Abstract:
A computing device (2002) accesses a machine learning model (2050) trained on training data (2032) of first bonding operations (1308, 2040A) (e.g., a ball and/or stitch bond). The first bonding operations comprise operations to bond a first set of wires (1504) to a first set of surfaces (1506, 1508). The machine learning model is trained by supervised learning. The device receives input data (2070) indicating process data (2074) generated from measurements of second bonding operations (2040B). The second bonding operations comprise operations to bond a second set of wires to a second set of surfaces. The device weights the input data according to the machine learning model. The device generates an anomaly predictor (2052) indicating a risk for an anomaly occurrence in the second bonding operations based on weighting the input data according to the machine learning model. The device outputs the anomaly predictor to control the second bonding operations.
Abstract:
An apparatus including a processor to receive search criteria including a data value for a search within a data field; in response to the receipt of the query instructions, and for each data cell within a super cell, perform the specified search by comparing the data value to ranges of values indicated in a corresponding cell index to determine whether the data cell includes a data record meeting the search criteria, and in response to a determination that the data cell includes such a data record, use a unique values index in the cell index to search the data records of the data cell to identify one or more data records meeting the search criteria; and in response to identifying at least one data record meeting the search criteria, provide an indication that at least the data cell includes at least one data record meeting the search criteria.
Abstract:
Machines can be controlled using advanced control systems. Such control systems may use an automated version of singular spectrum analysis to control a machine. For example, a control system can perform singular spectrum analysis on a time series by: generating a trajectory matrix from the time series, performing singular value decomposition on the trajectory matrix to determine elementary matrices and corresponding eigenvalues, and automatically categorizing the elementary matrices into groups. The elementary matrices can be automatically categorized into the groups by: generating a matrix of w-correlation values based on the eigenvalues, categorizing the w-correlation values into a predefined number of w-correlation sets, and forming the groups based on the predefined number of w-correlation sets. The control system can then determine component time-series based on the groups, and generate a predictive forecast using the component time-series. The control system can use the predictive forecast to control operation of the machine.
Abstract:
A computing device resolves a prioritized list of Internet protocol (IP) address to domain names. Each request of a plurality of requests is added to a request list using a priority value. A lookup request packet is created from a first request selected from the request list and then removed from the request list. The lookup request packet is sent to a third computing device, and includes an IP address for which to resolve the domain name. A response is received from the third computing device that includes the IP address and the domain name of the IP address. The IP address is added to keystore data in association with the domain name. When the request list includes a next request, the next request is selected from the request list, and processing continues with creating the lookup request packet with the next request.
Abstract:
A computer system computes a score for a received data exchange and, in accordance with a neural network and input variables determined by received current exchange and history data, the computed score indicates a condition suitable for a denial. A set of attribution scores are computed using an Alternating Decision Tree model in response to a computed score that is greater than a predetermined score threshold value for the denial. The computed score is provided to an assessment unit and, if the computed score indicates a condition suitable for the denial and if attribution scores are computed, then a predetermined number of input variable categories from a rank-ordered list of input variable categories is also provided to the assessment unit of the computer system.
Abstract:
Systems and methods are provided for a grid computing system that performs analytical calculations on data stored in a distributed database system. A grid-enabled software component at a control node is configured to invoke database management software (DBMS) at the control node to cause the DBMS at a plurality of the worker nodes to make available data to the grid- enabled software component local to its node; instruct the grid-enabled software components at the plurality of worker nodes to perform an analytical calculation on the received data and to send the results of the data analysis to the grid-enabled software component at the control node; and assemble the results of the data analysis performed by the grid-enabled software components at the plurality of worker nodes.
Abstract:
Systems and methods are provided for generating multiple system state projections for one or more scenarios using a grid computing environment. A central coordinator software component executes on a root data processor and provides commands and data to a plurality of node coordinator software components. A node coordinator software component manages threads which execute on its associated node data processor and which perform a set of matrix operations. Stochastic simulations use results of the matrix operations to generate multiple state projections. Additional processing can be performed by the grid computing environment based upon the generated state projections, such as to develop risk information for users.
Abstract:
Disclosed is a method and apparatus for frame-transition effects, frame-specific access and reverse play in digitally compressed motion video, such video complying with the MPEG-1 standard. Transitions between two frames of video are effectuated by selecting a FROM frame and a TO frame, generating a stream of bidirectionally dependent duplicator frames which vary in their motion vector references to the FROM frame and the TO frame according to a predefined pattern, placing the FROM frame in the past buffer of a decoder, placing the TO frame in the future frame of a decoder, feeding the stream of duplicator frames to the decoder, causing the duplicator frames to be displayed, and beginning normal playback of the video stream containing the TO frame at the TO frame position. Frame-specific access is accomplished by determining the location of the target frame, determining the type of the target frame, identifying the reference frames to which the target frame directly and indirectly refers, parsing the reference frames with a decoder while the decorder's video display is suppressed, enabling the video display, and beginning normal decoder playback at the target frame location in said video bitstream. Reverse play is accomplished by employing this process for successive target frames where each target frame chosen immediately precedes the previous target frame in display order.
Abstract:
An apparatus includes processor (s) to: generate a set of candidate n-grams based on probability distributions from an acoustic model for candidate graphemes of a next word most likely spoken following at least one preceding word spoken within speech audio; provide the set of candidate n-grams to multiple devices; provide, to each node device, an indication of which candidate n-grams are to be searched for within the n-gram corpus by each node device to enable searches for multiple candidate n-grams to be performed, independently and at least partially in parallel, across the node devices; receive, from each node device, an indication of a probability of occurrence of at least one candidate n-gram within the speech audio; based on the received probabilities of occurrence, identify the next word most likely spoken within the speech audio; and add the next word most likely spoken to a transcript of the speech audio.
Abstract:
An apparatus includes a processor component caused to: retrieve metadata of organization of data within a data set, and map data of organization of data blocks within a data file; receive indications of which node devices are available to perform a processing task with a data set portion; and in response to the data set including partitioned data, compare the quantities of available node devices and of the node devices last involved in storing the data set. In response to a match, for cacti map data map entry: retrieve a hashed identifier for a data sub-block, and a size for each of the data sub-blocks within the corresponding data block; divide the hashed identifier by the quantity of available node devices; compare the modulo value to a designation assigned to each of the available node devices; and provide a pointer to the available node device assigned the matching designation.