DETAILED ACTION
Claims 1-12 and 14-17 are pending in the application and claims 1-12 and 14-17 are rejected.
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 .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 10/9/2025 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 1-12 and 14-17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Claim 6 recites “An information processing method” which recites a series of steps and therefore is a process. Claim 1 recites An information processing device” therefore is a machine. Claim 7 recites”A non-transitory computer-readable medium” therefore is a manufacture.
Step 2A Prong One: Claims 1, 6, and 7 recite limitations “execute” and “execute”. These limitations are processes that, under their broadest reasonable interpretation, covers performance of the limitation in the mind, but for the recitation of generic computer components. That is, other than reciting processor or a producer party, nothing in the claim element precludes the step from practically being performed in a human mind or with the aid of pen and paper. For example, “execute” in the context of this claim encompasses a user mentally, and with the aid of pen and paper writing the changes down on a sheet of paper and examine the list to identify the relevant ones
Step 2A Prong Two: The judicial exception is not integrated into a practical application. The claim recites the additional elements "receive” and “transmit” this limitation amounts to data gathering which is considered to be insignificant extra solution activity (MPEP 2106.05(g); and "receive” and “transmit”; this limitation is a mere generic response of collected and analyzed data which is considered to be insignificant extra solution activity (MPEP 2106.05(g) and are elements merely invoking a generic computer environment (processor, database, memory) and basic data-gathering or outputting functions (MPEP 21.96.05(f)) hence reciting insignificant extra solution activities.
The one or more hardware processors and one or more non-transitory computer-readable storage media in these steps are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. (see MPEP 2106.05(f)). The claim is directed to an abstract idea.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The limitations "receive” and “transmit” are recognized by the courts as well-understood, routine, and conventional activities when they are claimed in a merely generic manner. No elements individually or in combination adds “significantly more” than the abstract idea hence are no more than well-understood, routine and conventional computer functions that merely apply the abstract idea on a generic computer. When viewed as an ordered combination, these additional elements do not integrate the abstract idea into a practical application and do not add significantly more than the abstract idea itself
Dependent claims are rejected for depending off independent claims.
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 of this title, 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.
Claim(s) 1, 2, 6, 7, 11 are/is rejected under 35 U.S.C. 103 as being unpatentable over Feleppa et al. US6238342 in view of Saraswatula US2021/0158498 Chuang et al. US2009/0027394 in view of Foley US2017/0147191
Regarding claim 1, Feleppa teaches: a memory; and
a processor coupled to the memory,
wherein the processor is configured to: (Feleppa see col. 2 lines 53-67 col. 1-19 col. 5 lines 21-47 processor coupled to memory)
receive material data related to a material, from a user terminal
execute analysis on the material data using a predetermined first analysis method and generate first analysis result data that is an analysis result from the first analysis method, (Feleppa see col. 8 lines 4-67 col. 9 lines 1-27 determine classification score based on received material data)
execute, analysis on the received material data using a second analysis method and generate second analysis result data that is an analysis result expressing a relationship between the received material data and data different from the received material data (Feleppa see col. 7 lines 46-67 col. 8 lines 1-48 col. 10 lines 47-59 classification a first time and a second time at a future time for a second classification result such that second result is compared to first result and classification done based on a score and using K-nearest neighbor analysis. Comparison of second result to first result, using score ranges and k-nearest neighbor all read on relationship between received material data and data different from received data)
transmit the generated first analysis result data and the generated second analysis result data to the user terminal. (Feleppa see col. 2 lines 9-26 col. 9 lines 27-32 classification data output and displaying classification scores)
Feleppa does not distinctly disclose: by controlling at least one of X-ray diffraction microscopy on the material and X-ray scattering microscopy on the material
at least partly by one or more machine learning models, and wherein the analysis result is map data expressing relationships between a plurality of data sets of the material data
in response to a user input to a plot point from a display of the map data of the analysis result of the second analysis result data, reconstruct and output to the display a waveform of the data represented by the plot point
in response to a user input to a predetermined region different from the plot points representing the material data already present on the map data is specified, reconstruct the material data corresponding to the predetermined region and output to the display a waveform of the material data represented by the predetermined region
However, Saraswatula teaches: by controlling at least one of X-ray diffraction microscopy on the material and X-ray scattering microscopy on the material (Saraswatula see paragraph 0005 0078 using x-ray transmission or diffraction microscopy on defect candidate wafer)
at least partly by one or more machine learning models (Saraswatula see paragraph 0065 0073 machine learning to detect defect candidate wafer and optionally classifying the candidates)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of ultrasonic classification as taught by Feleppa to include microscopy and machine learning as taught by Saraswatula for the predictable result of more efficiently collecting data and analyzing data
Feleppa does not distinctly disclose: and wherein the analysis result is map data expressing relationships between a plurality of data sets of the material data
in response to a user input to a plot point from a display of the map data of the analysis result of the second analysis result data, reconstruct and output to the display a waveform of the data represented by the plot point
in response to a user input to a predetermined region different from the plot points representing the material data already present on the map data is specified, reconstruct the material data corresponding to the predetermined region and output to the display a waveform of the material data represented by the predetermined region
However, Chuang teaches: and wherein the analysis result is map data expressing relationships between a plurality of data sets of the material data
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of ultrasonic classification as taught by Feleppa to include plotting data sets as taught by Chuang for the predictable result of more efficiently managing and organizing data
Feleppa does not distinctly disclose: in response to a user input to a plot point from a display of the map data of the analysis result of the second analysis result data, reconstruct and output to the display a waveform of the data represented by the plot point
in response to a user input to a predetermined region different from the plot points representing the data already present on the map data is specified, reconstruct the data corresponding to the predetermined region and output to the display a waveform of the material data represented by the predetermined region
However, Foley teaches: in response to a user input to a plot point from a display of the map data of the analysis result of the second analysis result data, reconstruct and output to the display a waveform of the data represented by the plot point (Foley see paragraph 0031 user to select points on a waveform and a corresponding waveform is shown on GUI)
in response to a user input to a predetermined region different from the plot points representing the data already present on the map data is specified, reconstruct the data corresponding to the predetermined region and output to the display a waveform of the material data represented by the predetermined region (Foley see paragraph 0031 user to select values from spreadsheet or data is entered into window and a corresponding waveform is shown on GUI)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of ultrasonic classification as taught by Feleppa to include displaying a plot as taught by Foley for the predictable result of more efficiently managing and organizing data
Regarding claim 2, Feleppa as modified further teaches: wherein the processor generates the second analysis result data after aligning a numerical range of the received material data to a specific numerical range. (Feleppa see col. 2 lines 35-52 col. 4 lines 39-65 classification scores divided into ranges, assigning likelihood of cancer score categorized by range)
Regarding claim 6, see rejection of claim 1
Regarding claim 7, see rejection of claim 1
Regarding claim 11, Feleppa as modified further teaches: material data (Feleppa see col. 8 lines 4-67 col. 9 lines 1-27 determine classification score based on received material data)
by the one or more machine learning models (Saraswatula see paragraph 0065 0073 machine learning to detect defect candidate wafer and optionally classifying the candidates)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of ultrasonic classification as taught by Feleppa to include microscopy and machine learning as taught by Saraswatula for the predictable result of more efficiently collecting data and analyzing data
Chuang teaches: generating plot points, including the plot point, corresponding to the plurality of data sets comprising at least both of a first data set of the received data and a second data set of the data different from the received data, wherein a first one of the plot points represents the first data set, and wherein a second one of the plot points represents the second data set, and wherein the plot point is one of the first one of the plot points and the second one of the plot points
generating a map comprising the plot points, and wherein the relationship is expressed by the map, and wherein the map comprising the plot points represents at least part of the map data
and wherein performing the analysis on the received data using the second analysis method comprises, extracting first specific values from the material data and extracting second specific values from the data different from the received data, and
wherein generating the plot points comprises generating the first one of the plot points based on the extracted first specific values and generating the second one of the plot points based on the extracted second specific values. (Chuang see paragraph 0022 0029 0038 0049 0052 data sets each have plurality of data points and plotting points on graph such that the graph can clearly depict relationships of two data sets)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of ultrasonic classification as taught by Feleppa to include plotting data sets as taught by Chuang for the predictable result of more efficiently managing and organizing data
Claim(s) 3 are/is rejected under 35 U.S.C. 103 as being unpatentable over Feleppa et al. US6238342 in view of Saraswatula US2021/0158498 Chuang et al. US2009/0027394 in view of Foley US2017/0147191 in view of Schutt et al. US2020/0403364
Regarding claim 3, Feleppa teaches: wherein the processor generates the second analysis result data after received material data (Feleppa see col. 7 lines 46-67 col. 8 lines 1-48 col. 10 lines 47-59 classification a second time on material data)
Feleppa does not teach: aligning a grid spacing of data contained in the received data to a specific grid spacing.
Schutt teaches: aligning a grid spacing of data contained in the received data to a specific grid spacing. (Schutt see paragraph 0076 elements arranged with a specific grid spacing)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of ultrasonic classification as taught by Feleppa to include grid spacing as taught by Schutt for the predictable result of more efficiently managing and organizing data
Claim(s) 4 are/is rejected under 35 U.S.C. 103 as being unpatentable over Feleppa et al. US6238342 in view of Saraswatula US2021/0158498 Chuang et al. US2009/0027394 in view of Foley US2017/0147191 in view of Ben-Haim US2021/0128009
Regarding claim 4, Feleppa does not teach: the second analysis result data is map data expressing relationships between a plurality of sets of the material data; and
in a case in which a specific region has been specified on the map data, the processor reconstructs the material data corresponding to the specific region
Ben-Haim teaches: the second analysis result data is map data expressing relationships between a plurality of sets of the material data; and
in a case in which a specific region has been specified on the map data, the processor reconstructs the material data corresponding to the specific region. (Ben-haim see paragraph 0007 0034 0145 0318 mapping voltage gradients of electric fields producing regions of the body and outside the body illustrating relationships between locations in space and reconstructing region of the map where Ben-haim modifying the primary reference reads on material data)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of ultrasonic classification as taught by Feleppa to include mapping regions as taught by Ben-Haim for the predictable result of more efficiently managing and organizing data
Claim(s) 5 are/is rejected under 35 U.S.C. 103 as being unpatentable over Feleppa et al. US6238342 in view of Saraswatula US2021/0158498 Chuang et al. US2009/0027394 in view of Foley US2017/0147191 in view of Lee US2012/0041280
Regarding claim 5, Feleppa does not teach: the processor stores the generated first analysis result data in a storage section; and
the processor stores the generated second analysis result data in the storage section
Lee teaches: the processor stores the generated first analysis result data in a storage section; and
the processor stores the generated second analysis result data in the storage section. (Lee see paragraph 0052 0077 server stores all analysis results)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of ultrasonic classification as taught by Feleppa to include storing analysis as taught by Lee for the predictable result of more efficiently managing and organizing data
Claim(s) 8 are/is rejected under 35 U.S.C. 103 as being unpatentable over Feleppa et al. US6238342 in view of Saraswatula US2021/0158498 Chuang et al. US2009/0027394 in view of Foley US2017/0147191 in view of Ohyama et al. US2015/0294609
Regarding claim 8, Feleppa does not teach: wherein the X- ray diffraction microscopy results in the analysis result indicating gradations of at least one of 0.1 degree and 0.5 degree.
Ohyama teaches: wherein the X- ray diffraction microscopy results in the analysis result indicating gradations of at least one of 0.1 degree and 0.5 degree. (Ohyama see paragraph 0076 laser emission performed in a small degree within a range controlled with good gradation reducing brightness to 0.5)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of ultrasonic classification as taught by Feleppa to include gradation as taught by Ohyama for the predictable result of more efficiently managing and organizing data
Claim(s) 9 are/is rejected under 35 U.S.C. 103 as being unpatentable over Feleppa et al. US6238342 in view of Saraswatula US2021/0158498 Chuang et al. US2009/0027394 in view of Foley US2017/0147191 in view of Yuhas US2016/0175824
Regarding claim 9, Feleppa as modified does not teach: wherein the analysis result of the first analysis method comprises at least one of a crystal phase of the material, phase fractions of the material, strain of the material, a crystal gain size of the material, and boundaries of the material.
However, Yuhas teaches: wherein the analysis result of the first analysis method comprises at least one of a crystal phase of the material, phase fractions of the material, strain of the material, a crystal gain size of the material, and boundaries of the material. (Yuhas see paragraph 0039 crystal phases)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of ultrasonic classification as taught by Feleppa to include microscopy as taught by Yuhas for the predictable result of more efficiently collecting data
Claim(s) 10 are/is rejected under 35 U.S.C. 103 as being unpatentable over Feleppa et al. US6238342 in view of Saraswatula US2021/0158498 Chuang et al. US2009/0027394 in view of Foley US2017/0147191 in view of Teplinsky et al. US2017/0262860
Regarding claim 10, Feleppa does not teach: wherein the second analysis result data indicates a manufacturing condition of the material determined based on the analysis result expressing the relationship between the received material data and the data different from the received material data, and
wherein the data different from the received material data is of another material other than the material
Teplinsky teaches: wherein the second analysis result data indicates a manufacturing condition of the material determined based on the analysis result expressing the relationship between the received material data and the data different from the received material data, and
wherein the data different from the received material data is of another material other than the material. (Teplinsky see paragraphs 0009 0108 comparing first item to second item based on attribute data of an item including manufacturing conditions)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of ultrasonic classification as taught by Feleppa to include determining counterfeit items as taught by Teplinsky for the predictable result of more efficiently managing and organizing data
Claim(s) 12 are/is rejected under 35 U.S.C. 103 as being unpatentable over Feleppa et al. US6238342 in view of Saraswatula US2021/0158498 Chuang et al. US2009/0027394 in view of Foley US2017/0147191 in view of Kamada US4626187
Regarding claim 12, Feleppa as modified further teaches: wherein the second analysis method comprises aligning, grid spacing (Chuang see paragraph 0006 0022 0029 0038 0049 0052 data sets each have plurality of data points and plotting points on graph such that the graph has set boundaries on x and y 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 modified a method of ultrasonic classification as taught by Feleppa to include plotting data sets as taught by Chuang for the predictable result of more efficiently managing and organizing data
Feleppa does not teach: wherein a first one of the material data and the data different from the received material data indicates gradations of 0.5 degrees,
wherein a second one of the material data and the data different from the received material data indicates gradations of 0.1 degrees, and
before extracting the first specific values and the second specific values, between the gradations of 0.5 degrees, of the first one of the material data and the data different from the received material data, and the gradations of the second one of the material data and the data different from the received material data indicates gradations of 0.1 degrees.
However, Kamada teaches: wherein a first one of the material data and the data different from the received material data indicates gradations of 0.5 degrees,
wherein a second one of the material data and the data different from the received material data indicates gradations of 0.1 degrees, and
before extracting the first specific values and the second specific values, between the gradations of 0.5 degrees, of the first one of the material data and the data different from the received material data, and the gradations of the second one of the material data and the data different from the received material data indicates gradations of 0.1 degrees. (Kamada see col. 4 lines 32-67 col.5 lines 1-2, reducing degree of gradation by adjusting viscosity of liquid materials controlling the difference between 0 to 5 P where between 0 and 5 include 0.1 and 0.5 degrees)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of ultrasonic classification as taught by Feleppa to include reducing degrees of gradations as taught by Kamada for the predictable result of more efficiently managing and controlling characteristics of materials
Claim(s) 14 are/is rejected under 35 U.S.C. 103 as being unpatentable over Feleppa et al. US6238342 in view of Saraswatula US2021/0158498 Chuang et al. US2009/0027394 in view of Foley US2017/0147191 in view of Mao et al. US7969439
Regarding claim 14, Feleppa as modified does not teach: wherein the processor is further configured to control the display to display the plot point among a plurality of plot points each colored according to an ordered sequence of data of the plot points
However, Mao teaches: wherein the processor is further configured to control the display to display the plot point among a plurality of plot points each colored according to an ordered sequence of data of the plot points. (Mao see col. 3 lines 24-38 col. 4 lines 26-36 col. 5 lines 51-67 col. 6 lines 1-3 sparse graph represented as sequence of points such that each point has a color value and displaying the graphs)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of ultrasonic classification as taught by Feleppa to include color organization in plotting as taught by Mao for the predictable result of more efficiently displaying information
Claim(s) 15 are/is rejected under 35 U.S.C. 103 as being unpatentable over Feleppa et al. US6238342 in view of Saraswatula US2021/0158498 Chuang et al. US2009/0027394 in view of Foley US2017/0147191 in view of Kawabata et al. US2014/0185927
Regarding claim 15, Feleppa as modified does not teach: wherein the processor is further configured to control the display to display the plot point among a plurality of plot points each colored according to numerical values obtained for each of a plurality of materials, the plurality of materials including the material.
Kawabata teaches: wherein the processor is further configured to control the display to display the plot point among a plurality of plot points each colored according to numerical values obtained for each of a plurality of materials, the plurality of materials including the material. (Kawabata see paragraph 0121 tracking changes of color of materials on graph recording changes in color difference or respective values and numbers to be displayed on screen)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of ultrasonic classification as taught by Feleppa to include color organization in plotting as taught by Kawabata for the predictable result of more efficiently displaying information
Claim(s) 16 are/is rejected under 35 U.S.C. 103 as being unpatentable over Feleppa et al. US6238342 in view of Saraswatula US2021/0158498 Chuang et al. US2009/0027394 in view of Foley US2017/0147191 in view of University of Utah, “A Case Study: Visualizing Material Point Method Data”, 2006, https://www.sci.utah.edu/~guilkey/MPMPubs/Bigler_etal.pdf hereafter referenced as University of Utah
Regarding claim 16, Feleppa as modified does not teach: wherein each plot point on the map data is colored in accordance with a performance values of the material or a manufacturing condition values of the material.
However, University of Utah teaches: wherein each plot point on the map data is colored in accordance with a performance values of the material or a manufacturing condition values of the material (University of Utah see pages 1-7 color map dataset with color associated with particular mass, volume speed and properties of solid material)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of ultrasonic classification as taught by Feleppa to include color mapping as taught by University of Utah for the predictable result of more efficiently displaying information
Claim(s) 17 are/is rejected under 35 U.S.C. 103 as being unpatentable over Feleppa et al. US6238342 in view of Saraswatula US2021/0158498 Chuang et al. US2009/0027394 in view of Foley US2017/0147191 in view of Sensorpod, “Pressure Distribution in Wafer-to-Wafer Bonding” March/April 2010 https://www.sensorprod.com/wp-content/uploads/2023/08/pr_wdpi-2010-03.pdf
Regarding claim 17, Feleppa as modified does not teach: wherein each plot point on the map data is colored in accordance with a manufacturing condition values of the material
However, Sensorpod teaches: wherein each plot point on the map data is colored in accordance with a manufacturing condition values of the material. (Sensorprod, see pages 1-4, parameters set to ensure high uniformity in manufacturing controlling temperature pressure and gap and color on a map represents pressure and colored data points represents multiple measurements in a single wafter)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified a method of ultrasonic classification as taught by Sensorpod to include color mapping as taught by University of Utah for the predictable result of more efficiently displaying information
Response to arguments
Applicant’s argument: 101 rejection should be withdrawn in light of new amendments
Examiner’s response: Applicant’s argument is considered but is not persuasive. Broadest reasonable interpretation as provided in the previous response is reasonable as the claims do not explain what kind of analysis is done. Given that no details are given to what kind of analysis is done, examiner not only does not fully understand the inventive concept which is an issue for allowability but also for 101 abstract idea analysis. If claims replaced the word analysis with the term “magic” it would not meaningfully change the inventive concept which is why examiner suggest adding detail to the analysis and also why examiner’s interpretation is reasonable. The rest of the claim is directly dependent on the analysis and therefore qualifies as for 101 rejection.
Claims deal with performing analysis on data which is a mental process as performing analysis is something that can be done in the mind or with pen and paper. The broadness of the claims further supports the examiner’s claim. While applicant claims there is technical improvement, however nothing in the claim is directed to that. The claims only apply the mental process. This is further supported by the broadness of the claims. Applicant’s argument about using a machine learning model and reciting expressing relationships does not overcome the 101 rejection as they are not actual steps taking to overcome using a mental process.
More importantly, examiner believes that the inventive concept has yet to be fully recited. Gathering data, performing analysis and displaying the analysis at a very general level is likely not inventive concept. Examiner believes that there is more detail and complexity to the inventive concept which would help to overcome the 101 rejection.
Examiner also notes the extreme broadness and lack of detail regarding the first and second analysis undermines all of applicant’s points. The entire inventive concept and all of the following limitations are directly dependent on the analysis. This uniquely makes and breaks applicant’s argument.
Applicant’s argument: Prior art does not teach a relationship
Examiner’s response: Applicant’s argument is considered but is not persuasive. The primary reference teaches a direct comparison using k-nearest neighbor analysis which is by definition defining a relationship. The saraswatula reference teaches the use of machine learning to classify candidates, this not only teaches an aspect of machine learning that can be combined with the primary reference, but the classification by itself also by definition teaches a relationship. This by broadest reasonable interpretation teaches a relationship. As stated above, applicant’s argument is uniquely unpersuasive because there is no details as to what kind of analysis is done. Relationship is broad term and analysis is a broad term so without more specific details prior art reads on the claim. If applicant intends for a different interpretation examiner suggests adding details to the claim to clarify making it obvious to that the kind of analysis and relationships in the prior art are different than what is recited in the claim.
Applicant’s argument: Prior art does not teach map data or user input plot points or reconstructing a waveform graph. This teaches the claimed concept. If applicant intends for a different interpretation examiner suggests adding details to the claim to clarify making it obvious to that the prior art is different than what is recited in the claim.
Examiner’s response: Applicant’s argument is considered but is not persuasive. Foley reference teaches user selecting points to generate a waveform
Applicant’s argument: Prior art of record does not teach newly amended subject matter
Examiner’s response: Applicant’s argument is moot as newly amended claims are responded to in the above rejection
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALLEN S LIN whose telephone number is (571)270-0612. The examiner can normally be reached on M-F 9-5.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kavita Stanley can be reached on (571)272-8352. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ALLEN S LIN/Primary Examiner, Art Unit 2153