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
Current application, US Application No. 19/200,815 filed 05/07/2025, is a Continuation of PCT/CN2023/101309 filed on 06/20/2023, and claims foreign priority to CN 202211651114.3 filed on 12/21/2022.
Examiner acknowledges that the certified copy of foreign priority copy has been received. However, the certified English translation copy of the original foreign document, which is not written in English, has not been received. There is no requirement to submit certified English translation copy at this stage according to 37 CFR 1.55(g)(3). However, should the need of certified English translated copy arise according to the cases mentioned in 37 CFR 1.55(g)(3), submission may be requested in the future.
DETAILED ACTION
This office action is responsive to the amendment filed on 10/15/2025. Claims 1-5 are currently pending.
Response to Amendment
Applicant's amendment is entered into further examination and appreciated by the examiner.
Response to Arguments/Remarks
Regarding remarks on the objections to the specification, the arguments are persuasive and the previous objections are withdrawn.
Regarding remarks on the objections to the claims, the amendment is accepted and the previous objections are withdrawn.
Regarding remarks on the rejections under 35 USC 112(b) to the claims, the amendment is accepted and the previous rejections are withdrawn. However, the amendment introduced a new limitation, which is not consistent with the specification and the earlier limitation. Please see the updated rejections below.
Regarding remarks on the rejections under 35 USC 101, applicant’s arguments accompanied with amended claims are fully considered, but are not persuasive because the following reasons.
Applicant argues (see pg. 15 par. 1 from the bottom – pg. 16 par. 2) that the claims do not recite an abstract idea, but merely involve an abstract idea at step 2A prong 1 analysis. In particular, claim 1 is directed to a measurement method for dioxin emission concentration using sensors to measure temperature, pressure and flow.
Examiner respectfully submits that the claims recites limitations that involves mathematical concept, i.e. performing mathematical calculation or showing mathematical relationship (see the detail analysis of each limitations below). The arguments that the current application uses sensors to measure temperature, pressure and flow are irrelevant at step 2A prong 1 analysis because measurement step is additional elements (or extra solution activity) that should be analyzed separately at step 2A ptong-2 and 2B.
Also the newly added limitation “measuring by sensors process variables including temperature pressure and flow of said MSWI process to detect drift data and improve accuracy of detection of DXN emission concentration” as one of main operational steps of “the online soft measurement method” appears misleading because the specification and the earlier limitation clearly states that the current method is based on a historical process data without having to measure using sensors (see specification - making full use of historical data for offline modeling is the first step to achieve online soft sensing. How to select historical data to build an offline model with low cost and keep it optimal performance is the primary issue that needs to be solved in DXN soft sensor modeling [0006], the process data of the typical sample pool is determined based on the historical process data set of MSWI [0010] and see earlier limitation “determining process data of a typical sample pool by applying a K-means weighting algorithm on a historical process data set of MSWI”) although the historical data should have been measured using recited sensors.
Applicant also argues (see pg. 16 par. 2 – pg. 21 par. 2) that (1) the claims disclose a novel method for soft-sensing Dioxin concentration by employing a drift indication control limit in combination with employing sensors to measure operating conditions to detect drift to improve the accuracy of soft-sensing DXN emission concentration, which is an improvement to the technology at step 2A prong 2 analysis and (2) the measurement itself being conventional or well-known is irrelevant to determining whether the combination of additional elements constitute a practical application because the determination belongs to step 2B instead of step 2a prong 2.
Examiner respectfully submits that (1) the argued novel method belong to the abstract idea. Improvements (or Novelty) of the abstract idea cannot be treated as an improvement to the technology. (See MPEP 2106.05(a) II - improvements in the abstract idea itself … simply provided … more information to facilitate … not improve computers or technology), (2) the recited measurement step can be analyzed in both step 2A prong 2 and 2B. In step 2A prong 2, the additional elements (or extra solution activities, e.g. measurements) are needed to be also analyzed whether they are particular or significant extra solution activities which indicate an integration of a practical application to the judicial exception in dependent of being “well understood routine and conventional” at step 2B.
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.
Claims 1-5 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention. As per claim 1, the newly added limitation “measuring by sensors process variables including temperature pressure and flow of said MSWI process to detect drift data and improve accuracy of detection of DXN emission concentration” contradicts with the earlier limitation and the specification that the current method is based on the collected historical process data. (see specification - making full use of historical data for offline modeling is the first step to achieve online soft sensing. How to select historical data to build an offline model with low cost and keep it optimal performance is the primary issue that needs to be solved in DXN soft sensor modeling [0006], the process data of the typical sample pool is determined based on the historical process data set of MSWI [0010] and see earlier limitation “determining process data of a typical sample pool by applying a K-means weighting algorithm on a historical process data set of MSWI”).
For the sake of the examination, the limitation “measuring by sensors process variables including temperature pressure and flow of said MSWI process to detect drift data and improve accuracy of detection of DXN emission concentration” is interpreted as “wherein the process variables in historical process data is obtained by measuring by sensors process variables including temperature, pressure and flow of said MSWI process to detect drift data and improve accuracy of detection of DXN emission concentration”.
As for claims 2-5, claims are also rejected because base claim 1 is rejected.
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 1-5 are rejected under 35 U.S.C. 101 because the claimed invention is directed to nonstatutory subject matter. The claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Specifically, representative claim 1 recites:
“An online soft measurement method for dioxin emission concentration in a municipal solid waste incineration (MSWI) process, (1.A) comprising:
determining process data of a typical sample pool by applying a K-means weighting algorithm on a historical process data set of MSWI; (1.B)
performing principal component analysis based on the process data of the typical sample pool to obtain a drift indicator control limit, wherein the drift indicator control limit reflects whether the MSWI process has drifted; (1.C.1)
constructing an offline model based on Fuzzy Tree-Based Learning (FTBL), and inputting the process data of the typical sample pool and historical dioxin (DXN) true value data of MSWI into the offline model for prediction calculation to obtain an offline calculation result; (1.C.2)
wherein the offline model comprises a feature mapping layer, an enhancement layer and an incremental layer; (1.C.3)
measuring by sensors process variables including temperature pressure and flow of said MSWI process to detect drift data and improve accuracy of detection of DXN emission concentration; (1.D.0)
performing principal component analysis based on online data, wherein the online data includes measurements of said process variables obtain by said measuring, and determining whether the online data is drift data or normal data based on the drift indicator control limit; (1.D.1)
when the online data is the normal data, jumping to the step "constructing an offline model based on FTBL, and inputting the process data of the typical sample pool and historical DXN true value data of MSWI into the offline model for prediction calculation to obtain an offline calculation result"; (1.D.2)
when the online data is the drift data, constructing an online model based on FTBL, and inputting the process data of the typical sample pool, the drift data, and output data of the incremental layer of the offline model into the online model for prediction calculation to obtain an online calculation result; (1.D.3)
wherein the online model comprises an online incremental layer; (1.D.4)
and determining the DXN emission concentration prediction value based on the offline calculation result and the online calculation result. (1.D.5)”
The claim limitations in the abstract idea have been highlighted in bold above; the remaining limitations are “additional elements”.
Under the Step 1 of the eligibility analysis, we determine whether the claims are to a statutory category by considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: Process, machine, manufacture, or composition of matter. The above claim is considered to be in a statutory category (Process - Method).
Under the Step 2A, Prong One, we consider whether the claim recites a judicial exception (abstract idea). In the above claim, the highlighted portion constitutes an abstract idea because, under a broadest reasonable interpretation, it recites limitations that fall into/recite an abstract idea exception. Specifically, under the 2019 Revised Patent Subject Matter Eligibility Guidance, it falls into the grouping of subject matter when recited as such in a claim limitation, that covers mathematical concepts (mathematical relationships, mathematical formulas or equations, mathematical calculations), and mental processes (concepts performed in the human mind including an observation, evaluation, judgement, and/or opinion).
For example, highlighted limitations/steps (1.B) – (1.C.3) and (1.D.1)-(1.D.5) are treated by the Examiner as belonging to Mathematical Concept grouping or a combination of Mathematical Concept and Mental Processing groupings or Mental Process grouping as the limitations include Mathematical Calculations, or show Mathematical Relationship with optional Mental judgement, or the limitations include Mental evaluations/judgements.
The limitation (1.B) shows mathematical calculation of the process data using K-means weighting algorithm.
The limitation (1.C.1) shows mathematical calculation of the drift indicator control limit using principal component analysis algorithm. See also mathematical equations in claims 2 and 3 for the determination the process data of the typical sample pool and principal component analysis, respectively.
The limitation (1.C.2) shows mathematical relationship and calculation among off line model, process data and off line calculation result. See mathematical equation of claim 4 for the offline model generation.
The limitation (1.C.3) describes the off line model and shows mental observation about the model.
The limitation (1.D.1) shows mathematical calculation of the online data using principal component analysis algorithm and mental evaluation regarding drift or normal data.
The limitation (1.D.2) shows mathematical relationship among offline model, process data and offline calculation result combined with a mental judgement on the online data being normal.
The limitation (1.D.3) shows mathematical relationship among online model, process data, the drift data and output data of the incremental layer of the offline model and the online calculation result with a mental judgement on the online data being drift. See mathematical equations in claim 5 for calculating online result.
The limitation (1.D.4) describes the online model and shows mental observation of the model.
The limitation (1.D.5) shows mathematical relationship among the DXN emission concentration prediction value, off line calculation result and online calculation result.
Next, under the Step 2A, Prong Two, we consider whether the claim that recites a judicial exception is integrated into a practical application.
In this step, we evaluate whether the claim recites additional elements that integrate the exception into a practical application of that exception.
The above claims comprise the following additional elements: (Side Note: duplicated elements are not repeated)
In Claim 1: “An online soft measurement method for dioxin emission concentration in a municipal solid waste incineration (MSWI) process”, “measuring by sensors process variables including temperature pressure and flow of said MSWI process to detect drift data and improve accuracy of detection of DXN emission concentration”;
As per claim 1, the additional element in the preamble “An online soft measurement method for dioxin emission concentration in a municipal solid waste incineration (MSWI) process” is not a meaningful limitation because the limitation simply shows that a method is for an abstract idea, i.e. calculating emission concentration value, which is about the MSWI process. No significant physical (or tangible) elements nor extra solution activities can be found either in the preamble. The limitation/step “measuring by sensors process variables including temperature pressure and flow of said MSWI process to detect drift data and improve accuracy of detection of DXN emission concentration” merely shows a data collection step in the art and only adds insignificant extra solutions to the judicial exception because the recited sensors are not particular in the art and the measurement step is recited in a high level of generality without specific details.
In conclusion, the above additional elements, considered individually and in combination with the other claim elements as a whole do not reflect an improvement to the computer technology or other technology or technical field, and, therefore, do not integrate the judicial exception into a practical application. No particular machine or real-world transformation are claimed. Therefore, the claims are directed to a judicial exception and require further analysis under the Step 2B.
Under Step 2B analysis, the above claims fail to include additional elements that are sufficient to amount to significantly more than the judicial exception as shown in the prior art of record.
The limitations/elements listed as additional elements above are well understood, routine and conventional steps/elements in the art according to the prior art of record. (See Tang ’140, Tang ‘585, Qiao, Tang ‘166, Al, Fujii, Togami, and others in the list of prior art of record)
Claims 1-5, therefore, are not patent eligible.
Allowable Subject Matter
Claims 1-5 recite subject matter which is allowable over the prior art, and would be allowable if rewritten or amended to overcome current objections and rejections.
The following is a statement of reasons for the indication of allowable subject matter: As per claim 1-5, the closest prior art of record, Tang ‘140 (WO 2023138140 A1), Tang ‘585 (WO 2021159585 A1), Qiao (US 20210033282 A1) and Tang ‘166 (WO 2020192166 A1), either singularly or in combination, fail to anticipate or render obvious limitations
“determining process data of a typical sample pool by applying a K-means weighting algorithm on a historical process data set of MSWI”,
“constructing an offline model based on Fuzzy Tree-Based Learning (FTBL), and inputting the process data of the typical sample pool and historical dioxin (DXN) true value data of MSWI into the offline model for prediction calculation to obtain an offline calculation result”,
“when the online data is the normal data, jumping to the step "constructing an offline model based on FTBL, and inputting the process data of the typical sample pool and historical DXN true value data of MSWI into the offline model for prediction calculation to obtain an offline calculation result";
when the online data is the drift data, constructing an online model based on FTBL, and inputting the process data of the typical sample pool, the drift data, and output data of the incremental layer of the offline model into the online model for prediction calculation to obtain an online calculation result’ and
“determining the DXN emission concentration prediction value based on the offline calculation result and the online calculation result” in combination with other limitations.
Tang ‘140 discloses
A soft-sensing method for dioxin emission during an MSWI process and using broad hybrid forest regression (BHFR) modeling technique which employes neural network layers (soft sensing method for dioxin emission during an MSWI process, BHFR model, feature mapping layer, feature extraction layer, feature enhancement layer and an incremental learning layer [abs]), but is silent regarding the above allowable limitations.
Tang ‘585 discloses
A dioxin emission concentration prediction method based on the hybrid integration of a random forest and a gradient boosting tree. The method improves the online DXN prediction precision by using a DXN prediction model construction method which integrates RF-based ( Random Forest based) DXN sub-model and GBDT (Gradient Boosting Decision Tree) based DXN sub-module (see - [abs]), but is silent regarding the above allowable limitations.
Quao discloses
A method for detecting a dioxin emission concentration of a municipal solid waste incineration process based on multi-level feature selection. A PLS (Partial Least Squares) algorithm-based DXN detection model is established and applied to detect the DXN emission concentration of the MSWI process (see – [abs]), but is silent regarding the above allowable limitations.
Tang ‘166 discloses
A method for building a soft measurement model for dioxin (DXN) emission concentration on the basis of a selective ensemble (SEN) of multi-source potential features [abs]), but is silent regarding the above allowable limitations.
As per claims 2-4 claims would be also allowable because base claim 1 would be allowable.
Notes with regard to Prior Art
The prior arts made of record are considered pertinent to applicant's disclosure.
Newly found references, Al (CN 115561001 A), Fujii (WO 2022102348 A1), Kadowaki (TW 202215178 A), Tang (CN 215297213 U, CN 113376209 A), Zhou (CN 112149355 A) and Togami (JP 2002054811 A) disclose use of sensors measuring temperature, pressure and flow for collecting the process data/variable for the waste processing/incineration.
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.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DOUGLAS KAY whose telephone number is (408) 918-7569. The examiner can normally be reached on M, Th & F 8-5, T 2-7, and W 8-1.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Arleen M Vazquez can be reached on 571-272-2619. 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 https://ppair-my.uspto.gov/pair/PrivatePair. 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.
/DOUGLAS KAY/Primary Examiner, Art Unit 2857
Prosecution Insights