Abstract: The processing of audio signals during playback is provided, so that audio signals that fall below a specified threshold loudness level are processed to avoid making unwanted background noise audible. N-channel audio is received from a playback volume controller/leveler (101). The level of the audio is compared with a threshold level. If the level is greater than the threshold level, the audio is processed with a first amount of gain in accordance with a first dynamic range control (DRC) compression curve that is tuned for professionally produced audio. If the level is less than or equal to the threshold level, the audio is processed with a second amount of gain in accordance with a second DRC compression curve that is designed to avoid boosting unwanted background noise. After applying the gain to the audio, the audio is sent to a downstream device.

Abstract: The present invention provides a process for treating a wort composition in a kettle, said method providing a significant energy saving compared to existing wort treatment processes. In particular, the process includes a hot-hold step for the wort, followed by gas sparging at elevated temperatures.

Abstract: The processing of audio signals during playback is provided, so that audio signals that fall below a specified threshold loudness level are processed to avoid making unwanted background noise audible. N-channel audio is received from a playback volume controller/leveler (101). The level of the audio is compared with a threshold level. If the level is greater than the threshold level, the audio is processed with a first amount of gain in accordance with a first dynamic range control (DRC) compression curve that is tuned for professionally produced audio. If the level is less than or equal to the threshold level, the audio is processed with a second amount of gain in accordance with a second DRC compression curve that is designed to avoid boosting unwanted background noise. After applying the gain to the audio, the audio is sent to a downstream device.

Abstract: A method for processing time series measurement data is provided. Data including a plurality of network performance metrics is received over a plurality of time periods. The received data is written to a plurality of measure data structures. The measure data structures are stored to a two dimensional array having a first dimension and a second dimension. The first dimension represents time and the second dimension represents a plurality of network entities. Elements of the two-dimensional array are compressed into BLOBs. Each one of the BLOBS is associated with a time period and a measure type associated with the data stored within a corresponding BLOB. The BLOBS are stored in a first table and second table. The first table is indexed by a combination of a network entity and a time period. The second table is indexed by a combination of a network performance metric and a network entity.

Abstract: A method for continuous data anomaly detection includes identifying a period of time covered by metrics data stored in a repository. The stored metrics data is categorized into a plurality of non-overlapping time segments. Statistical analysis of the stored metrics data is performed based on the identified period of time. A range of acceptable metric values is dynamically generated based on the performed statistical analysis.

Abstract: A method for continuous data anomaly detection includes identifying a period of time covered by metrics data stored in a repository. The stored metrics data is categorized into a plurality of non-overlapping time segments. Statistical analysis of the stored metrics data is performed based on the identified period of time. A range of acceptable metric values is dynamically generated based on the performed statistical analysis.

Abstract: A method for processing time series measurement data is provided. Data including a plurality of network performance metrics is received over a plurality of time periods. The received data is written to a plurality of measure data structures. The measure data structures are stored to a two dimensional array having a first dimension and a second dimension. The first dimension represents time and the second dimension represents a plurality of network entities. Elements of the two-dimensional array are compressed into BLOBs. Each one of the BLOBS is associated with a time period and a measure type associated with the data stored within a corresponding BLOB. The BLOBS are stored in a first table and second table. The first table is indexed by a combination of a network entity and a time period. The second table is indexed by a combination of a network performance metric and a network entity.

Abstract: A distributed network traffic flow monitoring system is provided. The system includes a plurality of network packet flow collector devices for receiving netflow packets associated with a traffic flow activity data at a network connection. The traffic flow activity data includes one or more transmissions between particular source and destination IP addresses. The system further includes a network packet flow coordinator device connected to the plurality of network packet flow collector devices and configured to aggregate probabilistic information related to the traffic flow activity data from the one or more of network packet flow collector devices and to estimate cardinality of the traffic flow activity data based on the aggregated probabilistic information.

Abstract: A storage system includes network monitoring device having NIC coupled to network and configured to capture raw data packets. The system further includes 4 data repositories. A first repository stores captured packets. A second repository stores captured packets' metadata. A third repository stores captured packets' and metadata's timestamp indexed data. A fourth repository stores captured packets' data flow. The storage system further includes a storage engine coupled to the repositories. The storage engine receives packet search criteria specifying at least a first time range. Data flow information associated with the search criteria is retrieved from the fourth repository. The retrieved data flow information is associated with a second, narrower, time range. Metadata information associated with the second time range is retrieved from the second repository using corresponding timestamp indexed data.

Abstract: A distributed network traffic flow monitoring system is provided. The system includes a plurality of network packet flow collector devices for receiving netflow packets associated with a traffic flow activity data at a network connection. The traffic flow activity data includes one or more transmissions between particular source and destination IP addresses. The system further includes a network packet flow coordinator device connected to the plurality of network packet flow collector devices and configured to aggregate probabilistic information related to the traffic flow activity data from the one or more of network packet flow collector devices and to estimate cardinality of the traffic flow activity data based on the aggregated probabilistic information.

Abstract: A storage system includes network monitoring device having NIC coupled to network and configured to capture raw data packets. The system further includes 4 data repositories. A first repository stores captured packets. A second repository stores captured packets' metadata. A third repository stores captured packets' and metadata's timestamp indexed data. A fourth repository stores captured packets' data flow. The storage system further includes a storage engine coupled to the repositories. The storage engine receives packet search criteria specifying at least a first time range. Data flow information associated with the search criteria is retrieved from the fourth repository. The retrieved data flow information is associated with a second, narrower, time range. Metadata information associated with the second time range is retrieved from the second repository using corresponding timestamp indexed data.

Abstract: A system and method are described for progressively efficiently filtering and gathering netflow data. Flow records are analyzed to find out which keys (addresses, conversations, protocols etc) meet defined filter parameters. The netflow data is processed and a data structure of fixed size is continually maintained in order to facilitate efficient retrieval of the gathered netflow data.

Abstract: A flow based detection system for detecting networks attacks on data networks. Flow records are collected in a novel data structure that facilitates efficient sorting. The sorted data structure can be subsequently analyzed in an efficient manner to find out if the network is under attack. An attack is identified if the numbers of unique corresponding addresses or conversations are too large.

Abstract: A system and method are described for progressively efficiently filtering and gathering netflow data. Flow records are analyzed to find out which keys (addresses, conversations, protocols etc) meet defined filter parameters. The netflow data is processed and a data structure of fixed size is continually maintained in order to facilitate efficient retrieval of the gathered netflow data.

Abstract: A flow based detection system for detecting networks attacks on data networks. Flow records are collected in a novel data structure that facilitates efficient sorting. The sorted data structure can be subsequently analyzed in an efficient manner to find out if the network is under attack. An attack is identified if the numbers of unique corresponding addresses or conversations are too large.

Abstract: A technique for identifying deviations in patterns of data traffic between host devices communicating over a network involves establishing a baseline traffic distribution by categorizing data traffic during a learning period. The baseline traffic distribution includes a list of categories and a metric value and a measure of variability of the metric value for each category in the list. An observed traffic distribution is generated by categorizing data traffic during an observation period. The observed traffic distribution includes a list of categories and a metric value associated with each category in the list. An alarm is generated in response to at least one of the metric values of the categories of the observed traffic distribution deviating significantly from the corresponding metric value in the baseline traffic distribution based on a pair-wise comparison of the observed metric values with respective thresholds established for corresponding categories of the baseline traffic distribution.

Abstract: A method, an apparatus, and a software product to process a plurality of input audio signals. The apparatus accepts a plurality of input signals and includes a multi-input, multi-output reverberator arranged to generate a set of output signals including delayed reverberation components simulating the reverberations a listener is likely to hear in a listening environment. The apparatus further includes a multi-input, two-output filter accepting the outputs of the reverberator and the plurality of input terminals, providing outputs for the left and right ears, and configured to implement a set of head related transfer functions corresponding to a listening environment and a set of directions of a listener in the listening environment.

Abstract: A technique for identifying deviations in patterns of data traffic between host devices communicating over a network involves establishing a baseline traffic distribution by categorizing data traffic during a learning period. The baseline traffic distribution includes a list of categories and a metric value and a measure of variability of the metric value for each category in the list. An observed traffic distribution is generated by categorizing data traffic during an observation period. The observed traffic distribution includes a list of categories and a metric value associated with each category in the list. An alarm is generated in response to at least one of the metric values of the categories of the observed traffic distribution deviating significantly from the corresponding metric value in the baseline traffic distribution based on a pair-wise comparison of the observed metric values with respective thresholds established for corresponding categories of the baseline traffic distribution.

Abstract: An apparatus for creating, utilizing a pair of oppositely opposed headphone speakers, the sensation of a sound source being spatially distant from the area between the pair of headphones, the apparatus comprising: (a) a series of audio inputs representing audio signals being projected from an idealised sound source located at a spatial location relative to the idealised listener; (b) a first mixing matrix means interconnected to the audio inputs and a series of feedback inputs for outputting a predetermined combination of the audio inputs as intermediate output signals; (c) a filter system of filtering the intermediate output signals and outputting filtered intermediate output signals and the series of feedback inputs, the filter system including separate filters for filtering the direct response and short time response and an approximation to the reverberant response, in addition to the feedback response filtering for producing the feedback inputs; and (d) a second matrix mixing means combining the filtered

Abstract: An apparatus for creating, utilizing a pair of oppositely opposed headphone speakers, the sensation of a sound source being spatially distant from the area between the pair of headphones, the apparatus comprising: (a) a series of audio inputs representing audio signals being projected from an idealised sound source located at a spatial location relative to the idealised listener; (b) a first mixing matrix means interconnected to the audio inputs and a series of feedback inputs for outputting a predetermined combination of the audio inputs as intermediate output signals; (c) a filter system of filtering the intermediate output signals and outputting filtered intermediate output signals and the series of feedback inputs, the filter system including separate filters for filtering the direct response and short time response and an approximation to the reverberant response, in addition to the feedback response filtering for producing the feedback inputs; and (d) a second matrix mixing means combining the filtered