Joseph Mcnamara et al.

Patent Trials and Appeals Board

Aug 12, 2019

15246729 - (D) (P.T.A.B. Aug. 12, 2019)

UNITED STATES PATENT AND TRADEMARK OFFICE
UNITED STATES DEPARTMENT OF COMMERCE
United States Patent and Trademark Office
Address: COMMISSIONER FOR PATENTS
P.O. Box 1450
Alexandria, Virginia 22313-1450
www.uspto.gov
APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO.
15/246,729 08/25/2016 Joseph McNamara DHS-0114 7708
15614 7590 08/12/2019
U.S. Department of Homeland Security, S&T/OGC
Assistant General Counsel, Intellectual Property
Mail Stop 0205
245 Murray Lane
Washington, DC 20528
EXAMINER
HARWARD, SOREN T
ART UNIT PAPER NUMBER
1631
NOTIFICATION DATE DELIVERY MODE
08/12/2019 ELECTRONIC
Please find below and/or attached an Office communication concerning this application or proceeding.
The time period for reply, if any, is set in the attached communication.
Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the
following e-mail address(es):
Kelly.Hyndman@hq.dhs.gov
Megan.Smith1@associates.hq.dhs.gov
lavanya.ratnam@hq.dhs.gov
PTOL-90A (Rev. 04/07)

UNITED STATES PATENT AND TRADEMARK OFFICE
____________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
____________

Ex parte JOSEPH MCNAMARA, ALEXANDER DEMASI
MICHAEL BROGDEN, and RONALD KRAUSS1
____________

Appeal 2019-001103
Application 15/246,729
Technology Center 1600
____________

Before JEFFREY N. FREDMAN, DEBORAH KATZ, and JOHN G. NEW,
Administrative Patent Judges.

NEW, Administrative Patent Judge.

DECISION ON APPEAL

1 Appellants identify the real party-in-interest as the Government of the
United States of America, as represented by the Secretary of Homeland
Security. App. Br. 3.

Appeal 2019-001103
Application 15/246,729

2

SUMMARY
Appellants file this appeal under 35 U.S.C. § 134(a) from the
Examiner’s Final Rejection of claims 1–4, 6–9, 11–13, 15, 16, and 18–20 as
unpatentable under 35 U.S.C. § 103 over Doganaksoy et al. (US
2004/0083083 A1, April 29, 2004) (“Doganaksoy”); Stat-Ease Inc., Design-
Expert 9 User’s Guide, Mixture Tutorial (May 2, 2014) (“DX9”); and Kury
et al. (US 5,958,299, September 28, 1999) (“Kury”). App. Br. 9.
We have jurisdiction under 35 U.S.C. § 6(b).
We AFFIRM.

NATURE OF THE CLAIMED INVENTION
Appellants’ invention is directed to a system and method for
designing and forming explosive simulants by matching tabulated physical
properties of simulants to those of explosive threats. Spec. ¶ 17.

REPRESENTATIVE CLAIM
Claim 1 is representative of the claims on appeal and recites:
1. A method for identifying and forming a simulant, the
method comprising:

displaying a listing of explosive threat compounds retrieved from
a threat database based upon a user selection of a graphical
user interface (GUI) control corresponding to the
explosive threat compounds, wherein each explosive
threat compound in the threat database is associated with
one or more metrics having target values;

Appeal 2019-001103
Application 15/246,729

3

receiving a selection of an explosive threat compound from the
displayed listing of explosive threat compounds using a
selection control of the GUI;

displaying a listing of simulant ingredients retrieved from an
ingredient database based upon the user selection of a GUI
control corresponding to the simulant ingredients, wherein
each simulant ingredient in the ingredient database is
associated with one or more metrics having ingredient
values;

receiving a selection of a plurality of ingredients from the
displayed listing of simulant ingredients;

identifying for evaluation, using processing circuitry, one or
more metrics based on a type of the selected explosive
threat compound, the one or more metrics being physical
properties including at least one of electron density,
effective atomic number, mass attenuation coefficient,
chemical compound ratio, dielectric constant and
millimeter wave reflectivity;

determining, using the processing circuitry, proportions of each
of the plurality of ingredients based on the ingredient
values of the selected plurality of ingredients;

outputting the determined proportions of each of the plurality of
ingredients if a target point specified by the target values
of the selected explosive threat compound lies within a
convex set defined by the ingredient values of the plurality
of ingredients;

receiving user input to adjust the convex set defined by the
ingredient values to more closely conform to the target
values of the explosive threat compound;

identifying alternative ingredients that conform to the target
values of the explosive threat compound as represented by
Appeal 2019-001103
Application 15/246,729

4

the user adjusted convex set, such that the alternative
ingredients serve as the plurality of ingredients;

and forming the simulant having the plurality of ingredients
based on the proportions of each of the plurality of
ingredients.

App. Br. 22–23.

ISSUES AND ANALYSIS
We agree with, and expressly adopt, the Examiner’s findings,
reasoning, and conclusion that the claims are prima facie obvious. We
address below the arguments raised by Appellants.

Issue 1
Appellants argue that the prior art does not teach the step of
“receiving user inputs to adjust the convex set defined by the ingredient
values.” App. Br. 14.
Analysis
The Examiner finds that Kury teaches “[s]ubstituting completely inert
simulants for explosives offers significant benefits in testing explosive
detection systems and in training operators.” Final Act. 7 (citing Kury col.
2, ll. 19–21). The Examiner finds that Kury teaches the simulants are
physical mixtures of two or more non-explosive components designed to
mimic explosive materials. Id. at 6 (citing Kury col. 2, ll. 37–40, 53–55).
Simulants mimic explosive materials by matching physical form and
homogeneity, x-ray transmission properties, mass density, and effective
Appeal 2019-001103
Application 15/246,729

5

atomic number (“Zeff”). Id. at 6–7 (citing Kury col. 2, ll. 40–43). The
Examiner finds that Kury teaches:
Explosive simulants can be designed, therefore, by carefully
selecting the composition and amount of the material
components (reagents), their measured mass densities, their grain
sizes (if appropriate), and the theoretical effective atomic number
of the final composition. Using these considerations, explosive
simulants were created that mimic the physical form, mass
density and effective atomic number of all types of explosives
(powders, plastics, and emulsions/gels).

Id. at 7 (citing Kury col. 5, ll. 9–17).
The Examiner finds that Doganaksoy teaches a material creation
system which can be used to design a material having desired properties.
Final Act. 4 (citing Doganaksoy ¶ 25). The Examiner finds that Doganaksoy
teaches a user may input desired properties and prioritize certain properties
by maximizing a property value, minimizing the property value, hitting a
target point value for the property value, or keeping property values within a
given range of acceptable values. Id.
The Examiner finds that Doganaksoy teaches searching a database for
design spaces having the desired properties and displaying the results to the
user. Ans. 5. (citing Doganaksoy ¶ 26). The Examiner finds that
Doganaksoy teaches that “design spaces typically represent a designed
experiment around a common set of ingredients, and may include the
following as independent (or manipulated) variables: relative proportions of
the ingredients, quality parameters of these ingredients, and processing
parameters, with the final material properties serving as the dependent (or
response) variables.” Id. at 7 (citing Doganaksoy ¶ 3). The Examiner finds
Doganaksoy teaches that users may select which design spaces they wish to
Appeal 2019-001103
Application 15/246,729

6

have scored according to user selected property values and priorities. Id. at
5 (citing Doganaksoy ¶¶ 26, 29). The Examiner finds that Doganaksoy
teaches several design spaces can be scored simultaneously and the
comparison results are output to the user. Final Act. 5 (citing Doganaksoy
¶ 39). The Examiner finds that by presenting and scoring various design
spaces, i.e., common sets of ingredients, following user input of selected
property values, Doganaksoy teaches the step of identifying alternative
ingredients that conform to the target values of the desired material. See
Ans. 7.
The Examiner finds DX9 teaches a software system with a graphical
user interface for optimizing a mixture of ingredients for a desired set of
physical properties. Final Act. 5 (citing DX9 p. 21). The Examiner finds
DX9 teaches the software includes an optimization tool for specifying
optimal ranges of the ingredients and physical properties of the mixture. Id.
(citing DX9 pp. 22–24). The Examiner finds DX9 teaches “solving an
optimization problem to determine proportions of the ingredients that create
a mixture that has optimal desired physical properties” and “reporting to the
solutions.” Id. at 5–6 (citing DX9 pp. 24–26). The Examiner finds that
DX9 teaches the software explores the impact of changing multiple
components on multiple responses by combining numerical optimization
with graphical analysis. Id. 6 (citing DX9 pp. 36–37).
Appellants contend that the rejection “fails to recognize or account for
the claimed concept of the user-adjusted set of values,” specifically claimed
as “receiving user input to adjust the convex set defined by the ingredient
values….” App. Br. 14. Appellants contend that:
Appeal 2019-001103
Application 15/246,729

7

As set forth in Doganaksoy at [0025], a user can search for
candidate design spaces, and input desired property values,
goals, etc., but at no point does Doganaksoy describe a selected
design space arising due to initial values that have been
submitted, with output presented to the user, and the initial values
being subsequently adjusted by the user.

App. Br. 15. With respect to the “convex set,” Appellants contend the
claimed invention refers to “a set of ‘selected N-dimensional ingredient
points’ . . . that is a single data point for each dimension/property. The
convex set is then defined as a region within the N-dimensional space
defined by the N-dimensional ingredient points.” Reply Br. 5–6 (citing
Spec. ¶ 31). Appellants contend that the convex set is illustrated by Figure 4
of their Specification, in which the shaded triangle represents a convex set,
the three vertices of the triangle represent three ingredients, and the point
inside the triangle represents the explosive threat. Id. at 2–3. Figure 4 of
Appellants’ Specification is reproduced below:
Appeal 2019-001103
Application 15/246,729

8

Figure 4 is a schematic that shows a graphical user interface.
Spec. ¶ 12

Appellants also point to Figure 4 to emphasize the difference between
“metric” and “value.” Id. at 2. According to Appellants, in Figure 4, each
“metric” corresponds to an axis, e.g., mass attenuation coefficient, Z
effective, and density,” whereas “values” correspond to the given values
along the given axis. Id. The system plots the ingredients in three
dimensions according to their ingredient values corresponding to each
metric. Id.
The Appellants argue that the claimed convex set is distinct from “the
mesh of potential new ingredients” cited by the Examiner. Reply Br. 5.
Appellants particularly argue:
Appeal 2019-001103
Application 15/246,729

9

The mesh in Doganaksoy is defined by a multitude of data values
corresponding to the various properties of potential new
materials calculated for a plurality of different percentages of
ingredients that make up the potential new material. As such, the
mesh constitutes a plurality of data points from which one
possible new material is selected. . . . In contrast, the claimed
invention refers to the use of a convex set that is defined by a set
of “selected N-dimensional ingredient points,” . . . that is a single
data point for each dimension/property. The convex set is then
defined as a region within the N-dimensional space defined by
the N-dimensional ingredient points.

Id. at 5–6 (citing Doganaksoy ¶¶47–53).
We are not persuaded. As shown by the Examiner, Kury teaches
creating simulant formulations by matching the properties of explosive
threats with combinations of selected non-explosive ingredients. Kury
col. 5, ll. 9–18. The ingredients each have ingredient values, e.g., amount,
mass density, and effective atomic number, associated with specific metrics.
See id. However, Kury does not teach an automated method for determining
ingredient combinations for simulant formulations according to ingredient
values. Doganaksoy teaches designing a material by inputting the desired
properties of the material, conducting an initial search of ingredients, i.e., gn
spaces, and presenting those results to the user. See Doganaksoy ¶¶ 25–26.
The user then selects which design spaces they wish to optimize by scoring
property values. Id. at ¶ 29. In other words, the user receives initial search
results, and then inputs adjustments to more closely conform to the
properties of the desired material. See id.
With respect to the “convex set,” the claims require a “convex set
defined by the ingredient values of the plurality of ingredients.” As
discussed supra, Kury teaches using ingredient values associated with
Appeal 2019-001103
Application 15/246,729

10

metrics that match simulant ingredients to explosive threats. The Examiner
finds that Doganaksoy teaches a mesh of acceptable ranges of ingredient
proportions for one or more design spaces. Ans. 4 (citing Doganaksoy ¶ 47).
Doganaksoy teaches building a mesh around n components, i.e., ingredients,
using a user-desired number of increments, i.e., ingredient values.
Doganaksoy ¶ 47. Doganaksoy teaches a list of materials that fall within the
desired range of ingredient values, and calculating properties, i.e., metrics,
for the materials. Id. at ¶ 53.
Although Doganaksoy does not teach a graphical interface for
adjusting the mesh, DX9 teaches a graphical optimization system in which
the user can adjust constraints and automatically identify proportions of
ingredients for desired physical properties of materials within a contour.
Ans. 6 (citing DX9 p. 32 (“By shading out regions that fall outside of
specified contours, you can identify desirable sweet spots for each response
— windows of opportunity where all specifications can be met”)).
Therefore, Doganaksoy in combination with DX9 and Kury teaches
receiving user input to adjust the convex set defined by the ingredient values
as claimed. Accordingly, we are not persuaded that the Examiner erred.

Issue 2
Appellants argue that the prior art does not teach “identifying
alternative ingredients that conform to the target values of the explosive
threat compound as represented by the user adjusted convex set.” App. Br.
14.
Appeal 2019-001103
Application 15/246,729

11

Analysis
Appellants argue that “Doganaksoy’s step of merely presenting
multiple candidates for user selection and comparison is fundamentally
different than receiving user input, providing output, receiving user
adjustment, and identifying alternative ingredients based on the user
adjustment.” App. Br. 16. Appellants contend that “the different design
spaces cannot constitute the claimed alternative ingredients, because
Doganaksoy does not state there is a changing of ingredients, and it is
merely conjecture on the part of the Examiner to conclude that different
design spaces inherently include alternative ingredients.” Id. Appellants
further argue that Doganaksoy fails to show identifying alternative
ingredients resulting from the user input to adjust the convex set. Id. at 17.
We are not persuaded. The Examiner finds that Doganaksoy teaches a
design space is a common set of ingredients, and in order to present different
design spaces, Doganaksoy necessarily presents different sets of ingredients
or “alternative ingredients.” Ans. 7. We agree. Doganaskoy teaches that
users score design spaces by adjusting property values, e.g., maximizing or
minimizing properties, hitting a specific target value, or setting a range.
Doganaksoy ¶¶ 29–37. Doganaksoy teaches that the scored designs spaces
are output to the user. Id. at ¶ 38. Doganaksoy teaches that “[t]hereafter . . .
users may be given the opportunity to predict new materials” by selecting
design spaces for further scoring, i.e., adjusting, “so that new, possible better
matching materials can be created/predicted.” Id. at ¶ 39. Doganaksoy
teaches “embodiments may be designed so that several design spaces can be
scored simultaneously using transfer functions. Once all the desired design
spaces are scored with transfer functions, users may be given the opportunity
Appeal 2019-001103
Application 15/246,729

12

to select various design spaces to compare [].” Id. Similarly, with respect to
the mesh of potential new materials, Doganaksoy teaches:
Once these new formulations/materials are predicted, overall
match scores may be calculated for each of these materials as
well, just as described for existing experimental runs above.
Next, the materials may be sorted by their respective overall
match scores, and the results may be output to the user. These
results preferably comprise data of existing experimental runs as
well as predicted materials, sorted accordingly, so users can
easily identify whether an existing experimental run or a newly-
predicted material best matches the desired set of properties.

Id. at ¶ 53. Doganaksoy thus teaches that the system predicts new
formulations/materials that match scoring inputs from the user and outputs
the new formulations/materials to the user. By predicting new formulations
or materials, that may take the form of a number of design spaces,
Doganaksoy teaches identifying alternative ingredients that conform to the
target values represented by the user adjusted input. We are consequently
not persuaded that the Examiner erred in concluding the claims are obvious
over Doganaksoy, DX9, and Kury, and we affirm the Examiner’s rejection
of the claims.

Issue 3
Appellants argue that the rejection fails to address each and every
claim element. App. Br. 19.

Analysis
Appellants contend that the Final Office action lacks “clearly
articulated reasoning to explain which aspects of the prior art are being
Appeal 2019-001103
Application 15/246,729

13

analogized to which aspects of the claims.” App. Br. 19. Appellants
contend the “Final Office Action does not even address every word in
Appellant’s claims, resorting simply to using ellipses to paraphrase the claim
language.” Id. Appellants contend “[a]ll words in a claim must be
considered in judging the patentability of that claim against the prior art.”
Reply Br. 6 (citing MPEP 2143.03).
We are not persuaded. The Examiner “explicitly indexed the
limitations by briefly quoting the first few words of the limitation and
assigning that limitation an index letter, then listing the corresponding prior
art teachings using the same index letter.” Ans. 8. Applying this format, the
Examiner identified the specific citations to the prior art references
combined in the rejection and applied the citations to the claims. Final Act.
4–7. Thus, the Examiner established prima facie obviousness, by
“notify[ing] the applicant … [by] stating the reasons for [its] rejection, or
objection or requirement, together with such information and references as
may be useful in judging of the propriety of continuing the prosecution of
[the] application.” In re Jung, 637 F.3d 1356, 1362 (Fed. Cir. 2011).
Appellants have presented arguments as to which of the recited elements are
allegedly lacking from the combination, which we have addressed supra.
Accordingly, we are not persuaded that the Examiner erred by failing to
address each and every claim element.

DECISION
The Examiner’s rejection of claims 1–4, 6–9, 11–13, 15, 16, and 18–
20 under 35 U.S.C. § 103 is affirmed.
Appeal 2019-001103
Application 15/246,729

14

No time period for taking any subsequent action in connection with this
appeal may be extended under 37 C.F.R. § 1.136(a)(l)(iv).

AFFIRMED