1387results about How to "Big amount of data" patented technology

An integrated circuit for data encryption/decryption and secure key management is disclosed. The integrated circuit may be used in conjunction with other integrated circuits, processors, and software to construct a wide variety of secure data processing, storage, and communication systems. A preferred embodiment of the integrated circuit includes a symmetric block cipher that may be scaled to strike a favorable balance among processing throughput and power consumption. The modular architecture also supports multiple encryption modes and key management functions such as one-way cryptographic hash and random number generator functions that leverage the scalable symmetric block cipher. The integrated circuit may also include a key management processor that can be programmed to support a wide variety of asymmetric key cryptography functions for secure key exchange with remote key storage devices and enterprise key management servers. Internal data and key buffers enable the device to re-key encrypted data without exposing data. The key management functions allow the device to function as a cryptographic domain bridge in a federated security architecture.

A framework for comparison and optimization of classifiers and features for classification of targets includes preparing training and testing sets, applying a classifier to the training set to achieve a distinctly trained classifier for each classifier applied, applying each resulting trained classifier to the testing data set, selecting an optimal classifier, and applying the optimal classifier to the target. The framework is used to optimally classify a physical representation of a target, such as a document, news article, or advertisement. The framework allows for targeted advertisements to be directed to consumers based on user preferences learned from user activities across a network.

A text-mining system and method automatically extracts useful information from a large set of tree-structured data by generating successive sets of candidate tree-structured association patterns for comparison with the tree-structured data. The number of times is counted that each of the candidate association patterns matches with a tree in the set of tree-structured data in order to determine which of the candidate association patterns frequently matches with a tree in the data set. Each successive set of candidate association patterns is generated from the frequent association patterns determined from the previous set of candidate association patterns.

A method of conducting a survey. The method includes providing a plurality of questions to respondents, at least some questions being provided to a plurality of the respondents, collecting answers to the questions from the respondents, transfer-ring at least some of the answers to respondents other than those who generated the answers, collecting responses to the transferred answers, at least some of the responses being qualitative, and providing a statistical report which is at least partially based on qualitative responses collected from the respondents.

The invention discloses a prediction method and visualization method of traffic jam. The methods comprise the following steps: GPS data sent back by a taxicab is utilized for being associated to roads in an electronic map through the map matching method; the road section speed calculated in terms of the matched data is utilized for judging the traffic state of road sections; the evolution rule of the traffic jam, including formation and dissipation of the traffic jam, is extracted with the utilization of the historical data; the traffic jam prediction is performed with the utilization of the sliding time window scheme after a real-time traffic information database is associated; the congestion intensity and the influence range of congested road sections can be presented by a thermodynamic chart after the congestion intensity of the congested road sections is calculated based on the prediction result. The prediction method provided by the invention can realize highly accurate traffic jam prediction, and the visualization method of the thermodynamic chart enables the traffic jam to be visualized and understandable, so that the location and the influence range of the traffic jam can be discerned conveniently.

A system for driver assessment and training comprising a simulator which can be operated by a driver or pilot under test or in training, the simulator displaying scenarios the driver or pilot must drive through or fly through. The inputs of the driver or pilot in reaction to the displayed scenario are fed to a free body model which calculates the resulting movement of the simulated vehicle in the displayed world. Scoring can be by analysis of calculated Fonda curves comparing the driver performance to performances by one or more normative drivers plotted by standard deviation from norm on the vertical axis and sample point on the horizontal axis. Simulator sickness can be mitigated by calculation and display of a mitigation object which partially obscures the virtual scene being displayed. Signature curves give the driver or pilots' performance at a glance.

The invention discloses a personal credit ecological platform, which is structured by a display layer, a middle layer and a data layer; the display layer is a front client platform, the middle layer is a background service platform, and the data layer is a data warehouse system; the whole ecological platform consists of a management end, a personal credit module, a merchant module, a payment flow, and a mobile APP. The platform data base is deep, the data quality is alive, the accuracy is high, the scale is wide, and the time track is rich, the data volume is huge and the dimension is wide. The platform deeply excavates the personal credit data, realizes the credit evaluation, provides the complete personal credit status, realizes the personal credit tracking management, and further controls the risk; besides, the client complaint procedure is added. The platform achieves the recommendation of potential and sustainable developed individual client for merchant users, and realizes the bidirectional push.

A communication system includes a communication utilizing apparatus connectable to a communications network and service provision apparatus for making services available to the communications utilizing apparatus. An accounting device is associated with the communications utilizing apparatus and includes a digital data storage device arranged to store details of the receipt of services by the communications utilizing apparatus a signalling circuit arranged to receive, via the communications network, signals indicating a payment due in respect of services provided by the service provision apparatus, and a comparison device arranged to compare the received indications with data derived from the stored details.

The invention discloses an inspection system and an implementation method for the electrical equipment of an unmanned aerial vehicle photovoltaic power station. The inspection system includes an airborne terminal, a ground terminal, and a wireless communication module. The camera or monitoring equipment collects the image data of the electrical equipment of the photovoltaic power station, and at the same time receives the control commands sent from the ground terminal to the airborne terminal; the ground terminal is set on the ground platform to process the data collected and sent back by the airborne terminal , to control the flight and shooting operations of the unmanned aerial vehicle on the ground; the wireless communication module completes the functions of transmitting flight control instructions, flight status data, and video return data between the airborne terminal and the ground terminal. The inspection system provides real-time high-definition viewing of infrared images and visible light images, which is convenient for timely resolution of faults. The images are analyzed on the ground side through pattern recognition. repair.

The Secure Networked Data Shadowing System is connected to a plurality of monitored computer systems via an existing communication medium to store the shadowed data. The data is encrypted by the monitored computer system using a cryptokey, and the data file is processed using a hash function prior to encryption, so the contents of this file are uniquely identified. Thus, the encrypted file is stored in its encrypted form and the hash index is used to identify the encrypted file. A “data de-duplication” process avoids storing multiple copies of the same files by identifying instances of duplication via the hash index. Files that have the same hash index can be reduced to a single copy without any loss of data as long as the file structure information for each instance of the file is maintained.

The invention discloses a short-term power load prediction method based on a multilayer improved GRU neural network. The method comprises the following steps: periodically establishing a sample data set; performing abnormal point identification and missing value processing on input data in the samples, performing standardized transformation on the processed data, and dividing the data set into a training set, a verification set and a to-be-predicted set; constructing the improved GRU neural network, and inputting the data of the training set in the network for training the same for multiple times to obtain a trained network, verifying the test learning result of the verification set by using the network for multiple times, and recording and storing the model weight of the optimal verification result; and inputting the to-be-predicted set in the trained optimal GRU model, calculating a standardized prediction result and performing reverse standardized transformation to obtain a final prediction result. By adoption of the short-term power load prediction method, the training speed and the training efficiency are improved.

The invention discloses a pedestrian re-identification method based on a generative adversarial network image super-resolution technology. The method includes the following steps: utilizing a Laplace pyramid generative adversarial network to generate a group of clear images, utilizing local maximum event expression and a Dense Correspondences algorithm to separately extract HSV color features, texture features and LAB color features of the images, carrying out fusion on the features, utilizing a cross vision quadratic discriminant analysis algorithm to conduct metric learning on the features, utilizing a Manhattan distance to calculate the distance between a probe set and a gallery set, and finally utilizing a multi-shot mode to carry out 1:N and N:N evaluation. A LAPGAN network is utilized to generate high-resolution image, and then a conventional method is utilized to obtain the features of the images and carry out corresponding matching. Deeping learning and the conventional method are combined to solve the problem of low image resolution caused by illumination, angle and other reasons, and an image matching rate is increased.

The present invention concerns a system for selecting and monitoring data plans for telecommunications systems, and methods of determining, learning and estimating usage patterns in-order to predict usage and tie this to cost and the overlaying of plan selection for cost optimization. Further, additional methods are applied to determine anomalous user behaviours and raise security and data leakage related events.

A novel approach is provided for avoiding the “slow-start restart” in TCP communications when network conditions dictate such. The disclosed approach serves to overcome the latency related to the “slow-start restart” by assessing network conditions and avoiding the “slow-start restart” when network conditions justify the avoidance. The disclosed methods, applications and devices implement the periodic communication of a probe packet that is generated and transmitted from a TCP sender to a TCP receiver during the period that the TCP network connection remains idle. Receipt of the probe packet by the TCP receiver will trigger transmission of an acknowledgment message by the TCP receiver. Upon receipt of the acknowledgement message the TCP sender will restart measurement of the idleness period and, as such the “slow-start restart” is avoided.

The invention discloses a curved surface defect automatic detection method and an apparatus thereof. The method comprises the following steps: 1, at a training phase, acquiring sample images, constructing a training set, performing manual defect identification on images in the training set, and marking areas where all defects appear; for each image in the training set, executing a defect pre-positioning step so as to obtain areas R where all the defects may appear; comparing the R with the manually marked areas where all the defects appear, and according to an overlap degree of the two, obtaining negative samples and positive samples through division; according to the positive samples and the negative samples, performing offline training of a deep neural network model, and outputting types of defect areas and concrete coordinates; and 2, at an online detection phase, acquiring current curved surface images to be detected, executing a defect pre-positioning step, obtaining sets R, and inputting the R into the network model, and obtaining the types and the concrete coordinates of the defect areas. The method and apparatus have the advantages of high adaptability, high real-time performance and high identification accuracy.

The invention relates to a method for implementing a workflow form, which comprises the following steps that: 1, a WEB client initiates a request for acquiring a form template to a workflow engine; 2, the workflow engine acquires the form template from a database and returns to the WEB client; 3, the WEB client performs attribute setting operation on the form template according to attribute description of the form template; and 4, the WEB client displays the processed form template. The invention also relates to a system for implementing the workflow form, which comprises a form formulating module, a WEB client, a workflow engine and a database. The technical scheme has the advantages of making a user flexibly formulate a needed workflow form per se according to service requirement, well meeting the requirement of service change of the user, setting a cache region in the form template in the workflow engine, improving the efficiency for acquiring the form template, greatly lightening working amount of maintenance personnel, reducing the development and maintenance cost and enhancing the system reusability.

The invention relates to a water quality multi-index detection method on the basis of an ultraviolet-visible absorption spectrum. The method comprises the following steps: (1) establishing a water quality algorithm model comprising each water quality index; (2) measuring to obtain the ultraviolet-visible absorption spectrum of the to-be-detected water; (3) calculating to obtain a primary calculation value of each water quality index in the to-be-detected water according to the water quality algorithm model and the ultraviolet-visible absorption spectrum of the to-be-detected water; (4) locally correcting the primary calculation value of each water quality index in the to-be-detected water to obtain a detection result corresponding to each water quality index; and (5) comparing the obtained detection result corresponding to each water quality index and relevant water quality standard of each water quality index, judging whether the to-be-detected water quality exceeds the standard or not and issuing an alarm. By measuring the ultraviolet-visible full-wavelength absorption spectrum of the detected water, combining with the water quality algorithm model and correction parameters, each water quality index in the water can be synchronously calculated. The method can be widely suitable for monitoring and alarming for various kinds of surface water, various kinds of sewage, drinking water, and for control of sewage and water supply treatment processes.

The invention discloses a steel rail tread defect recognition method based on combination of a gray image and a depth image. The method comprises the steps of establishing a steel rail tread image data set by utilizing a registered gray image and depth image pair of a steel rail tread, dividing the data set into a training sample set and a test sample set, and preprocessing the images of the dataset; performing defect recognition by adopting a special convolutional neural network structure, wherein a front end of the network is provided with two branch structures, which can extract features from the gray image and the depth image of the steel rail tread respectively; fusing feature information of the gray image and the depth image through feature graph connection, and then outputting preliminary prediction results by adopting a prediction module; and finally, screening the preliminary defect prediction results by adopting a non-maximum suppression method to obtain a final steel rail defect recognition result. The method combines two-dimensional and three-dimensional features of the steel rail tread at the same time, has the capability of distinguishing real defects and pseudo-defects, can reduce the misjudgment rate and the missing detection rate, and is especially suitable for defect recognition in a complex environment.

The invention discloses a real-time traffic condition acquisition method based on a mobile intelligent terminal. The mobile intelligent terminal identifies the traffic condition according to sensor information, traces a running route in combination with a road database in real time and calculates the running time according to a traced result of the running route and uploads the real-time road condition information to a server; and the server analyses massive received real-time traffic condition information, removes repeated data, saves the result into a traffic condition database and estimates the real-time traffic condition for a minority of road sections in short of uploaded data according to the traffic condition data in the traffic condition database by the compressive sensing technology, to collect the real-time traffic condition of the whole urban traffic network. According to the invention, the mobile intelligent terminal can be used for collecting the real-time traffic condition information so as to obtain massive traffic condition data. The method has the characteristics of low cost, high accuracy, high data volume, good real-time property, high network coverage, good expansibility and the like, and has a quite wide application prospect.

The invention provides a heterogeneous database platform data synchronization method. The heterogeneous database platform data synchronization method includes the following steps that a first external data exchange module and a second external data exchange module which correspond to a source database and a target database respectively are installed in a PostgreSQL database, and a first external data exchange module extender, a first external server, a second external data exchange module extender and a second server are built, wherein the source database and the target database are heterogeneous databases; a first external data table and a second external data table which are in mapping relation with the source database and the target database respectively are built, and triggers for capturing data changes are built. The PostgreSQL database and the corresponding data exchange modules serve as media innovatively to achieve data synchronization/copying between external multi-source heterogeneous databases.

In a system manages a plurality of pieces of sensor information in a plant, or the like, it can be reducing an amount of data stored in a database and easily a processing for searching a place of an anomaly and an anomaly cause.

A database management method for use in a computer for managing a database, the database management method including: a step of analyzing a query; a step of generating a first inquiry for searching the database for compressed data; a step of generating a second inquiry for executing a search of time-series data; a step of extracting given data from the obtained time-series data, based on a response result of the second inquiry; and a step of generating an output result by extracting data to be output to a client computer from the given data.

The invention discloses a traffic state detecting method based on multi-data fusion. On the basis of a clustering algorithm, GPS track segmentation is carried out on taxi GPS data and mobile phone GPSdata respectively based on users to obtain all taxi GPS segmentation tracks and mobile phone GPS segmentation tracks; with the taxi GPS segmentation tracks as training samples, an identification model is constructed and similar taxi GPS segmentation tracks are extracted in the mobile phone GPS segmentation tracks; on the basis of a map matching algorithm, the taxi GPS segmentation tracks and thesimilar taxi GPS segmentation tracks are matched to road sections in an urban road network; with a matching result of the two kinds of tracks, vehicle driving speeds at the corresponding road sectionsare calculated respectively; and according to an evidence theory, the vehicle driving speeds, calculated respectively based on the matching result of the two kinds of tracks, of the road section arefused and the vehicle driving speed of the road section is estimated. Therefore, the urban road traffic state information is detected accurately.