Abstract: First sample data is generated to render an instance of a first graph element type with a first axis. Second sample data is generated to render an instance of a second graph element type with a second axis parallel to the first axis. Data points used for the first axis are different from data points used for the second axis. A first axis selector is presented in association with the first axis. An indicator is received that indicates selection of the presented first axis selector. After receipt of the indicator, a second indicator is received that indicates selection of a shared role between the first axis and the second axis. After receipt of the second indicator, the instance of the second graph element type is rendered with the first axis. Third data points used for the second axis automatically have the same value as first data points used for the first axis.

Abstract: A computing device predicts a probability of a transformer failure. An analysis type indicator defined by a user is received. A worth value for each of a plurality of variables is computed. Highest worth variables from the plurality of variables are selected based on the computed worth values. A number of variables of the highest worth variables is limited to a predetermined number based on the received analysis type indicator. A first model and a second model are also selected based on the received analysis type indicator. Historical electrical system data is partitioned into a training dataset and a validation dataset that are used to train and validate, respectively, the first model and the second model. A probability of failure model is selected as the first model or the second model based on a comparison between a fit of each model.

Abstract: Various embodiments are generally directed to an apparatus, method and other techniques for receiving a request to generate a bootable image in a cloud-based computing environment, creating a block storage volume in the cloud-based computing environment in response to receiving the request, the block storage volume having one or more partitions. Further, an apparatus, method and so forth may include installing software comprising one or more files in a file system on the block storage volume in the cloud-based computing environment, creating a snapshot of the file system including the software in the cloud-based computing environment, and creating a bootable image from the snapshot of the file system in the cloud-based computing environment.

Abstract: A computing device is provided that supports receipt and processing of blocks of streamed data associated with an event and provision of pre-rendered and compressed events to event client systems with a high-throughput. The computing device includes a compression optimizer module that determines how to make new compressed blocks of the right level of compression as the blocks of streamed data are received from an event publishing system. The compression optimizer module utilizes a tree map and unique identifiers to selectively compress, read, and recompress the blocks of streamed data associated with each event. To prevent duplicate work in compressing the streamed data, compressed blocks are re-used where possible to support requests from the event client systems. Each new block includes a unique identifier defined by the event publishing system that generated the event, so that a previous version of the event in a compressed block can be replaced.

Abstract: A method of adding a link to a network of linked nodes is provided. Received scoring information includes a first node identifier, a second node identifier, and a link value. The link value is determined using an analytic model. A first anchored network record for which a first node associated with the first node identifier is an anchor is identified. A first link record is added to the identified first anchored network record using the first node identifier, the second node identifier, and the link value. A first node record associated with the second node identifier is added to the identified first anchored network record. A node record is identified for the first node in the identified anchored network record. A network score value included in the identified node record is computed based on the link value. The identified node record is updated with the computed network score value.

Abstract: In a method of rendering a plurality of graph elements, first sample data is generated to render an instance of a first graph element type in a first cell of a canvas panel. An indicator is received that indicates a second graph element type to present in the first cell overlaid with the instance of the first graph element type. Second sample data is generated to render an instance of the second graph element type in the first cell overlaid with the instance of the first graph element type. An indicator is received that indicates selection of a fourth indicator of the instance of the second graph element type. An indicator is received that indicates dropping of the fourth indicator into a second cell. Third sample data is generated to render a second instance of the second graph element type in the second cell.

Abstract: Embodiments are generated directed to method, medium, and system including processing circuitry to generate records including randomly selected events for each of one or more subjects having one or more of the same category parameters as a subject of a particular event. The processing circuitry may also present, on a display device, a computer-generated model based on the records, the model having a decision tree data structure having decision tree nodes corresponding with historical events from the records, each of the decision tree nodes having an indication of a likelihood of occurrence for the particular event based on whether a corresponding history event of the decision tree node occurred or did not occur within a specific time period. Embodiments of the real-time distributed nature of the systems and processing discussed herein can solve big data analytics processing problems and facilitate data anomaly detection.

Abstract: Techniques to generate custom electronic forms are described. An apparatus may comprise a logic device and an application having a form manager component. The form manager component may be operative on the logic device to manage one or more forms for a user interface of the application during a run-time mode of the application. The form manager component may have a custom prompt module operative to determine whether an application context interface is available for a dynamic form prompt of a form. The form manager component may determine whether a custom language interface is available for the dynamic form prompt when the application context interface is available. The form manager component may retrieve custom content in a custom presentation language for the dynamic form prompt when the custom language interface is available. Other embodiments are described and claimed.

Abstract: A computing device identifies outliers. Support vectors, Lagrange constants, a center threshold value, an upper control limit value, and a lower control limit value are received that define a normal operating condition of a system. The center threshold value, the upper control limit value, and the lower control limit value are computed from the vectors and the Lagrange constants. A first plurality of observation vectors is received for a predefined window length. A window threshold value and a window center vector are computed. A window distance value is computed between the window center vector and the support vectors. Based on comparisons between the computed values and the received values, the first plurality of observation vectors is identified as an outlier relative to the normal operating condition of the system. When the first plurality of observation vectors are identified as the outlier, an alert is output.

Abstract: A method of generating a decision tree is provided. A leaf assignment for each proposed split in generating the decision tree is incremented using a Gray code.

Abstract: This disclosure describes methods, systems, computer-readable media, and apparatuses for efficiently calculating group-by statistics. A data set that includes multiple entries is accessed. The multiple entries are grouped into group-by subsets which are formed on two or more group-by variables and which are subsets are subsets of the data set. Cardinality data is determined for each of the group-by subsets, wherein cardinality data represents a number of entries in a group-by subset. At least one summary of data in each of the group-by subsets is generated, wherein each of the summaries includes the cardinality data determined for the group-by subset. Objects for the group-by subsets are initialized such that the objects store the summaries. The objects may then be used to generate multiple statistical summaries of the data set.

Abstract: Techniques to determine settings for an electrical distribution network are described. Some embodiments are particularly directed to techniques to determine settings for an electrical distribution network using power flow heuristics. In one embodiment, for example, an apparatus may comprise a model reception component, a forecast component, and an optimization component. The model reception component may be operative to receive a model of an electrical distribution network having multiple capacitor banks and multiple voltage regulators, each of the multiple capacitor banks represented in the model by a model capacitor bank, each of the multiple voltage regulators represented in the model by a model voltage regulator, the electrical distribution network having a radial layout in which power flows from a source to multiple nodes in which each node is associated with one voltage regulator. The forecast reception component may be operative to receive a forecast for demand on the electrical distribution network.

Abstract: A computing device restores a state of an analytic model. A first indicator of a dataset is received. A second indicator is received of an analytic model state file in which a state of an analytic model is stored. A reentry point name of a function to restore the analytic model is extracted from the state stored in the analytic model state file indicated by the received second indicator. The function is called using the extracted reentry point name to restore the state of the analytic model. The dataset indicated by the received first indicator is scored using the restored state of the analytic model. Scoring results from the scored dataset are written to an output file.

Abstract: An apparatus includes 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 each 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.

Abstract: Various embodiments are generally directed to an apparatus, method and other techniques for receiving a request to generate a bootable image in a cloud-based computing environment, creating a block storage volume in the cloud-based computing environment in response to receiving the request, the block storage volume having one or more partitions. Further, an apparatus, method and so forth may include installing software comprising one or more files in a file system on the block storage volume in the cloud-based computing environment, creating a snapshot of the file system including the software in the cloud-based computing environment, and creating a bootable image from the snapshot of the file system in the cloud-based computing environment.

Abstract: Exemplary embodiments are generally directed to methods, mediums, and systems for accounting for extensions or reductions of the period for which a resource (e.g., computer processor time, scientific apparatus, storage units, devices, etc.) is allocated. According to exemplary embodiments, allocation-based aggregated effects of extension and relinquishment are modeled. The modeled effects are used to offset allocation forecasts based on historical data. As a result, the dimensionality of the problem of incorporating in-house data is greatly reduced as compared to other techniques, and allocation forecasts can be made more accurately and efficiently.

Abstract: Systems and methods are provided for identifying and detecting unauthorized user activity and for decreasing the rate of false-positives. The disclosed systems and techniques may involve analysis of users' past activity data so that individual classifications and authorization decisions with respect to requested user activity are based on activity data associated with a user's use of multiple services.

Abstract: A computing device sorts a plurality of data points in a first dimension. A first data point has a first value, a second data point has a second value, and a third data point has a third value defined in a second dimension. (a) The second value is compared to the first and third values. (b) When the second value is less than the first value and greater than the third value, or the second value is greater than the first value and less than the third value, the data point is deleted. (c) The first data point is defined as the second data point. (d) The second data point is defined as the third data point. (e) The third data point is defined as a next data point. (a)-(e) are repeated until each of the plurality of data points is defined as the third data point to define a plurality of sampled data points as remaining data points of the plurality of data points.

Abstract: Exemplary embodiments are generally directed to methods, mediums, and systems for correcting censored or constrained historical data with various possible types of computing devices, including cloud-based devices, personal computing devices, and edge-based devices. The corrected data may be used in forecasting, for example to forecast demand for a limited resource. In some embodiments, the data is modeled at a higher level of granularity than an individual record. The aggregated demand may then be pro-rated over a group of categories or users where a given category of users that might be small or nonexistent over a certain time frame may be better accommodated. Moreover, it may be easier or more efficient to make assumptions and employ computing resources at the aggregate level.

Abstract: Various embodiments are directed to techniques for countering oscillation in community assignments of nodes in a network during detection of its communities. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium includes instructions operable to cause a computing device to derive a first connectedness metric of a first community to which a first node of a network belongs and a second connectedness metric of a second community to which a second node of the network belongs in parallel in an iteration of parallel detection of communities in the network, wherein the first and second nodes are connected in the network; randomly pin the first node to prevent its reassignment to another community during the iteration; compare the first and second connectedness metrics during the iteration; and reassign the second node from the second community to the first community based on the comparison. Other embodiments are described and claimed.