945 results about "Data subject" patented technology

An exemplary embodiment of the present invention includes a method to enforce privacy preferences on exchanges of personal data of a data-subject. The method comprises the steps of: specifying data-subject authorization rule sets having subject constraints, receiving a request message from a requester and a requester privacy statement, comparing the requester privacy statement to the subject constraints, and releasing the data-subject data in a response message to the requester only if the subject constraints are satisfied. The requester privacy statement includes purpose, retention, recipient, and access information, wherein the purpose information specifies the purpose for which the requested data is acquired, the retention information specifies a retention policy for the requested data, the recipient information specifies the recipients of the requested data, and the access information specifies whether the requested data should be accessing to the data-subject after the data has been released.

A method and system in a remote computer network for allowing users to customize on-line search engines for on-line data searches. An on-line search engine is provided at a remote network site, such that the on-line search engine may be displayed at local network sites linked to the computer network. An independent user-defined search plug-in program is then designated for limiting the scope of online data searches to particular data subjects, such that the user-defined search plug-in program is called for processing by the on-line search engine during on-line data searches by the on-line search engine at a local network site utilizing search terms. The independent user-defined search plug-in program is subsequently stored at the local network site. Finally, the independent user-defined search plug-in program is automatically linked with the search terms, such that all searches performed by the on-line search engine at the local network site operate according to parameters determined by the user-defined search plug-in program and the search terms.

A method for scheduling the delivery of multimedia data packets over a communications medium with a limited bandwidth. The packets may contain data representing images, sounds, or other media which are to be delivered from a source or server to a recipient or client. The 6 method described here minimizes the delay between the point in time when a client requests the multimedia data and the point in time when the client may start presenting the data without risk of interruption, for a given communications bandwidth. This method also determines the minimum buffer sizes needed by the client in order to present this multimedia data subject to the specified bandwidth limit.

Systems and methods for verifying data including income and employment, assets, healthcare claims, clinical data, and other types of data subject to various regulatory and/or privacy restrictions.

The invention relates to distributed active phased array radar and a beam forming method thereof. A transceiving component array consists of digital transceiving components which comprise analog front ends, power amplifiers, low-noise amplifiers and front-end digital units. The distributed active phased array radar further comprises a central processor, the central processor is connected with the multiple front-end digital units through a local area network by means of the hierarchical distributed processing technology, and used for setting operating modes of all of the front-end digital units and waveform data and receiving baseband data to guarantee reliability of target echo data subjected to digital synthesis and sending public clock signals to the front-end digital units through a clock network to guarantee synchronization of clock signals of each port. The multiple front-end digital units are correspondingly distributed in an antenna array, and each front-end digital unit is matched with one transceiving component. The distributed active phased array radar and the beam forming method thereof have the advantages of high flexibility, flexibility in data processing mode and improvement of phased array radar performances.

The invention discloses a firework identification method and a firework identification system based on deep learning of an image. The firework identification method comprises the following steps of step 1, acquiring a label-free sample image set and a label sample image set; step 2, obtaining a label-free training data set and a label training data set; step 3, performing whitening preliminary processing on training data; step 4, based on the label-free training data subjected to the whitening preliminary processing, constructing a deep neutral network based on sparse self coding by adopting unsupervised learning, and extracting a basic image feature set of the label-free training data; step 5, convolving basic image features and pooling image data; step 6, training a Softmax classifier based on the convolved and pooled label training data set; step 7, inputting the convolved and pooled images to be identified into the trained Softmax classifier to obtain the identification result. According to the firework identification method and the firework identification system disclosed by the invention, the visual identification rate of fireworks and a similar object can be effectively improved, and automatic identification with higher precision for the fireworks can be realized.

A method and computer system for dynamically selecting an optimal lock mode in a multiprocessor environment. The method determines a quantity of read-side and write-side acquisitions, and evaluates the data to determine an optimal lock mode for efficiently operating the computer system while maintaining reduced overhead. The method incorporates data received from the individual units within a central processing system, the quantity of write-side acquisitions in the system, and data which has been subject to secondary measures, such as formatives of digital filters. The data subject to secondary measures includes, but is not limited to, a quantity of read-side acquisitions, a quantity of write-side acquisitions, and a quantity of read-hold durations. Based upon the individual unit data and the system-wide data, including the secondary measures, the operating system may select the most efficient mode of operation from among the locking modes available. Accordingly, efficiency of a computer system may be enhanced with the ability to selectively choose an optimal locking mode based upon selected and calculated parameters.

An auditing framework for determining whether a database disclosure of information adhered to its data disclosure policies. Users formulate audit expressions to specify the (sensitive) data subject to disclosure review. An audit component accepts audit expressions and returns all queries (deemed “suspicious”) that accessed the specified data during their execution.

The invention belongs to the technical field of automatic radar HRRP (high resolution range profile) object identification and particularly relates to compressive sensing based range profile object identification. Range profile object identification includes the steps: constructing a matching dictionary according to a radar echo model, selecting an appropriate test matrix for compressive sensing of a training sample range profile and to-be-identified test sample range profile which are known in type information so as to achieve data dimension reduction; then, subjecting data subjected to compressive sensing to sparse reconstruction so as to obtain sparse coefficients of the training sample range profile and the test sample range profile under the matching dictionary; utilizing the sparse coefficient of the training sample range profile as a pattern vector, and identifying the test sample range profile according to a nearest neighbor method. By the aid of compressive sensing based range profile object identification, since sparse coefficient characteristics of objects under the dictionary are extracted, redundancy is avoided, calculating amount is decreased and unnecessary noise is avoided.

The invention discloses a high-precision positioning method based on an MEMS (Micro Electro Mechanical System) inertial sensor. The high-precision positioning method comprises the following steps: firstly, fixedly connecting the MEMS inertial sensor on a foot of a pedestrian, enabling the MEMS inertial sensor to sense a motion state of the foot, acquiring foot navigation information of the foot in real time, and realizing transmission by Bluetooth; secondly, holding an Android mobile phone by the pedestrian, and receiving and saving data provided by the MEMS inertial sensor in real time at an Android client; thirdly, carrying out denoising processing on the data; fourthly, obtaining a zero velocity interval by adopting a zero velocity detection algorithm, and then carrying out error correction by combining a zero velocity update algorithm with a state estimation algorithm; fifthly, displaying data subjected to error correction and compensation in real time by the Android client through a user interface. According to the high-precision positioning method disclosed by the invention, extra auxiliary basic setting is not needed; good positioning precision of various complex motion states in indoor positioning can be maintained; real-time correction and error compensation are realized by adopting a mobile terminal, and the motion track is displayed in real time by a user interaction interface.

A printing apparatus records a predetermined test pattern on printing paper, and reads the test pattern by means of a scanner. The scanner reads the test pattern at a resolution lower than the resolution of a recording head. This allows the automatic and fast reading of the test pattern. Additionally, the printing apparatus performs an interpolation process on read data, and judges whether there is an abnormality in nozzles or not, based on the read data subjected to the interpolation process. This reproduces the positions of and spacing between lines recorded on the printing paper with high accuracy to achieve the exact judgment as to whether there is an abnormality in the nozzles or not. Therefore, an inspection with a high degree of reliability is accomplished.

The invention discloses a commodity target word oriented emotional tendency analysis method, which belongs to the field of the analysis processing of online shopping commodity reviews. The method comprises the following four steps that: 1: corpus preprocessing: carrying out word segmentation on a dataset, and converting a category label into a vector form according to a category number; 2: word vector training: training review data subjected to the word segmentation through a CBOW (Continuous Bag-of-Words Model) to obtain a word vector; 3: adopting a neural network structure, and using an LSTM(Long Short Term Memory) network model structure to enable the network to pay attention to whole-sentence contents; and 4: review sentence emotion classification: taking the output of the neural network as the input of a Softmax function to obtain a final result. By use of the method, semantic description in a semantic space is more accurate, the data is trained through the neural network so as to optimize the weight and the offset parameter in the neural network, parameters trained after continuous iteration make a loss value minimum, at the time, the trained parameters are used for traininga test set, and therefore, higher accuracy can be obtained.

The invention discloses an internet-of-things gateway and a medical monitoring system comprising the same. The gateway comprises a sensing network access unit, a protocol conversion unit and a communication network access unit, wherein the sensing network access unit is used for receiving sensing data input by sensing equipment; the protocol conversion unit is used for analyzing the sensing data, calling a data adapting protocol according to an analysis result, coding the data subjected to secondary analysis by using a ubliquitous machine to machine protocol (UMMP) after performing secondary coding on the sensing data according to the data adapting protocol and outputting the coded sensing data to the communication network access unit; and the communication network access unit is used for selecting an access mode of the data and outputting the coded sensing data to the internet-of-things management platform in the access mode. The system has wide access capability and strong protocol conversion capability, so that the medical monitoring system comprising the internet-of-things gateway can be connected with the medical monitoring equipment supporting an international medical standard protocol to realize comprehensive monitoring on a patient.

The embodiment of the invention discloses a data transmission method. The method comprises the following steps: acquiring collected audio-video data, and performing coding compression on the audio-video data; performing segmenting packetization on the audio-video data subjected to coding compression according to a preset segmenting packetization strategy; allocating data packets to communication links, respectively corresponding to a plurality of configured wireless communication modules, for transmission, wherein at least two communication links corresponding to thewireless communication modules adopt different mobile telecommunication networks for communication; and acquiring network bandwidth information of each communication link in real time, adjusting allocation of the data packets in real time and/or adjusting coding parameters for coding the audio-video data in real time to adjust the code rate of the audio-video data subjected to coding compression. Through adoption of the method, a problem of live broadcast lag phase or failure caused by the fact that the possibility of communication blind zones and poor signals is high when the mobile telecommunication networks are used for audio-video live broadcasting in the prior art is solved, and urgent needs of outdoor live broadcasting and mobile live broadcasting operations are met.

A program of storing electronic files in a searchable database includes opening an electronic file having a body of text data. The file's body is stored in a body text file in a memory of a computer system. An attachment associated with the electronic file is opened. Text data of the attachment is stored in an attachment text file of the computer system. The body text file is imported into a body text file field of a first database record of a searchable database. The attachment text file is imported into an attachment text file field of a second database record of the searchable database.

The invention discloses an existing railway line retesting method based on the on-board laser radar technology. Firstly, control marks are arranged along a railway to be tested at preset intervals; secondly, position coordinates of the center point of each control mark on a railway engineering coordinate system are measured; thirdly, laser point cloud data and image data of rails, railway equipment and facilitates (such as annunciators, turnouts and contact net rods), terrain around the railway and the control marks along the railway are obtained, and colors of the image data are assigned to corresponding laser point cloud data; fourthly, the obtained colorized laser point cloud data are subjected to precision refining treatment with the position coordinates of the control marks as reference points, so that errors in the colorized laser point cloud data are eliminated; fifthly, rail surface linear laser point data are extracted from the colorized laser point cloud data subjected to the precision refining treatment; and sixthly, the line type of the existing railway is restored through the rail surface linear laser point data. Information of the existing line is accurately obtained under the condition that operation of the railway is not influenced.

A method of measuring a location of a user equipment (UE) located indoors in a wireless network includes receiving signals from a plurality of access points (APs), performing training for machine learning using the received signals or information acquired from the received signals, setting a weight vector to be applied to a relevance vector machine (RVM) method using data subjected to the training for machine learning, and applying RVM regression to the set weight vector and measured strengths of the received signals and determining whether the signals received from the plurality of APs are line of sight (LOS) signals or non line of sight (NLOS) signals.

The invention relates to a medical big-data acquisition and analysis system and method. The medical big-data acquisition and analysis method includes: installing a data acquisition unit at the place where medical data are acquired, and uploading the acquired data to an online medical acquisition platform; subjecting to the stored data to data processing; finding out a rule in the data; applying the data subjected to analysis to medical fields to carry out clinical decision and disease warning and analyze behaviors of patients. The medical big-data acquisition and analysis system comprises the online acquisition platform, an HDFS (hadoop distributed file system), an Hbase and a Hadoop frame, and is divided into four layers, namely a foundation layer, a platform layer, a function layer and a service layer. Staff health conditions can be acquired in real time, massive medical data are stored in a distributed manner, the massive data are analyzed rapidly by batch processing of big data, the clinical decision and disease warning are carried out, the behaviors of the patients are analyzed, multiple treatment schemes are put forward clinically, and early warnings are made for outbreaks of epidemic diseases.

The invention belongs to the technical field of gear detection and measurement, in particular relates to a gear load wireless monitoring system and an interactive multi-stage gear physical simulation method finished based on the same. The invention overcomes the defects and limitations of the existing gear monitoring and simulation method. The gear load wireless monitoring system comprises an upper computer and a lower computer, wherein the lower computer is internally arranged on a measured gear structure, and the lower computer with a wireless transmission function is in wireless transmission with the upper computer. The interactive multi-stage gear physical simulation method comprises the following steps of: detecting an external field; carrying out gear solid modeling, and carrying out grid partition on the gear solid model by adopting swept mapping; setting boundary conditions; carrying out finite element analysis; and verifying the data subjected to finite element analysis and actual measurement. According to the invention, wireless data transmission and load identification testing schemes are used for correcting the error of CAE (Computer Aided Engineering) analysis so as to master the stress rule of the gear, thereby providing a basis for fatigue life prediction. The system and method provided by the invention have higher practical and economic values.

The invention relates to the technical field of hydroelectric generating set fault diagnosis, in particular to a hydroelectric generating set fault diagnosis method and system based on a DdAE (Difference Differential Algebraic Equations) deep learning model. The method and the system are established on the basis of the analysis of the original vibration data of the hydroelectric generating set, adeep learning characteristic extraction method based on a multilayer neural network model is adopted, a complex manual processing and feature extraction process is not required, an ASFA (Aquatic Sciences and Fisheries Abstracts) method based on random search is adopted to carry out the structural parameter adjustment and optimization of the DdAE to achieve a purpose of strategy optimization. A deep denoising automatic encoder model is used for realizing the distributed expression of original data, and reconstruction data subjected to feature extraction is input into a Softmax regression modelto judge the work state and the fault type of the hydroelectric generating set. The analysis of a network experiment result indicates that the method can be effectively applied to the hydroelectric generating set fault diagnosis.

The invention provides a big-data-oriented ETL (Extraction-Transformation-Loading) method and device. The method comprises the following steps: obtaining a parameter configuration file; according to the parameter configuration file, carrying out parameter configuration on data to be synchronized; and through an ETL method, synchronizing the data subjected to the parameter configuration. A data importing and exporting function among various data sources can be realized, and various data transformation operations based on hdfs data is realized through the simple configuration of a visual interface.

The invention discloses a medical insurance fraud detection method based on multiple features. The method comprises: aimed at treatment histories of all patients suffered from the same disease in medical insurance declaration data, in combination with medicine classification knowledge, adopting probability statistics, mixture Gaussian modeling, feature fusion and other techniques to extract multiple secondary feature data with higher distinction degree; then, vectorizing the treatment histories of the patients based on the secondary feature data; and then, after carrying out clustering analysis on treatment data marked with 'normal', adopting a non-linear support vector machine classification technique to establish multiple classification hyperplanes for each type of normal treatment data subjected to clustering and treatment data marked with 'fraud', so that the fraud detection can be carried out on non-marked medical insurance data. The method can be used for quickly and effectively detecting the fraud data existent in the medical insurance data, and has relatively high accuracy.

The invention discloses a characteristic space-based backward and forward adaptive wave beam forming method, and relates to the technical field of medical ultrasonic imaging. The method comprises the following steps of: performing focusing delay processing and backward and forward smoothing on a plurality of paths of sampled signals of a received array to obtain a sample covariance matrix estimate; performing diagonal loading on the sample covariance matrix estimate and then combining with a direction vector to calculate an adaptive wave beam forming weight; performing characteristic decomposition on the backward and forward covariance matrix estimate after the diagonal loading to construct a signal subspace; projecting the adaptive wave beam forming weight into the signal subspace to obtain a new adaptive wave beam forming weight; and finally, performing weighted summation on a plurality of paths of data subjected to the backward and forward smoothing by the new adaptive wave beam forming weight so as to obtain a path of adaptive wave beam signal. By using the method, the problems of improving the image resolution and contrast, being sensitive to the direction error and the like existing in the conventional adaptive wave beam forming algorithm are solved, and the overall quality of the ultrasonic imaging is comprehensively improved.

The invention provides a phase noise compensation method suitable for large line width and high order modulation CO-OFDM system. The method comprises the following steps: performing channel equalization on training symbol data of a receiving terminal after performing Kalman filter on the same in the frequency domain; setting pilot frequency subcarrier data with certain intervals for each OFDM symbol on a transmitting terminal, and performing preset CPE phase noise estimation and compensation at pilot frequency subcarriers in the frequency domain based on extended Kalman filter (EKF); and finally, converting frequency domain data subjected to CPE phase noise compensation into the time domain, and realizing blind ICI phase noise compensation by using the Avg-BL method, then performing pre- judgment, converting the frequency domain data subjected to the judgment into the time domain, applying time domain data and original time domain data of the receiving terminal to time domain unscented Kalman filter, calculating a final phase noise compensation value, and performing compensation. By adoption of the phase noise compensation method, a better phase noise equalization effect is obtained, and the spectrum utilization rate of the system is improved.

The invention relates to an interference suppression method based on BeiDou-I satellite signal reception. The method comprises the following steps of: (1) receiving N*(1-theta) BeiDou digital intermediate-frequency data and buffering the front N*theta sampling point data; (2) selecting window functions with the window length of N, combining the received N*(1-theta) BeiDou digital intermediate-frequency data and the received front N*theta sampling point data into N data to be analyzed in time sequence and sequentially multiplying the N data to be analyzed by N window function quotients; (3) carrying out FFT (Fast Fourier Transform) on the N data subjected to windowing treatment and storing the real part data and the imaginary part data of the N frequency points subjected to FFT; (4) calculating the module values of the frequency points subjected to the FFT; (5) calculating a threshold value according to the average value of the module values and the module values the current batch of data under a non-interference environment; (6) calculating attenuation quotients corresponding to interference frequency points; (7) attenuating according to the interference frequency point positions and the attenuation quotients which are acquired through calculation; and (8) carrying out IFFT (Inverse Fast Fourier Transform) on a frequency domain signal subjected to interference suppression.

The invention discloses a calculation method for large spatial scale vegetation coverage by combining with an unmanned aerial vehicle (UAV) image. The calculation method comprises the following steps: carrying out atmospheric correction and geometrical correction on a remote sensing image, calculating NDVI (Normalized Difference Vegetation Index) and obtaining an effective region according to a predetermined threshold value; splicing UAV pictures and obtaining an orthoimage, registering satellite data subjected to geometrical correction with the spatial position, selecting a typical sample area from the UAV image, and interpreting proportions of all ground objects in the typical sample area by using unsupervised classification; randomly selecting one part of the sample area, and solving the reflectivity of all ground object end elements by using the proportions of all the ground objects in the sample area and the corresponding satellite remote sensing band reflectivity and combining with a least square method; solving the vegetation coverage of all pixels in the effective image area by using a spectral decomposition model and the reflectivity of all the ground object end element; correcting calculation results of the vegetation coverage by using data of a residual sample area. The core of the calculation method disclosed by the invention is based on a method of acquiring the end-element reflectivity of the UAV and a vegetation coverage correction model, and the calculation accuracy of the large spatial scale vegetation coverage can be effectively improved.

The invention discloses a method for importing data. The method comprises the following steps: obtaining service files from a service system, generating static meta data according to the service files and ensuring the static meta data to access a target database corresponding to the service system; and using the static meta data for converting the formats of the service data in the target database and importing the data subjected to format conversion into a target data storage area. The method has the following advantage: the accuracy, usability and efficiency of data import are improved. The invention also discloses a device applying the method.

The invention discloses an increment compensation dynamic adaptive enhancement-based fault diagnosis method. The method comprises the following steps of 1, collecting vibration signals in various states for a vibration sensor at a driving end of a motor; 2, preprocessing fault data of a bearing device; 3, adding a training sample into a random noise to serve as an input of a denoising autocoder to perform unsupervised greedy layer-by-layer pre-training; 4, when new device state data exists, performing new fault mode extraction by using an existing trained DAE model, performing similar mode comparison by utilizing a mode similarity algorithm, performing increment combination on new fault modes by adopting an increment active fusion algorithm, and calculating dynamic weighting by utilizing a weight dynamic compensation algorithm; 5, training an SVM classifier by taking labeled fault data and unlabeled fault data subjected to dynamic deep learning training weighting as input vectors; 6, performing global fine adjustment on related parameters in the whole model by utilizing a BP algorithm; and 7, performing classification diagnosis of fault types.

In accordance with the invention, a postal security device (PSD) (10) contains a non-volatile memory (13) which does not depend on battery power such as an EEPROM (13), and contains a nonvolatile memory (14, 16) which does depend on battery power, such as a static RAM. The PSD (10) also contains an encryption engine (12, 14, 22). An encryption key is developed and is stored in the static RAM (14), which is sized to be only large enough to contain the encryption key. A large body of data, too large to fit in the static RAM, is encrypted by means of the encryption engine (12, 14, 22) and with reference to the encryption key, and is stored in the EEPROM (13). This body of data typically includes cryptographic keys and sensitive bit-images. When the PSD is powered, a large RAM (typically a dynamic RAM) (16) is available to receive the large body of data, decrypted using the encryption key. A tamper switch (17) cuts power to both RAMs (14, 16) in the event of tampering.

In an adaptive modulation communication system that adaptively varies a modulation scheme for each transmit unit, a transmitting-side apparatus sets different error detecting units corresponding to bit position, and transmits data subjected to error detecting processing on a different error detecting unit basis corresponding to bit position, and a receiving-side apparatus performs demodulation independently for each of the error correcting units using different demodulation patterns to obtain received data.