Abstract: A system and method for anomaly interpretation and mitigation. A method includes extracting at least one input feature vector from observation data related to an observation; applying an isolation forest to the at least one input feature vector, wherein the isolation forest includes a plurality of estimators, wherein each estimator is a decision tree, wherein the output of each estimator is a split-path of a plurality of split-paths, each split-path having a path-length and including name and a corresponding value for a respective output feature of a plurality of output features; generating a mapping object based on the application of the isolation forest to the at least one feature vector, wherein the mapping object includes the plurality of split-paths; clipping the mapping object based on the path-length of each split-path; and determining at least one mitigation action based on the clipped mapping object.

Abstract: A system and method for anomaly detection. A method includes recursively partitioning a sample of device activity data including deterministic characteristics of a population of devices over iterations in order to create partitions. Each iteration includes determining a split density metric for a candidate subpopulation created by splitting a portion of the population with respect to a corresponding type of deterministic characteristic. The split density metric for the candidate subpopulation is determined based on a density value of the candidate subpopulation and a coverage value of the corresponding type of deterministic characteristic. The partitions include each candidate subpopulation meeting a split density metric threshold. A baseline for each of the partitions is established based on device activity for devices represented in device activity data of the partition. An anomaly is detected based on behavior of a device and the baseline established for a partition corresponding to the device.

Abstract: A mobile handset configured to estimate the radiation absorbed per mass of tissue of a user, and to perform an action in case the absorbed radiation exceeds a predefined threshold. The absorbed radiation may be estimated during a call. Additionally or alternatively, a prediction of the absorbed radiation level may be estimated and given to the user while the handset is not engaged in a call. various data items such as received power per time, estimated absorbed radiation and location may be transmitted to a server. A server application may use these data items to create regional maps of a cellular network coverage and quality by accumulating multiple inputs from a plurality of individual mobile handsets.

Abstract: A mobile handset configured to estimate the radiation absorbed per mass of tissue of a user, and to perform an action in case the absorbed radiation exceeds a predefined threshold. The absorbed radiation may be estimated during a call. Additionally or alternatively, a prediction of the absorbed radiation level may be estimated and given to the user while the handset is not engaged in a call. various data items such as received power per time, estimated absorbed radiation and location may be transmitted to a server. A server application may use these data items to create regional maps of a cellular network coverage and quality by accumulating multiple inputs from a plurality of individual mobile handsets.