Abstract: A computer readable storage medium configured to cause a system to perform operations of computing the standard deviation of a plurality of K?1 most recent heart beat intervals and a current heart beat interval (I1) from a plurality of consecutive heart beat intervals, from a sum (S1) of K most recent heart beat intervals squared and the sum (S2) of the K most recent heart beat intervals and a Kth oldest heart beat interval (I2). The computer readable storage medium calculates an updated sum (S1?) of S1 minus I2 squared plus I1 squared and the updated sum (S2?) of S2 minus I2 plus I1, and a square root of the sum of the ratio of S1? to K and of the ratio of the square of S2? to the square of K.

Abstract: Techniques are provided that include obtaining a Document Object Model of an HTML document. A configuration XPath is obtained identifying, as of a configuration time, a node within the Document Object Model as a native advertisement placement candidate container. Additional information is obtained regarding native advertisement placement candidate containers within the Document Object Model, and an injection XPath, identifying a node within the Document Object Model as a native advertisement placement candidate container, is generated at an injection time, subsequent to the configuration time, based on the configuration XPath and the additional information. The additional information may include information regarding at least one of a title element, description element and image element identified by a user as being associated with native advertisement placement candidate containers. Generating the injection XPath may include removing a numerical identifier from one or more tags of the configuration XPath.

Abstract: Techniques are provided that include obtaining a Document Object Model of an HTML document, such as a web page of a publisher. Elements of the Document object model may be identified that are associated with native advertisement placement candidate containers. Based at least in part on analysis associated with the Document Object Model, and utilizing at least some of the identified elements, one or more native advertisement placement candidate containers may be determined. Some techniques may utilize, in the analysis, identification of one or more secondary source HTML documents associated with a primary HTML document, and may identify, within the secondary source HTML document(s), content associated with native advertisement placement candidate containers of the primary HTML document(s).

Abstract: Techniques are provided that include obtaining a Document Object Model of an HTML document, such as a web page of a publisher. Elements of the Document object model may be identified that are associated with native advertisement placement candidate containers. Based at least in part on analysis associated with the Document Object Model, and utilizing at least some of the identified elements, one or more native advertisement placement candidate containers may be determined. With some techniques, the analysis includes identifying a deepest set of nodes in the Document Object Model, corresponding to a particular tag sequence, whose cardinality is no less than a cardinality of a set of nodes in the Document Object Model, corresponding to a particular tag sequence, corresponding to the identified elements. Some techniques may utilize XPaths in the analysis.

Abstract: Techniques are provided that include obtaining a Document Object Model of an HTML document, such as a web page of a publisher. Elements of the Document Object Model may be identified that are associated with native advertisement placement candidate containers. Based at least in part on analysis associated with the Document Object Model, and utilizing at least some of the identified elements, one or more native advertisement placement candidate containers may be determined. Some techniques may utilize, in the analysis, construction and utilization of a suffix tree of a string of tags comprising all tags in the Document Object Model. Some techniques may utilize, in the analysis, a node flattening technique in connection with the Document Object Model.

Abstract: A computer readable storage medium configured to cause a system to perform operations of computing the standard deviation of a plurality of K-1 most recent heart beat intervals and a current heart beat interval (I1) from a plurality of consecutive heart beat intervals, from a sum (S1) of K most recent heart beat intervals squared and the sum (S2) of the K most recent heart beat intervals and a Kth oldest heart beat interval (I2). The computer readable storage medium calculates an updated sum (S1?) of S1 minus I2 squared plus I1 squared and the updated sum (S2?) of S2 minus I2 plus I1, and a square root of the sum of the ratio of S1? to K and of the ratio of the square of S2? to the square of K.

Abstract: Techniques are provided that include obtaining a Document Object Model of an HTML document, such as a web page of a publisher. Elements of the Document Object Model may be identified that are associated with native advertisement placement candidate containers. Based at least in part on analysis associated with the Document Object Model, and utilizing at least some of the identified elements, one or more native advertisement placement candidate containers may be determined. Some techniques may utilize, in the analysis, construction and utilization of a suffix tree of a string of tags comprising all tags in the Document Object Model. Some techniques may utilize, in the analysis, a node flattening technique in connection with the Document Object Model.

Abstract: A computer readable storage medium configured to cause a system to perform operations of computing the standard deviation of a plurality of K?1 most recent heart beat intervals and a current heart beat interval (I1) from a plurality of consecutive heart beat intervals, from a sum (S1) of K most recent heart beat intervals squared and the sum (S2) of the K most recent heart beat intervals and a Kth oldest heart beat interval (I2). The computer readable storage medium calculates an updated sum (S1?) of S1 minus I2 squared plus I1 squared and the updated sum (S2?) of S2 minus I2 plus I1, and a square root of the sum of the ratio of S1? to K and of the ratio of the square of S2? to the square of K.

Abstract: Techniques are provided that include obtaining a Document Object Model of an HTML document, such as a web page of a publisher. Elements of the Document Object Model may be identified that are associated with native advertisement placement candidate containers. Based at least in part on analysis associated with the Document Object Model, and utilizing at least some of the identified elements, one or more native advertisement placement candidate containers may be determined. Some techniques may utilize, in the analysis, construction and utilization of a suffix tree of a string of tags comprising all tags in the Document Object Model. Some techniques may utilize, in the analysis, a node flattening technique in connection with the Document Object Model.

Abstract: Techniques are provided that include obtaining a Document Object Model of an HTML document, such as a web page of a publisher. Elements of the Document Object Model may be identified that are associated with native advertisement placement candidate containers. Based at least in part on analysis associated with the Document Object Model, and utilizing at least some of the identified elements, one or more native advertisement placement candidate containers may be determined. Some techniques may utilize, in the analysis, construction and utilization of a suffix tree of a string of tags comprising all tags in the Document Object Model. Some techniques may utilize, in the analysis, a node flattening technique in connection with the Document Object Model.

Abstract: In one embodiment, a method includes accessing an inverted index of a searchable set of objects including key words. The inverted index includes multiple lists each corresponding to a particular key word and identifying a particular subset of the objects including the particular key word. The method includes generating a binary decision diagram (BDD) for each of one or more of the lists. The BDD corresponds to the particular key word of the list, and each decision node of the BDD represents an object in the searchable set of objects including the particular key word of the list. The method includes storing each of one or more of the lists as its BDD. Storage of the BDD facilitates more efficient storage of the inverted index.

Abstract: Techniques are provided that include obtaining a Document Object Model of an HTML document, such as a web page of a publisher. Elements of the Document Object Model may be identified that are associated with native advertisement placement candidate containers. Based at least in part on analysis associated with the Document Object Model, and utilizing at least some of the identified elements, one or more native advertisement placement candidate containers may be determined. Some techniques may utilize, in the analysis, construction and utilization of a suffix tree of a string of tags comprising all tags in the Document Object Model. Some techniques may utilize, in the analysis, a node flattening technique in connection with the Document Object Model.

Abstract: In one embodiment, modeling topics includes accessing a corpus comprising documents that include words. Words of a document are selected as keywords of the document. The documents are clustered according to the keywords to yield clusters, where each cluster corresponds to a topic. A statistical distribution is generated for a cluster from words of the documents of the cluster. A topic is modeled using the statistical distribution generated for the cluster corresponding to the topic.

Abstract: A method of determining stress includes receiving a data signal including multiple consecutive RR intervals of a subject. The method may also include calculating heart rate variability (HRV) data for the subject from the data signal. The method may also include calculating an RR integral average (RRIA) from the HRV data, the RRIA indicating a stress level of the subject.

Abstract: A method of operating an image-sensing device includes detecting a trigger. The method also includes, in response to detecting the trigger, changing an operating mode of the image-sensing device from a first operating mode having a first spatial resolution and a first temporal resolution to a second operating mode having a second spatial resolution and a second temporal resolution. The second spatial resolution may be lower than the first spatial resolution and the second temporal resolution may be higher than the first temporal resolution. The method may also include capturing video data in the second operating mode, the video data having the second spatial resolution and the second temporal resolution.

Abstract: In particular embodiments, a method includes accessing data streams from a first group of physiological sensors monitoring a person, a second group of deconfounding sensors monitoring the person, and a third group of sensors monitoring a stressor, analyzing data sets collected from the person when the person is exposed and not exposed to the stressor, and determining a current stress factor for the stressor with respect to the person based on the analysis.

Abstract: In particular embodiments, a method includes accessing a first binary decision diagram (BDD) representing data streams from sensors, selecting portions from the first BDD based on ease-of-analysis, and constructing a plurality of sub-BDDs by partitioning the first BDD, wherein the sub-BDDs comprises a first sub-BDD representing the selected portions, and second sub-BDDs representing the non-selected portions.

Abstract: In particular embodiments, a method includes analyzing a binary decision diagram (BDD) representing a data stream from a sensor to determine a compression rate of the BDD and indicating a sensor malfunction in the sensor if the compression rate of the BDD deviates from a specified compression rate range.

Abstract: A computer readable storage medium configured to cause a system to perform operations of computing the standard deviation of a plurality of K?1 most recent heart beat intervals and a current heart beat interval (I1) from a plurality of consecutive heart beat intervals, from a sum (S1) of K most recent heart beat intervals squared and the sum (S2) of the K most recent heart beat intervals and a Kth oldest heart beat interval (I2). The computer readable storage medium calculates an updated sum (S1?) of S1 minus I2 squared plus I1 squared and the updated sum (S2?) of S2 minus I2 plus I1, and a square root of the sum of the ratio of S1? to K and of the ratio of the square of S2? to the square of K.

Abstract: Techniques are provided that include obtaining a Document Object Model of an HTML document, such as a web page of a publisher. Elements of the Document Object Model may be identified that are associated with native advertisement placement candidate containers. Based at least in part on analysis associated with the Document Object Model, and utilizing at least some of the identified elements, one or more native advertisement placement candidate containers may be determined. Some techniques may utilize, in the analysis, construction and utilization of a suffix tree of a string of tags comprising all tags in the Document Object Model. Some techniques may utilize, in the analysis, a node flattening technique in connection with the Document Object Model.