127 results about "Data averaging" patented technology

A thermostat system according to the invention includes: a central control device (typically a programmable thermostat with a processor having: a CPU, real time clock and a memory for storing a control program and data information), multiple rooms comprising a conditioned space, environmental control equipment, and multiple environmental sensors capable of sensing an environmental condition (such as temperature, humidity, or other condition). The sensors are associated with transmission means, which control transmission of sensor signals, and occupancy sensors. Each sensor measures a local environmental condition. Occupancy sensors comprise infrared or other motion sensors, light detection sensors, door opening sensors, and other such sensors that detect the presence of humans in a room of the conditioned space where its associated sensor is located. Space conditioning equipment is activated by comparison of a setpoint to a control value averaged from values of environmental conditions in occupied rooms.

The invention discloses a flow processing operation scheduling method and system for dynamically adjusting task allocation. The method comprises the steps of receiving the flow processing operation bya main control node server, and generating an initial task allocation scheme according to a given reference concurrency degree, available resources in a cluster and the self structure of the flow processing operation; during the service operation process of the flow processing operation, automatically reporting the own running state information of each calculation node server to a main control node server by the calculation node server itself, uniformly summarizing the running state information of all calculation node servers by the main control node server, and conducting the corresponding aggregation operation; predicting the data average processing amount and the corresponding resource occupation value of the next time period according to the information after the aggregation operationby the main control node server; further dynamically adjusting the flow processing task instances of all the calculation node servers, finally generating a dynamic allocation scheme of the flow processing operation and distributing the dynamic allocation scheme to corresponding calculation node servers.

A user interface for a pulse oximetry device that calculates physiologic parameters of a subject including at least a subject's heart rate and S_pO₂, is disclosed wherein the interface comprises a graphical display of at least one raw data signal of the pulse oximetry device that maintains heart and breath rate components and a display of the calculated heart rate and S_pO₂ of the subject. The interface may further include a user selectable data averaging function in which the interface is configured to selectively obtain and display averages of at least some of the calculated physiologic parameters over a defined period.

The invention belongs to the technical field of assembly and fastening, and provides a bolt pre-tightening force prediction method based on machine learning. The method comprises the following steps of data acquisition, data-based problem analysis, data averaging processing, multiple regression modeling, model parameter identification, statistic inspection and model verification and analysis, wherein tightening torque, a tightening angle and a nut end surface friction coefficient are used as input parameters, and the pre-tightening force is used as a prediction value. According to the method,the pre-tightening force can be effectively controlled through prediction, and a foundation is laid for obtaining good machine performance. The metod can be widely popularized in the technical field of assembly and fastening.

The invention relates to a method for recommending a target object, computing equipment and a computer storage medium. The method comprises the steps of generating input data, wherein the input data at least comprises click features, browsing features, purchase features and target object features of a user for a target object; averagely segmenting the input data into a plurality of sub-input data;predicting a click probability of the user through the first neural network model; predicting, via a second neural network model, a probability of transformation with respect to the target object, the second neural network model and the first neural network model sharing at least an embedding layer; and predicting a recommendation probability about the target object based on the click probabilityof the user, the transition probability about the target object and the third loss function. According to the method and the apparatus, the defect of overfitting caused by sparse sampled user behavior characteristics can be avoided, and optimization of multiple targets associated with the recommended target object is considered at the same time.

According to some embodiments, a Single-Instruction/Multiple-Data (SIMD) averaging instruction is used to process pixels of image data. The averaging instruction generates a set of four-pixel averages, where each average is generated from two pixels in a first source register and two pixels in a second source register. The first source register contains a plurality of pixels from a first row of pixels and the second source register contains a plurality of pixels from a second row. In one embodiment, the first and second rows are adjacent rows in an image and the averaging instruction is used, for example, to down-scale an image, perform color conversion, and the like. In another embodiment, the first and second rows are from different images and the averaging instruction is used, for example, in motion estimation for video encoding, in motion compensation for video decoding, and the like.

A digital camera for determining the chromaticity coordinates and the related color temperature of an object and the method thereof. A photosensor receives the reflected light of the object and outputting image data. An averaging unit outputs the red average, the green average and the blue average according to the image data. A chromaticity coordinate unit transforms the red average, the green average and the blue average into tristimulus values using a transformation matrix and outputs a chromaticity coordinate according to the tristimulus values. A color temperature unit outputs the color temperature according to the chromaticity coordinates.

A finger contact detecting apparatus, which detects a finger being swept on a fingerprint sensor of the finger contact detecting apparatus, the finger contact detecting apparatus including, a pixel data averaging unit calculating an average value of pixel data collected by the fingerprint sensor; a deviation adding unit calculating, based on the average value and respective pixel data of predetermined pixels obtained by the fingerprint sensor, a summation of deviations of the respective pixel data of the predetermined pixels; and a finger contact detecting unit determining whether the finger is separated from the fingerprint sensor based on the summation of deviations and a predetermined threshold value.

The invention discloses an anti-interference channel switching method suitable for a wireless sensor network. At first, according to IEEE802.11 wireless channel distribution and IEEE802.15.4 wireless channel distribution, wireless sensor network channels based on the IEEE802.15.4 are classified. According to a classification result, the wireless sensor network channels are reconstituted to channel assemblies of different types. Wireless sensor network nodes are classified through a minimum repeated node coordination method to correspond to the channel assemblies of the different types. A time superframe is divided into a plurality of time slots, and each time slot is divided into multiple secondary time slots. The network nodes carry out awakening monitoring on the corresponding time slots through a pseudorandom algorithm or an inquiry dispatch list method. At last, each network node carries out channel switching on the corresponding time slot according to a Latin square algorithm and an initial channel of the network node. According to the method, the performance indexes of end-to-end data average time delay, the data time delay upper limit and time delay jittering are improved.

The invention discloses a storage method for a data storage model of a credible cloud storage system. In the method, the confidence of a node is defined according to the ratio of on-line time to total time of the node to ensure that the node has highest confidence and best stability; and data access time is defined according to the available bandwidth between a user and the node and the existenceof a file requested by the user to ensure that data access time is minimum and the total data quantity stored in various nodes does not exceed the storage space of the nodes. The heuristic solving strategy reduces average data access time, and the average confidence gradually becomes more stable with the increase of the quantity of scheduling data. The method improves the reliability of the data and high efficiency of the access, ensures the safety and credibility of the cloud storage system, and has significance in the fields of cloud computing and dependable computing.

The invention provides a remote calling method. The remote calling method comprises the following steps that a client-side sends requests for calling remote methods and obtaining return values to a server side; the server side receives the requests and establishes a plurality of threads so as to execute the called remote methods, wherein in the executing process of the called remote methods, any thread in the threads is allowed to return a part of the return values through a part of return interfaces and the returning times are not limited; after all the return values are returned, the server side sends a calling end notice to the client-side. According to the remote calling method, any thread is allowed to return a part of the return values through a part of return interfaces and the returning times are not limited, the average data return time is shortened, distributed system interlayer data aggregation is quickened, data generation and data transmission are made to run in a staggered mode, and the responding time of a whole system is shortened. The invention further provides a remote calling system.

The invention relates to a hybrid updating industrial wireless sensor network scheduling method based on information age, and belongs to the technical field of industrial wireless sensor networks. According to the method, for an industrial wireless sensor network in which two data updating modes of periodic data and non-periodic data are mixed and coexist, the average information age of data in the network is optimized. Meanwhile, a throughput factor is considered; the link scheduling method comprises the following steps of: performing joint optimization on a link scheduling problem of a minimum information age and throughput weighted sum in a time slot-by-slot scheduling mode, expressing the optimization problem as a finite state Markov decision process, performing approximate representation on a state value function by utilizing a deep Q network, and obtaining the link scheduling method by adopting a deep reinforcement learning mode. According to the joint optimization method provided by the invention, the dimensionality of a system state space is reduced, and the timeliness of data delivery and the throughput of a network are improved.

Disclosed herein is a three dimensional small bin electromagnetic consecutive array data acquisition method used in oil exploration comprising the steps of recording data using small bin lattices on execution of arrangement electrodes, each acquisition station (E_x, E_y) records the natural electromagnetic field time series data with the same acquisition parameter simultaneously; interference is removed first, for recorded data processing to get interference-free data; for border points and center point, the recording point serves as center point, and the same component from adjacent two points to total points area added together to obtain the average value of electric field data at time domain for each observation point; for corner points, the average values of the same electric field component from adjacent two points to total survey points toward bin direction is calculated; the electric field components acquired in maximum space serve as the new electric field values respectively; new time series data acquired in which the noise and the static shift effect have been suppressed, and apparent resistivity and phase curves of each point are acquired after processing with conventional method.

The present invention provides a method for judging abnormality of a converter valve power module according to capacitor status. A capacitance value of the power module is calculated through a bridgearm data real-time analysis unit; a background database identifies a certain type of data abnormality; 1) a mean value and a standard deviation of this kind of data are calculated; the power module which deviates from the mean value of the data by more than a specified multiple of the standard deviation is determined as an abnormal module; 2) the parameters such as the capacitance values and optical fibre communication bit error rates of all power modules of one bridge arm are statistically compared with each other in the bridge arm to find out the abnormal module; 3) the parameters of one bridge arm such as the capacitance value and optical fibre communication bit error rate are statistically analyzed in a time range; if the parameters are significantly correlated with time, the power module is abnormal. The deterioration of the power module can be detected in advance by comprehensively detecting the parameters such as the capacitance value and communication optical fiber bit error rate of each power module.

The invention relates to a database system optimization method and device. The database system optimization method includes the steps: snap-shooting performance data of SQL (structured query language)statements of a database system every preset first time, arranging snapshots according to a time sequence, and saving the arranged snapshots; correspondingly performing variance calculation on performance data of a current snapshot and performance data of a snapshot of front sequence, and calculating total cache read data quantity and single average cache read data execution quantity corresponding to each SQL statement within the preset first time; acquiring the sum of number valves of the total cache read data quantity and the single average cache read data execution quantity of each SQL statement, and selecting SQL statements to be optimized based on the sum of the number valves. The performance data comprises execution times and cache read data quantity. According to the method, the SQL statements needing to be optimized can be accurately positioned, and optimizing efficiency is improved.

The present invention belongs to the technical field of power grid monitoring and relates to a submarine optical cable breakpoint location and disturbance location analysis method and system. The method comprises the following steps that: a data acquisition card is adopted to acquire signal strength data on an optical cable, multiple-point data averaging is performed on the acquired signal strength data, so that signal strength curves are obtained; the plurality of signal strength curves are accumulated; the absolute value of the difference of strength accumulation curves is calculated, so that a difference value curve is obtained, every two adjacent signal strength curves being accumulated to obtain one strength accumulation curve; values on the difference value curve are compared with athreshold value, points on the difference value curve, which exceed the threshold value, are judged as submarine cable disturbance events, if events occur in all points behind a certain point, it canbe determined that the point is an optical cable breakpoint; and points which are located behind the point on the strength accumulation curves and have vertical coordinates smaller than 0, are disturbance points. According to the submarine optical cable breakpoint location and disturbance location analysis method and system of the invention, the signals are accumulated in space and in time, so that a high signal-to-noise ratio is obtained; two adjacent groups of accumulated signals are subtracted from each other, so that the disturbance condition of the submarine optical cable can be judged,and the breakpoint position of the submarine optical cable is obtained. Therefore, with the method and system adopted, the breakpoint position of the optical cable can be judged when the disturbance of the optical cable is detected, and judgment is accurate, and calculation time is short.

The invention discloses a composite SPWM algorithm for a constant-current LED driving chip, and belongs to the field of LED display. The method includes: setting a digit N, a refresh level G and an optimization level K of the display gray data; when the gray data is not smaller than 512, dividing the gray data into H-bit high-order data and L-bit low-order data, N = H + L; according to the refresh level G and the optimization level K, averagely distributing H-bit high-order data into 2L sub-cycles, and uniformly distributing L-bit low-order data into the 2L sub-cycles; when the gray scale data is smaller than 512, dividing the gray scale data into a high gray scale group and a low gray scale group according to the actual gray scale data, namely visual data and invisible data, and grouping the invisible data according to the gray scale data by taking the actual gray scale data as a group; according to the gray data and the optimization level K, scattering the whole display period, totally 2N clock periods, into gray data sub-periods, and according to the optimization level K, uniformly distributing the visible data and the invisible data into the sub-periods.

The invention provides an abnormal stress diagnosis method for an FPSO single-point mooring system; the method comprises the following steps: monitoring sea condition environment data, FPSO motion and anchor chain tension data through a sensor arranged on an FPSO, and obtaining a basic database of monitoring data needed by evaluation; performing data cleaning on the acquired monitoring data, the data cleaning comprising data exception screening and time continuity checking; analyzing the cleaned monitoring data, setting monitoring time periods, and calculating the sea condition environment data, the FPSO movement data and the anchor chain tension data average value of each monitoring time period; setting monitoring periods, and counting FPSO movement and anchor chain tension data under different wind wave and flow combined sea conditions in each continuous monitoring period in each monitoring period; calculating an overall evaluation standard value; and evaluating whether the whole mooring system has an abnormal stress condition or not under the current sea condition through monitoring data.

The invention discloses an LED driving chip display control distributed PWM algorithm, and belongs to the technical field of LED display. The algorithm includes: setting a display gray binary data bitN and a refresh multiple M, wherein N is a positive integer and M is a non-negative integer less than N; according to the refresh multiple M, scattering the whole display period into 2M sub-periods,wherein each sub-period comprises 2K clock periods, and K is equal to N-M; dividing the gray scale data into M-bit high-order data and K-bit low-order data according to the refresh multiple M; averagely distributing the high-order data to 2M sections of sub-periods according to the size of the gray scale data; scattering and distributing the low-order data in 2M sections of sub-periods according to the size of the gray scale data; and combining the high-order data and the low-order data to generate distributed PWM scatter data. On the basis of a traditional PWM display algorithm, the display period is scattered through the distributed PWM algorithm, and the overall refresh rate is increased on the premise that the total gray scale is not changed; and supplementary design is performed on the distributed PWM algorithm, so that the problem of low gray blocks is effectively solved.

The invention relates to a method for determining a typical daily load curve by using comprehensive energy system energy consumption big data. According to the method, the original energy consumptionhistorical data is subjected to standardized preprocessing, so that the influence caused by large order-of-magnitude difference of data participating in clustering analysis is eliminated, abnormal data generated by human and other non-resistance factors are eliminated, and the accuracy and reasonability of a result are ensured. The optimal clustering number is determined by adopting a double-indexmutual verification method of a contour coefficient method SILHOUETTE index and an elbow method SSE index, so that the phenomenon of non-optimal result caused by self-calculation characteristics of asingle index is avoided. Compared with a typical daily load curve selected by a traditional peak load-apportionment proportional method, the method for solving the typical daily load by using the data averaging processing in the classification cluster has the advantages that the classification characteristics of the obtained energy consumption data are closer to the actual energy consumption demand characteristics, and the load prediction is more representative.