Abstract:
Described are a system and method for determining an event occurrence rate. A sample set of content items may be obtained. Each of the content items may be associated with at least one region in a hierarchical data structure. A first impression volume may be determined for the at least one region as a function of a number of impressions registered for the content items associated with the at least one region. A scale factor may be applied to the first impression volume to generate a second impression volume. The scale factor may be selected so that the second impression volume is within a predefined range of a third impression volume. A click-through-rate (CTR) may be estimated as a function of the second impression volume and a number of clicks on the content item.
Abstract:
A field programmable device is disclosed, including a plurality of logic blocks; a plurality of connections connecting the logic blocks; configuration circuitry for outputting configuration data for programming the field programmable device, the configuration circuitry providing at least one pair of outputs; and error detection circuitry for comparing the outputs to determine if there has been a configuration error.
Abstract:
A method and apparatus for customizing content presented to individual users or user segments is provided. There may be three components, a web portal and toolbar component, a modeling component, and a scoring component. The web portal and toolbar component presents content items and collects data. The web portal and toolbar component generates user event data based on the user actions. The user event data is forwarded to the modeling component. The modeling component generates content scoring functions based on user event data and attributes of content items. Content scoring functions may be unique to individual user segments. The content scoring functions based on content features generate probability a content item will be viewed. The scoring component decides which content items are placed in a portal. The scoring component uses the scoring functions generated by the modeling component to rank content items in real time.
Abstract:
A Programmable Logic Device providing reduction in power consumption for sequential logic and data storage functions, including at least one circuit arrangement configurable to function as a dual-edge-triggered flip-flop operating on a selected one or both edges of the circuit clock.
Abstract:
A method and system for assisting a user in generating a report regarding a procedure such as a medical procedure. A first display region provides a hierarchical menu of available keywords from a knowledge base. A second display region provides a hierarchical menu of particular keywords that have been selected by the user. A third display region provides a report from a sentence that was generated by populating a sentence model based on the selected keywords. The sentence can be edited by selecting a keyword from the sentence, then selecting a replacement keyword from the first display region. A grammar engine corrects the grammar of the sentence based on user settings for the keywords.
Abstract:
A method and system for capturing patient related data in an endoscopic system comprising an imaging node adapted to capture and display endoscopic images during the course of an endoscopic examination. The patient data capture system and method includes a display device that provides an interface to enable a user to enter data relating to a patient examined during the examination, including patient vital sign information at various phases of care relating to the endoscopic examination and, further including individual graphic controls for enabling entry of values relating to the patient's vitals information. The entered patients vitals information is associated with a timestamp. The patient vitals information and associated timestamps are stored in a database record associated with the patient. Further data capable of being entered into the system includes medications administered, Aldrete scores and intraprocedural assessments.
Abstract:
Systems, methods, and computer storage media having computer-executable instructions embodied thereon for rewriting queries and labeling word pairs. Queries are received and alternate words are identified for word pairs (i.e., query words and alternate words). Word pair links are presented to users and indicators are received based on actions taken by the users. Labels are assigned to the word pairs based on the indicators and communicated to a classifier.
Abstract:
A method and apparatus for anomaly detection in a data stream are disclosed. In one embodiment, the present method detects an anomalous condition in a data stream, by calculating at least one expected base event count for at least one event in the data stream for a time interval, obtaining an actual event count for the at least one event in the data stream, applying at least one shrinkage factor to the at least one expected base event count to obtain at least one actual estimated event count and detecting the anomalous condition in accordance with the actual event count and the at least one actual estimated event count.
Abstract:
Described are a system and method for determined an event occurrence rate. A sample set of content items may be obtained. Each of the content items may be associated with at least one region in a hierarchical data structure. A first impression volume may be determined for the at least one region as a function of a number of impressions registered for the content items associated with the at least one region. A scale factor may be applied to the first impression volume to generate a second impression volume. The scale factor may be selected so that the second impression volume is within a predefined range of a third impression volume. A click-through-rate (CTR) may be estimated as a function of the second impression volume and a number of clicks on the content item.
Abstract:
A method for predicting future responses from large sets of dyadic data includes measuring a dyadic response variable associated with a dyad from two different sets of data; measuring a vector of covariates that captures the characteristics of the dyad; determining one or more latent, unmeasured characteristics that are not determined by the vector of covariates and which induce local structures in a dyadic space defined by the two different sets of data; and modeling a predictive response of the measurements as a function of both the vector of covariates and the one or more latent characteristics, wherein modeling includes employing a combination of regression and matrix co-clustering techniques, and wherein the one or more latent characteristics provide a smoothing effect to the function that produces a more accurate and interpretable predictive model of the dyadic space that predicts future dyadic interaction based on the two different sets of data.