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 .
Response to Amendment
The amendment filed 09/26/2025 has been entered. As directed, claims 1, 3, 5 and 6 have been
amended, claims 2 and 4 have been canceled and no claims is added. Thus claims 1, 3, 5 and 6 remain pending in the application. However, new rejection under U.S.C. 35 § 112(a) is made based on the newly amended claims.
Response to Arguments
With respect to the Applicant’s argued rejection under 35 § U.S.C. 101 in “Applicant Arguments/Remarks Made in an Amendment,”:
Applicant argues:
…
Claims 1-6 stand rejected under 35 USC 101 as allegedly being directed to non-statutory subject matter. This rejection is respectfully traversed.
Paragraph [0003] of the present specification recites:
"The temperature is a key parameter reflecting a smelting process state. The temperature of the tuyere raceway plays a role in guiding workers to judge the operation condition of the tuyere raceway. However, the internal temperature of the blast furnace is hard to measure by the workers due to technological characteristics and structural factors of the blast furnace, so that the exact value of the internal temperature of the tuyere raceway cannot be obtained on site; and operators cannot adjust parameters of blast, coal injection, and the like of the blast furnace in time, and the production efficiency is reduced. Therefore, it is of great significance to know the exact temperature value of the blast furnace tuyere raceway on site."
Based on the above recitation, the technical feature of "step 6: adjusting parameters of the blast furnace based on the prediction and calculation of the combustion temperature of the blast furnace tuyere raceway" has been added in to the independent claim 1 of the present application, so as to integrate the claimed inventions into a practical application.
The amended independent claim 1 can be applied to adjust the parameters of the blast furnace accordingly.
Further, the amended independent claim 1 can generate the effect of "increasing the product quality and production efficiency."
In view of the foregoing amendments and remarks, it is respectfully submitted that all claims are directed to statutory subject matter. Reconsideration and withdrawal of the 35 USC 101 rejection are respectfully requested.
(see Response filed 09/26/2025 [pages 6-7]).
In response to the applicant's argument, the examiner respectfully disagrees.
The newly amended limitation of claim 1, “step 6: adjusting parameters of the blast furnace …,” as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, a person is capable of observing a temperature value, evaluating whether the temperature is too high or too low, and mentally deciding what parameter should be modified (e.g., increasing or decreasing air flow, coal injection, or oxygen rate) (The courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011).).
Further, the limitation “step 6: adjusting parameters of the blast furnace based on the prediction and calculation of the combustion temperature of the blast furnace tuyere raceway,” which is merely a recitation of insignificant extra-solution (post-solution) activity: Insignificant application (i.e., adjusting parameters of blast furnace based on predicted and calculated combustion temperature) which does not integrate a judicial exception into practical application (see MPEP § 2106.05(g)). See also In re Brown, 645 Fed. App'x 1014, 1016-1017 (Fed. Cir. 2016) (non-precedential).
Under Step 2B, the additional limitations do not provide significantly more than the judicial exception. In particular, the limitation does not recite any specialized hardware, unconventional component, improved computer architecture, or any particular technological mechanism that performs adjustment step in an unconventional manner. Therefore, the additional element, individually or in combination, amount to no more than applying computer components or controller to perform well-understood, routine and conventional functions, which is insufficient to qualify as “significantly more” than the abstract idea under Step 2B, and independent claim 1, and dependent claims are directed to patent ineligible subject matter under 35 U.S.C. § 101.
For the reasons discussed above, applicant’s arguments have been considered but are not
persuasive. The claims are directed to abstract ideas (mental process and mathematical concepts), are not integrated judicial exception into a practical application, and do not recite additional elements amount to significantly more than the judicial exception. The rejection under 35 U.S.C. § 101 is maintained.
Applicant’s arguments, see “Arguments/Remarks Made in an Amendment,” pages 7-8, filed
09/26/2025, with respect to the rejection under 35 U.S.C. 112, have been fully considered but they are not persuasive.
The applicant argues, “That is, according to the description of the specification, one of ordinary skill in the art would recognize prior-art structure, such as computer, camera, and corresponding sensors, corresponding to the steps, wherein the camera and the sensors are connected to the computer, which should not be considered as new matters. For example, according to the description of the specification, one of ordinary skill in the art would unambiguously know: the step of collecting picture data of the present invention can by performed by camera; the step of extracting characteristics of the picture data of the present invention can be performed by sensors; and steps of data processing and calculating can be performed by computer.” However, one of ordinary skilled in the art would not understand how a sensor could perform the step of “extracting characteristics of the picture data,” and the specification contains no explanation of what structure performs this function. In addition, the newly amended paragraph [0032] introduces subject matter that was not present in the original disclosure cannot be relied upon to provide written description support. Therefore, the rejection under 35 U.S.C. 112 is maintained.
Specification
The amendment filed 09/26/2025 is objected to under 35 U.S.C. 132(a) because it introduces new matter into the disclosure. 35 U.S.C. 132(a) states that no amendment shall introduce new matter into the disclosure of the invention. The added material which is not supported by the original disclosure is as follows: Paragraph [0032], “For example, the embodiments of the present invention may be performed by a system comprising a computer, sensors, and cameras, wherein the sensors and the cameras are connected to the computer, and wherein the sensors may include a temperature sensor, a pressure sensor, and/or a flow sensor corresponding to various physical variable data.” The original filed specification only recites functional steps (e.g., collecting, extracting and calculating), and does not describe or identify any corresponding structure (e.g., a system, computer, camera or sensors) used to perform the functions. The amendment introduces specific structural components and system configurations that were not disclosed or implied with sufficient detail in the original filed specification. Because none of these components were described, mentioned, or implied in the originally filed application, the newly amended paragraph introduces subject matter that extends beyond the original disclosure. Applicant is required to cancel the new matter in the reply to this Office Action.
Claim Objections
Claims 1, 3 and 6 are objected to because of the following informalities:
Claim 1 recites “step 1.1: collecting the picture data of flame combustion at the blast furnace tuyere raceway” and “step 3.1: using the picture data of flame combustion at the blast furnace tuyere raceway …” should read as “step 1.1: collecting the picture data of the flame combustion at the blast furnace tuyere raceway” and “step 3.1: using the picture data of the flame combustion at the blast furnace tuyere raceway …”
Claim 3 also recites element “the picture data of flame combustion”, they are objected for the similar reason.
Claim 6 recites “ending the parameter optimization process after iterative termination conditions set by the sine cosine optimization algorithm are met” should read as “ending the parameter optimization process in the step 4, after iterative termination conditions set by the sine cosine optimization algorithm are met.”
Appropriate correction is required.
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 “step”. Such claim limitation(s) is/are:
The limitation of claim 1:
step 1: collecting picture data of flame combustion at the blast furnace tuyere raceway, physical variable data reflecting operation states of a blast furnace and combustion temperature data of the blast furnace tuyere raceway;
step 2: extracting characteristics of the picture data of the flame combustion at the blast furnace tuyere raceway;
step 3: constructing a multi-kernel least squares support vector regression model based on a Pearson correlation coefficient method and a least squares support vector regression algorithm as a soft measurement model for the temperature of the blast furnace tuyere raceway;
step 4: optimizing parameters of the soft measurement model for the temperature of the blast furnace tuyere raceway by using a sine cosine optimization algorithm;
step 5: taking optimal kernel function parameters of the picture data, kernel function parameters of the physical variable data and regularization parameters in the multi-kernel least squares support vector regression model, found in step 4, as final parameters of the soft measurement model for the temperature of the blast furnace tuyere raceway, and achieving prediction and calculation of a combustion temperature of the blast furnace tuyere raceway;
step 6: adjusting parameters of the blast furnace based on the prediction and calculation of the combustion temperature of the blast furnace tuyere raceway; …
step 1.1: collecting the picture data of flame combustion at the blast furnace tuyere raceway;
step 1.2: collecting the physical variable data reflecting the operation states of the blast furnace, wherein the physical variable data reflecting the operation states of the blast furnace includes hot air temperature, hot air pressure, cold air flow, furnace top pressure, pure oxygen flow and gas utilization rate; and
step 1.3: collecting the combustion temperature data of the blast furnace tuyere raceway, and
wherein step 3 comprises:
step 3.1: using the picture data of flame combustion at the blast furnace tuyere raceway and the physical variable data reflecting the operation states of the blast furnace, obtained in step 1.1 and step 1.2, as sample input data, and using the combustion temperature data of the blast furnace tuyere raceway, obtained in step 1.3, as sample temperature label data;
step 3.2: determining kernel function types and the kernel function parameters corresponding to the picture data collected in step 1.1 and the physical variable data collected in step 1.2, and calculating kernel matrices corresponding to the picture data and the physical variable data, respectively;
step 3.3: multiplying the combustion temperature data and a transpose vector thereof to construct a tuyere raceway combustion temperature data matrix on the premise of limiting the combustion temperature data of the blast furnace tuyere raceway obtained in step 1.3 as a column vector;
step 3.4: expanding by columns the kernel matrices calculated according to the picture data and the physical variable data in step 3.2 and the tuyere raceway combustion temperature data matrix constructed in step 3.3, and converting the kernel matrices into corresponding column vectors:
step 3.5: calculating a correlation coefficient between the column vectors corresponding to the picture data and the column vectors corresponding to the tuyere raceway combustion temperature data matrix by using the Pearson correlation coefficient method and calculating a correlation coefficient between the column vectors corresponding to the physical variable data and the column vectors corresponding to the tuyere raceway combustion temperature data matrix by using the Pearson correlation coefficient method;
step 3.6: determining weights of the kernel matrices of the picture data and the physical variable data, and constructing a combined kernel matrix of the blast furnace tuyere raceway by using a weighted summation method; and
step 3.7: constructing the multi-kernel least squares support vector regression model based on the least squares support vector regression algorithm by using the combined kernel matrix constructed in step 3.6 and the temperature label data in step 3.1 as the soft measurement model for the temperature of the blast furnace tuyere raceway.
The limitation of claim 3:
step 2.1: converting the picture data of flame combustion at the blast furnace tuyere raceway, collected in step 1.1, into an HSV color space from an RGB color space; and
step 2.2: extracting HSV nonuniform quantization characteristics of the picture data of flame combustion at the blast furnace tuyere raceway from the HSV color space.
The limitation of claim 6:
step 4.1: determining parameter optimization objects, wherein the parameter optimization objects are the kernel function parameters of the picture data and the kernel function parameters of the physical variable data in step 3.2, and the regularization parameters in the multi-kernel least squares support vector regression model; and
step 4.2: taking a root mean square error index of the soft measurement model for the temperature of the blast furnace tuyere raceway in step 3 as a fitness function of the sine cosine optimization algorithm, calculating all processes in step 3 in a cyclic iteration before optimal parameters are obtained, and ending the parameter optimization process after iterative termination conditions set by the sine cosine optimization algorithm are met.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend 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 avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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.
Claims 1, 3 and 5-6 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph,
as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim limitation “step x (e.g., step 1, step 1.1, step 2, step 2.1 , etc.)” of claims 1, 3 and 6 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. The originally filed disclosure is devoid of any structure that performs the functions recited in the claim, and the newly added structural description in amended paragraph [0032] does not clearly correspond to the claimed functions. Paragraph [0032] recites, “the embodiments of the present invention may be performed by a system comprising a computer, sensors, and cameras, wherein the sensors and the cameras are connected to the computer, …” Since the disclosure is provided only as an example and recites that the invention may be performed by a system, it is unclear whether the claimed method is intended to be performed by the system or by some other structure, including manually or mentally. However, even considering the amended disclosure, it does not identify which structure performs which recited function, and does not describe how the disclosed structure performs the particular operations recited in the claims. In addition, the specification does not explain how any structure performs the function of extracting characteristics of the picture data of the flame combustion, or how any structure performs the function of adjusting parameters of the blast furnace based on the predicted and calculated temperature. The amended disclosure does not provide any association between the recited system components and the specific functional steps required by the claims. No corresponding structure is described in the specification to perform the entire recited function, rendering the claim indefinite. 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.
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1, 3, 5 and 6 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph,
as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
claim 1 recites “step 6: adjusting parameters of the blast furnace based on the prediction and calculation of the combustion temperature of the blast furnace tuyere raceway.” In this case, the step 6 contains subject matter which was not described in the specification. For example, in the instant specification: [0003], “The temperature is a key parameter reflecting a smelting process state. The temperature of the tuyere raceway plays a role in guiding workers to judge the operation condition of the tuyere raceway. However, the internal temperature of the blast furnace is hard to measure by the workers due to technological characteristics and structural factors of the blast furnace, so that the exact value of the internal temperature of the tuyere raceway cannot be obtained on site; and operators cannot adjust parameters of blast, coal injection, and the like of the blast furnace in time, and the production efficiency is reduced. Therefore, it is of great significance to know the exact temperature value of the blast furnace tuyere raceway on site.” The specification does not disclose how parameters of the blast furnace are to be adjusted based on a predicted or calculated temperature, what furnace parameters are adjusted, what rules or relations between the predicted temperature and the adjustment, or what mechanism (manual or automatic) performs the adjustment. The paragraph [0003] fails to disclose any implementation details necessary to perform Step 6, does not describe any connection between the predicted temperature and the operational parameters of the blast furnace in a manner that would allow one of ordinary skilled in the art to understand and perform the claimed adjusting step. Therefore, the step 6 that performs the function was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor at the time the application was filed, had possession of the claimed invention. The remaining claims 3, 5 and 6 are dependent upon claim 1 listed above and rejected for the same reason.
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.
The claim(s) 1, 3, 5 and 6 are rejected under 35 USC § 101 because the claimed invention is
directed to judicial exception an abstract idea, it has not been integrated into practical application and the claims further do not recite significantly more than the judicial exception. Examiner has evaluated the claims under the framework provided in the 2019 Patent Eligibility Guidance published in the Federal Register 01/07/2019 and has provided such analysis below.
Step 1: Are the claims to a process, machine, manufacture or composition of matter?"
Yes, Claims 1, 3, 5 and 6 are directed to method and fall within the statutory category of processes.
In order to evaluate the Step 2A inquiry "Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?" we must determine, at Step 2A Prong 1, whether the claim recites a law of nature, a natural phenomenon or an abstract idea and further whether the claim recites additional elements that integrate the judicial exception into a practical application.
Step 2A Prong 1:
Claim 1: The limitations of “step 2: extracting characteristics of the picture data of the flame combustion at the blast furnace tuyere raceway,” as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, a person is capable of observing (e.g., visually inspect) the picture data of the flame combustion, and mentally evaluate characteristics such as brightness, color distribution, or flame shape to infer temperature distribution, luminosity, or emission intensity (The courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011).).
Claim 1: The limitations of “step 6: adjusting parameters of the blast furnace …,” as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, a person is capable of observing a temperature, value, evaluating whether the temperature is too high or too low, and mentally deciding what parameter should be modified (e.g., increasing or decreasing air flow, coal injection, or oxygen rate) (The courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011).).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
In MPEP 2106.04(II)(B): A claim may recite multiple judicial exceptions. For example, claim 4 at issue in Bilski v. Kappos, 561 U.S. 593, 95 USPQ2d 1001 (2010) recited two abstract ideas, and the claims at issue in Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 101 USPQ2d 1961 (2012) recited two laws of nature. However, these claims were analyzed by the Supreme Court in the same manner as claims reciting a single judicial exception, such as those in Alice Corp., 573 U.S. 208, 110 USPQ2d 1976.
Claim 1, The limitation recites “step 3: constructing a multi-kernel least squares support vector regression model based on a Pearson correlation coefficient method and a least squares support vector regression algorithm as a soft measurement model for the temperature of the blast furnace tuyere raceway; step 4: optimizing parameters of the soft measurement model for the temperature of the blast furnace tuyere raceway by using a sine cosine optimization algorithm; and step 5: taking optimal kernel function parameters of the picture data, kernel function parameters of the physical variable data and regularization parameters in the multi-kernel least squares support vector regression model, found in step 4, as final parameters of the soft measurement model for the temperature of the blast furnace tuyere raceway, and achieving prediction and calculation of the combustion temperature of the blast furnace tuyere raceway; step 3.1 … step 3.2 … step 3.3 … step 3.4 … step 3.5 … step 3.6 … step 3.7 …” as drafted, under its broadest reasonable interpretation (BRI) in light of specification, can be reasonably considered to represent mathematical concept, specifically:
MPEP 2106.4(a)(2)(I): “The mathematical concepts grouping is defined as mathematical
relationships, mathematical formulas or equations, and mathematical calculations”.
MPEP 2106.04(a)(2)(I)(A), “A mathematical relationship is a relationship between variables or numbers. A mathematical relationship may be expressed in words or using mathematical symbols.”
Further, MPEP recites: “For example, a step of "determining" a variable or number using mathematical methods or "performing" a mathematical operation may also be considered mathematical calculations when the broadest reasonable interpretation of the claim in light of the specification encompasses a mathematical calculation.
The limitations of “step 3: constructing a multi-kernel least squares support vector regression model based on a Pearson correlation coefficient method and a least squares support vector regression algorithm as a soft measurement model for the temperature of the blast furnace tuyere raceway" and “… step 3.2: determining kernel function types and the kernel function parameters corresponding to the picture data collected in step 1.1 and the physical variable data collected in step 1.2, and calculating kernel matrices corresponding to the picture data and the physical variable data, respectively; step 3.3: multiplying the combustion temperature data and a transpose vector thereof to construct a tuyere raceway combustion temperature data matrix on the premise of limiting the combustion temperature data of the blast furnace tuyere raceway obtained in step 1.3 as a column vector; step 3.4: expanding by columns the kernel matrices calculated according to the picture data and the physical variable data in step 3.2 and the tuyere raceway combustion temperature data matrix constructed in step 3.3, and converting the kernel matrices into corresponding column vectors: step 3.5: calculating a correlation coefficient between the column vectors corresponding to the picture data and the column vectors corresponding to the tuyere raceway combustion temperature data matrix by using the Pearson correlation coefficient method and calculating a correlation coefficient between the column vectors corresponding to the physical variable data and the column vectors corresponding to the tuyere raceway combustion temperature data matrix by using the Pearson correlation coefficient method; step 3.6: determining weights of the kernel matrices of the picture data and the physical variable data, and constructing a combined kernel matrix of the blast furnace tuyere raceway by using a weighted summation method: and step 3.7: constructing the multi-kernel least squares support vector regression model based on the least squares support vector regression algorithm by using the combined kernel matrix constructed in step 3.6 and the temperature label data in step 3.1 as the soft measurement model for the temperature of the blast furnace tuyere raceway.” The limitation can be considered to represent mathematical concepts. In the specification: [0048] – [0073], disclose the mathematical relationships, mathematical formulas or equations, and mathematical calculations.
The limitations of “step 4: optimizing parameters of the soft measurement model for the temperature of the blast furnace tuyere raceway by using a sine cosine optimization algorithm.” The limitation can be considered to represent mathematical concepts. In the specification: [0074] – [0078], disclose the mathematical relationships, mathematical formulas or equations, and mathematical calculations.
The limitations of “step 5: taking optimal kernel function parameters of the picture data, kernel function parameters of the physical variable data and regularization parameters in the multi-kernel least squares support vector regression model, found in step 4, as final parameters of the soft measurement model for the temperature of the blast furnace tuyere raceway, and achieving prediction and calculation of a combustion temperature of the blast furnace tuyere raceway.” The limitation can be considered to represent mathematical concepts, claim limitation clearly recites “… prediction and calculation of the combustion temperature …” based on all optimized kernel function parameters and regularization parameters in the multi-kernel least squares support vector regression model as mathematical calculations. In the specification: [0025]-[0026], discloses the mathematical relationships and mathematical calculations.
Therefore, claim 1 recites judicial exceptions. The claims have been identified to recite judicial exceptions, Step 2A Prong 2 will evaluate whether the claims as a whole integrates the exception into a practical application of that exception.
Step 2A Prong 2: Claim 1: The judicial exception is not integrated into a practical application.
In particular, the claims recite the following additional elements - “collecting picture data of flame combustion at the blast furnace tuyere raceway, physical variable data reflecting operation states of a blast furnace and combustion temperature data of the blast furnace tuyere raceway” and “step 1.1: collecting the picture data of flame combustion at the blast furnace tuyere raceway; step 1.2: collecting the physical variable data reflecting the operation states of the blast furnace, wherein the physical variable data reflecting the operation states of the blast furnace includes hot air temperature, hot air pressure, cold air flow, furnace top pressure, pure oxygen flow and gas utilization rate; and step 1.3: collecting the combustion temperature data of the blast furnace tuyere raceway” and “step 3.1: using the picture data of flame combustion at the blast furnace tuyere raceway and the physical variable data reflecting the operation states of the blast furnace, obtained in step 1.1 and step 1.2, as sample input data, and using the combustion temperature data of the blast furnace tuyere raceway, obtained in step 1.3, as sample temperature label data,” which are merely a recitation of insignificant extra-solution data gathering (i.e., receiving/collecting data and inputting collected data) activity (see MPEP § 2106.05(g)) with the broad reasonable interpretation, which does not integrate a judicial exception into practical application.
Further, the following additional limitation of claim 1, “step 6: adjusting parameters of the blast furnace based on the prediction and calculation of the combustion temperature of the blast furnace tuyere raceway,” which is merely a recitation of insignificant extra-solution (post-solution) activity: Insignificant application (i.e., adjusting parameters of blast furnace based on predicted and calculated combustion temperature) which does not integrate a judicial exception into practical application (see MPEP § 2106.05(g)). See also In re Brown, 645 Fed. App'x 1014, 1016-1017 (Fed. Cir. 2016) (non-precedential). Adding a final step of adjusting parameter of the blast furnace to a process that only recites computing parameter of soft measurement model, and predicting and calculating the temperature of a combustion temperature (mathematical calculations) does not add a meaningful limitation to the process of computing parameter of soft measurement model, and predicting and calculating the temperature of a combustion temperature.
Therefore, "Do the claims recite additional elements that integrate the judicial exception into a practical application? No, these additional elements do not integrate the abstract idea into a practical application and they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
After having evaluated the inquires set forth in Steps 2A Prong 1 and 2, it has been concluded that claim 1 not only recite a judicial exception but that the claims are directed to the judicial exception as the judicial exception has not been integrated into practical application.
Step 2B: Claim 1: The claim does not include additional elements, alone or in combination, that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than generic computing components which do not amount to significantly more than the abstract idea. Limitations that the courts have found not to be enough to qualify as "significantly more" when recited in a claim with a judicial exception include: i. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 573 U.S. at 225-26, 110 USPQ2d at 1984 (see MPEP § 2106.05(f)); ii. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d)); iii. Adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering in conjunction with a law of nature or abstract idea such as a step of obtaining information about credit card transactions so that the information can be analyzed by an abstract mental process, as discussed in CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375, 99 USPQ2d 1690, 1694 (Fed. Cir. 2011) (see MPEP § 2106.05(g)) ; …
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network, …; iii. Electronic recordkeeping, … (updating an activity log). iv. Storing and retrieving information in memory,…
The additional limitations do not provide significantly more than the judicial exception. In particular, the limitation does not recite any specialized hardware, unconventional component, improved computer architecture, or any particular technological mechanism that performs collection and adjustment steps in an unconventional manner. Therefore, the additional element, individually or in combination, amount to no more than applying computer components or controller to perform well-understood, routine and conventional functions, which is insufficient to qualify as “significantly more” than the abstract idea under Step 2B.
Therefore, "Do the claims recite additional elements that amount to significantly more than the judicial exception? No, these additional elements, alone or in combination, do not amount to significantly more than the judicial exception. Having concluded analysis within the provided framework, claim 1 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Dependent claims 3, 5 and 6 are also similar rejected under same rationale as cited above wherein these claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. These claims are merely further elaborate the mental process itself (and/or mathematical operations) or providing additional definition of process which does not impose any meaningful limits on practicing the abstract idea. Claims 3, 5 and 6 are also rejected for incorporating the deficiency of their independent claim 1.
Claim 3 recites “step 2.1: converting the picture data of flame combustion at the blast furnace tuyere raceway, collected in step 1.1, into an HSV color space from an RGB color space; and step 2.2: extracting HSV nonuniform quantization characteristics of the picture data of flame combustion at the blast furnace tuyere raceway from the HSV color space.”
This merely specifies converting the picture data into HSV color space from an RGB color space, and further defines extracting HSV nonuniform quantization characteristics of the picture data from the HSV color space; therefore, it merely adding the words "apply it" (or an equivalent) with the judicial exception, or instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, and applying a computer component to perform a convert and extract step based on received picture data at high level of generality is simply the act of instructing a computer to perform generic functions, which is merely an instruction to apply a computer to the judicial exception or significant more. Therefore, the claim 3 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Claim 5 recites “after the correlation coefficients between the column vectors corresponding to the picture data and the column vectors corresponding to the tuyere raceway combustion temperature data matrix and between the column vectors corresponding to the physical variable data and the column vectors corresponding to the tuyere raceway combustion temperature data matrix are calculated in step 3.5 by using the Pearson correlation coefficient method, respectively, taking a respective proportion of the correlation coefficients corresponding to the picture data and the physical variable data to a sum of the correlation coefficients as a weight of each kernel matrix; and multiplying the kernel matrices of the picture data and the physical variable data by respective weights, and then performing a summation to form the combined kernel matrix.”
This merely specifies calculating correlation coefficients between column vectors corresponding to the picture data and physical variable data and the column vectors of the tuyere raceway combustion temperature data matrix using the Pearson correlation coefficient method; taking a respective proportion of each correlation coefficient relative to the total as the weight of each kernel matrix; multiplying the kernel matrices of the picture data and physical variable data by their corresponding weights; and performing a summation to generate the combined kernel matrix; therefore, it merely mathematical concepts (see instant specification [0064], [0072] and [0073]). Therefore, the claim 5 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Claim 6 recites “step 4.1: determining parameter optimization objects, wherein the parameter optimization objects are the kernel function parameters of the picture data and the kernel function parameters of the physical variable data in step 3.2, and the regularization parameters in the multi-kernel least squares support vector regression model; and step 4.2: taking a root mean square error index of the soft measurement model for the temperature of the blast furnace tuyere raceway in step 3 as a fitness function of the sine cosine optimization algorithm, calculating all processes in step 3 in a cyclic iteration before optimal parameters are obtained, and ending the parameter optimization process after iterative termination conditions set by the sine cosine optimization algorithm are met.”
This merely specifies using a fitness function of a sine cosine optimization algorithm to minimize a root mean square error function for determining optimal kernel and regularization parameters in a regression model, by iteratively recalculating prior steps until termination conditions are satisfied; therefore, it merely an extension of mental process (i.e., determine …), mathematical concepts (i.e., calculating…), and a recitation of insignificant extra-solution data gathering (i.e., cyclic iteration) activity (see MPEP § 2106.05(g)) which does not integrate a judicial exception into practical application.. Therefore, the claim 6 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Allowable Subject Matter
Claims 1, 3, 5 and 6 would be allowable if rewritten or amended to overcome the rejection(s)
under 35 U.S.C 101, 35 U.S.C. 112(a), and 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action.
The following is a statement of reasons for the indication of allowable subject matter: Regarding
Claim 4, the closest prior arts found, “Image-Based Flame Detection and Combustion Analysis for Blast Furnace Raceway” by Zhang, published in April, 2019 discloses of image-based flame detection system specific to the blast furnace raceway to research the actual combustion condition in the raceway. The system mainly consists of an optical detector to capture raceway images and a digital image processing unit to extract flame features. In this paper, the nonlinear partial least-squares colorimetry and Monte Carlo method with iterative optimization are developed to obtain the temperature distribution of the raceway. (abstract); Wang CN106909705A, discloses of extracting the corresponding historical data from the database as the training set of the forecasting model, the forecasting model is trained by the method of dynamic neural network to realize the rolling of the model; Tong CN110033175A discloses of a soft measurement method based on an integrated multi-kernel partial least squares regression model, which aims to establish and fuse a kernel partial least squares (KPLS) regression model corresponding to a plurality of kernel functions, so as to avoid the selection problem of the kernel functions and steps (1) – (13) (see page.1-6 and abstract); “Parameter optimization of support vector regressio