Abstract: Disclosed are a device of complex gas mixture detection based on optical-path-adjustable spectrum detection and a method therefor, and the device includes: a light source configured for generating an incident beam and emitting the incident beam into an optical gas cell; the optical gas cell, including a cavity configured for accommodating a gas sample, and a reflection module group configured for reflecting the incident beam and a track arranged in the cavity, where the track is consistent with a light path of the light beam in the cavity; a detector module that is connected with the track in a relatively movable manner and is configured for receiving light beams and obtaining spectral data, where an optical path is changed by moving the detector module relative to the track; and a data acquisition unit that is configured for acquiring the spectral data obtained by the detector module.

Abstract: The present invention provides a femtosecond pulse laser modulator and a miniature two-photon microscopic imaging device. The femtosecond pulse laser modulator includes a negative dispersion light path and a positive dispersion light path, wherein the negative dispersion light path includes a laser input fiber, which is configured to transmit laser compensated for through prechirp; the positive dispersion light path is located between a femtosecond pulse laser and the negative dispersion light path, and is configured to compensate for, through prechirp, negative dispersion of the laser produced in the laser input fiber. The femtosecond laser modulator provided in the present invention provides distortion-free transmission for the femtosecond pulse laser with a center wavelength in 920 nm, and effectively excites commonly used biological indicators.

Abstract: Disclosed are a method and a system for scheduling a task in cloud computing. The feature information of the task is parameterized; the task is classified; the best working node is obtained by computation through a Bacteria Foraging Optimization Algorithm (BFOA) according to the classification result; and the best working node is matched with the task. Obviously, the BFOA is adopted to implement task scheduling and resource allocation in cloud computing, so that the cloud computing has the advantages of group, intelligent and parallel search, simplicity in escaping from a local minimum and the like for the scheduling of a user task group, is favourable for keeping the diversity of the task group in the cloud computing, can meet the requirement of the user better, and improves the degree of satisfaction of user experience.

Abstract: Disclosed are a method and a system for scheduling a task in cloud computing. The feature information of the task is parameterized; the task is classified; the best working node is obtained by computation through a Bacteria Foraging Optimization Algorithm (BFOA) according to the classification result; and the best working node is matched with the task. Obviously, the BFOA is adopted to implement task scheduling and resource allocation in cloud computing, so that the cloud computing has the advantages of group, intelligent and parallel search, simplicity in escaping from a local minimum and the like for the scheduling of a user task group, is favourable for keeping the diversity of the task group in the cloud computing, can meet the requirement of the user better, and improves the degree of satisfaction of user experience.