DETAILED ACTIONS
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
This office action is in response to the amendments/arguments submitted by the Applicant(s) on 11/25/2025.
Status of the Claims
Claims 1-20 are pending.
Claims 1, 5, 9, 11 and 18 are amended.
Response to Arguments
Rejections Under 35 U.S.C. 103
Applicant's arguments, see remarks pages 7-11, filed 11/25/2025.
with respect to the rejection(s) of Claims under 35 U.S.C. 103 has been considered, and are moot because the amendment has necessitated a new ground of rejections. The new rejections are set forth below.
Claim Rejections - 35 USC § 102
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 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 –
(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.
Claims 1, 6-10, 11, 16-18, and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by James Gregory Stanley (US 2015/0160148 A1, hereinafter Stanley).
Regarding claim 1, Stanley teaches
A method (Stanley, Figure 14) comprising:
A method comprising: measuring a first charge generated by a first excitation signal and transferred during a first time interval having a first length to a first electrode; (Stanley, Figure 1, [0008] Techniques used in some embodiments of the invention include: (b)using a "charge transfer" technique such that switches and the voltage on a capacitor are used to measure a capacitance on a sensor; (c) using multiple charge transfer times to gain relative information about a material;” [0086] Referring back to FIG. I, the system using a transfer time burst strategy uses a modified sequence as described below. First, S2 118 is opened. Then Sl 112 is closed, which charges the capacitor Cq 116 until Cq 116 has a voltage of Vcharge 114. Next, SI is opened, and a measurement of the voltage on Cq 116 is made using the AID converter 122 of the microprocessor. A charge transfer burst counter is initialized to zero. S2 118 is closed for a short "charge transfer time," such as l00 ns, and the charge transfer burst counter is incremented for each pulse of the burst”. Also see (Stanley, Figure 14, [0107]) mounted to a container holding a test fluid (Stanley, Figure 14, The method begins by receiving the liquid between at least two conducting electrodes, as in block 910”);
measuring a second charge generated by a second excitation signal and
transferred during a second time interval having a second length greater than the first length to the first electrode (Stanley, Figure 1, [0086], [0087] The process of opening S2 118. closing SI 112, opening S 1112, measuring the voltage on Cq 116, closing S2 118 and opening S2 118 for each pulse in burst mode, and measuring the voltage again on Cq 116 is repeated again, except in the second process a relatively larger charge transfer time is used, such as 200 ns”); and
determining a parameter of the test fluid based on a first charge transfer curve generated based on the first charge and the second charge (Stanley, Figure 4-7, transfer curve, Figure 14, [0107] Another exemplary method, method 900, is illustrated in FIG. 14. The method 900 includes a process of measuring a property of a liquid using a liquid property measurement system. a value is calculated related to the capacitance between the at least two conducting electrodes using the first voltage and second voltage, as in block 960” [0039] FIG. 4 shows voltage 210 on the capacitor Cq (in Volts (V)) as a function of time (charge transfer time) 212 (inseconds) after the switch S2 is initially closed and then opened after 100 ns.).
Regarding claim 6, Stanley teaches the method of claim 1,
Stanley, further teaches wherein: measuring the first charge comprises integrating a current provided to the first electrode during the first time interval. (Stanley, Figure 1, system 100, measurement cell 110, [0012], The method includes receiving the liquid between at least two conducting electrodes. A capacitor is charged a first time. A switch connected to the capacitor is closed for a first time period to at least partially discharge the capacitor. Voltage on the capacitor is measured
to determine a first voltage”).
Regarding claim 7, Stanley teaches the method of claim 1,
Stanley, further teaches comprising: measuring a third charge generated by the first excitation signal and transferred during the first time interval to a second electrode mounted to the container; measuring a fourth charge generated by the second excitation signal and transferred during the second time interval to the second electrode; and (Stanley, figure 4-5, [0069] the process is repeated with the opening and closing of S2 318, as described in relation to the system 100 shown in FIG. 1. If the process is used to generate measurements for Rll 302, RI2 304, and the measurement cell 310, up to twelve different voltage measurements can be made (i.e., four voltage measurements for each of RI 1 302, RI2 304, and the measurement cell 31 O; corresponding to six voltage measurements related to the short charge transfer time, and six voltage measurements related to the long charge transfer time”). generating a second charge transfer curve based on the third charge and the fourth charge, wherein: determining the parameter of the test fluid based on the first charge transfer curve comprises determining the parameter of the test fluid based on the first charge transfer curve and the second charge transfer curve (Stanley, figure 4-5, [0069] “. [0107], a value is calculated related to the capacitance between the at least two conducting electrodes using the first voltage and second voltage, as in block 960. The initial voltage can also be used to calculate the value related to the capacitance between the at least two conducting electrodes. [0108] The calculated capacitance can be used to detem1ine the dielectric constant of the liquid”,).
Regarding claim 8, Stanley teaches the method of claim 1,
Stanley further teaches wherein: determining the parameter of the test fluid comprises determining at least one of conductivity, permittivity, ethanol concentration, diesel exhaust treatment fluid concentration, or water hardness. (Stanley, [0013] In some embodiments, the calculated value may be the dielectric constant and/or the conductivity of the liquid” [0006] “An exemplary application of some embodiments of this invention is measuring quality of diesel exhaust fluid
(DEF).”)
Regarding claim 9, Stanley teaches the method of claim 1,
Stanley further teaches comprising: controlling a device based on the parameter of the test fluid. (Stanley,[005] Embodiments of the invention are operable to make
absolute capacitive measurements using sensors where a relatively low resistance (e.g., less than lO0Q) is placed directly across the capacitance to be measured. [0006] An exemplary application of some embodiments of this invention is measuring quality of diesel exhaust fluid (DEF). DEF is used in a diesel engine after-treatment to reduce mono-nitrogen oxides (NOx) emissions from the engine's exhaust. However, embodiments of the invention are
also applicable to other products that use or can benefit from a repeatable measure of the dielectric constant and conductivity of a liquid (or other material)”. NOTE: examiner interpreted “controlling a device based on test fluid parameter” as application of the measurement system into a device. Such as application of the measurement system in engine exhaust system for “diesel exhaust fluid (DEF)” quality check).
Regarding claim 10, Stanley teaches the method of claim 1,
Stanley further teaches comprising: determining that an upper surface of the test fluid in the container is at a higher elevation than a second electrode mounted to the container; and connecting the first electrode in series with the second electrode. (Stanley, Figure 11, [0092] A level measurement cell 640 (or level sensor) is formed by electrode E2 632 and electrode El 642.,)
Regarding claim 11, Stanley teaches
A system (Stanley, Figure 11, system 600), comprising:
a container (Stanley, Figure 11, Tank 601);
a first electrode mounted to the container (Stanley, Figure 11, electrode E2 632);
a signal generator (microprocessor 123),
configured to apply a first excitation signal to the first electrode during a first time interval having a first length and to apply a second excitation signal to the first electrode during a second time interval having a second length greater than the first length (Stanley, Stanley, Figure 11, The system includes two measurement cells. A quality measurement cell 630 (or quality sensor) is formed by electrode E2 632 and electrode E3 634. The quality measurement cell 630 is coupled to Cq 616 and the voltage measurement circuit 619 via the electrode E3 634 through a switch S3 636. A level measurement cell 640 (or level sensor) is forn1ed by electrode
E2 632 and electrode El 642. The level measurement cell 640 is coupled to Cq 616 and the voltage measurement circuit 619 via the electrode El 642 through a switch SI 646. The electrode E2 632 is coupled to a common voltage collllection
(e.g., ground voltage)])”;
a first device configured to measure a first charge generated by the first
excitation signal and transferred during the first time interval to the first electrode and to
measure a second charge generated by the second excitation signal and transferred
during the second time interval to the first electrode (Stanley, Figure 1, [0008] Techniques used in some embodiments of the invention include: (b)using a "charge transfer" technique such that switches and the voltage on a capacitor are used to measure a capacitance on a sensor; (c) using multiple charge transfer times to gain relative information about a material;” [0086] Referring back to FIG. I, the system using a transfer time burst strategy uses a modified sequence as described below. First, S2 118 is opened. Then Sl 112 is closed, which charges the capacitor Cq 116 until Cq 116 has a voltage of Vcharge 114. Next, SI is opened, and a measurement of the voltage on Cq 116 is made using the AID converter 122 of the microprocessor. A charge transfer burst counter is initialized to zero. S2 118 is closed for a short "charge transfer time," such as l00 ns, and the charge transfer burst counter is incremented for each pulse of the burst”. Also see (Stanley, Figure 14,[0107]) mounted to a container holding a test fluid (Stanley, Figure 14, The method begins by receiving the liquid between at least two conducting electrodes, as in block 910”);; and
a processor (Micro processor 123) configured to determine a parameter of a test fluid in the container (Stanley, [0013] In some embodiments, the calculated value may be the dielectric constant and/or the conductivity of the liquid” based on a first charge transfer curve generated based on the first charge and the second charge. Stanley, figure 4-5, [0069] “. [0107], a value is calculated related to the capacitance between the at least two conducting electrodes using the first voltage and second voltage, as in block 960. The initial voltage can also be used to calculate the value related to the capacitance between the at least two conducting electrodes. [0108] The calculated capacitance can be used to detem1ine the dielectric constant of the liquid”,).
Regarding claim 16, Stanley teaches the system of claim 11,
Stanley further teaches wherein: determining the parameter of the test fluid comprises determining at least one of conductivity, permittivity, ethanol concentration, diesel exhaust treatment fluid concentration, or water hardness. (Stanley, [0013] In some embodiments, the calculated value may be the dielectric constant and/or the conductivity of the liquid” [0006] “An exemplary application of some embodiments of this invention is measuring quality of diesel exhaust fluid
(DEF).”)
Regarding claim 17, Stanley teaches the system of claim 11,
Stanley further teaches comprising: controlling a device based on the parameter of the test fluid. (Stanley,[005] Embodiments of the invention are operable to make
absolute capacitive measurements using sensors where a relatively low resistance (e.g., less than lO0Q) is placed directly across the capacitance to be measured. [0006] An exemplary application of some embodiments of this invention is measuring quality of diesel exhaust fluid (DEF). DEF is used in a diesel engine after-treatment to reduce mono-nitrogen oxides (NOx) emissions from the engine's exhaust. However, embodiments of the invention are
also applicable to other products that use or can benefit from a repeatable measure of the dielectric constant and conductivity of a liquid (or other material)” NOTE: examiner interpreted “controlling a device based on test fluid parameter” as application of the measurement system into a device. Such as application of the measurement system in engine exhaust system for “diesel exhaust fluid (DEF)” quality check).
Regarding claim 18, Stanley teaches
A non-transitory computer-readable medium storing (Stanley, Microprocessor 123)
instructions that when executed facilitate performance of operations comprising:
receiving a first charge generated by a first excitation signal and transferred
during a first time interval having a first length to a first electrode mounted to a container
holding a test fluid; (Stanley, Figure 1, [0008] Techniques used in some embodiments of the invention include: (b)using a "charge transfer" technique such that switches and the voltage on a capacitor are used to measure a capacitance on a sensor; (c) using multiple charge transfer times to gain relative information about a material;” [0086] Referring back to FIG. I, the system using a transfer time burst strategy uses a modified sequence as described below. First, S2 118 is opened. Then Sl 112 is closed, which charges the capacitor Cq 116 until Cq 116 has a voltage of Vcharge 114. Next, SI is opened, and a measurement of the voltage on Cq 116 is made using the AID converter 122 of the microprocessor. A charge transfer burst counter is initialized to zero. S2 118 is closed for a short "charge transfer time," such as l00 ns, and the charge transfer burst counter is incremented for each pulse of the burst”. Also see (Stanley, Figure 14,[0107]) mounted to a container holding a test fluid (Stanley, Figure 14, The method begins by receiving the liquid between at least two conducting electrodes, as in block 910”);
receiving a second charge generated by a second excitation signal and
transferred during a second time interval having a second length greater than the first
length to the first electrode (Stanley, Figure 1, [0086], [0087] The process of opening S2 118. closing SI 112, opening S 1112, measuring the voltage on Cq 116, closing S2 118 and opening S2 118 for each pulse in burst mode, and measuring the voltage again on Cq 116 is repeated again, except in the second process a relatively larger charge transfer time is used, such as 200 ns”); and
determining a parameter of the test fluid based on a charge transfer curve
generated based on the first charge and the second charge. (Stanley, Figure 4-7, transfer curve, Figure 14, [0107] Another exemplary method, method 900, is illustrated in FIG. 14. The method 900 includes a process of measuring a property of a liquid using a liquid property measurement system. a value is calculated related to the capacitance between the at least two conducting electrodes using the first voltage and second voltage, as in block 960” [0039] FIG. 4 shows voltage 210 on the capacitor Cq (in Volts (V)) as a function of time (charge transfer time) 212 (inseconds) after the switch S2 is initially closed and then opened after 100 ns.).
Regarding claim 20, Stanley teaches the non-transitory computer-readable medium of claim 18,
Stanley further teaches wherein: determining the parameter of the test fluid comprises determining at least one of conductivity, permittivity, ethanol concentration, diesel exhaust treatment fluid concentration, or water hardness (Stanley, [0013] In some embodiments, the calculated value may be the dielectric constant and/or the conductivity of the liquid” [0006] “An exemplary application of some embodiments of this invention is measuring quality of diesel exhaust fluid
(DEF).”)
Claim Rejections - 35 USC § 103
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.
Claims 2-5, and 12-15, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Stanley and in view of Goldsmith et al. (US 2023/0333051 A1, hereinafter Goldsmith, previously cited).
Regarding claim 2, Stanley teaches the method of claim 1,
Stanley is silent on wherein: determining the parameter of the test fluid comprises determining the parameter using a fluid classification model based on the first charge transfer curve.
However, Goldsmith teaches wherein: determining the parameter of the test fluid comprises determining the parameter using a fluid classification model based on the first charge transfer curve. (Goldsmith, Figure 10, S1006, [0249] “In certain applications the method 1000 continues and includes determining 1006 one or more output characterization parameters as output data of a machine learning
model by applying a reduced complexity form of a fit function that models transfer curves (…) transfer curve information used as input data to the machine learning model”),
It would have been obvious to a person of ordinary skill before the effective filing date to modify Stanley’s method and incorporate a machine learning fluid classification model to incorporate transfer curve data as input with the benefit of determining the output characteristic parameters as taught by Goldsmith (Goldsmith, [0006]-[0009])
Regarding claim 3, Combination of Stanley and Goldsmith teaches the method of claim 2,
Stanley is silent on wherein: the fluid classification model comprises a neural network model, and the method comprises training the neural network model using a first reference charge transfer curve for a reference fluid with a first ground state and a second reference charge transfer curve for the reference fluid with a second ground state different than the first ground state.
However, Goldsmith teaches wherein: the fluid classification model comprises a neural network model (Goldsmith, Figure 7A, Machine learning model), and the method comprises training the neural network model using a first reference charge transfer curve for a reference fluid with a first ground state and a second reference charge transfer curve for the reference fluid with a second ground state different than the first ground state(Goldsmith, Figure 8, S806, [0236],” some implementation, the method 800 continues and includes training 806 a machine learning model to reconstruct transfer curve information that corresponds to expected outputs from the reduced complexity fit function for the transfer curve information within a predetermined reconstruction coefficient of determination”.[0009], In one or more aspects, the techniques described herein relate to an apparatus, where the transfer curve information includes one or more vectors including elements corresponding to 2D FET excitation conditions varied in accordance with a predetermined incrementally varying voltage sweep of a liquid gate bias voltage, and/or a 2D channel input bias voltage varied at a predetermined characteristic
resonance frequencies; and further including output elements corresponding to 2D FET output signals generated in response to the 2D FET excitation conditions and to biochemical interactions occurring in the liquid”).
It would have been obvious to a person of ordinary skill before the effective filing date to modify Stanley’s method and incorporate a machine learning fluid classification model to incorporate transfer curve data as input with the benefit of determining the output characteristic parameters as taught by Goldsmith (Goldsmith, [0006]-[0009])
Regarding claim 4, Combination of Stanley and Goldsmith teaches the method of claim 2,
Stanley is silent on wherein: the fluid classification model comprises a neural network model, and the method comprises training the neural network model using a first reference charge transfer curve associated with a first reference fluid having a first known characteristic and a second reference charge transfer curve associated with a second reference fluid having a second known characteristic different than the first known characteristic.
However, Goldsmith teaches wherein: the fluid classification model comprises a neural network model, and the method comprises training the neural network model using a first reference charge transfer curve associated with a first reference fluid (Goldsmith, Figure 8, S806, [0236],” some implementation, the method 800 continues and includes training 806 a machine learning model to reconstruct transfer curve information that corresponds to expected outputs from the reduced complexity fit function for the transfer curve information within a predetermined reconstruction coefficient of determination”.[having a first known characteristic and a second reference charge transfer curve associated with a second reference fluid having a second known characteristic different than the first known characteristic. [0009], In one or more aspects, the techniques described herein relate to an apparatus, where the transfer curve information includes one or more vectors including elements corresponding to 2D FET excitation conditions varied in accordance with a predetermined incrementally varying voltage sweep of a liquid gate bias voltage, and/or a 2D channel input bias voltage varied at a predetermined characteristic resonance frequencies”. NOTE: can measure under two different frequencies or time period. Each frequency corresponds to a time period).
It would have been obvious to a person of ordinary skill before the effective filing date to modify Stanley’s method and incorporate a machine learning fluid classification model to incorporate transfer curve data as input with the benefit of determining the output characteristic parameters as taught by Goldsmith (Goldsmith, [0006]-[0009])
Regarding claim 5, Combination of Stanley and Goldsmith teaches the method of claim 4,
Stanley further teaches comprising: placing the first reference fluid in the container; (Stanley, Figure 14, The method begins by receiving the liquid between at least two conducting electrodes, as in block 910”);
generating the first reference charge transfer curve by: measuring a third charge generated by a third excitation signal and transferred during a third time interval to the first (Stanley, Figure 14, [0107] The process can repeat to discharge the capacitor for a second time period that is different (e.g., shorter or longer) than the first time period. More particularly, the method can continue by charging the capacitor again. The next step may include closing the switch to at least partially discharge the capacitor. Then, the voltage is measured on the capacitor after a second time period to determine a third voltage, as in block 950. Next, a value is calculated related to the capacitance between the at least two conducting electrodes using the first voltage and second voltage, as in block 960. The initial voltage can also be used to calculate the value related to the capacitance between the at least two conducting electrode”
measuring a fourth charge generated by a fourth excitation signal and
transferred during a fourth time interval having a fourth length greater than the third
length to the first electrode; (Stanley, Figure 1, [0008] Techniques used in some embodiments of the invention include: (b)using a "charge transfer" technique such that switches and the voltage on a capacitor are used to measure a capacitance on a sensor; (c) using multiple charge transfer times to gain relative information about a material”, Figure 14, NOTE: the process can be repeated for 3rd, 4rth ---- nth times with different charge transfer time intervals. see figures 4-5, the voltage measurements for different time periods [0018] FIG. 4 illustrates a diagram of the voltage discharge by a capacitor over 100 nanosecond closure of a second switch. [0019] FIG. 5 illustrates a diagram of the voltage discharge by a capacitor over 200 nanosecond closure of the second switch”, any 4rth measurement can be the fourth time intervals, and it could be greater than the previous one as in [0107]) and
generating the first reference charge transfer curve based on the third charge and the fourth charge. (Stanley, Figures 4-5, [0039] “FIG. 4 shows voltage 210 on the capacitor Cq (in Volts (V)) as a function of time (charge transfer time) 212 (in
seconds) after the switch S2 is initially closed and then opened after 100 ns”.
.
Regarding claim 12, Stanley teaches the system of claim 1,
Stanley is silent on wherein: the processor is configured to determine the parameter using a fluid classification model based on the first charge transfer curve.
However, Goldsmith teaches wherein: determining the parameter of the test fluid comprises determining the parameter using a fluid classification model based on the first charge transfer curve. (Goldsmith, Figure 10, S1006, [0249] “In certain applications the method 1000 continues and includes determining 1006 one or more output characterization parameters as output data of a machine learning
model by applying a reduced complexity form of a fit function that models transfer curves of the 2D FETs to transfer curve information used as input data to the machine learning model”),
It would have been obvious to a person of ordinary skill before the effective filing date to modify Stanley’s method and incorporate a machine learning fluid classification model to incorporate transfer curve data as input with the benefit of determining the output characteristic parameters as taught by Goldsmith (Goldsmith, [0006]-[0009]).
Regarding claim 13, Combination of Stanley and Goldsmith teaches the system of claim 12,
Stanley is silent on wherein: the fluid classification model comprises a neural network model.
However, Goldsmith teaches wherein: the fluid classification model comprises a neural network model. (Goldsmith, Figure 7A, Machine learning model),
It would have been obvious to a person of ordinary skill before the effective filing date to modify Stanley’s method and incorporate a machine learning fluid classification model to incorporate transfer curve data as input with the benefit of determining the output characteristic parameters as taught by Goldsmith (Goldsmith, [0006]-[0009]).
Regarding claim 14, Combination of Stanley and Goldsmith teaches the system of claim 11,
Stanley, further teaches wherein: the first device comprises a current integrator. (Stanley, [0029] FIG. 1 100)
Regarding claim 15, Combination of Stanley and Goldsmith teaches the system of claim 11,
Stanley further teaches comprising: a second electrode mounted to the container (Stanley, [0009], “The measurement cell is made of at least two conducting electrodes configured to receive a liquid between the conducting electrodes”,)
, wherein: the first device is configured to measure a third charge generated by the first excitation signal and transferred during the first time interval to a second electrode mounted to the container measure a fourth charge generated by the second excitation signal and transferred during the second time interval to the second electrode, and generate a second charge transfer curve based on the third charge and the fourth charge(Stanley, figure 4-5, [0069] the process is repeated with the opening and closing of S2 318, as described in relation to the system 100 shown in FIG. 1. If the process is used to generate measurements for Rll 302, RI2 304, and the measurement cell 310, up to twelve different voltage measurements can be made (i.e., four voltage measurements for each of RI 1 302, RI2 304, and the measurement cell 31 O; corresponding to six voltage measurements related to the short charge transfer time, and six voltage measurements related to the long charge transfer time” ).
, and the processor (Stanley, Figure 1, Microprocessor 123) is configured to determine the parameter of the test fluid in the container based on the first charge transfer curve and the second charge transfer curve (Stanley, figure 4-5, [0069] “the process is repeated with the opening and closing of S2 318, as described in relation to the system 100 shown in FIG. 1. If the process is used to generate measurements for Rll 302, RI2 304, and the measurement cell 310, up to twelve different voltage measurements can be made (i.e., four voltage measurements for each of RI 1 302, RI2 304, and the measurement cell 31 O; corresponding to six voltage measurements related to the short charge transfer time, and six voltage measurements related to the long charge transfer time. [0107], a value is calculated related to the capacitance between the at least two conducting
electrodes using the first voltage and second voltage, as in block 960. The initial voltage can also be used to calculate the value related to the capacitance between the at least two conducting electrodes. [0108] The calculated capacitance can be used to detem1ine the dielectric constant of the liquid”,).
Regarding claim 19, Stanley teaches the non-transitory computer-readable medium of claim 18,
Stanley is silent on wherein the operations comprise: determining the parameter of the test fluid using a fluid classification model based on the charge transfer curve.
However, Goldsmith teaches wherein the operations comprise: determining the parameter of the test fluid using a fluid classification model based on the charge transfer curve (Goldsmith, Figure 10, S1006, [0249] “In certain applications the method 1000 continues and includes determining 1006 one or more output characterization parameters as output data of a machine learning
model by applying a reduced complexity form of a fit function that models transfer curves of the 2D FETs to transfer curve information used as input data to the machine learning model”),
It would have been obvious to a person of ordinary skill before the effective filing date to modify Stanley’s method and incorporate a machine learning fluid classification model to incorporate transfer curve data as input with the benefit of determining the output characteristic parameters as taught by Goldsmith (Goldsmith, [0006]-[0009]).
Conclusion
Citation of Pertinent Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Sampson et al. (US 2005/0149278 A1) recites “An apparatus and method for obtaining a measurement of various qualities of an electrochemical cell (12). The apparatus includes first (9) and second (10) electrodes and an excitation source (8) for providing a time varying excitation voltage to the first electrode (9). The excitation voltage (8) is switched between two voltage levels with the first and
second voltages alternately applied to the first electrode for predetermined times. An external capacitance (Cout) is connected between the second electrode (10) and ground. The apparatus is capable of determining the time related
rates at which electrical charge is transferred from the first electrode (9) to charge the external capacitance (Cout). These rates, here termed Transient Immitivity Response (TIR), may be provided as a digital or analog output (11).” (Abstract).
SCHALK et al (DE10231946A1) recites “The present invention relates to a method for measuring the fill level of a fluid, in particular a liquid, in a container by measuring the average charging current of one or more capacitors which are periodically charged and discharged. The invention also relates to a corresponding fill level sensor which is suitable for carrying out the method and which has a DC voltage source (11), at least one capacitive sensor element (14) which has a measuring electrode (13) and a counter electrode (15), an electronic switch (12), which can be switched periodically between a first position for charging the measuring electrode (13) and a second position for discharging the measuring electrode (13), and means (18) for measuring the average charging current flowing between the DC voltage source (11) and the measuring electrode (13) includes
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DILARA SULTANA whose telephone number is (571)272-3861. The examiner can normally be reached Mon-Fri, 9 AM-5:30 PM.
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, EMAN ALKAFAWI can be reached on (571) 272-4448. 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.
/DILARA SULTANA/Examiner, Art Unit 2858
/ALESA ALLGOOD/Primary Examiner, Art Unit 2858