Computer technologies for enabling smart shipping using QR codes

Provided herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for using innovative computer technologies to enable smart shipping of items sold from sellers to buyers. An embodiment performs operations that include: predicting shipping information for shipping an item associated with a first user to a destination designated by a second user, including determining a category of the item to identify similar items from a historical database; storing at least some of the shipping information in databases of an Internet site; and generating a machine readable code associated with the item or the shipping information, wherein a shipper uses information from scanning the code to access and retrieve the shipping information from the databases of the site using an application programming interface (API) of the site, and wherein the shipper uses the retrieved shipping information to ship the item to the destination.

BACKGROUND

Field

This disclosure is generally directed to computer technologies for enabling smart and intelligent shipping of items sold from sellers (sometimes called first users herein) to buyers (sometimes called second users herein).

Background

There are many websites and apps that allow users to sell new or used products. Often, though, shipping from the seller to the buyer can be a challenge. For example, a seller may not have a box that is big enough or strong enough to ship the item that he sold. Or, the seller may not know how to package the item to prevent damage while being shipped. Also, in situations where the website collects shipping fees from the buyer, the website could lose money if the shipping fees were underestimated due to inaccurate information provided by the seller (such as the dimensions, weight, brand, model, description, etc., of the item sold).

SUMMARY

Provided herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for using innovative computer technologies to enable smart shipping of items sold from sellers to buyers.

An embodiment performs operations that include: predicting shipping information for shipping an item associated with a first user to a destination designated by a second user, including determining a category of the item to identify similar items from a historical database; storing at least some of the shipping information in databases of an Internet site; and generating a machine readable code associated with the item or the shipping information, wherein a shipper uses information from scanning the code to access and retrieve the shipping information from the databases of the site using an application programming interface (API) of the site, and wherein the shipper uses the retrieved shipping information to ship the item to the destination.

In an embodiment, predicting the shipping information includes: accessing actual shipping information from past listings in the historical database corresponding to the similar items; and using at least some of the actual shipping information as the predicted shipping information for shipping the item to the destination.

The operations may also include: storing other of the shipping information in databases of the shipper, wherein the shipper uses the code to retrieve such other of the shipping information from the shipper databases, wherein such other shipping information is not available to the first user to thereby enable an anonymous transaction.

In an embodiment, the shipper provides feedback to the site pertaining to actual shipping of the item to the destination, wherein the feedback includes actual weight and dimensions of the item, an actual box size, and whether the item was hazardous. Such feedback may be stored in the historical database in a past listing associated with the item.

In an embodiment, multiple items associated with the first seller may be shipped to multiple second sellers. In this case, the operations include: predicting shipping information for shipping the multiple items to destinations indicated by the second sellers, including grouping items to a same second user, or to second users proximate to each other; storing at least some of the shipping information of the multiple items in the databases of the site; and generating a single machine readable code associated with all of the multiple items, wherein the shipper uses information from scanning the single code to access and retrieve the shipping information of the multiple items from the databases of the site, and wherein the shipper uses the retrieved shipping information of the multiple items to ship the multiple items to the destinations of the second sellers via a local shipping office for at least some of the grouped items.

In another embodiment, the operations may include: receiving notification that the second user wishes to return the item to the first user; accessing actual shipping information for shipping the item to a destination of the first user; storing at least some of the actual shipping information in the databases of the site; and generating a second machine readable code associated with the item or the actual shipping information, wherein the shipper uses information from scanning the second code to access and retrieve the actual shipping information from the databases of the site, and wherein the shipper uses the retrieved actual shipping information to ship the item to the destination of the first user.

Further features and advantages of the embodiments disclosed herein, as well as the structure and operation of various embodiments, are described in details below with reference to the accompanying drawings. It is noted that this disclosure is not limited to the specific embodiments described herein. Such embodiments are presented herein for illustrative purposes only. Additional embodiments will be apparent to a person skilled in the relevant art based on the teachings contained herein.

DETAILED DESCRIPTION

Provided herein are system, apparatus, device, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for facilitating shipping of products sold via an Internet site using an optical, machine-readable code. In some embodiments, the code may be a bar code or QR (quick response) code, or any other type of optical, machine-readable code. An example QR code202is shown inFIG. 2.

FIG. 1illustrates a computing environment102that includes an Internet site106. In some embodiments, site106enables sellers104to list and sell new or used items110to buyers112. Examples of site106include MERCARI.COM, AMAZON.COM, EBAY.COM, CRAIGSLIST.COM, POSHMARK.COM, etc., to name just some examples.

In the example ofFIG. 1, a seller104has created a listing160that is stored in a listing database142of site106, wherein the listing160offers an item110for sale. The listing160may include information144about the item110, such as make, model, brand, year, description, weight, dimensions, etc. Some of this information144may not be accurate as to the item110. For example, the weight and dimensions in the information144may not accurately describe the item110. The accuracy of the information144may depend on the knowledge and experience level of the seller104as to the item110and the creation of listings160.

The listing160may also include information146pertinent to shipping the item110; this shipping information146is further discussed below.

The listing database142may include any number of listings160of items110being offered for sale by their respective sellers104.

The site106includes a historical database150that includes listings160that have sold in the past. The site106also includes an application programming interface (API)148for enabling other entities (such as but not limited to shipper114) to access data contained in, for example, listing database142, and/or other databases of the site106. An example of API148is shown inFIG. 3, which is further described below.

The site106includes predictive modules152and a shipping module156for enabling the smart shipping of items110from sellers104to buyers112. The predictive modules152and/or shipping module156may include artificial intelligence and machine learning technologies for performing their functions. The predictive modules152and shipping module156are further described below.

Assume a buyer112views the listing160while browsing the site106, and decides to purchase the item110. As will be appreciated, the seller104must now ship the item110to the buyer112. But shipping can be a challenge for many people, especially people who do not have printers to print a shipping label, people who do not have shipping materials to pack the item110(especially if the item110is large or odd sized), and people who are not experienced with calculating and purchasing postage to ship the item110. These shipping challenges may deter people from listing their items110for sale on the site106. Accordingly, this disclosure provides embodiments for using innovative computer technologies to facilitate the smart and intelligent shipping of items110sold via the site106using an optical, machine readable code, such as but not limited to a QR code.

FIG. 4illustrates a flowchart of a method402for using innovative computer technologies to enable smart shipping of items sold from sellers to buyers, according to some embodiments. Method402can be performed by processing logic that can comprise hardware (e.g., circuitry, dedicated logic, programmable logic, microcode, etc.), software (e.g., instructions executing on a processing device), or a combination thereof. It is to be appreciated that not all steps may be needed to perform the disclosure provided herein. Further, some of the steps may be performed simultaneously, or in a different order than shown inFIG. 4, as will be understood by a person of ordinary skill in the art.

Method402shall be described with reference toFIGS. 1-3. However, method402is not limited to those example embodiments.

In404, as noted above, a given seller104creates a listing160on the site106to sell item110. The listing160is stored in listing database142, and is available for public viewing to users visiting the site106.

Also in404, assume a given buyer112views the listing160and buys the offered item110. Thereafter, the buyer112pays for the item110.

In406, the shipping module156in the site106generates (that is, predicts) shipping information pertinent to shipping the item110to the buyer112(that is, to a destination indicated by the buyer112). Such shipping information may include: (1) contact information of the buyer112, such as the name, address, phone number, etc., of the buyer112; (2) information particular to the item110, such as the size of the item110, the weight of the item110, whether the item110constitutes liquid or hazardous materials, whether the item110is subject to export regulations, etc.; (3) whether the buyer112selected local pickup rather than shipping; and/or (4) information particular to the sale of the item110, such as the delivery date, shipping speed, weekend delivery, signature required, etc., selected by the buyer112as part of her purchase of the item110.

It is noted that some of this information may be included as item information144in the listing160(such as dimensions and weight of the item110). But, as noted above, the seller104may have incorrectly entered this information when creating the listing160. Accordingly, in some embodiments, the shipping module156does not use this item information144for shipping the item110to the buyer112. Rather, in406, the shipping module156uses the predictive module152to generate (that is, predict) shipping information pertinent to shipping the item110to the buyer112.

In some embodiments, with regard to the foregoing, the predictive module152in the site106may use artificial intelligence and machine learning to generate estimates of properties of the item110that are pertinent to shipping the item110, such as the dimensions and weight of the item, whether the item110is fragile or constitutes hazardous materials, the size of the box needed to ship the item110, the strength of the box needed to ship the item110, the type of shipping materials needed to pack the item110in the shipping box, the shipping cost, etc.

The predictive module152may generate these estimates by first analyzing the listing160to identify the item110. For example, the predictive module152may analyze the listing160to determine the category of the item110(it is noted that the category of the item110may have been determined prior to406by the predictive module152or other modules in the site106; in this case, the predictive module156may retrieve the category of the item110from the listing information144in the listing160). Example categories include smartphone, APPLE MACBOOK, garden tool, men's belt, motorcycle, office desk, woman's purse, comic books, etc. Example embodiments for automatically identifying the category of items110is provided in U.S. patent application Ser. No. 16/288,379 titled “Probabilistic Item Matching And Searching,” filed Feb. 28, 2019, which is herein incorporated by reference in its entirety, and any of those embodiments may be used herein for automatically determining the category of any given item110(whether performed in406or prior to406).

Also in406, the predictive module152may analyze the listing160to determine other identifying properties of the item110, such as the make, model, brand, year of production, etc., of the item110.

Then, the predictive module152may use this information (that is, category, make, model, brand, year of production, etc., of the item110) to search the historical database150to identify and accessed past listings162where the same or similar items were sold. In some embodiments, such identified past listings162include actual shipping-related information164(as opposed to predicted or estimated shipping information), such as the actual dimensions, weight, box size and type, whether liquid or hazardous, etc., of actually shipping the items associated with the past listings162.

Such actual shipping information164from the identified past listings162may be pertinent to the shipping of the item110to the buyer112, since the identified past listings162relate to items that are the same or similar to the item110. Accordingly, the shipping module156stores the actual shipping information164in the shipping information146of the listing160(or in some other database record in the site106that is associated with the item110and/or listing160).

In408, the shipping module156identifies a shipper114that was selected by the seller104, or that is located proximate to the location of the shipper114, or that has a partnership relationship with the site106. For example, the shipper114could be UPS, FEDERAL EXPRESS, US MAIL, etc. The shipping module156then accesses databases154of the identified shipper114, and stores therein information pertinent to the shipping of the item110to the buyer112. Such information may include the name of the buyer112, the telephone number of the buyer112, and the address of the buyer112. In some embodiments, such information of the buyer112is not available to the seller104. Accordingly, embodiments of this disclosure operate to protect such contact information of the buyer112from being disclosed to the seller104, to thereby enable anonymous transactions between sellers104and buyers112.

In410, the shipping module156generates an optical, machine readable code, such as but not limited to a QR code130(an example QR code is shown inFIG. 2). The QR code130is generated and configured to indicate, designate, include, correlate to, link to, associate with, or otherwise identify the item110that was purchased by the buyer112, the listing160associated with the item110, and/or the shipping information pertaining to the item110that was stored in the shipper databases154in408. In some embodiments, the QR code130does not include contact information of either the buyer112or the seller104, or other information regarding the item110other than specified in the previous sentence, to thereby further enable anonymous transactions between sellers104and buyers112.

In some embodiments, the QR code130may be generated by functionality within the shipper114. In this case, the shipping module156may interact with the shipper114(via an API provided by the shipper114) to obtain the QR code130from the shipper114.

Also in410, the shipping module156provides the QR code130to the seller104. For example, the shipping module156may include the QR code130as part of an email to the seller104, or the QR code130may be accessible to the seller104by accessing his account on the site106. In a similar manner, the shipping module156may inform the seller104which shipper114to use to ship the item110.

In412, the seller104takes the item110to the shipper114. For example, the shipper114could be any UPS store, assuming UPS was identified to the seller104in410.

In414, the seller104provides the QR code130to the shipping service114. This may be done by showing the shipping service114a printout of the QR code130, or by showing the seller104's phone or tablet (where the email from the site106or the seller104's account on the site106is displayed).

The shipping service114reads the QR code130using a scanner116or similar device. As noted above, the QR code130indicates, designates, includes, correlates to, links to, associates with, or otherwise identifies the item110that was purchased by the buyer112, the listing160associated with the item110, and/or the shipping information pertaining to the item110that was stored in the shipper databases154in408. Accordingly, in414, the shipping service114uses information (called the SiteUniqueID; seeFIG. 3) obtained from scanning the QR code130to access and retrieve shipping information pertaining to the item110from its shipper databases154. Also in414, the shipping service114uses this information from the QR code130to access and retrieve the shipping information146from databases in the site106(such as from the listing160in the listing database142).

According to some embodiments, the shipping service114accesses databases in the site106using the site106's application programming interface (API)148.FIG. 3illustrates an example API148. The API148includes a request302and a response304.

Thus, in414, the shipping service114sends a request302via the Internet to the site106to access and obtain the shipping information146. The request302includes a SiteUniqueID that was obtained from scanning the QR code130, and that is unique for the item110, as discussed above. The request302also includes a ShipperUniqueID, which is the shipper114's unique transaction identification (ID) for the item110.

Further in414, in response to receiving the request302from the shipper114, the site106generates and transmits to the shipper (via the Internet) a response304. The response304includes:

ShipperUniqueID: This is the same from the request302.

SiteUniqueID: This is the same from the request302.

successFlag: This is a Boolean flag that indicates whether the request302is valid. successFlag may be false if there was an error in scanning the QR code130, if the purchase of the item110by the buyer112was cancelled by the buyer112, or if proper payment of the item110was not received, to name just some examples. If successFlag is false, the shipper114will not ship the item110, and method402ends. If successFlag is true, method402continues with416or418, as discussed below.

boxCategories: This indicates the size of the box that the shipper114should use to ship the item110to the buyer112. Example values include small, medium, large, extra large, extra extra large, etc. This shipping information was predicted by the predictive module152in406.

serviceLevel: This indicates the service level for shipping the item110. Example values include basic, standard, expedited, fragile, hazardous, liquid. This field may include one or more of these values. Some of these values may have been selected by the buyer112(such as whether to use basic, standard or expedited shipping). Other values (such as whether fragile or hazardous) may have been predicted by the predictive module152in406.

itemExpectedWeight: This indicates the expected weight of the item110, as predicted by the predictive module152in406.

itemID: This is the site106's identification (ID) for the item110.

itemName: This is a description of the item110, taken from the item information144in the listing160.

The response304may include additional information. For example, the response304may indicate whether the buyer112has elected local pickup (rather than shipping) in order to save shipping costs.

In416, the shipper114packs and ships the item110to the buyer112according to the information accessed and obtained in414.

In418, the shipper114stores the item110for local pickup by the buyer112. The shipper114may contact the buyer112(via email or text, for example, where such contact information of the buyer112was obtained in414) to inform the buyer112that the item110is available for pickup.

In420, the shipper114provides feedback to the site106regarding the actual shipment of the item110to the buyer112(assuming416rather than418was performed). Such feedback may include: the actual box size used; the type of box; the actual weight and dimensions of the item110; whether the item110was fragile or hazardous; the actual shipping cost, etc. The shipper114may provide such feedback via the API148, in a message similar in format to the response304.

In422, the site106stores the listing160in the historical database150, such that the listing160becomes a new past listings162. The site106stores the received feedback as actual shipping information164in this new past listing162. In this way, shipping predictions made by the predictive module152in406improve over time. The site106may also bill or credit the seller104for deficient or excess shipping costs, respectively, depending on the actual shipping costs provided by the shipper114in420.

FIG. 5illustrates a flowchart of a method502for using innovative computer technologies to enable smart shipping of items sold from sellers to buyers, wherein a given seller has sold and must now ship multiple items, according to some embodiments. Method502can be performed by processing logic that can comprise hardware (e.g., circuitry, dedicated logic, programmable logic, microcode, etc.), software (e.g., instructions executing on a processing device), or a combination thereof. It is to be appreciated that not all steps may be needed to perform the disclosure provided herein. Further, some of the steps may be performed simultaneously, or in a different order than shown inFIG. 5, as will be understood by a person of ordinary skill in the art.

Method502shall be described with reference toFIGS. 1-3. However, method502is not limited to those example embodiments.

As indicated by504, assume the seller104is selling multiple items110via multiple listings160. Also assume, as indicated by506, that multiple ones of these items110are purchased by one or more buyers112.

Conventionally, each of these sold items110are treated as separate transactions, such that the seller104is required to manage and keep track of the shipments of the items110to buyer(s)112. But according to some embodiments of this disclosure, the shipping module156in the site106treats the sold items110as a single transaction, and issues to the seller104a single QR code130that covers shipments of all the sold items110. Also, the shipping module156intelligently ships the items110in the least number of boxes possible (even if there are multiple buyers112) to thereby reduce shipping costs.

Accordingly, in508, the shipping module156analyzes the sold items110and the buyers112, in order to group items110together so as to reduce packing and shipping costs. For example, items110purchased by the same buyer112, or buyers112who are located closed to each other, are grouped together. As a result of508, the sold items110are separated into one or more groups.

In510, the shipping module156generates (that is, predicts) shipping information pertinent to shipping the items110to the buyers112. Specifically, the predictive module152may generate estimates of properties of the item110that are pertinent to shipping the items110. The operation of510is similar to the operation of406inFIG. 4.

In512(similar to408), the shipping module156accesses databases154of the shipper114, and stores therein shipping information pertinent to the shipping of the items110to the buyers112. In the case of a grouping of items110that have buyers112who are physically close to each other, the shipping information may specify a location proximate to the buyers112(such as a local UPS store, in the case where the shipper is UPS). The items110in this group would be shipped to this local UPS store, and from there the items can be separated and then individually shipped to the respective buyers112, or held for local pickup.

In514(similar to410), the shipping module156generates a single optical, machine readable code, such as but not limited to QR code130. The QR code130corresponds and applies to all the purchased items (from506). The shipping module156provides the QR code130to the seller104.

In518(similar to414), the seller104provides the QR code130to the shipping service114. The shipping service114reads the QR code130using a scanner116or similar device. Then, the shipping service114uses information (called the SiteUniqueID; seeFIG. 3) obtained from scanning the QR code130to access and retrieve shipping information pertaining to the items110from its shipper databases154. Also in518, the shipping service114uses the information from the QR code130to access and retrieve the shipping information146from databases in the site106for the items110.

As discussed above, the shipping service114sends a request302via the Internet to the site106to access and obtain the shipping information146for the items110.

Further in518, in response to receiving the request302from the shipper114, the site106generates and transmits to the shipper (via the Internet) one or more responses304. In some embodiments, the site106generates a response304for each grouping of items110(where some groupings may include a single item110). Or, the site106may generate a response304for each item110irrespective of groupings.

In520(similar to416), the shipper114packs and ships the items110according to the information retrieved in518. As noted above, items110in the same group may be packed and shipped together to a local shipper office for subsequent pickup or shipping to the respective buyers112(this is indicated by526).

In522, the shipper114sends feedback to the site106. The operation of522is similar to420.

In524(similar to422), the site106stores the listings160for the sold items110in the historical database150, such that the listings160become new past listings162. The site106stores the received feedback as actual shipping information164in these new past listings162. In this way, shipping predictions made by the predictive module152in510improve over time.

FIG. 6illustrates a flowchart for using innovative computer technologies to enable smart shipping of items returned from buyers to sellers, according to some embodiments. Method602can be performed by processing logic that can comprise hardware (e.g., circuitry, dedicated logic, programmable logic, microcode, etc.), software (e.g., instructions executing on a processing device), or a combination thereof. It is to be appreciated that not all steps may be needed to perform the disclosure provided herein. Further, some of the steps may be performed simultaneously, or in a different order than shown inFIG. 6, as will be understood by a person of ordinary skill in the art.

Method602shall be described with reference toFIGS. 1-3. However, method602is not limited to those example embodiments.

As indicated by604, assume the buyer112is not satisfied with the item110(that was purchased via method402or502, or via some other method). Also assume the buyer112contacts the site106to return the item110to the seller104(as indicated by606).

In608, the site106stores shipping information to ship the item110from the buyer112to the seller104in the shipper databases154. The operation of608is similar to408and512.

In610, the shipping module156generates an optical, machine readable code, such as but not limited to QR code130. The QR code130corresponds and applies to the item110that the buyer112wishes to return. The shipping module156provides the QR code130to the buyer112. The operation of610is similar to410and514.

In612, the buyer112takes the item110to the shipper114. The operation of612is similar to412and516.

In614, the buyer112provides the QR code130to the shipping service114. The shipping service114reads the QR code130using a scanner116or similar device. Then, the shipping service114uses information (called the SiteUniqueID; seeFIG. 3) obtained from the QR code130to access and retrieve shipping information pertaining to the item110from its shipper databases154. Also in614, the shipping service114uses the information from the QR code130to access and retrieve the shipping information146from databases in the site106for the items110(such as from the past listings database162). The operation of614is similar to414and518. But in this case, what is retrieved by the shipper114is the actual shipping information164pertaining to actual shipment of the item110, rather than predicted or estimated shipping information146. Such actual shipping information164was provided to the site106as feedback in420and522.

In616, the shipper114validates the transaction for fraud prevention by using the information retrieved in614from the site106's databases. For example, the shipper114may confirm that the weight of the item being returned matches the weight of the original shipment of the item110to the buyer112. If the weight of the returned item is less than the original weight, then that may indicate that the buyer112is not returning the proper item, or is not including all the parts (for example, the buyer112may have neglected to include the power cord in the case where the item110is a notebook computer). If a discrepancy is detected, the shipper114may decline to ship the item110. In this case, the buyer112can try to return the item at a later time (after gathering together the proper item110to return), or contact the site106to resolve the issue.

In618(similar to416and520), assuming no discrepancy was detected in616, the shipper114packs and ships the item110according to the information retrieved in614.

Example Computer System

Various embodiments and/or components therein can be implemented, for example, using one or more computer systems, such as computer system700shown inFIG. 7. Computer system700can be any computer or computing device capable of performing the functions described herein. For example, one or more computer systems700or portions thereof can be used to implement any embodiments discussed herein, and/or any combination or sub-combination thereof.

Computer system700includes one or more processors (also called central processing units, or CPUs), such as a processor704. Processor704is connected to a communication infrastructure or bus706.

One or more processors704can each be a graphics processing unit (GPU). In some embodiments, a GPU is a processor that is a specialized electronic circuit designed to process mathematically intensive applications. The GPU can have a parallel structure that is efficient for parallel processing of large blocks of data, such as mathematically intensive data common to computer graphics applications, images, videos, etc.

Computer system700also includes a main or primary memory708, such as random access memory (RAM). Main memory708can include one or more levels of cache. Main memory708has stored therein control logic (i.e., computer software) and/or data.

Computer system700can also include one or more secondary storage devices or memory710. Secondary memory710can include, for example, a hard disk drive712and/or a removable storage device or drive714. Removable storage drive714can be a floppy disk drive, a magnetic tape drive, a compact disk drive, an optical storage device, tape backup device, and/or any other storage device/drive.

Removable storage drive714can interact with a removable storage unit718. Removable storage unit718includes a computer usable or readable storage device having stored thereon computer software (control logic) and/or data. Removable storage unit718can be a floppy disk, magnetic tape, compact disk, DVD, optical storage disk, and/any other computer data storage device. Removable storage drive714reads from and/or writes to removable storage unit718in a well-known manner.

According to an exemplary embodiment, secondary memory710can include other means, instrumentalities or other approaches for allowing computer programs and/or other instructions and/or data to be accessed by computer system700. Such means, instrumentalities or other approaches can include, for example, a removable storage unit722and an interface720. Examples of the removable storage unit722and the interface720can include a program cartridge and cartridge interface (such as that found in video game devices), a removable memory chip (such as an EPROM or PROM) and associated socket, a memory stick and USB port, a memory card and associated memory card slot, and/or any other removable storage unit and associated interface.

Computer system700can further include a communication or network interface724. Communication interface724enables computer system700to communicate and interact with any combination of remote devices, remote networks, remote entities, etc. (individually and collectively referenced by reference number728). For example, communication interface724can allow computer system700to communicate with remote devices728over communications path726, which can be wired and/or wireless, and which can include any combination of LANs, WANs, the Internet, etc. Control logic and/or data can be transmitted to and from computer system700via communication path726.

In some embodiments, a non-transitory, tangible apparatus or article of manufacture comprising a tangible computer useable or readable medium having control logic (software) stored thereon is also referred to herein as a computer program product or program storage device. This includes, but is not limited to, computer system700, main memory708, secondary memory710, and removable storage units718and722, as well as tangible articles of manufacture embodying any combination of the foregoing. Such control logic, when executed by one or more data processing devices (such as computer system700), causes such data processing devices to operate as described herein.

CONCLUSION