Abstract: A multicomponent nanocapsule composition comprising a core particle, an oil phase encapsulating the core particle, and an aqueous phase in which the encapsulated core particle is suspended is provided. The porous particle includes a cationic surfactant encapsulated in a porous particle. The oil phase includes an anionic surfactant and a zwitterionic surfactant. A method of making a multicomponent nanocapsule composition is also provided. A method of treating a hydrocarbon-bearing formation with the multicomponent nanocapsule composition is provided. The method may include providing a multicomponent nanocapsule composition, introducing the multicomponent nanocapsule composition into the hydrocarbon-bearing formation, displacing hydrocarbons from the hydrocarbon-bearing formation by contacting the multicomponent nanocapsule composition with the hydrocarbons, and recovering the hydrocarbons.

Abstract: A multicomponent nanocapsule composition comprising a core particle, an oil phase encapsulating the core particle, and an aqueous phase in which the encapsulated core particle is suspended is provided. The porous particle includes a cationic surfactant encapsulated in a porous particle. The oil phase includes an anionic surfactant and a zwitterionic surfactant. A method of making a multicomponent nanocapsule composition is also provided. A method of treating a hydrocarbon-bearing formation with the multicomponent nanocapsule composition is provided. The method may include providing a multicomponent nanocapsule composition, introducing the multicomponent nanocapsule composition into the hydrocarbon-bearing formation, displacing hydrocarbons from the hydrocarbon-bearing formation by contacting the multicomponent nanocapsule composition with the hydrocarbons, and recovering the hydrocarbons.

Abstract: A multicomponent nanocapsule composition comprising a core particle, an oil phase encapsulating the core particle, and an aqueous phase in which the encapsulated core particle is suspended is provided. The porous particle includes a cationic surfactant encapsulated in a porous particle. The oil phase includes an anionic surfactant and a zwitterionic surfactant. A method of making a multicomponent nanocapsule composition is also provided. A method of treating a hydrocarbon-bearing formation with the multicomponent nanocapsule composition is provided. The method may include providing a multicomponent nanocapsule composition, introducing the multicomponent nanocapsule composition into the hydrocarbon-bearing formation, displacing hydrocarbons from the hydrocarbon-bearing formation by contacting the multicomponent nanocapsule composition with the hydrocarbons, and recovering the hydrocarbons.

Abstract: A method for storing input data in a flash memory. The method comprising generating a codeword by encoding the input data with an error correcting code and generating a shaped codeword by applying a shaping function to at least a part of the codeword. The shaping function comprising logically inverting every n-th occurrence of a bit associated with a high-charge storage state in the part of the codeword. The method further comprising writing the shaped codeword to the flash memory, generating an estimated shaped codeword by reading the flash memory, generating soft decision information for the estimated shaped codeword, and retrieving the input data by decoding the soft decision information using an error correcting code soft decoder.

Abstract: A method for storing input data in a flash memory. The method comprising generating a codeword by encoding the input data with an error correcting code and generating a shaped codeword by applying a shaping function to at least a part of the codeword. The shaping function comprising logically inverting every n-th occurrence of a bit associated with a high-charge storage state in the part of the codeword. The method further comprising writing the shaped codeword to the flash memory, generating an estimated shaped codeword by reading the flash memory, generating soft decision information for the estimated shaped codeword, and retrieving the input data by decoding the soft decision information using an error correcting code soft decoder.

Abstract: A method of soft decoding received signals. The method comprising defining quantisation intervals for a signal value range, determining a number of bits in each quantisation interval that are connected to unsatisfied constraints, providing, the number of bits in each quantisation interval that are connected to unsatisfied constraints, as an input to a trained model, wherein the trained model has been trained to cover an operational range of a device for soft decoding of signals, determining, using the trained model, a log likelihood ratio for each quantisation interval, and performing soft decoding using the log likelihood ratios.

Abstract: A method of soft decoding received signals. The method comprising defining quantisation intervals for a signal value range, determining a number of bits in each quantisation interval that are connected to unsatisfied constraints, providing, the number of bits in each quantisation interval that are connected to unsatisfied constraints, as an input to a trained model, wherein the trained model has been trained to cover an operational range of a device for soft decoding of signals, determining, using the trained model, a log likelihood ratio for each quantisation interval, and performing soft decoding using the log likelihood ratios.

Abstract: A method of generating soft decision detection parameters for a plurality of received signals. The method comprises defining a hard decision boundary and a plurality of quantisation intervals wherein each quantisation interval extends from the hard decision boundary by an interval distance, selecting a log likelihood value from a set of log likelihood values for each received signal based on the quantisation interval in which the received signal is detected, performing a soft decoding using a plurality of log likelihood values, adjusting the set of log likelihood values based on a result of the soft decoding, determining an error probability for a quantisation interval, comparing the error probability against a target error probability and adjusting the interval distance in order to obtain the target error probability.

Abstract: A method of storing a number of data values in a plurality of flash memory cells wherein each flash memory cell has a plurality of storage states and each data value is selected from a set of possible data values. The method comprises programming the number of data values to the plurality of flash memory cells using a mapping which uniquely associates each combination of storage states for the plurality of flash memory cells with a concatenated data value from a set of concatenated data values wherein the set of concatenated data values comprises a concatenated data value for every combination of possible data values for the number of data values, the concatenated data value has a position for each data value in the number of data values and the mapping is such that between adjacent storage states all but one data values are identical and each position in the concatenated data value changes the data value it represents between the same storage states on each flash memory cell.

Abstract: A method of decoding data stored in non-volatile memory in which each memory cell stores data by adopting one of a plurality of storage states.

Abstract: A method of generating soft decision detection parameters for a plurality of received signals. The method comprises defining a hard decision boundary and a plurality of quantisation intervals wherein each quantisation interval extends from the hard decision boundary by an interval distance, selecting a log likelihood value from a set of log likelihood values for each received signal based on the quantisation interval in which the received signal is detected, performing a soft decoding using a plurality of log likelihood values, adjusting the set of log likelihood values based on a result of the soft decoding, determining an error probability for a quantisation interval, comparing the error probability against a target error probability and adjusting the interval distance in order to obtain the target error probability.

Abstract: A method of soft decoding received signals. The method comprises defining quantisation intervals for a signal value range, determining a number of bits detected in each quantisation interval, a number of bits in each quantisation interval that are connected to unsatisfied constraints and a probability that the error correction code is unsatisfied, determining an overall bit error rate based on the probability that the error correction code is unsatisfied, determining a log likelihood ratio for each quantisation interval based on the overall bit error rate, the number of bits detected in each quantisation interval and the number of bits in each quantisation interval that are connected to unsatisfied constraints and performing soft decoding using the log likelihood ratios.

Abstract: A method of decoding data stored in non-volatile memory in which each memory cell stores data by adopting one of a plurality of storage states.

Abstract: A method of soft decoding received signals. The method comprises defining quantisation intervals for a signal value range, determining a number of bits detected in each quantisation interval, a number of bits in each quantisation interval that are connected to unsatisfied constraints and a probability that the error correction code is unsatisfied, determining an overall bit error rate based on the probability that the error correction code is unsatisfied, determining a log likelihood ratio for each quantisation interval based on the overall bit error rate, the number of bits detected in each quantisation interval and the number of bits in each quantisation interval that are connected to unsatisfied constraints and performing soft decoding using the log likelihood ratios.

Abstract: There is provided a device and method for demodulating a pulse amplitude modulated, hereinafter referred to as PAM, signal. The device comprises memory storing a set of boundaries of regions in which the log likelihood ratio, hereinafter referred to as LLR, for each bit to be determined is represented by a linear function of the received signal, along with the properties of the linear function for each bit for each region; and a controller. The controller is configured to: receive a PAM signal to be demodulated; determine which region the signal falls within; for each bit to be determined, retrieve the properties of the linear function for the LLR for the bit within the determined region and determine, from this linear function, the LLR value for the bit; and demodulate the signal based on the determined LLR values.

Abstract: A device for use in demodulating modulated signals by determining a value for a log likelihood ratio. The device has a storage device to store executable instructions and a processor to execute the instructions stored on the memory device.

Abstract: There is provided a device and method for demodulating a pulse amplitude modulated, hereinafter referred to as PAM, signal. The device comprises memory storing a set of boundaries of regions in which the log likelihood ratio, hereinafter referred to as LLR, for each bit to be determined is represented by a linear function of the received signal, along with the properties of the linear function for each bit for each region; and a controller. The controller is configured to: receive a PAM signal to be demodulated; determine which region the signal falls within; for each bit to be determined, retrieve the properties of the linear function for the LLR for the bit within the determined region and determine, from this linear function, the LLR value for the bit; and demodulate the signal based on the determined LLR values.

Abstract: A device for use in demodulating modulated signals by determining a value for a log likelihood ratio. The device has a storage device to store executable instructions and a processor to execute the instructions stored on the memory device.

Abstract: A semi-moist cranberry fruit product which is produced by slicing the fruit and through a sugar-spraying process in conjunction with wash-rinsing, surface air drying and vacuum drying or vacuum freeze-drying with sudden release of vacuum. The semi-moist fruit produced has an unusual appearance, consistent, texture and typical, but sweetened cranberry flavor and/or cranberry and orange flavor. Further collecting sweetened juice runoff from the fruit and drying the runoff to produce a taffy-like flavoring additive usable as a candy when the moisture content is reduced to 4-9% or reducing the moisture content to 1-2% and producing a crystalline flavoring additive.

Abstract: A semi-moist fruit product produced by a sugar-syrupping processing used in conjunction with wash-rinsing, surface air-drying and freeze-drying particularly adapted for use with blueberries, cherries and other similarly constituted fruits, whereby, liquid within the fruit is removed from the fruit through osmotic pressure exchange and is replaced by sugar molecules and an equilibrium is reached, thereafter through washing, rinsing and blotting of excess syrup, the process ensures independent individual dried fruit from sticking together, followed by freezing, vacuuming drying and packaging.