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 .
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Japanese Patent Application No. 2022-060531, filed on March 31, 2022.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 01/19/2024 & 03/23/2023 are compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that use the word “means” or “step” but are nonetheless not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph because the claim limitation(s) recite(s) sufficient structure, materials, or acts to entirely perform the recited function. Such claim limitation(s) is/are:
“an acquisition part configured to acquire…”
“an evaluation part configured to evaluate an accuracy of prediction…” in claim 1.
“an acquisition step of acquiring updated second auxiliary filter information…”
“an evaluation step of evaluating an accuracy of prediction…” in claim 9.
Because this/these claim limitation(s) is/are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are not being interpreted to cover only the corresponding structure, material, or acts described in the specification as performing the claimed function, and equivalents thereof.
If applicant intends to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to remove the structure, materials, or acts that performs the claimed function; or (2) present a sufficient showing that the claim limitation(s) does/do not recite sufficient structure, materials, or acts to perform the claimed function.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 1 limitation “an acquisition part configured to acquire…” and “an evaluation part configured to evaluate an accuracy of prediction…” invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. At most the specification merely cites examples of acquisition and communication parts on pg. 42 as, “both the communication part 12 and the input part 13 are examples of the acquisition part. In addition, the controller 11 is an example of the evaluation part. Further, the processing according to the first regulation is an example of the first processing”. As such, the claims and the specification are devoid of any structure that explicitly performs the functions in the claims. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
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.
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.
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) 1-2, 6-7, & 9-10 is/are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication NO. 20230020146 “Mizoguchi” and further in light of U.S. Patent Application Publication NO. 20160116392 “Carpenter”.
Claim 1:
Mizoguchi teaches a model evaluation device comprising: an acquisition part configured to acquire updated second auxiliary (i.e. para. [0016], “FIG. 5 is a flowchart illustrating a procedure of processing when the controller performs the adjustment discharge on the battery, performs the refresh charge, and performs the correction of the SOC, estimation of a degradation level, and adjustment of a load”, wherein it is noted that the BRI for learning encompasses observing and a system becoming aware of such data. Wherein the BRI for updated secondary filter information encompasses a correction to an estimation for the part. The BRI for first auxiliary part information encompasses a first predicted information for a part and wherein the BRI for second auxiliary part information encompasses further information about a same part, such as estimated state of charge that is updated),
the first auxiliary (i.e. para. [0172], “The learning model DB 145 stores a learning model 146 generated for each of the plurality of reached SOCs (estimated SOCs)”, wherein the first auxiliary part information is a prediction for a degraded state of charge (SOC) based on battery data),
the second auxiliary filter information indicating a regulation for estimating a reliability of a prediction result by the mathematical model while using the first auxiliary (i.e. para. [0206], “The controller 11 can cause the learning model 146 to be relearned such that reliability of the estimation of the degree of degradation is improved based on the degree of degradation estimated using the learning model 146 and the degree of degradation obtained by actual measurement in a predetermined row of the use history”, wherein the BRI for a regulation encompasses how the reliability of the prediction result by the learning model may be improved while using the first prediction results); and an evaluation part configured to evaluate an accuracy of prediction by the mathematical model while using the second (i.e. para. [0031], “The estimated SOC is corrected by the SOC (hereinafter, referred to as actually measured SOC) based on the residual capacity derived from the above history. For example, the estimated SOC is replaced with the actually measured SOC. Thereafter, the SOC is estimated based on, for example, the current integration method with the replaced actually measured SOC as a reference. The average value of the estimated SOC and the actually measured SOC may be used as the updated SOC”, wherein the BRI for case input-scheduled data encompasses actual data that is scheduled to be input into the model in order to obtain an updated estimated SOC).
While Mizoguchi teaches a generating and updated a model for degradation of a target part, where the target part is a battery, Mizoguchi may not explicit teach using
Auxiliary filter information
However, Carpenter teaches,
Auxiliary filter information (i.e. para. [0035], “an exemplary solution to the problems in conventional systems and methods is to provide a better technique based on a more accurate model of the contamination of the filter 118 and/or the filter 189 and using the data obtained from one or more of the plurality of sensors 103 (e.g., the pressure sensor 128) in the model to better predict and improve an estimate of the remaining useful life of the filter 118 and/or the filter 189 in real-time as the filter 118 and/or the filter 189 is being used by the machine 100 during operation of the machine 100”, wherein it is noted that at least a first information prediction of a filter degradation and a second information that is filter data used to update an estimation prediction).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to add auxiliary filter information, to the recursive machine learning estimation methods of Mizoguchi, with how specifically first and second filter information is used as part of a machine learning degradation estimation method, as taught by Carpenter. One would have been motivated to combine specific data selection of Carpenter with the machine learning of Mizoguchi as the combination improves the functioning of a system by solving the complex problem of accurately predicting when the filter and/or the filter in the machine needs to be changed or replaced, and how much remaining useful life of the filter and/or the filter remains.
Claim 2:
Mizoguchi and Carpenter teach the model evaluation device according to claim 1.
Mizoguchi further teaches
wherein the data for generation is multi-dimensional time series data showing a change over time in each of a plurality types of variables that are expressing a state related to the degradation of the analysis target (i.e. para. [0084], “using the usable period as a reference, the ratio of the usable period remaining at the time of evaluation may be determined as the SOH. Using the voltage during the normal temperature high rate discharge as a reference, the voltage during the normal temperature high rate discharge at the time of evaluation may be used for the evaluation of SOH”, wherein it is noted that the data for generating an estimation of degradation is multi-dimensional as it encompasses both temperature and time data over a period of time related to the target part).
Claim 6:
Mizoguchi and Carpenter teach the model evaluation device according to claim 1.
Mizoguchi further teaches
wherein, in the learning, the first auxiliary filter information and the second auxiliary filter information are updated such that reliability of an estimation result by the mathematical model with respect to data obtained by actual measurement improves a data inclusion rate that is a probability which is a predetermined reliability or more (i.e. para. [2026], “the degree of degradation obtained by actual measurement in a predetermined row of the use history DB 35, the actually measured degradation level is obtained, and when the estimated degree of degradation is matched with the degree of degradation based on the actually measured degradation level, the probability of the degree of degradation can be increased by inputting and relearning a large number of teacher data in which the degree of degradation is associated with the internal resistance of this row. When the estimated degree of degradation is not matched with the actually measured degree of degradation, the teacher data in which the actually measured degree of degradation is associated with the internal resistance is input and the relearning is performed”, wherein the BRI for improving a data inclusion rate that is a probability which is a predetermined reliability or more encompasses how including actual data degradation data improves the data inclusion rate by including more data. The BRI for a predetermined reliability or more encompasses a measured actual degree of degradation, thus real historical degradation data in included to update a model when the probability for a degree of degradation is not more or matched with an actual degree of degradation).
Claim 7:
Mizoguchi and Carpenter teach the model evaluation device according to claim 1.
Mizoguchi further teaches wherein, in the learning, the first auxiliary filter information and the second auxiliary filter information are updated such that a difference between the estimation result by the mathematical model and physical or chemical characteristics included in the degradation of the analysis target is reduced (i.e. para. [0061], “the estimation unit may input the internal resistance or the conductance of a target lead-acid battery or lead-acid battery module to a learning model that outputs a degree of degradation to estimate the degree of degradation of the lead-acid battery or lead-acid battery module when the internal resistance or the conductance is input using the internal resistance or the conductance and a label data indicating the degree of degradation as teacher data”, wherein the BRI for physical and chemical chart eristics encompasses the internal resistance and conductance of a lead-acid battery is used to update and get a more accurate estimated degree of degradation).
Claim 9:
Claim 9 is the device claim reciting similar limitations to Claim 1 and is rejected for similar reasons.
Claim 10:
Claim 9 is the medium claim reciting similar limitations to Claim 1 and is rejected for similar reasons.
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication NO. 20230020146 “Mizoguchi” and further in light of U.S. Patent Application Publication NO. 20160116392 “Carpenter”, as applied to claim 2 above, and further in view of U.S. Patent Application Publication NO. 20120290879 “Shibuya”.
Claim 3:
Mizoguchi and Carpenter teach the model evaluation device according to claim 2.
Mizoguchi and Carpenter may not explicit teach
wherein the first processing is data conversion processing of converting the multi-dimensional time series data into 1- dimensional data.
However Shibuya teaches wherein the data for generation is
wherein the first processing is data conversion processing of converting the multi-dimensional time series data into 1- dimensional data.
(i.e. para. [0093-0095], “the dimension of the feature space may be further higher and the dimension of the affine partial space may also be any dimension as long as the dimension of the affine partial space is smaller than the feature space and smaller than the number of the learning data. …the local sub-space classifier is a method of creating a k-1-dimensional affine partial space by using k-approximate data of evaluation data q”, wherein in a case where K=2, then the classifier would convert the multi-dimensional data down to a 1 dimensional data features)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to add wherein the first processing is data conversion processing of converting the multi-dimensional time series data into 1- dimensional data, to the recursive machine learning estimation methods of Mizoguchi, with how data may be converted with a conversion processing of converting the multi-dimensional time series data into 1- dimensional data, as taught by Shibuya. One would have been motivated to add the dimensionality reducing algorithms of Shibuya with the machine learning of Mizoguchi-Carpenter as the combination improves the precision of a model that is inputting whole sensor signals with minimal effort.
Allowable Subject Matter
Claims 4, 5, and 8 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.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
U.S. Patent Application Publication NO. 20130282626 “White” teaches in para. [0161], that “a test/validation approach may be used to allow empirical determination of the accuracy of the model generation process. In this approach the observed data is split into two sets; a training set and a validation set. A predictive model is then generated using by the statistical model engine using the training set. A set of predictions is then made by the model using the validation set. The predictions for the validation set are compared against the observed results for the validation set, and appropriate confidence statistics are then produced to assess the accuracy of the model”.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAVID H TAN whose telephone number is (571)272-7433. The examiner can normally be reached M-F 7:30-4:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Cesar Paula can be reached at (571) 272-4128. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/D.T./Examiner, Art Unit 2145
/CHAU T NGUYEN/Primary Examiner, Art Unit 2145