DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
CLAIM INTERPRETATION
2. The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
3. Use of the word “means” (or “step for”) in a claim with functional language creates a rebuttable presumption that the claim element is to be treated in accordance with 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph). The presumption that 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph) is invoked is rebutted when the function is recited with sufficient structure, material, or acts within the claim itself to entirely perform the recited function.
Absence of the word “means” (or “step for”) in a claim creates a rebuttable presumption that the claim element is not to be treated in accordance with 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph). The presumption that 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph) is not invoked is rebutted when the claim element recites function but fails to recite sufficiently definite structure, material or acts to perform that function.
Claim elements in this application that use the word “means” (or “step for”) are presumed to invoke 35 U.S.C. 112(f) except as otherwise indicated in an Office action. Similarly, claim elements that do not use the word “means” (or “step for”) are presumed not to invoke 35 U.S.C. 112(f) except as otherwise indicated in an Office action.
4. The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
5. This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitations use a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier.
Such claim limitations are:
“a visual output device configured to”, "a user interface configured to", "a communication module configured to", "a training system configured to", "a classification system configured to", "smart device is configured to", "surface characterizing device system is configured to", and "trained classification model is configured to" in claims 118, 119, 120, 127-129, and 131.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
For more information, see MPEP § 2173 et seq. and Supplementary Examination Guidelines for Determining Compliance With 35 U.S.C. 112 and for Treatment of Related Issues in Patent Applications, 76 FR 7162, 7167 (Feb. 9, 2011).
Claim Rejections - 35 USC § 112
6. The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 132 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 132 recites the limitation "said plurality of predefined surface characteristic classes " in line 1-2 and " from the group of binder system classes" in line 2-3 and " from the list" in line 4. There is insufficient antecedent basis for this limitation in the claim.
Claim Rejections - 35 USC § 103
7. 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.
8. Claims 118-131 and 133-137 are rejected under 35 U.S.C. 103 as being unpatentable over "Nondestructive evaluation of aircraft coatings with infrared diffuse reflectance spectra", Proceedings of Spice, IEEE, US, 12 May, 2015 by Hans et al. (hereinafter Hans) (Submitted by Applicant in IDS) in view of CN106679805A by Qu et al. (hereinafter Qu).
Regarding Claim 118, Hans teaches a surface characterizing device system, comprising at least one sensor configured to acquire a measurement of at least one characteristic of a surface comprising a cured coat (Title, Abstract, Introduction);
a training input measurement or a labelled training input measurement for a training system configured to train a classification model for characterizing a surface comprising a cured coat, or an input measurement for a classification system configured to classify said surface comprising a cured coat (Abstract, Introduction, Equipment, Data Collection, Data Analysis, Sample Classification) but does not explicitly teach:
a processor and memory configured to establish a representation of said measurement;
a visual output device configured to indicate at least a measurement or connection status;
a user interface configured to control measurement; and
a communication module configured to establish a communication channel with a cloud and transmit said representation of said measurement via said communication channel;
wherein said surface characterizing device system is a portable system and being battery powered;
wherein said surface characterizing device system comprises a measurement buffer and is configured to temporarily store said representation of said measurement in said measurement buffer when said communication module is prevented from establishing said communication channel and transmit said temporarily stored representation upon reestablishment of said communication channel;
wherein said temporarily stored representation is one of.
However, Qu teaches a processor and memory configured to establish a representation of said measurement (Page 2-4);
a visual output device configured to indicate at least a measurement or connection status (Page 5);
a user interface configured to control measurement (Page 21); and
a communication module configured to establish a communication channel with a cloud and transmit said representation of said measurement via said communication channel (Page 3, 16, 21);
wherein said surface characterizing device system is a portable system and being battery powered (Page 5, 9);
wherein said surface characterizing device system comprises a measurement buffer and is configured to temporarily store said representation of said measurement in said measurement buffer when said communication module is prevented from establishing said communication channel and transmit said temporarily stored representation upon reestablishment of said communication channel (Page 4, 10, 15).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Hans by Qu as taught above such that a processor and memory configured to establish a representation of said measurement;
a visual output device configured to indicate at least a measurement or connection status;
a user interface configured to control measurement; and
a communication module configured to establish a communication channel with a cloud and transmit said representation of said measurement via said communication channel;
wherein said surface characterizing device system is a portable system and being battery powered;
wherein said surface characterizing device system comprises a measurement buffer and is configured to temporarily store said representation of said measurement in said measurement buffer when said communication module is prevented from establishing said communication channel and transmit said temporarily stored representation upon reestablishment of said communication channel;
wherein said temporarily stored representation is one of: a training input measurement or a labelled training input measurement for a training system configured to train a classification model for characterizing a surface comprising a cured coat, or an input measurement for a classification system configured to classify said surface comprising a cured coat is accomplished in order to provide accurate image information and spectral information for transmitting the test object, transmitting image information of the test object and spectral information to obtain the test results, and receive external data transmission module (Qu, Page 3).
Regarding Claim 119, Hans as modified by Qu teaches the surface characterizing device system is a distributed system comprising a portable measurement device (Qu, Title, Page 1: portable micro spectrometer) and portable smart device (Qu, Page 16: transmission module);
wherein the measurement device (Qu, Title, Page 1: portable micro spectrometer) comprises at least one of said at least one sensor (Qu, Page 2);
wherein the smart device (Qu, Page 16: transmission module) comprises at least said communication module configured to establish said communication channel with said cloud (Page 16: the spectrometer is connected to an external processing terminal via a transmission module, including, but not limited to, a mobile terminal, a PC, a cloud, or the like); and
wherein the measurement device (Qu, Title, Page 1: portable micro spectrometer) is communicatively coupled to said smart device (Qu, Page 16: transmission module) to transfer said measurement or said representation (Qu, Page 16).
Regarding Claim 120, Hans as modified by Qu teaches the smart device is configured to assign to the representation of said measurement one or more of further data from a sensor of said smart device, training input labels, metadata obtained by the smart device, information about periods where said communication module has been prevented from establishing said communication channel (Qu, Page 4, 10, 15).
Regarding Claim 121, Hans as modified by Qu teaches said measurement buffer is configured to temporarily store at least two of said representations of said measurements (Qu, Page 4, 10, 15: temporarily store two-dimensional image information and two-dimensional spectral information of the object to be measured collected by the two-dimensional spectral sensor when the transmission environment is unsatisfactory).
Regarding Claim 122, Hans as modified by Qu teaches said sensor is configured for making spectroscopy measurements (Qu, Page 2: portable micro spectrometer comprising: a two-dimensional spectral sensor).
Regarding Claim 123, Hans as modified by Qu teaches the sensor is configured to obtain the spectroscopy measurements by attenuated total reflectance ATR spectroscopy at wavelengths in the range of 5,500 nm to 8,000 nm (Hans, Equipment: sampling range 4000-650 cm-1 (2500 nm-15385 nm)).
Regarding Claim 124, Hans as modified by Qu teaches said surface characterizing device system comprises at least one infrared emitter (Hans, Abstract: Infrared, Qu: Page 12: infrared), and at least one sensor (Hans, Abstract: spectrometer, inherently teaches sensor, Qu, Page 2: sensor) configured for attenuated total reflection spectroscopy of said surface comprising a cured coat to obtain a spectroscopy measurement (See Claims 118, 123 rejection) but does not explicitly teach at least one prism.
However, it is considered obvious to try all known solutions when there is a recognized need in the art (at least one prism), there had been a finite number of identified, predictable solutions to the recognized need (at least one prism or without prism), and when one of ordinary skill in the art could have pursued the known potential solutions with a reasonable expectation of success. See MPEP § 2143, E. Furthermore, such an arrangement would imply to one of ordinary skill in the art before the effective filing date of the claimed invention to use at least one prism in order to optically couple light into a sample interface via total internal reflection, achieving the specific angle of incidence.
Regarding Claim 125, Hans as modified by Qu teaches said at least one infrared emitter, said at least one prism and said at least one sensor are configured to perform spectroscopy (See Claim 124 rejection) in a range of at least one of the following: the long wavelength infrared LWIR range, the range of 8,000 nm to 10,500 nm, the medium wavelength infrared MWIR range, the range of 5,500 nm to 8,000 nm, the range of 5,500 nm to 10,500 nm (Hans, Equipment: sampling range 4000-650 cm-1 (2500 nm-15385 nm)).
Regarding Claim 126, Hans as modified by Qu teaches said surface characterizing device system (See Claim 118 rejection) but does not explicitly teach comprises one or more of a pressure sensor and an accelerometer sensor.
However, it is considered obvious to try all known solutions when there is a recognized need in the art (one or more of a pressure sensor and an accelerometer sensor), there had been a finite number of identified, predictable solutions to the recognized need (one or more of a pressure sensor and an accelerometer sensor or without one or more of a pressure sensor and an accelerometer sensor), and when one of ordinary skill in the art could have pursued the known potential solutions with a reasonable expectation of success. See MPEP § 2143, E. Furthermore, such an arrangement would imply to one of ordinary skill in the art before the effective filing date of the claimed invention to use one or more of a pressure sensor and an accelerometer sensor in order to measure how hard the probe pushes against a surface and how much it vibrates. These two sensors work together to map surface texture, friction, and roughness accurately in real time.
Regarding Claim 127, Hans as modified by Qu teaches said surface characterizing device system is configured to perform a filtering or pre-validation of measurements and determine whether to temporarily store said representation of said measurement in said measurement buffer based on a result of said filtering or pre- validation (Qu, Page 4, 10, 15: when the transmission environment is unsatisfactory thus inherently teaches filtering or pre- validation).
Regarding Claim 128, Hans as modified by Qu teaches said surface characterizing device system comprises a trained classification model for characterizing a surface comprising a cured coat, and wherein said surface characterizing device system is configured to perform a classification based on said representation of said measurement (See Claim 118 rejection) but does not explicitly teach determine whether to temporarily store said representation on the basis of a result of said classification.
Hans further teaches one way of improving the accuracy of a discriminant classification model is to adjust the cost of misclassification, as demonstrated in figure 5. In this example, we assume the cost of misclassifying a treated sample as untreated is 100x higher than vice versa. The adjusted classification rule still correctly assigned all 36 untreated samples, but now correctly assigns 28 of the unknown treated samples for an accuracy of 78%. This is much improved over the 28% accuracy before adjusting the cost; however, the classifier still does not achieve 100% accuracy as expected from an examination of figure 5. These results show that a larger sample set is necessary to ensure the training data set adequately represents the test data (Result and Discussion, Page 8).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to determine whether to temporarily store said representation on the basis of a result of said classification in a cache or buffer. This saves memory space, speeds up processing, and handles complex data only when needed.
Regarding Claim 129, Hans as modified by Qu teaches said trained classification model is configured to classify said surface into at least one predefined surface characteristic class from a plurality of predefined surface characteristic classes based on said measurement (See Claim 118 rejection), the surface characteristic classes comprising one or more classes selected from a group of binder system classes, a group of coat manufacturer classes, a group of coating product classes, or a combination thereof (Hans, Abstract: two different types of coatings, classified as either aged or unaged with 100% accuracy).
Regarding Claim 130, Hans as modified by Qu teaches method of measuring a characteristic of a surface comprising a cured coat (See Claim 118 rejection. Note: an apparatus claim can be used to implement a method claim);
the method comprising steps of:
providing a surface characterizing device system in a first environment where communication with a cloud external to said first environment is prevented (Qu, Page 4, 10, 15);
using the surface characterizing device system to acquire a measurement of at least one characteristic of a surface comprising a cured coat (See Claim 118 rejection);
storing a representation of said measurement temporarily in a measurement buffer of said surface characterizing device system (Qu, Page 4, 10, 15);
providing said surface characterizing device system in a second environment (Qu, Page 3, 16, 21);
establishing a communication channel between said surface characterizing device system and said cloud (Qu, Page 3, 16, 21); and
transmitting said temporarily stored representation of said measurement to said cloud (Qu, Page 3, 16, 21).
Regarding Claim 131, Hans as modified by Qu teaches computer-implemented (inherently teaches, Qu, Page 21: processor, computer) classification method of characterizing a surface comprising a cured coat (See Claim 118 rejection. Note: an apparatus claim can be used to implement a method claim), the method comprising steps of:
providing a trained classification model by receiving training input measurements from a surface characterizing device system based on measurements of training surfaces comprising a cured coat (Hans, Abstract, Introduction, Equipment, Data Collection, Data Analysis, Sample Classification);
generating labelled training input measurements by individually labelling said training input measurements in accordance with a plurality of predefined surface characteristic classes (Hans, Abstract, Introduction, Equipment, Data Collection, Data Analysis, Sample Classification);
establishing a training data set on the basis of said labelled training input measurements (Hans, Abstract, Introduction, Equipment, Data Collection, Data Analysis, Sample Classification);
providing a classification model (Hans, Abstract, Introduction, Equipment, Data Collection, Data Analysis, Sample Classification);
training said classification model based on said training data set to provide a trained classification model (Hans, Abstract, Introduction, Equipment, Data Collection, Data Analysis, Sample Classification);
receiving an input measurement from a surface characterizing device system based on a measurement of said surface comprising a cured coat (Hans, Abstract, Introduction, Equipment, Data Collection, Data Analysis, Sample Classification); and
classifying said surface into at least one of said predefined surface characteristic classes based on said input measurement using said trained classification model to produce a classification output (Hans, Abstract, Introduction, Equipment, Data Collection, Data Analysis, Sample Classification);
wherein said surface characterizing device system (Qu, Title, Page 1: portable micro spectrometer) comprises at least one sensor (Qu, Page 2) configured to acquire a measurement of at least one characteristic of a surface comprising a cured coat (See Claim 118 rejection);
a processor and memory configured to establish a representation of said measurement (Qu, Page 2-4);
a visual output device configured to indicate at least a measurement or connection status (Qu, Page 5);
a user interface configured to control measurement (Qu, Page 21); and
a communication module configured to establish a communication channel with a cloud and transmit said representation of said measurement via said communication channel (Qu, Page 3, 16, 21);
wherein said surface characterizing device system is a portable system and being battery powered (Qu, Page 5, 9); and
wherein said surface characterizing device system comprises a measurement buffer and is configured to temporarily store said representation of said measurement in said measurement buffer when said communication module is prevented from establishing said communication channel and transmit said temporarily stored representation upon reestablishment of said communication channel (Qu, Page 4, 10, 15).
Regarding Claim 133, Hans as modified by Qu teaches each of said input measurements or labelled training input measurements is based on spectroscopy measurement obtained by attenuated total reflectance ATR spectroscopy (See Claim 123 rejection. Also see 131 rejection) of at least 20 different wavelengths (Hans, Equipment: sampling range 4000-650 cm-1 (2500 nm-15385 nm) thus teaches at least 20 different wavelengths);
wherein the at least 20 different wavelengths are in the infrared IR range, selected from one or more of:
the mid infrared MIR range, the near infrared NIR range, the short wavelength infrared SWIR range, the medium wavelength infrared MWIR range, the long wavelength infrared LWIR range, the range of 8,000 nm to 10,500 nm, the range of 5,500 nm to 8,000 nm, the range of 2,500 nm to 20,000 nm, the range of 4,000 nm to 12,000 nm, the range of 5,500 nm to 10,500 nm, or combination thereof (Hans, Equipment: sampling range 4000-650 cm-1 (2500 nm-15385 nm)).
Regarding Claim 134, Hans as modified by Qu teaches the spectroscopy measurements are obtained (See Claim 131 rejection) but does not explicitly teach while maintaining a pressure of a spectroscopy measurement device against said surface of at least one of at least 5 kg, at least about 10,000 kPa, at least 100 kgf/cm2.
However, it is considered obvious to try all known solutions when there is a recognized need in the art (maintaining a pressure of a spectroscopy measurement device against said surface of at least one of at least 5 kg, at least about 10,000 kPa, at least 100 kgf/cm2), there had been a finite number of identified, predictable solutions to the recognized need (maintaining a pressure of a spectroscopy measurement device against said surface of at least one of at least 5 kg, at least about 10,000 kPa, at least 100 kgf/cm2 or without maintaining a pressure of a spectroscopy measurement device against said surface of at least one of at least 5 kg, at least about 10,000 kPa, at least 100 kgf/cm2), and when one of ordinary skill in the art could have pursued the known potential solutions with a reasonable expectation of success. See MPEP § 2143, E. Furthermore, such an arrangement would imply to one of ordinary skill in the art before the effective filing date of the claimed invention to maintain a pressure of a spectroscopy measurement device against said surface of at least one of at least 5 kg, at least about 10,000 kPa, at least 100 kgf/cm2 in order to eliminate optical interface gaps and standardize the physical properties of the sample.
Note: This specific parameters profile is common in industrial materials testing, downhole oil/gas logging, and deep-tissue medical diagnostics
Regarding Claim 135, Hans as modified by Qu teaches classification model (See Claim 131 rejection) but does not explicitly teach said is a supervised classification model and a convolutional neural network.
However, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to use a supervised classification model and a convolutional neural network in order to analyze data (Note: This combination maps labeled data to specific categories while automatically handling the massive complexity and spatial patterns of images without manual feature engineering).
The examiner takes Official Notice that a supervised classification model and a convolutional neural network is well-known, or to be common knowledge in the art is capable of instant and unquestionable demonstration as being well-known. As noted by the court in In re Ahlert, 424 F.2d 1088, 1091, 165 USPQ 418,420 (CCPA 1970).
Regarding Claim 136, Hans as modified by Qu teaches the trained classification model (See Claim 131 rejection) but does not explicitly teach is updated by re-training or transfer learning according to one or more update trigger from the list of: receipt of new training input measurements, expiry of an update deadline, establishment of a new surface characteristic class, modification of an existing surface characteristic class.
However, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to update by re-training or transfer learning according to one or more update trigger in order to build a new machine learning model from scratch using all data, while transfer learning updates an existing model using new data. Triggering these updates upon receiving new input measurements helps models adapt to data drift, prevent performance decay, and maintain high accuracy over time.
The examiner takes Official Notice that re-training or transfer learning according to one or more update trigger is well-known, or to be common knowledge in the art is capable of instant and unquestionable demonstration as being well-known. As noted by the court in In re Ahlert, 424 F.2d 1088, 1091, 165 USPQ 418,420 (CCPA 1970).
Regarding Claim 137, Hans as modified by Qu teaches said trained classification model (See Claim 131 rejection) but does not explicitly teach is transferred from said cloud computing system to said surface characterizing device system for performing said step of classifying a surface locally.
However, it is considered obvious to try all known solutions when there is a recognized need in the art (transferred from said cloud computing system to said surface characterizing device system), there had been a finite number of identified, predictable solutions to the recognized need (transferred from said cloud computing system to said surface characterizing device system or without transferred from said cloud computing system to said surface characterizing device system), and when one of ordinary skill in the art could have pursued the known potential solutions with a reasonable expectation of success. See MPEP § 2143, E. Furthermore, such an arrangement would imply to one of ordinary skill in the art before the effective filing date of the claimed invention to transfer from said cloud computing system to said surface characterizing device system in order to allow for real-time classification, lower operating costs, and reliable offline performance without needing an internet connection.
Claim Rejections - 35 USC § 103
9. 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.
10. Claim 132 is rejected under 35 U.S.C. 103 as being unpatentable over Hans in view of Qu and further in view of Patent Pub. No. 2023/0151244 A1 by Martinsen (hereinafter Martinsen).
Regarding Claim 132, Hans as modified by Qu teaches said plurality of predefined surface characteristic classes is a plurality of classes (Hans, Abstract: two different types of coatings, classified as either aged or unaged with 100% accuracy) but does not explicitly teach selected from the group of binder system classes;
wherein said group of binder system classes comprises one or more class from the list of acrylic, epoxy, polyaspartic, polyurethane, polysiloxane, alkyd, silicate, silicone, polyurea, rosin, vinyl copolymers, polydimethylsiloxane, and hybrid technologies.
However, Martinsen teaches from the group of binder system classes;
wherein said group of binder system classes comprises one or more class from the list of acrylic, epoxy, polyaspartic, polyurethane, polysiloxane, alkyd, silicate, silicone, polyurea, rosin, vinyl copolymers, polydimethylsiloxane, and hybrid technologies (Par. [0001, 0008]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective date of the claimed invention to modify Hans as modified by Qu by Martinsen such that plurality of classes selected from the group of binder system classes;
wherein said group of binder system classes comprises one or more class from the list of acrylic, epoxy, polyaspartic, polyurethane, polysiloxane, alkyd, silicate, silicone, polyurea, rosin, vinyl copolymers, polydimethylsiloxane, and hybrid technologies is accomplished in order to offer potential benefits such as good weatherability, abrasion and corrosion resistance and lower volatile organic contents. Systems based on polysiloxane resins may also possess shorter curing times compared to epoxy systems and can be effectively formulated with a higher volume solids content (Martinsen, Par. [0008]).
Additional Prior Art
11. The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure. The reference listed teaches of other prior art method/system of characterizing Samples Using Neural Networks.
US Patent Pub. No. 2020/0333185 A1 by Vrabie et al (Fig. 1).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMIL AHMED whose telephone number is (571)272-1950. The examiner can normally be reached M-F: 9:00 AM - 5:00 PM.
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/JAMIL AHMED/Primary Examiner, Art Unit 2877
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