Ex Parte Belenky et al

Patent Trial and Appeal Board

Oct 31, 2017

12253703 (P.T.A.B. Oct. 31, 2017)

UNITED STA TES p A TENT AND TRADEMARK OFFICE
APPLICATION NO. FILING DATE
12/253,703
44192 7590
Liang IP, PLLC
1750 112 Avenue NE
Suite D-151
Bellevue, WA 98004
10/17/2008
11/02/2017
FIRST NAMED INVENTOR
Gregory Belenky
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
ATTORNEY DOCKET NO. CONFIRMATION NO.
271588014US1 9910
EXAMINER
DELI CH, STEPHANIE ZAGARELLA
ART UNIT PAPER NUMBER
3623
NOTIFICATION DATE DELIVERY MODE
11/02/2017 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):
jim@liangip.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
BEFORE THE PATENT TRIAL AND APPEAL BOARD
Ex parte GREGORY BELENKY and HANS VAN DONGEN
Appeal2016-005155
Application 12/253,703 1
Technology Center 3600
Before ROBERT E. NAPPI, JAMES W. DEJMEK, and
JOYCE CRAIG, Administrative Patent Judges.
DEJMEK, Administrative Patent Judge.
DECISION ON APPEAL
Appellants appeal under 35 U.S.C. § 134(a) from a Final Rejection of
claims 1-24. We have jurisdiction over the pending claims under 35 U.S.C.
§ 6(b ).
We affirm.
1 Appellants identify Washington State University as the real party in
interest. Br. 1.
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Application 12/253,703
STATEMENT OF THE CASE
Introduction
Appellants' disclosed and claimed invention relates to "systems and
methods for rostering and scheduling to reduce fatigue and its consequences
by integrating mathematical models capable of predicting fatigue with
software/hardware components capable of rosters and/or work schedules."
Spec. i-f 7.
Claim 1 is representative of the subject matter on appeal and is
reproduced below with the disputed limitation emphasized in italics:
1. A computer implemented method for generating a roster for an
operation, comprising:
receiving information of a plurality of shifts of the operation and
resource units for an objective function, the objective function
encapsulating at least one operational constraint of the operation,
wherein the objective function includes a fatigue module configured to
calculate a fatigue level for the individual resource units;
evaluating the objective function to
generate a plurality of possible rosters within the
operational constraint for assigning the resource units to the
individual shifts, each possible roster including at least some of
the resource units assigned to the plurality of shifts;
for each of the possible rosters,
for each resource unit in the roster, calculate a fatigue
level of the resource unit with the fatigue module based at
least in part on the shift assigned to the resource unit in the
roster by tracking a homeostatic and circadian processes over
time across estimated periods of wakefulness and sleep of the
resource unit;
calculate an overall fatigue metric for the roster by
analyzing the calculated fatigue levels of the resource units
assigned to the shifts in the roster;
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select a roster from the plurality of generated possible
rosters based on the overall fatigue metrics of the individual
rosters; and
implementing the selected roster for the resource units during
operation to reduce a fatigue level of the resource units within the
operational constraint of the operation.
The Examiner's Rejections
1. Claims 1-24 stand rejected under 35 U.S.C. § 101 as being
directed to non-statutory subject matter. Final Act. 6-8.
2. Claims 1-3, 5-9, and 11-24 stand rejected under 35 U.S.C.
§ 103(a) as being unpatentable over Zhu (US 2007/0192263 Al; Aug. 16,
2007); Konop (US 2005/0154634 Al; July 14, 2005); and Moore-Ede (US
2006/0200008 Al; Sept. 7, 2006).2 Final Act. 8-36.
ANALYSIS3
Re} ection under 3 5 U.S. C. § 101
Appellants dispute the Examiner's conclusion that the pending claims
are directed to patent-ineligible subject matter under 35 U.S.C. § 101.
Br. 7-10. In particular, Appellants argue the Examiner has not specifically
identified what abstract idea the claims are allegedly directed to and that the
Examiner has compared the claims "to a concept not relevant to the claimed
subject matter." Br. 8-9. Further, Appellants contend that, when considered
2 The Examiner has withdrawn the rejection under 35 U.S.C. § 103(a) of
claims 4 and 10. Ans. 2.
3 Throughout this Decision, we have considered the Appeal Brief, filed
August 31, 2015 ("Br."); the Examiner's Answer, mailed February 11, 2016
("Ans."); and the Final Office Action, mailed March 31, 2015 ("Final Act."),
from which this Appeal is taken.
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as a whole, the claims amount to "significantly more than an abstract idea."
Br. 10. Specifically, Appellants assert the claims relate to particular
variables and how the variables are used and gathered, and the process by
which a roster is selected and used. Br. 10.
For the reasons discussed below, Appellants have not persuaded us of
error. The Supreme Court's two-step framework guides our analysis. Alice
Corp. Pty. Ltd. v. CLS Banklnt'l, 134 S. Ct. 2347, 2355 (2014). If a claim
falls within one of the statutory categories of patent eligibility (i.e., a
process, machine, manufacture or composition of matter) then the first
inquiry is whether the claim is directed to one of the judicially-recognized
exceptions (i.e., a law of nature, a natural phenomenon, or an abstract idea).
If so, the second step is to determine whether any element, or combination of
elements, amounts to significantly more than the judicial exception.
Although the independent claims each broadly fall within the statutory
categories of patentability, the Examiner determines the claims are directed
to a judicially-recognized exception-i.e., an abstract idea. Final Act. 6-8;
Ans. 2--4. In particular, the Examiner determines the claims are directed to
the abstract idea of a mathematical relationship or formula. Final Act. 6; see
also Ans. 3--4 (the claims are "directed toward the abstract idea of evaluating
an objective function to generate a roster where fatigue levels are calculated
and an overall fatigue level is used to select a roster for implementation").
Instead of using a definition of an abstract idea, "the decisional
mechanism courts now apply is to examine earlier cases in which a similar
or parallel descriptive nature can be seen-what prior cases were about, and
which way they were decided." Amdocs (Isr.) Ltd. v. Openet Telecom, Inc.,
841F.3d1288 (Fed. Cir. 2016) (citing Elec. Power Grp., LLC v. Alstom
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S.A., 830 F.3d 1350, 1353-54 (Fed. Cir. 2016)); accord United States Patent
and Trademark Office, July 2015 Update: Subject Matter Eligibility
(July 30, 2015), p. 3,
https://www.uspto.gov/sites/default/files/documents/ieg-july-2015-
update.pdf (instructing examiners that "a claimed concept is not identified as
an abstract idea unless it is similar to at least one concept that the courts
have identified as an abstract idea."). As part of this inquiry, we must "look
at the 'focus of the claimed advance over the prior art' to determine if the
claim's 'character as a whole' is directed to excluded subject matter."
Affinity Labs. of Texas v. DirecTV, LLC, 838 F.3d 1253, 1257 (Fed. Cir.
2016).
Here, Appellants' claims are directed to generating a roster (i.e.,
schedule) based on at least one operating constraint (e.g., a rule,
requirement, or preference) and a fatigue value associated with the resources
(i.e., the people being added to the schedule). As part of the roster
generation, a plurality of possible rosters are generated and for each possible
roster a fatigue level of each resource is calculated as well as an overall
fatigue level (i.e., fatigue metric or fatigue value) for the roster. Based on
the calculated fatigue metrics, a roster is selected from the plurality of
possible rosters and is implemented.
Our reviewing court has concluded that abstract ideas include
"collecting information, including when limited to particular content." Elec.
Power, 830 F.3d at 1353. Further, "analyzing information by steps people
go through in their minds, or by mathematical algorithms, without more,
[are] mental processes within the abstract-idea category." Elec. Power, 830
F.3d at 1354. Additionally, "1) collecting data, 2) recognizing certain data
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within the collected data set, and 3) storing that recognized data in memory"
is also an abstract idea. Content Extraction & Transmission LLC v. Wells
Fargo Bank, N.A., 776 F.3d 1343, 1347 (Fed. Cir. 2014). Similarly, the
court has concluded that "collecting, displaying, and manipulating data" is
an abstract idea. Intellectual Ventures I LLC v. Capital One Fin. Corp., 850
F.3d 1332, 1340 (Fed. Cir. 2017). Also, as the Examiner identified (see
Final Act. 7; Ans. 3--4), in Digitech Image Techs., LLC v. Elec.for Imaging,
Inc., 758 F.3d 1344, 1350 (Fed. Cir. 2014), "a process of organizing
information through mathematical correlations and is not tied to a specific
structure or machine" is an abstract idea.
Further, merely combining several abstract ideas does not render the
combination any less abstract. RecogniCorp, LLC v. Nintendo Co., Ltd., 855
F.3d 1322, 1327 (Fed. Cir. 2017) ("Adding one abstract idea (math) to
another abstract idea ... does not render the claim non-abstract."); see also
FairWarning IP, LLC v. Iatric Sys., Inc., 839 F.3d 1089, 1094 (Fed. Cir.
2016) (determining the pending claims were directed to a combination of
abstract ideas).
In the Specification, Appellants describe the objective function as a
mathematical model. Spec. ,-r 15. Thus, as claimed, to generate a roster,
information is received and used to generate a plurality of possible rosters
based on operational constraints (i.e., a restriction or rule (see Spec. ,-r 12)),
and calculations of a fatigue metric for (i) each individual resource based on
fatigue data, and (ii) collectively, for each possible roster, are used to select
the roster to be implement. Similar to Digitech, and contrary to Appellants'
assertion (see, e.g., Br. 9), information (e.g., shift needs, resource data,
operational constraints, and fatigue data) is organized through mathematical
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correlations (i.e., as part of the mathematical model of the objective
function). Further, the receipt of data and analysis of the data also fall
within the realm of abstract ideas. Accordingly, we agree with the Examiner
that the claims are directed to an abstract idea.
Because we determine the claims are directed to an abstract idea, we
analyze the claims under step two to determine if there are additional
limitations that individually, or as an ordered combination, ensure the claims
amount to "significantly more" than the abstract idea. Alice, 134 S. Ct. at
2357. The implementation of the abstract idea involved must be "more than
the performance of 'well-understood, routine, [and] conventional activities
previously known to the industry."' Content Extraction, 776 F.3d at 1347-
48.
Here, we agree with the Examiner that the additional limitations,
separately, or as an ordered combination, do not provide meaningful
limitations (i.e., do not add significantly more) to transform the abstract idea
into a patent eligible application. Final Act. 7-8; Ans. 4. As described in
the Specification, "[ t ]he objective function 201 can be minimized (or
maximized) using mathematical and/or numerical approaches typically
performed with the use of a computer." Spec. i-f 21. The relevant question is
whether the claims do more than simply instruct the practitioner to
implement the idea on a generic computer. See Alice, 134 S. Ct. at 2359. As
the Examiner explains:
The claims do not include additional elements that are sufficient
to amount to significantly more than the judicial exception
because the additional elements merely recite routine and
conventional activities previously known in the industry.
Specifically, the claims set forth receiving information, selecting
data and implementing a selection, which can be interpreted as
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broadly as outputting data. Thus each of these additional
elements require no more than a generic computer to perform
their functions and are well understood, routine and conventional
activities that could be performed by any computer
implementation.
Final Act. 7-8. See also BuySAFE, Inc. v. Google, Inc., 765 F.3d 1350,
1355 (Fed. Cir. 2014) ("That a computer receives and sends the information
over a network-with no further specification-is not even arguably
inventive.").
Appellants also argue the claims "do not preempt any 'building blocks
of ingenuity, scientific exploration, technological work, and the modem
economy."' Br. 9.
"[W]hile preemption may signal patent ineligible subject matter, the
absence of complete preemption does not demonstrate patent eligibility."
FairWarning IP, 839 F.3d at 1098 (quotingAriosa Diagnostics, Inc. v.
Sequenom, Inc., 788 F.3d 1371, 1379 (Fed. Cir. 2015); see also OIP Techs.,
Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1362---63 (Fed. Cir. 2015), cert.
denied, 136 S. Ct. 701, 193 (2015) ("[T]hat the claims do not preempt all
price optimization or may be limited to price optimization in the e-
commerce setting do not make them any less abstract."). Further, "[ w ]here a
patent's claims are deemed only to disclose patent ineligible subject matter
under the Mayo framework, as they are in this case, preemption concerns are
fully addressed and made moot." Ariosa, 788 F.3d at 1379.
For the reasons discussed supra, we are unpersuaded of Examiner
error. Accordingly we sustain the Examiner's rejection of independent
claim 1 under 35 U.S.C. § 101. For similar reasons, we also sustain the
Examiner's rejection of independent claims 14 and 21, which recite similar
limitations and were not argued separately. See Br. 7-10; see also 37 C.F.R.
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§ 41.37(c)(l)(iv). Additionally, we sustain the Examiner's rejection of
claims 2-13, 15-20, and 22-24, which depend therefrom and were not
argued separately.
Rejection under 35 U.S.C. § 103
a. Claims 1, 5-7, 9, and 11-24
Appellants argue the Examiner's proposed combination of modifying
Zhu' s roster generation system to use the fatigue metric calculations of
Konop and Moore-Ede would render Zhu's technique inoperable. Br. 13. In
particular, Appellants assert the genetic algorithm (GA) used by Zhu "relies
upon the genes to maintain their static qualities during mutations and re-
combinations [and a] gene representing a fatigue metric ... is dynamic ...
and thus cannot maintain its static qualities." Br. 13. In support of this
position, Appellants present a hypothetical scenario of updating a roster
using Zhu' s approach and suggest that because fatigue is a function of
various dynamic factors and not a static property of elements of a roster, Zhu
cannot optimize a schedule that accounts for fatigue. Br. 14--16.
As an initial matter, it is well settled that mere attorney arguments and
conclusory statements, which are unsupported by factual evidence, are
entitled to little probative value. In re Geisler, 116 F.3d 1465, 1470 (Fed.
Cir. 1997); see also In re Pearson, 494 F.2d 1399, 1405 (CCPA 1974)
(attorney argument is not evidence). Contrary to Appellants' suggestion,
Zhu explicitly states "[t]he genetic algorithm evolution is based upon
dynamic adjustingfactors." Zhu i-f 65 (emphasis added); see also Zhu i-f 38
("the preferred embodiment applies a novel dynamic gene modeling
method"). Further, as the Examiner explains, even under a static gene
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modeling scenario, "specifically measured values for fatigue represent
instantaneous measurements which are used in the calculations"-in other
words, a snapshot value of fatigue may be used in Zhu' s genetic algorithm.
Ans. 5. Appellants do not persuasively rebut the Examiner's findings and
explanation. Accordingly, we are unpersuaded of Examiner error.
Appellants also assert the proposed combination fails to teach or
suggest calculating an overall fatigue metric for the roster. Br. 17-18.
Specifically, Appellants contend Konop, as relied on teaches deriving a
fatigue value for a crewmember, but not for a roster. Br. 17. Additionally,
Appellants acknowledge Moore-Ede teaches calculating a "Fatigue Score"
for a group of individuals, but argue the Fatigue Score is not for a roster with
which the individuals are associated. Br. 18.
Non-obviousness cannot be established by attacking references
individually where, as here, the ground of unpatentability is based upon the
teachings of a combination of references. In re Keller, 642 F.2d 413, 426
(CCP A 1981 ). Rather, the test for obviousness is whether the combination
of references, taken as a whole, would have suggested the patentee's
invention to a person having ordinary skill in the art. In re Merck & Co.,
800 F.2d 1091, 1097 (Fed. Cir. 1986).
We are unpersuaded of Examiner error because the Examiner relies on
the combined teachings of Zhu, Konop, and Moore-Ede in rejecting the
pending claims. Final Act. 8-36. In particular, the Examiner concludes:
[I]t would be obvious to one of ordinary skill in the art to
combine the ability to calculate an overall fatigue metric for a
plurality of rosters, or scheduled periods of time, with the
techniques for determining individual fatigue levels for resources
to be assigned to shifts in possible rosters because each of the
elements were known, but not necessarily combined as claimed.
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The technical ability existed to combine the elements as claimed
and the result of the combination is predictable because each of
the elements perform the same functions as they did
independently. By incorporating the ability to sum the individual
fatigue levels for resource units assigned to shifts in a roster, for
each roster, to generate an overall fatigue score for each roster
the combination enables comparisons to be made that enable
conclusions related to relationships between fatigue and specific
work-rest schedules to be drawn which will increase corrective
intervention results.
Final Act. 13-14 (citing Moore-Ede i-fi-1357-360); see also Ans. 6-7.
We agree with the Examiner's findings and conclusions.
Additionally, to the extent Appellants' arguments are directed to the
calculated fatigue levels are based at least in part on tracking homeostatic
and circadian processes, we note both Konop and Moore-Ede teach or
suggest the use of such information. See, e.g., Konop i1 91 and Moore-Ede
i-fi-12, 88, and 147.
For the reasons discussed supra, we are unpersuaded of Examiner
error. Accordingly, we sustain the Examiner's rejection under 35 U.S.C.
§ 103(a) of independent claim 1. Contrary to Appellants' assertion (see
Br. 22-24), we agree with the Examiner that independent claims 14 and 21
recite limitations commensurate in scope with those recited in claim 1. Ans.
10-11. Appellants advance similar arguments to those presented with
respect to claim 1. For similar reasons to those discussed regarding claim 1,
we do not find Appellants' arguments persuasive of Examiner error.
Accordingly, we sustain the Examiner's rejection under 35 U.S.C. § 103(a)
of independent claims 14 and 21. Further, we sustain the Examiner's
rejection of claims 5-7, 9, and 11-13, 15-20, and 22-24, which depend
therefrom and were not argued separately.
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b. Claims 2 and 8
Similar to claim 1, Appellants present similar arguments that the
Examiner's proposed combination fails to teach calculating the fatigue levels
of the resource (i.e., an individual) and of the roster (i.e., a group of
individuals). See Br. 18-19, 21-22. For similar reasons to those discussed
regarding claim 1, we are unpersuaded of Examiner error. Accordingly, we
sustain the Examiner's rejection of claims 2 and 8 under 35 U.S.C. § 103(a).
c. Claim 3
Claim 3 depends from claim 1 and recites, in relevant part, that "the
objective function further encapsulates at least one operational outcome" and
that the generation of possible rosters conform within the operational
constraint and operational outcome.
Appellants assert "Zhu does not disclose finding an optimal roster
based on both an operational constraint and an operational outcome."
Br. 20. Appellants contend the Examiner's reading of Zhu (and, therefore,
the rejection) is incorrect because operational constraints are not the same as
operational outcomes. Br. 20.
The Specification describes operational outcomes as being either
desirable (e.g., profit, output, yield, or bandwidth) or undesirable (e.g.,
fatigue, loss, risk of error, accidents, or cost). Spec. ,-r 12. An "operational
constraint ... refers to limitations and/or restrictions that a particular process
or operation must follow or that would be desirable to meet." Spec. ,-r 12.
The Examiner finds, and we agree, Zhu teaches determining an
optimal schedule that accounts for individual requirements (e.g., annual
leave or restrictions, see Zhu ,-r 41) and meeting hard and soft constraints.
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Ans. 8 (citing Zhu i-fi-136-40. As the Examiner explains, the claimed
operational constraints are the individual requirements and hard and soft
constraints and "the optimal roster with [an] even distribution of staff and
shifts is the operational outcome." Ans. 8 (citing Zhu i-fi-141--46). Further,
Zhu discloses generating a roster to achieve a desired workload (i.e., an
operational outcome).
For the reasons discussed supra, we are unpersuaded of Examiner
error. Accordingly, we sustain the Examiner's rejection of claim 3.
DECISION
We affirm the Examiner's decision rejecting claims 1-24 under
35 U.S.C. § 101.
We affirm the Examiner's decision rejecting claims 1-3, 5-9, and 11-
24 under 35 U.S.C. § 103(a).
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). See
37 C.F.R. § 41.50(f).
AFFIRMED
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