Abstract:
The disclosure discloses a registration method or an unregistration method for a home information machine and a home information machine thereof, to solve the problem of low security and reliability in the prior art when a Portable Part (PP) machine is registered on the home information machine. The registration method comprises: a Fixed Part (FP) module of the home information machine receives a registration command and first verification information sent by a Mobile Internet Device (MID) module of the home information machine, wherein the first verification information is used to verify verification information input by the PP machine to be registered; the FP module enters a registration state, and receives a registration request and second verification information sent by the PP machine to be registered; the FP module verifies the second verification information by the first verification information, determines whether the registration of the PP machine to be registered is successful according to the verification result, and exits the registration state when determining that the registration of the PP machine to be registered is successful. When the technical solution of the disclosure is used, security and reliability during the registration process of the PP machine can be improved.
Abstract:
A dual-energy material identification method and system with under-sampling is disclosed. A CT image of the object is obtained by using the CT image reconstruction method, while the dual-energy projections are under-sampled to obtain a few samples. Photoelectric coefficient integral and Compton coefficient integral are computed from these dual-energy projection data. The CT image is segmented into regions with image processing technique, and the regions are labeled. The length by which a few dual-energy rays crosses each labeled region is computed, and an equation system is established with dual-energy preprocessing dual-effect decomposition reconstruction method to compute Photoelectric coefficient and Compton coefficient, and then atomic number and electron density of material in each region are computed. The material of the object can be identified with the atomic number.
Abstract:
Negative Poisson's ratio (NPR) or auxetic are used to make lightweight wheels and runflat tires. The NPR tires can be tailored and functionally-designed to optimally meet the runflat requirements for both military and commercial vehicles. NPR-runflat tires may be fabricated using standard materials and simple manufacturing processes, resulting in low-cost and high-volume production. In preferred embodiments the runflat tire designs are fully compatible with Central Tire Inflation Systems (CTIS), while providing a performance equivalent to current military vehicle solutions but at half the weight. An auxetic wheel according to the invention comprises a line defining an axis of rotation; and a plurality of concentric rings of unit cells surrounding the axis, each unit cell being constructed of a plurality of members defining a Negative Poisson's Ratio (NPR) structure. The outermost ring of unit cells is arranged to facilitate rolling terrain contact, such that the stiffness of the structure in the localized region of loading due to terrain contact increases as the wheel rotates. A layer of material may be disposed between the concentric rings of unit cells which in preferred embodiments comprise a plurality of nested-V shapes. A cover may be provided over the outermost ring of unit cells forming a tire which may, or may not, be inflated.
Abstract:
A signal classifying method and apparatus are disclosed. The signal classifying method includes: obtaining a spectrum fluctuation parameter of a current signal frame determined as a foreground frame, and buffering the spectrum fluctuation parameter; obtaining a spectrum fluctuation variance of the current signal frame according to spectrum fluctuation parameters of all buffered signal frames, and buffering the spectrum fluctuation variance; and calculating a ratio of signal frames whose spectrum fluctuation variance is above or equal to a first threshold to all the buffered signal frames, and determining the current signal frame as a speech frame if the ratio is above or equal to a second threshold or determining the current signal frame as a music frame if the ratio is below the second threshold. In the embodiments of the present invention, the spectrum fluctuation variance of the signal is used as a parameter for classifying the signals, and a local statistical method is applied to decide the type of the signal. Therefore, the signals are classified with few parameters, simple logical relations and low complexity.
Abstract:
A signal identifying method includes obtaining signal characteristics of a current frame of input signals; deciding, according to the signal characteristics of the current frame and updated signal characteristics of a background signal frame before the current frame, whether the current frame is a background signal frame; detecting whether the current frame serving as a background signal frame is in a first type signal state; and adjusting a signal classification decision threshold according to whether the current frame serving as a background signal frame is in the first type signal state to enhance the speech signal identification capability.
Abstract:
Embodiments of the present invention relate to a signal identifying method, including: obtaining signal characteristics of a current frame of input signals; deciding, according to the signal characteristics of the current frame and updated signal characteristics of a background signal frame before the current frame, whether the current frame is a background signal frame; detecting whether the current frame serving as a background signal frame is in a first type signal state; and adjusting a signal classification decision threshold according to whether the current frame serving as a background signal frame is in the first type signal state to enhance the speech signal identification capability.
Abstract:
A dual-energy material identification method and system with under-sampling is disclosed. A CT image of the object is obtained by using the CT image reconstruction method, while the dual-energy projections are under-sampled to obtain a few samples. Photoelectric coefficient integral and Compton coefficient integral are computed from these dual-energy projection data. The CT image is segmented into regions with image processing technique, and the regions are labeled. The length by which a few dual-energy rays crosses each labeled region is computed, and an equation system is established with dual-energy preprocessing dual-effect decomposition reconstruction method to compute Photoelectric coefficient and Compton coefficient, and then atomic number and electron density of material in each region are computed. The material of the object can be identified with the atomic number.
Abstract:
A signal classifying method and apparatus are disclosed. The signal classifying method includes: obtaining a spectrum fluctuation parameter of a current signal frame determined as a foreground frame, and buffering the spectrum fluctuation parameter; obtaining a spectrum fluctuation variance of the current signal frame according to spectrum fluctuation parameters of all buffered signal frames, and buffering the spectrum fluctuation variance; and calculating a ratio of signal frames whose spectrum fluctuation variance is above or equal to a first threshold to all the buffered signal frames, and determining the current signal frame as a speech frame if the ratio is above or equal to a second threshold or determining the current signal frame as a music frame if the ratio is below the second threshold. In the embodiments of the present invention, the spectrum fluctuation variance of the signal is used as a parameter for classifying the signals, and a local statistical method is applied to decide the type of the signal. Therefore, the signals are classified with few parameters, simple logical relations and low complexity.
Abstract:
Negative Poisson's ratio (NPR) or auxetic are used to make lightweight wheels and runflat tires. The NPR tires can be tailored and functionally-designed to optimally meet the runflat requirements for both military and commercial vehicles. NPR-runflat tires may be fabricated using standard materials and simple manufacturing processes, resulting in low-cost and high-volume production. In preferred embodiments the runflat tire designs are fully compatible with Central Tire Inflation Systems (CTIS), while providing a performance equivalent to current military vehicle solutions but at half the weight. An auxetic wheel according to the invention comprises a line defining an axis of rotation; and a plurality of concentric rings of unit cells surrounding the axis, each unit cell being constructed of a plurality of members defining a Negative Poisson's Ratio (NPR) structure. The outermost ring of unit cells is arranged to facilitate rolling terrain contact, such that the stiffness of the structure in the localized region of loading due to terrain contact increases as the wheel rotates. A layer of material may be disposed between the concentric rings of unit cells which in preferred embodiments comprise a plurality of nested-V shapes. A cover may be provided over the outermost ring of unit cells forming a tire which may, or may not, be inflated.
Abstract:
Systems, methods, and devices for simultaneously distributing mass notifications to multiple users. A mass notification system receives input data and, based on this input data, creates notifications for mass distribution. The notifications are then transmitted to computing devices used by the users who are to be notified.