42 results about "Feature dependency" patented technology

Metrology methods and respective software and module are provided, which identify and remove measurement inaccuracy which results from process variation leading to target asymmetries. The methods comprise identifying an inaccuracy contribution of process variation source(s) to a measured scatterometry signal (e.g., overlay) by measuring the signal across a range of measurement parameter(s) (e.g., wavelength, angle) and targets, and extracting a measurement variability over the range which is indicative of the inaccuracy contribution. The method may further assume certain functional dependencies of the resulting inaccuracy on the target asymmetry, estimate relative donations of different process variation sources and apply external calibration to further enhance the measurement accuracy.

Systems and method are provided for analyzing target, process and metrology configuration sensitivities to a wide range of parameters, according to external requirements or inner development and verification needs. Systems comprise the following elements. An input module is arranged to receive parameters relating to targets, target metrology conditions and production processes, to generate target data. A metrology simulation unit is arranged to simulate metrology measurements of targets from the target data and to generate multiple metrics that quantify the simulated target measurements. A sensitivity analysis module is arranged to derive functional dependencies of the metrics on the parameters and to define required uncertainties of the parameters with respect to the derived functional dependencies. Finally, a target optimization module is arranged to rank targets and target metrology conditions with respect to the simulated target measurements.

Reusable JSP code snippets are defined and instrumented for Website testing and production. A user may define tile definitions in a markup language file for a number of JSP code snippets to be included in a store page. Upon receiving store inputs comprising tile definitions and jar files for the features, tables may be generated that map features to stores and features dependencies to features. Based on the tables, the store inputs may be validated. If no error occurs, run time files may be generated and JSP code snippets may be instrumented to the appropriate location for Website testing and production.

The invention provides a method and a device for determining a regression testing range. The method comprises the steps of S1, determining function units in to-be-tested software in advance and establishing a function dependence tree according to a dependence relationship between the determined function units; and S2, searching function units depending on a modified function unit by beginning from the modified function unit in the function dependence tree, searching function units depending on each searched function unit when a regression test is carried out, and using the modified function unit and all searched function units as the regression testing range of the to-be-tested software. According to the method and the device, which are provided by the invention, the accuracy of the regression test can be ensured while the testing resource and the testing time are saved.

A recommender system for use on a mobile platform or other computing device provides a user with a recommended list of products with default product quantities that are based on prior purchase behavior of the user or customer. This feature relies on analyzing a customer's past purchases and associating a score with each product. The scoring system indicates the statistical likelihood that the customer would want or need to purchase that item on their next order. The customer analysis takes into account, e.g., the number of times a customer has ordered a product, how frequently the product is ordered by the customer, how many days since the respective customers last order and the customers average order size in providing the recommended list of products.

The embodiment of the invention provides an aspect-level sentiment analysis method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining a target sentence to be subjected to aspect-level sentiment analysis and aspect words in the target sentence; based on the similar structure data set, performing aggregation feature processing on the target sentence and the aspect words to obtain fusion feature information corresponding to the target sentence; performing feature conversion on the fused feature information by using a bidirectional long-short-term memory network to obtain hidden state features corresponding to the target sentence; preprocessing the target sentence and the aspect words to obtain a dependency graph corresponding to the target sentence and position coding features corresponding to the words in the target sentence; and inputting the hidden state features, the dependency graph and the position coding features into a pre-trained graph convolutional neural network to obtain an emotion analysis result corresponding to the aspect words. According to the embodiment of the invention, the accuracy of the sentiment analysis result can be improved.

A method and a controller for controlling the execution of a computer program having multitasking capability on a computing element, especially on a microprocessor, of a controller (20) for controlling and / or regulating a system. The system may take up various possible system states. At the beginning of the execution of a function, in order that the input variables required for carrying out the function of computer program are present with certainty, the following steps may be executed: subdividing the computer program into a plurality of functionally linked functionalities; defining possible operating states for the functionalities; defining the possible system states of the system, in that specifiable operating states are allocated to the functionalities for each system state; ascertaining the dependencies of the functionalities upon one another, a first functionality being dependent upon a second functionality if at least one input variable of the first functionality is ascertained in the second functionality; and centrally specifying the operating states required for a certain system state, taking into consideration the ascertained dependencies among the functionalities and further boundary conditions.

In business systems, one or more methods can be used to reduce an amount of redundant data. In one implementation, a method to reduce redundancy within a data model in a database, in which the data model is represented by at least one table, includes determining a number of distinct values of partial keys in a table. Each partial key represents at least one row in the table. The method includes reordering one or more columns of the table by cardinality of partial keys, in which the cardinality of a partial key represents a number of distinct values of the partial key. The method further includes determining whether pairs of partial keys are functionally dependent and eliminating one or more columns having functional dependencies from the table.

Techniques and mechanisms described herein facilitate adaptive fuzzy fallback stratified sampling. According to various embodiments, an actual or estimated minimum vertex cover of a feature dependency graph representing a dataset may be determined. The dataset may include a plurality of feature vectors and a plurality of features. Each feature vector may include a plurality of feature values that correspond with the features. The feature dependency graph may represent a plurality of conditional dependencies between the features. The minimum vertex cover may designate a subset of the features for strata selection. The feature vectors may be partitioned into a plurality of strata based on the designated subset of features. Each stratum may include one or more of the feature vectors. Each feature vector may be assigned to a corresponding stratum based on the values of the designated subset of features for the feature vector.

The invention belongs to the field of computer vision, and in particular relates to a method for detecting that a monitoring video of a road area is blocked by leaves. Firstly, a deep learning platform based on Mask R-CNN is established to train the network model of road area and leaf target, and then the detected road area results are optimized to meet the recognition expectations in urban video surveillance scenes; The display and understanding of the positional relationship of the three-dimensional space on the two-dimensional plane in monitoring, the defined occlusion rules, and finally the judgment result of whether there is a road area blocked by leaves. The present invention can replace the traditional manual method of browsing a large number of videos to check and confirm the occlusion of leaves one by one, get rid of the characteristic dependence based on subjective experience disputes such as the size of the leaf area, distribution area, distance, etc., and realize the three-dimensional space by simulating in two-dimensional space Occlusion-aware applications.

The embodiment of the invention discloses a business object labeling method, device, server and storage medium. The method includes: extracting text information from the business object, and writing it into a text collection; extracting candidate phrases from the text information, and candidate words in the candidate phrases have feature dependencies; within the scope of the text collection , respectively calculating the correlation between the candidate words for the candidate phrases; selecting the target candidate phrases from the candidate phrases based on the correlation; the candidate words in the target candidate phrases are marked as the Label information of the business object. There is no need for the user to manually select a suitable word as the label of the business object, which reduces the workload and improves the efficiency.

The invention discloses a failure recovery method based on precursor dependence to mainly solve the problems that in an existing failure recovery technology, a failure point cannot be accurately positioned, and multi-system repeated backup atom functions are arranged with the dependence of a single detection point. According to the technical scheme, a functional dependence tree is structured for an application case needing failure data recovery; secondly, backup of the atom function of the functional dependence tree is built; thirdly, recovery processing is carried out when a root node of the functional dependence tree breaks down, an external storage device is searched for the latest full backup, the failure atom function is recovered according to the full backup, all increment backup after the latest full backup are searched for, increment recovery is carried out on the failure atom function one by one according to the sequence, and finally the root node is recovered. By means of the failure recovery method, function detailing can be carried out on an application, and targeted recovery can be carried out when a failure occurs; furthermore, a double-layer backup mode is used, the backup efficiency is improved, and the method can be used for failure data recovery of the application case.