Abstract: The embodiment of the present disclosure provides a method for crystallizing compound sugar solution of xylose and sucrose, including: introducing a mixed solution of sucrose crystals, xylose crystals and water into a crystallization device, setting a stirring speed in a range of 60 rpm-120 rpm, a temperature in a range of 75° C.-80° C., a vacuum pump pressure in a range of 50 mbar-200 mbar, evaporating the mixed solution until a Brix value of the mixed solution reaches a range of 78 Brix-81 Brix, and stopping the vacuum evaporation, adjusting the temperature to a range of 70° C.-75° C., dropwise adding food-grade isopropanol solution or ethanol solution to the evaporated mixed solution, adding sucrose seed crystals, and continuing stirring to obtain a solution, when small seed crystals grow in the solution, dropping the temperature to a range of 40° C.-60° C. at a rate of 10° C./h, and then stirring for 6 h to obtain the mixed sugar solution; centrifuging and drying at 40° C.-60° C.

Abstract: A method and system for control of BTM of electric drive bulldozers based on deep learning includes: obtaining a micro-load segment at the current moment in a load spectrum and predicting a micro-load segment at the next moment using a Markov chain model; carrying out a weighting calculation of the segment using the segment at the current moment and a corresponding weight thereof with the predicted segment and a corresponding weight thereof, and then calculating motor speed, motor torque, and a state of charge (SOC) of battery under the segment after being weighted; and taking a real-time battery outlet water temperature, occupant cabin temperature, occupant cabin target temperature and ambient temperature as well as the motor speed, motor torque and SOC, so as to obtain a control strategy of the electric compressor speed, and further obtain a method for control of BTM of the electric drive bulldozer.

Abstract: The present invention provides RNA aptamer probes for detection of target genetic material and methods for using the probes. In some embodiments, the invention provides devices for the detection of the target genetic material using the probes of the preset invention. In some embodiments, the invention provides methods for designing RNA aptamer probes for detection of target genetic material. In some embodiments, the target genetic material is genetic material from a pathogen. In some embodiments the pathogen is influenza virus. In some embodiments, the devices of the present invention may be used outside of laboratory setting and do not require any specialized skills. In some embodiments, the devices of the present invention are used in conjunction with a mobile phone camera.

Abstract: Methods, devices and systems for improving travel planning, booking and viewing using an integrated travel platform are described. An example method includes presenting, by an integrated electronic travel platform to a user, a profile comprising a plurality of fields to receive a set of parameters associated with a trip that comprises a plurality of modalities, analyzing, using a shared ontology data structure, the profile to determine a plurality of options for each of the plurality of modalities, wherein each of the plurality of options conforms to the set of parameters for the corresponding modality, presenting, to the user, the plurality of options, receiving, from the user, a plurality of selections corresponding to one option from the plurality of options for each of the plurality of modalities, performing, while remaining within the integrated electronic travel platform, a booking operation for each of the plurality of selections.

Abstract: A method of dynamically modifying target selection with a neural network includes dynamically modifying a selection function by controlling an amount of imbalance of connections in the neural network. A selected neuron represents one of multiple candidate targets.

Abstract: Methods and devices of various embodiments provide enhanced location services by leveraging a system of beacon devices each broadcasting data that is useful in calculating locations and report of the trustworthiness of neighbor beacon devices. Various embodiments include a method performed by a beacon device that may include obtaining location data using a first functionality, evaluating sensor data to identify a breach of trust condition at the beacon device, generating authentication data that indicates any identified breach of trust condition, receiving one or more neighbor beacon broadcast messages using a second functionality, determining whether the one or more neighbor beacon broadcast messages include trustworthy location data, and broadcasting an outgoing broadcast message that includes the obtained location data, timing data, the generated authentication data, and data indicating whether the one or more neighbor beacon broadcast messages include trustworthy location data.

Abstract: Various embodiments provide methods for controlling landings of a UAV in a landing zone including a plurality of landing bays. Various embodiments include a method implemented on a computing device for receiving continuous real-time sensor data from a transceiver and from sensors onboard the UAV, and detecting a target landing bay within the plurality of landing bays within the landing zone that is available for landing based on the continuous real-time sensor data. Orientation and position coordinates for landing in the target landing bay may be calculated based on the continuous real-time sensor data. Information regarding positions and flight vectors of a plurality of autonomous UAVs may be obtained, and a flight plan for landing in the target landing bay may be generated based on the orientation and the position coordinates, positions and flight vectors of the plurality of autonomous UAVs and a current orientation and position of the UAV.

Abstract: Various embodiments provide methods for controlling landings of a UAV in a landing zone including a plurality of landing bays. Various embodiments include a method implemented on a computing device for receiving continuous real-time sensor data from a transceiver and from sensors onboard the UAV, and detecting a target landing bay within the plurality of landing bays within the landing zone that is available for landing based on the continuous real-time sensor data. Orientation and position coordinates for landing in the target landing bay may be calculated based on the continuous real-time sensor data. Information regarding positions and flight vectors of a plurality of autonomous UAVs may be obtained, and a flight plan for landing in the target landing bay may be generated based on the orientation and the position coordinates, positions and flight vectors of the plurality of autonomous UAVs and a current orientation and position of the UAV.

Abstract: Methods and apparatus are provided for training a neural device having an artificial nervous system by modulating at least one training parameter during the training. One example method for training a neural device having an artificial nervous system generally includes observing the neural device in a training environment and modulating at least one training parameter based at least in part on the observing. For example, the training apparatus described herein may modify the neural device's internal learning mechanisms (e.g., spike rate, learning rate, neuromodulators, sensor sensitivity, etc.) and/or the training environment's stimuli (e.g., move a flame closer to the device, make the scene darker, etc.). In this manner, the speed with which the neural device is trained (i.e., the training rate) may be significantly increased compared to conventional neural device training systems.

Abstract: Methods and devices of various embodiments provide enhanced location services by leveraging a system of beacon devices each broadcasting data that is useful in calculating locations and report of the trustworthiness of neighbor beacon devices. Various embodiments include a method performed by a beacon device that may include obtaining location data using a first functionality, evaluating sensor data to identify a breach of trust condition at the beacon device, generating authentication data that indicates any identified breach of trust condition, receiving one or more neighbor beacon broadcast messages using a second functionality, determining whether the one or more neighbor beacon broadcast messages include trustworthy location data, and broadcasting an outgoing broadcast message that includes the obtained location data, timing data, the generated authentication data, and data indicating whether the one or more neighbor beacon broadcast messages include trustworthy location data.

Abstract: Methods and apparatus are provided for effecting modulation using global scalar values in a spiking neural network. One example method for operating an artificial nervous system generally includes determining one or more updated values for artificial neuromodulators to be used by a plurality of entities in a neuron model and providing the updated values to the plurality of entities.

Abstract: Certain embodiments of the present disclosure relate to a technique for image reconstruction that employs cascaded over-complete dictionaries (i.e., collections of bases) for extracting features and building representations for images at different reconstruction levels. Each dictionary on a different reconstruction level can be learned and optimized for the purpose of capturing either generic or discriminative features. By finding sparse representations through the cascaded dictionaries, an image can be reconstructed and recognized.

Abstract: A method for configuring long short-term memory (LSTM) in a spiking neural network includes decoding input spikes into analog values within the LSTM. The method further includes implementing the LSTM based on an encoded representation of the analog values. The implementing can include encoding the analog values using base expansive coding, rate coding, latency coding or synaptic weight coding.

Abstract: Certain embodiments of the present disclosure relate to a technique for image reconstruction that employs cascaded over-complete dictionaries (i.e., collections of bases) for extracting features and building representations for images at different reconstruction levels. Each dictionary on a different reconstruction level can be learned and optimized for the purpose of capturing either generic or discriminative features. By finding sparse representations through the cascaded dictionaries, an image can be reconstructed and recognized.

Abstract: A method for maintaining a state variable in a synapse of a neural network includes maintaining a state variable in an axon. The state variable in the axon may be updated based on an occurrence of a first predetermined event. The method also includes updating the state variable in the synapse based on the state variable in the axon and an occurrence of a second predetermined event.

Abstract: Differential encoding in a neural network includes predicting an activation value for a neuron in the neural network based on at least one previous activation value for the neuron. The encoding further includes encoding a value based on a difference between the predicted activation value and an actual activation value for the neuron in the neural network.

Abstract: A method of dynamically modifying target selection with a neural network includes dynamically modifying a selection function by controlling an amount of imbalance of connections in the neural network. A selected neuron represents one of multiple candidate targets.

Abstract: A method for transmitting values in a neural network includes obtaining a parameter value. The method also includes encoding the parameter value based on at least one value used by a neuron. The encoding is based on a spike to be transmitted via a spike channel.

Abstract: Values are synchronized across processing blocks in a neural network by encoding spikes in a first processing block with a value to be shared across the neural network. The spikes may be transmitted to a second processing block in the neural network via an interblock interface. The received spikes are decoded in the second processing block so as to generate a value that is synchronized with the value of the first processing block.