Abstract: Algorithms for detecting endotracheal intubation and/or misplacement of endotracheal tubes in child patients during anesthesia for use with anesthesia machines, mechanical ventilators, and/or respiratory function monitors. An algorithm uses end-tidal carbon dioxide (EtCO2), and tidal volume (TV) or peak inspiratory pressure (PIP) to detect exact intubation time. Another algorithm uses respiratory parameters to identify and/or confirm the type of airway device used during mechanical ventilation, and to detect if and when an issue has arisen with use of a specific airway device to provide real-time decision support to attending medical care professionals.

Abstract: Techniques and mechanisms described herein facilitate adaptive fuzzy fallback stratified sampling. According to various embodiments, an actual or estimated minimum vertex cover of a feature dependency graph representing a dataset may be determined. The dataset may include a plurality of feature vectors and a plurality of features. Each feature vector may include a plurality of feature values that correspond with the features. The feature dependency graph may represent a plurality of conditional dependencies between the features. The minimum vertex cover may designate a subset of the features for strata selection. The feature vectors may be partitioned into a plurality of strata based on the designated subset of features. Each stratum may include one or more of the feature vectors. Each feature vector may be assigned to a corresponding stratum based on the values of the designated subset of features for the feature vector.

Abstract: Algorithms for detecting endotracheal intubation and/or misplacement of endotracheal tubes in child patients during anesthesia for use with anesthesia machines, mechanical ventilators, and/or respiratory function monitors. An algorithm uses end-tidal carbon dioxide (EtCO2), and tidal volume (TV) or peak inspiratory pressure (PIP) to detect exact intubation time. Another algorithm uses respiratory parameters to identify and/or confirm the type of airway device used during mechanical ventilation, and to detect if and when an issue has arisen with use of a specific airway device to provide real-time decision support to attending medical care professionals.

Abstract: Techniques and mechanisms described herein facilitate adaptive fuzzy fallback stratified sampling. According to various embodiments, an actual or estimated minimum vertex cover of a feature dependency graph representing a dataset may be determined. The dataset may include a plurality of feature vectors and a plurality of features. Each feature vector may include a plurality of feature values that correspond with the features. The feature dependency graph may represent a plurality of conditional dependencies between the features. The minimum vertex cover may designate a subset of the features for strata selection. The feature vectors may be partitioned into a plurality of strata based on the designated subset of features. Each stratum may include one or more of the feature vectors. Each feature vector may be assigned to a corresponding stratum based on the values of the designated subset of features for the feature vector.

Abstract: Techniques and mechanisms described herein facilitate adaptive fuzzy fallback stratified sampling. According to various embodiments, an actual or estimated minimum vertex cover of a feature dependency graph representing a dataset may be determined. The dataset may include a plurality of feature vectors and a plurality of features. Each feature vector may include a plurality of feature values that correspond with the features. The feature dependency graph may represent a plurality of conditional dependencies between the features. The minimum vertex cover may designate a subset of the features for strata selection. The feature vectors may be partitioned into a plurality of strata based on the designated subset of features. Each stratum may include one or more of the feature vectors. Each feature vector may be assigned to a corresponding stratum based on the values of the designated subset of features for the feature vector.

Abstract: Techniques and mechanisms described herein facilitate the dynamic selection of bid price. According to various embodiments, a base bid price may be determined for an advertising opportunity bid request received at a communications interface during a designated time period. A designated bid price may be for the advertising opportunity bid request. The designated bid price may be determined at least in part by applying a bid multiplier value to the base bid price. The bid multiplier value may reflect a target pacing rate associated with the designated time period. A bid placement message may be transmitted via the communications interface. The bid placement message may identify the advertising opportunity bid request and the designated bid price.

Abstract: Techniques and mechanisms described herein facilitate the performance metric based placement of bids. According to various embodiments, a first threshold value for bid placement may be identified. The first threshold value may designate a first threshold performance metric level for advertising opportunity bid requests received during a designated time period. An estimated performance metric may be determined for a designated advertising opportunity bid request received during the designated time period. A bid placement message may be transmitted via a communications interface when the estimated performance metric is greater than the first threshold value. The bid request may identify the designated advertising opportunity bid request and a bid placement value.

Abstract: Techniques and mechanisms described herein facilitate efficient budget pacing. According to various embodiments, a plurality of advertising request opportunities may be received at a communications interface during a time interval divided into a plurality of time periods. The time periods may include a designated time period, and a pacing rate for the designated time period may be determined. Each of the advertising request opportunities may be capable of being purchased to present a respective online advertisement. The pacing rate may designate a portion of the advertising request opportunities received during the designated time period on which to bid. One or more instructions may be transmitted to place a plurality of bids on selected ones of the advertising request opportunities received during the designated time period in accordance with the pacing rate.

Abstract: Techniques and mechanisms described herein facilitate adaptive fuzzy fallback stratified sampling. According to various embodiments, an actual or estimated minimum vertex cover of a feature dependency graph representing a dataset may be determined. The dataset may include a plurality of feature vectors and a plurality of features. Each feature vector may include a plurality of feature values that correspond with the features. The feature dependency graph may represent a plurality of conditional dependencies between the features. The minimum vertex cover may designate a subset of the features for strata selection. The feature vectors may be partitioned into a plurality of strata based on the designated subset of features. Each stratum may include one or more of the feature vectors. Each feature vector may be assigned to a corresponding stratum based on the values of the designated subset of features for the feature vector.

Abstract: A method of calculating the fast Fourier transform or the inverse fast Fourier transform of a series of N real samples x(n), with N power of two, operating according to a time interleaving algorithm and providing the sample series X(n) in ascending order to index n and using limited calculating storage means. A method of calculating the fast Fourier transform or the inverse fast Fourier transform of a series of N conjugated complex samples X(n), with N power of two, operating according to a frequency interleaving algorithm.