882 results about "Key factors" patented technology

A DataPath Engine coupled to a SAN provides automated storage provisioning between an application on a Storage Area Network (SAN) attached server and a data volume on a SAN attached storage subsystem. The apparatus provides a simple user interface that allows operators to use pre-created policies for criteria to select data paths that meet organizations uptime and performance requirements. The apparatus uses pathing methodologies to select the optimal data path from the candidates by rating SAN state, uptime, performance, and other key factors. This apparatus allows an enterprise to more efficiently and effectively manage and monitor large, complex, distributed SANs.

The invention relates to an SOH (state-of-health) online estimation method of a battery pack. The SOH online estimation method comprises the following steps of: measuring temperature T, voltage V and current I of an electric automobile during actual operation to acquire the following function: SOC (state-of-charge)=f(T, V, I) by utilizing a normalization algorithm, establishing a database with one-to-one correspondence between the temperature T, the voltage V and the current I and the SOC, measuring the SOC of a monomer battery with lowest voltage in an online manner by utilizing the database, and further measuring the SOH of the battery pack. The SOH online estimation method disclosed by the invention has the beneficial effects that: 1) as the measured SOC is that of the monomer battery with the lowest voltage, which is a key factor for restricting the discharge capacity of the battery pack, a user can know the SOH of the batteries in a more visual manner, the remaining capacity of the batteries can be judged in a more accurate manner by combining with the SOC value, and the continue voyage course of the electric automobile can be estimated in a more accurate manner; and 2) if the problem is caused by attenuation of the battery capacity, the problem can be obviously seen through the SOH, and the efficiency of after-sale service is improved.

The invention provides a contact network three-dimensional reconstruction method based on SIFT and LBP point cloud registration. The method comprises the first step of obtaining initial three-dimensional point cloud data of the environment where parts of a contact network to be reconstructed are located through motion-sensing peripheral Kinect for Windows, and conducting denoising, simplifying, partitioning clustering, fusing and other preprocessing operations on the initial three-dimensional point cloud data to obtain single-view-angle point cloud data of the parts of the contact network to be reconstructed, the second step of extracting key points through an SIFT algorithm, constructing description vectors of the key points by means of LBP features of uniform patterns and determining the corresponding relations between the key points in different point clouds according to the distances between the vectors, the third step of completing point cloud registration through a rough registration method and an ICP fine registration method and obtaining the complete three-dimensional point cloud data of the parts of the contact network to be reconstructed, and the fourth step of completing three-dimensional reconstruction through the Poisson surface reconstruction method and obtaining a three-dimensional model. According to the method, the key factor is point cloud registration which is the key step influencing the three-dimensional reconstruction speed; the description vectors of the key points are constructed by means of the LBP features of the uniform patterns, so that vector dimensions are reduced, the matching speed of the corresponding relations is increased, registration is accelerated, and the three-dimensional reconstruction speed is increased.

The invention provides a multiparty joint key production and digital sign method and system. A joint sign private key d is composed of m private key factors di. The i is equal to [1, m]. The m is greater than or equal to 3. The m private key factors di are produced by the joint parties independently and secretly when the private key is produced and are stored in own devices secretly. The joint digital sign is finished by the parties according to a certain sequence and is finished jointly through utilization of the secretly stored key factors di based on calculation. The system comprises m joint parties. Each joint party has an independent subsystem. Each subsystem is composed of three parts: a joint key production module, a joint sign first component calculation module and a joint sign second component calculation module. According to the method and the system, the multiparty joint key production and digital sign method of an SM2 cryptographic algorithm and various formed systems: acentric and centered systems are realized. The digital sign is no longer finished by a single individual and is finished by multiple parities jointly.

Consumer-generated product reviews are a mainstay of electronic commerce and a key factor in the consumer decision process. A shopper's typical online purchase decision can involve tedious reading of multiple reviews written by previous purchasers in order to find and compare products for purchase. Disclosed herein is an automated system, and associated methods, that identifies the product attributes discussed in consumer reviews and summarizes consumer sentiment for each attribute for each product thus, offering immense value to consumers and retailers alike.

The invention relates to the big data technology field, and the object of the invention is to provide a power plant device intelligent prediction overhaul method and a power plant device intelligent prediction overhaul system based on big data. According to the invention, the maintenance data of the maintenance working can be accumulated, and the quantitative analysis can be carried out, and at the same time, the on-line update of the maintenance database can be carried out, and then the latest maintenance data support can be provided for the maintenance personnel. The power plant device intelligent prediction overhaul method based on the big data is characterized in that a fault example knowledge base can be established; initial symptoms and necessary additional remark information of an example to be diagnosed can be acquired; retrieval key factors can be formed according to the additional remark information; the retrieval in the fault example knowledge base can be carried out according to the key factors, when the complete matching is realized, and then the conclusion and the maintenance scheme of the example can be returned, otherwise the similarity of the example to be diagnosed can be calculated, and a plurality of most similar fault examples can be extracted from the fault example knowledge base, and used as the return results; whether the retrieval is completed can be determined, when the retrieval is completed, then the results can be returned, otherwise the retrieval in the fault example knowledge base according to the key factors is required to be continued.

The invention relates to a method for classifying field questions by integrating with syntax structure relationship and field characteristics, which comprises the following steps: field terms are collected; a special field question classification system is defined; the syntax structures of the questions are analyzed; a sentence trunk is extracted; the sentence truck and the field vocabulary are taken as question classification characteristics; a question classification model is built through an improved Bayesian classification algorithm method; a special field question classification training corpus and a test corpus are set up; a special field question classifier is set up. Because question classification is a very important step in an answering system and a key factor for establishing answer extraction strategies and positioning answers, the method of the invention can select the sentence trunk and the field vocabulary as the classification characteristics based on the syntax structure analysis by integrating with the field characteristics, adopts the improved Bayesian classification algorithm method, builds the question classification model and takes the question classification test in the field of Yunnan tourism; the result shows the method is effective, and improves the field question classification accuracy, thereby offering consultancy service to the users with high efficiency, quickly and accurately.

The invention provides a driving behavior evaluation system which comprises a vehicle-mounted intelligent terminal, a cloud server, a mobile client and a management background. The vehicle-mounted intelligent terminal is used to collect and process vehicle data and transmit the data to the cloud server. The cloud server is provided with a driving risk scoring model which periodically calculates and scores driving data. A user views driving behavior evaluation in the account of the user through the mobile client. An insurance company views the driving behavior evaluation and data details of thecorresponding user through the management background. The system provided by the invention can visually detect and evaluate key driving safety factors, prevents risk understanding rule revising caused by indicators used in a guarantee slip, and reduces the claims cost of an insurance company.

The invention discloses a new network word discovery method in combination with internal polymerization degree and external discrete information entropy. The new network word discovery method comprises the following steps: carrying out word segmentation treatment on all text sentences in network corpora, and taking all different segmented word strings as candidate word strings; and calculating the internal polymerization degree and the external discrete information entropy of the candidate word string with the frequency of occurrence in the network corpora exceeding a fixed threshold value, and further judging if a candidate target word string is a new network word according to the internal polymerization degree and the external discrete information entropy of the candidate word string. According to the new network word discovery method, two key factors for judging if one candidate word string is the new network word are proposed as follows: the internal polymerization degree and the external discrete information entropy of the candidate word string, and meanwhile, the stability, the independence and the completeness of the candidate word string are considered, so that the new network word can be effectively discovered.

Network-on-Chip (NoC) is an oncoming solution to the communication bottleneck of System-on-Chip (SoC). For a good design, it runs a simulation verification before the design is realized. The key factors to the accuracy and simulation speed of a simulator depend on how the simulator abstracts the NoC design. The present invention provides an object-oriented NoC modeling, which divides the NoC design space into many design blocks and models them into many abstraction levels. The present invention defines these models carefully to obtain good hardware accuracy. The present invention also provides an object implementation library of different abstraction levels. Thereby, the present invention can reduce the coding time via selecting required components from the object implementation library, inheriting them with some modifications or using them directly. The present invention extends the design exploration space of NoC, preserves good hardware characteristics, and significantly reduces coding effort of a new NoC design.

This invention introduces a method, system and computer readable media that enables a computer system or computer networked system to perform enterprise portfolio transition optimization. The invention considers several key factors that are traditionally treated informally. The invention provides a sequential decision model for enterprise portfolio transition management of computer and software resources. Using a finite state Markov Decision process, a mathematical formulation is developed to ensure an optimal enterprise portfolio transition plan, with the objective of balancing expected value and risk, that is solved numerically via an approximate dynamic programming algorithm. The output of the model is a set of recommendations in the form of a transition plan for each of the computer and software resources selected within the enterprise portfolio during each phase of a planning horizon.

A probability evaluation method of failure caused by typhoon to a power transmission line is suitable for evaluating failure probability after the power transmission line is affected by the typhoon. The method mainly comprises the steps of quantitative evaluation on the power transmission line affected by the typhoon as well as environmental factors and probability modeling of the line failure caused by the typhoon. In the quantitative evaluation, ways of the failure caused by the typhoon to the power transmission line and key factors including inner factors (design strength, state and the like of lines) and outer factors (typhoon, terrain, rainfall and other factors) are mainly evaluated; and in the probability modeling, a reasonable failure probability model is mainly established to calculate the line failure probability corresponding to the quantitative evaluation results of the key factors. The probability evaluation method has the beneficial effects that the evaluation on various loads and real-time anti-wind capability of complicated lines and towers is avoided, the effect of the inner factors and the outer factors and the characteristics of the various failure ways are simultaneously considered, a mechanism that the failure of the line is caused by the typhoon is satisfied, and the capacity of a power system in defending the typhoon disaster is improved in combination with a wide-area measurement, analysis, protection and control system.

The invention discloses a power network area division method based on an evaluation index system of a power distribution network and clustering analysis. The power network area division method comprises the following steps of: S1, selecting multiple primary indexes capable of reflecting the current situation of a power distribution network in a certain urban, and establishing the evaluation index system of the power distribution network by utilizing a systematic clustering method; S2, determining the comprehensive weight of each evaluation index in each class in the evaluation index system by adopting a subjective and objective analysis method, in which an improved hierarchical analysis method and an entropy weight method are combined, and, in combination with a scoring value of each evaluation index, obtaining the comprehensive score of the power distribution network in an evaluated area; and S3, performing clustering analysis of the comprehensive score of the power distribution network in the evaluated area so as to obtain a classification result of the power distribution network in the whole area. According to the power network area division method disclosed by the invention, on the basis of the general characteristics of the power distribution network, the development current situation and the development capability of the power distribution network are scientifically evaluated; and practical and reliable basis is provided for determining a key factor influencing development of the power distribution network.

The invention relates to a key management method used for a wireless sensor network, in particular relates to a key management method adopting the combined key technology, and belongs to the field of wireless sensor network safety technology. The key management method comprises the three steps as follows: system building, key generation and key updating, wherein the step of key generation comprises three processes of system parameter building, key factor and mapping algorithm generation, and shared key building. Compared with the prior art, the key management method has certain degrees of improvements on safety, storage and energy conservation, solves the problem that the sensor mode storage space is limited, ensures that any adjacent nodes can share a key, makes up for a deficiency that the sensor network is not provided with an authentication center, and saves the storage space.

The invention discloses a method for evaluating a distributed photovoltaic receiving capability of a power distribution network. The method comprises the following steps: analyzing factors restricting the distributed photovoltaic receiving capability; constructing a distributed photovoltaic receiving capability analysis optimization model; carrying out sequential verification for a specific photovoltaic configuration scheme; selecting an optimization algorithm suitable for photovoltaic receiving capability analysis; analyzing a photovoltaic integrated receiving capability; and the like. According to the method, from the perspective of influences exerted by distributed solar power on the operation mechanism and the analysis model of the distributed power network, key factors affecting the photovoltaic receiving capability of the power network are presented, the photovoltaic receiving capability optimization model is established under a sequential analysis framework, an optimization algorithm applied to solving the problem of the photovoltaic receiving capability is brought forward, the effectiveness of the algorithm is verified through an IEEE standard example, correlation principles and suggestions about reasonable access of the distributed solar power are put forward, and a good theoretical foundation good scientific guidance are provided for receiving and planning of distributed power sources and planning construction work of load response measures at a demand side.

The invention relates to a driving behavior evaluation method based on the image identification technology. The method comprises steps that S1, whether a vehicle starts is determined, if the vehicle starts, a S2 is performed; if the vehicle does not start, a standby state continues; S2, the sensor information of the vehicle is acquired, the sensor information is comprehensively determined and analyzed to acquire vehicle driving data; S3, the image information of objects around the vehicle is acquired, and distances of the objects around the vehicle relative to the vehicle are calculated; S4, classification processing of the identified objects and the identified images is carried out, and corresponding data is recorded; and S5, the vehicle driving data acquired in the S2 and the image identification classification data of the S4 are uploaded to a cloud server and are stored in a database DataBase. The method is advantaged in that key driving safety factors can be visually detected and evaluated, a mode of rule reforming for risk understanding through indexes utilized by traditional declaration forms is not employed, and compensation cost of an insurance company is reduced.

The invention relates to the technical field of a medical treatment information decision-making system and provides a method for extracting a morbidity key factor and early warning a disease. The method comprises the following steps: pre-treating a data: converting a medical record file data into a training value matrix; establishing a disease early warning model; and searching for an optimal early warning model through verification. The invention also provides a system for extracting the morbidity key factor and early warning the disease. Through the method and the system for extracting the morbidity key factor and early warning the disease provided by the invention, a high-risk factor of the disease is extracted, the early warning of disease mutation is performed, the realization is simple and the effect is good.

The invention discloses a method for evaluating probability of forest fire induced transmission line fault, which belongs to the technical field of power systems and automation thereof. By adopting the method disclosed by the invention, quantitative evaluation on probability of forest fire induced transmission line fault is realized, an accurate line fault probability model is created according to the principle of the forest fire induced transmission line fault, internal and external factors related to the transmission line fault are correctly reflected, the evaluation on the probability of the forest fire induced transmission line fault is not depended on the accumulation of historical data, and key factors can be considered, so that the adaptability is strong. The method disclosed by the invention is used for greatly promoting the risk management of transmission lines and improving the external disaster defense ability of the power systems.

The invention discloses a method for safely transmitting data based on a wireless network. A pair of key factors and a group of key sets are respectively arranged at a system end and an equipment end; during communication of the system end and the equipment end, a sender calculates a check sum of the data to be sent, calculates an authentication identifier (ID) by using the key factors and an equipment identifier, randomly selects a key from the key sets to encrypt the data to be sent, and sends the encrypted data and an adopted key code; and after receiving the data, the receiver acquires the corresponding key from the key sets through the key code, decrypts the data, calculates the authentication ID by using the equipment identifier and the key factors, judges whether the authentication ID accords with the authentication ID which is sent, and judges whether the check sum is accurate if the authentication ID accords with the authentication ID which is sent, so that the data can be safely transmitted. The method has the advantages that: the equipment identifier is fully utilized; functions of dynamic identity identification, data check and transmission encryption are integrated; safety communication of the data can be guaranteed; and presetting of an unrepeatable master key in each piece of equipment is not required.

The invention provides a new algorithm for an atmospheric environment capacity by using a region air quality model (RAQM). The new algorithm comprises the following computation steps: utilizing a meso-scale meteorological model to perform analog computation on an average value of year-round meteorological elements per hour in an estimation region to obtain uout and uin; utilizing the RAQM to perform analog computation on an average value of pollutant concentration per hour in an estimation year in the estimation region to obtain c; using a process analysis module to output transportation volumes Fout and Fin, dry deposition volume Ddry, wet deposition volume Dwet and chemical conversion volume T of pollutants per hour; performing the computation to obtain V and Asection; using cstandard to obtain a static volume of each atmospheric pollutant in the estimation region; and according to an expression of atmospheric environment capacity Q, performing the calculation to obtain a total environmental volume of atmospheric pollutants in the estimation region. With the adoption of the new algorithm provided by the invention, not only is the maximal capacity of atmospheres to contain the pollutants, regional transportation features of the atmospheric pollutants are reflected, but also key factors of influencing the pollutants in the estimation region are obtained, and assessment judgment basis such as more reasonable theories, more reliable data and more credible result can be provided for atmospheric environmental impact assessment.

The invention relates to a heterogeneous wireless network access selection method based on users. According to different service flow communication requirements of the users, network, terminal and user parameters are extracted, parameter key factors are quantized based on a fuzzy function, parameters are compared through an analytic hierarchy process, and the weights of the key factors are obtained; then according to an ordinal number preference algorithm similar to an ideal scheme, the close degree value of alternative network parameters is obtained by combining the parameter quantized value with the weights; network access is selected according to the close degree value. Network received signal intensity is sampled and pre-estimated, and calling drop caused by attenuation of received signal intensity of a selected access network is reduced. Through an improved fuzzy decision quantitative method, algorithm complexity caused by building of a fuzzy rule base is avoided, and calculation complexity is lowered. Optimal network access can be selected according to service types of the users, network congestion is reduced, and network resources are fully utilized.

The invention relates to a coating method capable of improving a laser induced damage threshold of a high-reflectivity film and belongs to the field of film optics. The coating method mainly aims at two key factors of absorption and defects influencing a laser induced damage threshold of a high-reflectivity laser film, and after electron beam evaporation coating of each film layer is finished, utilizes high-energy ion beams to bombard the film layer. The coating method retains unique and beneficial performances of a laser film coated by electron beam thermal evaporation, improves intrinsic absorption and defect density of a film, greatly improves a laser induced damage threshold of a high-reflectivity film, and has the characteristics of strong pertinence, high coating quality, simpleness and good feasibility.

The invention relates to a task optimized-scheduling method in a data center on the basis of critical paths of a workflow. The task optimized scheduling method comprises the following steps of according to the difference of all subtasks in the applied workflow, determining key factors influencing the system performance by the data center, comparing the cost performance of all the subtasks according to an optimization objective and the workflow characteristics, and determining resource nodes distributed to all the subtasks so as to provide two scheduling methods of the resource nodes on the basis of different requirements of users and enable the rent of the resource nodes to be optimized or the processing time of the workflow to be shortest, so the maximum data processing capability purchased by unit fund is realized while the rent expense of resources is saved, or the cost performance of the system is improved, the operating efficiency of the system is enhanced, the processing time of the workflow is reduced, and simultaneously, the execution plan of the resource nodes is generated. The task optimized-scheduling method has the beneficial effects that the two factors of the time and the quantity of the nodes in the rent cost of resource nodes are both considered, the minimized rent expense of the resource nodes is used for purchasing the resource nodes with the strongest computing capability; a mathematical model of the method can adapt to various types of applications, and the operating cost of the applications is greatly reduced.

The invention provides a dynamic frictional force testing system and a dynamic frictional force testing method of pavement materials, which aim at solving the problems that a skid resistant testing method in the prior art is large in deviation of testing results, cannot perform testing in all weather and is poor in stability of testing results and the like. The dynamic frictional force testing system of pavement materials comprises a turning system, a loading system, a temperature control system and a testing system. The dynamic frictional force testing system of pavement materials and the testing method adopt simulated dynamic friction and simulate temperature, rotation speed, pressure and other key factors to test dynamic frictional force of the pavement materials. The dynamic frictional force testing system and the dynamic frictional force testing method of pavement materials have the advantages of being capable of performing testing in all weather, accurate in testing results, stable in testing results, and further capable of directly observing appearance changing of the pavement materials under the dynamic friction condition.

An inventory forecasting model and its construction method based on chaotic neural network. The inventory of finished products is the key factor in precise distribution. If the inventory of finished products is sufficient, accurate delivery will be guaranteed, but the high inventory of finished products will bring a negative impact on the enterprise. The risk is high. On the one hand, it is difficult to process other materials after the original roll is processed into finished products. Once the user does not use it, it is likely to become a waste product. On the other hand, the finished product inventory takes up a large inventory space, which will make Limited storage capacity is getting tighter. The present invention divides the work into two phases. The first is the learning phase. The data of all the distribution users of the sample companies in the past three years are used as samples to establish a model, and these samples are used to learn and adjust the connection weight coefficients of the chaotic neural network, so that the network Realize the given input-output relationship; then the implementation stage, use the trained neural network to obtain the expected effect, establish a perfect calculation model, and realize the reasonable setting of the inventory.

The invention discloses a method for using a most influential node in a social network to achieve efficient viral marketing. The method for using the most influential node in the social network to achieve efficient viral marketing sequentially includes the steps of user definition and resource definition, establishment of edge connection for relationships between users and resources, establishment of interest strength between every two users, definition of importance measure indexes of weighted network nodes in boundary viewing dimension, calculation of a sum of edge weights in an NN assembly in a weighted network, establishment of a marketing model and the like. According to the method for using the most influential node in the social network to achieve efficient viral marketing, attention records between the users and the resources in the real social network are used, user interests are found, user interest strength relational diagrams are constructed, common attention of the users is used, on this basis, a half-partial centrality method based on neighborhood information is adopted to determine influential nodes, the nodes serve as initial nodes, spread of marketing information is carried out on a user interest network, key factors which can well restore interpersonal interaction processes in real life and comprise the accumulation effect, the social reinforcement effect and friend relationship strength are introduced into a spreading model, and the method for using the most influential node in the social network to achieve efficient viral marketing has the advantages of being low in calculated amount and good in robustness.

The invention provides a forest aboveground biomass inversion method fused with spectrum and texture features and a forest aboveground biomass inversion system fused with the spectrum and texture features. The method comprises the following steps of calculating an aboveground biomass of a research region sample plot so as to obtain a sample plot biomass observation value; performing geometric correction and radiometric correction on high-resolution remote-sensing image panchromatic data and multispectral data; respectively performing statistical regression on the sample plot biomass observation value and a corresponding spectrum feature vegetation index, and selecting a spectrum feature inversion model; extracting various texture feature variables under different windows, respectively performing statistical regression on the sample plot biomass observation value and the corresponding texture feature variables, and selecting a texture feature inversion model; determining a weight through a sensitivity analysis of a spectrum key factor and a texture key factor, constructing a spectrum texture feature combination inversion model of the biomass, and realizing the forest aboveground biomass inversion. The method and the system provided by the invention have the advantages that the spectrum features and the texture features are fused, and the advantages of the spectrum features and the texture features for biomass inversion are fully exerted, so that the quantitative inversion precision of a forest aboveground biomass is effectively improved.

A microthermophotovoltaic (micro-TPV) system is a novel micro power device. The system fully utilizes the high surface-to-volume ratio of a microcombustor, and is able to deliver and electrical power output of 0.5-10 W in a package of the order of centimeters. The system comprises mainly a combustor-emitter, a filter, a photovoltaic (PV) cell array, and cooling fins. The combustor-emitter functions to convert chemical energy into radiative heat energy. The filter is able to recycle a large part of the unusable energy that cannot be converted into electricity by the PV cell array. The PV cell array is used to convert radiative heat energy into electricity. The system has no moving parts. Its fabrication and assembly are relatively easy. As a result, it can be readily used as a power source of micro mechanical devices and portable devices, in which convenience and low cost reliability and ease of maintenance are the key factors of consideration.

The invention discloses a control method and a control device for anti-condensation of an air conditioner, and belongs to the technical field of air conditioners. The control method comprises the following steps: whether the air conditioner runs in a first state is continuously detected; a first time T1 of running in the first state of the air conditioner is recorded; when the first time T1 reaches a first preset time T1 ', the air conditioner is set to be switched to a second state for running; and a second time T2 of continuously running in the second state of the air conditioner is recordeduntil the second time T2 reaches a second preset time T2 ', and then the air conditioner is switched from the second state to the first state to run. The corresponding control device is manufacturedaccording to the control method. According to the control method and the control device, an angle of an air guide plate and a rotating speed of a fan are simultaneously used as important conditions for judging whether condensation can be easily generated or not and key factors of preventing the condensation from being generated, whether the air conditioner is in a state of easily generating condensation or not can be accurately judged, and the condensation can be prevented from being generated in a targeted mode.

Relational database applications such as index selection, histogram tuning, approximate query processing, and statistics selection have recognized the importance of leveraging workloads. Often these applications are presented with large workloads, i.e., a set of SQL DML statements, as input. A key factor affecting the scalability of such applications is the size of the workload. The invention concerns workload compression which helps improve the scalability of such applications. The exemplary embodiment is broadly applicable to a variety of workload-driven applications, while allowing for incorporation of application specific knowledge. The process is described in detail in the context of two workload-driven applications: index selection and approximate query processing.