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 .
Status of the claims
The amendments received on June 30, 2026 have been acknowledged and entered. Claims 1-4, 6, and 12-16 are amended. Claims 9 and 19 are cancelled. Thus, claims 1-8, 10-18, and 20 are pending.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-8, 10-18, and 20 under 35 U.S.C. 101 have been considered but are moot in view of the new ground of rejection necessitated by the amendment. However, since Applicant’s arguments rely on current rejection, Applicant’s arguments are addressed as follows:
On the pages 4-5 of the Remarks, Applicant alleges that “[A]mended claim 1 limits the construction of a candidate deployment graph based on real gas pipeline network physical connection relationships, in which nodes and edges completely correspond to physical pipelines and physical connection relationships between pipelines; a GNN is used to predict the future failure probability of each entity node, and quantitative scoring is completed through a fixed weighted summation formula
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to filter the optimal target deployment graph from multiple candidate deployment graphs. This model calculation is not a pure mathematical calculation, but uses pipeline network physical topology and entity node characteristics as inputs, and entity failure risks and impact ranges as outputs, providing a quantitative basis for on-site emergency deployment. The final generated deployment plan includes exclusive physical construction parameters such as crossover parameters, gas supply parameters, and pressure regulation parameters, directly defining the specific hardware operation modes, operation scope, and operation indicators of the emergency vehicle on site, guiding physical devices to execute engineering actions such as pipeline crossover, temporary gas supply, and pressure adjustment, thoroughly completing the closed loop from abstract data analysis to entity physical operation. These features are analogous to Example 47 (Anomaly Detection) of the Subject Matter Eligibility Examples, when algorithm output results directly drive specialized hardware to perform physical operations or solve real industrial equipment failures, it constitutes an effective integration of judicial exceptions. This case is logically consistent with a plastic injection molding controller (MPEP Example 45): both translate data analysis/model calculation results into control commands, driving underlying physical equipment to perform operations that change the state of the physical world.”
Examiner respectfully disagrees. The claimed feature merely use GNN model using quantitative scoring to determine a plurality of candidate deployment plans. There is no improvement of GNN model itself but use backpropagation algorithm and gradient descent algorithm wherein the failure prediction model is a Graph Neural Network model configured to receive the candidate deployment graph as input and output predicted future failure probability of each individual node. Therefore, GNN is mathematical calculations similar to claim 2 in example 47 that is not related to example 45.
On the page 5 of the Remarks, Applicant alleges that “[E]ven assuming arguendo that the pending claims are directed to an abstract idea, amended claim 1 recites elements that qualify as "significantly more" under considerations endorsed by M.P.E.P. § 2106.05. The claimed invention provides an improvement to another technology by reciting the full physical linkage of "hardware collection - platform computation - model deduction - parameter output - field construction," which improves the safety and disposal efficiency of the pipeline network. This entire set of processes is not a conventional activity generally known in this field. The overall solution solves industry technical pain points such as strong subjectivity in traditional gas emergency assessments, insufficient risk prediction, lack of quantitative standards for on- site construction, and unreasonable emergency dispatching, bringing substantive technical improvements in pipeline network emergency safety, disposal efficiency, and operation precision.”
Examiner respectfully disagrees. Applicant has argued that the abstract idea itself is significant. However, an abstract idea itself is just that, abstract, and whether such feature is or is not significant does not preclude it from being considered abstract. An abstract idea by itself, whether it or not it has a benefit, does not reasonably overcome a 101 rejection because it is still an abstract idea. Applicant has not, respectfully, demonstrated with evidence why the abstract idea itself would amount to more than an abstract idea. Therefore, the above advantages relate to abstract idea limitations which are not considered. The Improvements in the abstract idea are not qualified as improvements indicating a practical application. Therefore, the pending claims are not patent eligible since a claim for a new abstract idea is still an abstract idea (see MPEP 2106.05(a).I) and an improvement in the abstract idea itself is not an improvement in technology (see MPEP 2106.05(a).II: Examples that the courts have indicated may not be sufficient to show an improvement to technology include: iii. Gathering and analyzing information using conventional techniques and displaying the result, TLI Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48)). Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Claim 1 does not present tangible or physical elements/components and/or integration of improvements to be indicative of specific features/structure/acts, for example, how and or with what to determine the deployment plan for the gas emergency vehicle which is associated with improving the safety and disposal efficiency of the pipeline network . Therefore, the claims have no significance more beyond the abstract idea. This is just a processor running algorithm related to mental processes and mathematical calculations. Similar limitations comprise the abstract ideas of Claims 12 and 20. Therefore, the independent claims 1, 12, and 20 are ineligible.
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 1-20 are rejected under 35 U.S.C. 101 because 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:
A method for assessing a smart gas emergency plan, executed by a smart gas safety management platform that performs bidirectional data interaction with a smart gas sensor network platform and a smart gas object platform, comprising:
obtaining a warning information distribution of a gas pipeline network via safety- related pipeline operational data acquired from monitoring and alarm devices deployed on gas pipeline facilities and transmitted to the smart gas safety management platform through the smart gas sensor network platform, the safety-related pipeline operational data including perceptual information generated by the monitoring and alarm devices of the smart gas object platform, the warning information distribution including warning information of at least one warning point location, the warning point location being a pipeline currently sending an alarm, wherein at least one associated point location is screened and derived from synchronized anomaly point locations pre-determined according to warning point feature parameters and historical anomaly statistics;
obtaining gas monitoring data of at least one associated point location corresponding to the at least one warning point location, the at least one associated point location being adjacent to the warning point location;
determining, based on the warning information distribution and the gas monitoring data of the at least one associated point location, at least one emergency processing point; and
wherein the at least one emergency processing point physically includes a point to be repaired, a point to be supplied with gas, and a point to be reinforced; the point to be repaired corresponds to a pipeline with abnormal damage including cracking, deformation or gas leakage requiring on-site maintenance: the point to be supplied with gas corresponds to a downstream pipeline of a faulty pipeline requiring temporary gas supply compensation to guarantee user gas consumption; the point to be reinforced corresponds to a aging or high-risk pipeline prone to rupture requiring structural reinforcement;
determining, based on a gas supply blockage range of the at least one emergency processing point, a deployment plan for a gas emergency vehicle, wherein the generated deployment plan is forwarded via a smart gas service platform to vehicle- mounted control terminals pre-installed on physical emergency vehicles, the deployment plan configured for physical field operation implementation by actual emergency vehicle hardware includes crossover construction, temporary gas supply and pressure regulation hardware units equipped on on-site gas emergency vehicles;
wherein the determining, based on a gas supply blockage range of the at least one emergency processing point, a deployment plan for a gas emergency vehicle includes:
determining a plurality of candidate deployment plans;
constructing, based on the gas pipeline network, the at least one emergency processing point, and the plurality of candidate deployment plans, a plurality of candidate deployment graphs; wherein nodes of each candidate deployment graph include multiple physical entity node types covering emergency gas supply nodes with crossover and gas supply parameter features, emergency maintenance nodes with pipeline failure type and failure time features, emergency reinforcement nodes with pipeline reinforcement parameter features, and non-emergency pipeline nodes with gas pipeline inherent features and gas transportation operation features; edges of each candidate deployment graph represent actual physical connectivity and pipeline connection relationship between corresponding pipeline point locations in a real gas pipeline network;
for each candidate deployment graph, determining, based on a failure prediction model, a failure probability of each node in the candidate deployment graph at at least one future moment, wherein the failure prediction model is a Graph Neural Network model configured to receive the candidate deployment graph as input and output predicted future failure probability of each individual node;
determining, based on a failure probability set and an estimated impact degree set for each of the plurality of the candidate deployment graphs, a target deployment graph;
wherein each candidate deployment graph is scored through weighted summation calculation expressed by a formula
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, wherein A stands for total evaluation score of the candidate deployment graph, n is a total number of nodes contained in the candidate deployment graph,
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, represents failure probability of an i-th node,
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represents estimated impact degree of the i-th node, and a candidate deployment graph having a minimum calculated score is selected as the target deployment graph;
determining, based on the target deployment graph, the deployment plan for the gas emergency vehicle, wherein the deployment plan defines exclusive physical construction parameters for on-site emergency operation, the physical construction parameters comprising crossover parameters including crossover position, pipeline connection mode and crossover pipe diameter, gas supply parameters including real- time gas supply flow rate and gas supply pressure, and pressure regulation parameters including pressure regulation range and pressure regulation amplitude for field gas pipeline emergency operation.
The claim limitations in the abstract idea have been highlighted in bold above; the remaining limitations are “additional elements.”
Step 1: 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).
Step 2A, Prong One: 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 exceptions. Specifically, under the 2019 Revised Patent Subject matter Eligibility Guidance, it falls into the groupings of subject matter when recited as such in a claim limitation that 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, the limitations of “determining, based on the warning information distribution and the gas monitoring data of the at least one associated point location (para. [0062]), at least one emergency processing point (see paras. [0082]-[0085], [0091], [0095]-[0096] of instant application),” “wherein the at least one emergency processing point physically includes a point to be repaired, a point to be supplied with gas, and a point to be reinforced; the point to be repaired corresponds to a pipeline with abnormal damage including cracking, deformation or gas leakage requiring on-site maintenance: the point to be supplied with gas corresponds to a downstream pipeline of a faulty pipeline requiring temporary gas supply compensation to guarantee user gas consumption; the point to be reinforced corresponds to a aging or high-risk pipeline prone to rupture requiring structural reinforcement (see paras. [0085]-[0094] of instant application)” is mental process based on mathematical expression. The limitation of the warning information distribution and the gas monitoring data of the at least one associated point location is a mathematical expression to be performed by abstract ( see MPEP 2106.04(a)(2)C states that There is no particular word or set of words that indicates a claim recites a mathematical calculation. That is, a claim does not have to recite the word "calculating" in order to be considered a mathematical calculation. 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).
“determining, based on a gas supply blockage range of the at least one emergency processing point (paras. [0095]-[0097]), a deployment plan for a gas emergency vehicle (see paras. [0100]-[0109] ),” “wherein the generated deployment plan is forwarded via a smart gas service platform to vehicle- mounted control terminals pre-installed on physical emergency vehicles, the deployment plan configured for physical field operation implementation by actual emergency vehicle hardware includes crossover construction, temporary gas supply and pressure regulation hardware units equipped on on-site gas emergency vehicles (see paras. [0086], [0098]-[0108] of instant application),” are mental process based on mathematical calculations. The limitation of a gas supply blockage range of the at least one emergency processing point is a mathematical expression to be performed by abstract (see MPEP 2106.04(a)(2)C). “wherein the determining, based on a gas supply blockage range of the at least one emergency processing point, a deployment plan for a gas emergency vehicle includes determining a plurality of candidate deployment plans (see para. [0095]-[0097], [0108], [0139]-[0141] of instant application)” is mental process based on mathematical calculations. The limitation of a gas supply blockage range of the at least one emergency processing point is a mathematical expression to be performed by abstract (see MPEP 2106.04(a)(2)C). Further, the limitation of “a gas emergency vehicle including determining a plurality of candidate deployment plans” merely defines or describes the candidate deployment plans that is performed by an abstract idea.
“for each candidate deployment graph, determining, based on a failure prediction model, a failure probability of each node in the candidate deployment graph at at least one future moment, wherein the failure prediction model is a Graph Neural Network model configured to receive the candidate deployment graph as input and output predicted future failure probability of each individual node (see paras. [0114]-[0120], [0139]-[0149] of instant application),” is mental process based on mathematical calculations. The limitation of a failure probability of each node in the candidate deployment graph at at least one future moment, using GNN , based on a failure prediction model is an indicative of mathematical calculations.
“determining, based on a failure probability set and an estimated impact degree set for each of the plurality of the candidate deployment graphs, a target deployment graph (see para. [0139] of instant application),” “wherein each candidate deployment graph is scored through weighted summation calculation expressed by a formula
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, wherein A stands for total evaluation score of the candidate deployment graph, n is a total number of nodes contained in the candidate deployment graph,
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, represents failure probability of an i-th node,
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represents estimated impact degree of the i-th node, and a candidate deployment graph having a minimum calculated score is selected as the target deployment graph (see paras. [0166]-[0170] of instant application),” is mental process based on mathematical calculations. The limitation of a failure probability set and an estimated impact degree set for each of the plurality of the candidate deployment graphs is an indicative of mathematical calculations.
“determining, based on the target deployment graph, the deployment plan for the gas emergency vehicle,” wherein the deployment plan defines exclusive physical construction parameters for on-site emergency operation, the physical construction parameters comprising crossover parameters including crossover position, pipeline connection mode and crossover pipe diameter, gas supply parameters including real- time gas supply flow rate and gas supply pressure, and pressure regulation parameters including pressure regulation range and pressure regulation amplitude for field gas pipeline emergency operation (see para. [0098]-[0114], [0151] of instant application)” are mental processes based on mathematical calculations. The limitation of the target deployment graph is an indicative of mathematical calculations. The detail description of the deployment plan for the gas emergency vehicle merely defines or describes the deployment plan that is performed by an abstract idea.
The limitation of “constructing, based on the gas pipeline network, the at least one emergency processing point, and the plurality of candidate deployment plans, a plurality of candidate deployment graphs; wherein nodes of each candidate deployment graph include multiple physical entity node types covering emergency gas supply nodes with crossover and gas supply parameter features, emergency maintenance nodes with pipeline failure type and failure time features, emergency reinforcement nodes with pipeline reinforcement parameter features, and non-emergency pipeline nodes with gas pipeline inherent features and gas transportation operation features; edges of each candidate deployment graph represent actual physical connectivity and pipeline connection relationship between corresponding pipeline point locations in a real gas pipeline network” is mathematical calculations. The limitations of “nodes of each candidate deployment graph including parameters” and “nodes of each candidate deployment graph” is an indicative of mathematical calculations. If a claim limitation, under its broadest reasonable interpretation, covers human mind and mathematical calculations, then it falls within “Mental Processes” and “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Similar limitations comprise the abstract ideas of Claims 12 and 20.
Step 2A, Prong Two: 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. This judicial exception is not integrated into a practical application. Therefore, none of the additional elements indicate a practical application.
Therefore, the claims are directed to a judicial exception and require further analysis under the Step 2B.
Step 2B:
The above claims comprise the following additional elements:
In Claim 1: a method for assessing a smart gas emergency plan, executed by a smart gas safety management platform that performs bidirectional data interaction with a smart gas sensor network platform and a smart gas object platform (preamble); obtaining a warning information distribution of a gas pipeline network via safety- related pipeline operational data acquired from monitoring and alarm devices deployed on gas pipeline facilities and transmitted to the smart gas safety management platform through the smart gas sensor network platform, the safety-related pipeline operational data including perceptual information generated by the monitoring and alarm devices of the smart gas object platform, the warning information distribution including warning information of at least one warning point location, the warning point location being a pipeline currently sending an alarm, wherein at least one associated point location is screened and derived from synchronized anomaly point locations pre-determined according to warning point feature parameters and historical anomaly statistics; obtaining gas monitoring data of at least one associated point location corresponding to the at least one warning point location, the at least one associated point location being adjacent to the warning point location;
In Claim 12: an Internet of Things (loT) system for assessing a smart gas emergency plan including a smart gas user platform, a smart gas service platform, a smart gas safety management platform, a smart gas sensor network platform, and a smart gas object platform (preamble); obtaining a warning information distribution of a gas pipeline network via safety- related pipeline operational data acquired from monitoring and alarm devices deployed on gas pipeline facilities and transmitted to the smart gas safety management platform through the smart gas sensor network platform, the safety-related pipeline operational data including perceptual information generated by the monitoring and alarm devices of the smart gas object platform, the warning information distribution including warning information of at least one warning point location, the warning point location being a pipeline currently sending an alarm, wherein at least one associated point location is screened and derived from synchronized anomaly point locations pre-determined according to warning point feature parameters and historical anomaly statistics; obtaining gas monitoring data of at least one associated point location corresponding to the at least one warning point location, the at least one associated point location being adjacent to the warning point location; and
In Claim 20: a non-transitory computer-readable storage medium storing computer instructions, wherein when reading the computer instructions in the storage medium, a computer implements the method for assessing a smart gas emergency plan (preamble); obtaining a warning information distribution of a gas pipeline network via safety- related pipeline operational data acquired from monitoring and alarm devices deployed on gas pipeline facilities and transmitted to the smart gas safety management platform through the smart gas sensor network platform, the safety-related pipeline operational data including perceptual information generated by the monitoring and alarm devices of the smart gas object platform, the warning information distribution including warning information of at least one warning point location, the warning point location being a pipeline currently sending an alarm, wherein at least one associated point location is screened and derived from synchronized anomaly point locations pre-determined according to warning point feature parameters and historical anomaly statistics; obtaining gas monitoring data of at least one associated point location corresponding to the at least one warning point location, the at least one associated point location being adjacent to the warning point location;
The additional elements such as the Internet of Things (IoT) system, a non-transitory computer-readable storage medium and computer in claims 1, 12, and 20 are recited at a high-level of generality without descriptions of its specific structure/features to perform the claimed features for producing the metal processes addressed above (MPEP 2106.05(d)).
Further, the additional element of “a method for assessing a smart gas emergency plan, executed by a smart gas safety management platform that performs bidirectional data interaction with a smart gas sensor network platform and a smart gas object platform,” “an Internet of Things (loT) system for assessing a smart gas emergency plan including a smart gas user platform, a smart gas service platform, a smart gas safety management platform, a smart gas sensor network platform, and a smart gas object platform,” and “a non-transitory computer-readable storage medium storing computer instructions, wherein when reading the computer instructions in the storage medium, a computer implements the method for assessing a smart gas emergency plan” are preamble statements reciting purpose or intended use (See MPEP 2111.02)(II)).
Further, note that step of “obtaining a warning information distribution of a gas pipeline network via safety- related pipeline operational data acquired from monitoring and alarm devices deployed on gas pipeline facilities and transmitted to the smart gas safety management platform through the smart gas sensor network platform, the safety-related pipeline operational data including perceptual information generated by the monitoring and alarm devices of the smart gas object platform, the warning information distribution including warning information of at least one warning point location, the warning point location being a pipeline currently sending an alarm, wherein at least one associated point location is screened and derived from synchronized anomaly point locations pre-determined according to warning point feature parameters and historical anomaly statistics” and “obtaining gas monitoring data of at least one associated point location corresponding to the at least one warning point location, the at least one associated point location being adjacent to the warning point location;” are insignificant (gathering data) extra-solution activity to perform abstract idea that is mental processes (i.e. determining at least one emergency processing point and determining a deployment plan for a gas emergency vehicle) (MPEP 2106.05(g)).
Claim 1 does not present tangible or physical elements/components and/or integration of improvements to be indicative of specific features/structure/acts, for example, how and or with what to determine the deployment plan for the gas emergency vehicle. Further, an abstract idea itself is just that, abstract, and whether such feature is or is not significant does not preclude it from being considered abstract. An abstract idea by itself, whether it or not it has a benefit, does not reasonably overcome a 101 rejection because it is still an abstract idea. Therefore, the above advantages relate to abstract idea limitations which are not considered. The Improvements in the abstract idea are not qualified as improvements indicating a practical application. The pending claims are not patent eligible since a claim for a new abstract idea is still an abstract idea (see MPEP 2106.05(a).I) and an improvement in the abstract idea itself is not an improvement in technology (see MPEP 2106.05(a).II and MPEP 2106.05(a).II: Examples that the courts have indicated may not be sufficient to show an improvement to technology include: iii. Gathering and analyzing information using conventional techniques and displaying the result, TLI Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48)). Therefore, the claims have no significance more beyond the abstract idea. This is just a processor running algorithm related to mental processes and mathematical calculations. Similar limitations comprise the abstract ideas of Claims 12 and 20. Therefore, the independent claims 1, 12, and 20 are ineligible.
Regarding claims 2-8, 10-11, and 13-18,
All features recited in these claims are abstract ideas, as all features found in these claims are directed towards metal processes or mathematical calculations steps. The explanation for the rejection of Claims 2-8, 10-11, and 13-18therefore are incorporated herein and applied to Claims 1 and 12. These claims therefore stand rejected for similar reasons as explained in above Claims 1 and 12.
No prior art is being applied to Claims 1-8, 10-18, and 20 because the prior art does not disclose or make obvious “wherein the at least one emergency processing point physically includes a point to be repaired, a point to be supplied with gas, and a point to be reinforced; the point to be repaired corresponds to a pipeline with abnormal damage including cracking, deformation or gas leakage requiring on-site maintenance: the point to be supplied with gas corresponds to a downstream pipeline of a faulty pipeline requiring temporary gas supply compensation to guarantee user gas consumption; the point to be reinforced corresponds to a aging or high-risk pipeline prone to rupture requiring structural reinforcement; determining, based on a gas supply blockage range of the at least one emergency processing point, a deployment plan for a gas emergency vehicle, wherein the generated deployment plan is forwarded via a smart gas service platform to vehicle- mounted control terminals pre-installed on physical emergency vehicles, the deployment plan configured for physical field operation implementation by actual emergency vehicle hardware includes crossover construction, temporary gas supply and pressure regulation hardware units equipped on on-site gas emergency vehicles; wherein the determining, based on a gas supply blockage range of the at least one emergency processing point, a deployment plan for a gas emergency vehicle includes: determining a plurality of candidate deployment plans; constructing, based on the gas pipeline network, the at least one emergency processing point, and the plurality of candidate deployment plans, a plurality of candidate deployment graphs; wherein nodes of each candidate deployment graph include multiple physical entity node types covering emergency gas supply nodes with crossover and gas supply parameter features, emergency maintenance nodes with pipeline failure type and failure time features, emergency reinforcement nodes with pipeline reinforcement parameter features, and non-emergency pipeline nodes with gas pipeline inherent features and gas transportation operation features; edges of each candidate deployment graph represent actual physical connectivity and pipeline connection relationship between corresponding pipeline point locations in a real gas pipeline network; for each candidate deployment graph, determining, based on a failure prediction model, a failure probability of each node in the candidate deployment graph at at least one future moment, wherein the failure prediction model is a Graph Neural Network model configured to receive the candidate deployment graph as input and output predicted future failure probability of each individual node; determining, based on a failure probability set and an estimated impact degree set for each of the plurality of the candidate deployment graphs, a target deployment graph; wherein each candidate deployment graph is scored through weighted summation calculation expressed by a formula
A
=
∑
i
=
1
n
x
i
×
y
i
, wherein A stands for total evaluation score of the candidate deployment graph, n is a total number of nodes contained in the candidate deployment graph,
x
i
, represents failure probability of an i-th node,
y
i
represents estimated impact degree of the i-th node, and a candidate deployment graph having a minimum calculated score is selected as the target deployment graph; determining, based on the target deployment graph, the deployment plan for the gas emergency vehicle, wherein the deployment plan defines exclusive physical construction parameters for on-site emergency operation, the physical construction parameters comprising crossover parameters including crossover position, pipeline connection mode and crossover pipe diameter, gas supply parameters including real- time gas supply flow rate and gas supply pressure, and pressure regulation parameters including pressure regulation range and pressure regulation amplitude for field gas pipeline emergency operation,” as currently claimed, in the combination, and as best understood.
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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/SANGKYUNG LEE/Examiner, Art Unit 2858
/LEE E RODAK/Supervisory Patent Examiner, Art Unit 2858
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