Abstract: A continuous anomaly detection service receives data stream and performs continuous anomaly detection on the incoming data streams. This continuous anomaly detection is performed based on anomaly detection definitions, which define a signal used for anomaly detection and an anomaly detection configuration. These anomaly detection definitions can be modified, such that continuous anomaly detection continues to be performed for the data stream and the signal, based on the new anomaly detection definition.

Abstract: Techniques are disclosed for anomaly detection based on a predicted value. A search query can be executed over a period of time to produce values for a key performance indicator (KPI), the search query defining the KPI and deriving a value indicative of the performance of a service at a point in time or during a period of time, the value derived from machine data pertaining to one or more entities that provide the service. A graphical user interface (GUI) enabling a user to indicate a sensitivity setting can be displayed. A user input indicating the sensitivity setting can be received via the GUI. Zero or more of the values as anomalies can be identified in consideration of the sensitivity setting indicated by the user input.

Abstract: A mobile phone may include an enclosure defining a front exterior surface of the mobile phone, a rear exterior surface of the mobile phone, and a side exterior surface of the mobile phone. The mobile phone may further include an audio output system configured to produce an audible alert in response to the mobile phone receiving an incoming call, a momentary ringer-control button positioned along a side exterior surface of the housing component, and a processing system configured to, in response to detecting an actuation of the momentary ringer-control button while a first ringer mode of the mobile phone is active, transition the mobile phone to a second ringer mode, and in response to detecting the actuation of the momentary ringer-control button while a second ringer mode of the mobile phone is active, transition the mobile phone to the first ringer mode.

Abstract: A continuous anomaly detection service receives data stream and performs continuous anomaly detection on the incoming data streams. This continuous anomaly detection is performed based on anomaly detection definitions, which define a signal used for anomaly detection and an anomaly detection configuration. These anomaly detection definitions can be modified, such that continuous anomaly detection continues to be performed for the data stream and the signal, based on the new anomaly detection definition.

Abstract: A portable electronic device includes a housing, a sensor array including a first camera module having a first field of view, a second camera module having a second field of view different from the first field of view, and a light source, and a rear cover formed from a glass material and defining a raised sensor array region positioned over the sensor array. The raised sensor array region defines a first hole extending through the rear cover and positioned proximate a first corner region of the raised sensor array region, and a second hole extending through the rear cover and positioned proximate a second corner region diagonal from the first corner region. The first camera module includes a first camera housing defining a recess at a corner of the first camera housing, and the second camera module includes a second camera housing extending into the recess.

Abstract: A portable electronic device may include a housing having a wall defining an opening in the housing and at least a portion of four side surfaces of the portable electronic device. The portable electronic device may further include a display at least partially within the housing, a front cover positioned in the opening in the housing and over the display, the front cover defining a front surface, a peripheral side surface extending from the front surface and at least partially surrounded by the wall of the housing, and a notch that, together with a portion of the wall of the housing, defines an acoustic port of the portable electronic device. The electronic device may further include an acoustic port cover positioned at least partially in the acoustic port and a speaker at least partially within the housing and configured to direct sound through the acoustic port cover.

Abstract: Techniques are disclosed for anomaly detection based on a predicted value. A search query can be executed over a period of time to produce values for a key performance indicator (KPI), the search query defining the KPI and deriving a value indicative of the performance of a service at a point in time or during a period of time, the value derived from machine data pertaining to one or more entities that provide the service. A graphical user interface (GUI) enabling a user to indicate a sensitivity setting can be displayed. A user input indicating the sensitivity setting can be received via the GUI. Zero or more of the values as anomalies can be identified in consideration of the sensitivity setting indicated by the user input.

Abstract: A facility for defining an event subtype using examples is described. The facility displays events identified among machine-generated data. The facility receives user input selecting a first subset of the events as examples of an event subtype. In response to receiving the user input, the facility displays a second subset of the events predicted to belong to the event subtype on the basis of the examples of the event subtype.

Abstract: An anomaly detection system includes a plurality of signals. Each of the signals is associated with an anomaly detection procedure that will be used to identify anomalies within the signal. Anomaly detection is performed by applying the anomaly detection procedure to a sequential set of data points of a signal. The signals are updated based on incoming data streams. The data streams are analyzed, and the sequential set of data points for each signal is updated based on data points extracted from the data streams.

Abstract: A display system includes a plurality of smart products arranged in a physical display setting in a retail store and being available for purchased by a customer, a display screen located behind the plurality of smart products, an input device and a controller coupled to the input device and to the display screen. The controller is configured to receive an indication from the input device to instruct digital media content to be displayed on the display screen. The digital media content includes a sequence of frames of digital images that describe information related to functional features of at least a first smart product and a second smart product on physical display in front of the display screen including the functional features of how the first smart product is interconnected to the second smart product so that the first smart product prompts the second smart product to perform a function.

Abstract: Techniques are disclosed for providing adaptive thresholding technology for Key Performance Indicators (KPIs) that are updated using training data. Adaptive thresholding technology may automatically assign new values or adjust existing values for one or more thresholds of one or more time policies. Assigning threshold values using adaptive thresholding may involve identifying training data (e.g., historical data, simulated data, or example data) for the time frames and analyzing the training data to identify variations within the data (e.g., patterns, distributions, trends). A threshold value may be determined based on the variations and may be assigned to one or more of the thresholds without additional user intervention.

Abstract: A facility for defining an event subtype using examples is described. The facility displays events identified among machine-generated data. The facility receives user input selecting a first subset of the events as examples of an event subtype. In response to receiving the user input, the facility displays a second subset of the events predicted to belong to the event subtype on the basis of the examples of the event subtype.

Abstract: A continuous anomaly detection service receives data stream and performs continuous anomaly detection on the incoming data streams. This continuous anomaly detection is performed based on anomaly detection definitions, which define a signal used for anomaly detection and an anomaly detection configuration. These anomaly detection definitions can be modified, such that continuous anomaly detection continues to be performed for the data stream and the signal, based on the new anomaly detection definition.

Abstract: Techniques are disclosed for anomaly detection. A search query can be executed over a period of time to produce values for a key performance indicator (KPI), the search query defining the KPI and deriving a value indicative of the performance of a service at a point in time or during a period of time, the value derived from machine data pertaining to one or more entities that provide the service. A graphical user interface (GUI) enabling a user to indicate a sensitivity setting can be displayed. A user input indicating the sensitivity setting can be received via the GUI. Zero or more of the values as anomalies can be identified in consideration of the sensitivity setting indicated by the user input. A GUI including information related to the values identified as anomalies can be caused to be displayed.

Abstract: A continuous anomaly detection service receives data stream and performs continuous anomaly detection on the incoming data streams. This continuous anomaly detection is performed based on anomaly detection definitions, which define a signal used for anomaly detection and an anomaly detection configuration. These anomaly detection definitions can be modified, such that continuous anomaly detection continues to be performed for the data stream and the signal, based on the new anomaly detection definition.

Abstract: Techniques are disclosed for providing a graphical user interface (GUI) for displaying and configuring adaptive or static thresholds for Key Performance Indicators (KPIs). The GUI may include one or more presentation schedules that may display threshold information associated with time policies. Each presentation schedule may include multiple time slots and span a portion of one or more time cycles. Some of the time slots may be associated with a specific time policy and may have a unifying appearance that distinguishes the time slots from timeslots associated with other time policies. The presentation schedules may arrange the time slots in a time grid arrangement (e.g., calendar grid view) or a graph arrangement with depictions (e.g., points, lines) that may illustrate KPI values and threshold markers that may illustrate the threshold values.

Abstract: A display system includes a plurality of smart products arranged in a physical display setting in a retail store and being available for purchased by a customer, a display screen located behind the plurality of smart products, an input device and a controller coupled to the input device and to the display screen. The controller is configured to receive an indication from the input device to instruct digital media content to be displayed on the display screen. The digital media content includes a sequence of frames of digital images that describe information related to functional features of at least a first smart product and a second smart product on physical display in front of the display screen including the functional features of how the first smart product is interconnected to the second smart product so that the first smart product prompts the second smart product to perform a function.

Abstract: A display system and method of displaying media content on a display screen includes a processor that receives from an input device an indication that one of a plurality of vignettes has been selected. The selected vignette is accessed from a data store. Each vignette includes digital media content. The digital media content is instructed by the processor to be played on a display screen located behind a plurality of smart products that are on display. Each smart product is positioned relative to the display screen at a set location. The digital media content includes a sequence of frames of digital images including frames that produce a halo of light behind a smart product being described in the frames.

Abstract: Techniques are disclosed for providing adaptive thresholding technology for Key Performance Indicators (KPIs) that are updated using training data. Adaptive thresholding technology may automatically assign new values or adjust existing values for one or more thresholds of one or more time policies. Assigning threshold values using adaptive thresholding may involve identifying training data (e.g., historical data, simulated data, or example data) for the time frames and analyzing the training data to identify variations within the data (e.g., patterns, distributions, trends). A threshold value may be determined based on the variations and may be assigned to one or more of the thresholds without additional user intervention.

Abstract: An anomaly detection system includes a plurality of signals. Each of the signals is associated with an anomaly detection procedure that will be used to identify anomalies within the signal. Anomaly detection is performed by applying the anomaly detection procedure to a sequential set of data points of a signal. The signals are updated based on incoming data streams. The data streams are analyzed, and the sequential set of data points for each signal is updated based on data points extracted from the data streams.