Abstract: An embodiment includes an orthopedic fusion system comprising: a cage; a curved first channel coupling a lateral wall of the cage to a superior surface of the cage; a curved second channel coupling the lateral wall of the cage to an inferior surface of the cage; a third channel coupling the superior surface of the cage to the inferior surface of the cage; a curved first anchor configured to slide within the first channel; a curved second anchor configured to slide within the second channel; and a resilient member comprising a resilient first arm that projects across a portion of the first channel and a resilient second arm that projects across a portion of the second channel. Other embodiments are described herein.

Abstract: A buy-online pickup-in-store (BOPIS) order at risk of abandonment is saved by converting the order to same-day delivery. A risk deadline is established using a combination of cognitive prediction, a customer-specific time frame, order constraints, and real-time data. The cognitive prediction uses a customer profile having historical data pertaining to previous BOPIS orders from this customer. If the product is not picked up by the risk deadline, a check is made to see if same-day delivery is feasible. If so, a notification is transmitted to the customer with proposed delivery details. The notification can be sent at an optimal time based on previous notifications sent to the customer and time constraints related to the order, and using an optimal communication channel based on previous engagement rates with the customer over different communication channels. Once confirmation is received from the customer, the product is shipped, saving the sale.

Abstract: In an approach to digital twin enabled equipment diagnostics based on acoustic modeling, a real-time audio input of an asset is received from a mobile device. The real-time audio input is analyzed using one or more acoustic modeling algorithms to establish a deviation from a baseline, where the baseline is associated with a digital twin of the asset. Responsive to determining the deviation from the baseline exceeds a predetermined threshold, the user is iteratively directed to move the mobile device until a stopping criteria is met.

Abstract: In order to detect possible damage to a delivered product, a set of first images of the product is created prior to delivery which are used to generate a first 3D photogrammetry model, and a set of second electronic images are created after delivery which are used to generate a second 3D photogrammetry model. The two models are then compared to determine whether there is a sufficient deviation to conclude the product has been damaged. The comparison is performed by a cognitive system trained with samples of before/after photogrammetry model pairs each associated with either a damaged condition or a not damaged condition. The baseline photogrammetry model is part of a blockchain record and the recipient photogrammetry model is added to the blockchain record. Intermediate photogrammetry models can also be built where there is more than one shipper along the delivery route to assign liability to the proper party.

Abstract: A buy-online pickup-in-store (BOPIS) order at risk of abandonment is saved by converting the order to same-day delivery. A risk deadline is established using a combination of cognitive prediction, a customer-specific time frame, order constraints, and real-time data. The cognitive prediction uses a customer profile having historical data pertaining to previous BOPIS orders from this customer. If the product is not picked up by the risk deadline, a check is made to see if same-day delivery is feasible. If so, a notification is transmitted to the customer with proposed delivery details. The notification can be sent at an optimal time based on previous notifications sent to the customer and time constraints related to the order, and using an optimal communication channel based on previous engagement rates with the customer over different communication channels. Once confirmation is received from the customer, the product is shipped, saving the sale.

Abstract: Buy-online pickup-in-store (BOPIS) order fulfillment is optimized by prioritizing BOPIS orders according to estimated pickup times. The pickup time for a given order is based on a customer profile and order details which can include product properties for a product in the order, characteristics of the physical store, and an order velocity indicative of an urgency of the customer in placing the order. The pickup times are estimated by a cognitive system trained with input samples comprised of historical BOPIS orders associated with actual pickup delays. The customer profiles include historical information regarding previous BOPIS orders from the customer such as a percentage of previous BOPIS orders actually picked up, and an average pickup delay for the previous BOPIS orders that were picked up. If any order pickup time is less than a predefined threshold, the system notifies the store associate with a warning that it is urgent.

Abstract: A computer system monitors network sites to provide expedited delivery services. Operation of a network site is monitored to determine that an item is being obtained from the network site. The network site is scraped to determine that the item is available at a physical location associated with the network site. A courier service is identified to transport the item from the physical location to the delivery location. Delivery of the item is enabled by the courier service to the delivery location. Embodiments of the present invention further include a method and program product for monitoring network sites to provide expedited delivery services in substantially the same manner described above.

Abstract: Aspects of the present disclosure relate to returns processing for product deliveries. An order can be received for a product by a customer. A return policy specifying a limited time frame in which an immediate return of the product can be completed can be determined. The customer is then permitted to complete the immediate return of the product by providing the product to the deliverer within the limited time frame.

Abstract: In an approach to digital twin enabled equipment diagnostics based on acoustic modeling, a real-time audio input of an asset is received from a mobile device. The real-time audio input is analyzed using one or more acoustic modeling algorithms to establish a deviation from a baseline, where the baseline is associated with a digital twin of the asset. Responsive to determining the deviation from the baseline exceeds a predetermined threshold, the user is iteratively directed to move the mobile device until a stopping criteria is met.

Abstract: In an approach to constructing a digital twin multi-dimensional model record using photogrammetry, a plurality of images of an asset are received from one or more mobile devices. A 3D model of the asset is constructed from the plurality of images. If the 3D model of the asset matches a digital twin record is determined.

Abstract: Buy-online pickup-in-store (BOPIS) order fulfillment is optimized by prioritizing BOPIS orders according to estimated pickup times. The pickup time for a given order is based on a customer profile and order details which can include product properties for a product in the order, characteristics of the physical store, and an order velocity indicative of an urgency of the customer in placing the order. The pickup times are estimated by a cognitive system trained with input samples comprised of historical BOPIS orders associated with actual pickup delays. The customer profiles include historical information regarding previous BOPIS orders from the customer such as a percentage of previous BOPIS orders actually picked up, and an average pickup delay for the previous BOPIS orders that were picked up. If any order pickup time is less than a predefined threshold, the system notifies the store associate with a warning that it is urgent.

Abstract: In order to detect possible damage to a delivered product, a set of first images of the product is created prior to delivery which are used to generate a first 3D photogrammetry model, and a set of second electronic images are created after delivery which are used to generate a second 3D photogrammetry model. The two models are then compared to determine whether there is a sufficient deviation to conclude the product has been damaged. The comparison is performed by a cognitive system trained with samples of before/after photogrammetry model pairs each associated with either a damaged condition or a not damaged condition. The baseline photogrammetry model is part of a blockchain record and the recipient photogrammetry model is added to the blockchain record. Intermediate photogrammetry models can also be built where there is more than one shipper along the delivery route to assign liability to the proper party.

Abstract: A buy-online pickup-in-store (BOPIS) order at risk of abandonment is saved by converting the order to same-day delivery. A risk deadline is established using a combination of cognitive prediction, a customer-specific time frame, order constraints, and real-time data. The cognitive prediction uses a customer profile having historical data pertaining to previous BOPIS orders from this customer. If the product is not picked up by the risk deadline, a check is made to see if same-day delivery is feasible. If so, a notification is transmitted to the customer with proposed delivery details. The notification can be sent at an optimal time based on previous notifications sent to the customer and time constraints related to the order, and using an optimal communication channel based on previous engagement rates with the customer over different communication channels. Once confirmation is received from the customer, the product is shipped, saving the sale.

Abstract: A buy-online pickup-in-store (BOPIS) order at risk of abandonment is saved by converting the order to same-day delivery. A risk deadline is established using a combination of cognitive prediction, a customer-specific time frame, order constraints, and real-time data. The cognitive prediction uses a customer profile having historical data pertaining to previous BOPIS orders from this customer. If the product is not picked up by the risk deadline, a check is made to see if same-day delivery is feasible. If so, a notification is transmitted to the customer with proposed delivery details. The notification can be sent at an optimal time based on previous notifications sent to the customer and time constraints related to the order, and using an optimal communication channel based on previous engagement rates with the customer over different communication channels. Once confirmation is received from the customer, the product is shipped, saving the sale.

Abstract: A method, computer system, and computer program product for in-transit package delivery is provided. The embodiment may determine whether package dimensions satisfy one or more preconfigured conditions. The embodiment may also, in response to determining the package dimensions satisfy the one or more preconfigured conditions, receive real-time location data and travel data for a user recipient and a courier. The embodiment may further determine a target delivery destination and target delivery time window. The embodiment may also transmit a delivery notification to the user recipient and the courier.

Abstract: A computer system monitors network sites to provide expedited delivery services. Operation of a network site is monitored to determine that an item is being obtained from the network site. The network site is scraped to determine that the item is available at a physical location associated with the network site. A courier service is identified to transport the item from the physical location to the delivery location. Delivery of the item is enabled by the courier service to the delivery location. Embodiments of the present invention further include a method and program product for monitoring network sites to provide expedited delivery services in substantially the same manner described above.

Abstract: A signal conditioner comprising several embodiments of transversal (FIR) filters that utilize symbol addressed multiplier lookup tables. In particular, five embodiments in accordance with the principles of the present invention are described. The present invention generates a predistorted waveform within the transversal filter that provides for compensation for the effects of nonlinear amplifiers and intersymbol interference. The present invention may be employed to digitally generate an arbitrary baseband waveform that represents a limited alphabet of symbols. The present invention dramatically simplifies the implementation of FIR filters where the application of the FIR filter is to provide a transversal filter function for waveforms that represent symbols. The degree of simplification is related to the number of bits that define the size of the symbol alphabet as compared to the number of bits required to adequately represent a digital sample of the waveform.

Abstract: A programmable PCM/TDM demultiplexer including an FA function unit including Frame Alignment Logic (FAL) hardware controlled by a Programmable Frame Alignment Controller (PFAC), and accompanied by a DECommutation and dejustification (DEC) function unit including Output Logic Hardware (OLH) controlled by a Programmable Decommutator Sequencer (PDS) controlled in turn by a Programmable Decommutator Sequencer Controller (PDSC).

Abstract: Adaptive equalizers and processing methods wherein data required to implement an adaptation algorithm is sampled at a rate that is significantly lower than the symbol rate. The adaptation algorithm is processed at this reduced rate, in that updated tap coefficients, sample timing errors and symbol clock error signals are computed at this reduced rate. An advantage of the adaptive equalizer and processing method of the present invention is that the adaptation algorithm may be implemented in equipment that operates at a clock rate that is much less then the symbol rate. In particular, the adaptation algorithm may be computed using software that is resident in inexpensive general purpose digital processor, such as a personal computer, for example.

Abstract: A fastener to retain at least two members together under spring tension including a bolt having a fastener head shaped with two lateral extending protrusions respectively forming two shoulders for engagement of an outside surface of one of the members to be secured together. An opening is provided through the members to be secured together and at least the opening through the latter-mentioned member which is to be engaged by the shoulders of the fastener head is generally contoured to the shape of the fastener head such that the fastened head freely passes through this opening in keyhole fashion and the bolt is turned so that the shoulders of the fastener head ride up onto this outside surface clamping the members together under spring tension. Lock recesses may be provided in the outside surface of the member closest to the fastener head to receive the shoulders of the fastener head in locking engagement.