Abstract: A system for receiving and deduplicating data strings transmitted over a network is disclosed. The system comprises one or more network sensors detecting data strings while in transit on the network; and non-transitory memory comprising instructions. When the instructions are executed by one or more processors, the one or more processors establish a plurality of Bloom filters, receive a first data string, perform a first insertion operation into each Bloom filter; determine, for each of one or more Bloom filters, a set of bits, whether presently set or cleared, to be unset; and unset each determined set of bits in the one or more Bloom filters. At a later moment in time, the first data string is received again, and each Bloom filter is queried to determine whether the first data string has been inserted, based on a current state of that Bloom filter.

Abstract: A system for receiving and deduplicating data strings transmitted over a network is disclosed. The system comprises one or more network sensors detecting data strings while in transit on the network; and non-transitory memory comprising instructions. When the instructions are executed by one or more processors, the one or more processors establish a plurality of Bloom filters, receive a first data string, perform a first insertion operation into each Bloom filter; determine, for each of one or more Bloom filters, a set of bits, whether presently set or cleared, to be unset; and unset each determined set of bits in the one or more Bloom filters. At a later moment in time, the first data string is received again, and each Bloom filter is queried to determine whether the first data string has been inserted, based on a current state of that Bloom filter.

Abstract: A system for receiving and deduplicating data strings transmitted over a network is disclosed. The system comprises one or more network sensors detecting data strings while in transit on the network; and non-transitory memory comprising instructions. When the instructions are executed by one or more processors, the one or more processors establish a plurality of Bloom filters, receive a first data string, perform a first insertion operation into each Bloom filter; determine, for each of one or more Bloom filters, a set of bits, whether presently set or cleared, to be unset; and unset each determined set of bits in the one or more Bloom filters. At a later moment in time, the first data string is received again, and each Bloom filter is queried to determine whether the first data string has been inserted, based on a current state of that Bloom filter.

Abstract: A system for collecting data artifacts from a production environment, storing them, and replaying them in a testing environment is disclosed. One or more processors receive a data artifact from a sensor in a production environment, and store the data artifact in a first storage with a unique identifier, while also storing in a second storage record(s) associating the unique identifier with a tag. A clone of at least a portion of the production environment is created within the testing environment, and an analytic targeting the data artifact is incorporated into the clone. Upon receiving a request to replay the data artifact, referencing the tag associated with the data artifact's unique identifier, the data artifact is replayed by causing the clone to receive the data artifact as if it were presently encountered. Logs of output from the clone's response are stored in a third storage for future analysis.

Abstract: A system for receiving and deduplicating data strings transmitted over a network is disclosed. The system comprises one or more network sensors detecting data strings while in transit on the network; and non-transitory memory comprising instructions. When the instructions are executed by one or more processors, the one or more processors establish a plurality of Bloom filters, receive a first data string, perform a first insertion operation into each Bloom filter; determine, for each of one or more Bloom filters, a set of bits, whether presently set or cleared, to be unset; and unset each determined set of bits in the one or more Bloom filters. At a later moment in time, the first data string is received again, and each Bloom filter is queried to determine whether the first data string has been inserted, based on a current state of that Bloom filter.

Abstract: A method is provided that includes identifying a plurality of data sets, each data set is associated with a distribution model and each data set is associated with an image having a first noise level. The method includes partitioning the data sets into a plurality of groups and generating a best representative estimate for each group, the estimate is associated with a second noise level that is less than the first noise level. The method further includes annotating each group and receiving an input data set. The method includes assigning the input data set to a group and annotating the input data set according to that group's annotation.

Abstract: An inhaler device (1) contains, or is capable of accepting, a plurality of doses of a medicament to be dispensed from the inhaler (1). To ameliorate the problem of double dosing from the inhaler (1), the device further comprises prevention means (26, 28, 40) for preventing, at least temporarily, the dispensing of a dose of medicament, and detection means (32) for detecting the inhalation of a previously dispensed dose of medicament. When the detection means (32) detects the inhalation of the previously dispensed dose of medicament, it releases the prevention means (26, 28, 40), allowing the device to dispense a further dose of medicament. The detection means (32) may be a pressure sensor, and the prevention means (26, 28, 40) may operate by causing a disengagement of an actuation mechanism.

Abstract: A method is provided that includes identifying a plurality of data sets, each data set is associated with a distribution model and each data set is associated with an image having a first noise level. The method includes partitioning the data sets into a plurality of groups and generating a best representative estimate for each group, the estimate is associated with a second noise level that is less than the first noise level. The method further includes annotating each group and receiving an input data set. The method includes assigning the input data set to a group and annotating the input data set according to that group's annotation.

Abstract: A method is provided that includes identifying a plurality of data sets, each data set is associated with a distribution model and each data set is associated with an image having a first noise level. The method includes partitioning the data sets into a plurality of groups and generating a best representative estimate for each group, the estimate is associated with a second noise level that is less than the first noise level. The method further includes annotating each group and receiving an input data set. The method includes assigning the input data set to a group and annotating the input data set according to that group's annotation.

Abstract: Various computer-implemented methods for classifying defects on a specimen are provided. One method includes assigning individual defects detected on the specimen to defect groups based on one or more characteristics of the individual defects. The method also includes displaying information about the defect groups to a user. In addition, the method includes allowing the user to assign a classification to each of the defect groups. Systems configured to classify defects on a specimen are also provided. One system includes program instructions executable on a processor for assigning individual defects detected on the specimen to defect groups based on one or more characteristics of the individual defects. The system also includes a user interface configured for displaying information about the defect groups to a user and allowing the user to assign a classification to each of the defect groups.

Abstract: A method is provided that includes identifying a plurality of data sets, each data set is associated with a distribution model and each data set is associated with an image having a first noise level. The method includes partitioning the data sets into a plurality of groups and generating a best representative estimate for each group, the estimate is associated with a second noise level that is less than the first noise level. The method further includes annotating each group and receiving an input data set. The method includes assigning the input data set to a group and annotating the input data set according to that group's annotation.

Abstract: An inhaler device (1) contains, or is capable of accepting, a plurality of doses of a medicament to be dispensed from the inhaler (1). To ameliorate the problem of double dosing from the inhaler (1), the device further comprises prevention means (26, 28, 40) for preventing, at least temporarily, the dispensing of a dose of medicament, and detection means (32) for detecting the inhalation of a previously dispensed dose of medicament. When the detection means (32) detects the inhalation of the previously dispensed dose of medicament, it releases the prevention means (26, 28, 40), allowing the device to dispense a further dose of medicament. The detection means (32) may be a pressure sensor, and the prevention means (26, 28, 40) may operate by causing a disengagement of an actuation mechanism.

Abstract: The present invention is an OCT imaging system user interface for efficiently providing relevant image displays to the user. These displays are used during image acquisition to align patients and verify acquisition image quality. During image analysis, these displays indicate positional relationships between displayed data images, automatically display suspicious analysis, automatically display diagnostic data, simultaneously display similar data from multiple visits, improve access to archived data, and provide other improvements for efficient data presentation of relevant information.

Abstract: A method and an apparatus automatically detect vessels in a diagnostic image. The method according to one embodiment accesses digital image data representing a diagnostic image; detects vessel candidates in the diagnostic image by processing the diagnostic image data, the step of detecting vessel candidates including identifying edge pixel pairs of vessels in a diagnostic image by iteratively adjusting a plurality of constraints relating to a general direction and shape of a vessel for a next iteration of edge pixel pair identification in a diagnostic image; and determines whether the plurality of edge pixel pairs form a vessel using learned features.

Abstract: Various computer-implemented methods for classifying defects on a specimen are provided. One method includes assigning individual defects detected on the specimen to defect groups based on one or more characteristics of the individual defects. The method also includes displaying information about the defect groups to a user. In addition, the method includes allowing the user to assign a classification to each of the defect groups. Systems configured to classify defects on a specimen are also provided. One system includes program instructions executable on a processor for assigning individual defects detected on the specimen to defect groups based on one or more characteristics of the individual defects. The system also includes a user interface configured for displaying information about the defect groups to a user and allowing the user to assign a classification to each of the defect groups.