Abstract: A method and an apparatus for camera-free light field video processing with all-optical neural network are disclosed. The method includes: mapping the light field video by a digital micro-mirror device (DMD) and an optical fiber coupler, a two-dimensional 2D spatial optical signal into a one-dimensional 1D input optical signal; realizing a multiply-accumulate computing model in a structure of all-optical recurrent neural network structure, and processing the 1D input signal to obtain the processed signal; and receiving the processed signal and outputting an electronic signal by a photodetector, or receiving the processed signal by a relay optical fiber for relay transmission of the processed signal. The method and system here realize light field video processing without the use of a camera and the whole system is all-optical, thus possessing the advantage in computing speed and energy-efficiency.

Abstract: A method for setting a device identifier comprises: obtaining a first APP (Application) list of a target device; performing matching between the first APP list and a second APP list to determine a number of identical APPs in both the first APP list and the second APP list; determining whether the determined number of identical APPs reaches a pre-set threshold; and when the determined number of identical APPs reaches the pre-set threshold, setting a device identifier corresponding to the second APP list as the target device's device identifier.

Abstract: A Mobile-Assisted edge computing framework including: one or more requests to be processed; an operator configured to assign the one or more requests to a static edge node; and a cloud configured to cache and pre-fetch services for the one or more requests; wherein the one or more requests include handled requests and unhandled requests, the static edge node is configured to process the handled requests, and one or more mobile edge nodes are configured to process the unhandled requests; and wherein the static edge node is configured to auction the unhandled requests to the one or more mobile edge nodes, the auction including: generating a candidate set of the one or more mobile edge nodes; assigning an unhandled request to a target mobile edge node of the candidate set; and processing the unhandled request via the target mobile edge node.

Abstract: A method for assigning a device fingerprint to a target device is provided. The method includes acquiring first attributes of the target device, the first attributes including at least one browser plug-in or one font; calculating a correlation value with respect the first attributes of the target device and second attributes of at least one second device having a device fingerprint stored in a device library. The first attributes correspond to the second attributes. The method further includes: if the correlation value is greater than or equal to a pre-determined threshold value, assigning the device fingerprint of the at least one second device to the target device; and if the correlation value is smaller than the pre-determined threshold value, storing the first attributes of the target device to the device library and assigning a new device fingerprint to the target device.

Abstract: A method for setting a device identifier comprises: obtaining a first APP (Application) list of a target device; performing matching between the first APP list and a second APP list to determine a number of identical APPs in both the first APP list and the second APP list; determining whether the determined number of identical APPs reaches a pre-set threshold; and when the determined number of identical APPs reaches the pre-set threshold, setting a device identifier corresponding to the second APP list as the target device's device identifier.

Abstract: A method for assigning a device fingerprint to a target device is provided. The method includes acquiring first attributes of the target device, the first attributes including at least one browser plug-in or one font; calculating a correlation value with respect the first attributes of the target device and second attributes of at least one second device having a device fingerprint stored in a device library. The first attributes correspond to the second attributes. The method further includes: if the correlation value is greater than or equal to a pre-determined threshold value, assigning the device fingerprint of the at least one second device to the target device; and if the correlation value is smaller than the pre-determined threshold value, storing the first attributes of the target device to the device library and assigning a new device fingerprint to the target device.