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 .
This action is responsive to communication filed on 16 December 2025. Claims 9-15 are pending in the case. Claim 9 is the independent claim. This action is non-final.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on December 16th, 2025 has been entered.
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 9-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claim 9,
At Step 1:
The claim is directed to a “method” and thus directed to a statutory category.
At Step 2A, Prong One:
The claim recites the following limitations directed to an abstract idea:
“wherein the number of points of a vertical axis corresponding to an input among the plurality of inputs corresponding to a continuous value is calculated on the discretization value received for said input, the number of points of an input comprising a categorical value is based on the corresponding finite set of categories of said input, each of the points of a vertical axis of an output corresponds to a selection of a specific point in each vertical axis corresponding to an input and is calculated using a mathematical model corresponding to said input, and the at least one measure of compliance indicates a compliance of the calculated outputs with the set of conditions” as drafted this recites a mathematical concept such as mathematical calculations.
At Step 2A, Prong Two:
The claim recites the following additional elements:
“and displaying, by the processing unit in a display screen, a parallel coordinate plot comprising a vertical axis for each of the plurality of inputs, each of the plurality of outputs, and for at least one measure of compliance, each vertical axis comprising a number of points, and wherein the parallel coordinate plot further comprises lines connecting at least one point of each vertical axis with at least one point of the neighbouring vertical axis” which is a high-level recitation of a generic computer components and represents mere instructions to apply on a computer as in MPEP 2106.05(f), which does not provide integration into a practical application.
“receiving, by the processing unit, a first signal including a plurality of inputs, each of the plurality of inputs corresponding to a continuous value or a categorical value, wherein the categorical value corresponds to a finite set of categories,” “receiving, by a processing unit, a second signal including a set of conditions for a plurality of outputs,” and “for each of the plurality of inputs corresponding to a continuous value, receiving a third signal including a discretization number,” which is insignificant extra-solution activity as receiving of data (i.e. mere data gathering) such as 'obtaining information' and the particulars of the retrieved data are merely “selecting information … for collection, analysis, and display” as identified in MPEP 2106.05(g) and does not provide integration into a practical application.
Viewing the additional limitations together and the claim as a whole, nothing provides integration into a practical application.
At Step 2B:
The conclusions for the mere implementation using a computer are carried over and does not provide significantly more.
With respect to the “receiving” identified as insignificant extra-solution activity above when re-evaluated this element is well-understood, routine, and conventional as evidenced by the court cases in MPEP 2106.05(d)(II), “i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); … OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network);” and thus remains insignificant extra-solution activity that does not provide significantly more.
Looking at the claim as a whole does not change this conclusion and the claim is ineligible.
Regarding claim 10,
At Step 1:
The claim is directed to a “method” and thus directed to a statutory category.
At Step 2A, Prong One:
The claim further recites limitations corresponding to the judicial exception recited in parent claim 9.
At Step 2A, Prong Two:
The claim recites the following additional elements:
“receiving, by the processing unit, a fourth signal including a user input for at least one of the plurality of inputs, the plurality of outputs and the measure of compliance; and modifying, by the processing unit, the parallel coordinate plot based on the user input; wherein the user input corresponds to a constraint for the at least one of the inputs, the plurality of outputs and the measure of compliance,” which is insignificant extra-solution activity as receiving of data (i.e. mere data gathering) such as 'obtaining information' and the particulars of the retrieved data are merely “selecting information … for collection, analysis, and display” as identified in MPEP 2106.05(g) and does not provide integration into a practical application.
“and modifying the parallel coordinate plot comprises providing a visual indication of the lines in the parallel coordinate plot connecting points of the vertical axis complying with the constraint.” which is a high-level recitation of a generic computer components and represents mere instructions to apply on a computer as in MPEP 2106.05(f), which does not provide integration into a practical application.
Viewing the additional limitations together and the claim as a whole, nothing provides integration into a practical application.
At Step 2B:
The conclusions for the mere implementation using a computer are carried over and does not provide significantly more.
Looking at the claim as a whole does not change this conclusion and the claim is ineligible.
Regarding claim 11,
At Step 1:
The claim is directed to a “method” and thus directed to a statutory category.
At Step 2A, Prong One:
The claim recites the following directed to an abstract idea:
“continuous values, a condition among the set of conditions corresponding to said output comprises an optimization direction that can be a minimization, a maximization, or an interval of the output given by an upper and a lower bound for a numerical value of said output,” as drafted this recites a mathematical concept such as mathematical calculations.
At Step 2A, Prong Two:
The claim does not recite any additional elements.
Viewing the additional limitations together and the claim as a whole, nothing provides integration into a practical application.
At Step 2B:
The conclusions for the mere implementation using a computer are carried over and does not provide significantly more.
Looking at the claim as a whole does not change this conclusion and the claim is ineligible.
Regarding claim 12,
At Step 1:
The claim is directed to a “method” and thus directed to a statutory category.
At Step 2A, Prong One:
The claim recites the following limitations directed to an abstract idea:
“categorical values within a finite set of categories, a condition among the set of conditions corresponding to said output comprises limiting the categorical value of said output to one or more categories among the finite set of categories,” as drafted this recites a mathematical concept such as mathematical calculations.
At Step 2A, Prong Two:
The claim does not recite any additional elements.
Viewing the additional limitations together and the claim as a whole, nothing provides integration into a practical application.
At Step 2B:
The conclusions for the mere implementation using a computer are carried over and does not provide significantly more.
Looking at the claim as a whole does not change this conclusion and the claim is ineligible.
Regarding claim 13,
At Step 1:
The claim is directed to a “method” and thus directed to a statutory category.
At Step 2A, Prong One:
The claim recites the following limitations directed to an abstract idea:
“at least one of a probability of the plurality of outputs complying with the set of conditions, a tolerance interval for said probability, a number of false positives or false negatives, a measures of robustness, or desirability function values,” as drafted this recites a mathematical concept such as mathematical calculations.
At Step 2A, Prong Two:
The claim does not recite any additional elements.
Viewing the additional limitations together and the claim as a whole, nothing provides integration into a practical application.
At Step 2B:
The conclusions for the mere implementation using a computer are carried over and does not provide significantly more.
Looking at the claim as a whole does not change this conclusion and the claim is ineligible.
Regarding claim 14,
At Step 1:
The claim is directed to a “method” and thus directed to a statutory category.
At Step 2A, Prong One:
The claim further recites limitations corresponding to the judicial exception recited in parent claim 9.
At Step 2A, Prong Two:
The claim recites the following additional elements:
“visual information indicating a value of the measure of compliance,” which is a high-level recitation of a generic computer components and represents mere instructions to apply on a computer as in MPEP 2106.05(f), which does not provide integration into a practical application.
Viewing the additional limitations together and the claim as a whole, nothing provides integration into a practical application.
At Step 2B:
The conclusions for the mere implementation using a computer are carried over and does not provide significantly more.
Looking at the claim as a whole does not change this conclusion and the claim is ineligible.
Regarding claim 15,
At Step 1:
The claim is directed to a “method” and thus directed to a statutory category.
At Step 2A, Prong One:
The claim further recites limitations corresponding to the judicial exception recited in parent claim 9.
At Step 2A, Prong Two:
The claim recites the following additional elements:
“a first colour and visual information indicating lower values of the measure of compliance comprises a second colour different from the first colour,” which is a high-level recitation of a generic computer components and represents mere instructions to apply on a computer as in MPEP 2106.05(f), which does not provide integration into a practical application.
Viewing the additional limitations together and the claim as a whole, nothing provides integration into a practical application.
At Step 2B:
The conclusions for the mere implementation using a computer are carried over and does not provide significantly more.
Looking at the claim as a whole does not change this conclusion and the claim is ineligible.
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 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim 9-15 are rejected under 35 U.S.C. 103 as being unpatentable over Vazquez et al. (A Mixed Integer Optimization Approach for Model Selection in Screening Experiments) in view of Desreumaux (US 2025/0037036 A1), further in view of Rosenberg et al. (US 2023/0259385 A1).
Regarding claim 1, Vazquez teaches a computer-implemented method for statistical modelling optimization, the method comprising:
receiving, by the processing unit, a first signal including a plurality of inputs, each of the plurality of inputs corresponding to a continuous value or a categorical value, wherein the categorical value corresponds to a finite set of categories; receiving, by a processing unit, a second signal including a set of conditions for a plurality of outputs; for each of the plurality of inputs corresponding to a continuous value, receiving a third signal including a discretization number (see Vazquez, Pages 4-6, 13-16, “Throughout the paper, we consider a linear regression model … The constraint in the optimization problem ensures that at most k terms are selected for inclusion in the regression model. … Mixed integer optimization is an optimization method to determine the values of a set of decision variables, which can be discrete or continuous, so as to maximize or minimize a particular linear or quadratic objective function, while satisfying a set of linear constraints (Bertsimas and Weismantel, 2005).” [The mixed integer optimization inputs discrete (i.e., categorical) or continuous variables in order to maximize or minimize an objective function, while satisfying a set of constraints (i.e., conditions).]);
However, Vazquez does not explicitly teach:
receiving, by the processing unit, a first signal including a plurality of inputs, each of the plurality of inputs corresponding to a continuous value or a categorical value, wherein the categorical value corresponds to a finite set of categories; receiving, by a processing unit, a second signal including a set of conditions for a plurality of outputs; for each of the plurality of inputs corresponding to a continuous value, receiving a third signal including a discretization number;
Desreumaux teaches:
receiving, by the processing unit, a first signal including a plurality of inputs, each of the plurality of inputs corresponding to a continuous value or a categorical value, wherein the categorical value corresponds to a finite set of categories; receiving, by a processing unit, a second signal including a set of conditions for a plurality of outputs; for each of the plurality of inputs corresponding to a continuous value, receiving a third signal including a discretization number (see Desreumaux, Paragraph [0019], “Discretization refers to a process of converting continuous attributes or features to discretized data sets. Assuming a dataset of n instances and p continuous descriptive attributes including attribute A, a discretization algorithm would discretize attribute A in this dataset into m consecutive and non-overlapping intervals:” [The continuous attribute is discretized into m (i.e., discretization number) consecutive and non-overlapping intervals (i.e., wherein the categorical value corresponds to a finite set of categories).]);
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Vazquez (teaching A Mixed Integer Optimization Approach for Model Selection in Screening Experiments) in view of Desreumaux (teaching supervised and multivariate continuous attributes discretization), and arrived at a method that incorporates discretization of continuous attributes. One of ordinary skill in the art would have been motivated to make such a combination for the purposes of finding a trade-off between information quality and statistical quality (see Desreumaux, Paragraph [0001]). In addition, both the references (Vazquez and Desreumaux) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as data analysis. The close relation between both the references highly suggests an expectation of success.
However, the combination of Vazquez, and Desreumaux do not explicitly teach:
and displaying, by the processing unit in a display screen, a parallel coordinate plot comprising a vertical axis for each of the plurality of inputs, each of the plurality of outputs, and for at least one measure of compliance, each vertical axis comprising a number of points, and wherein the parallel coordinate plot further comprises lines connecting at least one point of each vertical axis with at least one point of the neighbouring vertical axis;
Rosenberg teaches:
and displaying, by the processing unit in a display screen, a parallel coordinate plot comprising a vertical axis for each of the plurality of inputs, each of the plurality of outputs, and for at least one measure of compliance, each vertical axis comprising a number of points, and wherein the parallel coordinate plot further comprises lines connecting at least one point of each vertical axis with at least one point of the neighbouring vertical axis (see Rosenberg, Paragraph [0101], “FIG. 5 is an example of an interactive visualization in static view. In this example, the interactive visualization can show a parallel coordinates plot 500 of a tuning experiment of a parallel tempering computational procedure with hyperparameters that are the inverse initial (e.g., beta start) and inverse final (e.g., beta_stop) temperatures, the number of replicas, and the number of sweeps. The gradient bar 501 can be a legend for the values of the primary metric. The values of the primary metric can also be represented in the residuals column. The other columns can be associated with the computational procedure hyperparameters that may be tuned and/or other metrics (e.g., fraction of solved problems). Each horizontal line may represent a parameter configuration, and the gradient color of the line may depend on the performance of the parameter configuration (e.g., performance according to the primary metric).” [Figure 5 displays a parallel coordinate plot the comprises a vertical axis for the beta start (i.e., inputs), residuals (i.e., outputs), and for the gradient bar (i.e., measure of compliance). The parallel coordinate plot comprises lines connecting at least one point of each vertical axis with at least one point of the neighboring vertical axis.]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Vazquez (teaching A Mixed Integer Optimization Approach for Model Selection in Screening Experiments) in view of Desreumaux (teaching supervised and multivariate continuous attributes discretization), further in view of Rosenberg (teaching methods and systems for hyperparameter tuning and benchmarking), and arrived at a method that incorporates a parallel coordinate plot. One of ordinary skill in the art would have been motivated to make such a combination for the purposes of finding the optimal parameters of an optimization solver using a specific problem class (see Rosenberg, Paragraph [0006]). In addition, the references (Vazquez, Desreumaux and Rosenberg) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as data analysis. The close relation between the references highly suggests an expectation of success.
The combination of Vazquez, Desreumaux, and Rosenberg further teaches:
wherein the number of points of a vertical axis corresponding to an input among the plurality of inputs corresponding to a continuous value is calculated on the discretization value received for said input, the number of points of an input comprising a categorical value is based on the corresponding finite set of categories of said input, each of the points of a vertical axis of an output corresponds to a selection of a specific point in each vertical axis corresponding to an input and is calculated using a mathematical model corresponding to said input, and the at least one measure of compliance indicates a compliance of the calculated outputs with the set of conditions (see Vazquez, Pages 4-6, 13-16, “Throughout the paper, we consider a linear regression model … The constraint in the optimization problem ensures that at most k terms are selected for inclusion in the regression model. … Mixed integer optimization is an optimization method to determine the values of a set of decision variables, which can be discrete or continuous, so as to maximize or minimize a particular linear or quadratic objective function, while satisfying a set of linear constraints (Bertsimas and Weismantel, 2005).” [The mixed integer optimization inputs discrete (i.e., categorical) or continuous variables in order to maximize or minimize an objective function, while satisfying a set of constraints (i.e., conditions). A linear regression model (i.e., mathematical model) is considered, in which it can output a prediction.] Also, see Desreumaux, Paragraph [0019], “Discretization refers to a process of converting continuous attributes or features to discretized data sets. Assuming a dataset of n instances and p continuous descriptive attributes including attribute A, a discretization algorithm would discretize attribute A in this dataset into m consecutive and non-overlapping intervals:” [The continuous attribute is discretized into m (i.e., discretization number) consecutive and non-overlapping intervals (i.e., wherein the categorical value corresponds to a finite set of categories).]).
Regarding claim 10, Vazquez in view of Desreumaux, further in view of Rosenberg teaches all the limitations of claim 9. Rosenberg further teaches:
receiving, by the processing unit, a fourth signal including a user input for at least one of the plurality of inputs, the plurality of outputs and the measure of compliance; and modifying, by the processing unit, the parallel coordinate plot based on the user input; wherein the user input corresponds to a constraint for the at least one of the inputs, the plurality of outputs and the measure of compliance, and modifying the parallel coordinate plot comprises providing a visual indication of the lines in the parallel coordinate plot connecting points of the vertical axis complying with the constraint (see Rosenberg, Paragraph [0076], “The visualizations may be interactive visualizations (e.g., dynamic to an input of a user). An example of an interactive visualization may be found in FIG. 5.” [Figure 5 displays an interactive visualization that allows a user to modify the inputs.]).
Regarding claim 11, Vazquez in view of Desreumaux, further in view of Rosenberg teaches all the limitations of claim 9. Vasquez further teaches:
continuous values, a condition among the set of conditions corresponding to said output comprises an optimization direction that can be a minimization, a maximization, or an interval of the output given by an upper and a lower bound for a numerical value of said output (see Vazquez, Page 11, “We can embed factor sparsity in the MIO approach by imposing an upper bound on the number of factors that can be included in the selected model.” [An upper bound may be imposed.]).
Regarding claim 12, Vazquez in view of Desreumaux, further in view of Rosenberg teaches all the limitations of claim 9. Desreumaux further teaches:
categorical values within a finite set of categories, a condition among the set of conditions corresponding to said output comprises limiting the categorical value of said output to one or more categories among the finite set of categories (see Desreumaux, Paragraph [0019], “Discretization refers to a process of converting continuous attributes or features to discretized data sets. Assuming a dataset of n instances and p continuous descriptive attributes including attribute A, a discretization algorithm would discretize attribute A in this dataset into m consecutive and non-overlapping intervals:” [The continuous attribute is discretized into m (i.e., discretization number) consecutive and non-overlapping intervals (i.e., wherein the categorical value corresponds to a finite set of categories).]).
Regarding claim 13, Vazquez in view of Desreumaux, further in view of Rosenberg teaches all the limitations of claim 9. Rosenberg further teaches:
at least one of a probability of the plurality of outputs complying with the set of conditions, a tolerance interval for said probability, a number of false positives or false negatives, a measures of robustness, or desirability function values (see Rosenberg, Figure 5, Paragraphs [0071], [0101], “the metric can be the time to solution that measures the total computational time to find a best known solution at least once with a probability of 0.99.” [The metric may be associated with a probability.]).
Regarding claim 14, Vazquez in view of Desreumaux, further in view of Rosenberg teaches all the limitations of claim 9. Rosenberg further teaches:
visual information indicating a value of the measure of compliance (see Rosenberg, Figure 5, Paragraph [0101], “The gradient bar 501 can be a legend for the values of the primary metric.” [Figure 5 displays a gradient bar for the values of the primary metric (i.e., measure of compliance).]).
Regarding claim 15, Vazquez in view of Desreumaux, further in view of Rosenberg teaches all the limitations of claim 14. Rosenberg further teaches:
a first colour and visual information indicating lower values of the measure of compliance comprises a second colour different from the first colour (see Rosenberg, Paragraph [0101], “the gradient color of the line may depend on the performance of the parameter configuration (e.g., performance according to the primary metric).” [Multiple gradient colors are visualized depending on the performance of the parameter configuration.]).
Response to Arguments
Applicant’s Arguments, filed December 16th, 2025, have been fully considered, but are not persuasive.
Applicant argues on pages 7-8 of Applicant's Remarks that the amended claims, do not recite an abstract idea, integrate the exception into a practical application, and amounts to significantly more than the abstract idea. The Examiner respectfully disagrees.
The limitations as claimed are processes that, under broadest reasonable interpretation, involve mathematical calculations. MPEP 2106.04(a)(2) C. Mathematical calculation states “A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number.” Thus, the limitations as claimed are processes that, under broadest reasonable interpretation, covers mathematical calculation, but for the recitation of generic computer components. Therefore, the limitations fall into the abstract ideas of mathematical concepts.
The additional limitations do not integrate the judicial exception into a practical application after evaluating the additional limitations individually and together in combination.
The limitations as claimed do not include limitations that are sufficient to amount to significantly more that the judicial exception because the limitations as claimed are recited at a high-level of generality and amounts to no more than mere instructions to apply the abstract idea to a computer environment (see MPEP 2106.05(f)).
Applicant argues on pages 9-10 of Applicant's Remarks that the cited references do not teach or suggest “a particular coordination between the discretization of continuous inputs, the handling of categorical inputs, the calculation of output points using mathematical models, and the display of compliance measures within the parallel coordinate plot structure.” The Examiner respectfully disagrees.
Applicant’s Arguments, filed December 16th, 2025, have been fully considered, but moot in light of the new grounds of rejection.
Applicant argues on pages 9-10 of Applicant's Remarks that “the Examiner’s motivation to combine the references is insufficient.” The Examiner respectfully disagrees.
In response to applicant’s argument that there is no teaching, suggestion, or motivation to combine the references, the examiner recognizes that obviousness may be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to one of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988), In re Jones, 958 F.2d 347, 21 USPQ2d 1941 (Fed. Cir. 1992), and KSR International Co. v. Teleflex, Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007). In this case, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have incorporated the teachings of Desreumaux and Rosenberg into Vazquez for the purposes of finding the optimal parameters of an optimization solver using a specific problem class (see Rosenberg, Paragraph [0006]). In addition, both the references (Vazquez, Desreumaux and Rosenberg) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as data analysis. The close relation between both the references highly suggests an expectation of success.
For the above reasons, it is believed that the rejections should be sustained.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HUSAM TURKI SAMARA whose telephone number is (571)272-6803. The examiner can normally be reached on Monday - Thursday, Alternate Fridays.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Apu Mofiz can be reached on (571)-272-4080. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/HUSAM TURKI SAMARA/
Examiner, Art Unit 2161
/APU M MOFIZ/Supervisory Patent Examiner, Art Unit 2161