592results about How to "Avoid one-sidedness" patented technology

The invention discloses an individualized recommendation method based network behaviors. The method includes the following steps: (A). Generate the corresponding network behavior log of the user according to the search request sent by the users to the server and the report on the completion of document download, and record the keyword searched by users and downloaded document; (B). Analyze and clean up network behavior log, and modify system knowledge database and user matching database; (C). Find out users with the same interest from the modified user matching database and introduce them to users, and take the documents that users are interested in as the recommended document resource for users. The invention also discloses an individualized recommendation system based on network behaviors, which consists of network behavior log generating module, log analysis handling module, recommendation generating module, knowledge database, and user matching database. The invention has the advantages of high operating efficiency, strong usability of results, easy maintenance and expansion of the system, and capability to trigger users' interest.

The invention provides a quantitative characterization method of low penetration double-medium sandstone oil reservoir microscopic aperture structure, which comprises the following steps: selecting experiment samples, effectively combining various experiments, distributing samples, processing and analyzing experiment test data, combining macroscopic background and microscopic rock core, and combining static state analysis and dynamic production reality, thereby realizing quantitative characterization of ultra-low penetration double-medium sandstone oil reservoir microscopic aperture structure from qualitative analysis and semi-quantitative evaluation. The invention has the advantages that more comprehensive influence factors and micro crack, aperture throat parameter and nuclear magnetic resonance movable fluid parameter are considered, so the characterization result can better reflect change characteristics of ultra-low penetration double-medium sandstone oil reservoir microscopic aperture structure, which are consistent to the production exploitation real cases of the oil field, thereby effectively avoiding one-sidedness and limitation of single aspect evaluation result.

In order to achieve the load balance of network access traffic, the invention discloses a method for providing domain name resolution services, belonging to the field of communication. The method comprises the following steps: receiving a DNS (domain name system) request message with a specified domain name, which is sent by a client, and forwarding the DNS request message to at least two DNS servers for domain name resolution, wherein the DNS servers belong to different ISPs (Internet service provider); receiving the response message of the IP (Internet protocol) addresses of each web server, which is acquired after the operation of the domain name resolution is conducted and returned by each DNS server; selecting on the principle that the load of each outlet is balanced from the acquired IP addresses of each web server according to the current free bandwidth of each outlet corresponding to each web server; and sending the selection results to the client. Accordingly, the invention can prevent the traffic from leaned to one side and achieve the load balance in the network system. The invention discloses an outlet gateway device, a DNS relay device and a communication system.

The invention discloses a senile dementia monitoring system based on a healthy service robot. The senile dementia monitoring system based on the healthy service robot comprises the healthy service robot, an intelligent terminal and a cloud server. The healthy service robot comprises a robot body, a main control unit, a human-computer interaction unit and a medical detection unit; the human-computer interaction unit is connected with the main control unit and comprises a tablet computer, and the tablet computer is arranged in front of the chest of the robot body; the medical detection unit is connected with the main control unit and comprises a brain electrical detection device which is independent of the robot body, and the brain electrical detection device is connected with the intelligent terminal and the tablet computer through Bluetooth signals; the intelligent terminal and the tablet computer are connected with the cloud server through the mobile Internet, and data interaction between the intelligent terminal and the tablet computer is achieved through wireless signals. By means of the senile dementia monitoring system based on the healthy service robot, automatic auxiliary diagnosis and treatment of senile dementia can be achieved, the diagnostic accuracy is improved, prevention and early detection of the senile dementia are facilitated, the pathogenetic condition is mitigated from exacerbating, and the purpose of healing is achieved.

The invention pertains to the field of the image fusion technology in image process, which relates to a quality comprehensive evaluation method of fusion images based on fuzzy neural network and comprises the following steps: a sample set of fusion images is established, and each group of samples comprises a subjective evaluation grade sample of fusion images and two or more than two objective evaluating indicator samples obtained by evaluating the fusion image objectively; a quality evaluation module of fusion images based on fuzzy neural network is established; the obtained samples are trained, and the subjective evaluation grade sample of fusion images is adopted as expected output, and the correlation parameters for evaluating indicator weighing and fuzzy membership function are generated through network learning; the objective evaluating indicator of fusion images to be evaluated is calculated, and the evaluation grade result is generated by taking advantage of the established fusion image quality evaluation module. The method of the invention has comparatively good flexibility, and in the way of network training, novel fusion image quality evaluating indicator is learnt, so as to expand network evaluation ability and realize completely automatic evaluation.

The invention discloses a building overall-deformation monitoring method based on a three-dimensional laser scanning technology. The method includes the following steps: obtaining building point cloud data, segmenting the point cloud data, regularizing the data, performing deformation analysis on a point cloud model and judging a building overall-deformation condition. The building overall-deformation monitoring method based on the three-dimensional laser scanning technology is capable of rapidly extracting three-dimensional space characteristics of the point cloud model from the building mass point cloud data and the space characteristics have rotation and translation invariance so that attitude of the building in a three-dimensional space can be expressed uniquely and according to the variance condition of the three-dimensional space characteristics of the building point cloud model, the overall deformation condition of the building, such as sedimentation, inclination and rotation and the like in the three-dimensional space can be analyzed and judged. The building overall-deformation monitoring method based on the three-dimensional laser scanning technology makes full use of complete point cloud data of the surface of the building to analyze the overall deformation condition of the building and the measurement and analysis technology based on faces effectively prevents locality and one-sidedness brought by a deformation analysis result in traditional deformation monitoring based on points.

The invention provides a grid security comprehensive evaluation method which includes that a set of complete two-stage in-advance comprehensive evaluation index system and an each-stage security evaluation index calculating method are built aiming at the requirement of grid security operation evaluation, a grid security comprehensive evaluation model based on a gray area correlation analysis method and the game theory is further provided, initial evaluation is conducted on each one-stage index by the model, an obtained evaluation result is subjected to comprehensive evaluation, a correlation coefficient matrix of each one-stage index is determined by adopting the gray area correlation analysis method, weights are obtained by utilizing a game collection model pair analytic hierarchy process (AHP), an artificial neural network (ANN) and an entropy weight method and are objectively combined to obtain a combined weight, initial evaluation is conducted on each one-stage index, the AHP is adopted to determine a one-stage index weight, and the one-stage index weight and an initial evaluation result are subjected to weighing calculation to further obtain a grid security comprehensive evaluation result, namely the grid security quality ordering.

The invention discloses a traffic flow state judgment method based on multiple-cross-section vision sensing clustering analysis. Traffic flow data are acquired by a PTZ video camera arranged on the road side and are adopted to judge the expressway road traffic flow state according to a clustering analysis method. By means of the traffic flow state judgment method, traffic flow data easy to acquire like speeds and flow are combined with upstream traffic flow data and downstream traffic flow data to achieve clustering analysis, acquired clustering results are clear, and certain fault tolerance exists. In practical application, the clustering number can be modified according to specific conditions, and clustering results are simplified. By means of the method, traffic condition division methods and critical data suitable for characteristics of current expressways are provided, and traffic flow conditions are accurately and comprehensively reflected.

The invention belongs to the technical field of radars and particularly relates to a dual deep neural network-based radar range profile target identification method. The method comprises the steps of firstly performing preprocessing operations of random distance disturbance, sample expansion, noise addition and the like on range profile data of a target to enhance the robustness of an identification system; secondly in combination with a deep learning theory, proposing a dual deep neural network (DDNN) with an adaptive learning rate, and performing unsupervised pre-training and supervised fine adjustment on the DDNN to obtain DDNN model parameters; thirdly performing pre-identification on test samples by utilizing the DDNN to obtain pre-identification results of the samples in two sub-networks; and finally according to the pre-identification results, performing time-space multi-level decision fusion by utilizing an improved DS evidence theory to obtain a target identification result.

The invention discloses a projection pursuit-based method for evaluating flooding risk of a drainage pipe network, which relates to the technical field of system comprehensive evaluation. The method integrates multi-aspect flooding risk effect factors from a drainage pipe network model, a geographic information system and a database system and uses a projection pursuit evaluation method for evaluating the flooding risk of the drainage pipe network. In the method, linear projection is conducted on each evaluation indicator sample; an optimal projection direction vector is searched in accordancewith a certain principle and the optimal projection direction vector reflects the important level of each evaluation indicator, namely objective weight, and based on the objective weight, a comprehensive evaluation number is established for conducting evaluation grading on the flooding risk of the drainage pipe network, thus providing technical support for emergency rescue in flood season. The method avoids one-sidedness of human analysis in evaluation process, has more scientific evaluation result, and can vividly and directly represent disaster risk degree and distribution due to an obtained flooding disaster risk map, thus providing excellent decision platform for rescue dispose.

The invention provides an online evaluation method for compaction quality of an earth and rockfill dam material and provides an online evaluation method for compaction quality of a dam material, which is suitable for monitoring rolling parameters and compaction effect in real time and taking dam material property into consideration. The compaction quality of the earth and rockfill dam material is comprehensively evaluated in real time; and a technical scheme adopted in the method is that the online evaluation method for the compaction quality of the earth and rockfill dam material comprises the following steps: collecting field test pit experiment results by using a PDA (Personal Digital Assistant); establishing a compaction quality evaluation model; figuring out the compact quality of each grid of the current construction bin surface; next, obtaining the compaction quality in any position of the current full construction bin surface by using a spatial interpolation method; furthermore, analyzing a quality qualified or disqualified area according to a compaction quality control principle, figuring out qualified rate of the compaction quality of the current construction bin surface; and feeding back the qualified rate in time to instruct field construction so as to control construction quality. The online evaluation method for the compaction quality of the earth and rockfill dam material, provided by the invention, is mainly applied to online evaluation of the compaction quality of the earth and rockfill dam material.

The present invention discloses a method for scanning loophole which is realized by a loophole scanner comprising a user end, a browser, a scanning host machine and a destination host, wherein the scanning host machine portion comprises a control platform, a scanning mode configuration module, a scanning module and a loophole library, the scanning mode configuration module is embedded in the control platform, the user end performs remote control to the remote scanning host machine through Web browsers.

The invention discloses a method and device for detecting rain fall through laser. The device comprises a laser light source meeting a certain wavelength and power requirement, a parallel sheet light beam generating system based on a specified generation method, a two-dimensional water particle bidirectional sampling measurement area formed by two parallel sheets perpendicularly intersected in the horizontal direction, a linear array sensor and a rain fall detecting data processing and information feedback system. The device for detecting the rain fall through laser greatly improves the constant and stable property of detecting light and reduces measurement errors caused by light source power fluctuation. A real time humidity / meteorological parameter sensing critical starting method is adopted. Due to the fact that calibration and correction are conducted before detection, the measurement errors caused by drifting of work points of the system can be reduced to the largest extent, and meanwhile energy consumption of a measurement system is reduced. By means of the device for detecting the rain fall through the laser, the rain fall, raininess and a raindrop spectrum can be accurately and continuously observed and measured in real time. The device for detecting the rain fall through the laser can be applied to the related fields for observing, measuring and forecasting the rain fall including weather, hydrology, high way conditions, airport taking-off and landing and the like.

The utility model discloses a system used for creating the chatting platform and comprises a chatroom creating and originating client and a server background chatroom creating system, wherein the chatroom creating and originating client is used for providing the customer with an operation interface for creating the chatroom, acquiring the creating information submitted by the customer and transmitting the acquired creating information to the server background chatroom creating system; the server background chatroom creating system is responsible for receiving the chatroom creating information from the chatroom creating and originating client, creating the chatroom based on the received creating information and noticing the chatroom creating and originating client with the created chatroom information. The utility model also discloses a method for creating the chatting platform; the utility model can enable the customer to initiatively create the chatroom based on the self-requirement and ensure the customer to participate in the self-interested topic.

The invention discloses a method for evaluating the health state of a wind turbine generator based on multi-dimensional SCADA data, and aims at solving the problem of incomplete evaluation caused by single parameter used for evaluating the health state of the wind turbine generator in the traditional method, and extracting a plurality of characteristic parameters representing unit degradation information. According to the method, mutual information between parameters in the SCADA system is calculated through an empirical Copula function, and the magnitude of the mutual information can reflectthe degree of influence of the parameters on the performance of the fan. The parameters with large mutual information values are used as health assessment objects, and compared with a traditional method that a wind power curve is used as an assessment object, assessment of the health state of the wind turbine generator is more comprehensive and accurate. A method for dividing working conditions according to wind speed intervals is introduced into the model. And the method is combined with kernel principal component analysis to establish a wind turbine generator health state evaluation model based on adaptive KPCA. The diagnosis result shows that the wind turbine generator health evaluation result of the model is superior to the evaluation result of a traditional method.

The invention relates to the technical field of enterprise safety production comprehensive risk assessment, in particular to a safety production risk assessment method and system based on multi-levelgrey correlation analysis. The risk assessment method includes the following steps: establishing a comprehensive evaluation index system of enterprise safety in production which includes multiple evaluation indexes; Standardizing the original value of each evaluation index of each enterprise; Determining the weights of each evaluation index of each enterprise; by using the grey relational analysismethod,calculating the relational coefficient of each evaluation index, and calculating the comprehensive risk score index of each enterprise according to the weight and the relational coefficient. The safety production risk assessment method and system based on multi-level grey relational analysis comprises a plurality of evaluation indexes, Overcoming the one-sidedness of single index as a riskassessment standard, the method and system can evaluate the comprehensive risk of any enterprise qualitatively or quantitatively, which is helpful for enterprises to find their own problems, and canalso provide the reference data for the regulatory department of the enterprise 's safe production status.

The invention provides a pole tower displacement monitoring system which comprises a pole tower displacement monitoring terminal and an underground displacement monitoring terminal which is electrically connected with the pole tower displacement monitoring terminal. The pole tower displacement monitoring terminal is provided on a pole tower and comprises a master control module, an overground pole tower displacement sensor, a power supply module and a communication module. The overground pole tower displacement sensor, the power supply module and the communication module are electrically connected with the master control module respectively. The underground displacement monitoring terminal is provided on underground basement rock and comprises a control module and a displacement sensor which is electrically connected with the control module. According to the above technical scheme, displacement of the pole tower and the basement rock are monitored respectively through utilizing the displacement sensor, displacement of the pole tower relative to the basement rock can be calculated through the displacement of the pole tower and the basement rock, according to the monitoring scheme, onesidedness of only monitoring an inclination angle of the pole tower in the prior art is overcome, carrying out real-time on-line monitoring on the displacement of the pole tower more comprehensively and accurately can be realized, monitoring of real state information of a pole tower state is realized, and further planning and construction of a national electrical network are facilitated.

The three-dimensional ultrasonic imaging non-destructive inspection system is used in detecting, locating, quantifying and classifying faults inside industrial products including components and parts, and its measurement data may be exchanged with other system for searching cause of the faults and improving quality. Structurally, it has ultrasonic system, electromechanical executing system, A / D system, signal processing system, 3D display system, automatic control system and timing system installed on a computerized platform. During operation, the ultrasonic system sends out ultrasonic pulse to workpiece and receives the echo, the A / D system processes the echo signal and converts into digital signal fed to the computer, the signal processing system establishes the 3D data base of faults, and the 3D display system displays the 3D ultrasonic image with its 3D figure display software.

The invention relates to a method for controlling the quality of radix scutellariae medicinal materials, comprising the following steps: taking standard radix scutellariae medical materials, obtaining a nuclear magnetic resonance spectroscopy thereof, and using characteristic ingredients of the radix scutellariae to identify the characteristic peak of medicinal effective ingredients as the characteristic peak of the radix scutellariae; taking a radix scutellariae sample to be tested, adopting the same method as a preparation method, a test condition and a test method of the standard radix scutellariae medical materials to test, obtaining a fingerprint electropherogram, and comparing the nuclear magnetic resonance spectroscopy of the radix scutellariae medicinal materials to be tested with the fingerprint electropherogram of the standard radix scutellariae medical materials. According to the differences of characteristic resonance peaks of the fingerprint electropherogram between the radix scutellariae medicinal materials to be tested and the standard radix scutellariae medical materials and number of common characteristic resonance peaks, the radix scutellariae medicinal materials can be classified as the following grades: high-class products: N is greater than 20, first-class products: N is greater than and equal to 18 and is less than or equal to 20, second-class products: N is greater than or equal to 16 and is less than 18, qualified products: N is greater than or equal to 14 and is less than 16, and unqualified products: N is less than 14.

The embodiment of the invention provides a method and a device for segmentation on the basis of webpage content classification. The method comprises the following steps of: extracting the text information of webpage contents in search resources; dividing the classes of the text information according to the classes of the webpage contents; segmenting the text information according to segmentation dictionaries corresponding to the classes of the text information. According to the embodiment of the invention, the classes of the text information of the webpage contents in the search resources are divided, and the text information is segmented on the basis of the segmentation dictionaries corresponding to the classes, so as to adapt to different classes of language characteristics better, meanwhile, the segmentation accuracy for different classes is also improved, and the optimal processing for local segmentation is realized; moreover, the improvement of the accuracy of segmentation is close to the intention of a user and improve the user experience, and then reduce the operations of re-input, search and the like of the user, and improve the simplicity of operation, meanwhile, the response of equipment on the operation of the user is reduced, and the consumption of the system resources of the equipment is reduced.

The invention discloses a clustering method for topic views based on sentence similarity. The clustering method can be used for clustering main views about a certain topic in internet. The clustering method comprises the following steps: firstly, constructing a view lexicon aiming at a topic by utilizing a human-computer cooperation mode; secondly, extracting all view sentences of the topic and performing the view clustering by using the similarity of the view sentences; finally, selecting a representative view sentence for each view class according to the average similarity of the sentences. The clustering method disclosed by the invention has the advantages that a clustering result can be more diversified and refined; a user is enabled to learn the views and details of various parties of the topic more clearly; fuzziness and one-sidedness of view clustering and description are effectively avoided.

The invention provides an image recognition method based on color and texture features. The method includes the steps of evenly and respectively dividing a detection image A and a matched image B into n sub-blocks, calculating the color feature similarity distance Dk(A,B) and the texture feature similarity distance Tk(A,B) between the sub-block k of the of the detection image A and the sub-block k of the matched image B, calculating the color feature similarity distance C(A,B) and the texture feature similarity distance T(A,B) between the detection image A and the matched image B, and judging the similarity S(A,B) of the detection image A and the matched image B according to the color feature similarity distance C(A,B) and the texture feature similarity distance T(A,B) between the detection image A and the matched image B, wherein k is larger than zero and smaller than or equal to n. Compared with the prior art, the feature similarity of the images is calculated on the basis of matching of the color features and the texture features, accuracy and objectivity are improved, and the subjective judgment of the key word index is avoided.

The invention discloses a perforation parameter optimization method for maintaining balanced expansion of staged fracturing cracks of a horizontal well. The perforation parameter optimization method comprises the following steps: S1, estimating an inlet net pressure value of the fracturing cracks of the horizontal well; s2, calculating a perforation hole friction coefficient required for maintaining balanced expansion of the horizontal well fracturing cracks; s3, calculating perforation characteristic parameters; s4, determining optimal perforation parameters; s5, establishing a complete fluid-solid coupling hydraulic fracture expansion calculation model; and S6, predicting and evaluating the fracturing effect of the target block after the optimized perforation parameters are adopted. According to the method, the stress field heterogeneity, fluid-solid coupling in the dynamic hydraulic fracture expansion process and the multi-fracture stress shadow effect are considered, the influencecaused by the perforation hole abrasion phenomenon is also considered, the method can be effectively used for maintaining fracture balance expansion of horizontal well staged fracturing, operation iseasy, and practicability is achieved.

The invention relates to an analysis technology in comprehensive consideration of fresh water input need of different ecological functions of lake ecological systems.. In the analysis technology, lakeecological water need functions are divided into an ecological function, an environment function and a production function, and further, lake ecological need water is divided into 9 types, includingevapotranspire water need quantity, leakage water need quantity, aquatic organism and habitat need water, lake out surface runoff need water, lake out subsurface runoff need water, energy production need water, self-purification need water, shipping need water and landscape recreation need water. The water resource function coefficient is determined according to the difference of a maximum principle and a lake management target, and the lake ecological water need quantity under multi-target requirement is determined finally, the requirements on lake ecological system production, life and ecological comprehensive water need are met, and the problem that the water need requirement for the integral ecological system is difficult to provide because of single original lake ecological need water computation target is solved.

The invention provides an automatic diagnosing system for energy conservation, emission reduction and repair of an automobile. The system comprises an energy conservation and emission reduction detecting device, and an energy conservation and emission reduction diagnosing service center, wherein the energy conservation and emission reduction detecting device comprises an oil consumption detecting module, a tail gas emission detecting module, an OBD detecting module, an engine detecting module and a basis system detecting module, and is used for detecting energy conservation and emission reduction data comprising the oil consumption and the tail gas emission of the automobile so as to generate the detected data to be transferred to the energy conservation and emission reduction diagnosing service center to be processed; and the energy conservation and emission reduction diagnosing service center comprises a data analysis server, an intelligent diagnosis server, an on-line expert diagnosing module and an assisting server. The system can be applied to the comprehensive detection for the superscalar positions of the automobile and the intelligent network bug diagnosis, so that maintenance technicians can accurately repair and maintain in time, the unnecessary dismounting for the automobile is reduced, the energy-saving technology of the automobile is promoted, the consumption of the fuel and the discharge amount of the pollutants for the automobile are reduced, and the purposes of energy conservation and emission reduction are realized.

The present invention provides a mobile network assessment method. The method comprises: setting the corresponding relationships of application scenes of a mobile network to be assessed and the weight of each assessment index and the score calculation mode of each assessment index in advance; determining the weight of each assessment index and the score calculation mode of each assessment index according to externally inputted application scenes and the corresponding relationships; obtaining original data used for calculating the index value of each assessment index; calculating the index value of each assessment index according to the original data; calculating the score of each assessment index according to the index value of each assessment index and the score calculation mode of each assessment index; and respectively calculating the score of network quality, the score of user perception and the score of investment benefit according to the score of each assessment index and the weight of each assessment index. The mobile network assessment method provided by the invention is able to improve the assessment accuracy of a mobile network.

The present invention provides a method and system for fault remote determination of an intelligent ammeter. The method comprises: obtaining voltage and current parameter values collected by an intelligent ammeter through a remote communication interface; comparing obtained voltage and current parameter values with a preset threshold; is the voltage and current parameter values and a normal value exceed the preset threshold, determining that the intelligent ammeter is located in a fault state; obtaining the position of the intelligent ammeter located in the fault state and collecting a plurality of influence factor conditions corresponding to the position; comparing with a preset history database according to the influence factor conditions, and obtaining normal corresponding parameter values of the intelligent ammeter; and determining the fault type of the intelligent ammeter through a preset fault determination rule on the basis of the normal parameter values. Through adoption of a comparison method, the method and system for fault remote determination of intelligent ammeter are able to more reliably determine the faults of an intelligent ammeter and avoid the one-sided view of data because of providing elaborate determination basis and determination results.

The invention discloses a safety start method of a tree topology in an IPv6 over low power wireless personal area network (6LoWPAN), belonging to the filed of networks. The method comprises mutual authentication and trust assessment. Before node deployment, a network deployer allocates a unique identification (ID) and key for each node, so that mutual authentication can be achieved between two nodes if only the ID of the opposite party is known; and when a child node selects father nodes to access a network, trust assessment is carried out on the candidate father nodes, and a utility value method in a multi-target objective decision technology is utilized to comprehensively assess three indexes, namely the number of hops from the father node to a base station, consumed energy and time delay, so as to select an optimal father node. According to the method, node energy is saved, mutual authentication can be carried out by only IDs of the nodes and a small amount of information exchange but without the participation of a base station, and attack of malicious node can be resisted. Due to the introduction of trust assessment, the sideness solely depending on energy or hops is avoided, the energy consumption of the whole network is balanced, and the life of the network is prolonged, thus the method can be applied to scenes with small amount of node movement.

The invention provides an automatic detection method for a brake shoe borer loss fault of a railway wagon. Firstly, an area classifier, a positioning classifier and a fault judgment classifier are trained firstly; a brake shoe borer image to be tested is segmented through the area classifier, in the areas obtained after segmentation, a multi-level multiple-cascade-connection detection concept is adopted, a brake shoe borer is positioned through the positioning classifier, whether the brake shoe borer is lost or not is judged through the fault judgment classifier, and fully automatic detection on the brake shoe borer loss fault of the railway wagon is realized. By means of the automatic detection method for the brake shoe borer loss fault of the railway wagon, the fault detection rate reaches 99 percent, the detection speed reaches five frames / second, and the actual application requirement is met.