Abstract: Systems and methods for distributed control and energy management of one or more communities of energy-consuming units may include aggregation of consumption data from units, and determining per-unit electricity consumption based thereon, including consumption of backup power provided by a community during periods of time of poor quality (brownouts) or blackouts of a utility. A system may calculate and assess to respective units per-unit costs for such backup power. A system may also issue a command or alert to units to carry out one or both of community electricity usage objectives and electricity quotas required by the utility, which may be determined through execution of rules.

Abstract: A fused image of the person's hand is accessed, the fused image having been generated using a segmented graylevel image and a segmented color image. The hand in the fused image is identified. One or more finger tips and one or more finger valleys in the fused image are identified. One or more fingers of the hand are segmented, based on the identified finger tips and finger valleys. The one or more fingers of the hand are labeled. One or more features for each finger of the hand are determined.

Abstract: A counterfeit detection system may include a memory storing a module comprising machine readable instructions to determine a X-identification (XID) associated with a product. The XID may include an unencrypted component and/or an encrypted component associated with a parameter associated with the product. The machine readable instructions may further include selecting one or more validation rules, from a plurality of validation rules, to select one or more validation techniques from a plurality of validation techniques used to determine an authenticity of the product. The machine readable instructions may further include using the one or more selected validation techniques to determine the authenticity of the product based on the XID associated with the product. The counterfeit detection system may include a processor to implement the module.

Abstract: A travel management system may include a client module to generate a request to update and/or search for data related to a trip. A database module may receive the request and communicate with a database. The database may include data organized in a trip data store table including unique keys respectively identifying trips. The database may further include index tables related to attributes of the trips and identified by the unique keys. The database module may obtain data related to the request from an index table corresponding to a unique key and forward a response to the client module.

Abstract: Multimodal biometric profiling may include receiving a cover image and a biometric template for a person. An indication of a security requirement related to biometric profiling for the person may be received. A threshold value may be determined based on the indicated security requirement. The threshold value may be used to limit a number of biometric template bits of the biometric template that are embedded in a predetermined bit position of a cover image pixel of the cover image based on cover image intensity associated with the predetermined bit position.

Abstract: A method for controlling a sensor may be performed by a mobile device including a processor and a memory. The method may include receiving raw data from the sensor, classifying the raw data into a context value, interpreting the context value into a higher-level context, receiving a predicted context based on the higher-level context, and controlling the sensor based on the predicted context. Controlling the sensor may include controlling a frequency at which raw data is received from the sensor, or an on/off state of the sensor. Control of the sensor may also be based on both the higher-level context and the predicted context.

Abstract: A method for adapting execution of an application on a mobile device may be performed by a mobile device including a processor and a memory. The method may include receiving an application context, a process context, and one other context. The method also includes analyzing at least one of the application context or the process context together with the one other context. The method also includes dynamically adapting execution of the application on the mobile device based on the analysis. Adapting execution of the application may include transferring processing related to the application to a backend server for processing.

Abstract: Biometric authentication technology, in which biometric data is maintained for a group of people. The biometric data includes sorted similarity scores, where each of the sorted similarity scores is computed to represent similarity between a corresponding biometric image and a reference image. A biometric verification system accesses a biometric image of at least a portion of a person, accesses the reference image, and computes a similarity score that represents similarity between the accessed biometric image and the reference image. The biometric verification system searches the sorted similarity scores included in the biometric data using the computed similarity score and outputs a result based on the searching.

Abstract: A transportation system may store a standard time of arrival table including standard time of arrivals for fixed stops and waypoints or geo-sections. Delay of a vehicle reaching a fixed stop is determined and may be used to determine an estimated time of arrival to a destination on the route. Delay may be determined in response to traversing the waypoints or geo-sections on the route, and the estimated time of arrival may be updated according to the delay at each waypoint or geo-section.

Abstract: Biometric matching technology, in which a watch list is managed, multiple images of a potential suspect are accessed, and parallel pre-processing of the multiple images is controlled. Based on the pre-processing, an image of the potential suspect to use in matching against the watch list is determined and the determined image is used to search sorted biometric data included in the watch list. A subset of persons from the watch list is identified based on the search and parallel analysis of the determined image of the potential suspect against detailed biometric data associated with the subset of persons in the watch list is controlled. Based on the parallel analysis, it is determined whether the potential suspect matches a person in the watch list and a result is outputted based on the determination.

Abstract: A method for controlling a sensor may be performed by a mobile device including a processor and a memory. The method may include receiving raw data from the sensor, classifying the raw data into a context value, interpreting the context value into a higher-level context, receiving a predicted context based on the higher-level context, and controlling the sensor based on the predicted context. Controlling the sensor may include controlling a frequency at which raw data is received from the sensor, or an on/off state of the sensor. Control of the sensor may also be based on both the higher-level context and the predicted context.

Abstract: Biometric matching technology, in which a watch list is managed, multiple images of a potential suspect are accessed, and parallel pre-processing of the multiple images is controlled. Based on the pre-processing, an image of the potential suspect to use in matching against the watch list is determined and the determined image is used to search sorted biometric data included in the watch list. A subset of persons from the watch list is identified based on the search and parallel analysis of the determined image of the potential suspect against detailed biometric data associated with the subset of persons in the watch list is controlled. Based on the parallel analysis, it is determined whether the potential suspect matches a person in the watch list and a result is outputted based on the determination.

Abstract: Biometric authentication technology, in which biometric data is maintained for a group of people. The biometric data includes sorted similarity scores, where each of the sorted similarity scores is computed to represent similarity between a corresponding biometric image and a reference image. A biometric verification system accesses a biometric image of at least a portion of a person, accesses the reference image, and computes a similarity score that represents similarity between the accessed biometric image and the reference image. The biometric verification system searches the sorted similarity scores included in the biometric data using the computed similarity score and outputs a result based on the searching.

Abstract: Biometric authentication technology, in which biometric data is maintained for a group of people. The biometric data includes sorted similarity scores, where each of the sorted similarity scores is computed to represent similarity between a corresponding biometric image and a reference image. A biometric verification system accesses a biometric image of at least a portion of a person, accesses the reference image, and computes a similarity score that represents similarity between the accessed biometric image and the reference image. The biometric verification system searches the sorted similarity scores included in the biometric data using the computed similarity score and outputs a result based on the searching.

Abstract: A transportation system may store a standard time of arrival table including standard time of arrivals for fixed stops and waypoints or geo-sections. Delay of a vehicle reaching a fixed stop is determined and may be used to determine an estimated time of arrival to a destination on the route. Delay may be determined in response to traversing the waypoints or geo-sections on the route, and the estimated time of arrival may be updated according to the delay at each waypoint or geo-section.

Abstract: Multimodal biometric profiling may include receiving a cover image and a biometric template for a person. An indication of a security requirement related to biometric profiling for the person may be received. A threshold value may be determined based on the indicated security requirement. The threshold value may be used to limit a number of biometric template bits of the biometric template that are embedded in a predetermined bit position of a cover image pixel of the cover image based on cover image intensity associated with the predetermined bit position.

Abstract: A method of preauthenticating a mobile node in advance of a switch from a current point of attachment (CPoA) to a next point of attachment (NPoA) is disclosed. One or more preauthentication requests are received at the CPoA. The one or more preauthentication requests include a proxy assignment from the mobile node. Each of the one or more preauthentication requests corresponds to one of one or more possible points of attachment (PPoAs). Using the CPoA, the mobile node is preauthenticated with the one or more PPoAs using a transitivity of trust between the mobile node, the CPoA, and one or more authentication servers.

Abstract: Biometric matching technology, in which a watch list is managed, multiple images of a potential suspect are accessed, and parallel pre-processing of the multiple images is controlled. Based on the pre-processing, an image of the potential suspect to use in matching against the watch list is determined and the determined image is used to search sorted biometric data included in the watch list. A subset of persons from the watch list is identified based on the search and parallel analysis of the determined image of the potential suspect against detailed biometric data associated with the subset of persons in the watch list is controlled. Based on the parallel analysis, it is determined whether the potential suspect matches a person in the watch list and a result is outputted based on the determination.

Abstract: The data vaporizer provides secure online distributed data storage services that securely store and retrieve data in a public distributed storage substrate such as public cloud. The data vaporizer vaporizes (e.g., fragmented into tiny chunks of configurable sizes) data and distributes the fragments to multiple storage nodes so that the data is not vulnerable to local disk failures, secures data so that even if some of the storage nodes are compromised, the data is undecipherable to the attacker, stores data across multiple cloud storage providers and/or parties using keys (e.g., tokens) provided by multiple parties (including the owners of the data) and maintains data confidentiality and integrity even where one or more data storage provider is compromised. The data vaporizer is configurable for different domain requirements including data privacy and anonymization requirements, encryption mechanisms, regulatory compliance of storage locations, and backup and recovery constraints.

Abstract: Intelligent application back stack management may include generating a first back stack for activities of an application that have been executed by a device that executes the application. The first back stack may include a back stack size limit. A further back stack may be generated for selected ones of the activities of the application if a total number of the activities of the application and further activities of the application exceeds the back stack size limit. The first back stack may be an in-memory back stack for the device that executes the application, and the further back stack may include an external on-device back stack for the device that executes the application and/or a Cloud storage based back stack. Intelligent application back stack management may further include regenerating an activity of the selected ones of the activities that is pulled from the further back stack.