47 results about "Outcomes evaluation" patented technology

The invention provides a method and apparatus to enable a user to perform upper extremity exercises. The apparatus includes an arm with one end connected to a base to securely support the arm while locating the other end adjacent to the user, proximate the user's upper extremities. The arm is formed with a plurality of joints at or between its ends, each joint having one or more rotational degrees of freedom while providing resistance to rotational movement in the one or more degrees of freedom, such that the free end of the arm can be moved in three dimensional space, and such that the arm is self-supporting. A manipulandum assembly including a plurality of manipulanda is attached to the free end of the arm, each manipulandum being positioned within hand grasping range of the user, and each manipulandum being or representing an object encountered in an upper extremity activity of the user's daily life. Sensors on the arm, joints or manipulanda sense movement or force, and relay signals to a processing device in order to sample, display, store and process the signals into kinematic or kinetic variables. These variables may be processed to control software programs such as computer games and to allow quantification of performance for outcome evaluation of therapy regimes.

The invention discloses an urban traffic carbon emission measurement and calculation system, and an urban traffic carbon emission measurement and calculation method. The urban traffic carbon emission measurement and calculation system comprises a driving factor generating module, a carbon emission measurement and calculation module and an emission reduction outcome evaluation module, wherein the driving factor generating module is used for extracting and generating driving factors according to various traffic emission reduction policies; the carbon emission measurement and calculation module is used for calculating energy consumption according to the driving factors, and calculating urban traffic carbon emission and atmospheric pollutant emission according to the energy consumption; and the emission reduction outcome evaluation module is used for evaluating emission reduction effects of the traffic emission reduction policies according to the urban traffic carbon emission and atmospheric pollutant emission. On the basis of fully analyzing the traffic emission reduction policies and combining with an LEAP model, the urban traffic carbon emission measurement and calculation system is established, scattered output data of the traditional model is integrated into a visual index, namely, the carbon emission, so that the carbon emission is liable to be used by decision makers directly, and the effective evaluation index and method are provided for the decision-making of policy support strength and time span.

Techniques for conducting a promotion of a product or service, managing various promotion activities, and rewarding promotion partners are disclosed. An incremental sales (e.g., incremental sales volume, revenue, and profit) analysis due to a promotion is performed and a fee is assessed based on a result of the incremental sales analysis. In some embodiments, performing the incremental analysis includes assigning to a control group a first subset of a plurality of target customers associated with the promotion, assigning to an offer group at least a second non-overlapping subset of the plurality of target customers, providing to at least the offer group but not to the control group an offer associated with the promotion, and determining an incremental change in sales of the product contributed by the customers in the offer group—as compared to sales contributed by the customers in the control group. In some embodiments, performing the incremental sales due to the promotion is determined based on a difference between a maximum allowable discount and an actual discount for individual customers.

The player is given the further enjoyment after the completion of a game and encouraged to participate in the next game. The relationship between characteristic parameters used for displaying a character and ability parameters of the player that are computed based on the execution of a game is defined for each character. The relationship between the characteristic parameters and the ability parameters is set to be different from character to character. Therefore, a character that the player has selected changes according to a game result. Because the way a character changes differs from character to character, the player is given the enjoyment of finding a character for which he / she can take advantage of his / her play style in addition to the enjoyment given by an actual game. In order to realize this enjoyment, a relationship between the characteristic parameters and the ability parameters of a character is intentionally made secret and unknown to the player when the player selects a character. Therefore, this stimulates the player's motivation to enter the game and encourages the player to actively enter the game in search of a character that is suitable for his / her own habit.

A method for performing a market analysis may include collecting survey data, which may include evaluation data for desired outcomes, the desired outcomes consisting of attributes of one or more products or services. The desired outcome evaluation data may include importance and satisfaction data. Further, the survey data may include evaluation data for potential features. The potential features evaluation data may include desirability data indicative of the affinity survey participants have for potential features. The method may further include processing the collected survey data using a computer processor. The processing may include calculating, based on the importance and satisfaction data, opportunity scores for the individual desired outcomes. The processing may also include correlating potential features with desired outcomes. In addition, the processing may include ranking the potential features based on the collected desirability data and the calculated opportunity score.

The present invention extends to methods, systems, and computer program products for isolating the evaluation of actual test results against expected test results from the test module that generates the actual test results. A results evaluation sub-system receives actual test results resulting from the execution of a test in a test environment. A results retrieval sub-system receives environmental data indicating that a test was performed in the test environment. The results retrieval sub-system selects one or more expected results from a results database based on the received environmental data. The results retrieval sub-system sends the selected one or more expected results to the results evaluation sub-system. The results evaluation sub-system receives the one or more selected results. The results evaluation sub-system evaluates the actual test results against the one or more expected results to determine if the test was successful.

The invention provides a knowledge-space-based behavior result evaluation method. The method is applied based on the analysis result of a user offline prediction model provided by an operator, an airline or any other service providers, and the behavior result of a user that might be off the line is compared and evaluated finally. Through training an offline prediction model, the data of the user is subjected to offline prediction and probability prediction. Meanwhile, through evaluating the influence of marketing or promotion means on the offline prediction probability change, a most efficient marketing means is selected. Therefore, the retention is conducted for users that are mostly likely to get off the line. Meanwhile, the maximum revenue is realized on the premise that the cost is limited to a certain degree.

A method for performing a market analysis may include collecting survey data, which may include evaluation data for desired outcomes, the desired outcomes consisting of attributes of one or more products or services. The desired outcome evaluation data may include importance and satisfaction data. Further, the survey data may include evaluation data for potential features. The potential features evaluation data may include desirability data indicative of the affinity survey participants have for potential features. The method may further include processing the collected survey data using a computer processor. The processing may include calculating, based on the importance and satisfaction data, opportunity scores for the individual desired outcomes. The processing may also include correlating potential features with desired outcomes. In addition, the processing may include ranking the potential features based on the collected desirability data and the calculated opportunity score.

The invention relates to an object reciprocating motion distance evaluation method based on deep learning, and the method comprises the following steps: carrying out the data sampling, and collectingthe motion acceleration change data of an object; segmenting a pressing waveform in a pulse form; correcting the data label so as to clearly see the discrete condition of the curve; marking data, integrating all pulse waveform data, calculating the weighted mean square error of each waveform, marking whether a single waveform is normal or abnormal according to the overall weighted mean square error range of the correct waveform and the abnormal waveform, disturbing a data set after marking is completed, and selecting a training set and a test set according to a certain proportion; establishinga convolutional neural network model for training, debugging parameters, optimizing the model, and storing the model to a file for subsequent reciprocating motion distance evaluation; evaluating data: putting to-be-evaluated data into the trained convolutional neural network model, and judging whether an evaluation result is normal or abnormal; and outputting an evaluation result to evaluate whether the object movement distance is proper.

One embodiment of the invention discloses an analysis and evaluation system and method based on reusable evaluation resource construction. The system comprises an evaluation application management module, an index system construction module, an evaluation index association module, a test evaluation scheduling module and an evaluation result display module. The evaluation application management module is used for managing different evaluation applications; the index system construction module is used for constructing an evaluation index system tree; the evaluation index association module is used for associating each index node in the evaluation index system tree with a certain index in an evaluation index library; the test evaluation scheduling module is used for loading and obtaining evaluation element information, scheduling evaluation resource data according to input test data and initialization parameters, completing evaluation calculation and obtaining an evaluation result; and the evaluation result display module is used for carrying out visual chart display on the evaluation result and automatically generating an evaluation report according to the evaluation result.

The invention discloses a time-space evaluation method for testability of a data acquisition system, belongs to the technical field of software testing, solves the problem that problems in a data acquisition process are difficult to solve due to the fact that the testability of the system is not evaluated in the prior art, and comprises the following steps of: A, determining an actual equipment use scene of a test environment; step B, determining the actual equipment composition of the test environment; step C, carrying out testability spatial dimension evaluation; step D, carrying out testability time dimension evaluation; and E, evaluating whether testability exists or not according to the evaluation results of the step C and the step D. The technical effects of evaluating the actual operation diversity of the data acquisition system and improving the testability of the system are achieved.

The invention provides a crowdsourcing result evaluation and reward distribution method based on an intelligent contract. The method comprises the following steps: encrypting a task solution by using a public key of a task; triggering a task evaluation and reward allocation process; the anonymous account with the answer result closest to the correct answer is selected for reward, and the reward result is recorded in the task chain module and the user chain module; obtaining current reward information of the anonymous account; initiating an application for synchronizing the reward information to the original account to the trusted execution environment module; applying for necessary user information from the user chain module so as to synchronize the information of the anonymous account to the original account; the privacy information of the original account and the privacy information of the anonymous account are combined into third privacy information of the original account, and the third privacy information is sent to the original account; a result returned by the trusted execution environment module is uploaded to the user chain module; and updating the original account. In this way, the user privacy in the reward distribution process and the fairness and justice of crowdsourcing result evaluation and reward distribution can be guaranteed.

The invention discloses a deep learning reasoning engine test method based on differential evaluation. A model import check module, an intermediate representation acquisition module and a result evaluation module are included. In the model import checking module, whether the engine supports all operators and related parameters involved in the model is analyzed, and whether the structure of the model is kept consistent after the model is imported into the engine is judged in combination with an exception capture mechanism in the engine and model structure comparison before and after import. Inthe middle representation acquisition module, IR data acquisition paths provided by different compilers are arranged, engine information and corresponding acquisition instructions are packaged throughmanual processing, and a unified calling interface is generated. In the result evaluation module, a compiler list suitable for the differential test task is obtained and includes a compiler name anda corresponding model source, and an intermediate representation obtaining interface is called to obtain IR data.

The invention discloses an evaluation method of developmental psychology types. The evaluation method comprises the following steps: acquiring instant physiological information, psychological information, intellectual information, cognitive information and basic information including age stages of an evaluated object; analyzing characters of the evaluated object according to the instant physiological information of a user, and separately evaluating a physiological state, an intellectual level and a cognitive level of the evaluated object based on the psychological information, the intellectualinformation, the cognitive information and the basic information including the age stages; and evaluating the developmental psychology types of the evaluated object based on the character analysis result in the step S2 and evaluation results of the physiological state, the intellectual level and the cognitive level. According to the method disclosed by the invention, influences of environmental adaptation and the cognitive information on physiological pressure are fully taken into consideration, so that evaluation on the developmental psychology is realized, a data plane is wide, and evaluation analysis is accurate.

The invention discloses a middle school student geographical chart reading disorder diagnosis and correction system comprising a reading disorder test question presetting module, a first grade test module, a first grade test result assessment module, a second grade test module, a second grade test result assessment module, a compensation learning module and a reach-the-standard evaluation module. Via the middle school student geographical chart reading disorder diagnosis and correction system, geographical chart reading disorder of students is detected via test questions with small difference; tiny and specific different is arranged between each test question and other test questions; effects are exerted on chart reading of the students by the difference; chart reading disorder points of the students can be inferred based on diagnosis results of the students; for each disorder point, corresponding compensation exercise or learning material is arranged so as to help the students overcome disorder; the system is applicable to each student (chart reader), and breakthrough strategies for common disorder can be provided for mass geographical chart readers via systematic compiling and analyzing operation.

The invention discloses a method for evaluating influencing factors of satisfaction degree of a rookie post station, a storage medium and a terminal device. The method comprises the following steps: receiving historical data of influencing factors of user satisfaction degree and constructing a social network according to the historical data; Calculating a network density of the social network andjudging whether the social network is feasible according to the network density; When the social network is feasible, analyzing the influencing factors of satisfaction centrally to obtain corresponding analysis results, and evulating the influencing factors of satisfaction according to the results. The invention comprehensively describes the influencing factors of the user and the satisfaction degree, the influencing factors of the satisfaction degree and the influencing factors of the satisfaction degree as well as the relationship between the user and the user by constructing a social network, and conducts central analysis on each influencing factor of the satisfaction degree to evaluate each influencing factor of the satisfaction degree respectively, thereby improving the accuracy of the evaluation.

The invention discloses a river water quality prediction method based on feature engineering. The method comprises the following steps: step A, acquiring monitoring data influencing river water quality; step B, preprocessing the monitoring data influencing the water quality of the river; c, constructing characteristic indexes influencing the water quality of the river; step D, performing feature index screening by adopting a correlation coefficient method, including performing feature screening of the LSTM model through a Pearson correlation coefficient method; e, model structure data processing: carrying out LSTM model structure data preprocessing on the screened characteristic indexes; f, performing model training and automatic parameter adjustment, including training the LSTM model and automatically adjusting and optimizing the parameters of the LSTM model, and storing the optimal model to a server; and G, model prediction and result evaluation: obtaining prediction data based on the optimal model, and evaluating the deviation between the prediction data and real data. In combination with multiple factors and multiple condition influence factors of the river, the prediction condition of the water quality change is reflected more accurately and more comprehensively.

The invention discloses application of LncRNA ENST00000514235 in serum as a marker for URSA (unexplained recurrent spontaneous abortion) diagnosis and pregnancy outcome evaluation. A corresponding detection kit is developed by taking the LncRNA ENST00000514235 as the marker for URSA diagnosis and pregnancy outcome evaluation. The detection kit has the advantages of high detection sensitivity, highspecificity, convenience in detection and capability of meeting diagnosis detection requirements of patients suffering from URSA, and clinical verification shows that the diagnosis accuracy rate is high.

The invention discloses an API (Application Programming Interface) recommendation result evaluation method based on functional similarity. For the API recommendation result evaluation method, for cases where the recommendation result is a set of APIs, the function similarity between the recommended API and the correct API is measured through three dimensions of name similarity, API annotation relevance and API call graph similarity; and according to the similarity, the contribution value of the recommendation result set of the API recommendation system is evaluated, and the contribution valueis used for replacing 0 or 1 in a traditional evaluation method, and the correctness of the recommendation result is calculated, so that correctness evaluation is more accurate and is close to a manual evaluation result.

The invention discloses a distributed random forest evaluation system and method with a privacy protection attribute. The system comprises a user and a random forest evaluation platform, wherein the evaluation platform is composed of t evaluation servers, and a decentralized distributed structure is adopted. The data evaluation method comprises the following four parts: initializing a system; sending user information; evaluating data in a random forest manner; and decrypting the evaluation result. According to the invention, random forest assessment is carried out on the encrypted user data under the condition that the user data and the decision tree model of the server side are not leaked, and only the target user can obtain the assessment result. Even if a small number of fault servers exist in the evaluation process, it can be ensured that the evaluation platform outputs a correct result. Therefore, the method and the system have very high robustness and practicability.

The invention provides a special effect synchronous evaluation method, device and equipment, a computer readable storage medium and a program product. The embodiment of the invention can be applied to various scenes such as cloud technology, artificial intelligence, intelligent transportation, vehicle-mounted and the like, and relates to an automatic testing technology and a cloud computing technology. The method comprises the following steps: in response to a trigger operation for an evaluation trigger identifier in an evaluation interface, obtaining a special effect video of a to-be-evaluated special effect; determining animation time information corresponding to a special effect animation of the to-be-evaluated special effect and audio time information corresponding to a special effect audio of the to-be-evaluated special effect based on an image sequence and an audio signal analyzed from the special effect video; determining an evaluation result according to the difference between the animation time information and the audio time information; wherein the evaluation result represents the synchronization condition of the special effect animation and the special effect audio; and displaying the evaluation result in a result display area of the evaluation interface. According to the invention, the intelligent degree of special effect synchronous evaluation can be improved.

The embodiment of the invention provides a data quality assessment method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring spatio-temporal trajectory data to be assessed; according to a preset quality evaluation algorithm, processing the spatial-temporal trajectory data to obtain an evaluation result corresponding to each evaluation dimension, the evaluation dimensions including a stability dimension and an accuracy dimension; based on a preset quality condition corresponding to each evaluation dimension, determining an evaluation result which does not meet the corresponding quality condition, and determining the evaluation dimension corresponding to the evaluation result as a low-quality dimension; and performing quality improvement processing on the spatio-temporal trajectory data by adopting a preset processing mode corresponding to the low-quality dimension to obtain processed spatio-temporal trajectory data. According to the scheme provided by the embodiment of the invention, the quality condition of the spatio-temporal trajectory data can be evaluated from multiple evaluation dimensions, and the low-quality dimensions in the spatio-temporal trajectory data can be subjected to quality improvement processing, so that the quality of the spatio-temporal trajectory data is improved.

The invention discloses application of LncRNA NONHSAT167899.1 as a marker URSA diagnosis and pregnancy outcome evaluation and develops a corresponding detection kit by taking LncRNA NONHSAT167899.1 asa marker for diagnosing URSA and evaluating pregnancy outcome. The kit is high in detection sensitivity, high in specificity and convenient to detect; the detection requirements of patients with URSAcan be met; clinical experiments show that the accuracy rate of the diagnosis is high.

The invention discloses an electric power data quality evaluation method and device. The method specifically comprises the steps of selecting a base layer data evaluation index and a criterion layer data evaluation index according to a to-be-evaluated data object, matching the basic layer data evaluation index and the criterion layer data evaluation index with a corresponding data evaluation ruleset, and endowing each criterion layer data evaluation index with a weight value W and an expected value E, extracting a to-be-evaluated data object and performing data preprocessing on the to-be-evaluated data object to obtain first processing data, performing base layer evaluation verification on the first processing data according to a base layer data evaluation index to obtain a first verification result, performing criterion layer evaluation verification on the first processing data according to a criterion layer data evaluation index to obtain a second verification result, and calculating a data quality comprehensive evaluation result according to the first verification result and the second verification result. The evaluation verification process reflects the quality level of the data resources with a plurality of quality dimension measurements to more accurately evaluate the quality of the data.