Abstract: In some examples, an electronic device includes sensor circuitry and token circuitry. The sensor circuitry may capture sensor data and the contract token circuitry may generate a contract acceptance token including an acceptance indication and sensor data captured by the sensor circuitry. The token circuitry may send the contract acceptance token including the sensor data to a different electronic device.

Abstract: An environment awareness system includes a memory and first and second modules. The memory is configured to store environmental data, one or more music composition templates, and one or more maps, where the environmental data is indicative of at least one of a state, condition, or change in an environment in which the environment awareness system is located. The first module is configured to receive and store the environmental data in the memory. The second module is configured to: based on the one or more music composition templates and the one or more maps, convert the environmental data to a music signal including modifying variables in the one or more music composition templates based on the environmental data; and based on the music signal, play out a musical composition via an audio system to audibly indicate the at least one of the state, condition, or change in the environment.

Abstract: An environment awareness system includes a memory and first and second modules. The memory is configured to store environmental data, one or more music composition templates, and one or more maps, where the environmental data is indicative of at least one of a state, condition, or change in an environment in which the environment awareness system is located. The first module is configured to receive and store the environmental data in the memory. The second module is configured to: based on the one or more music composition templates and the one or more maps, convert the environmental data to a music signal including modifying variables in the one or more music composition templates based on the environmental data; and based on the music signal, play out a musical composition via an audio system to audibly indicate the at least one of the state, condition, or change in the environment.

Abstract: In some examples, image based target analysis may include performing a search to identify an image, and determining whether a target is present in the image, and image metadata. Image based target analysis may further include performing, in response to a determination that the target is present in the image, based on a relationship of the target to an entity, and the image metadata, a further search to identify another image, and generating, based on the image and/or the other image, a result indicative of further information on the target.

Abstract: In some examples, image based target analysis may include performing a search to identify an image, and determining whether a target is present in the image, and image metadata. Image based target analysis may further include performing, in response to a determination that the target is present in the image, based on a relationship of the target to an entity, and the image metadata, a further search to identify another image, and generating, based on the image and/or the other image, a result indicative of further information on the target.

Abstract: Example implementations relate to a traffic management system. For example, the traffic management system may receive data from a plurality of connected vehicles. The traffic management system may determine the relative positions of non-connected vehicle to the connected vehicles and may cluster connected vehicles and non-connected vehicles into a flock. The traffic management system may determine a flock traffic pattern and a nature of the flock traffic pattern, based on data received from the connected vehicles.

Abstract: In example implementations, an apparatus is provided. The apparatus includes an interface, an inheritance engine, an anomaly detection module and a processor. The interface communicates with a sensor array. The inheritance engine is used to create a model of the sensor array based on information collected from the each one of a plurality of nodes in the sensor array over the interface. The anomaly detection engine is used to monitor the sensor array in accordance with the model to detect an anomaly and initiate a corrective action to correct the anomaly in two or more of the plurality of nodes within the sensor array simultaneously. The processor is in communication with the inheritance engine and the anomaly detection engine is used to execute instructions associated with the inheritance engine and the anomaly detection engine.

Abstract: Examples associated with data validation are disclosed. One example includes a sensor attribute data store having information describing attributes of a set of distributed sensors. A pattern data store stores information describing patterns indicating anomalous sensor activity. A data aggregation module flags data received from a tested sensor as anomalous data when the anomalous data exceeds a variance level described by an attribute of the tested sensor. A data validation module validates the anomalous data by comparing the anomalous data to the patterns indicating anomalous sensor activity. A learning module updates the pattern indicating anomalous sensor activity based on a result received from the validation logic after the validation logic validates data received from the tested sensor.

Abstract: Systems, methods, and non-transitory computer readable media configured to receive a first media item from a search engine. One or more seed data items can be generated from the first media item. Further, a search query can be generated. The search query can include one or more of the seed data items. Subsequently, the search query can be provided to the search engine.

Abstract: In some examples, image based target analysis may include performing a search to identify an image, and determining whether a target is present in the image, and image metadata. Image based target analysis may further include performing, in response to a determination that the target is present in the image, based on a relationship of the target to an entity, and the image metadata, a further search to identify another image, and generating, based on the image and/or the other image, a result indicative of further information on the target.

Abstract: In example implementations, an apparatus is provided. The apparatus includes an interface, an inheritance engine, an anomaly detection module and a processor. The interface communicates with a sensor array. The inheritance engine is used to create a model of the sensor array based on information collected from the each one of a plurality of nodes in the sensor array over the interface. The anomaly detection engine is used to monitor the sensor array in accordance with the model to detect an anomaly and initiate a corrective action to correct the anomaly in two or more of the plurality of nodes within the sensor array simultaneously. The processor is in communication with the inheritance engine and the anomaly detection engine is used to execute instructions associated with the inheritance engine and the anomaly detection engine.

Abstract: Example implementations relate to a traffic management system. For example, the traffic management system may receive data from a plurality of connected vehicles. The traffic management system may determine the relative positions of non-connected vehicles to the connected vehicles and may cluster connected vehicles and non-connected vehicles into a flock. The traffic management system may determine a flock traffic pattern and a nature of the flock traffic pattern, based on data received from the connected vehicles.

Abstract: Examples associated with data validation are disclosed. One example includes a sensor attribute data store having information describing attributes of a set of distributed sensors. A pattern data store stores information describing patterns indicating anomalous sensor activity. A data aggregation module flags data received from a tested sensor as anomalous data when the anomalous data exceeds a variance level described by an attribute of the tested sensor. A data validation module validates the anomalous data by comparing the anomalous data to the patterns indicating anomalous sensor activity. A learning module updates the pattern indicating anomalous sensor activity based on a result received from the validation logic after the validation logic validates data received from the tested sensor.

Abstract: In some examples, an electronic device includes sensor circuitry and token circuitry. The sensor circuitry may capture sensor data and the contract token circuitry may generate a contract acceptance token including an acceptance indication and sensor data captured by the sensor circuitry. The token circuitry may send the contract acceptance token including the sensor data to a different electronic device.

Abstract: Embodiments of the present invention disclose a system and method of collision measurement for a vehicle. According to one embodiment, a plurality of photonic crystals configured to produce a color change state are distributed on an area of the vehicle. Furthermore, a location tag is also positioned on the vehicle for providing mapping data relating to the location of the photonic crystals along said vehicle. Upon receiving external crash impact, a measurement of force is computed based on the color change state of at least one photonic crystal caused by the crash impact.

Abstract: A method including receiving a plurality of roles in a data processing system and adding a part-time resource to at least one role. The method also includes determining, in the data processing system, if a project duration has changed as a result of adding the part-time resource, and if the project duration has changed, repeating the process at the adding step. The method also includes storing results corresponding to the resources assigned to roles. There is also a similar data processing system and machine-usable medium.

Abstract: Embodiments of the present invention disclose a method and system for providing train traffic advice. According to one embodiment, train status information associated with at least one train is received at a data center hosting a train traffic advisor application. Train crossing location data is stored in a database and retrieved by the train traffic advisor application. Based on the received train status information and the train crossing location data, train traffic information associated with the at least one train is calculated. Subscribing devices are identified by the train traffic advisor application, and the train traffic information is communicated to at least one of the identified subscribing devices.

Abstract: Embodiments of the present invention disclose a system and method of collision measurement for a vehicle. According to one embodiment, a plurality of photonic crystals configured to produce a color change state are distributed on an area of the vehicle. Furthermore, a location tag is also positioned on the vehicle for providing mapping data relating to the location of the photonic crystals along said vehicle. Upon receiving external crash impact, a measurement of force is computed based on the color change state of at least one photonic crystal caused by the crash impact.

Abstract: Embodiments of the present invention disclose a method and system for providing train traffic advice. According to one embodiment, train status information associated with at least one train is received at a data center hosting a train traffic advisor application. Train crossing location data is stored in a database and retrieved by the train traffic advisor application. Based on the received train status information and the train crossing location data, train traffic information associated with the at least one train is calculated. Subscribing devices are identified by the train traffic advisor application, and the train traffic information is communicated to at least one of the identified subscribing devices.

Abstract: A system, method, and computer program product for resource collaboration estimation (RCET). The method includes determining types of human resources to be used for a project. The method also includes calculating and storing an effort full time equivalent (FTE) according to the types of human resources. The method also includes calculating and storing a communication FTE according to the types of human resources. The method can also calculate the total effort of each team per phase based on additional communication overhead, and derive the total cost and duration based on the number of FTEs. A data processing system includes various means for performing corresponding steps, and a computer program product includes instructions for executing corresponding steps.