Abstract: Systems and methods which allow for the integration of occupancy detection with traditional leak detection systems to further enhance the detection of dangerous leaks and allow them to be responded to in a more effective manner. The occupancy system will typically be integrated with flow detection systems, however, water presence detectors can also be integrated in another embodiment.

Abstract: Systems and methods that can utilize the detection of human occupancy without fiducial elements to control an environmental, security, or other system within a structure. The systems and method can initiate communication to a human user directly, and can alter their operation based on human presence.

Abstract: Systems and methods that can utilize the detection of human occupancy without fiducial elements to control an environmental, security, or other system within a structure. The systems and method can initiate communication to a human user directly, and can alter their operation based on human presence.

Abstract: Systems and methods that can utilize the detection of human occupancy without fiducial elements to control an environmental, security, or other system within a structure. The systems and method can initiate communication to a human user directly, and can alter their operation based on human presence.

Abstract: In one embodiment, a sequence of input words is received. Each of the input words is encoded as an indicator vector, wherein a sequence of the indicator vectors captures features of the sequence of input words. The sequence of the indicator vectors is then mapped to a distribution of a contextual probability of a first output word in a sequence of output words. For each subsequent output word, the sequence of the indicator vectors is encoded with a context, wherein the context comprises a previously mapped contextual probability distribution of a fixed window of previous output words; and the encoded sequence of the indicator vectors and the context is mapped to the distribution of the contextual probability of the subsequent output word. Finally, a condensed summary is generated using a decoder by maximizing the contextual probability of each of the output words.

Abstract: In one embodiment, a sequence of input words is received. Each of the input words is encoded as an indicator vector, wherein a sequence of the indicator vectors captures features of the sequence of input words. The sequence of the indicator vectors is then mapped to a distribution of a contextual probability of a first output word in a sequence of output words. For each subsequent output word, the sequence of the indicator vectors is encoded with a context, wherein the context comprises a previously mapped contextual probability distribution of a fixed window of previous output words; and the encoded sequence of the indicator vectors and the context is mapped to the distribution of the contextual probability of the subsequent output word. Finally, a condensed summary is generated using a decoder by maximizing the contextual probability of each of the output words.

Abstract: Systems and methods that can utilize the detection of human occupancy without fiducial elements to control an environmental, security, or other system within a structure. The systems and method can initiate communication to a human user directly, and can alter their operation based on human presence.

Abstract: In one embodiment, a sequence of input words is received. Each of the input words is encoded as an indicator vector, wherein a sequence of the indicator vectors captures features of the sequence of input words. The sequence of the indicator vectors is then mapped to a distribution of a contextual probability of a first output word in a sequence of output words. For each subsequent output word, the sequence of the indicator vectors is encoded with a context, wherein the context comprises a previously mapped contextual probability distribution of a fixed window of previous output words; and the encoded sequence of the indicator vectors and the context is mapped to the distribution of the contextual probability of the subsequent output word. Finally, a condensed summary is generated using a decoder by maximizing the contextual probability of each of the output words.

Abstract: Applications in social networks support interaction between members through various types of channels such as notifications, newsfeed, and so forth. For each channel, applications are ranked based on their user affinity measures. User affinity is based on measuring positive and negative interactions by users as both senders and recipients of messages generated by applications. Metrics are computed for the different types of messages and interactions provided by applications. For each channel, an application receives user affinity score based on specific weighted combination of the metrics. Applications use channel resources to send messages to increase their user base. Given the large number of applications that are available, the extent to which applications are allowed to use channels is controlled, limiting their resource consumption. User affinity scores of applications calculated for a channel are used to decide the allocation of channel resources for an application.

Abstract: Systems and methods that can utilize the detection of human occupancy without fiducial elements to control an environmental, security, or other system within a structure. The systems and method can initiate communication to a human user directly, and can alter their operation based on human presence.

Abstract: Applications in social networks support interaction between members through various types of channels such as notifications, newsfeed, and so forth. For each channel, applications are ranked based on their user affinity measures. User affinity is based on measuring positive and negative interactions by users as both senders and recipients of messages generated by applications. Metrics are computed for the different types of messages and interactions provided by applications. For each channel, an application receives user affinity score based on specific weighted combination of the metrics. Applications use channel resources to send messages to increase their user base. Given the large number of applications that are available, the extent to which applications are allowed to use channels is controlled, limiting their resource consumption. User affinity scores of applications calculated for a channel are used to decide the allocation of channel resources for an application.

Abstract: Applications in social networks support interaction between members through various types of channels such as notifications, newsfeed, and so forth. For each channel, applications are ranked based on their user affinity measures. User affinity is based on measuring positive and negative interactions by users as both senders and recipients of messages generated by applications. Metrics are computed for the different types of messages and interactions provided by applications. For each channel, an application receives user affinity score based on specific weighted combination of the metrics. Applications use channel resources to send messages to increase their user base. Given the large number of applications that are available, the extent to which applications are allowed to use channels is controlled, limiting their resource consumption. User affinity scores of applications calculated for a channel are used to decide the allocation of channel resources for an application.

Abstract: Applications in social networks support interaction between members through various types of channels such as notifications, newsfeed, and so forth. For each channel, applications are ranked based on their user affinity measures. User affinity is based on measuring positive and negative interactions by users as both senders and recipients of messages generated by applications. Metrics are computed for the different types of messages and interactions provided by applications. For each channel, an application receives user affinity score based on specific weighted combination of the metrics. Applications use channel resources to send messages to increase their user base. Given the large number of applications that are available, the extent to which applications are allowed to use channels is controlled, limiting their resource consumption. User affinity scores of applications calculated for a channel are used to decide the allocation of channel resources for an application.

Abstract: Applications in social networks support interaction between members through various types of channels such as notifications, newsfeed, and so forth. For each channel, applications are ranked based on their user affinity measures. User affinity is based on measuring positive and negative interactions by users as both senders and recipients of messages generated by applications. Metrics are computed for the different types of messages and interactions provided by applications. For each channel, an application receives user affinity score based on specific weighted combination of the metrics. Applications use channel resources to send messages to increase their user base. Given the large number of applications that are available, the extent to which applications are allowed to use channels is controlled, limiting their resource consumption. User affinity scores of applications calculated for a channel are used to decide the allocation of channel resources for an application.

Abstract: Applications in social networks support interaction between members through various types of channels such as notifications, newsfeed, and so forth. For each channel, applications are ranked based on their user affinity measures. User affinity is based on measuring positive and negative interactions by users as both senders and recipients of messages generated by applications. Metrics are computed for the different types of messages and interactions provided by applications. For each channel, an application receives user affinity score based on specific weighted combination of the metrics. Applications use channel resources to send messages to increase their user base. Given the large number of applications that are available, the extent to which applications are allowed to use channels is controlled, limiting their resource consumption. User affinity scores of applications calculated for a channel are used to decide the allocation of channel resources for an application.

Abstract: Applications in social networks support interaction between members through various types of channels such as notifications, newsfeed, and so forth. For each channel, applications are ranked based on their user affinity measures. User affinity is based on measuring positive and negative interactions by users as both senders and recipients of messages generated by applications. Metrics are computed for the different types of messages and interactions provided by applications. For each channel, an application receives user affinity score based on specific weighted combination of the metrics. Applications use channel resources to send messages to increase their user base. Given the large number of applications that are available, the extent to which applications are allowed to use channels is controlled, limiting their resource consumption. User affinity scores of applications calculated for a channel are used to decide the allocation of channel resources for an application.

Abstract: Applications in social networks support interaction between members through various types of channels such as notifications, newsfeed, and so forth. For each channel, applications are ranked based on their user affinity measures. User affinity is based on measuring positive and negative interactions by users as both senders and recipients of messages generated by applications. Metrics are computed for the different types of messages and interactions provided by applications. For each channel, an application receives user affinity score based on specific weighted combination of the metrics. Applications use channel resources to send messages to increase their user base. Given the large number of applications that are available, the extent to which applications are allowed to use channels is controlled, limiting their resource consumption. User affinity scores of applications calculated for a channel are used to decide the allocation of channel resources for an application.

Abstract: Applications in social networks support interaction between members through various types of channels such as email, notifications, newsfeed, and so forth. For each channel, applications are ranked based on their user affinity measures. User affinity is based on measuring positive and negative interactions by users as both senders and recipients of messages generated by applications. Metrics are computed for the different types of messages and interactions provided by applications. For each channel, an application receives user affinity score based on specific weighted combination of the metrics. Applications use channel resources to send messages to increase their user base. Given the large number of applications that are available, the extent to which applications are allowed to use channels is controlled, limiting their resource consumption. User affinity scores of applications calculated for a channel are used to decide the allocation of the number of messages allowed for an application for a channel.

Abstract: The present invention relates to a self-service engine for implementation in a business management system for rendering a virtual host. The virtual host replaces a customer service representative usually employed in an enterprise, such as a retail outlet, hotel or the like, who assists a customer. The self-service engine determines responses to events based on a set of rules, and renders the response on output devices. The response might, for example, be rendered as an animated human with a voice output.