Abstract: Example embodiments of a system and method for providing a congestion measurement in a network are disclosed. In an example embodiment information is received at an information transfer rate, from a source network device. A sample of the information may be taken before the information is transmitted to a destination network device. In an example embodiment, a congestion measurement value is computed that corresponds to the sample and represented with at least two bits. A multi-bit indicator of the congestion measurement value is then transmitted to control the information transfer rate of information arriving in the future.

Abstract: Example embodiments of a system and method for providing a congestion measurement in a network are disclosed. In an example embodiment information is received at an information transfer rate, from a source network device. A sample of the information may be taken before the information is transmitted to a destination network device. In an example embodiment, a congestion measurement value is computed that corresponds to the sample and represented with at least two bits. A multi-bit indicator of the congestion measurement value is then transmitted to control the information transfer rate of information arriving in the future.

Abstract: The present invention is directed to a method for making a pneumatic tire having a foam noise damper, the pneumatic tire comprising two spaced inextensible beads; a ground contacting tread portion; a pair of individual sidewalls extending radially inward from the axial outer edges of said tread portion to join the respective beads, the axial outer edges of the tread portion defining a tread width; a supporting carcass for the tread portion and sidewalls; an innerliner disposed radially inward of the carcass, the innerliner having a innerliner surface facing an interior cavity of the tire; the method comprising the steps of: applying a silicone adhesive to the innerliner surface to form an adhesive prepared surface; applying a solid foam noise reducer to the adhesive prepared surface; and curing the adhesive.

Abstract: The present invention is directed to a method for making a tire having a foam noise damper, comprising the steps of: pressing a barrier layer onto an exposed virgin surface of a green tire innerliner to adhere the barrier layer to the virgin surface and thereby form a protected green innerliner; exposing the protected green innerliner to the release agent; curing the protected green innerliner; removing the barrier layer to reveal the virgin surface substantially free of the release agent; applying a foamable liquid to the virgin surface; and foaming the foamable liquid to form a foam noise damper secured to the virgin surface.

Abstract: Embodiments of the present invention are directed to methods and systems for determining unknowns in rating matrices. In one embodiment, a method comprises forming a rating matrix, where each matrix element corresponds to a known favorable user rating associated with an item or an unknown user rating associated with an item. The method includes determining a weight matrix configured to assign a weight value to each of the unknown matrix elements, and sampling the rating matrix to generate an ensemble of training matrices. Weighted maximum-margin matrix factorization is applied to each training matrix to obtain corresponding sub-rating matrix, the weights based on the weight matrix. The sub-rating matrices are combined to obtain an approximate rating matrix that can be used to recommend items to users based on the rank ordering of the corresponding matrix elements.

Abstract: Class-based bandwidth partitioning of a sequence of packets of varying packet classes is performed, such as, but not limited to determining whether or not to admit a packet to a queue based on a probability corresponding to a class of packets associated with the packet, with this probability being based on measured arrival traffic and a fair share based on the length of the queue. Data path processing is performed on each packet to determine whether to admit or drop the packet, and to record the measured received traffic. Control path processing is periodically performed to update these probabilities based on determined arrival rates and fair shares for each class of packets. In this manner, a relatively small amount of processing and resources are required to partition bandwidth for a scalable number of classes of packets.

Abstract: Media-aware and TCP-compatible bandwidth sharing may be provided. In various embodiments, a network node may periodically update a virtual congestion level for a transmission stream in a network. The transmission stream may comprise at least one video stream and at least one data stream. The network node may then calculate, based at least in part on the virtual congestion level, a random packet marking probability or a random packet drop probability. In turn, the network node may either drop or mark transmission packets according to the calculated marking and dropping probability. The network node may further calculate an optimal video transmission rate for the at least one video stream and adjust a video transmission rate for the at least one video stream accordingly. Rate-distortions parameters for the at least one video stream may influence the optimal video transmission rate calculation for the at least one video stream.

Abstract: A collaborative filtering method for evaluating a group of items to aid in predicting utility of items for a particular user comprises assigning an item value of either known or missing to each item of the group of items, and applying a modification scheme to the item values of the missing items to assign a confidence value to each of the item values of the missing items to thereby generate a group of modified item values. The group of items having modified item values and the group known items are evaluated to generate a prediction of utility of items for a particular user.

Abstract: The present invention is directed to a method for making a tire having a foam noise damper, comprising the steps of: pressing a barrier layer onto an exposed virgin surface of a green tire innerliner to adhere the barrier layer to the virgin surface and thereby form a protected green innerliner; curing the protected green innerliner; removing the barrier layer to reveal the virgin surface; and securing a foam noise damper to the virgin surface.

Abstract: The present invention is directed to a method for making a tire having a foam noise damper, comprising the steps of: disposing a foam noise damper onto a virgin surface of a green tire innerliner; disposing a barrier layer over the foam noise damper, the foam noise damper being located between the virgin surface of the green tire innerliner and the barrier layer; incorporating the green tire innerliner into a green tire; curing the green tire; and removing the barrier layer to reveal the foam noise damper.

Abstract: The present invention is directed to a method for making a tire having a foam noise damper, comprising the steps of: disposing a silicone rubber foam noise damper onto an exposed virgin surface of a green innerliner of a green tire; disposing a barrier layer over the silicone rubber foam noise damper, the silicone rubber foam noise damper being located between the virgin surface of the green tire innerliner and the barrier layer; curing the green tire; and removing the barrier layer to reveal the silicone rubber foam noise damper.

Abstract: For each first entity of a subset of a number of first entities, an expected improvement of a predictive performance of a collaborative filtering model if additional ratings of the first entity in relation to a plurality of second entities were obtained is estimated. Particular first entities from the subset of the first entities of which to obtain the additional ratings in relation to the second entities are selected based at least on the expected improvements that have been determined. The additional ratings of the particular first entities in relation to the second entities are obtained.

Abstract: The present invention provides improved methods and devices for managing network congestion. Preferred implementations of the invention allow congestion to be pushed from congestion points in the core of a network to reaction points, which may be edge devices, host devices or components thereof. Preferably, rate limiters shape individual flows of the reaction points that are causing congestion. Parameters of these rate limiters are preferably tuned based on feedback from congestion points, e.g., in the form of backward congestion notification (“BCN”) messages. In some implementations, such BCN messages include congestion change information and at least one instantaneous measure of congestion. The instantaneous measure(s) of congestion may be relative to a threshold of a particular queue and/or relative to a threshold of a buffer that includes a plurality of queues.

Abstract: In one embodiment, apparatus and methods for apparatus and methods for fair bandwidth allocation are disclosed. In one embodiment, a method includes (i) determining a drop probability for each of a plurality of classes of packets being dropped or admitted to a queue, wherein each drop probability is based on a weighted fair bandwidth allocation process that is performed with respect to the plurality of classes and a plurality of packet arrival rates and predefined weights for such classes; and (ii) dropping a particular packet or admitting such particular packet to the queue based on the drop probability for such particular packet's class, wherein such dropping or admitting operation is further based on one or more drop precedence factors that are also determined periodically for each class if such one or more drop precedence factors are selected for such each class.

Abstract: In an example embodiment, there is disclosed herein logic encoded in at least one tangible media for execution and when executed operable to receive a packet. The logic determines a client associated with the packet. The client associated with a service set, and the service set associated with a transmitter. The logic determines a drop probability for the selected client determines a current packet arrival rate for the selected client and determines whether to enqueue or drop the packet based on the drop probability for the selected client and the current packet arrival rate associated with the selected client. The drop probability is based on a packet arrival rate and virtual queue length for the, which is based on a packet arrival rate and virtual queue length for the service set that is based on a packet arrival rate and virtual queue length for the transmitter.

Abstract: The present invention provides improved methods and devices for managing network congestion. Preferred implementations of the invention allow congestion to be pushed from congestion points in the core of a network to reaction points, which may be edge devices, host devices or components thereof. Preferably, rate limiters shape individual flows of the reaction points that are causing congestion. Parameters of these rate limiters are preferably tuned based on feedback from congestion points, e.g., in the form of backward congestion notification (“BCN”) messages. In some implementations, such BCN messages include congestion change information and at least one instantaneous measure of congestion. The instantaneous measure(s) of congestion may be relative to a threshold of a particular queue and/or relative to a threshold of a buffer that includes a plurality of queues.

Abstract: Embodiments of the present invention are directed to methods and systems for determining unknowns in rating matrices. In one embodiment, a method comprises forming a rating matrix, where each matrix element corresponds to a known favorable user rating associated with an item or an unknown user rating associated with an item. The method includes determining a weight matrix configured to assign a weight value to each of the unknown matrix elements, and sampling the rating matrix to generate an ensemble of training matrices. Weighted maximum-margin matrix factorization is applied to each training matrix to obtain corresponding sub-rating matrix, the weights based on the weight matrix. The sub-rating matrices are combined to obtain an approximate rating matrix that can be used to recommend items to users based on the rank ordering of the corresponding matrix elements.

Abstract: A system and method for providing personalized recommendations are disclosed herein. A system includes a processor and a software system executed by the processor. The software system provides a recommendation for an item. The recommendation is based on a comparison of a low-rank approximation of a domain matrix to a user profile. The user profile is based, in part, on the low-rank approximation of the domain matrix.

Abstract: In one embodiment, apparatus and methods for apparatus and methods for fair bandwidth allocation are disclosed. In one embodiment, a method includes (i) determining a drop probability for each of a plurality of classes of packets being dropped or admitted to a queue, wherein each drop probability is based on a weighted fair bandwidth allocation process that is performed with respect to the plurality of classes and a plurality of packet arrival rates and predefined weights for such classes; and (ii) dropping a particular packet or admitting such particular packet to the queue based on the drop probability for such particular packet's class, wherein such dropping or admitting operation is further based on one or more drop precedence factors that are also determined periodically for each class if such one or more drop precedence factors are selected for such each class.

Abstract: There is described a system and computer-implemented method for providing a recommendation based on a sparse pattern of data. An exemplary method comprises determining a likelihood that an item for which no user preference data is available will be preferred. The exemplary method also comprises determining a likelihood that an item for which user preference data is available for users other than a particular user will be preferred based on the likelihood that the item for which no user preference data is available will be preferred. The exemplary method additionally comprises predicting that an item for which no user preference data relative to the particular user is available will be preferred if the likelihood that the particular user will prefer the item exceeds a certain level.