Ex Parte Khanna et al

Patent Trial and Appeal Board

Oct 13, 2017

11618309 (P.T.A.B. Oct. 13, 2017)

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.
11/618,309 12/29/2006 Richendra Khanna 120137.550 5606
500 7590 10/13/2017
SFFD TNTFT T FFTT TAT PROPFRTY T AW GROT TP T T P
EXAMINER
701 FIFTH AVE KIM, STEVEN S
SUITE 5400
SEATTLE, WA 98104 ART UNIT PAPER NUMBER
3685
MAIL DATE DELIVERY MODE
10/13/2017 PAPER
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.
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
BEFORE THE PATENT TRIAL AND APPEAL BOARD
Ex parte RICHENDRA KHANNA,
EUGENE KALENKOVICH,
and RAJIV CHOPRA
Appeal 2016-000554
Application 11/618,309
Technology Center 3600
Before ANTON W. FETTING, NINA L. MEDLOCK, and
BRADLEY B. BAYAT, Administrative Patent Judges.
FETTING, Administrative Patent Judge.
DECISION ON APPEAL
STATEMENT OF THE CASE1
Richendra Khanna, Eugene Kalenkovich, and Rajiv Chopra
(Appellants) seek review under 35U.S.C. § 134 of a final rejection of
claims, the only claims pending in the application on appeal. We have
jurisdiction over the appeal pursuant to 35 U.S.C. § 6(b).
1 Our decision will make reference to the Appellants’ Appeal Brief (“App.
Br.,” filed May 5, 2015) and Reply Brief (“Reply Br.,” filed October 5,
2015), and the Examiner’s Answer (“Ans.,” mailed August 6, 2015), and
Final Action (“Final Act.,” mailed January 5, 2015).
Appeal 2016-000554
Application 11/618,309
The Appellants invented techniques for detecting inappropriate
activity, such as to detect users engaged in inappropriate activities based on
their interactions with a Web site or other electronic information service.
Spec., para. 1.
An understanding of the invention can be derived from a reading of
exemplary claim 1, which is reproduced below (bracketed matter and some
paragraphing added).
1. A computer-implemented method for an electronic
marketplace to automatically inhibit inappropriate interactions
of users with the electronic marketplace, the method
comprising:
[1] receiving, by one or more configured computing systems of
the electronic marketplace,
information describing a sequence of multiple
interactions of a user with the electronic marketplace,
the sequence of multiple user interactions being related to
a single potential transaction within the electronic
marketplace that involves the user and one or more items
and including a path of multiple information resources
being accessed by the user;
[2] automatically determining, by the one or more configured
computing systems,
whether the user is suspected of being engaged in
fraudulent activity with respect to the electronic
marketplace by applying multiple assessment tests to the
received information to assess multiple factors related to
the sequence of multiple interactions;
[3] determining, by the one or more configured computing
systems,
that the user is suspected of being engaged in fraudulent
activity based on the applying of the multiple assessment
tests,
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the applying of the multiple assessment tests including
determining whether the path of multiple information
resources accessed by the user is associated with a
distinct other user previously engaged in fraudulent
activities; and
[4] taking, by the one or more configured computing systems,
one or more actions to inhibit the fraudulent activity by
the user.
The Examiner relies upon the following prior art:
McNair US 5,375,244
Johnson US 5,615,408
Ronning US 7,165,051 B2
O’Connell US 2007/0239604 A1
Dec. 20, 1994
Mar. 25, 1997
Jan. 16, 2007
Oct. 11,2007
Claims 1, 4—7, 12—16, 19, 21—23, 25—31, 38, and 42 stand rejected
under 35U.S.C. § 101 as directed to non—statutory subject matter.
Claims 1, 4—7, 12—16, 19, 21—23, 25—31, 38, and 42 stand rejected
under 35 U.S.C. § 112(a) as lacking a supporting written description within
the original disclosure.
Claims 1, 6, 7, 15, 16, 19, 21—23, 25—31, 38, and 42 stand rejected
under 35 U.S.C. § 103(a) as unpatentable over O'Connell, Ronning, and
McNair.
Claims 4, 5, and 12—14 stand rejected under 35 U.S.C. § 103(a) as
unpatentable over O’Connell, Ronning, McNair, and Johnson.
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ISSUES
The issues of eligible subject matter turn primarily on whether the
claims recite more than conceptual fraud protection advice for computer
implementation. The issues of written description turn primarily on whether
the Specification supports the claims. The issues of obviousness turn
primarily on whether a description of collecting individual statistics
followed by collective analysis is substantial evidence that it was at least
predictable to also use those individual statistics in the analysis in any
manner.
FACTS PERTINENT TO THE ISSUES
The following enumerated Findings of Fact (FF) are believed to be
supported by a preponderance of the evidence.
Facts Related to the Prior Art
O ’Connell
01. O’Connell is directed to detecting fraudulent behavior based on
analysis of user-browser interaction, such as during an Internet or
e-commerce session. O’Connell, para. 1.
02. O’Connell’s fraud detection server determines fraud detection
results based on the user-browser interaction during the current
session and known fraudulent behavioral patterns and returns the
fraud detection results to the user. Based on the fraud detection
results and in response to a request by the user for an action, the e-
commerce application may perform an action such as allowing the
requested transaction, requesting additional authentication
information, or rejecting the requested action. The e-commerce
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application uses the fraud detection results to detect suspicious or
fraudulent behavior and help prevent fraudulent transactions from
occurring. Id. at para. 24.
03. O’Connell’s client computer system transmits indications of the
user’s interaction with the browser to the incoming interaction
server via a network to facilitate determination of fraud detection
results. The user-browser interaction data transmitted by the
client computer system may include both indications of the user-
browser interaction as well as identification information. Id. at
para. 26.
04. O’Connell’s user interactions with a browser may be classified
into general categories such as keyboard interactions, movement
device interactions, and navigation/selection tendencies.
Keyboard interactions may include interactions of a user with the
keyboard, including key-down time (how long a particular key is
pressed), typing rate, time or pauses between keystrokes, numeric
keypad usage, capitalization keystroke sequences, common typing
errors, etc. A particular user, for example, may typically hold
down the ‘o’ key for milliseconds less time than she holds down
the ‘k’ key, a pattern that may emerge consistently over continued
data entry. This particular difference may reflect both hardware
differences (e.g., the keyboard spring for each key on a particular
keyboard) as well as the user’s natural or learned typing pattern.
A different user may have a larger gap between the two letters, a
smaller gap, no gap, or a reversal of the longer hold time,
providing a characteristic that potentially distinguishes the two
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users. While one such characteristic may generally be insufficient
for authentication purposes, an aggregation of different behaviors
provides increasing authentication strength as more data is
collected and more factors are considered. Keyboard interactions
may include the particular keys selected for tasks, the pauses in
between actuations or the length of actuations, etc. Id. at para. 27.
05. O’Connell describes how the details of a user’s interaction
while using a website using their browser may provide an
indication of fraudulent behavior by that user. Id. at para. 28.
06. O’Connell describes how its fraud detection server may
determine fraud detection results based on the user’s interaction
with a browser during the current session and known fraudulent
behavior patterns. Upon receiving a request for fraud detection
results for a particular user from an e-commerce application, the
fraud detection server may access the stored user-browser
interaction data for that user and a fraud detection module may
analyze the stored data and compare the user-browser interaction
data for the current session with known human or automated
program fraudulent behavior. The user-browser interaction data
for the current session may, in some embodiments, be stored in
the user-browser interaction database. The fraud detection results
may include an indication of the likelihood that the person (or
entity) acting as the user of the current session is in fact the actual
user or is actually a different user or automated program instead
engaging in fraudulent behavior. The fraud detection results may
be a final result (i.e., it is fraudulent behavior or it is not), a fraud
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detection score that provides an indication of the degree of
likelihood of fraudulent behavior evidenced by the user, or any
other representation of the results. Id. at para. 34.
07. O’Connell describes how its fraud detection server may
transmit the determined fraud detection results to the requesting e-
commerce application, which may in turn determine its course of
action based at least in part on the fraud detection results. Once
the e-commerce application determines its course of action based
on the fraud detection results, any requested actions of the user,
and its own internal criteria, the e-commerce may perform the
selected action. Id.at para. 35.
Ronning
08. Ronning is directed to performing adaptive fraud screening for
electronic commerce transactions in order to detect and prevent
attempted fraud in conjunction with the transactions. Ronning
1:18-21.
09. Ronning describes a fraud detection mechanism active during
electronic commerce transactions. The fraud detection
mechanism determines a likelihood that the electronic purchase
order is attempted fraud based upon (i) information associated
with the user-entered information and (ii) factors relating to a
user’s real-time interaction with the server during a transaction to
process the electronic purchase order. Id. at 1:63—2:1.
10. Ronning describes generating the cumulative fraud ranking by
analyzing page/order movement/history of an electronic
commerce transaction. This processing generally involves
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recording how a user progressed through the transaction, and
comparing that progression with known profiles indicating
fraudulent transactions and known profiles indicating normal
(non-ffaudulent) transactions. Ronning stores the known profiles
for use in the comparison, and the known profiles may be updated
as Ronning records additional profiles and associates them with
attempted fraudulent or normal transactions. For example, a
progression of pages for a normal transaction may include a user
accessing welcome page, search page, product information page,
and then check out page. A progression of pages for an attempted
fraudulent transaction may include, for example, a user repeatedly
accessing the shopping basket page and then the check out page
several times in a row. In addition, Ronning may include files,
known and referred to as “cookies,” written to a user’s machine to
identity the machine in order to detect particular events from the
same machine such as, for example, repeated submission of orders
from the same machine with potentially different names or other
information. Id. at 11:20-44.
McNair
11. McNair is directed to controlling access to a resource, such as a
telecommunications network or a computer, so that access by
unauthorized persons is disallowed. McNair 1:6—10.
12. McNair describes how data obtained from transactions
involving both valid and fraudulent users are clustered in a
multidimensional attribute space, with each of the clusters
representing an attribute profile of similar user behaviors. Next,
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the similarity between the attributes of an access attempt and the
attribute profiles represented by the clusters is evaluated, to
identify the profiles of valid and fraudulent users that most closely
resemble the attributes of the access attempt. If desired, an access
decision can then be made simply based upon which type of user
(valid or fraudulent) the access attempt most closely resembles. If
desired, the history of previous access attempts by particular users
may be stored and used subsequently in the access decision
process. Id. at 1:54—2:10.
ANALYSIS
Claims 1, 4—7, 12—16, 19, 21—23, 25—31, 38, and 42 rejected under
35 U.S.C. § 101 as directed to non—statutory subject matter
The Supreme Court
set forth a framework for distinguishing patents that claim laws
of nature, natural phenomena, and abstract ideas from those that
claim patent-eligible applications of those concepts. First, . . .
determine whether the claims at issue are directed to one of
those patent-ineligible concepts. If so, we then ask, “[w]hat
else is there in the claims before us? To answer that question,
. . . consider the elements of each claim both individually and
“as an ordered combination” to determine whether the
additional elements “transform the nature of the claim” into a
patent-eligible application. [The Court] described step two of
this analysis as a search for an “‘inventive concept’”—i.e., an
element or combination of elements that is “sufficient to ensure
that the patent in practice amounts to significantly more than a
patent upon the [ineligible concept] itself.”
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Alice Corp. Pty. Ltd. v CLS Bank Inti, 134 S. Ct. 2347, 2355 (2014) (citing
Mayo Collaborative Services v. Prometheus Laboratories, Inc., 132 S. Ct.
1289 (2012)).
To perform this test, we must first determine whether the claims at
issue are directed to a patent-ineligible concept. The Examiner finds the
claims directed to determining whether a user is suspected of being engaged
in fraudulent activity. Final Act. 5.
Although the Court, in Alice, made a direct finding as to what the
claims were directed to, we find that this case’s claims themselves and the
Specification provide enough information to inform one as to what they are
directed to.
The preamble to claim 1 recites that it is a method to inhibit
inappropriate interactions of users with the marketplace. The steps in
claim 1 result in determining suspected fraud and taking appropriate action.
The Specification at paragraph 1 recites that the invention relates to
detecting inappropriate activity. Thus, all this evidence shows that claim 1
is directed to fraud detection.
It follows from prior Supreme Court cases, and Bilski v Kappos, 561
U.S. 593 (2010) in particular, that the claims at issue here are directed to an
abstract idea. Like the risk hedging in Bilski, the concept of fraud detection
is a fundamental business practice long prevalent in our system of
commerce. The use of fraud detection is also a building block of any credit
system. Thus, fraud detection, like hedging, is an “abstract idea” beyond the
scope of § 101. See Alice, 134 S. Ct. at 2356.
As in Alice, we need not labor to delimit the precise contours of the
“abstract ideas” category in this case. It is enough to recognize that there is
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no meaningful distinction in the level of abstraction between the concept of
risk hedging in Bilski and the concept of fraud detection at issue here. Both
are squarely within the realm of “abstract ideas” as the Court has used that
term. See Alice, 134 S. Ct. at 2357.
The remaining claims merely describe parameters and generalized
techniques for fraud detection. We conclude that the claims at issue are
directed to a patent-ineligible concept.
The introduction of a computer into the claims does not alter the
analysis at Mayo step two.
the mere recitation of a generic computer cannot transform a
patent-ineligible abstract idea into a patent-eligible invention.
Stating an abstract idea “while adding the words ‘apply it’” is
not enough for patent eligibility. Nor is limiting the use of an
abstract idea “‘to a particular technological environment.’”
Stating an abstract idea while adding the words “apply it with a
computer” simply combines those two steps, with the same
deficient result. Thus, if a patent’s recitation of a computer
amounts to a mere instruction to “implement^]” an abstract
idea “on ... a computer,” that addition cannot impart patent
eligibility. This conclusion accords with the preemption
concern that undergirds our §101 jurisprudence. Given the
ubiquity of computers, wholly generic computer
implementation is not generally the sort of “additional
feature[e]” that provides any “practical assurance that the
process is more than a drafting effort designed to monopolize
the [abstract idea] itself.”
Alice, 134 S. Ct. at 2358 (citations omitted).
“[T]he relevant question is whether the claims here do more than
simply instruct the practitioner to implement the abstract idea ... on a
generic computer.” Alice, 134 S. Ct. at 2359. They do not.
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Taking the claim elements separately, the function performed by the
computer at each step of the process is purely conventional. Using a
computer to receive data and make determinations about such data amounts
to electronic data query and retrieval—one of the most basic functions of a
computer. All of these computer functions are well-understood, routine,
conventional activities previously known to the industry. In short, each step
does no more than require a generic computer to perform generic computer
functions.
Considered as an ordered combination, the computer components of
Appellants’ method add nothing that is not already present when the steps
are considered separately. Viewed as a whole, Appellants’ method claims
simply recite the concept of fraud detection as performed by a generic
computer. The method claims do not, for example, purport to improve the
functioning of the computer itself. Nor do they effect an improvement in
any other technology or technical field. Instead, the claims at issue amount
to nothing significantly more than an instruction to apply the abstract idea of
fraud detection using some unspecified, generic computer. Under our
precedents, that is not enough to transform an abstract idea into a patent-
eligible invention. See Alice, 134 S. Ct. at 2360.
As to the structural claims, they
are no different from the method claims in substance. The
method claims recite the abstract idea implemented on a generic
computer; the system claims recite a handful of generic
computer components configured to implement the same idea.
This Court has long “wam[ed] ... against” interpreting § 101“in
ways that make patent eligibility ‘depend simply on the
draftsman’s art.’”
Id.
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We further adopt the Examiner’s findings and analysis from the Final
Office Action at page 5 and the Answer at pages 3—11 and reach similar
legal conclusions. We now turn to the Reply Brief arguments.
We are not persuaded by Appellants’ argument that the particular
claim limitations remove the claims from being a mere abstract idea under
part one of the two-part test. Reply Br. 17. Appellants conflate parts 1 and
2 of the Alice test. The first part asks whether the claim is directed to an
abstract idea, not whether all of the limitations are non-specific. As we find
supra, the claims themselves and the Specification provide evidence that the
claims are directed to fraud detection, which is a generalized abstract
concept.
As to the second part of the Alice test, the limitations Appellants point
to recite the use of a computer network, which itself is generic; data
characteristics, such as what the data are related to; the use of plural generic
assessment tests; and comparing the path the user took to other paths by at
least one other particular user, which amounts to comparing the modus
operandi of users. None of these limitations recites any particular
implementation for doing so. As such, these amount to no more than
conceptual advice on how to detect fraud in a generic computer network.
We are not persuaded by Appellants’ argument that the additional data
recited in claim 4 amount to more than an abstract idea. Reply Br. 18—19.
This is essentially the same argument as in support of claim 1, but
contending that further data details make a difference. Simply adding to the
data receiving and analysis inputs does not alter what the claim is directed to
and does not show that receiving and using any amount of data is not a
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conventional computer activity. There is no numeric threshold beyond
which data entry turns from being conventional to being inventive.
We are not persuaded by Appellants’ argument that independent
claim 7 is patent-eligible. Id. at 20-21. Independent claim 7 is essentially a
broader form of claim 1 to which additional data inputs are added. As we
find with claim 4 supra, simply adding data inputs does not alter the
analysis.
We are not persuaded by Appellants’ argument that dependent
claim 25 is patent-eligible. Id. at 21—22. Dependent claim 25 adds the
purpose — but not the implementation of the tests — characterizes the outputs,
and combines the test results. Combining data is another conventional
computer activity and describing the character and purpose of a limitation
alone without implementation does not show invention.
We are not persuaded by Appellants’ argument that independent
claims 38 and 42 are patent-eligible. Id. at 22—25. Claims 38 and 42 are
computer instructions and device variants of claim 1 and the arguments here
are unpersuasive for the same reasons as with claim 1.
We are not persuaded by Appellants’ argument that the claims are
non-abstract when viewed as a whole. Id. at 25—29. As we find supra, each
of the claims recites conceptual advice on generic fraud detection and adds
that it be implemented on a computer, but with no implementation details.
Appellants further argue that the asserted claims are akin to the
claims found patent-eligible in DDR Holdings, LLC v. Hotels.com, L.P.
773 F.3d 1245 (Fed. Cir. 2014). In DDR Holdings, the court evaluated the
eligibility of claims “address[ing] the problem of retaining website
visitors that, if adhering to the routine, conventional functioning of
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Internet hyperlink protocol, would be instantly transported away from a
host’s website after ‘clicking’ on an advertisement and activating a
hyperlink.” Id. at 1257. There, the court found that the claims were patent-
eligible because they transformed the manner in which a hyperlink
typically functions to resolve a problem that had no “pre-Internet
analog.” Id. at 1258. The court cautioned, however, “that not all claims
purporting to address Internet-centric challenges are eligible for patent.”
Id. For example, in DDR Holdings, the Court distinguished the patent-
eligible claims at issue from claims found patent-ineligible in
Ultramercial. See id. at 1258—59 (citing Ultramercial, Inc. v. Hulu, LLC,
772 F.3d 709, 715—16 (Fed. Cir. 2014). As noted there, the Ultramercial
claims were “directed to a specific method of advertising and content
distribution that was previously unknown and never employed on the
Internet before.” Id. at 1258 (quoting Ultramercial, 772 F.3d at 715-
lb). Nevertheless, those claims were patent-ineligible because they
“merely recite[d] the abstract idea of ‘offering media content in exchange
for viewing an advertisement, ’ along with ‘routine additional steps such as
updating an activity log, requiring a request from the consumer to view the
ad, restrictions on public access, and use of the Internet.’” Id.
Similarly, Appellants’ asserted claims recite, receiving,
determining, and taking action. This is precisely the type of network
activity found ineligible in Ultramercial. To the extent Appellants may be
arguing that “a path of multiple information resources being accessed” is or
creates a technological problem, we find that this is no more than the
electronic equivalent of conventional transactional paths commercial
transactions have traversed through financial and mercantile intermediaries
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for centuries. Indeed it is the electronic equivalent of a stapled sheaf of
paper resulting along such a path, and to instruct one to review it is no more
than to review transactional history in general.
Claims 1, 4—7, 12—16, 19, 21—23, 25—31, 38, and 42 rejected under
35 U.S.C. § 112(a) as lacking a supporting written description within the
original disclosure
As to claim 1, this turns on whether a “distinct other user” in the
recited limitation “determining whether . . . accessed by the user is
associated with a distinct other user” is supported by the Specification. Final
Act. 6—7. We are persuaded by Appellants’ argument that it is. Appellants
transcribe Specification paragraphs 15, 19, 20, and 34 and underline several
limitations as support for such an other user. App. Br. 31—32; Reply Br. 31—
33. This is consistent with the support pointed to in the Appeal Brief at
page 5. The Examiner tellingly finds that the Appellants relied on
Specification paragraphs 15, 19, 20, and 30 (not 34). Ans. 15. The
paragraph the Examiner omits, paragraph 34, describes “a particular
interaction sequence may be selected for heightened scrutiny for various
reasons, such as an associated user being previously identified as being
potentially suspect and/or the interaction sequence including one or more
interactions previously identified as particularly suspect.” Such an
associated user would be a distinct other user.
The remaining independent claims have the same issue. Appellants’
arguments are similarly persuasive.
As to claim 5, reciting “the path of multiple information resources is
consecutively accessed by the user,” we are persuaded by Appellants’
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argument that the Specification supports this at paragraph 12, reciting
“embodiments the assessment tests may analyze information about a
sequence of multiple related interactions.” App. Br. 37. In any event,
Examiner withdraws this rejection. Ans. 19.
Claims 1, 6, 7, 15, 16, 19, 21—23, 25—31, 38, and 42 rejected under
35 U.S.C. § 103(a) as unpatentable over O'Connell, Ronning, and McNair
We are not persuaded by Appellants’ argument that the prior art
applied fails to describe limitation 3, “determining whether the path of
multiple information resources accessed by the user is associated with a
distinct other user previously engaged in fraudulent activities,” as recited in
claim 1. App. Br. 42-45. The Examiner cites McNair as describing
collecting individual access attempts by individual users as part of the
history used for fraud detection.
The Examiner finds “it certainly would be within the realm of
obviousness to one having ordinary skill in the art to include any known
data, e.g. profile created from a distinct other user previously engaged in
fraudulent activities, in known profile.” Ans. 24. We agree McNair
presents substantial evidence that it was known to those of ordinary skill to
collect such data for distinct other users. The issue is then whether it was
predictable to use, in any way, this data on its individual basis in addition to
any collective basis further described by the art.
Again, no implementation is recited, so no particular technological
use of this individual data is recited. The issue is simply whether it was
predictable to use individual as well as collective data, even for the purpose
of pattern comparison. It would seem inconsistent for McNair to collect
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individual data with no intent of using it somehow. So McNair at minimum
suggests using such individual data for some purpose, and as McNair is
directed to fraud detection, that purpose would encompass fraud detection.
We further find that using individual data as exemplary representations of
outliers or canonical forms is widespread in data analysis generally, and that
fraud is not an especially individual activity, but is frequently practiced by
associates. As a result, it was at least predictable for those practicing
O’Connell, on seeing how McNair relies on individual as well as collective
user data for fraud detection, to extend its analysis to similarly include
individual other users.
We are not persuaded by Appellants’ argument that adding individual
data to collective data still results in only collective data. Reply Br. 10. The
issue is not whether it was predictable to add individual data to collective
data, but to use both individual and collective data in fraud analysis.
As to the remaining claims, we adopt the Examiner’s findings and
analysis and reach similar legal conclusions.
Claims 4, 5, and 12—14 rejected under 35 U.S.C. § 103(a) as unpatentable
over O'Connell, Ronning, McNair, and Johnson
Appellants rely on their arguments in support of claim 1.
CONCLUSIONS OF LAW
The rejection of claims 1, 4—7, 12—16, 19, 21—23, 25—31, 38, and 42
under 35 U.S.C. § 101 as directed to non—statutory subject matter is proper.
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The rejection of claims 1, 4—7, 12—16, 19, 21—23, 25—31, 38, and 42
under 35 U.S.C. § 112(a) as lacking a supporting written description within
the original disclosure is improper.
The rejection of claims 1, 6, 7, 15, 16, 19, 21—23, 25—31, 38, and 42
under 35 U.S.C. § 103(a) as unpatentable over O'Connell, Ronning, and
McNair is proper.
The rejection of claims 4, 5, and 12—14 under 35 U.S.C. § 103(a) as
unpatentable over O'Connell, Ronning, McNair, and Johnson is proper.
DECISION
The decision to reject claims 1, 4—7, 12—16, 19, 21—23, 25—31, 38, and
42 is affirmed.
No time period for taking any subsequent action in connection with this
appeal may be extended under 37 C.F.R. § 1.136(a). See 37 C.F.R.
§ 1.136(a)(l)(iv) (2011).
AFFIRMED
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