Abstract: A monitoring device for detecting anomalies on the basis of sensor data determined over time is provided, including an input interface to receive a new sensor data point, an analysis unit to determine a minimum reachability distance for the new sensor data point with respect to a selection of adjacent training data points and to determine a minimum position for the new sensor data point in a reachability diagram, to insert the new sensor data point in the reachability diagram after the minimum position and before the training data point having a greater reachability distance than the determined minimum reachability distance, to assign the new sensor data point to a particular cluster and to assign a status as normal or abnormal, and an output interface to output the assignment determined for the new sensor data point the result of the anomaly detection.

Abstract: A plurality of event inputs, each corresponding to a unique occurrence of an event within a time period, are received by a processor from one or more event status reporting units is provided. The time period includes an ordered sequence of time slots. The event inputs are grouped into event clusters. Each event cluster corresponds to a unique time slot and includes the event inputs that occurred within the corresponding time slot. The event inputs within a given event cluster are temporally arranged for each of the event clusters. A total count of the event inputs within the given event cluster is determined. Finally, for each of the event clusters, a first representation of the total count and a second representation of the temporal distribution of events along with an indication of the corresponding time slot are displayed simultaneously and distinctly on a display unit.

Abstract: Event inputs, each belonging to one of predefined event categories, are received from event status reporting units. A time period, a time duration within which the event inputs were received, is segregated into an ordered sequence of time slots. Inputs are categorized according to the time slots and the event categories. Ranks, based on weights of unique event inputs, are assigned to each of the predefined event categories within each of the time slots. A count of symbols for each time slot is defined. Each symbol represents a unique predefined event category. The time slots and the defined count of symbols ordered according to the ranks of the respective predefined event categories represented by the symbols for each of the time slots are displayed. Each symbol includes an indication of the weight of unique event inputs categorized for the selected predefined event category and for the selected time slot.

Abstract: A plurality of event inputs, each corresponding to a unique occurrence of an event within a time period, are received by a processor from one or more event status reporting units is provided. The time period includes an ordered sequence of time slots. The event inputs are grouped into event clusters. Each event cluster corresponds to a unique time slot and includes the event inputs that occurred within the corresponding time slot. The event inputs within a given event cluster are temporally arranged for each of the event clusters. A total count of the event inputs within the given event cluster is determined. Finally, for each of the event clusters, a first representation of the total count and a second representation of the temporal distribution of events along with an indication of the corresponding time slot are displayed simultaneously and distinctly on a display unit.

Abstract: Processing geographical information includes storing geographical information including a map dataset and associated context dataset in a memory. A central window subset based on the map data set and the associated context dataset is extracted from the memory. A frame window subset based on an associated context dataset that is adjacent to the central window subset is extracted from the memory. The central window subset and the frame window subset are transferred to a graphics memory.

Abstract: Event inputs, each belonging to one of predefined event categories, are received from event status reporting units. A time period, a time duration within which the event inputs were received, is segregated into an ordered sequence of time slots. Inputs are categorized according to the time slots and the event categories. Ranks, based on weights of unique event inputs, are assigned to each of the predefined event categories within each of the time slots. A count of symbols for each time slot is defined. Each symbol represents a unique predefined event category. The time slots and the defined count of symbols ordered according to the ranks of the respective predefined event categories represented by the symbols for each of the time slots are displayed. Each symbol includes an indication of the weight of unique event inputs categorized for the selected predefined event category and for the selected time slot.

Abstract: Processing geographical information includes storing geographical information including a map dataset and associated context dataset in a memory. A central window subset based on the map data set and the associated context dataset is extracted from the memory. A frame window subset based on an associated context dataset that is adjacent to the central window subset is extracted from the memory. The central window subset and the frame window subset are transferred to a graphics memory.

Abstract: Representations of reviews regarding at least one offering of an enterprise are received, wherein the representations of the reviews contain attributes and opinion words. Distance associations between the attributes and the opinion words in the representations are determined according to a distance mapping strategy that uses distances between the attributes and the opinion words in a section. A visualization of the reviews is generated according to the determined associations.