DETAILED ACTION
The following claims are pending in this office action: 1-20
Claims 1, 8 and 15 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 .
Drawings
The drawings filed on 09/27/2022 are accepted.
Claim Rejections - 35 USC § 102
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.
Claim 1, 8, 15 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Dodeja et al. (US 10380218 B2) [hereinafter "Dodeja"].
As per claim 1, Dodeja discloses a processor-implemented method, the method comprising: identifying one or more roles corresponding to one or more users;([Dodeja, [Abstract]]”The request may be associated with one or more attributes.”) determining a set of tags corresponding to sections of a document; ([Dodeja, [Abstract]” The method may also include identifying a section of the code that is enclosed by a set of tags that specify requirements for accessing the section of the code.”) associating tags from the set of tags with associated roles from the one or more roles; ([Dodeja, [Abstract]”The request may be associated with one or more attributes. The method may also include identifying a section of the code that is enclosed by a set of tags that specify requirements for accessing the section of the code”) filtering a view of the document for a user from the one or more users according to the tags from the set of tags, the associated roles, and a set of roles corresponding to the user; ([Dodeja, [Abstract]” determining that the one or more attributes associated with the request do not meet the requirements for accessing the section of the code. The method may further include sending the code for displaying the web content to the client device with the section of the code enclosed by the set of tags removed”) and presenting the view to the user. ([Dodeja, [Abstract]” The method may further include sending the code for displaying the web content to the client device with the section of the code enclosed by the set of tags removed.”)
As per claim 8, Dodeja discloses a computer system, the computer system comprising: one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising:([ Dodeja, clm17]” A system comprising: one or more processors; and one or more memory devices comprising instructions that, when executed by the one or more processors, cause the one or more processors to perform operations”) identifying one or more roles corresponding to one or more users; ;([Dodeja, [Abstract]]”The request may be associated with one or more attributes.”) determining a set of tags corresponding to sections of a document; ([Dodeja, [Abstract]” The method may also include identifying a section of the code that is enclosed by a set of tags that specify requirements for accessing the section of the code.”) associating tags from the set of tags with associated roles from the one or more roles; ([Dodeja, [Abstract]”The request may be associated with one or more attributes. The method may also include identifying a section of the code that is enclosed by a set of tags that specify requirements for accessing the section of the code”) filtering a view of the document for a user from the one or more users according to the tags from the set of tags, the associated roles, and a set of roles corresponding to the user; ([Dodeja, [Abstract]” determining that the one or more attributes associated with the request do not meet the requirements for accessing the section of the code. The method may further include sending the code for displaying the web content to the client device with the section of the code enclosed by the set of tags removed”) and presenting the view to the user. ([Dodeja, [Abstract]” The method may further include sending the code for displaying the web content to the client device with the section of the code enclosed by the set of tags removed.”)
As per claim 15, Dodeja discloses a computer program product, the computer program product comprising: one or more computer-readable tangible storage medium and program instructions stored on at least one of the one or more tangible storage medium, the program instructions executable by a processor capable of performing a method, the method comprising:([Dodeja, Clm12]” A non-transitory, computer-readable medium comprising instructions that, when executed by one or more processors, causes the one or more processors to perform operations comprising…”) identifying one or more roles corresponding to one or more users;([Dodeja, [Abstract]]”The request may be associated with one or more attributes.”) determining a set of tags corresponding to sections of a document;([Dodeja, [Abstract]” The method may also include identifying a section of the code that is enclosed by a set of tags that specify requirements for accessing the section of the code.”) associating tags from the set of tags with associated roles from the one or more roles; ([Dodeja, [Abstract]”The request may be associated with one or more attributes. The method may also include identifying a section of the code that is enclosed by a set of tags that specify requirements for accessing the section of the code”) filtering a view of the document for a user from the one or more users according to the tags from the set of tags, the associated roles, and a set of roles corresponding to the user; ([Dodeja, [Abstract]” determining that the one or more attributes associated with the request do not meet the requirements for accessing the section of the code. The method may further include sending the code for displaying the web content to the client device with the section of the code enclosed by the set of tags removed”) and presenting the view to the user. ([Dodeja, [Abstract]” The method may further include sending the code for displaying the web content to the client device with the section of the code enclosed by the set of tags removed.”)
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 2, 9 and 16 are rejected under 35 U.S.C. §103 as being unpatentable over Dodeja et al. (US 10380218 B2) [hereinafter “Dodeja”] in view of Lui et al. (US 12081668 B2) [hereinafter “Lui”] .
As per claim 2, Dodeja discloses the method of claim 1, Dodeja does not explicitly disclose wherein providing the view of the document to the user is performed using a message authentication code as a security measure. However, Lui discloses wherein providing the view of the document to the user is performed using a message authentication code as a security measure.([Lui, [0015]]”…. after the CDN performs authentication on the first authentication credential by using the first key and determines that the first authentication credential passes the authentication, whether the content resource is stored in the CDN; and when the CDN determines that the content resource is not stored in the CDN after the CDN performs authentication on the first authentication credential and determines that the first authentication credential passes the authentication, the second authentication credential is used for the cloud server to send, after the cloud server performs authentication on the second authentication credential by using the second key and determines that the second authentication credential passes the authentication, the content resource to the client.” Lui further discloses “In a possible design, the first encryption algorithm is one of a symmetric encryption algorithm, an asymmetric encryption algorithm, a hash algorithm, or an HMAC algorithm, and the second encryption algorithm is one of a symmetric encryption algorithm, an asymmetric encryption algorithm, a hash algorithm, or an HMAC algorithm.”[0021]. Therefore, it would have been obvious before the effective filing date of the claimed invention for one of ordinary skill in the art to integrate into Dodeja wherein providing the view of the document to the user is performed using a message authentication code as a security measure as suggested by Lui. One of ordinary skill in the art would have been motivated to do so because Lui expressly teaches using message authentication codes which is HMAC-based authentication to secure access to content resources by verifying authentication credentials prior to content delivery, thereby providing a well-known and predictable security mechanism for ensuring that only authenticated users are permitted to access protected content.
As per claim 9, Dodeja discloses the computer system of claim 8. Dodeja does not explicitly disclose wherein providing the view of the document to the user is performed using a message authentication code as a security measure. However, Lui discloses wherein providing the view of the document to the user is performed using a message authentication code as a security measure.([Lui, [0015]]”…. after the CDN performs authentication on the first authentication credential by using the first key and determines that the first authentication credential passes the authentication, whether the content resource is stored in the CDN; and when the CDN determines that the content resource is not stored in the CDN after the CDN performs authentication on the first authentication credential and determines that the first authentication credential passes the authentication, the second authentication credential is used for the cloud server to send, after the cloud server performs authentication on the second authentication credential by using the second key and determines that the second authentication credential passes the authentication, the content resource to the client.” Lui further discloses “In a possible design, the first encryption algorithm is one of a symmetric encryption algorithm, an asymmetric encryption algorithm, a hash algorithm, or an HMAC algorithm, and the second encryption algorithm is one of a symmetric encryption algorithm, an asymmetric encryption algorithm, a hash algorithm, or an HMAC algorithm.”[0021]. Therefore, it would have been obvious before the effective filing date of the claimed invention for one of ordinary skill in the art to integrate into Dodeja wherein providing the view of the document to the user is performed using a message authentication code as a security measure as suggested by Lui. One of ordinary skill in the art would have been motivated to do so because Lui expressly teaches using message authentication codes which is HMAC-based authentication to secure access to content resources by verifying authentication credentials prior to content delivery, thereby providing a well-known and predictable security mechanism for ensuring that only authenticated users are permitted to access protected content.
As per claim 16, Dodeja discloses the computer program product of claim 15, Dodeja does not disclose wherein providing the view of the document to the user is performed using a message authentication code as a security measure. However, Lui discloses wherein providing the view of the document to the user is performed using a message authentication code as a security measure.([Lui, [0015]]”…. after the CDN performs authentication on the first authentication credential by using the first key and determines that the first authentication credential passes the authentication, whether the content resource is stored in the CDN; and when the CDN determines that the content resource is not stored in the CDN after the CDN performs authentication on the first authentication credential and determines that the first authentication credential passes the authentication, the second authentication credential is used for the cloud server to send, after the cloud server performs authentication on the second authentication credential by using the second key and determines that the second authentication credential passes the authentication, the content resource to the client.” Lui further discloses “In a possible design, the first encryption algorithm is one of a symmetric encryption algorithm, an asymmetric encryption algorithm, a hash algorithm, or an HMAC algorithm, and the second encryption algorithm is one of a symmetric encryption algorithm, an asymmetric encryption algorithm, a hash algorithm, or an HMAC algorithm.”[0021].Claim 16 recites the same additional limitation as claim 9. Accordingly, this claim is rejected under the same rationale as claim 9.
Claims 3, 4, 10, 11, 17, 18 are rejected under 35 U.S.C. §103 as being unpatentable over Dodeja et al. (US 10380218 B2) [hereinafter “Dodeja”] in view of Shi et al. "A Mechanism to Resolve the Unauthorized Access Vulnerability Caused by Permission Delegation in Blockchain-Based Access Control," in IEEE Access, vol. 8, pp. 156027-156042, 2020, doi: 10.1109/ACCESS.2020.3018783” [hereinafter “Shi”]
As per claim 3, Dodeja discloses the method of claim 1. Dodeja does not explicitly disclose wherein a role from the one or more roles is identified by a non- fungible token in a blockchain wallet. However, Shi discloses wherein a role from the one or more roles is identified by a non- fungible token in a blockchain wallet. ([Shi, pp.156027-156028, section I.] “Permission delegation refers to the behavior that an entity passes to another a specific permission after obtaining it. Adding a permission delegation module to access control enriches the functions of the latter and provides users with another way to obtain permissions in addition to requesting authorization. It is especially applicable when the owner and manager of the object are inconsistent.”) Therefore, it would have been obvious before the effective filing date of the claimed invention for one of ordinary skill in the art to integrate into Dodeja wherein a role from the one or more roles is identified by a non- fungible token in a blockchain wallet as suggested by Shi. One of ordinary skill in the art would have been motivated to incorporate Shi’s non-fungible token-based access framework in order to provide a secure, tamper-resistant, and decentralized mechanism for identifying roles and controlling access.
As per claim 4, Dodeja discloses the method of claim 3. Dodeja does not explicitly disclose wherein the non-fungible token is a soulbound token. However, Shi discloses wherein the non-fungible token is a soulbound token. ([Shi, pp.156027-156028, 156039]” Permission delegation refers to the behavior that an entity passes to another a specific permission after obtaining it”. Shi adds that “ ...only subjects that meet the constraints can receive tokens” and further shows that “…....the algorithm integrates the access policy for permissions into the permission token.”) The examiner interprets Shi as disclosing a permission token constrained by embedded access policy condition, which the Examiner understands as a soulbound token. Therefore, it would have been obvious before the effective filing date of the claimed invention for one of ordinary skill in the art to integrate into Dodeja wherein the non-fungible token is a soulbound token as suggested by Shi. One of ordinary skill in the art would have been motivated to do so because Shi teaches binding permission tokens to embedded access policy conditions, thereby preventing transferability and improving access control security.
As per claim 10, Dodeja discloses the computer system of claim 8. Dodeja does not explicitly disclose wherein a role from the one or more roles is identified by a non-fungible token in a blockchain wallet. However, Shi in the same field of endeavor discloses wherein a role from the one or more roles is identified by a non-fungible token in a blockchain wallet. ([Shi, pp.156027-156028, section I.] “Permission delegation refers to the behavior that an entity passes to another a specific permission after obtaining it. Adding a permission delegation module to access control enriches the functions of the latter and provides users with another way to obtain permissions in addition to requesting authorization. It is especially applicable when the owner and manager of the object are inconsistent.”).Claim 10 recites the same additional limitation as claim 3. Accordingly, this claim is rejected under the same rationale as claim 3.
As per claim 11, Dodeja discloses the computer system of claim 10. Dodeja does not explicitly discloses wherein the non-fungible token is a soulbound token. However, Shi discloses wherein the non-fungible token is a soulbound token. ([Shi, pp.156027-156028, 156039]” Permission delegation refers to the behavior that an entity passes to another a specific permission after obtaining it”. Shi adds that “ ...only subjects that meet the constraints can receive tokens” and further shows that “…....the algorithm integrates the access policy for permissions into the permission token.”). Claim 11 recites the same additional limitation as claim 4. Accordingly, this claim is rejected under the same rationale as claim 4.
As per claim 17, Dodeja discloses the computer program product of claim 15. Dodeja does not disclose wherein a role from the one or more roles is identified by a non-fungible token in a blockchain wallet. However, Shi discloses wherein a role from the one or more roles is identified by a non- fungible token in a blockchain wallet ([Shi, pp.156027-156028, section I.] “Permission delegation refers to the behavior that an entity passes to another a specific permission after obtaining it. Adding a permission delegation module to access control enriches the functions of the latter and provides users with another way to obtain permissions in addition to requesting authorization. It is especially applicable when the owner and manager of the object are inconsistent.”).Claim 17 recites the same additional limitation as claim 3. Accordingly, this claim is rejected under the same rationale as claim 3.
As per claim 18, Dodeja discloses the computer program product of claim 17. Dodeja does not disclose wherein the non-fungible token is a soulbound token. Dodeja does not explicitly disclose wherein the non-fungible token is a soulbound token. However, Shi discloses wherein the non-fungible token is a soulbound token. ([Shi, pp.156027-156028, 156039]” Permission delegation refers to the behavior that an entity passes to another a specific permission after obtaining it”. Shi adds that “ ...only subjects that meet the constraints can receive tokens” and further shows that “…....the algorithm integrates the access policy for permissions into the permission token.”) Claim 18 recites the same additional limitation as claim 4. Accordingly, this claim is rejected under the same rationale as claim 4.
Claims 5-7, 12-14, 19 and 20 are rejected under 35 U.S.C. §103 as being unpatentable over Dodeja et al. (US 10380218 B2) [hereinafter “Dodeja”] in view of El-Rayes et al. (US 20200257847 A1) [hereinafter “El-Rayes ”] .
As per claim 5, Dodeja discloses the method of claim 1. Dodeja does not disclose wherein determining the set of tags is performed using artificial intelligence and a neural network. However, El-Rayes in the same field of endeavor discloses wherein determining the set of tags is performed using artificial intelligence and a neural network.([ El-Rayes , [0054]”…. a first step 100 creates a model. Such model creation 100 can involve training an artificial intelligence model such as a deep neural network using a collection of PDF documents so the model machine learns from the files (block 200). The resulting model is then generated (block 300). The resulting model is used to analyze and classify structures of a file and generate tags for those structures (block 400). An optional automatic or manual review step (block 500) determines whether the tags generated by the automatic classification are correct. The results of the review step may be used to touch up the files and in particular the tags generated for the files (block 600).”). Therefore, it would have been obvious before the effective filing date of the claimed invention for one of ordinary skill in the art to modify Dodeja to further include wherein determining the set of tags is performed using artificial intelligence and a neural network as suggested by El-Rayes . One of ordinary skill in the art would have been motivated to do so because El-Rayes expressly teaches using artificial intelligence and deep neural networks to automatically analyze document structures and generate tags, thereby improving automation, accuracy, and efficiency of tag determination.
As per claim 6, Dodeja discloses the method of claim 1. Dodeja does not disclose wherein associating tags with associated roles is performed using artificial intelligence and a neural network. However, El-Rayes in the same field of endeavor discloses wherein associating tags with associated roles is performed using artificial intelligence and a neural network.([ El-Rayes [0054], [0056] ]”…. a first step 100 creates a model. Such model creation 100 can involve training an artificial intelligence model such as a deep neural network using a collection of PDF documents so the model machine learns from the files (block 200)…….the tags generated for the files (block 600)”) and further “… shows that the parameters are sent to the AI Tag predictor module (440) that uses the model to predict the type of tag.”). Therefore, it would have been obvious before the effective filing date of the claimed invention for one of ordinary skill in the art to modify Dodeja to further include wherein associating tags with associated roles is performed using artificial intelligence and a neural network as suggested by El-Rayes . One of ordinary skill in the art would have been motivated to do so because El-Rayes teaches applying artificial intelligence and deep neural networks to automatically analyze document structures and predict tag types, yielding predictable improvements in automation, accuracy and efficiency.
As per claim 7, Dodeja discloses the method of claim 1. Dodeja discloses associating higher-level tags with associated roles but fails to explicitly disclose determining one or more higher-level tags that include one or more lower-level tags from the set of tags. However, El-Rayes discloses determining one or more higher-level tags that include one or more lower-level tags([ El-Rayes [0044], [0047]” …(a) generating a model in response to learning from a set of similar, well tagged PDF files and user input to select the metrics to be used for prediction in that model. Images within these documents are rendered and their features are extracted and saved in a repository along with any provided alternative text; (b) Previously tagged or untagged files are opened and are divided into blocks. Blocks are then checked for well-known patterns and subdivided accordingly into sub-blocks and an AI tag predictor module uses the generated model to predict the type of tag (providing additional Meta data as required by accessibility standards); (c) Heading levels for heading tags may be adjusted to ensure compliance with accessibility standards; (d) A Figure AI module, in which figures are compared to other figures stored in the database and if a good match is found, it is assigned Meta data (for example Alternative Text) provided in the database; and (e) …case” and further adds that “The documents may be divided into blocks and sub-blocks) from the set of tags([ El-Rayes [0049], [0068]]”The heading level is adjusted to ensure compliance with accessibility standards”….” When a tag is predicted to be a Heading, an algorithm is used to possibly adjust the Heading level to ensure compliance with accessibility standards.”).Therefore, it would have been obvious before the effective filing date of the claimed invention for one of ordinary skill in the art to modify Dodeja to further include determining one or more higher-level tags that include one or more lower-level tags from the set of tags as suggested by El-Rayes . One of ordinary skill in the art would have been motivated to do so because El-Rayes teaches to enable automated hierarchical tag determination that integrates naturally with role-based access control, thereby reducing manual tag assignment, improving consistency across document structures, and enhancing scalability of role-associated tagging.
As per claim 12, Dodeja discloses the computer system of claim 8. Dodeja does not explicitly disclose wherein determining the set of tags is performed using artificial intelligence and a neural network. However, El-Rayes in the same field of endeavor discloses wherein determining the set of tags is performed using artificial intelligence and a neural network.([ El-Rayes , [0054]”…. a first step 100 creates a model. Such model creation 100 can involve training an artificial intelligence model such as a deep neural network using a collection of PDF documents so the model machine learns from the files (block 200). The resulting model is then generated (block 300). The resulting model is used to analyze and classify structures of a file and generate tags for those structures (block 400). An optional automatic or manual review step (block 500) determines whether the tags generated by the automatic classification are correct. The results of the review step may be used to touch up the files and in particular the tags generated for the files (block 600).”). Claim 12 recites the same additional limitation as claim 5. Accordingly, this claim is rejected under the same rationale as claim 5.
As per claim 13, Dodeja discloses the computer system of claim 8. Dodeja does not explicitly disclose wherein associating tags with associated roles is performed using artificial intelligence and a neural network. However, El-Rayes in the same field of endeavor discloses wherein associating tags with associated roles is performed using artificial intelligence and a neural network.([ El-Rayes [0054], [0056] ]”…. a first step 100 creates a model. Such model creation 100 can involve training an artificial intelligence model such as a deep neural network using a collection of PDF documents so the model machine learns from the files (block 200)…….the tags generated for the files (block 600)”) and further “… shows that the parameters are sent to the AI Tag predictor module (440) that uses the model to predict the type of tag.”). Claim 13 recites the same additional limitation as claim 6. Accordingly, this claim is rejected under the same rationale as claim 6.
As per claim 14, Dodeja discloses the computer system of claim 8. Dodeja discloses associating higher-level tags with associated roles but fails to explicitly disclose determining one or more higher-level tags that include one or more lower-level tags from the set of tags. However, El-Rayes discloses determining one or more higher-level tags that include one or more lower-level tags([ El-Rayes [0044], [0047]” …(a) generating a model in response to learning from a set of similar, well tagged PDF files and user input to select the metrics to be used for prediction in that model. Images within these documents are rendered and their features are extracted and saved in a repository along with any provided alternative text; (b) Previously tagged or untagged files are opened and are divided into blocks. Blocks are then checked for well-known patterns and subdivided accordingly into sub-blocks and an AI tag predictor module uses the generated model to predict the type of tag (providing additional Meta data as required by accessibility standards); (c) Heading levels for heading tags may be adjusted to ensure compliance with accessibility standards; (d) A Figure AI module, in which figures are compared to other figures stored in the database and if a good match is found, it is assigned Meta data (for example Alternative Text) provided in the database; and (e) …case” and further adds that “The documents may be divided into blocks and sub-blocks) from the set of tags([ El-Rayes [0049], [0068]]”The heading level is adjusted to ensure compliance with accessibility standards”….” When a tag is predicted to be a Heading, an algorithm is used to possibly adjust the Heading level to ensure compliance with accessibility standards.”). Claim 14 recites the same additional limitation as claim 7. Accordingly, this claim is rejected under the same rationale as claim 7.
As per claim 19, Dodeja discloses the computer program product of claim 15. Dodeja does not disclose wherein determining the set of tags is performed using artificial intelligence and a neural network. . However, El-Rayes in the same field of endeavor discloses wherein determining the set of tags is performed using artificial intelligence and a neural network.([ El-Rayes , [0054]”…. a first step 100 creates a model. Such model creation 100 can involve training an artificial intelligence model such as a deep neural network using a collection of PDF documents so the model machine learns from the files (block 200). The resulting model is then generated (block 300). The resulting model is used to analyze and classify structures of a file and generate tags for those structures (block 400). An optional automatic or manual review step (block 500) determines whether the tags generated by the automatic classification are correct. The results of the review step may be used to touch up the files and in particular the tags generated for the files (block 600).”). Claim 19 recites the same additional limitation as claim 12. Accordingly, this claim is rejected under the same rationale as claim 12.
As per claim 20, Dodeja discloses the computer program product of claim 15. Dodeja does not explicitly disclose wherein associating tags with associated roles is performed using artificial intelligence and a neural network. However, El-Rayes in the same field of endeavor discloses wherein associating tags with associated roles is performed using artificial intelligence and a neural network.([ El-Rayes [0054], [0056] ]”…. a first step 100 creates a model. Such model creation 100 can involve training an artificial intelligence model such as a deep neural network using a collection of PDF documents so the model machine learns from the files (block 200)…….the tags generated for the files (block 600)”) and further “… shows that the parameters are sent to the AI Tag predictor module (440) that uses the model to predict the type of tag.”). Claim 20 recites the same additional limitation as claim 13. Accordingly, this claim is rejected under the same rationale as claim 13.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Iampietro et al. (US 8200669 B1) discloses managing smart tags using a hierarchical structure, wherein tags are organized into parent and child relationships.
Biazetti et al. (US 20210157947 A1) discloses dynamically assigning and enforcing permissions bases on roles, attributes, and contextual conditions.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Komi N. AMEVIGBE whose telephone number is (571)272-3381. The examiner can normally be reached Monday-Friday 2pm-10pm.
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, Carl Colin can be reached at (571) 272-3862. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/K.N.A./Examiner, Art Unit 2493
/CARL G COLIN/Supervisory Patent Examiner, Art Unit 2493