731results about "Computing models" patented technology

The motion of the movable sections of the robot is taken for a periodic motion so that the attitude of the robot can be stably controlled in a broad sense of the word by regulating the transfer of the movable sections. More specifically, one or more than one phase generators are used for the robot system and one of the plurality of controllers is selected depending on the generated phase. Then, the controller controls the drive of the movable sections according to continuous phase information. Additionally, the actual phase is estimated from the physical system and the frequency and the phase of the phase generator are regulated by using the estimated value, while the physical phase and the phase generator of the robot system are subjected to mutual entrainment so that consequently, it is possible to control the motion of the robot by effectively using the dynamics of the robot.

Automatic process control of additive manufacturing. The system includes an additive manufacturing device for making an object and a local network computer controlling the device. At least one camera is provided with a view of a manufacturing volume of the device to generate network accessible images of the object. The computer is programmed to stop the manufacturing process when the object is defective based en the images of the object.

A system that facilitates performance of a focused search over a collection of sites comprises a subweb that corresponds to a topic and / or user characteristic(s) that are of interest to the user. The subweb includes a plurality of domains and / or paths (e.g. sites) that are related to the topic and / or the user characteristic(s). Each of the sites within the subweb is assigned a weight that indicates relevance of the site to the desirable topic and / or user characteristic(s). A search engine employs the subweb to facilitate focusing a search over a collection of sites. The search engine receives a query, and utilizes the subweb to focus a search over the selection of sites corresponding to the topic and / or user characteristic(s) represented by the subweb. The results from the search are returned to the user based at least in part upon the relevance weights assigned to the sites within the subweb.

A system for fully integrated collection of business impacting data, analysis of that data and generation of both analysis-driven business decisions and analysis driven simulations of alternate candidate business actions has been devised and reduced to practice. This business operating system may be used predict the outcome of enacting candidate business decisions based upon past and current business data retrieved from both within the corporation and from a plurality of external sources pre-programmed into the system. Both single parameter set and multiple parameter set analyses are supported. Risk to value estimates of candidate decisions are also calculated.

A system and method for providing various user interfaces is disclosed. In one embodiment, the various user interfaces include a series of user interfaces that guide a user through the machine learning process. In one embodiment, the various user interfaces are associated with a unified, project-based data scientist workspace to visually prepare, build, deploy, visualize and manage models, their results and datasets.

Provided is a multi-tiered cascading crawling system for finding on a network information related to one or more predetermined topics or subtopics of interest. In general, embodiments of the present invention provide a system that operates in multiple “tiers,” where at least some of the output of one tier is used to comprise the input of the next tier. Each tier generally analyzes collections of documents on the network using successively more restrictive criteria about the subject matter of each collection and / or about which collections may be related to the one or more topics or subtopics. In general, only the final tier performs an exhaustive crawl of all of the documents of the collections that are identified by the system as being relevant to the topic or subtopic of interest.

The invention relates to an automatic selection method for machine learning in cloud computer environment. By using a cloud computing platform, a user can automatically and intelligently build a machine learning mathematic model which meets actual problems without building the operation environment of machine learning, selecting a machine to learn algorithm and even adjusting complicated machine learning functions and accompanying parameters but only using a Web method to upload sample data. Through the method, the use of machine learning is free from the environmental constraints and displays the advantages of the cloud computing platform, so that the machine learning model building is transparent to the user, so as to best reduce the use threshold of machine learning. The automatic selection method for machine learning in cloud computing environment solves the disadvantages of the unpredictability of model building selection, the manual experience of parameter adjustment, the difficulties of common users and the like when machine learning is applied in actual life.

An improved method and system are provided for creating tasks and for inputting information associated with created tasks according to an electronic task management application or system. Electronic correspondence items may be flagged as tasks. Upon flagging an individual electronic correspondence item, a corresponding task is created for the flagged item, and the created task is then populated into and exposed by one or more applications used for displaying tasks such as a tasks application, calendar application, or electronic to-do list application. Properties such as task start dates and task categories may be applied to the created task, as desired.

A system for helping a chemist to identify pharmacophoric mechanisms, based on a set of input data representing many chemical compounds. Given an input data set defining for each compound a feature characteristic and an activity characteristic, a computer agglomeratively clusters representations of the molecules based on their feature characteristics. The result of this process is a multi-domain pyramid structure, made up of a number of nodes each representing one or more molecules. For each node, the computer identifies a representative feature set (such as a largest substructure common among the molecules in the node) and a representative activity level (such as an average of the activity levels of the molecules in the node). The computer then provides as output to a chemist a description of all or part of the pyramid. This process thus converts a large set of raw data into an understandable and commercially useful form, which can assist the chemist in developing beneficial new pharmaceuticals.

A system and method for ensuring that machines having invalid or corrupt states are restricted from accessing host resources are provided. A quarantine agent (QA) located on a client machine acquires statements of health from a plurality of quarantine policy clients. The QA packages the statements and provides the package to a quarantine enforcement client (QEC). The QEC sends the package to a quarantine Health Certificate Server (HCS) with a request for a health certificate. If the client provided valid statements of health, the HCS grants the client health certificate that may be used in IPsec session negotiation.

Systems and methods are described for updating an influence model used to manage physical conditions of an environmentally controlled space. A method comprises operating an environmental maintenance system in a first production mode with the influence model until an event causes the system to enter a second production mode. In the second production mode a first actuator's operation level is varied and operation levels of other actuators are optimized. The influence model is adjusted based on the operation levels.

The invention relates to the artificial intelligence technical field, in particular to a text classification feature selection and weigh calculation method based on field knowledge. The method combines sample statistics and field glossaries to construct a filed classification feature space, utilizes internal knowledge relations in the field, calculates the similarity between the glossaries, and then adjusts the corresponding feature weight of classification feature vectors. Moreover, the method adopts a learning algorithm of a support vector machine to construct a field text classification model and then realize field text classification. As shown by text classification laboratory results of the Yunan tourist field and the non-tourist field, the classification accuracy of the method is improved by 4 percent compared with the text classification effect of the improved TFIDF feature weigh method.

The motion of the movable sections of the robot is taken for a periodic motion so that the attitude of the robot can be stably controlled in a broad sense of the word by regulating the transfer of the movable sections. More specifically, one or more than one phase generators are used for the robot system and one of the plurality of controllers is selected depending on the generated phase. Then, the controller controls the drive of the movable sections according to continuous phase information. Additionally, the actual phase is estimated from the physical system and the frequency and the phase of the phase generator are regulated by using the estimated value, while the physical phase and the phase generator of the robot system are subjected to mutual entrainment so that consequently, it is possible to control the motion of the robot by effectively using the dynamics of the robot.

A cognitive alteration system includes a storage unit at least to store one or more scripts, each to control a cognitive alteration process where the process occurs within at least one of: a dedicated session and a follow-up open time period and where the storage unit stores both a script per dedicated session and a script per follow-up open time period for the process; a script handler at least to run at least one script; at least one of a wearable and a non-wearable element to sense an attribute of a subject or to provide an output to the subject during one of the dedicated session and the follow-up open time period; an information analyzer at least to perform analysis of the readings of the at least one element, an integrator to integrate the analysis and a script updater to update at least one of the scripts.

The system has number of environmental sensors to sense various environmental parameters of the personal environment envelope surrounding the individual and multiple biological sensors to sense biological and physiological condition of the individual. The system includes a personal environment envelop setting module to define preferred settings based on input from the individual. The system has a processing module to process the environmental parameters sensed by the sensors and the preferred settings to generate alerts. The processing module, also receives information from other sources and is capable of dynamically compute recommendations, map these with the preferences of the individual for enabling the preferred conditions. The system also has a server module configured to receive, store, analyze and machine learn from data of the plurality of environmental parameters sensed by the plurality of sensors and the preferred settings along with ambient environmental data from plurality of persons for epidemiology study.

A system for controlling a rendering engine by using specialized commands. The commands are used to generate a production, such as a television show, at an end-user's computer that executes the rendering engine. In one embodiment, the commands are sent over a network, such as the Internet, to achieve broadcasts of video programs at very high compression and efficiency. Commands for setting and moving camera viewpoints, animating characters, and defining or controlling scenes and sounds are described. At a fine level of control math models and coordinate systems can be used make specifications. At a coarse level of control the command language approaches the text format traditionally used in television or movie scripts. Simple names for objects within a scene are used to identify items, directions and paths. Commands are further simplified by having the rendering engine use defaults when specifications are left out. For example, when a camera direction is not specified, the system assumes that the viewpoint is to be the current action area. The system provides a hierarchy of detail levels. Movement commands can be defaulted or specified. Synchronized speech can be specified as digital audio or as text which is used to synthesize the speech.

A method for predicting a time to failure of a component in a system is presented. The method comprises obtaining a set of data measurements related to the component. The set of data measurements are representative of a plurality of parameters including a plurality of leading parameters. The method comprises generating a prediction model based upon the leading parameters considered in combination. The prediction model is then used to predict the time to failure of the component based on a set of real-time measurements, wherein the plurality of parameters are processed to predict the time to failure for the component. Finally, a confidence level for the predicted time to failure is determined based upon the plurality of parameters.

The invention belongs to the information extraction technology in the artificial intelligence field, and provides a semi-supervised Chinese named entity recognition method based on deep learning for the Chinese text in the specific field with only a small amount of labeled data and a large amount of unlabeled data. Specifically, the method includes the following steps: firstly, constructing a character-based deep learning named entity recognition model; secondly, design a scoring device, train a learning device and a scoring device by using that annotated data; thirdly, designing a semi-supervised learning framework to realize semi-supervised Chinese named entity recognition using unlabeled data. The invention can improve the accuracy and recall rate of the Chinese named entity recognitionin the specific field.

The invention discloses a database SQL infusion protecting method based on self-learning, comprising a learning phase and a filtering phase. The learning phase works in safe environment. At the moment, all SQL sentences are legitimate SQL sentences generated by an application system. A knowledge model (knowledge base) of the legitimate SQL sentences can be constituted by analyzing the sentences as well as analyzing and summarizing the characteristics of the sentences on the basis of sentence analysis results. The filtering phase works in real environment. At the moment, all SQL sentences are assumed to be possibly illegitimate SQL sentences. The sentences undergo pattern matching with the knowledge base established in the safe environment. If the matching is successful, the sentences are legitimate SQL sentences, otherwise, the sentences are illegitimate SQL sentences. The database SQL infusion protecting method has the advantage that an SQL infusion protecting system based on learning the legitimate SQL sentences can greatly reduce the false report rate and missing report rate which are caused by traditional SQL infusion protection, and the defending capability of the whole system can be improved.

A synthetic single crystal diamond material comprising: a first region comprising electron donor defects; a second region comprising quantum spin defects; and a third region between the first and second regions. The second and third regions have a lower concentration of electron donor defects than the first region. The first and second regions are sufficiently close to allow electrons to be donated from the first region to the second region, thus forming negatively charged quantum spin defects in the second and positively charged defects in the first region, and sufficiently far apart to reduce other coupling interactions between the first and second regions which would otherwise unduly reduce the decoherence time of the plurality of quantum spin defects and / or produce strain broaden of a spectral line width of the plurality of quantum spin defects in the second region.

The invention provides a massive log data intelligent operation and maintenance system. The system comprises a log collecting module, a log processing module, a log storage module and a business application module, wherein the log collecting module is used for collecting application logs, operation system logs and network equipment logs on a target machine, structuring log data and then outputtingthe log data to the log processing module; the log processing module is used for real-time processing and offline processing, real-time processing comprises real-time statistics, real-time alarming and real-time analysis, and offline processing comprises data batch storage, offline analysis and machine learning; then the processed information is sent to the log storage module; the log storage module is used for storing original log data, index data, statistical analysis data and resource configuration data, and comprises a MySQL relation database, a Redis memory database, an Elastic search engine and an HBase column storage database; the business application module is used for providing functions of inquiry statistics, monitoring and alarming, intelligent reports, instrument panels and knowledge bases through a web interface, and the data is read out from the log storage module.

The invention relates to a multi-resolution medical image registration method based on the quantum-behaved particle swarm optimization, which is characterized in that the method comprises the following step of: firstly removing the backgrounds of the two images to be registered to keep the images off the interference of noise; next obtaining the images with low resolution from the two background-removed images via the wavelet transform, using the low resolution to be the object, taking the normalized mutual information as the objective function, using the quantum-behaved particle swarm optimization, then the images with the high resolution to be the object, and obtaining the rotation amount and the translation amount between the two images to be registered to finish the image registration by using the Powell method. With solving a plurality of local extrema based on the objective function of the mutual information, the invention greatly improves the registration precision and speed, reaching up to the sub-pixel level; and is widely applicable to the fields of the image discrimination of the clinical diagnosis, the framing of the radiation treatment, the image guided surgical, etc.

The invention discloses an on-line transformer fault diagnosis method based on support vector machines (SVM) and dissolved gas analysis (DGA), which belongs to the field of transformer fault diagnosis. The method comprises the following steps of: acquiring the concentration of fault feature gases including H2, CH4, C2H2, C2H4 and C2H6 in transformer insulating oil by a gas chromatographic analysis method, normalizing the data through a preprocessing system, sending the data to a classification diagnosis system assembled by an integrative learning method and formed by six SVM classifiers according to a decision process, classifying the measurement data through calculation, judging the running state of the transformer, and at last outputting the diagnosis results. In the method, the support vector machines (SVM) of the artificial intelligence technology are adopted to analyze the gases in the oil, and the relation between gas components and the running state of the transformer can be objectively and essentially reflected, thereby the accuracy of fault diagnosis is effectively improved.

A system and method for management of network traffic flow for one or more networks of interconnected computing devices, including predicting one or more types of network traffic data flows using a Machine Learning (ML) classifier, and updating the ML classifier according to identified changes in the network traffic data flows. Using software-defined-networking (SDN) tools and an updated ML classifier, training data is generated to formulate accurate new predictions of the one or more types of network traffic data flows. Network traffic flow is regulated based on the generated new predictions.

The 3D active real-time positioning system based on binocular vision and laser ranging consists of three parts of vision processing subsystem, control subsystem and mechanical mechanism. The target image the video camera under the control of image acquisition card obtains is processed in the vision processing computer to obtain the 2D position information in image coordinate sent to the public memory area. Then, the control computer obtains the position information from the public memory area, performs coordinate conversion and real-time programming, outputs via D / A converter board to the driver to drive the motor and controls the laser via the angle encoder feedback loop to irradiate the target accurately. Finally, the depth information the range finder measures is fed back to the vision computer to obtain the 3D position information of the target. The system has the advantages of high distance precision, high activity, high real-time performance, low cost, etc.

Described is a system and method by which an auxiliary computing device having an auxiliary display platform that displays information corresponding to data that originated on the main computer system may be extended by a device manufacturer. Extended hardware is added to the device, such as a radio receiver and / or an audio decoder. The auxiliary display platform is layered and extensible at each layer, and includes an extensible hardware abstraction layer that is extensible to support extended hardware if needed, and a driver layer that is extensible by adding driver code for the extended hardware. A runtime layer is also extensible to support the extended hardware as needed, as are libraries, the auxiliary shell program and other managed code. The client API is also extensible to allow applications on the main computer system to communicate with extended hardware via the device runtime layer.

A method and apparatus are provided for adapting an exponential probability model. In a first stage, a general-purpose background model is built from background data by determining a set of model parameters for the probability model based on a set of background data. The background model parameters are then used to define a prior model for the parameters of an adapted probability model that is adapted and more specific to an adaptation data set of interest. The adaptation data set is generally of much smaller size than the background data set. A second set of model parameters are then determined for the adapted probability model based on the set of adaptation data and the prior model.