A method includes receiving, by a client application executing on a mobile computing device, livestock information, the livestock information including one or more of information about a livestock facility or information about items of livestock at the livestock facility. The method also includes capturing, by the client application, images of the items of livestock at the livestock facility. Further, the method includes determining an identification of one of the items of livestock based at least partially on an analysis of one or more of the images that were captured. The method includes transmitting, by the client application, the livestock information, the images to an insurance server system, and the identification.

A method includes receiving, by a client application executing on a mobile computing device, livestock information, the livestock information including one or more of information about a livestock facility or information about items of livestock at the livestock facility. The method also includes capturing, by the client application, images of the items of livestock at the livestock facility. Further, the method includes determining an identification of one of the items of livestock based at least partially on an analysis of one or more of the images that were captured. The method includes transmitting, by the client application, the livestock information, the images to an insurance server system, and the identification.

A computer-implemented method includes: receiving, using a processor, a decimal floating point number; and using a floating point unit within the processor to convert the decimal floating point number into a binary coded decimal number, wherein the floating point unit starts a conversion loop subsequent to a rounding loop starting, wherein the rounding loop and the conversion loop run in parallel once started.

A computer-implemented method includes: receiving, using a processor, a decimal floating point number; and using a floating point unit within the processor to convert the decimal floating point number into a binary coded decimal number, wherein the floating point unit starts a conversion loop subsequent to a rounding loop starting, wherein the rounding loop and the conversion loop run in parallel once started.

Embodiments of the invention are directed to a computer-implemented method of for parallel conversion to binary coded decimal format. The method includes receiving, by a floating point unit (FPU), a value in binary floating point (BFP) format. The BFP value includes an integer part and a fractional part. The FPU converts the BFP value to a binary coded decimal (BCD) value. In parallel to converting the BFP value to a BCD value, the FPU performs a rounding operation on the BFP value. The FPU receives the rounding information and operates on the BCD value accordingly.

Embodiments of the invention are directed to a computer-implemented method of for parallel conversion to binary coded decimal format. The method includes receiving, by a floating point unit (FPU), a value in binary floating point (BFP) format. The BFP value includes an integer part and a fractional part. The FPU converts the BFP value to a binary coded decimal (BCD) value. In parallel to converting the BFP value to a BCD value, the FPU performs a rounding operation on the BFP value. The FPU receives the rounding information and operates on the BCD value accordingly.

Edge-sensitive, state-based single flux quantum (SFQ) based circuitry and related methods convert return-to-zero (RZ) or non-return-to-zero (NRZ) encoded SFQ-pulse-based signals to bilevel NRZ phase signals that can subsequently be converted to bilevel voltage signals by an output amplifier (OA). The SFQ-based circuitry can be integrated with a current amplification stage of a driver that can be coupled to a stage of the OA. The SFQ-based circuitry can be made to be compatible with RQL-encoded input signals that can be either RZ or NRZ. The SFQ-based circuitry can thus be compatible with both wave-pipelined (WPL) and phase-mode (PML) RQL circuitry. Because the SFQ-based circuitry and related methods are edge-sensitive and state-based, they can function at system clock rates in excess of 1 GHz with reduced glitches and improved bit error rates as compared to other superconducting RZ-NRZ conversion circuitry and methods.

A computer-implemented method includes: receiving, using a processor, a decimal floating point number; and using a floating point unit within the processor to convert the decimal floating point number into a binary coded decimal number, wherein the floating point unit starts a conversion loop subsequent to a rounding loop starting, wherein the rounding loop and the conversion loop run in parallel once started.

A computer-implemented method includes: receiving, using a processor, a decimal floating point number; and using a floating point unit within the processor to convert the decimal floating point number into a binary coded decimal number, wherein the floating point unit starts a conversion loop subsequent to a rounding loop starting, wherein the rounding loop and the conversion loop run in parallel once started.

Embodiments of the invention are directed to a computer-implemented method of for parallel conversion to binary coded decimal format. The method includes receiving, by a floating point unit (FPU), a value in binary floating point (BFP) format. The BFP value includes an integer part and a fractional part. The FPU converts the BFP value to a binary coded decimal (BCD) value. In parallel to converting the BFP value to a BCD value, the FPU performs a rounding operation on the BFP value. The FPU receives the rounding information and operates on the BCD value accordingly.