DETAILED ACTION
This Final Office Action is in response to the arguments and amendments filed September 03, 2025.
Claims 1 is amended.
Claims 2 and 5 are canceled.
Claims 3 and 4 are originals.
Claims 6 and 7 are new.
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 .
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.
Claim 1, 3, 4, 6 and 7 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more.
Step 1 (The Statutory Categories): Is the claim to a process, machine, manufacture, or composition of matter? MPEP 2106.03.
Step 1, claim 1, 3, 4, 6 and 7 are directed to a system (i.e., a machine). Thus, the claims are directed to statutory categories of invention. However, the claims are rejected under 35 U.S.C. 101 because they are directed to an abstract idea, a judicial exception, without reciting additional elements that integrate the judicial exception into a practical application.
The analysis proceeds to Step 2A Prong One.
Step 2A Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon? MPEP 2106.04.
The abstract idea of claim 1 and 7 is (claim 1 being representative):
A computer for matching vehicles comprising a controller and a communication interface, the controller being configured to:
acquire, via the communication interface, requests to exchange components of vehicles;
acquire, via the communication interface from each of the vehicles, sensor data on the component equipped with each of the vehicles;
perform a calculation process on each of the sensor data to achieve degree of deterioration of the component of each of the vehicles, the degree of deterioration being in a predetermined range of value;
select a pair of vehicles whose components are to be exchanged based on the requests; [[and]]
determine second parts to be exchanged in the pair among first parts composing the components based on the degree of deterioration by identifying the first parts to be the second parts in a case in which a difference in the degree of deterioration of the first parts between the vehicles in the pair is within a first threshold range; and
output, via the first communication interface, exchange information for the components, the exchange information including information on the pair of the vehicles and information on the second parts to be exchanged.
The abstract idea steps italicized above are those which could be performed mentally, including with pen and paper. The steps describe, at a high level, obtaining information and making determinations. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, including generating, determining, acquiring, and/or opinions, then it falls within the Mental Processes – Concepts Performed in the Human Mind grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Additionally, and alternatively, the abstract idea steps italicized above relate to the rules or instructions pertaining to generating, acquiring, performing, determining and selecting parts for repair. This is further supported by [0016] of applicant’s specification as filed. If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavioral relationships, interactions between people, including social activities, teaching, and/or following rules or instructions, then it falls within the Certain Methods of Organizing Human Activity – Managing Personal Behavior Relationships, Interactions Between People grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application? MPEP 2106.04.
This judicial exception is not integrated into a practical application because the additional elements are merely instructions to apply the abstract idea to a computer, as described in MPEP 2106.05(f).
Claim 1 recites the following additional elements: A computer, a controller, a communication interface, and a sensor data
These elements are merely instructions to apply the abstract idea to a computer, per MPEP 2106.05(f). Applicant has only described generic computing elements in their specification, as seen in [0051] of applicant’s specification as filed, for example.
Further, the combination of these elements is nothing more than a generic computing system applied to the tasks of the abstract idea. Because the additional elements are merely instructions to apply the abstract idea to a generic computing system, they do not integrate the abstract idea into a practical application, when viewed in combination. See MPEP 2106.05(f).
Therefore, per Step 2A Prong Two, the additional elements, alone and in combination, do not integrate the judicial exception into a practical application. The claim is directed to an abstract idea.
Step 2B (The Inventive Concept): Does the claim recite additional elements that amount to significantly more than the judicial exception? MPEP 2106.05.
Step 2B involves evaluating the additional elements to determine whether they amount to significantly more than the judicial exception itself.
The examination process involves carrying over identification of the additional element(s) in the claim from Step 2A Prong Two and carrying over conclusions from Step 2A Prong Two pertaining to MPEP 2106.05(f).
The additional elements and their analysis are therefore carried over: applicant has merely recited elements that facilitate the tasks of the abstract idea, as described in MPEP 2106.05(f).
Further, the combination of these elements is nothing more than a generic computing system. When the claim elements above are considered, alone and in combination, they do not amount to significantly more.
Therefore, per Step 2B, the additional elements, alone and in combination, are not significantly more. The claims are not patent eligible.
The analysis takes into consideration all dependent claims as well: claims 1, 3, 4, 6 and 7.
Accordingly, claims 1, 3, 4, 6 and 7 are rejected under 35 USC § 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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.
Claim(s) 1, 3, 4, 6, and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Zobrist et al [2014/0074865], hereafter Zobrist, in view of Konrardy et al [11,526167] hereafter Konrardy.
As per claim 1 and 7 (Similar scope and language);
Zobrist discloses:
A computer for matching vehicles comprising a controller and a communication interface, the controller being configured to:
{[0045] In some embodiments, the repair correlation system 100 or the recommendation system receives the request from a first computing device over a computer network and responds to the request by transmitting the repair data over the computer network to the first computing device.}
acquire, via the communication interface, requests to exchange components of vehicles;
{[0004] The repair correlation system can respond to requests for repair data for a particular vehicle with a response that includes repair data for other vehicles that have been identified as having an identical or similar system. In some embodiments, the repair correlation system may provide a confidence ranking to the repair data based on the similarity of the systems across the different vehicles.
[0045] In some embodiments, the repair correlation system 100 or the recommendation system receives the request from a first computing device over a computer network and responds to the request by transmitting the repair data over the computer network to the first computing device. For example, if a query requests possible repairs to a problem occurring in vehicle system A, the repair correlation system 100 can respond with repair data for vehicle system A and related vehicle system B, even if vehicle system B is a different vehicle made by a different manufacturer. By responding with the associated repair data, the repair correlation system 100 can broaden the pool of available repair data while maintaining a high level of relevancy in the suggested repairs. Thus, a user of the repair correlation system 100 may be more likely to find an applicable repair procedure even if that repair procedure was intended for a different vehicle. The process 200 can then end.}
perform a calculation process on each of the sensor data to achieve degree of deterioration of the component of each of the vehicles, the degree of deterioration being in a predetermined range of value;
{[0041] At block 220, the repair correlation system 100 identifies related vehicle system(s) to the first vehicle system based at least partly on the matching key parts. The related vehicle systems can include vehicle systems from different vehicles and different manufacturers. In some cases, there may be no related vehicle systems, one related system or multiple related systems. In some embodiments, the repair correlation system 100 may identify vehicle systems as related with varying levels of certainty using a confidence score. For example, if 4 of 5 key parts match, then the repair correlation system 100 may give a confidence score of 80% (⅘=0.80). In some embodiments, the confidence score may be calculated by weighting some key part matches more than others. For example, the key parts may be weighted by relative costs or importance of the part to the system. By using weighting, the repair correlation system 100 can account for varying levels of effect on the applicability of repairs that differences between key parts may have. For example, if a first vehicle system uses a first part while a second vehicle system uses a second part, but the different parts have little or no effect to the operation of the first vehicle system and the second vehicle system, then the repair correlation system 100 can apply a lower weight to the mismatch of the first part and the second part in calculating the confidence score.
select a pair of vehicles whose components are to be exchanged based on the requests; [[and]]
{[0039] At block 215, the repair correlation system 100 identifies parts from other vehicles matching the key parts identified in block 205. For example, the repair correlation system 100 can search for identical or similar parts numbers for the respective key parts. In some situations, the same parts may be referred to using different part numbers. For example, two different vehicle manufacturers may use different parts numbers for the same part provided by a parts manufacturer. The parts data obtained by the repair correlation system 100 can include data on the different parts numbers that may be assigned to the same part.}
determine second parts to be exchanged in the pair among first parts composing the components based on the degree of deterioration
{[0041] At block 220, the repair correlation system 100 identifies related vehicle system(s) to the first vehicle system based at least partly on the matching key parts. The related vehicle systems can include vehicle systems from different vehicles and different manufacturers. In some cases, there may be no related vehicle systems, one related system or multiple related systems. In some embodiments, the repair correlation system 100 may identify vehicle systems as related with varying levels of certainty using a confidence score. For example, if 4 of 5 key parts match, then the repair correlation system 100 may give a confidence score of 80% (⅘=0.80). In some embodiments, the confidence score may be calculated by weighting some key part matches more than others. For example, the key parts may be weighted by relative costs or importance of the part to the system. By using weighting, the repair correlation system 100 can account for varying levels of effect on the applicability of repairs that differences between key parts may have. For example, if a first vehicle system uses a first part while a second vehicle system uses a second part, but the different parts have little or no effect to the operation of the first vehicle system and the second vehicle system, then the repair correlation system 100 can apply a lower weight to the mismatch of the first part and the second part in calculating the confidence score.
[0042] At block 225, the repair correlation system 100 associates repair data for the related vehicle system(s) with the first vehicle system of the first vehicle. In one embodiment, the repair correlation system 100 records or otherwise indicates that the repair data for the related vehicle system is applicable to the first vehicle system because the related vehicle system and the first vehicle system are identical or at least similar. For example, the repair correlation system 100 may alter or add an entry into the vehicle system database 120 to associate the related vehicle system repair data with the first vehicle system.}
by identifying the first parts to be the second parts in a case in which a difference in the degree of deterioration of the first parts between the vehicles in the pair is within a first threshold range; and
{[0037] In some embodiments, the repair correlation system 100 automatically selects the key parts for the first vehicle system even if no existing designations of key parts are specified for the first vehicle system. For example, the system 100 can select key parts by ordering or ranking the key parts of the first vehicle system. In one embodiment, the repair correlation system 100 may order the parts of the first vehicle system based on a selection criterion (e.g., cost, size relative to the system, etc.) and then select the top X (e.g., 1, 2, 3, 4, etc.) parts as the key parts. In some situations, the selection criteria can serve as proxies to the importance of the part to the vehicle system. For example, if important parts of two vehicle systems are the same, then it may be more likely that repairs that are applicable to one vehicle system are also applicable to another system with the same important parts.
[0041] At block 220, the repair correlation system 100 identifies related vehicle system(s) to the first vehicle system based at least partly on the matching key parts. The related vehicle systems can include vehicle systems from different vehicles and different manufacturers. In some cases, there may be no related vehicle systems, one related system or multiple related systems. In some embodiments, the repair correlation system 100 may identify vehicle systems as related with varying levels of certainty using a confidence score. For example, if 4 of 5 key parts match, then the repair correlation system 100 may give a confidence score of 80% (⅘=0.80). In some embodiments, the confidence score may be calculated by weighting some key part matches more than others. For example, the key parts may be weighted by relative costs or importance of the part to the system. By using weighting, the repair correlation system 100 can account for varying levels of effect on the applicability of repairs that differences between key parts may have. For example, if a first vehicle system uses a first part while a second vehicle system uses a second part, but the different parts have little or no effect to the operation of the first vehicle system and the second vehicle system, then the repair correlation system 100 can apply a lower weight to the mismatch of the first part and the second part in calculating the confidence score.}
output, via the first communication interface, exchange information for the components, the exchange information including information on the pair of the vehicles and information on the second parts to be exchanged.
{[0041] At block 220, the repair correlation system 100 identifies related vehicle system(s) to the first vehicle system based at least partly on the matching key parts. The related vehicle systems can include vehicle systems from different vehicles and different manufacturers. In some cases, there may be no related vehicle systems, one related system or multiple related systems. In some embodiments, the repair correlation system 100 may identify vehicle systems as related with varying levels of certainty using a confidence score. For example, if 4 of 5 key parts match, then the repair correlation system 100 may give a confidence score of 80% (⅘=0.80). In some embodiments, the confidence score may be calculated by weighting some key part matches more than others. For example, the key parts may be weighted by relative costs or importance of the part to the system. By using weighting, the repair correlation system 100 can account for varying levels of effect on the applicability of repairs that differences between key parts may have. For example, if a first vehicle system uses a first part while a second vehicle system uses a second part, but the different parts have little or no effect to the operation of the first vehicle system and the second vehicle system, then the repair correlation system 100 can apply a lower weight to the mismatch of the first part and the second part in calculating the confidence score.}
Zobrist, does not disclose the following limitations. However, Konrardy does disclose the following limitations:
Konrardy discloses:
acquire, via the communication interface from each of the vehicles, sensor data on the component equipped with each of the vehicles;
{[Col 5, line 19 -30] In some embodiments, the component may be a sensor providing sensor data to at least one of the one or more autonomous operation features, in which case the operating data may include sensor data generated by the sensor. Likewise, the component may be a software component associated with the one or more autonomous operation features. In such instances, the operating data may include software data regarding operation of the software component. The deterioration of performance may be detected by determining that the software component is a corrupted copy of a software program or not a current version of the software program.
[Col 9, line 31 -42] Either or both of the mobile device 110 or on-board computer 114 may communicate with the network 130 over links 112 and 118, respectively. Either or both of the mobile device 110 or on-board computer 114 may run a Data Application for collecting, generating, processing, analyzing, transmitting, receiving, and/or acting upon data associated with the vehicle 108 (e.g., sensor data, autonomous operation feature settings, or control decisions made by the autonomous operation features) or the vehicle environment (e.g., other vehicles operating near the vehicle 108). Additionally, the mobile device 110 and on-board computer 114 may communicate with one another directly over link 116.}
Motivation: It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify an exchange of vehicle components as disclosed by Zobrist with an addition of a sensor data as taught by Konrardy, to determine the component.
As per claim 3
Zobrist discloses:
The computer according to claim 1, wherein the controller is configured to select the pair of the vehicles to have a greater number of the second parts.
{[0017] For example, the repair correlation system 100 may compare the search query with a list of keywords or otherwise process the search query to identity terms from the search query related to vehicle systems. In some embodiments, the user may specify the vehicle system using a list of vehicle systems (e.g., drop downs or selection lists) or by otherwise providing a selection of a vehicle system to the repair correlation system 100 (e.g., using a vehicle model). In the above example, the repair correlation system 100 can determine the query is related to engines by identifying the keyword “engine.” The repair correlation system 100 can further identify that the vehicle system in question is an engine of a 1998 Chrysler Town and Country. Using this information, the repair correlation system 100 can look up data in the vehicle systems data repository 120 to identify key components of the particular engine.
[0037] In some embodiments, the repair correlation system 100 automatically selects the key parts for the first vehicle system even if no existing designations of key parts are specified for the first vehicle system. For example, the system 100 can select key parts by ordering or ranking the key parts of the first vehicle system. In one embodiment, the repair correlation system 100 may order the parts of the first vehicle system based on a selection criterion (e.g., cost, size relative to the system, etc.) and then select the top X (e.g., 1, 2, 3, 4, etc.) parts as the key parts. In some situations, the selection criteria can serve as proxies to the importance of the part to the vehicle system. For example, if important parts of two vehicle systems are the same, then it may be more likely that repairs that are applicable to one vehicle system are also applicable to another system with the same important parts.}
As per claim 4:
Zobrist discloses:
The computer according to claim 1, wherein the controller is configured to determine the first parts to be parts that are to be exchanged with new parts in a case in which degree of deterioration of the first parts is determined to exceed a second threshold value.
{[0037] In some embodiments, the repair correlation system 100 automatically selects the key parts for the first vehicle system even if no existing designations of key parts are specified for the first vehicle system. For example, the system 100 can select key parts by ordering or ranking the key parts of the first vehicle system. In one embodiment, the repair correlation system 100 may order the parts of the first vehicle system based on a selection criterion (e.g., cost, size relative to the system, etc.) and then select the top X (e.g., 1, 2, 3, 4, etc.) parts as the key parts. In some situations, the selection criteria can serve as proxies to the importance of the part to the vehicle system. For example, if important parts of two vehicle systems are the same, then it may be more likely that repairs that are applicable to one vehicle system are also applicable to another system with the same important parts.}
As per claim 6
Konrardy discloses:
The computer according to claim 1, wherein the degree of deterioration of the component of each of the vehicles is an indicator of a state of the component that changes with use of the component.
{[Col 4, line 39 – 55]; In one aspect, a computer-implemented method for maintaining components of vehicles having one or more autonomous operation features may be provided. The method may include (1) monitoring operating data regarding operation of the one or more autonomous operation features of the vehicle; (2) accessing baseline data associated with proper functioning of the one or more autonomous operation features; (3) detecting a deterioration of performance of a component of the vehicle based upon the operating data and the baseline data; (4) determining a component maintenance requirement status associated with the component based upon the detected deterioration of performance; (5) generating a notification including information regarding the component maintenance requirement status and a recommendation to repair or replace the component; and/or (6) presenting the notification to an owner, operator, or other party associated with the vehicle.
[Col 51, line 55 – Col 52, line 11]; At block 810, the on-board computer 114 may determine whether a malfunction or deterioration of performance of the component is likely to exist based upon the results of the evaluation of the operating data. This may include detecting whether performance of a component is likely to have deteriorated based upon a comparison of the operating data and the baseline date. Similarly, this may include detecting whether a component is likely to be malfunctioning based upon the operating data and the baseline data. Where the component is a sensor 120, this may include determining that the sensor data generated by the sensor 120 is unreliable based upon a comparison against baseline sensor data or based upon analysis with using a trained model. For example, a likelihood or probability of component malfunction or performance deterioration may be compared against a threshold level to determine whether there is a sufficient risk of component malfunction or performance deterioration to take further action. Where the component is a software component, this may include determining that the software component is a corrupted or out-of-date (i.e., not current) version of a software program or routine. When the on-board computer 114 determines the likelihood of component malfunction or performance deterioration is sufficiently low, the method 800 may terminate.}
Motivation: It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify an exchange of vehicle components as disclosed by Zobrist with an addition of a measurement of deterioration for the vehicle as taught by Konrardy, to determine the component.
Response to Arguments
In response to the argument filled August 5, 2025, regarding the 101 rejections, the Examiner Respectfully disagrees.
In view of applicant’s amendments and clarifying remarks, examiner withdraws the objection to the specification.
Applicant argues that the amended claim 1 recites, “that the claimed controller is configured to: acquire, via the communication interface, requests to exchange components of vehicles; acquire, via the communication interface from each of the vehicles, sensor data on the component equipped with each of the vehicles; ... and output, via the first communication interface, exchange information for the components ....” Applicant argues that the communication, performed by a controller via a communication interface, with external apparatuses such as a vehicle or a terminal apparatus over a network is not a merely mental process because a human cannot communicate with external apparatuses over a network in her/his mind.
Examiner Respectfully disagrees.
Examiner notes that the aspects pertaining the acquiring, requesting, performing selecting, and determining an output for component exchange information recites an abstract idea consistent with the “mental process” groupings and a byproduct of human mental work. The examiner reviewed these as steps of the identified abstract idea in the Step 2A Prong 1 Analysis and additional elements in Step 2A Prong 2 Analysis.
Applicant argues that regarding Step 2A, Prong 2, the additional elements recited in the claims are not technical improvement and merely implementing the abstract idea using generic technology, and thus the additional elements are not significantly more or transformative into a practical application. (See MPEP 2106.05(f)).
The Examiner respectfully disagrees.
Examiner notes that the system is directed to a mental process. 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). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 (2012) Mental processes [] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 19 3, 197 (1978).
Furthermore, the Examiner notes that the computer, controller and communication interface is used for acquiring, performing, selecting, requesting, and determining an output for component exchange information. These elements are not with respect to the abstract idea but additional elements considered under Step 2(a)(II) and 2(b) prong analysis. These are merely generic technology with no technical improvement rather an improvement to the abstract idea using generic technology. See specification {[0007]}.
The Examiner maintains the claims recite an abstract idea.
Therefore, for the foregoing reasons the Examiner has maintained the 35 USC 101 rejection.
Regarding the prior art rejections, the Examiner respectfully disagrees.
Applicant argues that the prior art of record fails to teach the claims, specifically that the prior art does not disclose acquiring sensor data on key parts from vehicles, much less calculating the confidence score for matching key parts based on the sensor data acquired from vehicles.
Examiner respectfully disagrees.
In response to applicant argument the prior art used does teach these limitations. Zobrist does teach a calculation process on each of the sensor data to achieve degree of deterioration. See Zobrist {[0041]}. Konrardy does teach a communication interface from each of the vehicles, sensor data. See Konrardy {Col 5. Line 19 – 30 and Col 9. Line 31-42]}
Applicant argues that the prior art of record fails to teach the claims that “the controller is configured to acquire, via the communication interface from each of the vehicles, sensor data on the component equipped with each of the vehicles; perform a calculation process on each of the sensor data to achieve degree of deterioration of the component of each of the vehicles, the degree of deterioration being in a predetermined range of value; and determine second parts to be exchanged in the pair among first parts composing the components based on the degree of deterioration”.
Examiner respectfully disagrees.
The Examiner is citing Zobrist for its repair correlation system that uses a database or other data repository of matching parts to identify related automotive sub-systems (e.g., engine, transmission, etc.) by matching key parts for sub-systems across different brands and models. See {[0004 and 0045]}; perform calculation process on each of the sensor data to determine the degree of deterioration of the component. See {[0041]}; Determining, and identifying similar vehicles whose components match. See {[0039 and 0042]};
The Examiner is citing Konrardy for its operation data; detecting a deterioration of performance of a component of the vehicle based upon the operating data and the baseline data; determining a component maintenance requirement status associated with the component based upon the detected deterioration of performance; generating a notification including information regarding the component maintenance requirement status and a recommendation to repair or replace the component. See {[Col. 5 Line 19-30; Col. 9 Line 31-42; Col.4 Line 39-55]}.
In terms of the arguments, Zobrist and Konrardy does teach specific limitations as amended.
Based on the considered amendments cited, 35 USC 103 references have been utilized to
teach the claimed invention (Claim 1, 6 and 7). As such claim 1, 3, 4, 6 and 7 are maintaining the 35 USC 103 rejection as considered above in light of the amended claim limitation. Lacking any further argument, claims 1, 3, 4, 6 and 7 are maintaining the 35 USC 103 rejection, as considered above in light of the amended claim limitation above.
Conclusion
THIS ACTION IS MADE FINAL. 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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/VICTOR CHIGOZIRIM ESONU/
Examiner, Art Unit 3629
/SARAH M MONFELDT/Supervisory Patent Examiner, Art Unit 3629