Abstract: Methods, non-transitory machine readable media, and computing devices that ensure correctness of file system analytics are disclosed. With this technology, a first generation number for a volume is incremented in response to a modification of a rule set that defines properties of objects of a file system associated with the volume. A determination is made when a second generation number in a first inode for a first one of the objects matches the first generation number. The first inode is identified based on a traversal of a directory tree associated with the file system. The modified rule set is applied to the properties for the first one of the objects to obtain values, when the second generation number fails to match the first generation number. Analytics data is output after the traversal has completed. The analytics data is generated in response to a query and is based on the values.

Abstract: Systems and methods are disclosed for characterizing websites and viewers, for predicting GRPs (Gross Rating Points) for online advertising media campaigns, and for pricing media campaigns according to GRPs delivered as opposed to impressions delivered. To predict GRPs for a campaign, systems and methods are disclosed for first characterizing polarized websites and then characterizing polarized viewers. To accomplish this, a truth set of viewers with known characteristics is first established and then compared with historic and current media viewing activity to determine a degree of polarity for different Media Properties (MPs)—typically websites offering ads—with respect to gender and age bias. A broader base of polarized viewers is then characterized for age and gender bias, and their propensity to visit a polarized MP is rated. Based on observed and calculated parameters, a GRP total is then predicted and priced to a client/advertiser for an online ad campaign.

Abstract: Systems and methods are disclosed for employing supervised machine learning methods with activities and attributes of viewers with truth as input, to produce models that are utilized in determining probabilities that an unknown viewer belongs to one or more demographic segment categories. Using these models for processing viewer behavior, over a period of time a database of known categorized viewers is established, each categorized viewer having a probability of belonging to one or more segment categories. These probabilities are then used in bidding for online advertisements in response to impression opportunities offered in online media auctions. The probabilities are also used in predicting on-target impressions and GRPs (Gross Rating Points) in advance of online advertising media campaigns, and pricing those campaigns to advertiser/clients.

Abstract: Systems and methods are disclosed for optimizing an online advertising campaign both before the campaign begins, and dynamically during the campaign. Optimizations are performed comparatively between a plurality of MPs (Media Properties) based on their relative cost-per-engagement. Comparisons are performed by first stack ranking MP inventory including any of sites, feeds, and verticals, based on cost per engagement. Once ranked, scores are assigned to the targeted inventory and a mean score is determined. Then, the inventory is rated as high, normal, or low impact based on their scores compared with the mean and a standard deviation for all scores. Higher impact sites with scores at least a standard deviation above the mean are initially favored, and the MP targeting strategy is dynamically adjusted during the campaign based on periodically re-evaluating the MP rankings, frequencies of engagement, and campaign progress relative to fulfillment in an allotted run time.

Abstract: Systems and methods are disclosed for optimizing an online advertising campaign both before the campaign begins, and dynamically during the campaign. Optimizations are performed comparatively between a plurality of MPs (Media Properties) based on their relative cost-per-engagement. Comparisons are performed by first stack ranking MP inventory including any of sites, feeds, and verticals, based on cost per engagement. Once ranked, scores are assigned to the targeted inventory and a mean score is determined. Then, the inventory is rated as high, normal, or low impact based on their scores compared with the mean and a standard deviation for all scores. Higher impact sites with scores at least a standard deviation above the mean are initially favored, and the MP targeting strategy is dynamically adjusted during the campaign based on periodically re-evaluating the MP rankings, frequencies of engagement, and campaign progress relative to fulfillment in an allotted run time.

Abstract: Presentation of a video clip is made to persons having a high probability of viewing the clip. A database containing viewers of previously offered video clips is analyzed to determine similarities of preferences among viewers. When a new video clip has been watched by one or more viewers in the database, those viewers who have watched the new clip with positive results are compared with others in the database who have not yet seen it. Prospective viewers with similar preferences are identified as high likelihood candidates to watch the new clip when presented. Bids to offer the clip are based on the degree of likelihood. For one embodiment, a data collection agent (DCA) is loaded to a player and/or to a web page to collect viewing and behavior information to determine viewer preferences. Viewer behavior may be monitored passively by different disclosed methods.

Abstract: Systems and methods are disclosed for optimizing an online advertising campaign both before the campaign begins, and dynamically during the campaign. Optimizations are performed comparatively between a plurality of MPs (Media Properties) based on their relative cost-per-engagement. Comparisons are performed by first stack ranking MP inventory including any of sites, feeds, and verticals, based on cost per engagement. Once ranked, scores are assigned to the targeted inventory and a mean score is determined. Then, the inventory is rated as high, normal, or low impact based on their scores compared with the mean and a standard deviation for all scores. Higher impact sites with scores at least a standard deviation above the mean are initially favored, and the MP targeting strategy is dynamically adjusted during the campaign based on periodically re-evaluating the MP rankings, frequencies of engagement, and campaign progress relative to fulfillment in an allotted run time.

Abstract: A computer-based method for determining a set of equity-indexed crediting parameters I for an enhanced minimum death benefit guarantee equity-indexed deposit product also having a rider charge C, an enhanced minimum death benefit rollup percentage E, a set of profitability requirements R, a principal amount P, and an account value A, with C, E, R, P, A, and I determined at the time of product purchase. The method includes the steps of generating a set of yield curve and equity index scenarios consistent with valuation parameters, setting a trial value Ij for I for said product, calculating the observed distribution D of profitability using the equity index scenarios, comparing D with R, and computing a revised trial value Ij+1 for I for the product.

Abstract: The present invention broadly comprises a computer-based method for determining a set of equity-indexed crediting parameters C for an enhanced free partial withdrawal equity-indexed deposit product, including: generating a set of yield curve and equity index scenarios consistent with valuation parameters; setting a trial value Ci for the set of equity-indexed crediting parameters C; generating a set of trial values for a T?i and a Wi for each scenario; calculating corresponding values for an A for each scenario; calculating an observed distribution D of profitability using the scenarios; comparing D with an R; and, in response to comparing, computing a revised trial value Ci+1 for C, where the steps of setting, generating, calculating values for A, calculating D, and comparing are performed by at least one general-purpose computer specially programmed to perform the steps of setting, generating, calculating values for A, calculating D, and comparing.

Abstract: Various user behaviors are passively monitored and recorded when a user/viewer interacts with a network video player, e.g. a web video player, while watching an online video clip. For one embodiment, a data collection agent (DCA) is loaded to the player and/or to a web page that displays the video clip. The DCA passively collects detailed viewing and behavior information without requiring any specific input or actions on the part of the user. Indications of user preferences are inferred by user actions leading up to viewing the video, while viewing the video, and just after and still related to viewing the video. The DCA periodically sends this information to a central server where it is stored in a central database and where it is used to determine preference similarities among different users. Recorded user preference information may also be used to rate a video itself.

Abstract: A displacement measuring cell may be used to measure linear and/or angular displacement. The displacement measuring cell may include movable and stationary electrodes in a conductive fluid. Electrical property measurements may be used to determine how far the movable electrode has moved relative to the stationary electrode. The displacement measuring cell may include pistons and/or flexible walls. The displacement measuring cell may be used in a touch-sensitive robotic gripper. The touch-sensitive robotic gripper may include a plurality of displacement measuring cells mechanically in series and/or parallel. The touch-sensitive robotic gripper may be include a processor and/or memory configured to identify objects based on displacement measurements and/or other measurements. The processor may determine how to manipulate the object based on its identity.

Abstract: Systems and methods are disclosed for characterizing websites and viewers, for predicting GRPs (Gross Rating Points) for online advertising media campaigns, and for pricing media campaigns according to GRPs delivered as opposed to impressions delivered. To predict GRPs for a campaign, systems and methods are disclosed for first characterizing polarized websites and then characterizing polarized viewers. To accomplish this, a truth set of viewers with known characteristics is first established and then compared with historic and current media viewing activity to determine a degree of polarity for different Media Properties (MPs)—typically websites offering ads—with respect to gender and age bias. A broader base of polarized viewers is then characterized for age and gender bias, and their propensity to visit a polarized MP is rated. Based on observed and calculated parameters, a GRP total is then predicted and priced to a client/advertiser for an online ad campaign.

Abstract: Presentation of a video clip is made to persons having a high probability of viewing the clip. A database containing viewers of previously offered video clips is analyzed to determine similarities of preferences among viewers. When a new video clip has been watched by one or more viewers in the database, those viewers who have watched the new clip with positive results are compared with others in the database who have not yet seen it. Prospective viewers with similar preferences are identified as high likelihood candidates to watch the new clip when presented. Bids to offer the clip are based on the degree of likelihood. For one embodiment, a data collection agent (DCA) is loaded to a player and/or to a web page to collect viewing and behavior information to determine viewer preferences. Viewer behavior may be monitored passively by different disclosed methods.

Abstract: Systems and methods are disclosed for characterizing websites and viewers, for predicting GRPs (Gross Rating Points) for online advertising media campaigns, and for pricing media campaigns according to GRPs delivered as opposed to impressions delivered. To predict GRPs for a campaign, systems and methods are disclosed for first characterizing polarized websites and then characterizing polarized viewers. To accomplish this, a truth set of viewers with known characteristics is first established and then compared with historic and current media viewing activity to determine a degree of polarity for different Media Properties (MPs)—typically websites offering ads—with respect to gender and age bias. A broader base of polarized viewers is then characterized for age and gender bias, and their propensity to visit a polarized MP is rated. Based on observed and calculated parameters, a GRP total is then predicted and priced to a client/advertiser for an online ad campaign.

Abstract: Presentation of a video clip is made to persons having a high probability of viewing the clip. A database containing viewers of previously offered video clips is analyzed to determine similarities of preferences among viewers. When a new video clip has been watched by one or more viewers in the database, those viewers who have watched the new clip with positive results are compared with others in the database who have not yet seen it. Prospective viewers with similar preferences are identified as high likelihood candidates to watch the new clip when presented. Bids to offer the clip are based on the degree of likelihood. For one embodiment, a data collection agent (DCA) is loaded to a player and/or to a web page to collect viewing and behavior information to determine viewer preferences. Viewer behavior may be monitored passively by different disclosed methods.

Abstract: A dual directional actuator may be linked to another actuator, device, object, or joint (e.g., a robotic limb or the like). A linkage mechanism may securely couple the actuator to the other actuator, device, object, or joint. Additionally, a piston axle bridge may couple the piston of the actuator to an internal or external axle. The dual directional actuator may be coupled to manifolds with integrated tee fittings to eliminate hoses external to a joint comprising one or more dual directional actuators.

Abstract: A multistage online auction for electronic advertising is described including simulation. A first stage auction occurs internally within a demand-side platform where multiple advertiser clients compete to determine whose advertisement is submitted to at least one external auction site. Within the internal auction, an advertiser client optionally simulates their participation. All bidders enter a bid and campaign targeting parameters. A simulating bidder's campaign is processed in real time just as those of real bidders. Ad placement opportunities received from an external auction site are filtered for each campaign producing a list of targetable impressions. For each targetable impression, the client placing the highest real bid has their ad and bid submitted to the second stage external auction. A simulating bidder receives a report on targetable impressions for their campaign. A targetable impression for a simulated bid that is higher than any real bid is reported as a winnable impression.

Abstract: Various user behaviors are passively monitored and recorded when a user/viewer interacts with a network video player, e.g. a web video player, while watching an online video clip. For one embodiment, a data collection agent (DCA) is loaded to the player and/or to a web page that displays the video clip. The DCA passively collects detailed viewing and behavior information without requiring any specific input or actions on the part of the user. Indications of user preferences are inferred by user actions leading up to viewing the video, while viewing the video, and just after and still related to viewing the video. The DCA periodically sends this information to a central server where it is stored in a central database and where it is used to determine preference similarities among different users. Recorded user preference information may also be used to rate a video itself.

Abstract: Various user behaviors are passively monitored and recorded when a user/viewer interacts with a network video player, e.g. a web video player, while watching an online video clip. For one embodiment, a data collection agent (DCA) is loaded to the player and/or to a web page that displays the video clip. The DCA passively collects detailed viewing and behavior information without requiring any specific input or actions on the part of the user. Indications of user preferences are inferred by user actions leading up to viewing the video, while viewing the video, and just after and still related to viewing the video. The DCA periodically sends this information to a central server where it is stored in a central database and where it is used to determine preference similarities among different users. Recorded user preference information may also be used to rate a video itself.

Abstract: A displacement measuring cell may be used to measure linear and/or angular displacement. The displacement measuring cell may include movable and stationary electrodes in a conductive fluid. Electrical property measurements may be used to determine how far the movable electrode has moved relative to the stationary electrode. The displacement measuring cell may include pistons and/or flexible walls. The displacement measuring cell may be used in a touch-sensitive robotic gripper. The touch-sensitive robotic gripper may include a plurality of displacement measuring cells mechanically in series and/or parallel. The touch-sensitive robotic gripper may be include a processor and/or memory configured to identify objects based on displacement measurements and/or other measurements. The processor may determine how to manipulate the object based on its identity.