Detailed Action
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of the Application and Claims
This action is in reply to the application filed on 1/10/2025.
IDS filed on 1/16/2025 is acknowledged and considered by the Examiner.
This communication is the first action on the merits.
Claims 1-20 is/are currently pending and have been examined.
Claim Rejections – 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Claim 1 (similarly 8, 15) recites, “A … for detecting and executing one or more changes in a planogram, comprising: …, and configured to:
identify one or more changes in a planogram for a retailer;
generate one or more tasks based on the one or more identified changes;
determine a task priority for each of the one or more generated tasks;
monitor, in real time, execution of the one or more generated tasks via … associated with the retailer, wherein the execution is specified by the task priority for each of the one or more generated tasks;
detect at least one error in the execution of the one or more generated tasks; and
transmit, in real time, one or more tasks to a … to account for the at least one error.
Analyzing under Step 2A, Prong 1:
The limitations regarding, …detecting and executing one or more changes in a planogram…identify one or more changes in a planogram for a retailer; generate one or more tasks based on the one or more identified changes; determine a task priority for each of the one or more generated tasks; monitor, in real time, execution of the one or more generated tasks via … associated with the retailer, wherein the execution is specified by the task priority for each of the one or more generated tasks; detect at least one error in the execution of the one or more generated tasks; and transmit, in real time, one or more tasks to a … to account for the at least one error…, under the broadest reasonable interpretation, can include a human using their mind and using pen and paper to perform the above identified limitations, therefore, the claims are directed to a mental process.
Further, …detecting and executing one or more changes in a planogram…identify one or more changes in a planogram for a retailer; generate one or more tasks based on the one or more identified changes; determine a task priority for each of the one or more generated tasks; monitor, in real time, execution of the one or more generated tasks via … associated with the retailer, wherein the execution is specified by the task priority for each of the one or more generated tasks; detect at least one error in the execution of the one or more generated tasks; and transmit, in real time, one or more tasks to a … to account for the at least one error…, are human observing changes in retail stores, human generating tasks and task priorities based on changes in retail stores, human accounting for errors in task performed by humans, which are fundamental economic principles or practices, managing personal behavior or relationships or interactions between people, therefore the claims, are directed to certain methods of organizing human activities.
Accordingly, the claims are directed to a mental process, certain methods of organizing human activities, and thus, the claims are directed to an abstract idea under the first prong of Step 2A.
Analyzing under Step 2A, Prong 2:
This judicial exception is not integrated into a practical application under the second prong of Step 2A.
In particular, the claims recite the additional elements beyond the recited abstract idea identified under Step 2A, Prong 1, such as:
Claim 1, 8, 15: system, a computer, comprising a processor and memory, one or more devices, mobile device, computer-implemented, A non-transitory computer-readable storage medium embodied with software
Claim 5, 12, 19: one or more cameras, one or more sensors and one or more devices capable of transmitting location data
, and pursuant to the broadest reasonable interpretation, as an ordered combination, each of the additional elements are computing elements recited at high level of generality implementing the abstract idea, and thus, are no more than applying the abstract idea with generic computer components.
Further, these additional elements generally link the abstract idea to a technical environment, namely the environment of a computer.
Additionally, with respect to, “…identify…”, “…transmit…”, these elements do not add a meaningful limitations to integrate the abstract idea into a practical application because they are extra-solution activity, pre and post solution activity - i.e. data gathering – “…identify…”, data output – “…transmit…”
Analyzing under Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception under Step 2B.
As noted above, the aforementioned additional elements beyond the recited abstract idea are not sufficient to amount to significantly more than the recited abstract idea because, as an order combination, the additional elements are no more than mere instructions to implement the idea using generic computer components (i.e. apply it).
Additionally, as an order combination, the additional elements append the recited abstract idea to well-understood, routine, and conventional activities in the field as individually evinced by the applicant’s own disclosure, as required by the Berkheimer Memo, in at least:
[0017] As shown in FIGURE 1, supply chain network 100comprising planogram update system 110,archiving system 120, and planning and execution system 130 may operate on one or more computers 150 that are integral to or separate from the hardware and/or software that support planogram update system 110,archiving system 120 and planning and execution system 130. One or more computers 150 may include any suitable input device 152, such as a keypad, mouse, touch screen, microphone, or other device to input information. Output device 154 may convey information associated with the operation of supply chain network 100, including digital or analog data, visual information, or audio information. One or more computers may include fixed or removable computer-readable storage media, including a non-transitory computer- readable medium, magnetic computer disks, flash drives, CD-ROM, in-memory device, or other suitable media to receive output from and provide input to supply chain network 100.
[0019] In addition, or as an alternative, supply chain network 100 may comprise a cloud- based computing system having processing and storage devices at one or more locations, local to, or remote from planogram update system 110,archiving system 120 and planning and execution system 130. In addition, each of one or more computers 150 may be a workstation, personal computer (PC), network computer, notebook computer, tablet, personal digital assistant (PDA), cell phone, telephone, smartphone, wireless data port, augmented or virtual reality headset, or any other suitable computing device.
[0029] In an embodiment user interface module 216 generates and displays a user interface (UI), such as, for example, a graphical user interface (GUI), that displays planograms or any other data of planogram update system 110 in charts or graphs, or any other visual representations of data of planogram update system 110. According to embodiments, user interface module 216 displays a GUI comprising interactive graphical elements for selecting one or more planograms and/or data of any kind stored in the database of planogram update system 110, and, in response to the selection, displaying the selected data on one or more display devices. User interface module 216 may generate interfaces for planograms or planogram tasks to be performed and transmit the interfaces to devices associated with users, such as smartphones or tablets of employees within a physical retail store. The users may then use the interfaces to perform planogram tasks in a task sequence, such as in sequence determined by the task priority determined by task priority module 214. In embodiments, user interface module 216 may generate non-visual interfaces, such as voice-based personal assistants or email messages or other text-based messages, and present planogram data to customers over such voice-based or text-based interfaces.
[0062] At seventh activity 314planogram update system 110 outputs a dynamic task sequence consisting of tasks associated with a particular user and a planogram associated with the tasks. In embodiments, the dynamic task sequence may be transmitted to a device associated with an associate or employer of the retailer, such as a tablet or smartphone.
[0070] At fourth activity 440planogram update system 110 monitors execution of the tasks generated at second activity 420 in sequence of the task priority determined at third activity 430.Planogram update system 110 may monitor execution in real time via devices associated with a physical store, including cameras or other sensors installed in the physical store, as well as devices associated with users or employees, including smartphones, tablets or other devices, such as IoT devices, that can transmit location data. In embodiments, if a task is performed out of sequence, or a task that was not in the set of tasks was performed, or the user has otherwise deviated from the task sequence, planogram update system 110 may perform dynamic re- sequencing to account for the deviated sequence. Planogram update system 110 may then transmit an updated task sequence to the user. In embodiments, the planogram update system 110 may perform dynamic resequencing in real time to account for a deviated sequence and transmit in real time an updated task sequence. For example, if an error occurs by a user executing a task, the Planogram update system 110 may detect the error in real time and transmit in real time one or more tasks to a mobile device of the user to account for the error. Planogram update system 110 may monitor execution of the tasks and send new task sequences as needed, until all tasks of the task sequence have been performed.
[0071] Reference in the foregoing specification to "one embodiment", "an embodiment", or "some embodiments" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment.
[0072] While the exemplary embodiments have been illustrated and described, it will be understood that various changes and modifications to the foregoing embodiments may become apparent to those skilled in the art without departing from the spirit and scope of the present invention.
Furthermore, as an ordered combination, these elements amount to generic computer components receiving or transmitting data over a network, performing repetitive calculations, electronic record keeping, and storing and retrieving information in memory, which, as held by the courts, are well-understood, routine, and conventional. See MPEP 2106.05(d).
Moreover, the remaining elements of dependent claims do not transform the recited abstract idea into a patent eligible invention because these remaining elements merely recite further abstract limitations that provide nothing more than simply a narrowing of the abstract idea recited in the independent claims.
Looking at these limitations as an ordered combination adds nothing additional that is sufficient to amount to significantly more than the recited abstract idea because they simply provide instructions to use a generic arrangement of generic computer components to “apply” the recited abstract idea, perform insignificant extra-solution activity, and generally link the abstract idea to a technical environment. Thus, the elements of the claims, considered both individually and as an ordered combination, are not sufficient to ensure that the claim as a whole amounts to significantly more than the abstract idea itself. Since there are no limitations in these claims that transform the exception into a patent eligible application such that these claims amount to significantly more than the exception itself, claims 1-20 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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 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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102 as being unpatentable by US Patent Publication to US20180293543A1 to Tiwari et al., (hereinafter referred to as “Tiwari”).
As per Claim 1, Tiwari teaches: A system for detecting and executing one or more changes in a planogram, comprising: a computer, comprising a processor and memory, and configured to: ([0122])
identify one or more changes in a planogram for a retailer; (in at least [0019] execute Blocks of the method S100 to implement perpetual inventory techniques to account for changing inventory in the store by recording (near) real-time changes in product stock on shelves throughout the store, such as to account for product units that are lost, damaged, stolen, misplaced, or not shelved.) [0026] the computer system can (re)construct a planogram of shelves throughout the store based on these RFID data and product data linked to these RFID data; the system can then implement this “constructed” planogram to detect changes in stock level throughout the store over time.)
generate one or more tasks based on the one or more identified changes; (in at least [0074] The system can also: implement methods and techniques described above to approximate the 2D or 3D location of a particular RFID tag that broadcast an RF signal that was interpreted as a particular SKU in the first list of unique SKUs; access product information of this particular SKU, as described above; generate a task specifying the approximate location of the particular RFID tag, product information of the particular SKU, and a prompt to remove a unit of the particular SKU from the inventory structure of interest; and then transmit this task to an associate of the store, thereby guiding the associate to correct misplaced products throughout the store. [0112] generates an electronic restocking list containing a filtered list of slots at inventory structures throughout the store in need of correction, such as addition of product, exchange of product, or straightening of product.)
determine a task priority for each of the one or more generated tasks; (in at least [0113] The computer system can also generate a stock correction task list to correct improperly-stocked slots. In this implementation, the system can generate a prioritized list of tasks to move misplaced products, to restock empty or improperly-stocked slots, etc. and then serve this task list to an associate (e.g., employee) of the store via a native stocking application executing on a mobile computing device (e.g., a tablet, a smartphone) carried by the associate. In this implementation, the computer system can implement methods and techniques described in U.S. patent application Ser. No. 15/347,689 to prioritize this list of tasks to correct improperly-stocked slots throughout the store.)
monitor, in real time, execution of the one or more generated tasks via one or more devices associated with the retailer, wherein the execution is specified by the task priority for each of the one or more generated tasks; (in at least [0105] in FIG. 3, the system: generates a 2D elevation image of an inventory structure, such as by stitching multiple discrete images recorded by the robotic system when occupying waypoints along the inventory structure into a single panoramic image of the inventory structure; implements methods and techniques described above to transform RFID values and related metadata collected by the robotic system when occupying the same waypoints into 2D plan or 3D locations of corresponding RFID tags within the store; and projects the 2D plan or 3D locations of these RFID tags onto the 2D elevation image of the inventory structure. The system can then: retrieve product data (e.g., SKU, serial number, data of manufacture, etc.) associated with each of these RFID values; and populate discrete regions of the 2D elevation image with corresponding product data in order to generate a visual representation of the inventory structure and unit-level product inventory in a single 2D visual document in Block S194.)
detect at least one error in the execution of the one or more generated tasks; and (in at least [0098] By then implementing this set of template images to identify products in images of the inventory structure, the computer system may more rapidly identify both products assigned to the inventory structure and RFID-tagged products mistakenly placed on the inventory structure, such as by a patron of the store. [0107] The computer system can also: implement machine vision techniques to identify slots stocked with incorrect products; identify products occupying these slots based on RFID values collected by the robotic system while navigating along the inventory structure but not contained in a list of SKUs assigned to the inventory structure by the planogram; and write a hotspot—indicating SKUs and/or other relevant data—to slots stocked with incorrect products represented in the 2D elevation image of the inventory structure. [0110] The computer system can then confirm whether a price value indicated in a price tag equals a price assigned to the corresponding product unit(s) (e.g., in the planogram or price database managed by the store) and then selectively prompt a store associated to correct the price tag if a difference is detected. For example, the computer system can transmit a location of the incorrect price tag and a correct price value for the price tag (or printable image for the correct price tag) to a mobile computing device associated with the store associate. [0112] system can generate a stocking status graph, table, or list of improperly-stocked slots throughout the store, such as including a mis-stocking mode (e.g., too many facings, too few facings, misoriented packaging, damaged packaging, outdated packaging, under quantity, over quantity, incorrect product location, etc.) for each improperly-stocked slot in this list based on stock values extracted from RFID and/or optical data collected by the robotic system, as shown in FIGS. 1, 2, 4, and 6. In this implementation, the system can serve this graph, table, or list to the manager of the store via a manager portal, such as executing on a desktop computer, a laptop computer, a tablet, or a smartphone, etc. [0120] By comparing this list of SKUs and their actual quantities to the planogram (or textual or numerical representation of the planogram), the system can also populate the digital report with indicators of slots or other inventory structures that are empty, under-stocked, over-stocked, or improperly-stocked with the incorrect product, etc. For example, the system can generate a textual list of the stock state of each slot in the store, such as ordered with empty slots followed by under-stocked slots followed by improperly-stocked slots, etc. and ordered by highest-value SKU to lowest-value SKU. Alternatively, the system can generate a 2D heat map of the stock states of slots throughout the store, such as indicating regions in which highest-value slots are empty in red, lower-value empty slots and overstocked-slots in a cooler color, and properly-stocked slots in even cooler colors.)
transmit, in real time, one or more tasks to a mobile device to account for the at least one error. (in at least [0110] The computer system can then confirm whether a price value indicated in a price tag equals a price assigned to the corresponding product unit(s) (e.g., in the planogram or price database managed by the store) and then selectively prompt a store associated to correct the price tag if a difference is detected. For example, the computer system can transmit a location of the incorrect price tag and a correct price value for the price tag (or printable image for the correct price tag) to a mobile computing device associated with the store associate. [0112] system can generate a stocking status graph, table, or list of improperly-stocked slots throughout the store, such as including a mis-stocking mode (e.g., too many facings, too few facings, misoriented packaging, damaged packaging, outdated packaging, under quantity, over quantity, incorrect product location, etc.) for each improperly-stocked slot in this list based on stock values extracted from RFID and/or optical data collected by the robotic system, as shown in FIGS. 1, 2, 4, and 6. In this implementation, the system can serve this graph, table, or list to the manager of the store via a manager portal, such as executing on a desktop computer, a laptop computer, a tablet, or a smartphone, etc.)
As per Claim 2, Tiwari teaches: The system of Claim 1,
wherein the one or more generated tasks comprise a task sequence. (in at least [0021] sequentially navigating to these waypoints and executing RFID interrogation parameters and imaging parameters defined by these waypoints. However, the computer system can alternatively define a continuous scan path along a shelving segment, a shelving structure, an aisle, a set of inventory structures, or throughout the entire store with fixed or varying (e.g., parametric or non-parametric) RFID interrogation and imaging parameters; and the robotic system can navigate along this continuous scan path while broadcasting an RFID interrogation signal, recording RFID values returned by RFID tags nearby, and/or recording optical (e.g., digital photographic) images substantially continuously along this path. [0044] determine that an inventory structure represents a hanging clothing rack stocked with hanging shirts based on data contained in the planogram of the store; then define a sequence of waypoints encircling the inventory structure; and specify a lower output power level for interrogation signals broadcast at each of these waypoints given lower density of materials between product stocked on the inventory structure and the robotic system at each of these waypoints. In yet another example, the computer system can: identify an inventory structure stocked with canned goods based on the planogram of the store; label the inventory structure as unsuitable for an RFID scan; and label waypoints defined along this inventory structure with triggers for optical scans only.)
As per Claim 3, Tiwari teaches: The system of Claim 1,
wherein the one or more transmitted tasks comprise an updated task sequence. (in at least [0052] Once the robotic system completes one or more scan routines at a waypoint, the robotic system can navigate to a next waypoint and repeat this process for each other waypoint defined for the store. [0082] interfaces with a restocking scheduler and with a point of sale system integrated into the store to track ingress of new products loaded onto the inventory structure throughout the store and to track egress or products from the store through sales; and updates quantities and/or types (e.g., SKUs) of products expected to be on the inventory structure throughout the store based on such product flux data. The robotic system can then implement these updated product quantity and/or type data when determining whether to repeat RFID scan routines at waypoints throughout the store in Block S140. [0065] the robotic system (or the remote computer system) can modify RFID interrogation parameters (e.g., interrogation power, inventory structure offset distance, robotic system speed, interrogation frequency, robotic system yaw orientation, etc.) based on data collected by the robotic system during a scan routine along an inventory structure in order to: ensure that RFID values are read from all RFID-tagged product units on the inventory structure; and/or improve accuracy of localization of these RFID tags. For example, the robotic system (or the remote computer system) can execute these closed-loop controls in real-time as the robotic system completes a scan routine at a single waypoint adjacent an inventory structure or as the robotic system traverses a short, continuous path along the inventory structure. Alternatively, the robotic system (or the remote computer system) can execute these processes asynchronously, such as once a scan of the inventory structure is completed or once the current scan cycle for the entire store is completed.)
As per Claim 4, Tiwari teaches: The system of Claim 1, wherein the computer is further configured to:
identify the one or more changes in the planogram by comparing an initial planogram with an updated planogram. (in at least [0061] in FIG. 4, inventory structures throughout the store are labeled with RFID tags or include integrated RFID tags loaded with substantially unique identifiers. In this variation, the system can track types, configurations, and locations, etc. of these inventory structures based on RFID values received by the robotic system during a scan cycle throughout the store. [0083] the system identifies RF signals as originating from RFID tags arranged on or in product units carried in shopping carts, carried in shopping baskets, or discarded onto the floor. For example, the system can extract—from the planogram—2D plan areas or 3D volumes of inventory structures throughout the store. In this example, during execution of a scan routine along an inventory structure of interest, the robotic system can: collect RFID values from nearby RFID tags in Block S120; implement methods and techniques described above to determine 2D or 3D locations of RFID tags within the store based on these RFID values and related metadata; and flag RFID values located outside of known plan areas or volumes of inventory structures in the store. The system can then remove unique product units corresponding to these flagged RFID values from a list of product units stocked on an adjacent inventory structure such that this list of product units represents a substantially authentic summary of the stock state of the inventory structure and excludes product units currently occupying shoppers' carts or baskets or product units discarded onto a floor of the store.)
As per Claim 5, Tiwari teaches: The system of Claim 1,
wherein the one or more devices associated with the retailer comprise one or more of: one or more cameras, one or more sensors and one or more devices capable of transmitting location data. (in at least [0024] The robotic system can also include cameras mounted statically to the mast, such as two vertically offset cameras on a left side of the mast and two vertically offset cameras on the right side of the mast, as shown in FIG. 3. The robotic system can additionally or alternatively include articulable cameras, such as: one camera on the left side of the mast and supported by a first vertical scanning actuator; and one camera on the right side of the mast and supported by a second vertical scanning actuator. Furthermore, each camera can include a zoom lens or a wide-angle lens, etc.)
As per Claim 6, Tiwari teaches: The system of Claim 1, wherein the computer is further configured to:
update the determined task priority for each task in real time based on one or more changing conditions at the retailer. (in at least [0113] generate a stock correction task list to correct improperly-stocked slots. In this implementation, the system can generate a prioritized list of tasks to move misplaced products, to restock empty or improperly-stocked slots, etc. and then serve this task list to an associate (e.g., employee) of the store via a native stocking application executing on a mobile computing device (e.g., a tablet, a smartphone) carried by the associate. In this implementation, the computer system can implement methods and techniques described in U.S. patent application Ser. No. 15/347,689 to prioritize this list of tasks to correct improperly-stocked slots throughout the store.)
As per Claim 7, Tiwari teaches: The system of Claim 1,
wherein the determined task priority is based, at least in part, on a lowest-cost task sequence for the tasks. (in at least [0067] the robotic system can flag the set of waypoints for a second set of scan routines if the target quantity of products assigned to the inventory structure by the planogram exceeds the actual quantity of unique RFID values collected along the set of waypoints by more than a preset threshold, such as: by a static difference of 5% for all inventory structures in the store; by 5% during low-traffic hours and by 15% during high-traffic hours; by a difference threshold proportional to a value (e.g., composite of margin and sale rate) of products assigned to the inventory structure (e.g., between 2% for high-value products and up to 15% for low-value products); etc. For example, the computer system can repeat a scan cycle at each waypoint in the set at an increased interrogation signal output power level in Block S150. In another example, the robotic system can: adjust a target orientation of the robotic system at each waypoint (e.g., by 15° to shift the plane of propagation of the interrogation signal out of the plane of RFID tags not previously detected); increase the density of waypoints along (or around) the inventory structure (e.g., to achieve greater overlap of interrogation signals at the inventory structure); and/or shift these waypoints further away from the inventory structure (e.g., to enable the interrogation signal to reach product units on shelves at the top and/or bottom of inventory structure). By thus implementing different power, distance, and/or orientation parameters when executing additional scan routines at waypoints along this inventory structure, the system can increase likelihood that any RFID tags—on product units stocked on the inventory structure—that were obscured from interrogation signals broadcast by the robotic system during the previous scan routine are excited during this next scan routine and thus return RFID values back to the robotic system, thereby increasing accuracy of inventory data collected by the robotic system for this inventory structure during the current scan cycle. [0109] For a particular product unit—in this first list of product units—the computer system can detect a price difference between a price assigned to the particular product unit and a price value indicated by an adjacent price tag in the set of price tags; and then generate a stock correction prompt to correct the adjacent price tag on the first inventory structure in response to detecting this price difference. [0104] the system can transmit the notification to the associate in real-time, such as if the first product is a high-value product determined to be empty during a high-traffic period at the store. Alternatively, the system can delay transmission of the notification to the associate until the robotic system completes a scan of the store, a full stock state of the store is determined from these scan data, and a list of restocking prompts is ordered according to values of these under- or mis-stocked products. [0120] By comparing this list of SKUs and their actual quantities to the planogram (or textual or numerical representation of the planogram), the system can also populate the digital report with indicators of slots or other inventory structures that are empty, under-stocked, over-stocked, or improperly-stocked with the incorrect product, etc. For example, the system can generate a textual list of the stock state of each slot in the store, such as ordered with empty slots followed by under-stocked slots followed by improperly-stocked slots, etc. and ordered by highest-value SKU to lowest-value SKU. Alternatively, the system can generate a 2D heat map of the stock states of slots throughout the store, such as indicating regions in which highest-value slots are empty in red, lower-value empty slots and overstocked-slots in a cooler color, and properly-stocked slots in even cooler colors.)
As per Claim 8-14 for a computer-implemented method (see at least Tiwari [0122]), respectively, substantially recite the subject matter of Claim 1-7 and are rejected based on the same reasoning and rationale.
As per Claim 15-20 for a non-transitory computer-readable storage medium (see at least Tiwari [0122]), respectively, substantially recite the subject matter of Claim 1-6 and are rejected based on the same reasoning and rationale.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PO HAN (Max) LEE whose telephone number is (571) 272-3821. The examiner can normally be reached on Monday - Thursday, 9 AM-6:30 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Rutao Wu can be reached on (571) 272-6045. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/PO HAN LEE/Primary Examiner, Art Unit 3623
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