133 results about "Conjoint analysis" patented technology

Disclosed are methods and apparatus for conducting market research and developing product designs. The methods involve generating and presenting, typically electronically, generations of design alternatives to persons participating in the design, selection, or market research exercise. The participants transmit data indicative of their preferences among or between the presented design alternatives. Some of the data is used to conduct a conjoint analysis or non-convergent exercise to investigate the drivers of the preferences of the group or its members, and at least a portion are used to derive follow-on generations of design alternatives or proposals. The follow-on designs are preferably generated through the use of an evolutionary or genetic computer program, influenced by the participants' preferences. The process results in the generation of one or more preferred product forms and information permitting a better understanding of what attributes of the product influence the preferences of the test group members.

Disclosed are methods and apparatus for conducting market research and developing product designs. The methods involve generating and presenting, typically electronically, generations of design alternatives to persons participating in the design, selection, or market research exercise. The participants transmit data indicative of their preferences among or between the presented design alternatives. Some of the data is used to conduct a conjoint analysis or non-convergent exercise to investigate the drivers of the preferences of the group or its members, and at least a portion are used to derive follow-on generations of design alternatives or proposals. The follow-on designs are preferably generated through the use of an evolutionary or genetic computer program, influenced by the participants' preferences. The process results in the generation of one or more preferred product forms and information permitting a better understanding of what attributes of the product influence the preferences of the test group members.

The market simulator / optimizer of the present invention combines partworth valuation techniques of Conjoint analysis with Nash equilibrium profit-maximization methodologies for sophisticated statistical treatment of a virtual available market comprising a multiplicity of virtual customers. An easy-to-use graphical user interface allows a user to arrange various market component icons to model various market characteristics. Associated with the market component icons are various distributions, including a benefit distribution containing values indicative of respective benefits to the multiplicity of virtual customer, and a cost distribution containing values indicative of respective costs associated with providing the respective benefits to the multiplicity of virtual customers.

The invention discloses an electrical equipment defect detection method based on fusion of an ultraviolet video and an infrared video. The electrical equipment defect detection method comprises the following steps: ultraviolet images and infrared images of electrical equipment are obtained, and meanwhile, high accuracy, position posture and time synchronization information of the electrical equipment are recorded at the time of shooting and imaging; according to any frame of the shot ultraviolet images and infrared images of the electrical equipment, multiple frames of continuous images previous to and following the frame are selected for automatic registration; the ultraviolet images and infrared images after the registration are subjected to heterologous data frame alignment based on a timestamp; the ultraviolet images are subjected to mean filtering, threshold segmentation, light spot detection, region growing and light spot clustering analysis to obtain discharge points; the infrared images are subjected to image mosaic, region segmentation, target extraction and temperature retrieval to obtain temperature anomaly; discharge and temperature conjoint analysis is conducted in combination with the ultraviolet images and infrared images after processing to obtain a diagnosis result report finally. The electrical equipment defect detection method based on fusion of the ultraviolet video and the infrared video is high in automation degree, efficient in detection and simple in operation.

The present invention is a software-based dynamic negotiation system that walks an individual or team through a preparation process so they are prepared to enter negotiations. To accomplish this goal, the system solicits feedback from key stakeholders and completes conjoint analysis to understand how team members weigh particular issues and options while also formulating scenarios to test weightings, offers an understanding of possible alternatives, and create equally weighted offers for use in delivering multiple equivalent simultaneous offers. The system provides a framework for effective negotiation that permeates negotiation strategy best practices throughout an organization, as all employees will undertake the same preparation process and utilize similar strategies.

A conjoint analysis method for electroencephalograph and electromyography signals based on autonomous movement and imagination movement comprises the steps of performing system setup, and using a LabVIEW 8.6 to generate square wave pulse signals; respectively collecting electroencephalograph signals and electromyography signals including electroencephalograph signals and electromyography signals in autonomous movement modalities and in imagination movement modalities; performing noise removal pretreatment on collected original data; performing electroencephalograph and electromyography time-domain signal analysis in the autonomous movement and imagination movement modalities on electroencephalograph and electromyography signal time-domain pictures which are performed with noise removal pretreatment in the autonomous movement and imagination movement modalities; performing time-frequency signal analysis on electroencephalograph and electromyography signals performed with noise removal pretreatment and in the autonomous movement and imagination movement modalities based on Morlet wavelet transformation; and performing partial directional coherence analysis, and in particular adopting granger causality to perform the partial directional coherence analysis. The conjoint analysis method provides new evaluation parameters for monitoring recovery auxiliary equipment and assessing organism movement level.

The invention discloses a brain ASL, SPECT and MRI image registration and fusion conjoint analysis method and system. Registration is respectively carried out to an ASL image and an MRI image by taking the MRI image as a standard; the ASL image and an SPECT image are fused according to different transparencies; a region to be computed is marked in the faultage of the SPECT image; a closed curve is obtained through carrying out a cubic spline interpolation to the ASL image; the volume and the gray value corresponding to the region to be computed and the gray value of an interesting region body through a circular truncated cone approach mode. According to the invention, the advantages of the ASL image reflected brain blood perfusion, the SPECT image reflected brain blood perfusion and the MRI provided brain structure change are combined; an interesting region is segmented and analyzed through providing interactive calibration operation a doctor and a medical expert; the judgement accuracy of a brain ischemic disease is improved; and iconography instructions are provided for a clinician to formulate a rational therapeutic schedule.

Methods, systems, and computer program products for facilitating user choices among complex alternatives utilize conjoint analysis in combination with psychological tests, skills tests, or configuration software to simplify choices to be made by the user. A selector tool presents a user with a first and second series of choices relating to attributes of complex alternatives available to the user. A utilities calculation engine calculates the relative utility of each of the complex alternatives to the user and presents output to the user, which indicates the relative utility of each of the complex alternatives. The user can then select the complex alternative that has the highest utility value for the user based on the calculated relative utility values. Configuration software, psychological tests, and / or skills tests or personality tests may be used before or after the conjoint analysis to facilitate user choices among complex alternatives by selecting attributes used for the conjoint analysis and / or selecting among results of the conjoint analysis.

The invention relates a visualization characterization technology of a coal sample, and in particular relates to a visualization quantitative CT (Captive Test) characterization method for component distribution and a physical structure of a coal sample. The visualization quantitative CT characterization method comprises the following steps of: sampling and pre-testing the coal sample; carrying out an X-ray absorption characteristic analysis on each component of a second coal sample; carrying out X-ray absorption characteristic analysis on residual minerals; carrying out a CT on the coal sample; establishing a mathematical model and carrying out a numerical analysis on CT slices; and carrying out visualization quantitative characterization. The CT characterization method provided by the invention adopts a plurality of CT data obtained by monochromatic X-ray experiment energy to carry out conjoint analysis, and detects the information of a component, dimension of which is smaller than CT resolution dimension, on a CT picture by establishing a data model on a single CT element, so that the visualization result of the component distribution characteristic and the physical structure of the coal sample is accurate.

The invention relates to a conjoint analysis method for estimating the DNA abundance of fishes based on an environment DNA technology. The conjoint analysis method includes the steps that the total DNA abundance of the fishes is acquired through timed and quantified PCR; the species composition proportion of the fishes is acquired through 454 GS-FLX Titanium sequencing analysis; conjoint analysis of target species is performed through sequencing data and timed and quantified PCR data; a relative distribution diagram of mitochondrial DNA of the fishes in an environment is drawn through sufer 8.0 software. Based on the environment DNA identification technology, weather species exist and how many species exist can be analyzed just by collecting water samples without depending on fish species capturing, a sampling method is simple, and fish resources can be protected to the maximum degree; meanwhile, for some species which are rarely distributed and difficult to capture, the method is still more effective than traditional fishing investigation, the method can effectively solve the problem that effective species specificity primers are difficult to obtain when multiple closely related species exist in samples, and NDA abundance information of all species can be known just by conducting experiment once respectively through the two technologies.

A system and method directed to improving efforts to plan for investor life goals. The method combines unique approaches of assessing investor risk tolerance using utility theory and investor preferences using conjoint analysis, Analytic Hierarchy Process (“AHP”), or the like in combination with existing industry financial projection methods using linear projections, Monte Carlo simulation, or the like. Further, the method improves upon existing financial projection approaches with the addition of regression techniques to streamline adjustments to the plan objectives, resources, and constraints. The method includes a means of determining an optimal combination of attribute preferences that have an acceptable probability of achieving plan goals while maximizing investor satisfaction as measured by total utility.

In a system and method for conjoint analysis, corresponding utility values are determined for a plurality of individual concept elements and for combinations of multiple concept elements, e.g., pair wise combinations of concept elements. A regression technique, e.g., least squares linear regression, may be used to determine the utility values.

The invention discloses an electrophysiological signal conjoint analysis-based human exercise ability determination method, which comprises the following steps of synchronously acquiring EMG (electromyography) and ECG (electrocardiograph) signals; performing R wave peak value identification on the ECG signal to obtain an HRV (Heart Rate Variability) signal, and performing time-domain analysis, frequency-domain analysis and nonlinear analysis on each signal; performing conjoint analysis on EMG parameters and HRV parameters, looking for a relevant parameter pair with significance by adopting correlation analysis, and making a research on the association effect of exercise ability and a heart load condition; extracting an EMG characteristic and an HRV characteristic, and calculating correlation coefficients of an integral EMG value and a root mean square of the EMG signal with the HRV parameters respectively; removing redundant information to obtain a characteristic vector by utilizing PCA (Principle Component Analysis); determining the exercise ability by taking the characteristic vector of mode identification input. According to the method, the accuracy and the convenience of a human exercise ability determination model can be effectively improved, and a basis can be provided for the selection of an astronaut.

The invention provides a graphical model full-life-cycle modeling method for federated learning, which comprises the following steps: analyzing a data sample before modeling, and determining a federated learning scheme; drawing up a modeling strategy according to a joint analysis operation result; adopting a dragging mode and using a federation feature engineering means to process the data; in thefederated model training process, after the two parties construct models respectively, exchanging an intermediate state model and a loss function which are obtained through calculation ; predicting and using the federated model; and monitoring the operation process of the federated model to obtain a model monitoring statistical index so as to realize maintenance iteration of the federated model.Personnel in each step of federated learning modeling can participate in optimization points through imaging, the personnel participation optimization difficulty is reduced, a later model applicationmaintenance way is provided, and the application scene and usability of the federated learning technology are improved.

The invention relates to a monitoring device, in particular to a monitoring and orientation system of pollution sources of electrical energy quality. The system provides monitoring and orientation of flickering pollution sources of an electrical network, realizes conjoint analysis of voltage signals and current signals for the first time, identifies the sources of flickering pollution components contained in load voltage or load current to achieve the technical purpose of flickering pollution orientation, and further provides monitoring and orientation of harmonic pollution sources and monitoring and orientation of sudden rise and sudden drop of voltage. The system realizes the on-line orientation function of the pollution sources of the electrical energy quality for the first time, provides effective centralized processing for a power supply system, avoids large-scale propagation of pollution signals, improves the power supply quality of the electrical network, provides unified standards and a theoretical basis for the solution of the pollution sources of the electrical energy, and has significance for technical development of monitoring and orientation of the pollution sources of the electrical network.

The invention relates to a partitioning processing-based SAR real-time imaging method and a system thereof. A distance echo pulse compression module is used for carrying out pulse compression on each received distance echo datum; an azimuth dimension partitioning processing module is used for carrying out range migration correction and Doppler parameter and kinematic parameter estimation on azimuth subaperture data; a full-aperture parameter estimation module is used for carrying out conjoint analysis and estimation on each azimuth subaperture parameter to obtain full-aperture Doppler parameters and kinematic errors; an envelope compensation module is used for carrying out envelop compensation on the azimuth subaperture data; and a distance dimension partitioning processing module is used for carrying out phase compensation, azimuth pulse compression, multi-look processing and quantization output on data which has undergone envelope compensation. Then, partitioning processing-based SAR real-time imaging processing is finished. The method has low requirements on system memory, can be adopted to effectively solve the problem that range variance leads to poor image quality, and is especially suitable for a SAR real-time imaging system which has high requirements on real-time performance.

The invention provides a river channel sand oiliness evaluation method comprising the steps as follows: step 1, making conjoint analysis of the structural setting and fracture features, and selecting a research zone; step 2, making reservoir-cap combined analysis in the selected research zone to determine the main oil-bearing series, and making fault activity conjoint analysis; step 3, characterizing the structural ridge in the determined main oil-bearing series to indicate the dominant path for oil and gas migration; step 4, applying a fluid test method under different lithological combination conditions; and step 5, classifying sand bodies and comprehensively evaluating the oiliness. According to the river channel sand oiliness evaluation method, the oiliness is evaluated scientifically and reasonably through comprehensive analysis of various factors, the multiplicity of solution is reduced, a favorable target is provided for well placement, and efficient offshore exploration is realized.

The invention discloses a group of genes for colorectal cancer prognosis. The group of genes comprises genes of nucleotide sequences shown in SEQ ID No.34 to SEQ ID No.66. In addition, the invention also discloses an application of the gene group. The application comprises application in preparation of a gene chip for colorectal cancer prognosis, and an application in preparation of a reagent for colorectal cancer prognosis. The gene contributes to improvement of the survival rate of a patient with a colorectal cancer after operation. The risk factor of death of the patient after operation can be rapidly judged by detection and conjoint analysis of the gene chip after the patient with the lung cancer has the radical operation. Thus, the patient with a high death risk factor can be subjected to adjuvant therapy in good time; and the survival time of the patient is prolonged.

The invention discloses a high-real-time quantitative ultrasonic detection method based on multi-angle stereo matching. Aiming at a serious restriction bottleneck between the fine quantitative representation capacity and detection instantaneity of defects of existing ultrasonic detection devices, a basic idea of a finite element is firstly introduced to rasterize a to-be-detected test piece, a plurality of ultrasonic transducers distributed in different directions of a space are utilized for sequentially irradiating grid cells, and a shifting relation between the fine quantitative representation capacity of the flexible coordinating defects and the detection instantaneity is realized by utilizing the wavelet-transform-based multi-resolution stereo matching correlation based on the acquisition of multichannel ultrasonic reflection echo signals. By collecting the multi-angle ultrasonic reflection echo signals, the high-real-time quantitative ultrasonic detection method has the advantage of complete carried information amount and is more beneficial to realization of the quantitative detection; by utilizing a basic theory of wavelet transform, the method has multi-resolution and time-frequency domain conjoint analysis capacities and is particularly suitable for time frequency signals such as ultrasonic waves and the like.

The invention discloses a method for measuring group delay by using wavelet transformation, which comprises the following steps of: performing the wavelet transformation on a measured interference signal; detecting the ridge of the wavelet transformation; and using the ridge of the wavelet transformation as the group delay to obtain the group delay. The method, through the conjoint analysis of a measured interference time frequency, can directly obtain the group delay from a transient cycle interfered at a local frequency, does not need to calculate the phase and carry out derivation, eliminates the influences caused by errors and oscillations in the phase deriving process, and effectively improves the precision of measuring the group delay.

The invention discloses a method for conjoint analysis of a mobile network condition by using a sweep generator and a testing mobile phone. The method comprises the following steps of: (1) importing sweep generator drive test data and testing mobile phone drive test data; (2) preprocessing the sweep generator drive test data and the testing mobile phone drive test data respectively; (3) analyzing a mobile network scene; (4) performing conjoint analysis on the sweep generator drive test data and the testing mobile phone drive test data and outputting a summary report of neighbor cells of disparate systems in a whole network; and (5) outputting an analysis result and a suggestion on optimization. According to the method, a scene analysis result and a neighbor cell configuration suggestion are obtained by processing and analyzing the imported sweep generator drive test data and testing mobile phone drive test data, the two items of data are subjected to conjoint analysis, meanwhile, an analysis result is displayed in a GIS (Geographic Information System), a network problem and a problem hidden trouble are positioned, the purposeful suggestion on optimization is given, and help is offered for optimization of a mobile network.

The invention discloses a denoising source separation based naval vessel vibration noise source separation and recognition method. The method includes: firstly, utilizing a naval vessel shell structure to observe statistical independence of components included in a vibration mixed signal, and establishing a mixed model of a vibration noise source of the naval vessel shell structure; secondly, utilizing a denoising source separation method to separate the vibration mixed signal observed by the naval vessel shell structure into a plurality of independent source components; thirdly, recognizing a naval vessel vibration noise source from the independent source components by utilizing naval vessel shell structure vibration source prior information and adopting a method of time domain and frequency domain conjoint analysis. The method is stable and efficient, capable of realizing on-line analysis, reliable in results, good in real-time performance, simple and feasible, suitable for separation and recognition of vibration noise source information of equipment like naval vessels, free of damage to naval vessel structures, convenient for accurate separation and recognition of vibration noise sources of the shell-structured equipment such as existing naval vessels, and capable of providing reliable bases for naval vessel vibration damping and denoising operation.

The invention discloses a wireless sensor network abnormal node detecting and positioning method based on subgraph processing. A central node set of a locally abnormal subgraph is screened out on thebasis of the idea of local subgraph processing and node domain-graph frequency domain conjoint analysis, whether abnormal nodes exist in a network is judged according to the matching degree of the screened node set and the central node of the local subgraph, meanwhile, and abnormal nodes in the wireless sensor network are positioned. Whether the network is abnormal can be judged, abnormal nodes inthe network can be positioned, a simple and effective method is provided for detection and positioning of abnormal nodes in the wireless sensor network, and the method has the characteristic of highdetection efficiency and can help the later repair work.

The present invention relates to an unstructured data decision method based on deep learning. The method specifically comprises: obtaining a trained deep learning neural network model, wherein the trained deep learning neural network model is a multi-factor joint decision neural network model trained by multi-factor training sample data; receiving online real-time collected clue data, wherein theclue data comprises a plurality of data types of unstructured data; carrying out conjoint analysis on the obtained clue data through a trained deep learning neural network model, and extracting feature clue information that is favorable to the decision; deciding the clue data according to the feature clue information, and generating a decision result; and feeding back the decision result. The method disclosed by the present invention can carry out more efficient and timely decision analysis on the unstructured data and implement online real-time analysis.

The invention discloses a method and device for measuring air resistance of a train. According to the characteristic that the air resistance of the train is substantially unrelated to the train mass and other resistances are in direct proportion to the train mass in the total resistance of the train, the air resistance of the train and other resistances of the train are decoupled from each other through train inertia measurement and total resistance conjoint analysis under different load conditions; therefore, the measurement problem of the air resistance of the train is solved; effective means are provided for completion of operation resistance formulas of middle and high speed passenger trains, evaluation of energy conservation design of the train, high speed train power configuration, train aerodynamics researches and the like; and important engineering significances are obtained.

The invention relates to a method for identifying Dosidicus gigas spatial distribution and a marine environment influence. The method comprises the following steps: 1) obtaining commercial fishing data of Dosidicus gigas and marine environment remote sensing data, and converting catch into catch per unit effort (CPUE); 2) monthly performing spatial distribution analysis for CPUE drawings of the Dosidicus gigas; 3) drawing a box plot for the marine environment data, and analyzing changes of marine environment factors in various months; 4) according to existing data, performing conjoint analysis for the CPUE, SST, SSS and SSH adopting an SAR model, and obtaining a relationship between the CPUE and the marine environment factors; and 6) predicting spatial distribution of a Dosidicus gigas resource by utilizing an established GAM model and the established SAR model, and evaluating an obtained result by utilizing a precision index. Compared with the prior art, the method has the advantages of significantly improved prediction accuracy and the like.

The invention relates to an ultrasonic image quantitative evaluation method, which comprises the following steps of: 1, preprocessing an obtained lung ultrasonic image; 2, carrying out image segmentation on the lung ultrasonic image; 3, carrying out quantitative analysis index extraction on the lung ultrasonic image; and 4, carrying out multi-parameter conjoint analysis on the lung ultrasonic image. According to the method, parameters related to the pleura line, the B line and the real lung change are extracted by adopting a method for carrying out quantitative analysis on the ultrasonic image, then a multi-parameter conjoint analysis method is utilized, all quantitative analysis indexes are comprehensively utilized, and finally a lung lesion degree classification result is obtained. Therefore, a non-invasive / quantitative lung ultrasound image quantitative evaluation method is provided for clinic, and the method can be better applied to rapid lesion screening, grading diagnosis and illness follow-up visit of a large range of people and critically ill bedside monitoring.