CTNF 18/962,716 CTNF 99179 Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. DETAILED ACTION Claims 1-20 are pending. Claims 1, 11, and 16 are independent. This Application was published as US 20260147819. Apparent priority is 27 November 2024. The instant Application is directed to a method of enriching telemetry data. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Step 1: The independent Claims are directed to statutory categories: Claim 1 is a method claim and directed to the process category of patentable subject matter. Claim 11 is a computer program product claim and is directed to the machine or manufacture category of patentable subject matter. Claim 16 is a device claim and directed to the machine or manufacture category of patentable subject matter. Step 2A, Prong One: Does the Claim recite a Judicially Recognized Exception? Abstract Idea? Are these Claims nevertheless considered Abstract as a Mathematical Concept (mathematical relationships, mathematical formulas or equations, mathematical calculations), Mental Process (concepts performed in the human mind (including an observation, evaluation, judgment, opinion), or Certain Methods of Organizing Human Activity (1-fundamental economic principles or practices (including hedging, insurance, mitigating risk), 2-commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations), 3- managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) and fall under the judicial exception to patentable subject matter?) The rejected Claims recite Mental Processes as further detailed below. Step 2A, Prong Two: Additional Elements that Integrate the Judicial Exception into a Practical Application? Identifying whether there are any additional elements recited in the claim beyond the judicial exception(s), and evaluating those additional elements to determine whether they integrate the exception into a practical application of the exception. “Integration into a practical application” requires an additional element(s) or a combination of additional elements in the claim to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception. Uses the considerations laid out by the Supreme Court and the Federal Circuit to evaluate whether the judicial exception is integrated into a practical application. The rejected Claims do not include additional limitations that point to integration of the abstract idea into a practical application and are therefore directed to a Mental Process . Claim 1 is a generic automation of a mental process because a human agent can obtain telemetry data, semantically enrich it by adding metadata such as a category, analyze it, and update a processing system based on the data. Prong Two of step 2A in the 101 analysis asks whether the abstract idea is integrated with a practical application. The answer is no in this instance because there is no technological solution in the Claim that “integrates” the abstract idea. The Claim only suggests that the abstract idea be applied. It does not describe an application. 1. A method of managing operation of data processing systems, the method comprising: obtaining, by a management system, at least a portion of telemetry data generated by the data processing systems, (agent reads a printout of telemetry data) the portion of telemetry data being indicated as requiring semantic enrichment based on semantic enrichment classifications; (agent sees that the data is marked as needing enrichment) obtaining, by the management system and using the portion of telemetry data, semantically enriched telemetry data based on a defined ontology; (agent labels the data according to defined categories) analyzing, by the management system, the semantically enriched telemetry data to obtain an analysis outcome; (agent sees that server A is not responding correctly) updating operation of the data processing systems based on the analysis outcome to obtain updated data processing systems; and (agent reboots server A) providing computer-implemented services using the updated data processing systems. (server A now correctly provides services) Step 2B: Search for Inventive Concept: Additional Element Do not amount to Significantly More : The limitations of "data processing systems" and “management system” are generic computers, according to [0050] of the specification, which are well-understood, routine, and conventional machine components that are being used for their well-understood, routine, and conventional and rather generic functions. Additionally, these limitations are expressed parenthetically and lack nexus to the Claim language and as such are a separable and divisible mention to a machine. Accordingly, they are not sufficient to cause the Claim to amount to significantly more than the underlying abstract idea. The Dependent Claims do not add limitations that could help the Claim as a whole to amount to significantly more than the Abstract idea identified for the Independent Claim: 2. The method of claim 1, further comprising: prior to obtaining the at least the portion of the telemetry data: obtaining, by the management system, a second portion of telemetry data from the data processing systems, the second portion of telemetry data being based on operation of the data processing systems; (agent reads a printout of data prior to the steps of claim 1) making, by the management system, a determination regarding whether the second portion of telemetry data is acceptable for use in a process; and (agent determines that the data is not categorized) in a first instance of the determination where the second portion of the telemetry data is not acceptable: establishing at least one of the semantic enrichment classifications based on the determination, the at least one of the semantic enrichment classifications indicating that the portion of the telemetry data is to be semantically enriched. (agent marks the data as needing to be enriched) 3. The method of claim 2, wherein making the determination comprises: sampling the second portion of the telemetry data to obtain samples; (agent picks 10 data points) identifying a ratio between a cardinality of a first portion of the samples that are usable in the process to a cardinality of the samples; (agent sees that 2 of the 10 data points need to be categorized) comparing the ratio to a threshold ratio; and (agent compares to the threshold that 90% of data must be categorized) in an instance of the comparing where the ratio does not meet the threshold ratio: concluding that the second portion of the telemetry data is not acceptable for use in the process. (agent concludes that the data is not acceptable) 4. The method of claim 3, wherein the threshold ratio is based on the process, and different threshold ratios are associated with different processes based on data needs of the different processes. (agent reads a chart which shows the thresholds for each process) 5. The method of claim 1, where the semantic enrichment classifications are based, at least in part, on an unacceptable usability of the at least the portion of the telemetry data in a process, and the semantically enriched telemetry data being acceptably usable in the process. (agent classifies the data that is marked needing categorization, and afterwards checks that it is usable) 6. The method of claim 3, wherein the process presumes that a first set of metadata for the at least the portion of the telemetry data is available, and (agent presumes that the data fits a valid category) the at least the portion of the telemetry data lacks at least a portion of the first set of metadata due to a different defined ontology used in generating metadata for the at least the portion of the telemetry data. (agent sees that the data does not have a valid category assigned) 7. The method of claim 4, wherein the at least the portion of the telemetry data is deemed to have an unacceptable usability due to a magnitude of difference between a different defined ontology and the defined ontology. (agent determines the data is unacceptable because 90% of the metadata is invalid) 8. The method of claim 1, wherein analyzing the semantically enriched telemetry data comprises: generating a dashboard based on the semantically enriched telemetry data; and (agent draws a graph of the data classifications) obtaining user input via the dashboard. (agent’s supervisor circles the data related to server A) 9. The method of claim 8, wherein updating the operation of the data processing systems comprises: modifying operation of at least one of the data processing systems based on the user input. (agent reboots server A based on the input) 10. The method of claim 1, wherein obtaining the semantically enriched telemetry data based on the defined ontology comprises at least one selected from a list of operations consisting of: replacing existing metadata with new metadata based on the defined ontology; and adding different metadata based on the defined ontology to the existing metadata. (agent adds categorization if it is missing, or crosses it out and adds a new category if it is invalid) The additional limitations introduced by the Dependent Claims are not sufficient as additional elements that integrate the judicial exception into a practical application or as additional elements that cause the Claim as a whole to amount to substantially more than the underlying abstract idea. With respect to Independent Claim 11 and independent Claim 16 , which have limitations similar to the limitations of Claim 1, the limitations of “non-transitory machine-readable medium,” “processor,” and “memory” are expressed parenthetically and lack nexus to the Claim language and as such are a separable and divisible mention to a machine. Accordingly, they do not include additional limitations that cause the Claim as a whole to amount to more than the underlying abstract idea. The Dependent Claims 12-15 and 17-20 are similar to claims 2-5 and do not add limitations that could integrate the judicial exception into a practical application or help the Claim as a whole to amount to significantly more than the Abstract idea identified for the Independent Claim. Claim Rejections - 35 USC § 102 07-07-aia AIA 07-07 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – 07-08-aia AIA (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. 07-15-aia AIA Claim(s) 1, 8-11, and 16 is/are rejected under 35 U.S.C. 102 (a)(1) as being anticipated by Crabtree et al. (US 20210019674 A1) . Regarding claim 1, Crabtree discloses: 1 . A method of managing operation of data processing systems, the method comprising: obtaining, by a management system, at least a portion of telemetry data generated by the data processing systems, ("[0146] FIG. 18 is a flow diagram of an exemplary method 1800 for risk-based vulnerability and patch management. According to the aspect, an advanced cyber decision platform may monitor all information about a network 1801, including (but not limited to) device telemetry data , log files, connections and network events, deployed software versions, or contextual user activity information..." ) the portion of telemetry data being indicated as requiring semantic enrichment based on semantic enrichment classifications ; ("[0126] The data then flows to a comprehension engine 2811 which using the same semantic computing techniques (e.g., Amazon Comprehend, SpaCy, IBM Watson Tone Analyzer) parses through the information determining relational attributes to the search query 3120..." – the relational attributes read on classifications. As mapped below, this data is then semantically enriched.) obtaining, by the management system and using the portion of telemetry data, semantically enriched telemetry data based on a defined ontology; ("[0126]... This process appends data with temporal, geospatial (geoJSON formatted), information reliability, and contextual metadata as determined by the system's 3110 machine learning algorithms and ontological axioms configuration." ) analyzing, by the management system, the semantically enriched telemetry data to obtain an analysis outcome; ("[0146]...This information is incorporated into a CPG 1802 to maintain an up-to-date model of the network in real-time. When a new vulnerability is discovered, a blast radius score may be assessed 1803 and the network's resiliency score may be updated 1804 as needed..." ) updating operation of the data processing systems based on the analysis outcome to obtain updated data processing systems; and ("[0146].... A security alert may then be produced 1805 to notify an administrator of the vulnerability and its impact, and a proposed patch may be presented 1806 along with the predicted effects of the patch on the vulnerability's blast radius and the overall network resiliency score..." ) providing computer-implemented services using the updated data processing systems. ([0093] discloses that systems are provided based on hardware or software updates. ) Regarding claim 8, Crabtree discloses : 8. The method of claim 1, wherein analyzing the semantically enriched telemetry data comprises: generating a dashboard based on the semantically enriched telemetry data; and ("[0095]... As previously disclosed 200, 351, one of the strengths of the advanced cyber-decision platform is the ability to finely customize reports and dashboards to specific audiences, concurrently is appropriate..." ) obtaining user input via the dashboard. ("[0005]...The system and method allow a user to query an individual or business and returns a profile and a rating associated with the relationship risk of that entity…"; see also Fig. 1 shows Client Access 105 which is used for both input and output. ) Regarding claim 9, Crabtree discloses : 9. The method of claim 8, wherein updating the operation of the data processing systems comprises: modifying operation of at least one of the data processing systems based on the user input. ("[0148] ... Finally, the computer-generated analysis would be subject to human review and correction 3005, improving the machine learning algorithm's accuracy in future analyses." – the machine learning algorithm is a data processing system and is modified based on user input.) Regarding claim 10, Crabtree discloses: 10. The method of claim 1, wherein obtaining the semantically enriched telemetry data based on the defined ontology comprises at least one selected from a list of operations consisting of: replacing existing metadata with new metadata based on the defined ontology; and adding different metadata based on the defined ontology to the existing metadata. ("[0053] Once the ontological databases are created or updated , where the data has been organized into typical ontological data structures e.g., classes, attributes, relations, axioms, etc., a knowledge graph is generated which may be presented to the user for advanced insight and analysis into the risk factors and relationships associated with the queried entity, but also is used by the system to answer additional queries through various procedures. " Creating the database adds different metadata, and updating the database replaced existing metadata.) Claim 11 is a medium claim with limitations corresponding to the limitations of Claim 1 and is rejected under similar rationale. Additionally, a non-transitory machine-readable medium of the Claim are taught by Crabtree (Mem 43, fig. 37) Claim 16 is a device claim with limitations corresponding to the limitations of Claim 1 and is rejected under similar rationale. Additionally, a processor and a memory of the Claim are taught by Crabtree (CPU 41; Mem 43, fig. 37) Claim Rejections - 35 USC § 103 07-20-aia AIA The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. 07-23-aia AIA The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. 07-21-aia AIA Claim (s) 2, 5-6, 12, 15, 17, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Crabtree in view of Chen (US 20100281061 A1) . Regarding claim 2, Crabtree discloses: 2. The method of claim 1, further comprising: prior to obtaining the at least the portion of the telemetry data: obtaining, by the management system, a second portion of telemetry data from the data processing systems, the second portion of telemetry data being based on operation of the data processing systems; ([0138] discloses that the data is collected continuously over time.) making, by the management system, a determination regarding whether the second portion of telemetry data is acceptable for use in a process; and (not explicitly disclosed ) in a first instance of the determination where the second portion of the telemetry data is not acceptable: establishing at least one of the semantic enrichment classifications based on the determination, the at least one of the semantic enrichment classifications indicating that the portion of the telemetry data is to be semantically enriched. (not explicitly disclosed) Crabtree does not explicitly disclose determining if the telemetry data is acceptable. Chen discloses: making, by the management system, a determination regarding whether the second portion of telemetry data is acceptable for use in a process; and ("0011- …A first node in the nodes is analyzed using an inference algorithm in a processor of a computer. The analyzing determines a semantic error in a data corresponding to the schema artifact represented at a second node. A correction for the data is provided to a data storage unit in a data processing system, a display in a data processing system, or a combination thereof, such that the correction eliminates the semantic error." ; see also [0007]-[0009] which disclose detecting errors and inaccuracies) in a first instance of the determination where the second portion of the telemetry data is not acceptable: establishing at least one of the semantic enrichment classifications based on the determination, the at least one of the semantic enrichment classifications indicating that the portion of the telemetry data is to be semantically enriched. ("0011- …A first node in the nodes is analyzed using an inference algorithm in a processor of a computer. The analyzing determines a semantic error in a data corresponding to the schema artifact represented at a second node . A correction for the data is provided to a data storage unit in a data processing system, a display in a data processing system, or a combination thereof, such that the correction eliminates the semantic error." ) Crabtree and Chen are considered analogous art to the claimed invention because they disclose data processing methods. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Crabtree with detecting data errors as disclosed by Chen. Doing so would have been beneficial so that inaccurate data could be corrected. (Chen [0009]) Regarding claim 5, Crabtree does not disclose the additional limitations. Chen discloses: 5. The method of claim 1, where the semantic enrichment classifications are based, at least in part, on an unacceptable usability of the at least the portion of the telemetry data in a process, and the semantically enriched telemetry data being acceptably usable in the process. (“[0071] An application can implement semantic data validation of the disjoint data by configuring personal and business data in the manner of FIG. 3. The semantic validation according to an embodiment of the invention may draw conclusion 320 that a person cannot be younger than the person's work experience. Thus, in this example, semantic validation of disjoint personal and business data can lead to a correction either the person's birthday or the person's years-of-experience, or both, which would otherwise not be possible by presently available statistical or syntactical methods.” The data is unacceptable if it is logically incorrect, and it is acceptable once corrected.) See claim 2 for motivation statement. Regarding claim 6, Crabtree discloses: 6. The method of claim 3, wherein the process presumes that a first set of metadata for the at least the portion of the telemetry data is available, and (“[0119] FIG. 25 is a block diagram showing an embodiment 2501 in which ontologies are generated by the automated ontology engine 2501 and used to provide semantic search capabilities through a semantic search engine 102. In this embodiment, the automated ontology generator 2502 receives information 2503 from a variety of public and private sources.”) the at least the portion of the telemetry data lacks at least a portion of the first set of metadata due to a different defined ontology used in generating metadata for the at least the portion of the telemetry data. (“[0119]… The results of the query context analyzer would be sent to the automated ontology shifter 2514, which would compare the query analysis with the complex index database to determine the user's intent, even where such intent is unstated …”) Claim 12 is a medium claim with limitations corresponding to the limitations of Claim 2 and is rejected under similar rationale. Claim 15 is a medium claim with limitations corresponding to the limitations of Claim 5 and is rejected under similar rationale. Claim 17 is a device claim with limitations corresponding to the limitations of Claim 2 and is rejected under similar rationale. Claim 20 is a device claim with limitations corresponding to the limitations of Claim 5 and is rejected under similar rationale . 07-21-aia AIA Claim (s) 3-4, 13-14, and 18-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Crabtree in view of Chen as applied in claim 3 above, further in view of Wallbaum et al. (US 20150281025 A1) . Regarding claim 3, Crabtree and Chen do not disclose the additional limitations. Wallbaum discloses: 3. The method of claim 2, wherein making the determination comprises: sampling the second portion of the telemetry data to obtain samples; identifying a ratio between a cardinality of a first portion of the samples that are usable in the process to a cardinality of the samples; ("[0034] According to a further exemplary embodiment of the invention, a respective media stream is determined to be periodically impaired, in case the maximum exists in the media stream's frequency distribution for a given number of (consecutive) good quality data records and, in addition, the number of accounted quality data records for a given number of (consecutive) good quality data records in the media stream's frequency distribution exceeds a threshold percentage of all quality data records that have been accounted for in the media stream's frequency distribution. The threshold percentage may be for example 50% or more." - Under the broadest reasonable interpretation, each data point being analyzed is a sample. The number of good quality data records is the cardinality of the usable portion of samples. All quality data records is the cardinality of the samples.) comparing the ratio to a threshold ratio; and in an instance of the comparing where the ratio does not meet the threshold ratio: concluding that the second portion of the telemetry data is not acceptable for use in the process. ("[0034] According to a further exemplary embodiment of the invention, a respective media stream is determined to be periodically impaired , in case the maximum exists in the media stream's frequency distribution for a given number of (consecutive) good quality data records and, in addition, the number of accounted quality data records for a given number of (consecutive) good quality data records in the media stream's frequency distribution exceeds a threshold percentage of all quality data records that have been accounted for in the media stream's frequency distribution. The threshold percentage may be for example 50% or more." – data that is impaired is not acceptable for the process.) Crabtree, Chen, and Wallbaum are considered analogous art to the claimed invention because they disclose data processing methods. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination with a threshold percentage as disclosed by Wallbaum. Doing so would have been beneficial so that inaccurate data could be corrected. (Chen [0009]) This combination falls under combining prior art elements according to known methods to yield predictable results or simple substitution of one known element for another to obtain predictable results. See MPEP 2141, KSR, 550 U.S. at 418, 82 USPQ2d at 1396. Regarding claim 4, Crabtree and Chen do not disclose the additional limitations. Wallbaum discloses: 4. The method of claim 3, wherein the threshold ratio is based on the process, and different threshold ratios are associated with different processes based on data needs of the different processes. ("[0035] In another exemplary embodiment of the invention, a periodic impairment of a respective media stream is only determined, in case the maximum exists in the media stream's frequency distribution for a given number of (consecutive) good quality data records and, in addition, the ratio between the total number of quality data records accounted for in the frequency distribution and the total number of quality data records of the media stream indicating an impairment of the media stream is below an impairment threshold ratio . The impairment threshold ratio may be for example 33%, 25% or another lower percentage/value ." ) See claim 3 for motivation statement. Claim 13 is a medium claim with limitations corresponding to the limitations of Claim 3 and is rejected under similar rationale. Claim 14 is a medium claim with limitations corresponding to the limitations of Claim 4 and is rejected under similar rationale. Claim 18 is a device claim with limitations corresponding to the limitations of Claim 3 and is rejected under similar rationale. Claim 19 is a device claim with limitations corresponding to the limitations of Claim 4 and is rejected under similar rationale . 07-21-aia AIA Claim (s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Crabtree in view of Chen and Wallbaum, as applied in claim 4 above, further in view of Kretz et al. (US 20130054621 A1) . Regarding claim 7, Crabtree does not disclose the additional limitations. Chen discloses: 7. The method of claim 4, wherein the at least the portion of the telemetry data is deemed to have an unacceptable usability (see mapping and motivation statement for claim 5) due to a magnitude of difference between a different defined ontology and the defined ontology. (not explicitly disclosed) Chen and Wallbaum do not explicitly disclose comparing the magnitude of difference between the ontologies. Kretz discloses: due to a magnitude of difference between a different defined ontology and the defined ontology. (“[0011]…the ontology similarity component i s further configured to generate the threshold confidence level based on an F-score and a significant difference calculation associated with the at least one semantic-based association;…”) Crabtree, Chen, Wallbaum, and Kretz are considered analogous art to the claimed invention because they disclose data processing methods. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination with a difference calculation for ontology as disclosed by Kretz. Doing so would have been beneficial so ontology can be aligned more effectively (Kretz [0006]). This combination falls under combining prior art elements according to known methods to yield predictable results or simple substitution of one known element for another to obtain predictable results. See MPEP 2141, KSR, 550 U.S. at 418, 82 USPQ2d at 1396 . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Shkuro et al. (“Positional Paper: Schema-First Application Telemetry”). Shkuro discloses a method of semantically enriching telemetry metadata based on schemas. Moraru et al. (“A Framework for Semantic Enrichment of Sensor Data”). Moraru discloses semantic enrichment of sensor data from an ontology. Any inquiry concerning this communication or earlier communications from the examiner should be directed to JON C MEIS whose telephone number is (703)756-1566. The examiner can normally be reached Monday - Thursday, 8:30 am - 5:30 pm EST. 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, Hai Phan can be reached at 571-272-6338. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /JON CHRISTOPHER MEIS/Examiner, Art Unit 2654 /HAI PHAN/Supervisory Patent Examiner, Art Unit 2654 Application/Control Number: 18/962,716 Page 2 Art Unit: 2654 Application/Control Number: 18/962,716 Page 3 Art Unit: 2654 Application/Control Number: 18/962,716 Page 4 Art Unit: 2654 Application/Control Number: 18/962,716 Page 5 Art Unit: 2654 Application/Control Number: 18/962,716 Page 6 Art Unit: 2654 Application/Control Number: 18/962,716 Page 7 Art Unit: 2654 Application/Control Number: 18/962,716 Page 8 Art Unit: 2654 Application/Control Number: 18/962,716 Page 9 Art Unit: 2654 Application/Control Number: 18/962,716 Page 10 Art Unit: 2654 Application/Control Number: 18/962,716 Page 11 Art Unit: 2654 Application/Control Number: 18/962,716 Page 12 Art Unit: 2654 Application/Control Number: 18/962,716 Page 13 Art Unit: 2654 Application/Control Number: 18/962,716 Page 14 Art Unit: 2654 Application/Control Number: 18/962,716 Page 15 Art Unit: 2654
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