Abstract: A customer order prediction system can include a computing device configured to obtain customer order data characterizing a customer’s interaction with an electronic marketplace and to obtain environmental data characterizing at least one event expected to effect the customer’s ordering behavior. The computing device can be further configured to generate feature data based on the customer data and the environmental data wherein the feature data organizes the customer data and the environmental data based on characteristics of an order size estimation model. The computing device is also configured to determine a predicted customer order size using the order size estimation model and to adjust a delivery availability of the electronic marketplace based on the predicted order size.

Abstract: An approach generates a speed profile for one or more delivery locations. The speed profile corresponds to location data of a delivery order for a respective delivery location, and indicates a plurality of events associated with a movement of a delivery order to the respective delivery location. The approach generates, based on the speed profile and location data corresponding to the delivery order, feature data of the respective delivery location. The approach applies a machine learning model to the generated feature data to output a door-step time prediction for the respective delivery location. The door-step time prediction is based on a time difference between timestamps of two events of the plurality of events associated with the movement of the delivery order. The approach generates a planned delivery route for the one or more delivery locations, based on the one or more delivery locations and respective the door-step time predictions.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to providing personalized samples to customers. In some embodiments, a system for providing personalized samples to customers comprises an online shopping server configured to host an online shopping website and receive item selections indicating items to add to the customer's cart, a database configured to store a list of sample types, and a purchase likelihood estimator configured to receive the items to add to the customer's cart, determine an identity of the customer, determine customer traits, determine available sample types and traits associated with the available sample types, calculate a probability score based on the customer traits and the traits associated with each of the available sample types, and add, to the customer's cart based on the probability scores for each of the available sample types, one or more samples from the one or more of the available sample types.

Abstract: A delivery route planning system can include a computing device configured to obtain order delivery data that includes information characterizing delivery locations and delivery time windows associated with a first plurality of orders and to determine a delivery plan based on the order delivery data. The computing device can be further configured to identify recyclable time in the delivery time and to obtain supplemental order delivery data that includes information characterizing supplemental orders characterizing delivery locations and delivery time windows associated a second plurality of orders. The computing system can add one or more supplemental order deliveries from the second plurality of orders to the delivery plan based on the recyclable time, the supplemental order delivery data and at least one predetermined delivery constraint.

Abstract: Systems, apparatuses, and methods are provided herein for automated customer recurring payment processing. A central computer system being configured to detect a payment date for a recurring payment associated with a customer account, retrieve customer payment information, and submit the customer payment information to a bank system. In the event the authorization fails and an error code corresponds to a payment information error, the system automatically generates a notification message to the customer at the messaging server, submits the updated customer payment information to the bank system, and updates an account status of the customer account when a payment authorization is received from the bank system.

Abstract: Systems, apparatuses, and methods are provided herein for automated advance purchase payment processing. A central computer system being configured to select a set of customer orders with a scheduled purchase date that is n days from a current date to process payment. In the event that the authorization fails and an error code corresponds to a payment information error, the system automatically generates a notification message to the customer at the messaging server, submits the updated customer payment information to the bank system, and processes the advance product order on the scheduled purchase date for delivery.

Abstract: Systems, apparatuses, and methods are provided herein for automated customer recurring payment processing. A central computer system being configured to detect a payment date for a recurring payment associated with a customer account, retrieve customer payment information, and submit the customer payment information to a bank system. In the event the authorization fails and an error code corresponds to a payment information error, the system automatically generates a notification message to the customer at the messaging server, submits the updated customer payment information to the bank system, and updates an account status of the customer account when a payment authorization is received from the bank system.

Abstract: Method and system embodiments of the present invention control the ascorbate concentration in produce treatments and particularly are exemplified in fresh cut fruit and vegetable treatments via measured refractivity and/or electrical conductivity of, and/or calcium ions present in, the treatment solution.

Abstract: Method and system embodiments of the present invention control the ascorbate concentration in produce treatments and particularly are exemplified in fresh cut fruit and vegetable treatments via measured refractivity and/or electrical conductivity of, and/or calcium ions present in, the treatment solution.

Abstract: Method and system embodiments of the present invention control the ascorbate concentration in produce treatments and particularly are exemplified in fresh cut fruit and vegetable treatments via measured refractivity and/or electrical conductivity of, and/or calcium ions present in, the treatment solution.

Abstract: Method and system embodiments of the present invention control the ascorbate concentration in produce treatments and particularly are exemplified in fresh cut fruit and vegetable treatments via measured refractivity and/or electrical conductivity of, and/or calcium ions present in, the treatment solution.

Abstract: Method and system embodiments of the present invention control the ascorbate concentration in produce treatments and particularly are exemplified in fresh cut fruit and vegetable treatments via measured refractivity and/or electrical conductivity of, and/or calcium ions present in, the treatment solution.

Abstract: The present invention provides a microbial consortium containing three hyperthermophilic, barophilic, acidogenic, anaerobic bacterial strains for enhanced oil recovery from oil reservoirs where temperatures range from 70° C. to 90? C. The said microbial consortium is unique in producing a variety of metabolic products mainly CO2, methane, biosurfactant, volatile fatty acids and alcohols in the presence of specially designed nutrient medium. These metabolic products increase sweep efficiency of crude oil from oil bearing poles of rock formation. The present invention also provides a process for enhancing the oil recovery by in situ application of the said microbial consortium.