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
Applicant has submitted amendments to the claims on 07/02/2026.
Allowable Subject Matter
Claims 7, 10-11, and 19 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 § 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.
Claim(s) 1-6, 8-9 and 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fujiwara et al (US PUB. 20230073260, herein Fujiwara) in view of Hill et al (US PUB. 20170316050, herein Hill).
Regarding claim 1, Fujiwara teaches A cooperative management system for causing a plurality of individual systems to operate in cooperation with each other as one overall system (0008 “a plurality of individual systems; and a host system configured to communicate to and from the plurality of individual systems”), the cooperative management system comprising:
a communication interface configured to communicate with the plurality of individual systems (0032);
a memory storing instructions and one or more processors configured to execute the instructions (0032) to:
acquire, via the communication interface from the plurality of individual systems (0032), values of candidate individual indicators that are evaluation indicators regarding respective individual systems and candidate operating parameters of the respective individual systems for controlling the candidate individual indicators (table 3, 0057, 0058 “as shown in FIG. 3, when the individual system 20 to which the optimization calculation module 50 belongs is the business site (individual system 20a), the electricity price is set as the objective function. Moreover, in this case, the contracted electric power and the reverse power flow inhibition are set as the constraint condition. Moreover, in this case, the contracted electric power value and an electric power use amount unit price are used as the other information”, fig. 2)
select, from the candidate individual indicators or the candidate operating parameters, a subset to be used for management of an overall indicator that is an evaluation indicator regarding the overall system (“[0069] With reference again to FIG. 2, after the prediction of the electric power demand (Step S130), the optimization calculation module 50 acquires and sets the unit imbalance amount and the incentive (Step S140). When the processing step of Step S140 is executed for the first time at the current interrupt timing, predetermined initial values are set to the unit imbalance amount and the incentive. Moreover, as described later, when the unit imbalance amount and the incentive are received from the host system 12, the received unit imbalance amount and incentive are set. [0070] Next, the optimization calculation module 50 uses the set objective function, constraint condition, unit imbalance amount, and incentive to execute the optimization calculation (Step S150). In the optimization calculation, for example, a weighted sum of the objective function, the incentive, and a function for reducing the unit imbalance amount is minimized under the constraint condition.”)
The cited prior art do not teach generate and store in the memory a relational model between the overall indicator and the selected subset; set a search problem using the relational model and current values of the selected subset; execute the search problem to determine conditions of the selected subset that improves the overall indicator; and transmit, via the communication interface to the respective individual systems, the determined conditions of the selected subset.
Hill teaches generate and store in the memory a relational model between the overall indicator and the selected subset (0033 “analytics system 220 automatically generates queries to perform the desired computations for linear and nonlinear feature selection, for each selected parameter and for each KPI. For example, for linear feature selection operations, the queries request computation of in-database sums, sums-of-squares and cross-products to compute Correlations or ANOVA (Analysis of Variance) measurements (effect size, F-values, values) with respect to each selected parameter and each selected KPI. For nonlinear feature selection, the queries request computation of optimal splits in each selected parameter. The optimal splits in each selected parameter will provide an improved relationship between the rank-ordered or discrete parameters and each selected KPI. In certain embodiments, the automatically generated queries perform Chi-Squared Automatic Interaction Detection (CHAID) type operations. In certain embodiments the automatically generated queries perform one or more operation that result in an index of lift or diagnostic value to identify the specific parameters showing the strongest relationship to the respective KPI's. The term lift in the context of predictive modeling refers to the improvement in the accuracy of a predictive model that is attributable to a particular parameter relative to the improvement in accuracy that can be expected by pure chance if a parameter (i.e., a variable) with random values were to be added to the prediction equations. In certain embodiments the analytics system 220 includes capabilities to prepare queries that explicitly evaluate interaction effects between pairs or triplets of selected parameters. For the purposes of this disclosure, interactions imply summary statistics that reflect on the joint importance of pairs or triplets of parameters that are present only when each of the respective parameters is present in a particular prediction model.”);
set a search problem using the relational model and current values of the selected subset; execute the search problem to determine conditions of the selected subset that improves the overall indicator; and transmit, via the communication interface to the respective individual systems, the determined conditions of the selected subset (0035 “After all queries have completed and returned the respective summary statistics (typically one statistic per parameter), the analytics system 210 then prepare a final result for each KPI, showing the set of parameters chosen from among all parameters that show the strongest relationship (linear, non-linear) to each selected KPI. In certain embodiments, the analytics system 210 prepare one or more diagnostic statistics and graphical displays to aid in the interpretation of results and subsequent post-processing and modeling of selected predictors. For example, in certain embodiments, the analytics system 210 prepares a Pareto chart which represents in a bar chart a bar for each parameter, where the length of the bar is proportional to the respective parameter's strength-of-relationship to the respective KPI.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to have modified the teachings of Fujiwara with the teachings of Hill since Hill teaches a means for “derive quickly and efficiently a subset of diagnostic parameters for predictive modeling” (0005).
Regarding claim 2, the cited prior art teach The cooperative management system according to claim 1.
Hill teaches wherein the one or more processors are further configured to generate the relational model based on operational data including values of the overall indicator and values of the selected subset acquired over time (0031 “If a respective data repository of the storage system 210 represents a relational database and the parameters and parameter values are stored in stacked format in a single table, then the user can select from among the Parameter Names in the stacked table. In certain embodiments, the single table includes one or more of Parameter Names, date/time-stamps or other index values. In certain embodiments, a database view of the data repository into multiple tables databases is organized to mimic a stacked format in a single table. If parameter values are stored or organized as columns, then the user can select from among all the field names. In certain embodiments, each data field or column represents the values for a single parameter. When selecting a particular column, the in-database feature selection system 254 performs computational operations which automatically determine if the selected parameters (e.g., the Parameter Names) contain discrete values such as tool names or continuous measurements such as tool or sensor measurements.”, 0033).
Regarding claim 3, the cited prior art teach the cooperative management system according to claim 2.
Fujiwara teaches wherein the one or more processors are further configured to select, as the selected subset, individual indicators or operating parameters that are capable of controlling the overall indicator ((“[0069] With reference again to FIG. 2, after the prediction of the electric power demand (Step S130), the optimization calculation module 50 acquires and sets the unit imbalance amount and the incentive (Step S140). When the processing step of Step S140 is executed for the first time at the current interrupt timing, predetermined initial values are set to the unit imbalance amount and the incentive. Moreover, as described later, when the unit imbalance amount and the incentive are received from the host system 12, the received unit imbalance amount and incentive are set. [0070] Next, the optimization calculation module 50 uses the set objective function, constraint condition, unit imbalance amount, and incentive to execute the optimization calculation (Step S150). In the optimization calculation, for example, a weighted sum of the objective function, the incentive, and a function for reducing the unit imbalance amount is minimized under the constraint condition.”).
Regarding claim 4, the cited prior art teach the cooperative management system according to claim 3.
Hill teaches wherein the one or more processors select, as the selected subset, individual indicators or operating parameters each having a correlation with the overall indicator equal to or greater than a threshold value (0015, 0033).
Regarding claim 5, the cited prior art teach the cooperative management system according to claim 1.
Fujiwara teaches wherein the one or more processors are further configured to set the search problem by applying the relational model to at least one of an objective function, a constraint equation, or a simulator used to search for the conditions of the selected subset (0035 0036).
Regarding claim 6, the cited prior art teach the cooperative management system according to claim 5.
Fujiwara teaches wherein the one or more processors are further configured to select characteristics of the search problem in accordance a formation method of the relational model (0069 0070).
Regarding claim 7, the cited prior art teach the cooperative management system according to claim 1.
wherein the one or more processors are further configured to: receive, from each individual system, an indication of whether the determined conditions are acceptable when one or more of the determined conditions are not acceptable, receive, from the respective individual systems, constraints for the selected individual indicators or constraints for the selected operating parameters; and re-execute the search problem based on the received constraints to determine updated conditions of the selected subset.
Regarding claim 8, the cited prior art teach the cooperative management system according to claim 1.
Fujiwara teaches wherein the overall indicator comprises a plurality of overall indicators, and wherein the one or more processors are further configured to determine the conditions of the selected subset so as to improve the plurality of overall indicators (0035).
Regarding claim 9, the cited prior art teach the cooperative management system according to claim 8.
Fujiwara teaches wherein the one or more processors are further configured to set a range of the conditions determined for an overall indicator having a first priority among the plurality of overall indicators as a condition for limiting a search range when determining conditions for an overall indicator having a second priority lower than the first priority (0035 “objective function is set for each individual system 20. For example, in the individual system 20a, the electricity price at the business site is set as the objective function. Moreover, for example, in the individual system 20b, the number of charge/discharge cycles of the battery is set as the objective function. The charge/discharge cycle extends from a start of charge to a start of next charge through an end of the charge, or from a start of discharge to a start of next discharge through an end of the discharge. The number of charge/discharge cycles is the number of times of the charge/discharge cycles. Moreover, for example, in the individual system 20c, an error between a target value and a prediction value of a state of charge (SOC) at a scheduled charge end time of the battery of the EV is set as the objective function. In the individual system 20c, a difference between a target pattern and a predicted pattern of a driving pattern of the EV (in other words, an operation pattern of the charger) may be set as the objective function”).
Regarding claim 12, the cited prior art teach the cooperative management system according to claim 1.
Fujiwara teaches wherein the one or more processors are further configured to display the determined conditions of the selected subset on a display screen (0008 0035).
Claims 13-18 and 20 are rejected using similar reasoning as the rejection of claims 1-6, 8-9 and 12 due to reciting similar limitations but directed towards a method.
Response to Arguments
Applicant’s arguments, filed 07/02/2026, with respect to the rejection(s) of claim(s) 1 under 35 USC 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Fujiwara et al (US PUB. 20230073260, herein Fujiwara) in view of Hill et al (US PUB. 20170316050, herein Hill).
Applicant’s argument in respect of the rejection of the claims under 35 USC 101 have been fully considered and are deemed persuasive. Therefore, the rejection of claims under 35 USC 101 has been withdrawn.
Applicant argues on page 15 Fujiwara does not teach the amendments to the claims. Examiner agrees. However, as a result of further search Hill has been introduced.
Hill teaches the relational model between the overall indicator and the selected subset (0033). Hill further teaches set a search problem using the relational model and current values of the selected subset; execute the search problem to determine conditions of the selected subset that improves the overall indicator; and transmit, via the communication interface to the respective individual systems, the determined conditions of the selected subset since Hill teaches searching for a set of parameters that show the strongest relationship to each selected KPI and transmit them (0035).
Therefore, claim 1 is rejected along with the dependent claims. Claim 13 is similar and is similarly rejected along with its dependent claims.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
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/TAMEEM D SIDDIQUEE/
Primary Examiner
Art Unit 2116
Prosecution Insights