Abstract: A method for multiple-round driver selection performed by a computing system, the method including receiving a service request from a user device; identifying a plurality of driver candidates based in part on the service request, such that each of the plurality of driver candidates has driver data; for each of the plurality of driver candidates, generating a score based on the driver data; grouping the plurality of driver candidates into a plurality of candidate groups based in part on the score of each of the plurality of driver candidates; iteratively transmitting a job request to each candidate group of the plurality of candidate groups until one or more job acceptance is received in response to the job request, such that the job request is transmitted to all drivers in each candidate group; selecting one of the one or more job acceptances; and assigning the service request to the driver associated with the selected one of the one or more job acceptances.

Abstract: A method for multiple-round driver selection performed by a computing system, the method including receiving a service request from a user device; identifying a plurality of driver candidates based in part on the service request, such that each of the plurality of driver candidates has driver data; for each of the plurality of driver candidates, generating a score based on the driver data; grouping the plurality of driver candidates into a plurality of candidate groups based in part on the score of each of the plurality of driver candidates; iteratively transmitting a job request to each candidate group of the plurality of candidate groups until one or more job acceptance is received in response to the job request, such that the job request is transmitted to all drivers in each candidate group; selecting one of the one or more job acceptances; and assigning the service request to the driver associated with the selected one of the one or more job acceptances.

Abstract: A method and system for sound-induced sleep is provided. The method includes detecting brainwave signals of a subject. The method further includes analyzing the brainwave signals to determine a current sleepy state of the subject and selecting a sound in response to the current sleepy state based on a quantified association index between the brainwave signals and acoustical features of the sound. The method further more includes playing the sound to the subject.

Abstract: A method for deriving optimal discriminating features indicative of a subject state when the subject listens to one of a set of musical pieces, comprising a step of extracting frequency features from the subject's EEG signal when the subject is in a first subject state and a second subject state, the frequency features being extracted from more than one frequency band in one set of time segments; and identifying optimal discriminating features from the extracted frequency features, the optimal discriminating features indicative of characteristics of the EEG signal when the subject is in the first subject state and the second subject state, wherein one of the first subject state and the second subject state indicates that the subject likes a musical piece while the other state indicates that the subject does not like the musical piece.

Abstract: A method and system for sound-induced sleep is provided. The method includes detecting brainwave signals of a subject. The method further includes analyzing the brainwave signals to determine a current sleepy state of the subject and selecting a sound in response to the current sleepy state based on a quantified association index between the brainwave signals and acoustical features of the sound. The method further more includes playing the sound to the subject.

Abstract: A method for deriving optimal discriminating features indicative of a subject state when the subject listens to one of a set of musical pieces, comprising a step of extracting frequency features from the subject's EEG signal when the subject is in a first subject state and a second subject state, the frequency features being extracted from more than one frequency band in one set of time segments; and identifying optimal discriminating features from the extracted frequency features, the optimal discriminating features indicative of characteristics of the EEG signal when the subject is in the first subject state and the second subject state, wherein one of the first subject state and the second subject state indicates that the subject likes a musical piece while the other state indicates that the subject does not like the musical piece.