32results about How to "Reduce data complexity" patented technology

The invention belongs to the technical field of electric energy quality classification and identification, and discloses a voltage sag disturbance classification method based on a Long Shore-Term Memory algorithm. According to the method, firstly, voltage sag disturbance data are processed through a data processing layer, then feature values are extracted through two layers of LSTM networks, feature dimension reduction processing is conducted through a full connection layer, and finally classification recognition is conducted through a sigmoid network layer. The electric energy quality sag disturbance correlation characteristics are extracted through the deep learning algorithm, and the limitation of a classification recognition modeling method based on time domain, frequency domain, transformation domain and other physical characteristics in the complex power grid environment in the aspects of adaptability, algorithm efficiency and accuracy is overcome. By using the model, the defectsof tedious and complex extraction steps, possible loss of original characteristics of part of signals and the like in the traditional method can be well overcome; The defect that gradient explosion is likely to happen to a traditional recurrent neural network (RNN) is overcome, and high voltage sag disturbance recognition accuracy is achieved.

An interface between an RF processing section and a baseband processing section supports general purpose message transmission as well as satellite positioning system signal sample transmission between the RF processing section and the baseband processing section. The interface includes a bi-directional message serial interface and a data serial interface. The complexity of the data serial interface may be minimized by using a single data bit signal line in the data serial interface.

The present invention provides an AMOLED pixel driving circuit and a pixel driving method. The AMOLED pixel driving circuit utilizes the 4T2C structure, comprising a first, a second, a third, a fourth thin film transistors (T1, T2, T3, T4), a first, a second capacitor (C1, C2) and an organic light emitting diode (OLED) with introducing a first, a second global signals (Vselx, Vsely) and a reference voltage (Vref); by providing the reference voltage (Vref) to the first node (a) via the third thin film transistor (T3), the data signal voltage (Vdata) can be simplified to diminish the complexity of the data signal voltage (Vdata). The process of writing the data signal voltage (Vdata) into the first thin film transistor T1, i.e. the driving the thin film transistor is separated from the reset stage (Reset) and the threshold voltage detection stage (Vth sensing) with the fourth thin film transistor (T4). Thus, the reset time and the compensation time can be increased to effectively compensate the threshold voltage changes of the drive thin film transistor and the display brightness of the AMOLED becomes more even to raise the display quality.

A supply network for supplying consumers with a medium is provided. Based on a reduction of data and a subsequent reconstruction of at least one pressure and / or flow value, the state at least at one further location in the supply network can be determined without having to be measured. An improved actuation of the at least one pump and / or of the at least one valve is thus possible. A device for pressure control in a supply network is also provided.

The present invention relates to a method for aligning a camera sensor to significant data which is text or barcode data to be recognized comprising the steps of:—capturing an image of the significant data by means of the camera sensor; —detecting a predominant alignment line of the significant data and detecting an angle thereof in relation to a horizontal line of the captured image; —determining image sections within the edge and line enhanced image which contain most likely significant data lines; —selecting a representative image section out of the determined image sections which is aligned with the predominant alignment line; —capturing a following image of the significant data; tracking the representative image section and determining the predominant alignment line out of the representative image section to achieve a fast calculation and audio or tactile feedback of the alignment quality to the user.

This invention relates to providing medical treatment for human and non-human patients. In particular, the invention provides methods and computer program products which reduce clinical data complexity, aid in the identification of actions taken during the course of care which result in disproportionate therapeutic effects, and allow for the “potentiation” of therapy in an individual patient.

The invention belongs to the field of stream processing and information security technology, and discloses a real-time system protection method based on streaming data processing. The real-time system protection method based on streaming data processing comprises the following steps: converting a received request into a requesting atom, and real-timely transmitting the requesting atom to a streaming data calculation framework; enabling the streaming data calculation framework to real-timely analyze the processing mode of the requesting atom based on a rule base and divide the processing mode into two categories: normal and abnormal; and executing operations or protections for the system according to the processing mode. According to the real-time system protection method disclosed by the invention, the request received by the system is real-timely analyzed before the system actually performs the operation, and thus the awkward problem that some of the existing systems give an alarm after being damaged can be effectively solved; and with the improvement of the computing ability of computers, the real-time performance of the data protection disclosed by the invention will be getting better and better, and good availability and promotion values can be achieved.

The present invention provides a reception apparatus for performing security tunneling and data re-transmission and unidirectionally receiving data from a transmission apparatus and a transmission apparatus for unidirectionally transmitting data to the reception apparatus. When the reception apparatus checks that there is an error in received data, the reception apparatus performs a switching operation or transmits a switching request signal to the transmission apparatus to notify of the error of the received data to the transmission apparatus. When the transmission apparatus has detected the switching, the transmission apparatus re-transmits data, in which an error is generated, to the reception apparatus. The transmission apparatus encrypts the data and transmits the encrypted data to the reception apparatus. According to the present invention, reliability and security of one-unidirectional data communication are improved.

The invention discloses an industrial building concrete carbonization depth prediction method. The method comprises the steps: obtaining historical data of industrial building carbonization depth in anatural environment and dividing the historical data into a training set and a test set; performing adaptive decomposition on the training set and the test set by using a variational modal decomposition method to obtain modal component sub-sequences of the training set and the test set; training each modal component sub-sequence of a gating cycle unit by using the modal component sub-sequence ofthe training set as a training prediction model, and establishing a gating cycle network carbonization depth prediction sub-model of each modal component sub-sequence of the training set; and predicting the modal component sub-sequences of the test set by using the gated cycle network carbonization depth prediction sub-model of each modal component sub-sequence of the training set, accumulating prediction values, and performing comparative analysis on the prediction values and a real value to complete industrial building concrete carbonization depth prediction evaluation. According to the method, the characteristics of the industrial building carbonization depth time sequence are mastered more meticulously, and the accuracy of carbonization depth prediction is greatly improved.

A non-uniformly sampled three-dimensional (3D) information representation method is revealed. Firstly, use a computer to reconstruct a 3D model according to a 3D model data. Then set up a projection point according to the 3D model. The projection point is projected onto the 3D mode so as to get a plurality of sampling points uniformly. Then create at least one 2D array data according to a plurality of horizontal parameters and a plurality of vertical parameters of a 3D sample model. The 2D array, data corresponds to the sampling points. Take samples from non-uniform area of the 3D model so as to generate a non-uniform element. Thus, the 3D model data is simplified and this is beneficial to representation, operation, storage and transmission of 3D data.

An interface between an RF processing section and a baseband processing section supports general purpose message transmission as well as satellite positioning system signal sample transmission between the RF processing section and the baseband processing section. The interface includes a bi-directional message serial interface and a data serial interface. The complexity of the data serial interface may be minimized by using a single data bit signal line in the data serial interface.

The present invention relates to a method for aligning a camera sensor to significant data which is text or barcode data to be recognized comprising the steps of:—capturing an image of the significant data by means of the camera sensor; —detecting a predominant alignment line of the significant data and detecting an angle thereof in relation to a horizontal line of the captured image; —determining image sections within the edge and line enhanced image which contain most likely significant data lines; —selecting a representative image section out of the determined image sections which is aligned with the predominant alignment line; —capturing a following image of the significant data; tracking the representative image section and determining the predominant alignment line out of the representative image section to achieve a fast calculation and audio or tactile feedback of the alignment quality to the user.

The invention provides a pilot working state recognition model establishing method. The method comprises the following steps of: S1, preprocessing flight data; S2, extracting features of the preprocessed flight data; S3, carrying out data dimensionality reduction on the extracted features by utilizing a Trelets algorithm; and S4, carrying out training and modeling on the dimensionality reduced data by utilizing a Gaussian process classifier optimized on the basis of cuckoo algorithm. The method has favorable time domain localization ability and is immune to noise interference so that the feature values are more cautious. According to the method, original data is reduced to lower dimensionality, so that the complexity of the dimensionality reduced data is reduced and basis is laid for further more correct classification; the parameter optimization is relatively easy and easier to converge; and global or approximate global optimization results are searched for functions as far as possible, so that the local optimization of models is avoided.

A method of forming a video signal by a decoder device is described wherein the method comprises receiving a bit-stream and decoder information, the decoder information signaling the decoder device the presence of one or more resolution components in the bitstream for forming a video signal, a resolution component representing a spatially subsampled version, preferably a polyphase subsampled version, of a first video signal having a first resolution, the one or more resolution components being part of a resolution component group, the group comprising a plurality of resolution components on the basis of which the first video signal is reconstructable; and, the decoder device parsing the bitstream and decoding the one or more resolution components into video frames on the basis of the decoder information.

The invention discloses a public steel structure building micro-strain prediction method and system. The method comprises the following steps: converting historical data of public steel structure building strain in a natural environment into micro-strain data; dividing the micro-strain data into a training set and a test set; performing adaptive decomposition on the training set by using a variational mode decomposition method to obtain a plurality of IMF components with different frequencies and high stability; training a GRU prediction model by using the IMF components of the training set, adjusting and updating weight parameters and offset parameters through a loss function, completing learning, determining parameters of the GRU prediction model, predicting data in a next time period by using the GRU micro-strain prediction sub-model, and obtaining a micro-strain prediction value of each IMF component; and superposing the micro-strain predicted values of the IMF components, and performing error comparison with a test set to complete the prediction of the strain of the public steel structure building. According to the method, the micro-strain time sequence characteristics of the public steel structure building can be mastered more meticulously, and the strain prediction precision is improved.

An interface between an RF processing section and a baseband processing section supports general purpose message transmission as well as satellite positioning system signal sample transmission between the RF processing section and the baseband processing section. The interface includes a bi-directional message interface and a data interface. The message interface supports transmission of power control messages to the RF processing section to provide detailed control over activation or de-activation of individual blocks of hardware circuitry in the RF processing section.

A supply network for supplying consumers with a medium is provided. Based on a reduction of data and a subsequent reconstruction of at least one pressure and / or flow value, the state at least at one further location in the supply network can be determined without having to be measured. An improved actuation of the at least one pump and / or of the at least one valve is thus possible. A device for pressure control in a supply network is also provided.

The present application relates to a kind of welding deformation detection devices for ship parts production, belong to ship detection technical field.The shell and welding mechanical arm are included, welding mechanical arm is integrated with arc sensor, shell is fixed with the rotating shaft of welding mechanical arm front end welding torch by connecting frame, shell bottom wall is equipped with slide hole, laser profile scanner is slidably connected in slide hole, the inner wall of shell is fixed with bracket at the position of both ends of slide hole, each bracket side wall is fixed with piston mechanism one, the movable end of two piston mechanisms one is fixed with the both sides of laser profile scanner respectively, the top end of two brackets is fixed with horizontal plate, and the side wall of horizontal plate lower end is rotatably connected with swing block by motor.The position of laser profile scanner is self-stabilized in the process of welding torch swing by setting swing block, piston mechanism two, piston mechanism one, smoke isolation component and adjusting component are set to realize the physical self-adaptive adjustment of smoke isolation strength with the swing amplitude of welding torch.

The invention discloses a diagnosis system and method for fault classification and positioning of a transformer winding. The system comprises a sweep generator, a transformer winding, a detection terminal, an inductor L1, a divider resistor R1, a divider resistor R2 and a capacitor C. The sweep generator outputs a sweep-frequency signal, the sweep-frequency signal is input to the transformer winding from a grounding point N through the inductor L1 and the divider resistor R1, flows through a high-voltage winding A in the transformer winding and is output, and after the sweep-frequency signal passes through a capacitor C and is divided by the divider resistor R2, sweep-frequency data is collected by the detection terminal; and the detection terminal diagnoses the fault type and position of the transformer winding through a constructed deep learning convolutional neural network model. According to the method, the fault positioning problem is solved on the basis of realizing high-precision fault type diagnosis, and the method has certain engineering significance. The method and the system have a good effect on a simulation sample constructed in the invention, the fault type diagnosis precision is up to 100%, and the fault positioning accuracy is up to 83.33%.

The invention relates to the field of computer graphics processing, in particular to a rough collision detection method in a large-scale scene. This method is mainly used to roughly detect collisions in large-scale virtual scenes. By introducing two parameters to judge the distribution of objects in the scene and the dynamic and static conditions, it is judged whether the data processing method of spatial reasoning or time reasoning is preferred, and the rough collision is further executed. detection. Achieve fast collision culling with low data complexity.

The invention discloses a multi-sensing signal fusion monitoring method and system for dimensionality reduction of milling data of thin-walled parts. The technical solution is to: obtain the original signal characteristic matrix; calculate the natural frequency of the workpiece and the tool according to the frequency response function, and calculate the corresponding milling parameters The main shaft rotation frequency and the tooth passing frequency are calculated, and the frequency bands where all wavelet packets are located are calculated; whether the wavelet packet frequency band contains the natural frequency of the workpiece, the tool natural frequency, the main shaft rotation frequency and the tooth passing frequency, and the frequency bands of different wavelet packets are respectively Take the value to get the eigenvector of the fusion multi-sensor signal; according to the eigenvector of the fusion multi-sensor signal, the original signal feature matrix is ​​converted into the fusion feature matrix; according to the requirement of the contribution degree in the milling state identification, the dimension-reduced feature vector matrix is ​​obtained , and output data dimensionality reduction results. The invention can reduce the complexity of data, and can effectively fuse the features of multi-sensing signals without affecting the training accuracy of machine learning.

This invention relates to a switch method and an exchanger for relay gateway of C& C08 exchanger, in which, the method includes: setting call source codes of all virtual network users of a local end a homogeneous value not mixed with that of ordinary users and that of relay cluster call of a relay gateway and setting out-cluster word crowns of all the virtual network users a homogeneous value and denying deleting word crowns from the cluster of the virtual network parameter, and when call source code of ordinary users dials the local word crown in number head set 0, it is processes as the number head process data and converts them to set 1 to be re-analyzed, yet that of the virtual network is not processed as the number head when dialing the local word head and the call of the out-cluster word head plus called number dialed by that of the virtual network is processed as a virtual network call, local word head is processed in set 1, the service attribute is local and the route points to the relay gateway.

The invention discloses a long-span steel structure building micro-strain short-term prediction method. The method comprises: obtaining historical data of the micro-strain of the large-span steel structure building, and dividing the historical data into a training set and a test set; performing adaptive decomposition on the training set and the test set by using a variational mode decomposition method to obtain each mode component sub-sequence of the training set and the test set; training each modal component sub-sequence in the gating circulation unit by using each modal component sub-sequence of the training set as a training sample, and establishing a short-term prediction sub-model of the gating circulation unit steel structure building micro-strain of each modal component sub-sequence of the training set; predicting each modal component sub-sequence of the test set by using the short-term prediction sub-model of the gated circulation unit steel structure building micro-strain of each modal component sub-sequence of the training set, and accumulating each predicted modal component sub-sequence of the test set to obtain a prediction set; and performing comparative analysis by using the prediction set and a test set in historical data. According to the invention, the short-term prediction precision of the micro-strain of the steel structure building is improved.

The invention provides a method of correcting supersonic wave partial discharge detection. The method comprises the following steps of extracting a plurality of partial discharge signal linearity frequency spectrums from historical data and then processing to acquire a coefficient matrix and a principal component characteristic of each partial discharge signal, and constructing a classification model of the partial discharge signals and each type of a linearity frequency spectrum mean value; acquiring a linearity frequency spectrum mean value of pure noise signals, and according to the coefficient matrix, acquiring a classification model of pure noise supersonic wave signals; adding each type of the linearity frequency spectrum mean value of the partial discharge signals to the linearity frequency spectrum mean value of the pure noise signals and correcting the classification model of the partial discharge signals; acquiring a signal to be detected, according to the coefficient matrix, acquiring a principal component characteristic of the signal to be detected and introducing into the classification model corrected by the pure noise and the partial discharge signals, and screening signal output with a minimum Euclidean distance in the corresponding classification model. By using the method, an artificial factor interference is avoided, an introduced characteristic dimension is low and training data is less so that purposes of labor saving and time saving, and an objective detection result are reached.

A diagnostic system and method for classification and location of transformer winding faults, the system includes a frequency sweeper, a transformer winding, a detection terminal, an inductor L1, a voltage dividing resistor R1, a voltage dividing resistor R2, and a capacitor C. The frequency sweep signal is output by the frequency sweeper, which is input to the transformer winding from the grounding point N through the inductor L1 and the voltage dividing resistor R1, flows through the high voltage winding A inside the transformer winding and is output, passes through the capacitor C and is divided by the voltage dividing resistor R2 , the detected terminal collects frequency sweep data; the detection terminal diagnoses the fault type and location of the transformer winding through the constructed deep learning convolutional neural network model. The invention solves the problem of fault location on the basis of realizing high accuracy of fault type diagnosis, and has certain engineering significance. The simulation sample constructed in the present invention has good effect, the fault type diagnosis accuracy is as high as 100%, and the fault location accuracy rate is as high as 83.33%.