Examples relate to a computer-implemented method or system including a processor that can perform certain operations. The operations can include obtaining inputs comprising dockout windows for routes from a depot, capacity information for the depot, and dockout preferences. The operations also can include determining respective assignment penalties associated with respective assignments for feasible combinations of the routes and time periods within the dockout windows for the routes. The operations additionally can include determining a solution set of the respective assignments that minimize a total penalty. The operations further can include reassigning at least a portion of dockout times in the solution set to spread out the portion of the dockout times at the depot based on the dockout preferences. The operations additionally can include outputting the dockout times, as reassigned, for the routes. Other embodiments are described.
Indoor bicycle trainers; Weighted vests for physical training purposes; Weight lifting equipment, namely, exercise bars, loading pins, weight benches, sleds for weight training, weight plate collars, weights for exercise, weight lifting belts, waterbags used for weight training, plyometric boxes, medicine balls; Pull up bars; Doorway pull-up bars; Storage racks for physical fitness equipment, namely, dumbbells, kettle bells, exercise weights; Physical fitness equipment, namely, exercise kits comprising of a fitness bar and resistance bands for pilates; Resistance bands for fitness purposes; Accessory attachments for manually-operated exercise equipment being resistance bands for increasing muscle resistance; Push-up handles; Rotating push-up handles; Chalk in liquid, solid or gel form for improving hand grip in sports; Slant boards for stretching for fitness purposes
36 - Financial, insurance and real estate services
37 - Construction and mining; installation and repair services
39 - Transport, packaging, storage and travel services
40 - Treatment of materials; recycling, air and water treatment,
42 - Scientific, technological and industrial services, research and design
43 - Food and drink services, temporary accommodation
44 - Medical, veterinary, hygienic and cosmetic services; agriculture, horticulture and forestry services
Goods & Services
Advertising; business management; business administration; office functions; electronic commerce services, namely, providing information about products via telecommunication networks; online advertising, marketing and promotion services for others; providing online advertising for others; providing consumer product information via the Internet or other communications networks; promoting the sale of the goods and services of others through customer loyalty and incentive programs for retail customers; computerized on-line ordering services for electrical and electronic goods, white goods, computers, computer software, telecommunications apparatus, audio and video equipment, household appliances, furniture, home furnishings, jewellery, clothing, footwear, bags, stationery, books, health and beauty products, toiletries, pharmaceutical preparations, cleaning preparations, garden products, DIY products, building materials, hand tools, pet products, office supplies, household goods, kitchenware, textiles, toys, sporting goods, foodstuffs, beverages, tobacco products, and automotive goods; computerized online ordering for electrical and electronic goods, white goods, computers, computer software, telecommunications apparatus, audio and video equipment, household appliances, furniture, home furnishings, jewellery, clothing, footwear, bags, stationery, books, health and beauty products, toiletries, pharmaceutical preparations, cleaning preparations, garden products, DIY products, building materials, hand tools, pet products, office supplies, household goods, kitchenware, textiles, toys, sporting goods, foodstuffs, beverages, tobacco products, and automotive goods; computerized online ordering service for electrical and electronic goods, white goods, computers, computer software, telecommunications apparatus, audio and video equipment, household appliances, furniture, home furnishings, jewellery, clothing, footwear, bags, stationery, books, health and beauty products, toiletries, pharmaceutical preparations, cleaning preparations, garden products, DIY products, building materials, hand tools, pet products, office supplies, household goods, kitchenware, textiles, toys, sporting goods, foodstuffs, beverages, tobacco products, and automotive goods; providing customer support services for electronic commerce sales transactions; third party order fulfilment services; supply chain management services; administration of frequent flyer programs; administration of consumer loyalty programs; administrative processing of purchase orders; advertising agency services; publicity agency services; rental of advertising space; advertising by mail order; rental of advertising time on communication media; production of advertising films; appointment scheduling services [office functions]; appointment reminder services [office functions]; auctioneering; bill-posting; outdoor advertising; rental of billboards [advertising boards]; book-keeping; accounting; business management assistance; business inquiries; business auditing; business management and organization consultancy; business management consultancy; business efficiency expert services; business appraisals; business investigations; business organization consultancy; business research; advisory services for business management; professional business consultancy; business information; business management of hotels; business management of performing artists; business management of sports people; business management for freelance service providers; business project management services for construction projects; providing business information via a web site; business management of reimbursement programmes for others; business management of reimbursement programs for others; commercial information agency services; commercial or industrial management assistance; commercial information and advice for consumers [consumer advice shop]; commercial administration of the licensing of the goods and services of others; provision of commercial and business contact information; commercial intermediation services; compilation of information into computer databases; compilation of statistics; computerized file management; cost price analysis; data search in computer files for others; demonstration of goods; design of advertising materials; direct mail advertising; dissemination of advertising matter; distribution of samples; document reproduction; drawing up of statements of accounts; economic forecasting; employment agency services; import-export agency services; invoicing; layout services for advertising purposes; market studies; marketing research; marketing; modelling for advertising or sales promotion; negotiation and conclusion of commercial transactions for third parties; news clipping services; arranging newspaper subscriptions for others; office machines and equipment rental; on-line advertising on a computer network; provision of an on-line marketplace for buyers and sellers of goods and services; opinion polling; organization of exhibitions for commercial or advertising purposes; organization of trade fairs for commercial or advertising purposes; organization of fashion shows for promotional purposes; outsourced administrative management for companies; outsourcing services [business assistance]; pay per click advertising; payroll preparation; payroll processing services; accounting services; tax advisory services; operation of telephone call centers; personnel management consultancy; personnel recruitment; photocopying services; rental of photocopying machines; presentation of goods on communication media, for retail purposes; price comparison services; procurement services for others [purchasing goods and services for other businesses]; psychological testing for the selection of personnel; public relations; publication of publicity texts; publicity material rental; radio advertising; relocation services for businesses; sales promotion for others; rental of sales stands; scriptwriting for advertising purposes; search engine optimization for sales promotion; search engine optimisation for sales promotion; secretarial services; shop window dressing; shorthand; sponsorship search; arranging subscriptions to telecommunication services for others; systemization of information into computer databases; tax preparation; tax filing services; telemarketing services; telephone answering for unavailable subscribers; television advertising; transcription of communications [office functions]; typing; updating of advertising material; updating and maintenance of data in computer databases; rental of vending machines; web site traffic optimization; web site traffic optimisation; web indexing for commercial or advertising purposes; word processing; writing of publicity texts; writing of curriculum vitae for others; writing of résumés for others; Promotion services, dissemination of advertising and promotional materials, demonstration of goods, direct mail advertising, document reproduction, market research, marketing, distribution of samples, shop window dressing, organisation and management of promotional and incentive schemes, information, advice and business assistance, all relating to the aforesaid services, export and import agencies, information storage and retrieval in the field of retail and wholesale merchandising, inventory and shelf arrangements, inventory control, travel management, business management planning and supervision, merchandise packaging design, product merchandising, promoting the goods and services of others by arranging for sponsors to affiliate their goods and services with entertainment services on site; operating online marketplaces for sellers and buyers of goods and/or services; Retail store services connected with the sale of electrical and electronic goods, white goods, computers, computer software, telecommunications apparatus, audio and video equipment, household appliances, furniture, home furnishings, jewellery, clothing, footwear, bags, stationery, books, health and beauty products, toiletries, pharmaceutical preparations, cleaning preparations, garden products, DIY products, building materials, hand tools, pet products, office supplies, household goods, kitchenware, textiles, toys, sporting goods, foodstuffs, beverages, tobacco products, and automotive goods; online retail store services connected with the sale of electrical and electronic goods, white goods, computers, computer software, telecommunications apparatus, audio and video equipment, household appliances, furniture, home furnishings, jewellery, clothing, footwear, bags, stationery, books, health and beauty products, toiletries, pharmaceutical preparations, cleaning preparations, garden products, DIY products, building materials, hand tools, pet products, office supplies, household goods, kitchenware, textiles, toys, sporting goods, foodstuffs, beverages, tobacco products, and automotive goods; wholesale retail store services connected with the sale of electrical and electronic goods, white goods, computers, computer software, telecommunications apparatus, audio and video equipment, household appliances, furniture, home furnishings, jewellery, clothing, footwear, bags, stationery, books, health and beauty products, toiletries, pharmaceutical preparations, cleaning preparations, garden products, DIY products, building materials, hand tools, pet products, office supplies, household goods, kitchenware, textiles, toys, sporting goods, foodstuffs, beverages, tobacco products, and automotive goods; computerized online ordering service featuring the wholesale and retail distribution of electrical and electronic goods, white goods, computers, computer software, telecommunications apparatus, audio and video equipment, household appliances, furniture, home furnishings, jewellery, clothing, footwear, bags, stationery, books, health and beauty products, toiletries, pharmaceutical preparations, cleaning preparations, garden products, DIY products, building materials, hand tools, pet products, office supplies, household goods, kitchenware, textiles, toys, sporting goods, foodstuffs, beverages, tobacco products, and automotive goods; retail pharmacy services; retail optical store services; retail bakery shops; retail automobile parts and accessories stores; operation of telephone call centers for others. Insurance; financial affairs; monetary affairs; real estate affairs; Issuance and transaction processing services of electronic credit card, debit card, gift card, and pre-paid purchase cards for the purchase of goods and services in-store, and electronically via the internet, mobile phone, and smart phone; life assurance services; loan services; insurance services; mortgage broking; pension advisory and planning services; estate agency services; banking services; financial services for private individuals; financing services; investment services; savings accounts; personal equity plans; tax exempt special savings accounts; purchase of shares; sale of shares; stocks and bonds brokerage; security brokerage; charge card services; discount card services; automated payment services; ATM banking services; issue and redemption of tokens and vouchers; credit card services, debit card services; administration of employee benefit plans; charitable fund raising; insurance claims administration; providing college scholarships; leasing of real estate; Financial transaction services, namely, providing secure commercial transactions and payment options; financial services, namely, providing electronic credit card, debit card, gift card, and pre-paid purchase cards electronically via the internet, mobile phone, and smart phone; payment processing services, namely, credit card, gift card, debit card and pre-paid purchase card transaction processing services Electronic payment services for purchase of goods and services; electronic payment services for purchase of goods and services in-store, electronically or via the Internet, mobile phone or smart phone; electronic processing of credit transactions and electronic payments via a computer network, mobile phone or smart phone; advice and information in connection with all the aforesaid services; financial services, namely, issuance and transaction processing services of electronic credit card, debit card, gift card, and pre-paid purchase cards for the purchase of goods and services in-store, and electronically via the internet, mobile phone, and smart phone; payment processing services, namely, credit card, gift card, debit card and pre-paid purchase card transaction processing services. Tyre and battery repair services; vehicle repair services; automotive maintenance services, namely tire and battery installation laundering services; dry cleaning services; vehicle cleaning services; repair of cleaning machines; installation, maintenance and repair of computer hardware; electrical appliance installation and repair; shoe repair; automobile repair and maintenance; computer repair and maintenance; Automotive maintenance services, namely, tire and battery installation; vehicle maintenance consultation; automotive maintenance services; vehicle maintenance and repair; providing an Internet website that features information about automotive maintenance and repair services; Construction services; Installation and repair services. Transport; logistics management in the field of consumer goods; Warehouse storage; packaging, pick-up, and delivery of goods; transportation and shipping services; packaging and storage of goods; freight logistics management; travel arrangement; warehousing services; Warehousing and distribution of the wares of others; shipping of wares; air transport; armored-car transport; barge transport; boat transport; boat storage; booking of seats for travel; bottling services; car rental; car transport; car parking; car sharing services; carting; cash replenishment of automated teller machines; collection of recyclable goods [transport]; courier services [messages or merchandise]; arranging of cruises; delivery of goods; delivery of newspapers; newspaper delivery; delivery of goods by mail order; distribution of energy; providing driving directions for travel purposes; electricity distribution; escorting of travelers; ferry-boat transport; flower delivery; franking of mail; rental of freezers; freight [shipping of goods]; freight forwarding; freight brokerage [forwarding (Am.)]; freight brokerage; freighting; garage rental; gift wrapping; guarded transport of valuables; hauling; ice-breaking; launching of satellites for others; lighterage services; message delivery; rental of motor racing cars; motor coach rental; rental of navigational systems; packaging of goods; parcel delivery; parking place rental; passenger transport; physical storage of electronically stored data or documents; pleasure boat transport; porterage; refrigerator rental; frozen-food locker rental; removal services; ship brokerage; stevedoring; storage of goods; storage; warehousing; storage information; rental of storage containers; taxi transport; towing; traffic information; transport services for sightseeing tours; transport of travellers; transport and storage of waste; transport and storage of trash; transport brokerage; transport reservation; transportation information; transportation logistics; transporting furniture; arranging of travel tours; travel reservation; unloading cargo; vehicle breakdown towing services; vehicle rental; rental of vehicle roof racks; rental of warehouses; water supplying; water distribution; rental of wheelchairs; wrapping of goods; transportation and delivery of goods and merchandise; tracking services relating to transportation of goods and merchandise; reservation and arrangement services relating to the transportation of goods and merchandise; transportation, delivery and collection of goods; transportation, delivery and collection of parcels, post and groceries; transportation, delivery and collection of retail items purchased online; logistics services; advisory, consultancy and information services relating to all the aforesaid. Treatment of materials; Recycling of waste and trash; Air purification and treatment of water; Printing services; Food and drink preservation; digital photo printing services; photographic services; photographic processing services; three-dimensional printing services; services for the transfer of photographic prints; framing; collation, folding, stapling, perforating, cutting and binding of printed, copied and typewritten material; tailoring; silversmith services; treatment of food products; treatment of food; treatment of cakes; processing of cakes; printing a design onto rice paper services; cake decorating services; custom cake decorating services; photographic film development services; photofinishing services; alteration and retouching of photographic images via a global computer network; framing, glazing, mounting, canvas transfer, and other fixation and treatment for display purposes, namely, transferring to canvas of original and reproduced pictures, paintings, color prints, posters, fine art prints, limited edition prints, photographs, lithographs, cartoons, film cells, art etchings, drawings, wall decor, sculptures and other decorative art objects; consultation and providing information concerning art framing, mounting and other fixation and treatment for display purposes, materials, dimensions, matting, glazing and art printing; custom framing services offered via computer networks and global communications networks; computerized on-line custom art framing services, consulting and advisory services on choosing art framing materials, dimensions, matting and glass and custom framing of such works of art, namely, framed and unframed original and reproduced paintings, color prints, pictures, printed art reproductions, limited edition prints, photographs, pictorial prints, en6/7 Draft cartoons, color pictures, art prints, art etchings, drawings, and posters thereof; custom manufacture of announcements, invitations, greeting cards, stationery, calling cards, scrapbook albums, brag books, memory books, photo albums, photo books, and books containing photos or images; consultancy, advisory and information services for or in relation to any or all of the aforementioned services. Scientific and technological services and research and design relating thereto; industrial analysis and research services; design and development of computer hardware and software; Designing, creating, maintaining and hosting online electronic commerce websites for others; platform as a service (PAAS) featuring computer software platforms for use in operating online marketplaces featuring a wide variety of consumer goods; platform as a service (PAAS) featuring computer software platforms for use in browsing, viewing, comparing, and purchasing a wide variety of consumer goods from online marketplaces; hosting a searchable website featuring the goods and services of other vendors; calibration [measuring]; cartography services; clinical trials; cloud seeding; cloud computing; computer rental; computer programming; computer software design; rental of computer software; computer system analysis; computer system design; computer software consultancy; computer virus protection services; computer technology consultancy; computer security consultancy; construction drafting; consultancy in the design and development of computer hardware; consultancy in the field of energy-saving; conversion of data or documents from physical to electronic media; conversion of computer programs and data, other than physical conversion; cosmetic research; creating and maintaining web sites for others; creating and designing website-based indexes of information for others [information technology services]; data security consultancy; data encryption services; design of interior décor; interior design; digitization of documents [scanning]; dress designing; duplication of computer programs; electronic data storage; electronic monitoring of personally identifying information to detect identity theft via the internet; electronic monitoring of credit card activity to detect fraud via the internet; energy auditing; engineering; graphic arts design; handwriting analysis [graphology]; hosting computer sites [web sites]; industrial design; information technology [IT] consultancy; providing information on computer technology and programming via a web site; installation of computer software; internet security consultancy; land surveying; maintenance of computer software; mechanical research; meteorological information; monitoring of computer systems by remote access; monitoring of computer systems to detect breakdowns; monitoring of computer systems for detecting unauthorized access or data breach; off-site data backup; outsource service providers in the field of information technology; packaging design; physics [research]; quality control; quality evaluation of wool; recovery of computer data; research and development of new products for others; research in the field of environmental protection; scientific laboratory services; scientific research; providing search engines for the internet; server hosting; E-commerce services, namely, providing user authentication services using biometric hardware and software technology for e-commerce transactions; Application service provider (ASP) featuring e-commerce software for use as a payment gateway that authorizes processing of credit cards or direct payments for merchants; software as a service [SaaS]; designing, creating, maintaining and hosting online retail and electronic commerce websites for others; styling [industrial design]; surveying; technical research; conducting technical project studies; technical writing; technological consultancy; telecommunications technology consultancy; material testing; textile testing; unlocking of mobile phones; updating of computer software; urban planning; vehicle roadworthiness testing; water analysis; weather forecasting; rental of web servers; web site design consultancy; developing and hosting a server on a global computer network for the purpose of facilitating e-commerce via such a server; software-as-a-service. ervices for providing food and drink; temporary accommodation; restaurant services; cafe, cafeteria, catering services; food preparation; advice relating to food and drink; creche services; services for providing cakes, including decorated cakes and personalised cakes; consultancy, advisory and information services for or in relation to any or all of the aforementioned services. Medical services; hearing aid services; optometry services; veterinary services; medical centres, pharmacy advice, pharmacy services, all being provided through retail and/or wholesale environments, both physical and online; hygienic and beauty care for human beings or animals; agriculture, horticulture and forestry services; nutrition advice; medical centres; hairdressing services; beauty care services; optician services; pharmacy advice; pharmacy services; spectacles, eyeglass and contact lens fitting services; provision of restrooms, toilets, changing rooms and baby changing facilities for customers.
A device may receive a plurality of retrieval sets, first sampling parameters, and second sampling parameters that are based on offline sampling that uses multiple-metric efficacy values that are based on one or more efficacy metrics and one or more policy metrics. The plurality of retrieval sets may be from a plurality of clusters of a set of object embeddings representative of a plurality of objects. The device may select a retrieval set of the plurality of retrieval sets by performing online sampling using the first sampling parameters. The device may determine an object ranking in the retrieval set by performing online sampling using the second sampling parameters. The device may generate code or markup based on the object ranking in the retrieval set.
G06F 16/2457 - Query processing with adaptation to user needs
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
36 - Financial, insurance and real estate services
39 - Transport, packaging, storage and travel services
Goods & Services
(1) Retail and on-line retail grocery store services; Retail and on-line retail grocery store services featuring a wide variety of consumer goods of others; Retail and on-line retail grocery store services featuring pickup, in-store pickup and home delivery service; Retail services, namely, administration of a discount program for enabling participants to obtain discounts on shipping services through use of a discount membership program; Customer loyalty program services featuring rewards in the form of discounted shipping services and early access to retail discounts and offers; Customer loyalty program services featuring a membership for unlimited free shipping of consumer goods purchased from retailer; Customer loyalty program services featuring a membership for unlimited expedited shipping of consumer goods purchased from retailer; Mobile retail store services featuring a wide variety of consumer goods of others. Advertising; business management, organization and administration; office functions.
(2) Credit card transaction processing services provided via mobile applications and website; Financial, monetary and banking services; insurance services; real estate services.
(3) Transport and delivery of goods; Transport; packaging and storage of goods; travel arrangement.
36 - Financial, insurance and real estate services
39 - Transport, packaging, storage and travel services
Goods & Services
(1) Retail and on-line retail grocery store services; Retail and on-line retail grocery store services featuring a wide variety of consumer goods of others; Retail and on-line retail grocery store services featuring pickup, in-store pickup and home delivery service; Retail services, namely, administration of a discount program for enabling participants to obtain discounts on shipping services through use of a discount membership program; Customer loyalty program services featuring rewards in the form of discounted shipping services and early access to retail discounts and offers; Customer loyalty program services featuring a membership for unlimited free shipping of consumer goods purchased from retailer; Customer loyalty program services featuring a membership for unlimited expedited shipping of consumer goods purchased from retailer; Mobile retail store services featuring a wide variety of consumer goods of others; Advertising; business management, organization and administration; office functions.
(2) Credit card transaction processing services provided via mobile applications and website; Financial, monetary and banking services; insurance services; real estate services.
(3) Transport and delivery of goods; Transport; packaging and storage of goods; travel arrangement.
8.
Systems and Methods for Managing and Coordinating Wireless Networks of Internet of Things (IoT) Devices
The present disclosure, in various embodiments, provides a system, method, and device for coordinating wireless networks of IoT devices. The method can include transmitting a coordination signal to a first gateway and a second gateway to coordinate a discovery process. A suspension signal can be transmitted to one or more of the first gateway or the second gateway based on suspension criteria to cause suspension of the discovery process at the first or second gateway.
The present disclosure, in various embodiments, provides a system, method, and device for network and device health monitoring in networks of Internet of Things (IoT) devices. The method can comprise generating device health data associated with an IoT device by extracting device diagnostic parameters from IoT device data and generating gateway health data associated with a gateway device by extracting gateway diagnostic parameters from gateway data. The method can further comprise determining whether any one of the gateway health data or the device health data meets a suspension criteria and transmitting a suspension signal to the gateway device in response to the gateway health data meeting a suspension criteria.
H04L 43/0817 - Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability by checking functioning
Example implementations relate to content item selection in a network environment. In an example, a plurality of user features is received and at least one characteristic of a plurality of content items having at least a first value is obtained. Using a causal inference framework and based on the plurality of user features, an expected increase in user interaction with the plurality of content items between the at least one characteristic of the plurality of content items having the first value and the at least one characteristic of the plurality of content items having a second value is calculated. Using the expected increase in user interaction with the plurality of content items, a recommended value for the at least one characteristic of the plurality of content items is calculated and an interface including the plurality of content items having the recommended value for the at least one characteristic is generated.
The present disclosure, in various embodiments, provides a system, method, and device for selective filtering of advertising messages in networks of Internet of Things (IoT) devices. The method can include determining whether an advertising message received at a first gateway meets a preset filtering criteria, and transmission of a coordination signal to the first gateway. The coordination signal can be configured to establish a connection between the first gateway and the IoT device if the advertising message meets the preset filtering criteria.
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
The present disclosure, in various embodiments, provides a system, method, and device for dynamic reconfiguration of networks of Internet of Things (IoT) devices. The method can include collecting network health data and gateway health data from a source gateway and transmitting a handoff signal to a source gateway. The handoff signal can initiate a device assignment routine when at least one trigger criterion is met, such as of a load-balancing event, a failover event, a roaming event, or a user-initiated event. A target gateway can be determined based on selection parameters and can receive relevant device details from the source gateway to enable the IoT device to connect with the target gateway.
H04L 41/0823 - Configuration setting characterised by the purposes of a change of settings, e.g. optimising configuration for enhancing reliability
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
13.
Systems and Methods for Coordinating Periodic Advertising with Responses (PAwR) Trains in High-Density IoT Environments
The present disclosure, in various embodiments, provides a system, method, and device for coordinating wireless networks of IoT devices. The method includes transmitting a coordination signal to a first gateway and a second gateway, and the coordination signal can be configured to coordinate a PAwR communication schedule. The PAwR communication schedule can include coordinated PAwR advertising intervals for the gateways.
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
G16Y 40/35 - Management of things, i.e. controlling in accordance with a policy or in order to achieve specified objectives
H04W 4/70 - Services for machine-to-machine communication [M2M] or machine type communication [MTC]
H04W 4/80 - Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
39 - Transport, packaging, storage and travel services
Goods & Services
Customs clearance services; Import-export agency services; Freight logistics management; Transportation logistics services, namely, arranging the transportation of goods for others; Business management of logistics for others; Arranging for pickup, delivery, storage and transportation of documents, packages, freight and parcels via ground and air carriers; Business advisory services in the field of importer-of-record administration; Business research and data analysis services in the field of field of transportation and supply chain logistics; Business advisory and consultancy services relating to export, export services, export promotion information and services; Business management consulting, strategic planning and business advisory services provided to customs compliance and tariff classification Import and export cargo handling services; Freight and transport brokerage; Supply chain logistics and reverse logistics services, namely, storage, transportation and delivery of goods for others by air, rail, ship or truck; Warehousing services, namely, storage, distribution, pick-up, and packing for shipment of documents, packages, raw materials, and other freight for others; Supply chain logistics and reverse logistics services, namely, storage, transportation and delivery of documents, packages, raw materials, and other freight for others by air, rail, ship or truck; Cargo transportation; Providing information concerning collection and delivery of assets in transit, namely, vehicles, trailers, drivers, cargo and delivery containers; Leasing of fixed and movable storage containers to commercial and residential users; Postal, freight and courier services; Transport and delivery of goods; Providing information via a website in the field of delivery of consumer goods; Providing an on-line computer database in the field of truck,rail, air, and ocean transportation; Locating and tracking of cargo for transportation purposes; Parcel delivery; Parcel shipping services; Advisory services relating to transport
16.
Enhanced PTID prediction and accurate fitment using a PTID understanding model
A system includes a processor and a non-transitory computer-readable medium storing computing instructions that, when executed, perform operations including tokenizing a query. Tokens are transformed into embeddings. The embeddings are passed through a classification layer, producing log its. A sigmoid function is applied to convert the log its into a probability vector for Part Terminology Identifiers (PTIDs) associated with one or more domains. The probability vector is filtered to retain PTIDs based on respective probabilities satisfying a threshold. A sum of the probabilities is a predetermined sum value. The PTIDs are ranked by their probabilities. Business logic is applied to the ranked PTIDs using a PTID Understanding Model to determine a final result output to a fitment service. The PTID Understanding Model is pretrained to trigger a fitment determination process and/or a query results filter process for the one or more domains when the final result is valid.
Advertising services; Cooperative advertising and marketing; Online advertising and promotional services; Promotional advertising of products and services of third parties through sponsoring arrangements and license agreements relating to construction toys
In some embodiments, systems and methods are provided herein useful to load and/or unload freight. In some embodiments, A system may include a mobile platform, a receiving conveyor on the mobile platform, a receiving conveyor actuator coupled to the receiving conveyor, a pick apparatus attached to the mobile platform. The pick apparatus may pick a first object from a stack of objects and release the first object to the receiving conveyor. The receiving conveyor may move away the first object released thereon from the stack of objects. The pick apparatus may move toward a second object in the stack of objects while the first object on the receiving conveyor is moved away from the stack of objects. The receiving conveyor actuator may change, based at least on a height of the second object, the height of the first portion of the receiving conveyor.
Example implementations related to generating interfaces for set completion and/or augmentation using contextual information are disclosed. In an example, a set of items associated with a completed first process is received. A set of contextually relevant items is generated based on the set of items using at least one graph neural network and a set of ranked contextually relevant items is generated by applying a listwise ranker to the set of contextually relevant items. Instructions that cause a user device to display an interface including at least a portion of the set of ranked contextually relevant items in ranked order are generated and a selection of at least one item from the set of ranked contextually relevant items is received. A set of updated items including the set of items and the at least one item is generated and a second process is implemented for the set of updated items.
37 - Construction and mining; installation and repair services
Goods & Services
(1) Installation and repair of locks; Installation of HVAC systems; Installation, maintenance and repair of heating, ventilation and air conditioning (HVAC) systems; HVAC contractor services; Plumbing services; Repair of household appliances and of residential heating, plumbing, air conditioning, and electrical systems; Handyman service, namely, building repair and maintenance; Pest control and extermination services, other than for agriculture, aquaculture, horticulture and forestry; Interior and exterior window cleaning services; Comprehensive preventative maintenance service for roofing systems; Janitorial cleaning and maintenance services; Cleaning of office buildings and commercial premises; Power washing services; Comprehensive preventative maintenance service for electrical systems; Contractor services, namely, review of and remedial recommendations for building plumbing, electrical and mechanical systems for others; Building maintenance and repair; Electrical repairs, maintenance, and installation of electrical wiring, outlets, light fixtures, and electrical panels; Real estate property cleaning, repair and maintenance services.
(2) Construction services; installation and repair services; mining extraction, oil and gas drilling.
Examples provide a multi-platform metadata sync and catalog permission granting system using a single shared cloud storage used by a plurality of linked cloud platforms. When new data is created and stored on the shared cloud storage or existing data is deleted or updated on the shared cloud storage, metadata associated with the storage location of the data and permission data associated with access control permissions is extracted from the source system creating the changes. The extracted metadata is migrated substantially in real time to all the other linked cloud platforms. A copy of the extracted metadata is stored by each linked cloud platform. Each linked cloud platform can access the same copy of data stored on the shared cloud storage. This eliminates redundant duplication of data on the linked cloud platforms to reduce system resource usage consumed by copying and storing data.
Sensor data from a sensor that is associated with a mobile device is obtained with respect to an asset of an indoor facility. Using the sensor data, location coordinates of the mobile device within the indoor facility, the coordinates being in a global frame of reference. Identification information associated with the asset is also received. The coordinates from the global frame of reference are converted to a frame of reference of the indoor facility. The converted coordinates and the identification information are associated with a work order associated with the asset. An asset map is updated with the converted coordinates of the asset and represents a digital twin of the indoor facility.
In some embodiments, apparatuses and methods are provided herein useful to provide product search results. In some embodiments, a system includes a communication interface to provide a search interface of a user interface to a plurality of user devices, a computer readable storage memory storing a product database and a set of computer executable instructions, and a control circuit to execute the set of computer executable instructions, causing the control circuit to: provide the search interface including a plurality of search modality options, receive a first query in a first modality from the search interface, generate, via a language model, a product results list based on the first query and the product database, receive a second query in a second modality from the search interface; and update, via the language model, the product results list based on the first query, the second query, and the product database.
In some embodiments, apparatuses and methods are provided herein useful to provide product search results. In some embodiments, a system includes a communication interface to provide a search interface of an e-commerce user interface to a plurality of user devices, a computer readable storage memory storing a product database and a set of computer executable instructions, and a control circuit configured to execute the set of computer executable instructions, causing the control circuit to: provide the search interface to a user device, receive a first query from the user device, generate, via a language model, a product list comprising a plurality of products, generate, via the language model, two or more dynamic categories; and provide, for display on the user device, the two or more dynamic categories for selection in the e-commerce user interface.
Example implementations related to interface template selection and population are disclosed. In an example, a plurality of rewards for optimization are received and at least one reward weight for each reward in the plurality of rewards is generated. A current reward value for each reward in the plurality of rewards is determined and a request for an interface from a user device is received. An interface template is selected using multi-objective optimization based on the current reward value and the at least one reward weight for each reward in the plurality of rewards and a set of content elements is selected based on the interface template. Instructions that cause the interface to be displayed on the user device are generated. The interface includes the interface template and the set of content elements.
Examples provide a system and method for selectively modifiable multi-item digital tags for editing digital tag display data associated with one or more items without altering data displayed on the same tag for other items linked to the tag. A digital tag manager provides a multiple editing options for selecting linking new items to a digital tag, removing already linked items from the digital tag, changing item display data for one or more of the items, or replacing items linked to the tag without completing resetting the digital tag. This enables users to manage item display data quickly and easily for multiple items without having to reset the tag and manually rescan each item to recreate the linkages between the items and the digital tag. An edit interface provides a user-friendly interface enabling the users to manage linked digital tag item data faster and more efficiently.
G06Q 10/087 - Inventory or stock management, e.g. order filling, procurement or balancing against orders
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
30.
SYSTEMS AND METHODS OF METADATA ABSTRACTION AND COMPARISON
Some embodiments provide systems to provide metadata abstraction for a comparison interface. An example system includes a non-transitory machine-readable medium storing instructions that, when executed by a processing resource, may cause the resource to: compile textual metadata associated with an item, determine a ranked list of use cases for the item based in part on using one or more prompts to a language model, at least one of the one or more prompts includes the textual metadata, receive, via a client interface provided to a client device, a selection of the item and a comparison item; and select a highlighted use case to display with the item in a comparison interface of the client interface, wherein the highlighted use case is selected based on the ranked list associated with the item and a ranked list of use cases associated with the comparison item in the use case database.
Some embodiments provide systems to control a production facility according to a production schedule comprising: a processing resource; a non-transitory machine readable medium storing executable instructions that, when executed, cause the processing resource to: generate, using a first trained model, sets of forecasted production optimizations of the multiple production lines using predicted product demand and production line data, relative to multiple objective constraints comprising production line change over time, a maximum uptime limit, and production line utilization; generate, using a second trained model and the sets of forecasted production optimizations, a first production schedule of the multiple production lines while complying with the multiple objective constraints; and control one or more system components of the multiple production lines consistent with the first production schedule to implement production of a respective one of the multiple different products.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
32.
CONVEYOR-BASED SYSTEMS AND METHODS FOR REORIENTING PACKAGING CONTAINERS
Systems and methods for orienting boxes to ensure they are positioned right side up as they move along a conveyor utilize one or more rotation chambers that rotate the boxes in 90-degree increments. The location of the boxes in the rotation chambers and the rotation direction of the rotation chambers is selected to prevent tumbling of the boxes during the rotation. Sensors may detect the orientation of the boxes moving on the conveyors to determine the number of rotations necessary to reorient the box such that the box is oriented with the correct side up, and the conveyor may be caused to precisely align the box with appropriate corner of the rotation chamber. The system can include multiple rotation chambers in series, allowing for the boxes to be rotated 90, 180, or 270 degrees, and includes sensors to verify the orientation of the boxes prior to and after the rotation.
B65G 47/248 - Devices influencing the relative position or the attitude of articles during transit by conveyors orientating the articles by turning over or inverting them
B65G 43/08 - Control devices operated by article or material being fed, conveyed, or discharged
In some embodiments, apparatuses and methods are provided herein useful to returning unwanted items collected by a user at a facility. In some embodiments, a system for returning unwanted items includes a drop zone repository unit. The unit includes a receptacle; a sensor; and a camera; and a control circuit. The control circuit executes computer program code to: determine that the user returned unwanted items; create a drop zone virtual acquisition listing; associate the unwanted items with the drop zone virtual acquisition listing and an identifier associated with the user; and provide the drop zone virtual acquisition listing and the identifier to an item acquisition system such that at acquisition completion, the drop zone virtual acquisition listing is processed and aggregated with collected virtual acquisition listings to remove the unwanted items in the drop zone virtual acquisition listing from an acquisition transaction.
An example method includes obtaining user data from a first platform including item identifiers, first audience data including first audience interactions, and second audience data including second audience interactions. The method includes generating synthetic data for a second platform, distinct from the first platform, based on the first audience data and the second audience data. Generating the synthetic data includes selecting a set of the first audience data and the second audience data and a predetermined number of the item identifiers, and adding the predetermined number of the item identifiers to respective audience interactions of the set of the first audience data and the second audience data to form the synthetic data. The method further includes transmitting the synthetic data to at least one computing device and receiving engagement data responsive to the synthetic data.
Example implementations relate to systems and methods for generating customized incentives to increase engagement. In an example, a system receive first data and second data distinct from the first data. The system determines, using a disengagement evaluator, disengagement scores for candidates in the first data, and selects a set of candidates from the first data having disengagement scores above a disengagement threshold to form disengagement candidates. The system determines, using an engagement evaluator, engagement scores for users that are based on the disengagement candidates and the second data, selects a set of the users having engagement scores above an engagement threshold to form engagement candidates. The system generates a notification for a user of the engagement candidates that includes an incentive for user interaction, and transmits the notification to a computing device the user of the engagement candidates.
Example implementations relate to systems and methods for re-ranking products of a query. Example computer implemented methods may include receiving an intermediate recall set of products of a query and obtaining features of a product of the intermediate recall set of products of the query. The computer implemented method can further include performing dense cross interactions between the query and the features of the product of the intermediate recall set of products using a cross-encoder model to generate a class prediction. The computer-implemented method can additionally include generating a re-rank score for the product of the intermediate recall set of products of the query by performing a model inference based at least on the class prediction. The computer-implemented method can also include re-ranking the product of the intermediate recall set of products based on the re-rank score for the product. Other embodiments are described.
Example implementations related to explore-exploit item recommendation using shared parameters are disclosed. In an example, interaction data for a set of candidate items is received, distribution parameters is determined for the candidate items, and updated distribution parameters are generated based on a mean of the distribution parameters. At least one updated parameter is associated with a first cluster of the candidate items. A subset of candidate items is ranked based on the of updated distribution parameters using an explore-exploit process and instructions are generated that cause an interface to be displayed on a user device. The interface includes at least a portion of the subset of candidate items in rank order. An interaction with at least one candidate item of the subset of candidate items is received from the user device and the set of distribution parameters is updated based on the interaction with the at least one candidate item.
Examples provide validation and visualization of data sources relied upon by a generative (GEN) artificial intelligence (AI) machine learning (ML) model when generating a response to a user query. The data sources are analyzed to determine whether each source is a valid source based on a degree of reliability of the source and relevance of the source to the query. A validation score and/or rank is generated for each source. An interactive user interface (UI) is generated which includes a query-response viewing pane for viewing the query and the response and an interactive source validation viewing pane for presenting the identified sources with the score and/or rank for each source. The interactive source validation pane can include summaries of the sources, links to relevant portions of the sources, collected sources data tables including selected portions of the sources, and text fields for user feedback used to retrain the model.
The disclosure herein describes context-based candidate data generation with self-refinement. An example disclosed operation includes: generating a batch of candidate data using a large language model (LLM) based generator, formatting the batch of candidate data according to a plurality of formatting constraints, evaluating, using a sequence of evaluators, a candidate of the batch of candidate data, determining whether any evaluator of the sequence of evaluators fails the candidate, based on determining that at least one evaluator of the sequence of evaluators fails the candidate, identifying a first failing evaluator, mapping an output of the first failing evaluator to a refiner instruction, refining, using a LLM based refiner, the candidate based on the refiner instruction, reformatting the refined candidate, and re-evaluating the refined candidate, until earlier of either a maximum of refine attempts is reached or all evaluators of the sequence of evaluators are successful.
Examples related to ranking offers based on machine learning are disclosed. An example may involve: receiving a request for ranking a plurality of offers associated with an item; generating offer related feature data based on the request; inputting the offer related feature data into a machine learning model to generate an order conversion score for each of the plurality of offers; generating, from the plurality of offers, a ranked list of offers based on their respective order conversion scores; and transmitting the ranked list of offers to a computing device.
Example implementations may relate to systems and methods for re-ranking item recommendations. For example, a computer-implemented method may include receiving recommended items for items in a cart of an online checkout. The computer-implemented method can also include iteratively generating clusters of a pair of recommended item of the recommended items and a fulfillment center of the recommended item, and a pair of an item of the items in the cart and a fulfillment center of the item in the cart. The computer-implemented can further include generating embeddings for the clusters, and determining a cluster combination of cluster combinations with an optimal cost. The computer-implemented can additionally include re-ranking recommended items of the cluster combination with the optimal cost, and transmitting for displaying, on a device of a user, at least a subset of the recommended items of the cluster combination with the optimal cost, as re-ranked. Other embodiments are described.
An integrated scale system for a checkout terminal in a retail environment is provided. The system includes a scale plate, a frame load plate under the scale plate, a plurality of load cells mounted on the frame load plate, and an electronic article surveillance (EAS) label deactivator positioned between the scale plate and the frame load plate. The load cells output signals indicating the weight of an item placed on the scale plate, while the EAS label deactivator is configured to deactivate EAS labels on items placed on the scale plate.
G01G 19/414 - Weighing apparatus or methods adapted for special purposes not provided for in groups with provisions for indicating, recording, or computing price or other quantities dependent on the weight using electromechanical or electronic computing means using electronic computing means only
G08B 13/24 - Electrical actuation by interference with electromagnetic field distribution
43.
PERSONALIZED ADVERTISING CONTENT DISPLAY BASED ON TIMING PARAMETER
Example implementations relate to providing advertising content. A transaction event associated with a user is detected. A timing parameter is determined based on transaction data associated with the transaction event and user profile information of a user. The timing parameter is indicative of an estimated time for the user to approach a fixed digital display device after the transaction event. Advertising content for the user is determined based on the user profile information. The advertising content is displayed on the fixed digital display based on the timing parameter.
Systems, apparatuses, and methods are provided for item induction into an automated storage and retrieval system. Some embodiments include a storage structure storing a plurality of totes, a transport system configured to move the totes within the storage structure and to and from workstations, a buffer storage, and a control system. The control system receives an identifier associated with an order indicating that items of the order have been placed into the buffer storage, selects a tote for the order based on associated order information and available space within the totes, and causes the transport system to deliver the selected tote to a workstation. Instructions are provided to transfer the buffered items into the tote, after which the transport system returns the tote and items to the storage structure. Partially filled totes associated with the order may be preferentially selected.
Systems, apparatuses, and methods are provided herein useful to identify items at checkout stations. In some embodiments, a checkout station includes an item staging area, an optical scanner, a display, and a computer vision system. The computer vision system may include a camera, a control circuit, and a machine-readable medium that stores instructions. The control circuit may execute a trained machine learning model to: determine whether a machine-readable code is received, identify the item based on the captured image, automatically update content shown in the display to identify the item, automatically update the content to provide at least two items similar to the item with a prompt for a user selection of the item, and automatically update the model. The control circuit may execute the model to automatically update the content to provide a prompt to scan the item.
Examples may relate to inventory management within a facility. In some embodiments, a facility has a first camera associated with a location and mounted to view a storage area and capture images of the storage area. A control circuit or processing resource can execute a machine learning model trained to: detect boundary features of a bin depicted in a first image; determine a bin location of the bin based on the location associated with the first camera; identify at least one inventory item stored in the bin based on a respective identifier associated with the at least one inventory item; and/or update inventory data based on identifying the at least one inventory item, wherein the inventory data is associated with the bin and at least one of the bin location and the location associated with the first camera.
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/52 - Surveillance or monitoring of activities, e.g. for recognising suspicious objects
47.
SYSTEMS AND METHODS FOR CATCHING AND REMOVING PALLETS AT PALLET STORAGE SLOTS
Systems, apparatuses, and methods are provided for facilitating removal of pallets from a pallet storage slot. In some embodiments, at least one pallet stop is coupled to at least one pallet support rail of the pallet storage slot. The pallet stop includes a plate having an upwardly-facing surface that supports a downwardly-facing surface of a pallet, a fixed stopper non-detachably coupled to the plate and extending upwardly therefrom to restrict movement of the pallet in a direction of removal, and at least one wheel rotatably coupled relative to the plate. During removal of the pallet from a pallet storage slot, the pallet stop permits the pallet to be lifted such that the downwardly-facing surface clears a top edge of the fixed stopper, placed onto the at least one wheel, and moved in the direction of removal while the at least one wheel supports the pallet and rotates.
Examples provide a traffic pattern recognition for accurate pixel-level travel time prediction. Historical travel-related data is obtained from vehicles traveling within various geographic regions that includes location data and speed data associated with each pixel in a plurality of pixels at a month, day, and hour level. A trained machine learning (ML) model predicts the speed of travel through each pixel at a weekday-hour-pixel (WHP) level. The ML model is trained using the historical travel-related data enabling the ML model to make accurate predictions of future travel times at the WHP level. The predicted speeds of travel are used to create a table of speed values for multiple pixel-timeslots associated with future dates. Each pixel-timeslot includes a predicted speed value for vehicles traveling through segments of each node on a given future data during a specific hour of the day enabling more accurate estimations of arrival time.
A system includes a conveyor that moves cases, a robot, a tool disposed at an end of an arm, of the robot, and a sensor. The sensor is positioned to obtain sensed visual information about cases that are located on the conveyor and is controlled by a control circuit. The control circuit receives the sensed visual information from the sensor and processes the sensed visual information to obtain coordinates of a location on a case to contact the case. The coordinates are selected such that damage to the case or contents of the case is prevented when the case is contacted by the tool at the location. The robot then contacts the case with the tool at the coordinates and then to lift and move the case to a selected location.
Examples may be related to webpage layout optimization. An example may involve: obtaining a request regarding a webpage; determining feature data associated with the webpage based on the request; determining at least one metric associated with the webpage; generating, based on the feature data and the at least one metric, a plurality of reward scores for a plurality of page elements respectively, wherein each reward score indicates a reward of a respective page element with respect to the at least one metric; determining a layout of the webpage based on the plurality of reward scores and the plurality of page elements; and creating the webpage according to the determined layout.
A method can include receiving, from a first sensor, an ambient temperature indicative of an amount of external heat to which a first storage container is exposed. The method can also include determining, with a first machine learning model, a first set of pre-cooling parameters for the first storage container based in part on factors comprising the ambient temperature indicative of an amount of external heat to which a first storage container is exposed, time of day, and a scheduled loading time for the first storage container. The method can further include transmitting a first request to a first pre-cooling system to initiate a cooling process for the first storage container in accordance with the first set of pre-cooling parameters. The method can also include predicting maintenance of the first storage container using a second machine learning model. Other embodiments are described.
B65D 88/74 - Large containers having means for heating, cooling, aerating or other conditioning of contents
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G06Q 10/0832 - Special goods or special handling procedures, e.g. handling of hazardous or fragile goods
52.
SYSTEMS AND METHODS OF IDENTIFYING AND ALLOCATING PRODUCTS WITHIN A RETAIL FACILITY
In some embodiments, apparatuses and methods are provided herein useful to identify and allocate products within a retail facility. A system may include a first set of cameras to capture sets of person images of a person and a second set of cameras to capture sets of product images of products. The system includes a person identification control circuit to process a first set of person images and generate a unique first person identifier, and a product identification control circuit to: determine there is a difference in a number of products, identify a product removed based on the determined difference; and determine that the person is at least a threshold distance from where the first product was identified; and a cart generation control circuit to: generate a virtual first zone cart associated with the first person identifier; and add the first product to the virtual first zone cart.
Some embodiments provide systems to enable product purchases comprising: multiple zones of a retail facility each comprising: a control circuit and computer memory storage system storing: a person identification code set executable to process a first set of images and generate a unique first person identifier; a product identification code set to identify a first product determined to have been removed by the first person; and a zone cart generation code set to generate a virtual first zone cart associated with the first person identifier and the first zone, and virtually add the first product to the virtual first zone cart; and a cumulative virtual cart generation control circuit to combining the virtual first zone cart with one or more additional virtual zone carts each exclusively associated with a respective one of additional person identifiers each within a threshold difference of the first person identifier.
In some embodiments, apparatuses and methods are provided herein useful to determine dimensions of items. In some embodiments, a system may include a plurality of caliper plates, wherein a location of each of the plurality of caliper plates is adjustable along a respective axis, a plurality of sensors, wherein at least one sensor of the plurality of sensors is positioned to detect a range of movement of each of the caliper plates, a user interface including a display, and a control circuit that: obtains, from the at least one sensor, measurement data indicating a distance moved by each of the caliper plates along their respective axis from an initial position to a final position, where each of the caliper plates is in contact with a respective side of an item; and processes the measurement data received from the at least one sensor to determine overall dimensions of the item.
In some embodiments, apparatuses and methods are provided herein useful to assess qualitative and quantitative features of items. In some embodiments, a system may include at least one database storing item data associated with at least one retail item of the plurality of retail items, and a trained machine learning model coupled to the at least one database, wherein the trained machine learning model, when executed by a processor-based control circuit of a computing device: obtains the item data from the at least one database, processes the item data obtained from the at least one database to generate a numerical value for two or more features of the at least one retail item; and consolidates each numerical value associated with the two or more features of the at least one retail item into an overall numerical value of the at least one retail item.
Examples provide a system and method for predicting future wastage of perishable goods received at a distribution center based on shelf life of each type of perishable item and age of arrival (AoA) when received. The system implements a ML model to predict the wastage for a given item or batch of items based on item-specific data, supplier data, transit data, etc. The system estimates quantity of throws at a DC level and/or a store level to reduce future wastage and ensure quality of perishable items received at the DC and stores. The system generates anomalous shipment alerts after quality control inspections at user-configurable intervals enabling users to take action to mitigate wastage. The predictions are used to determine whether to recommend rejection of a shipment and return to a supplier or acceptance of the shipment with possible additional actions to mitigate the predicted future wastage.
Examples may be related to developing a conversation-based virtual assistant. An example may involve: obtaining, from a user, a query selecting one or more items from at least one list of items; determining context information associated with the at least one list of items; obtaining at least one template including a position reference placeholder; generating at least one prompt, based at least in part, by replacing the position reference placeholder with a plurality of position reference terms such that each position reference term corresponds to a different manner of referring to an item position; training a natural language model by using the at least one prompt; inputting the query and the context information to the trained natural language model to identify the one or more items selected by the query and generate a response referring to the identified one or more items; and presenting the response to the user.
Examples provide a future inventory (FI) ordering system that enables orders of temporarily out-of-stock (OOS) items that are not currently on-hand at a fulfillment center (FC). A temporarily unavailable OOS item is made available for purchase with an extended estimated date of delivery (EEDD) as a future delivery (FD) item. A status indicator can be provided to distinguish FD items from currently in-stock items via a user interface (UI) device. Machine learning models are used to predict transit time, dwell time, and/or receiving time for the FD item using lane-specific data, dynamic extrinsic data, and other item-related data. The EEDD is predicted using the predicted transit time. A delivery notification including the EEDD for the FD item to the user via the UI device. Unloading of trailers containing FD items is prioritized at the FC to ensure timely delivery of FD items within the predicted EEDD.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
Examples provide an archway truss for supporting devices, such as sensor devices generating sensor data for objects passing through the archway and a digital display device displaying dynamic content to users moving through the archway. The archway truss includes vertical support members attached to a horizontal top member. A central support member is reinforced to protect against cart impacts. Cameras are attached to the archway truss and positioned to capture images of objects in carts moving through the archway truss. Radio frequency identification (RFID) tag readers and other sensor devices are removably attached to the archway truss to gather item identification data for objects in the carts. Pairs of wing barriers are provided for each vertical support to block the field of view of the cameras from objects outside the lanes formed by the archway truss. An exterior covering provides padding to protect users contacting the archway truss.
G06K 7/10 - Methods or arrangements for sensing record carriers by electromagnetic radiation, e.g. optical sensingMethods or arrangements for sensing record carriers by corpuscular radiation
In some embodiments, apparatuses and methods are provided herein useful to wheel-based power generation on a cart for transporting commercial products. In some embodiments, a system may include at least one wheel that rotates in multiple directions; a first shaft coupled to the at least one wheel; a rotation transmitter coupled to the at least one wheel and the first shaft; a first gear coupled to the first shaft; a second gear coupled to the first gear; a second shaft coupled to the second gear; and a generator coupled to the second shaft to generate power by converting rotation of the at least one wheel into an alternating current power output. The system may include a control unit coupled to the generator to convert the alternating current power output into a direct current power, and a power storage component coupled to the generator, to store the direct current power output.
B62B 3/00 - Hand carts having more than one axis carrying transport wheelsSteering devices thereforEquipment therefor
B62B 3/14 - Hand carts having more than one axis carrying transport wheelsSteering devices thereforEquipment therefor characterised by provisions for nesting or stacking, e.g. shopping trolleys
Example implementations relate to systems and methods for detecting disengagement. In an example, a system determines, by a risk identifier, predetermined risk labels based on the user data. The system determines, using a risk evaluator that receives input features, a risk of disengagement for a user. The system determines, using a risk interpreter that receives the input features and the predetermined risk labels, a disengagement reason for the user. The system also determines, based on the risk of disengagement and the disengagement reason, a disengagement prevention incentive for the user. The system further presents, at a computing device associated with the user, a user interface element for interacting with the disengagement prevention incentive.
Example implementations related to automated anomaly detection in time-series datasets are disclosed. In an example, a request for an automated redemption operation is received. The request includes a plurality of time-series data elements. A reconstruction error is generated for the request using a trained autoencoder model that receives the plurality of time-series data elements. The reconstruction error is representative of a difference between the plurality of time-series data elements and a reconstructed plurality of time-series data elements generated by the trained autoencoder model. In response to determining the reconstruction error is above the predetermined threshold and that the request for the automated redemption operation satisfies at least one anomaly detection rule, execution of the automated redemption operation is prevented.
A quick-connect powered case holds an electrically-powered shelf module (e.g., electronic shelf label), and has a pair of power terminal arms and a connector inside that is coupled to the power terminal arms. The case may be quickly affixed to a shelf fixture that supports a product shelf and has electrically conducting brackets. The brackets provide supplied electrical power from conducting vertical shelf rails. When the power terminal arms contact the shelf brackets and the shelf module is plugged into the connector, electrical power flows from the shelf brackets, through the power terminal arms and connector, into the shelf module. For safety, the shelf fixture has an insulating cover over the shelf brackets, with openings that permit each of the power terminal arms to electrically couple with one of the shelf brackets. The power terminal arms are sufficiently thin that the product shelf lies flat on the shelf fixture.
A47B 57/42 - Cabinets, racks or shelf units, characterised by features for adjusting shelves or partitions with means for adjusting the height of detachable shelf supports consisting of hooks coacting with openings the shelf supports being cantilever brackets
A47B 57/46 - Cabinets, racks or shelf units, characterised by features for adjusting shelves or partitions with means for adjusting the height of detachable shelf supports consisting of screwbolts as connecting members the shelf supports being cantilever brackets
Example implementations relate to communication element selection in a network environment. In an example, a plurality of user features is received and input data derived from the plurality of user features is processed using a window logic and provided to an attention-based machine learning model. A plurality of communication elements is provided to the attention-based machine learning model, which assigns one or more weights to each of the plurality of communication elements for a subsequent time period based on the plurality of user features obtained from a preceding time period. A score for each of the plurality of communication elements based on the one or more weights for each of the plurality of communication elements is calculated and an interface including a communication element of the plurality of communication elements having a highest calculated score is generated.
A computer-implemented method is provided that can smooth a truck flow to a destination node. Input data can be received by a truck flow planning (TFP) system, including truck demand data, truck capacity constraints, and node capacity constraints. The TFP system can include truck demand projection (TDP), truck flow optimization (TFO), and receding horizon control (RHC) components. Truck demand can be projected over a horizon. A plan for the truck flow can be generated that reduces variability while at least maintaining inventory health and can include formulating the plan as a Mixed Integer Programming (MIP) problem. The plan can be adjusted when one or more of new input data features, outputs of the RHC component, outputs of a truck planning optimization (TPO) component, or outputs of a truck load optimization (TLO) component are within thresholds. The plan, as generated and adjusted, can be based on a rolling time window.
Systems and methods for sampling item data. One such method includes receiving, from for each of a plurality of items, a recognition rate corresponding to a rate of success of correlation between: image data of the item captured by an image capture device, and an identified selection of the item from item selection data generated by an item tracker configured to generate the item selection data for lists of selected items. The method further includes determining, from the plurality of items, a plurality of target items having recognition rates failing to satisfy a recognition threshold; identifying, from the item selection data, a plurality of candidate items lists each including at least one of the plurality of target items; determining, by the computing device, a group of top items lists from the plurality of candidate items lists; and retrieving, by the computing device, image data associated with the top selected-items lists.
G06V 10/762 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using clustering, e.g. of similar faces in social networks
G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
A system for onboarding internet of things (IoT) devices. The system includes a storage device storing, for each of a plurality of IoT devices, a device profile associated with the IoT device; and an IoT edge hub comprising a processor and a computer-readable medium. The computer-readable medium stores instructions that are operative upon execution by the processor to, for each of the plurality of IoT devices: establish a low-level connection with the IoT device and receive a device identifier (ID) from the IoT device; retrieve, from the storage device, the device profile associated with the IoT device using the device ID; receive a data packet from the IoT device in a device data format associated with the IoT device; and using the device profile, convert the data packet to a converted data formatted in a predefined data format associated with the IoT edge hub.
Example systems and methods use trained models and large language models (LLMs) to generate synthetic search queries in connection with item searches. An example system includes: a database including past user search queries directed to items of interest to users; a processing resource; and a machine readable medium storing instructions that cause the processing resource to: generate, using a first trained model, metadata fields for an item where the first trained model uses past user search queries, an item classification showing a relationship of the item to other items, and/or the features and attributes of the item; generate, using a second trained model, a prompt to query LLMs to generate synthetic search queries that may be asked by a user; receive the synthetic search queries from the LLMs; and map, using a trained categorization model, each of the received synthetic search queries to item categories.
There are provided systems and methods that use trained models and large language models (LLMs) to generate synthetic search queries with tagged item attributes. The system includes: a database containing items with attributes and values associated with the attributes; a processing resource; and a machine readable medium storing instructions that cause the processing resource to: generate, using a first trained model, a first prompt to query an LLM to extract focused item attributes for an item; receive the focused product attributes; generate, using a second trained model, a second prompt based on the focused item attributes to query the LLM to generate synthetic search queries; tag, using the second trained model, each of the synthetic search queries with value pairs that include a focused item attribute and a value for that attribute; and receive the tagged synthetic search queries.
A system includes an electronic database, a central hub processing resource, and a computer readable medium storing instructions that, when executed by the processing resource provide a client center user interface to receive catalog information from a client side system, electronically store the catalog information in the electronic database, and provide a fulfillment gateway. The fulfillment gateway integrates the client side system with a plurality of hub participants by making information input by the client side system accessible to the hub participants. Electronic orders are received at the hub according to the published catalog. The electronic orders are processed by the processing resource and a fulfillment option is accessed to fulfill the electronic order. The ordered item is picked and delivered to the customer.
Example implementations relate to systems and methods for detecting anomalies in performance data and changing a status based on the detected anomalies. In an example, a system receives performance data obtained during an anomaly detection window. The system determines, using a decomposer, a data decomposition of the performance data. The system determines, using an anomaly value generator; a plurality of anomaly values based on the data decomposition. The system determine, using an anomaly scorer, an anomaly score based on the plurality of anomaly values. The system also, in accordance with a determination that the anomaly score is above an anomaly threshold, generates a notification for adjusting a user status, and transmits the notification for adjusting the user status to a computing device.
Examples may be related to anomaly detection using machine learning. An example may involve receiving a risk assessment request regarding a transaction; generating feature data based on the risk assessment request; and determining, using a machine learning model, a risk score based on the feature data. The machine learning model may be trained based on an objective function characterizing a plurality of objectives. Recommendation data regarding the transaction may be generated based on the risk score, and transmitted to a computing device.
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentialsReview and approval of payers, e.g. check of credit lines or negative lists
In some embodiments, apparatuses and methods are provided herein useful to generate personalized content. In some embodiments, a system comprising a processing resource; a machine readable medium storing instructions that, when executed, cause the processing resource to: aggregate, session data during a client session; update, periodically and during the interaction session, one or more inference indicators associated with the client in an inference cache storage, the one or more inference indicators being determined via a trained machine learning model using the session data and historical data in a historical data database; identify a trigger event based on client interactions; retrieve, in response to the trigger event, at least one inference indicator associated with the client from the inference cache storage; and generate a personalized content for display on the client device based on the at least one inference indicator retrieved from the inference cache storage.
Systems and methods for utilizing an artificial intelligence (AI) model to reduce storage resource utilization. One such method including receiving data associated with a plurality of stagnant items determined inactive for a threshold time. The method further includes, using an AI model trained using data related to the plurality of stagnant items, analyzing the data associated with the plurality of stagnant items to identify at least one candidate item of the plurality of stagnant items for including in a bundling option. The method further includes generating a bundling recommendation including the bundling option, wherein the bundling option includes the at least one candidate item. The method further includes presenting the bundling recommendation along with an acceptance indicator for accepting the bundling recommendation and a rejection indicator for rejecting the bundling recommendation.
Examples provide a system for converting a paper-based list of items into a digital list with greater accuracy using generative artificial intelligence (Gen AI) and historical data associated with items frequently purchased with a given geographical region. A text-based list of items is extracted from an image of a paper-based list of items using optical character recognition (OCR), optical marker recognition (OMR), and/or fuzzy matching. The list can include specific items and/or generic descriptions of item types. A machine learning (ML) model analyzes historical data for item purchasing trends and user-specific transaction data to identify the most commonly purchased specific items for each generic item type. A single predicted specific item mapped to each generic item type is used to populate a digital list representing the paper-based list with greater accuracy without user intervention. User feedback enables re-training of the ML model to further improve accuracy of the item recognition.
Examples relate to a computer-implemented method of system including a processor that can perform certain operations. The operations can include obtaining campaign inputs for a campaign associated with product specifications for an advertiser. The operations also can include generating, using an approximate nearest neighbor similarity search, targeting cuts for a targeting tactic based at least on the campaign inputs. The targeting cuts can be personalized to the advertiser and the product specifications. The operations additionally can include generating an optimized ad group plan including one or more groups of the targeting cuts and, for each of the one or more groups of the targeting cuts, a respective recommended maximum bid, a respective expected amount of winning impressions, and a respective budget allocation. The operations further can include outputting the optimized ad group plan for the campaign. Other embodiments are described.
Examples may be related to cross-category recommendation. An example may involve identifying an anchor item to be presented to a user via a user interface, wherein the anchor item is in a first category; and evaluating, using a machine learning model, a degree of cross-category intent of the user based at least partially on real-time interaction data of the user. The degree of cross-category intent may indicate a likelihood that the user will engage with any item in a second category that is different from the first category. An eligibility of the user to receive an item recommendation in the second category can be determined based on the degree of cross-category intent. A recommended item in the second category may be determined based on the eligibility, and presented to the user together with the anchor item in the user interface.
Example implementations related to user attrition prediction and interface generation are disclosed. In an example, time series datasets that each include interaction data points including a corresponding time stamp are received. One or more features are extracted and a time series label is generated for each time series dataset based at least in part on a gap between each of the plurality of interaction data points. An attrition prediction model is trained using the time series datasets and the corresponding time series label. The attrition prediction model generates an attrition likelihood. A user-specific time series dataset is received and a user-specific attrition likelihood is generated. An interface intervention is generated based on the user-specific attrition likelihood and instructions are transmitted that cause an interface including the interface intervention to be displayed on a user device associated with the user-specific time series dataset.
Store exit verification system and method for retail purchases are provided. The system comprises a sensor array, a display device, and a control circuit. The sensor array collects information from items in a shopping container placed in a shopping container placement area. The control circuit identifies a transaction identifier associated with the shopping container, retrieves an item list associated with the transaction identifier, identifies items in the shopping container based on the information collected via the sensor array, determines whether an intervention condition is present based on a comparison of the item list with the identified items, and indicates a verification completion via the display device if no intervention condition is detected.
G08B 13/196 - Actuation by interference with heat, light, or radiation of shorter wavelengthActuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
Examples provide a smart bagging station including a halo array of sensor devices generating sensor data associated with a detection zone surrounding the smart bagging station. The smart bagging station includes barcode scanners in a curved arrangement within a recessed sensor device housing located behind a bagging device. As a user places an item into a bag, the item is automatically scanned by the barcode scanners without re-orienting the item or passing it across a scanning sensor. Other sensor devices, including RFID tag readers, cameras, and/or weight sensors are located at multiple locations above the bagging device, below the bagging device, on the sides of the bagging device, and/or behind the bagging device creating a detection zone encompassing the bagging area. Items within the detection zone are automatically identified using different types of sensor data without requiring the manual scanning for faster and more efficient checkout.
37 - Construction and mining; installation and repair services
Goods & Services
Installation and repair of locks; Installation of HVAC systems; Installation, maintenance and repair of heating, ventilation and air conditioning (HVAC) systems; HVAC contractor services; Plumbing services; Repair of household appliances and of residential heating, plumbing, air conditioning, and electrical systems; Handyman service, namely, building repair and maintenance; Pest control and extermination services, other than for agriculture, aquaculture, horticulture and forestry; Interior and exterior window cleaning services; Comprehensive preventative maintenance service for roofing systems; Janitorial cleaning and maintenance services; Cleaning of office buildings and commercial premises; Power washing services; Comprehensive preventative maintenance service for electrical systems; Contractor services, namely, review of and remedial recommendations for building plumbing, electrical and mechanical systems for others; Building maintenance and repair; Electrical repairs, maintenance, and installation of electrical wiring, outlets, light fixtures, and electrical panels; Real estate property cleaning, repair and maintenance services
Example implementations relate to output guardrails in automated systems. In an example, a user input from a user device is received by a first trained model and an initial output is generated in response to the first trained model receiving the user input from the user device. The initial output is compared to a set of target response elements, each of the target response elements include at least a portion of a machine generated utterance. A revised output is generated by applying a mitigation logic selected based on the at least one target response element and the revised output is transmitted to the user device when the output of the first trained machine learning model includes at least one target response element. The initial output is transmitted to the user device when the initial output does not include at least one target element.
There are provided systems and methods for communicating with transaction processors and handling error codes received from them. A system may include: database(s) including records with acquisition completion methods; a processing resource; and a machine readable medium storing instructions. The processing resource may: access a record; retrieve an acquisition completion method; transmit a first communication including a first electronic acquisition completion attempt with the first acquisition completion method to an acquisition completion processor; receive an electronic communication from the acquisition completion processor including a decline indication and including an error code; determine that the error code matches one of a first set of error codes that are terminal error codes or matches one of a second set of error codes that are retry error codes. The processing resource updates the record based on receiving a terminal error code and retries the communication based on receiving a retry error code.
In some embodiments, apparatuses and methods are provided herein useful to provide data generation and abstraction for items of a platform. Some embodiments, system may include a database storing data associated with a plurality of items, a processing resource, and a machine readable medium storing instructions that when executed cause the processing resource to: generate, using a first trained model, a first prompt to query at least one LLM to design a series of steps to determine one or more insights associated with a target item; receive the series of steps from the at least one LLM; generate, using an additional trained model, a step specific prompt to query the at least one LLM to provide a step specific insight factor; receive the step specific insight factor; and output data to cause a display of a user device to display the target item and the insight.
A method includes receiving candidate recommended items based on an item included in routine reorders of a user. For each candidate recommended item, dimension features for each dimension are embedded as embedding vectors. The dimensions include a user preference, a department affinity, a model suitability, and an item conversion potential dimension. The embedding vectors are combined into a feature vector input to a deep neural network (DNN) model to generate a ranking score representing a likelihood that the user engages with the candidate recommended item. Dimension-specific scores are obtained from intermediate layers of the DNN model including a user preference, a department affinity, a model suitability, and an item conversion potential score, which are output by a multilayer perceptron (MLP) network applied to respective embedding vectors. A final score is derived by incorporating the ranking score with respective weighted contributions. The candidate recommended items are ranked by the final scores.
Some embodiments provide systems to control digital communications comprising: a transceiver; a processing resource; and a medium storing instructions executed to cause the processing resource to: during a current session, determine acquisition execution intent prediction features; trigger a query to a first trained model; identify a first inferred acquisition execution type based on the acquisition execution intent prediction features; repeatedly evaluate according to a predefined interval whether to trigger a refresh of the first inferred acquisition execution type; trigger a first refresh query; identify, using the first trained model, a second inferred acquisition execution type; identify a set of one or more items corresponding to the in-session search; filter the set to a sub-set of items that satisfy the search and comply with the second inferred acquisition execution type; and control the data communications transceiver to transmit response data in controlling the remote client computing device to render content.
H04L 65/1089 - In-session procedures by adding mediaIn-session procedures by removing media
G06F 12/0813 - Multiuser, multiprocessor or multiprocessing cache systems with a network or matrix configuration
H04L 41/16 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
H04L 65/1096 - Supplementary features, e.g. call forwarding or call holding
21 - HouseHold or kitchen utensils, containers and materials; glassware; porcelain; earthenware
Goods & Services
(1) Insulated carriers for food and beverages; Lunch boxes; Lunch pails; Household or kitchen utensils and containers; cookware and tableware, except forks, knives and spoons; combs and sponges; brushes, except paintbrushes; brush-making materials; articles for cleaning purposes; unworked or semi-worked glass, except building glass; glassware, porcelain and earthenware.
04 - Industrial oils and greases; lubricants; fuels
08 - Hand tools and implements
10 - Medical apparatus and instruments
20 - Furniture and decorative products
21 - HouseHold or kitchen utensils, containers and materials; glassware; porcelain; earthenware
24 - Textiles and textile goods
Goods & Services
(1) Candles; Industrial oils and greases, wax; lubricants; dust absorbing, wetting and binding compositions; fuels and illuminants; candles and wicks for lighting.
(2) Manicure and pedicure implements, namely, nail files, nail clippers, cuticle pushers, tweezers, nail and cuticle scissors; Hand-operated hand tools and implements; cutlery; side arms, except firearms; razors.
(3) Massage apparatus; Maternity support belts for medical purposes; Surgical, medical, dental and veterinary apparatus and instruments; artificial limbs, eyes and teeth; spectacles, contact lenses and sunglasses; orthopaedic articles; suture materials; therapeutic and assistive devices adapted for persons with disabilities; massage apparatus; apparatus, devices and articles for nursing infants; sexual activity apparatus, devices and articles.
(4) Mirrors; Furniture, mirrors, picture frames; containers, not of metal, for storage or transport; unworked or semi-worked bone, horn, whalebone or mother-of-pearl; shells; meerschaum; yellow amber.
(5) Bath brushes; candle holders not of precious metal; bath sponges; Household or kitchen utensils and containers; cookware and tableware, except forks, knives and spoons; combs and sponges; brushes, except paintbrushes; brush-making materials; articles for cleaning purposes; unworked or semi-worked glass, except building glass; glassware, porcelain and earthenware.
(6) Handkerchiefs made of textile; Textiles and substitutes for textiles; household linen; curtains of textile or plastic.
06 - Common metals and ores; objects made of metal
10 - Medical apparatus and instruments
14 - Precious metals and their alloys; jewelry; time-keeping instruments
18 - Leather and imitations of leather
20 - Furniture and decorative products
26 - Small items for dressmaking; artifical flowers; false hair
Goods & Services
(1) Fashion masks being sanitary masks for protection against viral infection; Surgical, medical, dental and veterinary apparatus and instruments; artificial limbs, eyes and teeth; spectacles, contact lenses and sunglasses; orthopaedic articles; suture materials; therapeutic and assistive devices adapted for persons with disabilities; massage apparatus; apparatus, devices and articles for nursing infants; sexual activity apparatus, devices and articles.
(2) Jewelry; costume jewelry; jewelry brooches; Precious metals and their alloys; jewellery, precious and semi-precious stones; horological and chronometric instruments.
(3) Handbags; wallets; bags, namely, travelling bags, cosmetic bags sold empty, beach bags, clutch bags, cross body bags, messenger bags, satchels, hobo bags, book bags, school bags, duffle bags, luggage, briefcases, clutches, backpacks and suitcases; Bags for sports, pet bags of canvas, canvas, vinyl and leather pouches for holding disposable bags to place pet waste in; diaper bags; Bags, namely, travelling bags, cosmetic bags sold empty, beach bags, canvas, clutch bags, cross body bags, messenger bags, satchels, hobo bags, book bags, school bags and duffle bags; luggage; purses; briefcases; wallets; clutches; handbags; backpacks; suitcases; pocketbooks; Bags for sports, pet bags of canvas, vinyl and leather pouches for holding disposable bags to place pet waste in, diaper bags Purses; Wallets; Handbags; Clothing for dogs; Leather and imitations of leather; animal skins and hides; luggage and carrying bags; umbrellas and parasols; walking sticks; whips, harness and saddlery; collars, leashes and clothing for animals.
(4) Buttons; button trims; rivet buttons; zipper pulls; Buttons; button trims, namely, trimmings for clothing; rivets; zipper pulls; hair accessories, namely, twisters, snap clips, claw clips, hair sticks, barrettes; brooches for clothing; Lace and embroidery, and haberdashery ribbons and bows; buttons, hooks and eyes, pins and needles; artificial flowers; hair decorations; false hair.
14 - Precious metals and their alloys; jewelry; time-keeping instruments
18 - Leather and imitations of leather
Goods & Services
(1) Jewelry; Precious metals and their alloys; jewellery, precious and semi-precious stones; horological and chronometric instruments.
(2) Handbags; dog clothing; Leather and imitations of leather; animal skins and hides; luggage and carrying bags; umbrellas and parasols; walking sticks; whips, harness and saddlery; collars, leashes and clothing for animals.
06 - Common metals and ores; objects made of metal
10 - Medical apparatus and instruments
11 - Environmental control apparatus
24 - Textiles and textile goods
Goods & Services
(1) Combination metal locks; Common metals and their alloys, ores; metal materials for building and construction; transportable buildings of metal; non-electric cables and wires of common metal; small items of metal hardware; metal containers for storage or transport; safes.
(2) Massage apparatus and instruments; foam massage rollers; heart rate monitors for sports activities; Acupressure mats; Short compression shorts; Surgical, medical, dental and veterinary apparatus and instruments; artificial limbs, eyes and teeth; spectacles, contact lenses and sunglasses; orthopaedic articles; suture materials; therapeutic and assistive devices adapted for persons with disabilities; massage apparatus; apparatus, devices and articles for nursing infants; sexual activity apparatus, devices and articles.
(3) Outdoor portable lighting products, namely, headlamps; Portable headlamps; Light strobes for use by runners; Apparatus and installations for lighting, heating, cooling, steam generating, cooking, drying, ventilating, water supply and sanitary purposes.
(4) Gym towels; golf towels; Magnetic golf towels; Textiles and substitutes for textiles; household linen; curtains of textile or plastic.
Examples provide image quality assessment using computer vision (CV) object detection and recognition with depth estimation. An image quality manager obtains image quality analysis data, including CV object recognition results and depth information for objects of interest. The image analysis data is analyzed to identify image quality issues present in the images. The type of image quality issues includes object detection type, depth type, and payload type issues, such as images with inconsistent distance from an object of interest, images in which the object of interest is either too close or too far away, images having excessive time gaps between images, payloads with too few images, payloads without object detections, etc. Image quality feedback identifying the type of image quality issues detected is generated and provided to users. The system uses image quality feedback to retrain the CV models. The feedback optionally includes suggested actions for resolving the detected issues.
G06T 7/55 - Depth or shape recovery from multiple images
G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
Example implementations relate to predicting fulfillment times for user requests. In an example, a user request including item data, a fulfillment location, and a provisional fulfillment time is received by a system. The system requests, via a fulfillment predictor, fulfillment data for the fulfillment location. The fulfillment data including at least a fulfillment order for the user request and ongoing fulfillment orders for the user request. The system, in response to receiving the fulfillment data, determines, by the fulfillment predictor, a predicted fulfillment time for the user request. The system determines whether a difference between the provisional fulfillment time and the predicted fulfillment time is within a fulfillment time threshold and, in accordance with a determination that the difference between the provisional fulfillment time and the predicted fulfillment time is outside the fulfillment time threshold, transmits the predicted fulfillment time to at least one computing device.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06Q 10/087 - Inventory or stock management, e.g. order filling, procurement or balancing against orders
05 - Pharmaceutical, veterinary and sanitary products
29 - Meat, dairy products, prepared or preserved foods
30 - Basic staples, tea, coffee, baked goods and confectionery
31 - Agricultural products; live animals
32 - Beers; non-alcoholic beverages
Goods & Services
(1) Food for babies; Pharmaceuticals, medical and veterinary preparations; sanitary preparations for medical purposes; dietetic food and substances adapted for medical or veterinary purposes; dietary supplements for human beings and animals; adhesive plasters, materials for dressings; material for filling teeth, dental wax; disinfectants; preparations for destroying vermin; fungicides, herbicides.
(2) Meat, fish, poultry and game; meat extracts; preserved, frozen, dried and cooked fruits and vegetables; jellies, jams, compotes; eggs; milk, cheese, butter, yogurt and other milk products; oils and fats for food; nut butter, potato chips; Meat extracts for culinary purposes; preserved, frozen, dried and cooked fruits, vegetables and seaweeds.
(3) Coffee, tea, cocoa and substitutes therefor; rice, pasta and noodles; tapioca and sago; flour and preparations made from cereals; bread, pastries and confectionery; chocolate; ice cream, sorbets and other edible ices; sugar, honey, treacle; yeast, baking-powder; salt, seasonings, spices, preserved herbs; vinegar, sauces and other condiments; ice (frozen water).
(4) Raw nuts; Raw and unprocessed agricultural, aquacultural, horticultural and forestry products; raw and unprocessed grains and seeds; fresh fruits and vegetables, fresh herbs; natural plants and flowers; bulbs, seedlings and seeds for planting; live animals; foodstuffs and beverages for animals; malt.
(5) Beers; non-alcoholic beverages; mineral and aerated waters; fruit beverages and fruit juices; syrups and other preparations for making non-alcoholic beverages; sparkling water; expressly excluding vegetable-based food drinking products.
