Abstract: In one example implementation, a log analysis system can comprise an activity engine to monitor user activity of a computer system, a baseline engine to generate an expected baseline of a log, and an abnormality engine to compare the log to the expected baseline to identify an abnormality, compare the abnormality to a user activity volume based on a correlation between the user activity volume and the log activity, and classify the log.

Abstract: The present invention provides a method for identifying abnormalities in personal energy consumption/usage. The method comprising the steps of: generating personal dynamic forecast model of energy usage patterns in sub-hourly resolution for defined time periods, based on historical personal usage data considering environmental/weather condition (temp, humidity), wherein the dynamic model apply adaptive gradient boost iterative learning algorithm using predefined periodical features and determining abnormalities of actual energy usage in defined time period by comparing predictions of the forecast model, wherein the predictions are calculated by applying the generated forecast model with the actual environmental condition at the relevant time period and identifying delta between the actual usage and the predicted usage patterns which exceeds a predefined threshold for predefined duration.

Abstract: In one example implementation, a log analysis system can comprise an activity engine to monitor user activity of a computer system, a baseline engine to generate an expected baseline of a log, and an abnormality engine to compare the log to the expected baseline to identify an abnormality, compare the abnormality to a user activity volume based on a correlation between the user activity volume and the log activity, and classify the log.

Abstract: Identifying log messages can include identifying candidate log messages and calculating a score for each of the candidate log messages. Identifying log messages can include identifying a log message potentially related to an event from the candidate log messages.

Abstract: A set of mutually intercommunicating units each include a transmitter arrangement and a receiver responsive to a single encoded signal. Each transmitter arrangement produces any one of the encoded signals other than its own. Each unit is associated with an important or valuable item, such as keys, cellphone, wallet/purse and the like, which are liable to being misplaced. To find a misplaced unit, any other unit is procured, and its transmitter code associated with the missing unit is energized. The missing unit responds to the transmitted code by annunciating, allowing it to be located.