DETAILED ACTION
The action is responsive to the Application filed on 08/12/2024. Claims 1-20 are pending in the case. Claims 1 and 11 are independent claims.
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 Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: "a storage component that stores and manages" in claim 1.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 1-10 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. As to claim 1, the scope of the claim is indefinite because the specification does not clearly disclose/link the corresponding structure for achieving the recited function in the following means plus function claim limitation: "a storage component that stores and manages". Claims 2-10 are rejected under the same rationale since they depend from claim 1.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Batlle (US 20180007203 A1).
As to claim 1, Batlle discloses a computer-implemented system for implementing an automated process and application transformation solution, the system comprising:
a tracking interface that performs data acquisition by dynamically capturing user interactions with at least one application via a communication network ("Referring now to FIG. 7, a method 700 for generating a customized user experience via a web server is illustrated. The method 700 begins at block 702 where a web server determines user interaction with a website from a user device. In an embodiment, the web server 600 may detect user interaction with a web page of a website via requests received from the user device 104, and gather any information about the user interaction include user information, location information, user device 104 type, current web page of the website, whether the website was accessed by a mobile application or web browser, time of interaction, Internet protocol address or any other device identifier, authenticated session information, and any other information that may be captured from a user interaction with a website and that would be apparent to one of skill in the art in possession of the present disclosure," Batlle paragraph 0054, capturing user interactions with a website);
a storage component that stores and manages the dynamically captured user interactions ("The predictive user interaction engine 204 may be configured to generate the first user interaction rules based on the real-time data and historical data received from the service provider system 102 and/or third party database 126," Batlle paragraph 0035, user interactions stored as historical data in a database);
an optimization processor that initiates a process transformation that correlates the dynamically captured user interactions and system activity data to generate an application model wherein the application model is optimized through a business process map and at least one recommendation for enhancement (“The user device 1602, the customer service terminal device 1604, the service provider system device 1606, and the third party device 1608 may each include one or more processors, memories, and other appropriate components for executing instructions such as program code and/or data stored on one or more computer readable mediums to implement the various applications, data, and steps described herein,” Batlle paragraph 0085; "In an embodiment, the instructions may be individual instructions that address a condition for a particular user, user account, and/or user device that is accessing the web server 600. In this embodiment, the webserver may gather an identifier of the user/user device such as user account information due to a login, and/or a device identifier of the user device 104. For example, the instructions may be based on recent activity of the user. The web server 600 may determine that a particular user logged into their account with the service provider system 102, and the web server 600 may transmit the user account information to the predictive management device 200. The predictive management device 200 may determine instructions based on the condition that is the user account information. The user account information may include recent activity of the user associated with the user account such that the recent activity as first data may be used to determine a condition exists along with an instruction based on the condition as in blocks 306 and 308 of method 300 described above. For example, the recent activity of a user account that has interacted with the web site of the web server 600 and accessed the user's account may indicate that the user purchased two of the same items but in different sizes, and the items have been shipped and received by the user. The predictive management device 200 may determine that under these conditions the user is likely looking for return information for one of the items, and may generate instructions that address returning items and obtaining a refund," Batlle paragraph 0056; "The method 700 proceeds to block 706 where the web server generates a customized website based on the instructions. In an embodiment, the web server 600 may generate one or more customized web pages based on the instructions received from the user interaction database 114 and/or the predictive management engine 200," Batlle paragraph 0057, correlating user interactions to predict the user would like to initiate a return and generating enhancement instructions that can be converted into code to generate a customized website (i.e., the instructions are a business process map));
responsive to the business process map, a code generation processor that generates a user guide interface, monitors data flows and automatically generates application computer code for transformation implementation to a target application ("The method 700 proceeds to block 706 where the web server generates a customized website based on the instructions. In an embodiment, the web server 600 may generate one or more customized web pages based on the instructions received from the user interaction database 114 and/or the predictive management engine 200. The method 700 then proceeds to operation 708 where the customized website is provided for display on the user device. In an embodiment, the web server 600 may provide the customized web pages of the customized web site to the user device 104, and the user device 104 may display the customized web page on a display of the user device 104," Batlle paragraph 0057); and
a workflow automation processor that deploys the application computer code in a target environment for transformation adoption and continuously gathers data and provides feedback for updated optimization for continuous improvement ("The method 700 proceeds to decision block 710 where the web server determines whether there is any user interaction with the customized website. In an embodiment, the web server 600 may determine whether the user is interacting with the customized website. If the user is no longer interacting or has closed out of the customized website, then the method 700 may end and the web server 600 may provide the information to the predictive management device 200. If the user interacts with the customized website, the method 700 may then proceed to block 712 where the web server transmits data associated with the interaction to the predictive management device 200," Batlle paragraph 0059, continually monitoring for further interactions in order to generate further instructions to further customize the website).
As to claim 2, Batlle discloses the system of claim 1, wherein artificial intelligence (AI) is applied to the captured user interactions to create one or more data insights ("The predictive management device may include one or more machine learning algorithms that may generate and provide instructions to a customer interaction database based on the historical data, real-time data, and/or any other data generated by the system and received by the predictive management device," Batlle paragraph 0026).
As to claim 3, Batlle discloses the system of claim 1, wherein the tracking interface comprises a browser interactive guide and tracking platform ("Referring now to FIG. 7, a method 700 for generating a customized user experience via a web server is illustrated. The method 700 begins at block 702 where a web server determines user interaction with a website from a user device. In an embodiment, the web server 600 may detect user interaction with a web page of a website via requests received from the user device 104, and gather any information about the user interaction include user information, location information, user device 104 type, current web page of the website, whether the website was accessed by a mobile application or web browser, time of interaction, Internet protocol address or any other device identifier, authenticated session information, and any other information that may be captured from a user interaction with a website and that would be apparent to one of skill in the art in possession of the present disclosure," Batlle paragraph 0054, accessing the website via a web browser and capturing user interactions / usage information).
As to claim 4, Batlle discloses the system of claim 3, wherein the browser interactive guide and tracking platform dynamically captures user interaction and usage information ("Referring now to FIG. 7, a method 700 for generating a customized user experience via a web server is illustrated. The method 700 begins at block 702 where a web server determines user interaction with a website from a user device. In an embodiment, the web server 600 may detect user interaction with a web page of a website via requests received from the user device 104, and gather any information about the user interaction include user information, location information, user device 104 type, current web page of the website, whether the website was accessed by a mobile application or web browser, time of interaction, Internet protocol address or any other device identifier, authenticated session information, and any other information that may be captured from a user interaction with a website and that would be apparent to one of skill in the art in possession of the present disclosure," Batlle paragraph 0054, accessing the website via a web browser and capturing user interactions / usage information).
As to claim 5, Batlle discloses the system of claim 4, wherein the user interaction comprises a sequence of user actions through one or more applications from a single user ("Referring now to FIG. 7, a method 700 for generating a customized user experience via a web server is illustrated. The method 700 begins at block 702 where a web server determines user interaction with a website from a user device. In an embodiment, the web server 600 may detect user interaction with a web page of a website via requests received from the user device 104, and gather any information about the user interaction include user information, location information, user device 104 type, current web page of the website, whether the website was accessed by a mobile application or web browser, time of interaction, Internet protocol address or any other device identifier, authenticated session information, and any other information that may be captured from a user interaction with a website and that would be apparent to one of skill in the art in possession of the present disclosure," Batlle paragraph 0054, capturing user interactions with a website coming from a single user device).
As to claim 6, Batlle discloses the system of claim 4, wherein the user interaction comprises a sequence of user actions through one or more applications from multiple users ("For example, the predictive management device 200, by use of one or more machine learning algorithms, may determine first conditions in the service provider system 102 that are similar to second conditions that have resulted in a user initiating a communication session with a customer service representative, but which resulted in a customer not initiating an interaction with a customer service representative. More specifically, the predictive management device 200 may determine that a frequently asked question (FAQ) link on the website hosted by the web server 108 was accessed by a group of users with conditions that are the same as, or similar to, users that initiated a communication session with a customer service representative. By following the user interaction rules, the predictive management device 200 may determine instructions for the web server 108 to more prominently display the FAQ link at a web page of the website when a particular user that satisfies the first conditions logs on to their user account through the web server 108 of the service provider system 102," Batlle paragraph 0039, monitoring the interactions of multiple users in order to generate a change in the UI).
As to claim 7, Batlle discloses the system of claim 1, wherein the system activity data is analyzed to create a visual representation of one or more process flows ("Thus, a system and method for a cross-platform customer service system has been described that may predict possible user interactions with a service provider system based on real-time and historical data that is processed by machine learning algorithms. Based on the predicted user interactions, the cross-platform customer service system may preemptively provide information to a user and/or perform actions to generate and provide a customized user experience that may help achieve a business goal of the service provider," Batlle paragraph 0082; " In an embodiment, the predictive user interaction engine 204 may include static rules that describe general goals of the service provider and that are updatable by the service provider. For example, a goal of the service provider may be to maximize profits, reduce the number of communication sessions between a user and a customer service representative, retain users as customers, increase consumption by the certain users, and any other goal, hierarchy of goals, or combination of goals that would be apparent to one of skill in the art in possession of the present disclosure. The predictive management device may consider these goals when generating the rules," Batlle paragraph 0035, using the predictive management system to identify opportunities to maximize profits, retain customers as users or decrease costs (i.e., bottlenecks, inefficiencies and process issues)).
As to claim 8, Batlle discloses the system of claim 7, wherein the one or more process flows identify one or more of: bottlenecks, inefficiencies and process issues that are used to improve optimization ("Thus, a system and method for a cross-platform customer service system has been described that may predict possible user interactions with a service provider system based on real-time and historical data that is processed by machine learning algorithms. Based on the predicted user interactions, the cross-platform customer service system may preemptively provide information to a user and/or perform actions to generate and provide a customized user experience that may help achieve a business goal of the service provider," Batlle paragraph 0082; " In an embodiment, the predictive user interaction engine 204 may include static rules that describe general goals of the service provider and that are updatable by the service provider. For example, a goal of the service provider may be to maximize profits, reduce the number of communication sessions between a user and a customer service representative, retain users as customers, increase consumption by the certain users, and any other goal, hierarchy of goals, or combination of goals that would be apparent to one of skill in the art in possession of the present disclosure. The predictive management device may consider these goals when generating the rules," Batlle paragraph 0035, using the predictive management system to identify opportunities to maximize profits, retain customers as users or decrease costs (i.e., bottlenecks, inefficiencies and process issues)).
As to claim 9, Batlle discloses the system of claim 1, wherein the workflow automation processor generates workflow analysis, insights and findings that are transmitted to an interactive user interface ("Section 1408 may include recent history of user interactions with the service provider and/or the customer service platforms. Section 1410 may include customer notes of previous interactions with the user associated with the user account and may be configured to allow the customer service representative to insert additional notes as the customer service representative interacts with the user of the user device 104," Batlle paragraph 0079).
As to claim 10, Batlle discloses the system of claim 1, wherein the user guide interface provides immediate and personalized assistance as a virtual guide to the target application ("For example, the recent activity of a user account that has interacted with the web site of the web server 600 and accessed the user's account may indicate that the user purchased two of the same items but in different sizes, and the items have been shipped and received by the user. The predictive management device 200 may determine that under these conditions the user is likely looking for return information for one of the items, and may generate instructions that address returning items and obtaining a refund. The predictive management device 200 may also determine that the user may be looking for exchange information to exchange one or more of the items for a different item. However, this scenario may be less likely than returning an item, which the instructions may take into account as causing the web server 600 to present the less likely scenario second to the more likely scenario, or in a less prominent area of the web page," Batlle paragraph 0056; "FIG. 9 is a screen shot of an embodiment of a user device displaying an updated customized web page 902 displayed via the web browser 800 of the user device 104. Based on the information about the particular user account provided by the web server 600 to the predictive management device 200, the predictive management device 200 may determine that a seventh FAQ illustrated by FAQ link 916 is the most relevant to the particular user, and an eighth FAQ illustrated by FAQ link 918 is another relevant FAQ, both of which may take the place of FAQ links 812 and 814 of FIG. 8," Batlle paragraph 0061, modifying the UI to offer personalized assistance for the user's specific situation).
As to claim 11, Batlle discloses a computer-implemented method for implementing an automated process and application transformation solution, the method comprising the steps of:
performing, via a tracking interface, data acquisition by dynamically capturing user interactions with at least one application via a communication network ("Referring now to FIG. 7, a method 700 for generating a customized user experience via a web server is illustrated. The method 700 begins at block 702 where a web server determines user interaction with a website from a user device. In an embodiment, the web server 600 may detect user interaction with a web page of a website via requests received from the user device 104, and gather any information about the user interaction include user information, location information, user device 104 type, current web page of the website, whether the website was accessed by a mobile application or web browser, time of interaction, Internet protocol address or any other device identifier, authenticated session information, and any other information that may be captured from a user interaction with a website and that would be apparent to one of skill in the art in possession of the present disclosure," Batlle paragraph 0054, capturing user interactions with a website);
storing and managing, via a storage component, the dynamically captured user interactions ("The predictive user interaction engine 204 may be configured to generate the first user interaction rules based on the real-time data and historical data received from the service provider system 102 and/or third party database 126," Batlle paragraph 0035, user interactions stored as historical data in a database);
initiating, via an optimization processor, a process transformation that correlates the dynamically captured user interactions and system activity data to generate an application model wherein the application model is optimized through a business process map and at least one recommendation for enhancement (“The user device 1602, the customer service terminal device 1604, the service provider system device 1606, and the third party device 1608 may each include one or more processors, memories, and other appropriate components for executing instructions such as program code and/or data stored on one or more computer readable mediums to implement the various applications, data, and steps described herein,” Batlle paragraph 0085; "In an embodiment, the instructions may be individual instructions that address a condition for a particular user, user account, and/or user device that is accessing the web server 600. In this embodiment, the webserver may gather an identifier of the user/user device such as user account information due to a login, and/or a device identifier of the user device 104. For example, the instructions may be based on recent activity of the user. The web server 600 may determine that a particular user logged into their account with the service provider system 102, and the web server 600 may transmit the user account information to the predictive management device 200. The predictive management device 200 may determine instructions based on the condition that is the user account information. The user account information may include recent activity of the user associated with the user account such that the recent activity as first data may be used to determine a condition exists along with an instruction based on the condition as in blocks 306 and 308 of method 300 described above. For example, the recent activity of a user account that has interacted with the web site of the web server 600 and accessed the user's account may indicate that the user purchased two of the same items but in different sizes, and the items have been shipped and received by the user. The predictive management device 200 may determine that under these conditions the user is likely looking for return information for one of the items, and may generate instructions that address returning items and obtaining a refund," Batlle paragraph 0056; "The method 700 proceeds to block 706 where the web server generates a customized website based on the instructions. In an embodiment, the web server 600 may generate one or more customized web pages based on the instructions received from the user interaction database 114 and/or the predictive management engine 200," Batlle paragraph 0057, correlating user interactions to predict the user would like to initiate a return and generating enhancement instructions that can be converted into code to generate a customized website (i.e., the instructions are a business process map));
responsive to the business process map, generating, via a code generation processor, a user guide interface, monitors data flows and automatically generates application computer code for transformation implementation to a target application ("The method 700 proceeds to block 706 where the web server generates a customized website based on the instructions. In an embodiment, the web server 600 may generate one or more customized web pages based on the instructions received from the user interaction database 114 and/or the predictive management engine 200. The method 700 then proceeds to operation 708 where the customized website is provided for display on the user device. In an embodiment, the web server 600 may provide the customized web pages of the customized web site to the user device 104, and the user device 104 may display the customized web page on a display of the user device 104," Batlle paragraph 0057); and
deploying, via a workflow automation processor, the application computer code in a target environment for transformation adoption and continuously gathers data and provides feedback for updated optimization for continuous improvement ("The method 700 proceeds to decision block 710 where the web server determines whether there is any user interaction with the customized website. In an embodiment, the web server 600 may determine whether the user is interacting with the customized website. If the user is no longer interacting or has closed out of the customized website, then the method 700 may end and the web server 600 may provide the information to the predictive management device 200. If the user interacts with the customized website, the method 700 may then proceed to block 712 where the web server transmits data associated with the interaction to the predictive management device 200," Batlle paragraph 0059, continually monitoring for further interactions in order to generate further instructions to further customize the website).
As to claim 12, it is substantially similar to claim 2 and is therefore rejected using the same rationale as above.
As to claim 13, it is substantially similar to claim 3 and is therefore rejected using the same rationale as above.
As to claim 14, it is substantially similar to claim 4 and is therefore rejected using the same rationale as above.
As to claim 15, it is substantially similar to claim 5 and is therefore rejected using the same rationale as above.
As to claim 16, it is substantially similar to claim 6 and is therefore rejected using the same rationale as above.
As to claim 17, it is substantially similar to claim 7 and is therefore rejected using the same rationale as above.
As to claim 18, it is substantially similar to claim 8 and is therefore rejected using the same rationale as above.
As to claim 19, it is substantially similar to claim 9 and is therefore rejected using the same rationale as above.
As to claim 20, it is substantially similar to claim 10 and is therefore rejected using the same rationale as above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
US 20160246885 A1 to Aravamudhan et al. discloses a proactive knowledge offering system and method where user interactions with a webpage are monitored to determine user intent and modifying the webpage according to the user intent;
US 20190042627 A1 to Osotio et al. discloses dynamic productivity content rendering based upon user interaction patterns where user interaction patterns are monitored and used to modify the graphical user interface of an application;
US 20180268073 A1 to Wang et al. discloses online user space exploration for recommendations where a machine learning model receives user interaction data and outputs changes to a website;
US 20180268337 A1 to Miller et al. discloses user objective assistance technologies where a machine learning model processes application user interaction data in order to generate instructions for modifying a user interface of the application;
US 20190043115 A1 to Purves et al. discloses a machine learning tool where a machine learning model monitors user interactions with a website and generates real-time changes to visual elements of the website;
US 20210191835 A1 to Gueta et al. discloses a system and method for struggle identification where user interactions with a website are monitored in order to determine struggle events and using the determined struggle events to generate changes for the website; and
US 20240394078 A1 to Bonnet et al. discloses a visual assist chatbot for improved accessibility of content by a visually impaired user where artificial intelligence receives user interaction data, uses the data to determine a visual assist level and modifying the layout and appearance of a website based on the determined visual assist level.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANIEL SAMWEL whose telephone number is (313) 446-6549. The examiner can normally be reached Monday through Thursday 8:00-6:00 EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kieu Vu can be reached at (571) 272-4057. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DANIEL SAMWEL/Primary Examiner, Art Unit 2171
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