motivated to do this modification in order to improve a predictive model, as suggested by Johannesson (Abstract).
Claims 8 – 12, 15, 17, 18 are rejected under 35 U.S.C. 103 as being unpatentable over ALBADAWI et al. US 2018/0132731 (hereinafter ALBADAWI) in view of Andreu et al. US 2022/0035353 (hereinafter Andreu).
Regarding claim 8, ALBADAWI teaches all the limitations of the base claims as outlined above.
But ALBADAWI does not explicitly teach:
receiving an indication of one or more constraints; and modifying the generated model to predict the behavior of the real-world system in accordance with the one or more constraints received.
However, Andreu teaches:
receiving an indication of one or more constraints (Fig. 2, [0061] - - receives linear constraint equations); and
modifying the generated model to predict the behavior of the real-world system in accordance with the one or more constraints received (Fig. 2, [0062] - - modify the coefficient matrix using the constraints to generate constrained coefficients 210).
ALBADAWI and Andreu are analogous art because they are from the same field of endeavor. They all relate to models.
Therefore before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by ALBADAWI, and incorporating constraints, as taught by Andreu.
One of ordinary skill in the art would have been motivated to do this modification in order to improve process control models result, as suggested by Andreu (Abstract).
Regarding claim 9, ALBADAWI teaches all the limitations of the base claims as outlined above.
But ALBADAWI does not explicitly teach:
receiving an indication of a hyper-parameter; and
wherein, in generating the model, the model is generated in accordance with the hyper-parameter.
However, Andreu teaches:
receiving an indication of a hyper-parameter (Fig. 2, [0061] - - receives linear constraint equations; constraints are hyper-parameters); and
wherein, in generating the model, the model is generated in accordance with the hyper-parameter (Abstract - - the model is consistent with incorporated constraints thus the model is generated in accordance with the constraints).
ALBADAWI and Andreu are analogous art because they are from the same field of endeavor. They all relate to models.
Therefore before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by ALBADAWI, and incorporating constraints, as taught by Andreu.
One of ordinary skill in the art would have been motivated to do this modification in order to improve process control models result, as suggested by Andreu (Abstract).
Regarding claim 10, ALBADAWI teaches all the limitations of the base claims as outlined above.
But ALBADAWI does not explicitly teach:
deploying the model to control operation of the real-world system.
However, Andreu teaches:
deploying the model to control operation of the real-world system ([0003] - - regression models are used in process control).
ALBADAWI and Andreu are analogous art because they are from the same field of endeavor. They all relate to models.
Therefore before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by ALBADAWI, and incorporating deploying the model, as taught by Andreu.
One of ordinary skill in the art would have been motivated to do this modification in order to predict process behavior using the model, as suggested by Andreu ([0003]).
Regarding claim 11, the combination of ALBADAWI and Andreu teaches all the limitations of the base claims as outlined above.
Andreu further teaches:
receiving, in the memory, an indication of a parameter of the real-world system; predicting real-time behavior of the real-world system by processing the received indication of the parameter using the model; and
controlling operation of the real-world system based on the predicted real-time behavior ([0003] - - predictions from regression models are used in process control).
ALBADAWI and Andreu are combinable for the same rationale as set forth.
Regarding claim 12, ALBADAWI teaches all the limitations of the base claims as outlined above.
But ALBADAWI does not explicitly teach:
integrating the model in a control loop, wherein the control loop (i) processes candidate operating characteristics of the real-world system using the model to determine predicted behavior change in the real-world system and (ii) responsively sets one or more operating characteristics in the real-world system based on the predicted behavior change.
However, Andreu teaches:
integrating the model in a control loop, wherein the control loop (i) processes candidate operating characteristics of the real-world system using the model to determine predicted behavior change in the real-world system and (ii) responsively sets one or more operating characteristics in the real-world system based on the predicted behavior change ([0003] - - regression models are used in process control; [0031] - - employ model process control to configure settings).
ALBADAWI and Andreu are analogous art because they are from the same field of endeavor. They all relate to models.
Therefore before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by ALBADAWI, and incorporating integrating the model in a control loop, as taught by Andreu.
One of ordinary skill in the art would have been motivated to do this modification in order to improve process control, as suggested by Andreu ([0003]).
Regarding claim 15, ALBADAWI teaches all the limitations of the base claims as outlined above.
But ALBADAWI does not explicitly teach:
deploying the model as a block in a process simulation.
However, Andreu teaches:
deploying the model as a block in a process simulation ([0033] - - models are used for process simulation).
ALBADAWI and Andreu are analogous art because they are from the same field of endeavor. They all relate to models.
Therefore before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by ALBADAWI, and incorporating models used for simulation, as taught by Andreu.
One of ordinary skill in the art would have been motivated to do this modification in order to improve process control, as suggested by Andreu ([0003]).
Regarding claim 17, ALBADAWI teaches all the limitations of the base claims as outlined above.
But ALBADAWI does not explicitly teach:
receiving, in the memory, an indication of a parameter of the real-world system; and
processing the received indication of the parameter of the real-world system using the model to estimate a property of the real-world system.
However, Andreu teaches:
receiving, in the memory, an indication of a parameter of the real-world system; and
processing the received indication of the parameter of the real-world system using the model to estimate a property of the real-world system ([0003] - - regression models are used in process control; [0035] - - “By using models 110 to predict the output of potential designs with hypothetical settings 132, process modeling system 130 can identify what proposed configuration of plant 120 is best suited to a user's needs.”).
ALBADAWI and Andreu are analogous art because they are from the same field of endeavor. They all relate to models.
Therefore before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by ALBADAWI, and incorporating using the model to estimate real world output, as taught by Andreu.
One of ordinary skill in the art would have been motivated to do this modification in order to improve process control, as suggested by Andreu ([0003]).
Regarding claim 18, the combination of ALBADAWI and Andreu teaches all the limitations of the base claims as outlined above.
Andreu further teaches:
the estimated property is at least one of: quality of a product produced by the real-world system; composition of effluent produced by the real-world system; composition of by-product produced by the real-world system; yield of a product produced by the real-world system; yield of a by-product produced by the real-world system; operational health of the real-world system; and energy consumption of the real-world system. ([0038] - - one could predict the mass of each element and estimate what fraction of mass in the particle corresponds to that atom, this is composition).
ALBADAWI and Andreu are combinable for the same rationale as set forth.
Claims 13, 14 are rejected under 35 U.S.C. 103 as being unpatentable over ALBADAWI et al. US 2018/0132731 (hereinafter ALBADAWI) in view of Lam et al. US 2014/0365180 (hereinafter Lam).
Regarding claim 13, ALBADAWI teaches all the limitations of the base claims as outlined above.
But ALBADAWI does not explicitly teach:
deploying the model as a surrogate model to determine optimized operations of the real-world system.
However, Lam teaches:
deploying the model as a surrogate model to determine optimized operations of the real-world system ([0041] - - “The surrogate model is refit to the augmented data, and the steps of optimization, model simulation and surrogate model rebuilding are iterated until one of several stopping criteria is met.”).
ALBADAWI and Lam are analogous art because they are from the same field of endeavor. They all relate to models.
Therefore before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by ALBADAWI, and incorporating a surrogate model, as taught by Lam.
One of ordinary skill in the art would have been motivated to do this modification in order to choose the optimal combination, as suggested by Lam ([0003]).
Regarding claim 14, the combination of ALBADAWI and Lam teaches all the limitations of the base claims as outlined above.
Lam further teaches:
iteratively testing candidate operations of the real-world system using the surrogate model until a behavior predicted by the model for given candidate operations meets one or more criteria ([0041] - - “The surrogate model is refit to the augmented data, and the steps of optimization, model simulation and surrogate model rebuilding are iterated until one of several stopping criteria is met.”).
ALBADAWI and Lam are combinable for the same rationale as set forth.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to YUHUI R PAN whose telephone number is (571)272-9872. The examiner can normally be reached Monday-Friday 8AM-5PM EST.
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/YUHUI R PAN/Primary Examiner, Art Unit 2116
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