DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
1. 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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
2. Claims 1-20 rejected under 35 U.S.C. 103 as being unpatentable over Yoo et al. ("Ship Route Optimization Considering On-Time Arrival Probability Under Environmental Uncertainty").
Regarding claims 1, 15, and 20, Yoo discloses a method comprising:
generating simulated routes from a first location to a second location (section IV, par.1-2: "numerical simulations of the route optimization from Tokyo to San Francisco"; "the Pareto set of ship routes is calculated), including a first simulated route under a first environmental condition and a second simulated route under a second environmental condition (section II-A, par.2: "ship speed model with input variable sets such as the engine RPM, weather ... "; see also figs. 2-3 representing engine power and ship speed influenced by wave height, wind speed and Beaufort Scale);
generating an uncertainty score for each of the simulated routes (fig.5 and section IV, par.2: "the Pareto set of ship routes is calculated using the weather information as shown in Fig. 5 (a), and then the uncertainty of arrival time for the obtained Pareto set is calculated");
comparing a first uncertainty score of the first simulated route and a second uncertainty score of the second simulated route (figs.5b-c; fig.6 and section IV, par.4: "we compared the probability distributions of arrival time for Case 1 with another candidate in the Pareto set, whose ETA is smaller than that of Case 1. For convenience, the other candidate is called Case 0" (comparing probability distributions to each other); or end of section IV: “the uncertainty of the arrival time, arising from environmental disturbances, is calculated and constraints are set to eliminate the undesirable solutions that might not arrive on time.” (comparing uncertainty scores to thresholds));
determining, using the comparison, an optimal simulated route from the simulated routes (section IV, par.4: "Case 1 exhibits a higher probability of timely arrival compared to Case 0, which means that not only the ETA but also the probability of arrival needs to be evaluated quantitatively"); and
providing the optimal simulated route to a ship for traversing a portion of water (figs.7-8).
Yoo does not disclose comparing a first uncertainty score of the first simulated route to a second uncertainty score of the second simulated route.
However, the claim language requires only that the uncertainty scores are compared to something, not necessarily to each other.
But even under the narrower interpretation, it would have been obvious before the effective filing date of the claimed invention to modify Yoo to compare the uncertainty scores to each other, as suggested by Yoo (by his comparison of the probability distributions to each other) and well known in the art, in order to maximize the probability that the ship will arrive at the destination on time, with predictable results.
Regarding claims 2 and 16, Yoo further discloses that generating the uncertainty scores comprises: generating two or more uncertainty distributions, including a first uncertainty distribution using data representing the first environmental condition and a second uncertainty distribution using data representing the second environmental condition; and combining a portion of the two or more uncertainty distributions to generate a combined uncertainty distribution (fig.6: this figure shows a multiplicity of probability distributions, which inherently constitute uncertainty distributions, for each of the routes Case 1 and Case 0. These uncertainty distributions are combined in the form of the curves of fig.6).
Regarding claims 3 and 17, Yoo further discloses that generating, using a combined uncertainty distribution generated using data representing the first environmental condition along a portion of the first simulated route, the first uncertainty score; and generating, using a combined uncertainty distribution generated using data representing the second environmental condition along a portion of the second simulated route, the second uncertainty score (fig.6: the uncertainty scores are the probabilities of timely arrival with the predetermined time constraint shown in this figure; see section IV, par.4: "Case 1 exhibits a higher probability of timely arrival compared to Case 0").
Regarding claims 4 and 18, Yoo further discloses that generating the uncertainty scores comprises: obtaining one or more values representing environmental conditions from an ocean model (figs. 2-3, 7-8 showing the modelled effects of wave height, wind speed and Beaufort Scale).
Regarding claims 5 and 19, Yoo further discloses that generating the first uncertainty score comprises obtaining one or more values representing the first environmental condition within an ocean region traversed by the first simulated route from an ocean model; and generating the second uncertainty score comprises obtaining one or more values representing the second environmental condition within an ocean region traversed by the second simulated route from the ocean model (figs. 2-3, 7-8 showing the modelled effects of wave height, wind speed and Beaufort Scale).
Regarding claim 6, Yoo further discloses that the first location and the second location represent sea ports (section IV: "Tokyo to San Francisco").
Regarding claim 7, Yoo further discloses obtaining initial data from the ship prior to generating the simulated routes from the first location to the second location (section II-A, explaining the preliminary development of a ship model).
Regarding claim 8, Yoo further discloses that the initial data includes data indicating the first location to the second location (section IV: "Tokyo to San Francisco").
Regarding claim 9, Yoo further discloses that the initial data includes route preferences of the ship (section IV: "Tokyo to San Francisco").
Regarding claim 10, Yoo further discloses that the initial data includes details of the ship (section II-A, explaining the preliminary development of a ship model).
Regarding claim 11, Yoo further discloses that generating the uncertainty scores comprises: obtaining uncertainty data representing at least one of (1) one or more wait times or (2) weather events; and using the uncertainty data to generate the uncertainty scores (figs. 2-3, 7-8 showing the modelled effects of wave height, wind speed and Beaufort Scale).
Regarding claim 12, Yoo further discloses that generating the simulated routes from the first location to the second location comprises: determining a path along water that connects the first location to the second location; and wherein generating the uncertainty scores comprises predicting current or weather events along at least a portion of the path (section IV: "the weather data were based on European Centre for Medium-Range Weather Forecasts").
Regarding claim 13, Yoo further discloses that predicting current or weather events along at least the portion of the path comprises: sampling from a starting distribution representing potential current or weather events along the portion of the path (section IV: "the resolution of the weather data was 1.0° for latitude and 1.0° for longitude". Therefore, one individual for SPEA2 consisted of a set of position and speed conditions as shown in Fig. 4 (a)").
Regarding claim 14, Yoo further discloses that sampling from the starting distribution representing potential current or weather events along the portion of the path comprises: sampling from the starting distribution using a Monte Carlo method for sampling distributions (paragraph 3 of section Ill specifies that "some of the initial population are randomly generated", which means that some of the considered routes are randomly generated, assessed and taken into account for the aggregated results (see figs.SA, 5B and SC). This method is a Monte Carlo method).
3. Claims 1-20 rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. (U.S. Patent Application Publication # US 2010/0280750).
Regarding claims 1, 15, and 20, Chen discloses a method comprising:
generating simulated routes (step 903 and par.120) from a first location to a second location (step 900 and par.119), including a first simulated route under a first environmental condition and a second simulated route under a second environmental condition (par.121);
generating an uncertainty score for each of the simulated routes (step 904 and par.121 : the "probability of reaching the end point from the start point" corresponds to an uncertainty score);
comparing a first uncertainty score of the first simulated route and a second uncertainty score of the second simulated route (step 906, par.124 and par.115);
determining, using the comparison, an optimal simulated route from the simulated routes (step 908-910 and par.114-115); and
providing the optimal simulated route to a ship for traversing a portion of water (step 910 and par.125).
Chen does not disclose comparing a first uncertainty score of the first simulated route to a second uncertainty score of the second simulated route.
However, the claim language requires only that the uncertainty scores are compared to something, not necessarily to each other.
But even under the narrower interpretation, it would have been obvious before the effective filing date of the claimed invention to modify Chen to compare the uncertainty scores to each other, as suggested by Chen (par.115) and well known in the art, in order to maximize the probability that the ship will arrive at the destination on time, with predictable results.
Regarding claims 2 and 16, Chen further discloses that generating the uncertainty scores comprises: generating two or more uncertainty distributions, including a first uncertainty distribution using data representing the first environmental condition and a second uncertainty distribution using data representing the second environmental condition; and combining a portion of the two or more uncertainty distributions to generate a combined uncertainty distribution (figs.7-8, par.122 "probability distribution", par.141-142 and steps 1206 and 1208 of fig.12 "combine the probabilities of each segment").
Regarding claims 3 and 17, Chen further discloses that generating, using a combined uncertainty distribution generated using data representing the first environmental condition along a portion of the first simulated route, the first uncertainty score; and generating, using a combined uncertainty distribution generated using data representing the second environmental condition along a portion of the second simulated route, the second uncertainty score (figs.7-8, par.122 "probability distribution", par.141-142 and steps 1206 and 1208 of fig.12 "combine the probabilities of each segment").
Regarding claims 4 and 18, Chen further discloses that generating the uncertainty scores comprises: obtaining one or more values representing environmental conditions from an ocean model (fig.4 and par.122-123 "wave height", "currents, tides").
Regarding claims 5 and 19, Chen further discloses that generating the first uncertainty score comprises obtaining one or more values representing the first environmental condition within an ocean region traversed by the first simulated route from an ocean model; and generating the second uncertainty score comprises obtaining one or more values representing the second environmental condition within an ocean region traversed by the second simulated route from the ocean model (fig.4 and par.122-123 "wave height", "currents, tides").
Regarding claim 6, Chen further discloses that the first location and the second location represent sea ports (par.4).
Regarding claim 7, Chen further discloses obtaining initial data from the ship prior to generating the simulated routes from the first location to the second location (par.123).
Regarding claim 8, Chen further discloses that the initial data includes data indicating the first location to the second location (par.4).
Regarding claim 9, Chen further discloses that the initial data includes route preferences of the ship (fixed departure and arrival locations in fig.6).
Regarding claim 10, Chen further discloses that the initial data includes details of the ship (par.123).
Regarding claim 11, Chen further discloses that generating the uncertainty scores comprises: obtaining uncertainty data representing at least one of (1) one or more wait times or (2) weather events; and using the uncertainty data to generate the uncertainty scores (par.6-7 and par.12).
Regarding claim 12, Chen further discloses that generating the simulated routes from the first location to the second location comprises: determining a path along water that connects the first location to the second location; and wherein generating the uncertainty scores comprises predicting current or weather events along at least a portion of the path (par.121, 123, 127).
Regarding claim 13, Chen further discloses that predicting current or weather events along at least the portion of the path comprises: sampling from a starting distribution representing potential current or weather events along the portion of the path (par.130, 140-141 and fig.12).
Regarding claim 14, Chen in view of common knowledge in the art further discloses that sampling from the starting distribution representing potential current or weather events along the portion of the path comprises: sampling from the starting distribution using a Monte Carlo method for sampling distributions (see at least Du Jian "Machine Learning-Based Approach to Liner Shipping Schedule Design": fig.2 and step 1 of p.418 "voyage data of S groups simulated by Monte Carlo method").
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHELLEY CHEN whose telephone number is (571)270-1330. The examiner can normally be reached Mondays through Fridays.
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/Shelley Chen/
Patent Examiner
Art Unit 3665
September 4, 2026
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