Abstract:
Radiation doses are optimized by providing a model of the set of beams and a target dose in normalized forms. A Gram matrix is determined from the model. The target dose is subsampled to determine initial intensity values for the set of beams. Then, the following steps are iterated until convergence. A very small positive value, 0
Abstract:
A method determines an optimal route to deliver a packet from a source node via relay nodes to a destination node in a network. A graph of nodes connected by edges represents possible routes in the network. A probability that the packet arrives at the destination before a deadline time is assigned to each edge. A minimal delay route is selected from the possible routes, and an arrival time for delivering the packet using the minimal delay route is determined. The arrival time is comparing to a deadline time, and the probabilities are scaled accordingly until the minimal delay route is an optimal route.
Abstract:
A battery pack is provided for a mobile communication device, comprising a casing defining a cavity that conforms, at least partially, to the outer shape of the mobile communication device and one or more rechargeable power cells housed within the thickness of the casing. An internal interface engages a corresponding interface on the mobile communication device to provide power from the one or more rechargeable cells to the mobile communication device. An external interface is electrically coupled to the internal interface in order to transmit signals from the mobile communication device to an external device and may further serve to recharge the one or more rechargeable power cells. The battery pack may also serve as an extendible platform by providing additional integrated communication interfaces and/or processors that can be utilized by the mobile communication device to extend its communication and/or processing capabilities.
Abstract:
A method determines an optimal route to deliver a packet from a source node via relay nodes to a destination node in a network. A graph of nodes connected by edges represents possible routes in the network. A probability that the packet arrives at the destination before a deadline time is assigned to each edge. A minimal delay route is selected from the possible routes, and an arrival time for delivering the packet using the minimal delay route is determined. The arrival time is comparing to a deadline time, and the probabilities are scaled accordingly until the minimal delay route is an optimal route.
Abstract:
A model of a class of objects is selected from a set of low-dimensional models of the class, wherein the models are graphs, each graph including a plurality of vertices representing objects in the class and edges connecting the vertices. First distances between a subset of high-dimensional samples of the objects in the class are measured. The first distances are combined with the set of low-dimensional models of the class to produce a subset of models constrained by the first distances and a particular model having vertices that are maximally dispersed is selected from the subset of models.
Abstract:
A particular model of a class of objects is selected from a set of models of the class, wherein the class models are graphs, each graph including a plurality of vertices representing objects in the class and edges connecting the vertices. Subsets of vertices of a selected set of graphs representing the class of objects are grouped to produce a subgraph. A set of anchor vertices is selected from the subgraph. Subgraph parameterizations are determined for the set of anchor vertices of the subgraph and the subgraph parameterizations are combined with the set of class models to identify a particular class model.
Abstract:
A collaborative filtering method first converts a relational database to a graph of nodes connected by edges. The relational database includes consumer attributes, product attributes, and product ratings. Statistics of a Markov chain random walk on the graph are determined. Then, in response to a query state, states of the Markov chain are determined according to the statistics to make a recommendation.
Abstract:
A method represents a class of objects. A set of samples for the objects in the class is acquired, there being one sample for each object, and each sample includes a plurality of data values representing characteristics of the object. The samples are grouped into subsets such that each subset intersects at least one other subset. For each subset, a low-dimensional parameterization is determined. Nullspaces of the low-dimensional parameterizations are averaged to obtain a matrix whose nullspace contains a low-dimensional representation of the class of objects.