Abstract:
Embodiments of the present invention may provide the capability to identify a specific object being interacted with that may be cheaply and easily included in mass-produced objects. In an embodiment, a computer-implemented method for object identification may comprise receiving a signal produced by a physical interaction with an object to be identified, the signal produced by an identification structure coupled to the object during physical interaction with the object, processing the signal to form digital data identifying the object, and accessing a database using the digital data to retrieve additional information identifying or describing properties of the object identified.
Abstract:
Data storage management by determining, for leaf and summary storage spaces of a data storage space hierarchy having at least two leaf storage spaces descending from at least one summary storage space, an invariant leaf attribute value for each leaf attribute type, an invariant summary attribute value for each descending leaf attribute type as a sum of the invariant leaf attribute values of all leaves descending from the summary storage space, and for each leaf, a variable leaf attribute value for each leaf attribute type, and, for each summary storage space, a variable summary attribute value for each descending leaf attribute type, where for each summary storage space, and for each storage space immediately descending from the summary storage space, each variable leaf attribute value of the immediately descending storage space is expressed as a proportion of the variable summary attribute value for the same attribute type.
Abstract:
Providing a machine-generated explanation of an outcome of a process execution engine includes inputting into a complex event processing (CEP) engine at least one predetermined event pattern specification and a sequence of events, the sequence of events generated, at least in part, by a process execution engine executing a predetermined process in real time. Using the CEP engine, an enriched event log is generated based on the input. The enriched event log includes the sequence of events and additionally includes one or more situational events corresponding to one or more of the sequence of events. The one or more situational events are derived by the CEP engine based on the at least one predetermined event pattern specification. A hypothesis-oriented, situationally aware explanation for the outcome of the predetermined process is determined using an artificial intelligence (AI) explainability framework with input of the enriched event log.
Abstract:
A computer-implemented method, computerized apparatus and computer program product for supporting parallel user interaction with physical and modeled system. A computerized digital model representing a real world physical system is obtained. An indication of a physical component of the system being subject to engagement by a user is received. A model component corresponding to the physical component is automatically determined. An interaction of the user with the model component is controlled based on at least one of the model and data obtained through engagement with the physical component.
Abstract:
A computer-implemented method, computerized apparatus and computer program product for supporting parallel user interaction with physical and modeled system. A computerized digital model representing a real world physical system is obtained. An indication of a physical component of the system being subject to engagement by a user is received. A model component corresponding to the physical component is automatically determined. An interaction of the user with the model component is controlled based on at least one of the model and data obtained through engagement with the physical component.
Abstract:
A computer-implemented method, computerized apparatus and computer program product for activity recognition using adaptive window size segmentation of sensor data stream. A data stream generated by one or more sensors is obtained. A frequency analysis of the data in a first segment of the data stream is performed. A size of a second segment is determined based on the frequency analysis. Activity recognition is performed for the second segment by extracting one or more features of the data therein and applying a machine learning process on the extracted features to obtain a classification of the data into an activity class.
Abstract:
A method of determining a range between two devices, which can for instance be wireless devices, such as handheld devices. The method performs a double-sided two-way ranging protocol at the two devices. This protocol causes the two devices to transmit and receive signals, with a view to determining the range between the two devices, using a two-way ranging methods, where each of the signals is a composite tone generated as a composition of two waveforms that are timewise separated by a gap to form a bipolar waveform. The gap is a zero or low-amplitude signal, contrasting with the two waveforms. The particular pattern in the correlation footprint eases the determination of the time of flight. The method can be used to measure social distancing.
Abstract:
A method, apparatus and product for interaction context-based control of output volume level. The method comprising: obtaining a vocal input from a user, wherein the vocal input is part of an interaction between the user and the voice-based interaction agent; determining an interaction context of the interaction between the user and the voice-based interaction agent; determining an output volume level of the voice-based interaction agent based on the interaction context; and providing to the user an output of the voice-based interaction agent, wherein the output comprises a voice-based output having a volume level of the output volume level.
Abstract:
Embodiments of the present invention may provide the capability to detect complex events while providing improved detection and performance. In an embodiment of the present invention, a method for detecting an event may comprise receiving data representing measurement or detection of physical parameters, conditions, or actions, quantizing the received data and selecting a number of samples from the quantized data, generating a hidden Markov model representing events to be detected using initial model values based on ideal conditions, wherein a desired output is defined as a sequence of states, and wherein a number of states of the hidden Markov model is less than or equal to the number of samples of the quantized data, adjusting the quantized data and the initial model values to improve accuracy of the model, determining a state sequence of the hidden Markov model, and outputting an indication of a detected event.
Abstract:
A method, apparatus and product for interaction context-based control of output volume level. The method comprising: obtaining a vocal input from a user, wherein the vocal input is part of an interaction between the user and the voice-based interaction agent; determining an interaction context of the interaction between the user and the voice-based interaction agent; determining an output volume level of the voice-based interaction agent based on the interaction context; and providing to the user an output of the voice-based interaction agent, wherein the output comprises a voice-based output having a volume level of the output volume level.