DETAILED ACTION
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite an abstract idea as discussed below. This abstract idea is not integrated into a practical application for the reasons discussed below. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception for the reasons discussed below.
Step 1 of the 2019 Guidance requires the examiner to determine if the claims are to one of the statutory categories of invention. Applied to the present application, the claims belong to one of the statutory classes of a process or product as a computer implemented method or a computer system/product.
Step 2A of the 2019 Guidance is divided into two Prongs. Prong 1 requires the examiner to determine if the claims recite an abstract idea, and further requires that the abstract idea belong to one of three enumerated groupings: mathematical concepts, mental processes, and certain methods of organizing human activity.
Claim 1 is copied below, with the limitations belonging to an abstract idea being underlined.
A system for minimizing safety hazards along a railroad track by optimizing visual railroad inspection frequency based on acquired data relating to railroad safety maintenance, comprising:
a memory for storing the acquired data relating to the railroad safety maintenance and an inspection frequency classification model to transform the acquired data from a raw form to a final inspection frequency value; and
a processor configured to execute computer program instructions that, when executed, cause the system to:
receive data related to a railroad track segment; generate continuous variables and categorical variables representing track segment condition indicators of concern;
convert and rescale continuous variables to match categorical variables; generate an inspection value for each of the variables;
generate a model that assigns a specific section of track to one of a plurality of inspection protocols based on the inspection values; and
generate an alert indicating the final inspection frequency to perform inspections.
Claim 11 is copied below, with the limitations belonging to an abstract idea being underlined.
A method of assessing frequency of visual track inspections, comprising:
receiving data related to a railroad track segment;
generating continuous variables and categorical variables representing track segment condition indicators of concern;
converting and rescaling continuous variables to match categorical variables; generating an inspection value for each of the variables; and
generating a model that assigns a specific section of track to one of a plurality of inspection protocols based on the inspection values.
The limitations underlined can be considered to describe a mathematical concept, namely a series of calculations leading to one or more numerical results or answers, obtained by a sequence of mathematical operations on numbers and/or mental steps. The lack of a specific equation in the claim merely points out that the claim would monopolize all possible appropriate equations for accomplishing this purpose in all possible systems. These steps recited by the claim therefore amount to a series of mental and/or mathematical steps, making these limitations amount to an abstract idea.
In summary, the highlighted steps in the claim above therefore recite an abstract idea at Prong 1 of the 101 analysis.
The additional elements in the claim have been left in normal font.
The additional limitations in relation to the memory and processor do not offer a meaningful limitation beyond generally linking the use of the method to a computer (see ALICE CORP. v. CLS BANK INT’L 573 U. S. 208 (2014)). The claim does not recite a particular machine applying or being used by the abstract idea.
The additional limitations of receiving data related to a railroad track segment equates to extrasolution data activity, i.e. data gathering (see MPEP 2106.05(g)). In addition, even if the generation of the alert was viewed as outputting/displaying an alert, such outputting would equate to extrasolution data activity, i.e. data reporting (see MPEP 2106.05(g)).
The claims do not integrate the abstract idea into a practical application. Various considerations are used to determine whether the additional elements are sufficient to integrate the abstract idea into a practical application. The claim does not recite a particular machine applying or being used by the abstract idea. The claim does not effect a real-world transformation or reduction of any particular article to a different state or thing. (Manipulating data from one form to another or obtaining a mathematical answer using input data does not qualify as a transformation in the sense of Prong 2.)
The claim does not contain additional elements which describe the functioning of a computer, or which describe a particular technology or technical field, being improved by the use of the abstract idea. (This is understood in the sense of the claimed invention from Diamond v Diehr, in which the claim as a whole recited a complete rubber-curing process including a rubber-molding press, a timer, a temperature sensor adjacent the mold cavity, and the steps of closing and opening the press, in which the recited use of a mathematical calculation served to improve that particular technology by providing a better estimate of the time when curing was complete. Here, the claim does not recite carrying out any comparable particular technological process.) In all of these respects, the claim fails to recite additional elements which might possibly integrate the claim into a particular practical application. Instead, based on the above considerations, the claim would tend to monopolize the abstract idea itself, rather than integrate the abstract idea into a practical application.
Step 2b of the 2019 Guidance requires the examiner to determine whether the additional elements cause the claim to amount to significantly more than the abstract idea itself. The considerations for this particular claim are essentially the same as the considerations for Prong 2 of Step 2a, and the same analysis leads to the conclusion that the claim does not amount to significantly more than the abstract idea.
Therefore, claims 1 and 11 are rejected under 35 U.S.C. 101 as directed to an abstract idea without significantly more.
Dependent claims 2-10 and 12-20 are similarly ineligible. The dependent claims merely add limitations which further detail the abstract idea, namely further mathematical/mental steps detailing how the data processing algorithm is implemented, i.e. additional software limitations. These do not help to integrate the claim into a practical application or make it significantly more than the abstract idea (which is recited in slightly more detail, but not in enough detail to be considered to narrow the claim to a particular practical application itself).
Claim Rejections - 35 USC § 112
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.
Claims 1-20 are 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 1 contains the following limitations in question:
a processor configured to execute computer program instructions that, when executed, cause the system to:
receive data related to a railroad track segment;
generate continuous variables and categorical variables representing track segment condition indicators of concern;
convert and rescale continuous variables to match categorical variables;
generate an inspection value for each of the variables;
generate a model that assigns a specific section of track to one of a plurality of inspection protocols based on the inspection values; and
generate an alert indicating the final inspection frequency to perform inspections.
Claim 11 contains the following limitations in question:
receiving data related to a railroad track segment;
generating continuous variables and categorical variables representing track segment condition indicators of concern;
converting and rescaling continuous variables to match categorical variables;
generating an inspection value for each of the variables; and
generating a model that assigns a specific section of track to one of a plurality of inspection protocols based on the inspection values.
The claim requires a particular series of steps. However, the scope of the claim language is not clear. Initially, the claim recites receiving data related to a railroad track segment, then followed by the limitation of generating continuous variables and categorical variables representing track segment condition indicators of concern. It is not clear as to if the data for the claimed continuous variables or categorical variables is present in the received data or if the data is generated by the processor. As best understood by the examiner, the continuous variable and categorical variables are data that is received by the processor.
Furthermore, the claim recites two the above two distinct steps: 1) convert and rescale continuous variables to match categorical variables and 2) generate an inspection value for each of the variables. However, the specification does not clearly describe each of the steps. As best understood by the examiner, each of the recited steps appear to describe the same step of the applicant’s disclosed invention. Thus, it is not clearly if the claimed conversion and rescaling of the variables and the generating of the inspection value are two distinct steps or if they encompass the disclosed concept of converting the continuous variable to a coded score, i.e. an inspection value, i.e. a singular step.
The first step of recalling the continuous variables to match the categorical variables is only described in paragraphs 0014 and 0020 of the applicant’s claimed invention. Paragraph 0014 is the only paragraph that further elaborates on the rescaling. Paragraph 0014 includes the following statement: “Advantageously, the system transforms the received inputs, such as BFI, MGT, and Rainfall by converting the inputs from continuous variables to whole-integer values and rescaling (e.g., normalizing) the values to match the categorical variables before contributing to the total score.”
As best understood by the examiner values are converted to whole-integer values to match the categorical variables before contributing to the total score. The only integer values that are contributed a total score are the coded score values. Furthermore, it is the only described conversion that would make one of the described continuous variables match one of the described categorical variables. For example, how else would a converted MGT, i.e. a continuous variable as described by the specification, be converted to match the categorical variable of Class Drop, a categorical variable as described by the specification, so they would match before contributing to a total score.
The claim also recites generating an inspection value for each of the variables, followed by the limitation of generating a model that assigns a specific section of track to one of a plurality of inspection protocols based on the inspection values. As best understood, the claim requires a different inspection value for each variable to make the plurality of inspection values required by the subsequent step. As best understood by the examiner, the only inspection value that is generated for each of the variables would also correspond the coded score.
So as best understood by the examiner, and based on the applicant’s specification, both of the clamed limitations appear to be describing the same step in the applicant’s disclosed invention. Since the individual steps of the clamed invention are not clearly described in the applicant’s specification, and might be conflicting with the detailed description of the applicant’s specification, the scope of the claimed invention is not clear.
The generic terms of converting, rescaling, and generating are very broad, and will be interpreted to relate to any process that links continuous and categorical variables to an inspection frequency of a railroad track.
Furthermore, the limitation of generating a model that assigns a specific section of track to one of a plurality of inspection protocols based on the inspection values it not readily clear. With respect to the recited limitation, the inspection values appear to have already determined for that section of track, 1) because the previous limitation indicates that they have been generated. So, the model cannot correspond to the discussed models/tables that relate variables to coded scores/index values. As best understood by the examiner, and according to the specification, once the inspection values/coded scores have been determined, the disclosed invention then determines a total score, which can be multiplied by an additional factor or not. This does not appear to a model that is generated by the processor. Is the model a mathematical algorithm, is the model a table of values that relates a particular value to an inspection frequency, is the model merely a numerical value itself as a number can model a characteristic of the railroad? As best understood, the model of the claimed invention could be method, means, table, algorithm, mental process for relating values to an inspection frequency of a railroad.
Claims 2-10 and 12-20 are rejected under 35 U.S.C. 112 because they incorporate the lack of clarity present in parent claims 1 and 11.
Claims 3 and 13 contain the following limitations in question:
3. The system of Claim 1, the computer program instructions further comprising hold a first variable at a fixed value and allowing all other variables to be drawn from a random pool of values based on the empirical density function for that variable.
13. The method of claim 11, further comprising holding a first variable at a fixed value and allowing all other variables to be drawn from a random pool of values based on the empirical density function for that variable.
It is not clear as to what variable that variable is referencing. Is it referencing a continuous variable or categorical variable in claim 1? Is it referencing a generated variable of claim 1, or is it referencing a rescaled variable of claim 1? Is it referencing the first variable, i.e. are the other variable randomly drawn based on an empirical density function of the first variable? Appropriate clarification is required.
As best understood by the examiner, the each of the other variable would have a corresponding empirical density function, and the other variables would be drawn from a random pool of values based on its corresponding empirical density function.
Claim Rejections - 35 USC § 102
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 11-12 and 15-17 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Federal Railroad Administration (Track and Rail and Infrastructure Integrity Compliance Manual).
Regarding claim 11, Federal Railroad Administration discloses a method of assessing frequency of visual track inspections (see page 2.1.82 last paragraph and table: shows minimum inspections requirements for various situations; see page 2.1.119 233(b): inspections of structures are visual inspections), comprising:
receiving data related to a railroad track segment (see page 1.3.6 last paragraph: On board ATIP cars, TGMS instrumentation generates automated signals processed online by a computer, which produces a graphical record of detailed track geometry measurements, i.e. computer receives data related to railroad track segment);
generating continuous variables and categorical variables representing track segment condition indicators of concern (see page 2.1.82 last paragraph and table: table is made of generated continuous, i.e. various MGTs, and categorical, i.e. class of track, freight, passenger, variables);
converting and rescaling continuous variables to match categorical variables (see page 2.1.82 last paragraph and table: discloses a plurality of MGT ranges);
generating an inspection value for each of the variables (see page 2.1.82 last paragraph and table: discloses inspection values with respect to combination of variables); and
generating a model that assigns a specific section of track to one of a plurality of inspection protocols based on the inspection values (see page 2.1.82 last paragraph and table: table meets the broad limitation of a model that assigns a specific track classification to one of the pluralities of inspection protocols, i.e. minimum of 0, 1, 3, or 4 time per year).
Regarding claim 12, Federal Railroad Administration further discloses generating a series of model results for every combination of input value (see page 2.1.82 last paragraph and table: table produces an inspection value, i.e. model results, for each and every combination of input values).
Regarding claim 15, Federal Railroad Administration further discloses wherein the inspection protocols can be three times a week, once a week, or twice per month (see page 2.1.19: 233(a), page 2.1.121 4th and 5th paragraph, and (b) and 2.1.122 4th paragraph: disclose that certain inspection are required a weekly inspection, i.e. once a week; see page 2.2.75 Table: discloses that inspection can be three time per week).
Regarding claim 16, Federal Railroad Administration further discloses wherein the inspection protocols are based on associated values for MGT, BFI, Rainfall, ClassDrop, CSP Category, Manual Defect, and CW Joint Count (see page 2.1.82 last paragraph and table: inspection protocols are based on MGT).
Regarding claim 17, Federal Railroad Administration further discloses wherein the converting and rescaling continuous variables includes converting the continuous variables to whole-integer values (see page 2.1.82 last paragraph and table: MGT, i.e. continuous variable, is converted and rescaled to whole-integer values as shown in the table).
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 1-2 and 5-7 are rejected under 35 U.S.C. 103 as being unpatentable over Federal Railroad Administration (Track and Rail and Infrastructure Integrity Compliance Manual) in view of Jumonji (US 20240212116).
Regarding claim 1, Federal Railroad Administration discloses a system for minimizing safety hazards along a railroad track by optimizing visual railroad inspection frequency based on acquired data relating to railroad safety maintenance (see page 2.1.82 last paragraph and table: shows minimum inspections requirements for various situations; see page 2.1.119 233(b): inspections of structures are visual inspections), comprising:
a memory for storing acquired data relating to the railroad safety maintenance (see page 1.2.3 and 1.3.6 last paragraph: On board ATIP cars, TGMS instrumentation generates automated signals processed online by a computer, which produces a graphical record of detailed track geometry measurements, i.e. computer receives data related to railroad track segment, computers have memory, discusses electronic records, stored data); and
a processor configured to execute computer program instructions that, when executed, cause the system to process data (see page 1.2.3 and 1.3.6 last paragraph: computers contain a processor PC stores electronic records, must be executing program instructions); and
further disclose receiving data related to a railroad track segment (see page 1.3.6 last paragraph: On board ATIP cars, TGMS instrumentation generates automated signals processed online by a computer, which produces a graphical record of detailed track geometry measurements, i.e. computer receives data related to railroad track segment);
generating continuous variables and categorical variables representing track segment condition indicators of concern (see page 2.1.82 last paragraph and table: table is made of generated continuous, i.e. various MGTs, and categorical, i.e. class of track, freight, passenger, variables);
converting and rescaling continuous variables to match categorical variables (see page 2.1.82 last paragraph and table: discloses a plurality of MGT ranges);
generating an inspection value for each of the variables (see page 2.1.82 last paragraph and table: discloses inspection values with respect to combination of variables); and
generating a model that assigns a specific section of track to one of a plurality of inspection protocols based on the inspection values (see page 2.1.82 last paragraph and table: table meets the broad limitation of a model that assigns a specific track classification to one of the pluralities of inspection protocols, i.e. minimum of 0, 1, 3, or 4 time per year).
Federal Railroad Administration does not expressly disclose a memory for storing the acquired data relating to the railroad safety maintenance and an inspection frequency classification model to transform the acquired data from a raw form to a final inspection frequency value; and
a processor configured to execute computer program instructions that, when executed, cause the system to implement steps related to the inspection frequency analysis, and
generate an alert indicating the final inspection frequency to perform inspections.
Jumonji discloses a memory for storing the acquired data relating to the railroad safety maintenance and an inspection frequency classification model to transform acquired data from a raw form to a final inspection frequency value (see Abstract and paragraphs 0182 and 0196: memory for storing data related to inspection frequency determination; discloses calculations can be considered a model that transforms the acquired data to an inspection frequency value); and
a processor configured to execute computer program instructions that, when executed, cause the system to implement steps related to the inspection frequency analysis (see Abstract and paragraphs 0182 and 0196: processor configured to implement inspection frequency determination algorithm), and
generate an alert indicating the final inspection frequency to perform inspections (see Fig. 4 and paragraph 0176-0177: discloses a display indicating inspection frequency associated with the diagnosis target, boxes with text can be considered an alert drawing attention to the inspection frequency required for particular segments; see paragraph 0057: method applicable to railways).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Federal Railroad Administration with the teachings of Jumonji, i.e. using a computer to generate and display an inspection frequency for particular track segments, for the advantageous benefit of allowing one to easily view how often different sections of the railway need to be inspected. This can make it easier for one to ensure that all the various sections meet their minimum inspection requirements.
Regarding claim 2, Federal Railroad Administration, previously modified, further discloses generate a series of model results for every combination of input value (see page 2.1.82 last paragraph and table: table produces an inspection value, i.e. model results, for each and every combination of input values).
Regarding claim 5, Federal Railroad Administration, previously modified, further discloses wherein the inspection protocols can be three times a week, once a week, or twice per month (see page 2.1.19: 233(a), page 2.1.121 4th and 5th paragraph, and (b) and 2.1.122 4th paragraph: disclose that certain inspection are required a weekly inspection, i.e. once a week; see page 2.2.75 Table: discloses that inspection can be three time per week).
Regarding claim 6, Federal Railroad Administration, previously modified, further discloses wherein the inspection protocols are based on associated values for MGT, BFI, Rainfall, ClassDrop, CSP Category, Manual Defect, or CW Joint Count (see page 2.1.82 last paragraph and table: inspection protocols are based on MGT).
Regarding claim 7, Federal Railroad Administration, previously modified, further discloses wherein the converting and rescaling continuous variables includes converting the continuous variables to whole-integer values (see page 2.1.82 last paragraph and table: MGT, i.e. continuous variable, is converted and rescaled to whole-integer values as shown in the table).
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Federal Railroad Administration (Track and Rail and Infrastructure Integrity Compliance Manual) in view of Jumonji (US 20240212116) and Ziavras (US 20170116383).
Regarding claim 3, Federal Railroad Administration and Jumonji do not expressly disclose wherein the computer program instructions further comprising hold a first variable at a fixed value and allowing all other variables to be drawn from a random pool of values based on the empirical density function for that variable.
Ziavras discloses a method of structural health monitoring related to railroads, wherein (see Abstract and paragraphs 0040 and 0083) wherein the computer program instructions further comprising hold a first variable at a fixed value and allowing all other variables to be drawn from a random pool of values based on the empirical density function for that variable (see paragraphs 0044 and 0076-0078: discloses one constant variable, and other variables that are generated using an empirical density function, the claim does not recite what the first variable is, what the other variable are, that only a single variable is fixed, due to the fact that the scope of the fixed variable and the other variables are not defined, and not even expressly tied to the variables in parent claim 1).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Federal Railroad Administration with the teachings of Ziavras, i.e. using an empirical density function to generate random variables, for the advantageous benefit of using the process to generate a plurality of simulations with respect to the monitoring devices, to evaluate and improve the accuracy a structural health monitoring device.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Federal Railroad Administration (Track and Rail and Infrastructure Integrity Compliance Manual) in view of Ziavras (US 20170116383).
Regarding claim 13, Federal Railroad Administration does not expressly disclose wherein comprising holding a first variable at a fixed value and allowing all other variables to be drawn from a random pool of values based on the empirical density function for that variable.
Ziavras discloses a method of structural health monitoring related to railroads, wherein (see Abstract and paragraphs 0040) wherein the computer program instructions further comprising hold a first variable at a fixed value and allowing all other variables to be drawn from a random pool of values based on the empirical density function for that variable (see paragraphs 0044 and 0076-0078: discloses one constant variable, and other variables that are generated using an empirical density function, the claim does not recite what the first variable is, what the other variable are, that only a single variable is fixed, due to the fact that the scope of the fixed variable and the other variables are not defined, and not even expressly tied to the variables in parent claim 11).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Federal Railroad Administration with the teachings of Ziavras, i.e. using an empirical density function to generate random variables, for the advantageous benefit of using the process to generate a plurality of simulations with respect to the monitoring devices, to evaluate and improve the accuracy a structural health monitoring device.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Federal Railroad Administration (Track and Rail and Infrastructure Integrity Compliance Manual) in view of Jumonji (US 20240212116) and McCasland (US 5856931).
Regarding claim 4, Federal Railroad Administration and Jumonji do not expressly disclose wherein the model can escalate a track segment for increased visual inspections if testing invalid or not tested.
McCasland discloses a computer system with a model/algorithm can escalate an inspection for increased inspections if testing invalid or not tested (see column 16 line 8 to line 25: in such a case, the percent overdue value can be weighted to either promote or demote an item in the scheduling priority of inspections, i.e. increasing priority of inspection based on a test that has not been done; and see column 4 lines 46-65: computer system implements the model/algorithm).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Federal Railroad Administration with the teachings of McCasland, i.e. prioritizing overdue inspections, for the advantageous benefit of drawing attention to areas that greatly need inspection attention to assure safe operations. Once modifying Federal Railroad Administration to prioritize missed railroad visual inspections, the modification would result in increasing visual inspections if testing invalid or not tested.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Federal Railroad Administration (Track and Rail and Infrastructure Integrity Compliance Manual) in view of McCasland (US 5856931).
Regarding claim 14, Federal Railroad Administration does not expressly disclose wherein the model can escalate a track segment for increased visual inspections if testing invalid or not tested.
McCasland discloses a computer system with a model/algorithm can escalate an inspection for increased inspections if testing invalid or not tested (see column 16 line 8 to line 25: in such a case, the percent overdue value can be weighted to either promote or demote an item in the scheduling priority of inspections, i.e. increasing priority of inspection based on a test that has not been done; and see column 4 lines 46-65: computer system implements the model/algorithm).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Federal Railroad Administration with the teachings of McCasland, i.e. prioritizing overdue inspections, for the advantageous benefit of drawing attention to areas that greatly need inspection attention to assure safe operations. Once modifying Federal Railroad Administration to prioritize missed railroad visual inspections, the modification would result in increasing visual inspections if testing invalid or not tested.
Claims 8-10 are rejected under 35 U.S.C. 103 as being unpatentable over Federal Railroad Administration (Track and Rail and Infrastructure Integrity Compliance Manual) in view of Jumonji (US 20240212116) and Chan (KR 20200077695).
Regarding claims 8 and 9, Federal Railroad Administration and Jumonji do not expressly disclose wherein the continuous variables are rescaled to match the categorical variables before contributing to a total score, and wherein the total score is a value for assessing frequency of visual track inspections.
Chan discloses a method of analyzing passing tonnage of a train wherein continuous variables are rescaled to match the categorical variables before contributing to a total score, and wherein the total score is a value for assessing frequency of visual track inspections (see page 4 paragraphs 3-10: discloses that measurement servers removes noise from measurements, uses spline interpolation to determine peak load, and axial load is determined by summing the load data measured at the same time of the left and right sides; see page 4 last 5 lines: measurements stored in used to determine rolling load, celebration, passing tonnage, passing tonnage per hour, passing tonnage per month, passing tonnage per month, passing tonnage per year, and total passing tonnage).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Federal Railroad Administration with the teachings of Chan, i.e. measuring the load on a railroad to determine MGT for a particular track, for the advantageous benefit of correctly setting an inspection frequency of the track that matches with actual load the track is experiencing.
Regarding claim 10, Federal Railroad Administration and Jumonji do not expressly disclose wherein the rescaled continuous variables are combined over individual track segments to generate a value for assessing frequency of visual track inspections.
Chan discloses wherein the rescaled continuous variables are combined over individual track segments to generate a value for assessing frequency of visual track inspections (see page 4 paragraphs 3-10: discloses that measurement servers removes noise from measurements, uses spline interpolation to determine peak load, and axial load is determined by summing the load data measured at the same time of the left and right sides; see page 4 last 5 lines: measurements stored in used to determine rolling load, celebration, passing tonnage, passing tonnage per hour, passing tonnage per month, passing tonnage per month, passing tonnage per year, and total passing tonnage, i.e. one can determine MGT from the measured load).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Federal Railroad Administration with the teachings of Chan, i.e. measuring the load on a railroad to determine MGT for a particular track, for the advantageous benefit of correctly setting an inspection frequency of the track that matches with actual load the track is experiencing.
Claims 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Federal Railroad Administration (Track and Rail and Infrastructure Integrity Compliance Manual) in view of Chan (KR 20200077695).
Regarding claims 18 and 19, Federal Railroad Administration does not expressly disclose wherein the continuous variables are rescaled to match the categorical variables before contributing to a total score and wherein the total score is a value for assessing frequency of visual track inspections.
Chan discloses a method of analyzing passing tonnage of a train wherein continuous variables are rescaled to match the categorical variables before contributing to a total score and wherein the total score is a value for assessing frequency of visual track inspections (see page 4 paragraphs 3-10: discloses that measurement servers removes noise from measurements, uses spline interpolation to determine peak load, and axial load is determined by summing the load data measured at the same time of the left and right sides; see page 4 last 5 lines: measurements stored in used to determine rolling load, celebration, passing tonnage, passing tonnage per hour, passing tonnage per month, passing tonnage per month, passing tonnage per year, and total passing tonnage).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Federal Railroad Administration with the teachings of Chan, i.e. measuring the load on a railroad to determine MGT for a particular track, for the advantageous benefit of correctly setting an inspection frequency of the track that matches with actual load the track is experiencing.
Regarding claim 20, Federal Railroad Administration does not expressly disclose wherein the rescaled continuous variables are combined over individual track segments to generate a value for assessing frequency of visual track inspections.
Chan discloses wherein the rescaled continuous variables are combined over individual track segments to generate a value for assessing frequency of visual track inspections (see page 4 paragraphs 3-10: discloses that measurement servers removes noise from measurements, uses spline interpolation to determine peak load, and axial load is determined by summing the load data measured at the same time of the left and right sides; see page 4 last 5 lines: measurements stored in used to determine rolling load, celebration, passing tonnage, passing tonnage per hour, passing tonnage per month, passing tonnage per month, passing tonnage per year, and total passing tonnage, i.e. one can determine MGT from the measured load).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Federal Railroad Administration with the teachings of Chan, i.e. measuring the load on a railroad to determine MGT for a particular track, for the advantageous benefit of correctly setting an inspection frequency of the track that matches with actual load the track is experiencing.
Relevant Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Bidaud (US 20140142868) discloses determining an inspection frequency of a track based on class, freight, passengers, speed and weight of the railcars, i.e. various continuous and categorical variables.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL J DALBO whose telephone number is (571)270-3727. The examiner can normally be reached M-F 9AM - 5PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Schechter can be reached at (571) 272-2302. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL J DALBO/Primary Examiner, Art Unit 2857