2919results about How to "Add dimension" patented technology

Implants or systems of implants apply a selected force vector or a selected combination of force vectors within or across the left atrium, which allow mitral valve leaflets to better coapt. The implants or systems of implants make possible rapid deployment, facile endovascular delivery, and full intra-atrial retrievability. The implants or systems of implants also make use of strong fluoroscopic landmarks.

A method for fabricating light emitting diode (LEDs) comprises providing a plurality of LEDs on a substrate wafer, each of which has an n-type and p-type layer of Group-III nitride material formed on a SiC substrate with the n-type layer sandwiched between the substrate and p-type layer. A conductive carrier is provided having a lateral surface to hold the LEDs. The LEDs are flip-chip mounted on the lateral surface of the conductive carrier. The SiC substrate is removed from the LEDs such that the n-type layer is the top-most layer. A respective contact is deposited on the n-type layer of each of the LEDs and the carrier is separated into portions such that each of the LEDs is separated from the others, with each of the LEDs mounted to a respective portion of said carrier.

A method for displaying an interactive game having a pre-determined outcome (e.g. a game of finite poker) displays an initial hand of cards, receives a player-specified designation as to which cards are to be held and which are to be discarded, and then displays an intermediate hand generated in accordance with the player-specified designation. Then a final hand is shown, and in those cases where the player-specified designation (Hold/Discard) is inconsistent with a transition from the intermediate hand to the final hand, an entertaining display is shown, such as a sequence of alternative playing cards. In some cases, the initial hand is a winning hand according to a predetermined payout schedule, and the final hand is a winning hand with a higher payout than the initial hand according to the same payout schedule. The disclosed methods can be used with other games, including reel-type games.

The invention provides an unsupervised domain-adaptive brain tumor semantic segmentation method based on deep adversarial learning. The method comprises the steps of deep coding-decoding full-convolution network segmentation system model setup, domain discriminator network model setup, segmentation system pre-training and parameter optimization, adversarial training and target domain feature extractor parameter optimization and target domain MRI brain tumor automatic semantic segmentation. According to the method, high-level semantic features and low-level detailed features are utilized to jointly predict pixel tags by the adoption of a deep coding-decoding full-convolution network modeling segmentation system, a domain discriminator network is adopted to guide a segmentation model to learn domain-invariable features and a strong generalization segmentation function through adversarial learning, a data distribution difference between a source domain and a target domain is minimized indirectly, and a learned segmentation system has the same segmentation precision in the target domain as in the source domain. Therefore, the cross-domain generalization performance of the MRI brain tumor full-automatic semantic segmentation method is improved, and unsupervised cross-domain adaptive MRI brain tumor precise segmentation is realized.

In an image classification system (70), a plurality of generative models (30) correspond to a plurality of image classes. Each generative model embodies a merger of a general visual vocabulary and an image class-specific visual vocabulary. A gradient-based class similarity modeler (40) includes (i) a model fitting data extractor (46) that generates model fitting data of an image (72) respective to each generative model and (ii) a dimensionality enhancer (50) that computes a gradient-based vector representation of the model fitting data with respect to each generative model in a vector space defined by the generative model. An image classifier (76) classifies the image respective to the plurality of image classes based on the gradient-based vector representations of class similarity.

The present invention relates generally to fiber optic connectors and adapters, and more specifically to a simplified fiber optic adapter assembly and integrated shutter mechanism. In various embodiments, the simplified fiber optic adapter assembly includes a one-piece outer housing, a one or two-piece inner housing, and several different clip arrangements, reducing the number of parts associated with conventional fiber optic adapter assemblies and eliminating the need for ultrasonic welding or the like. In various embodiments, the integrated shutter mechanism includes one or more shutter doors that are opened internally via the motion required for connector installation.

A semiconductor product includes a first semiconductor chip that includes input/output circuitry enabling transfer of data from memory banks of the semiconductor product to an external electronic device and/or from an external electronic device to the memory banks of the semiconductor product. A number of second semiconductor chips are stacked on and electrically coupled to the first semiconductor chip. The second semiconductor chips are stacked on one another. Each second semiconductor chip of the plurality of second semiconductor chips comprises at least one of the memory banks of the semiconductor product. The memory banks of the second semiconductor chips are accessible by the input/output circuitry arranged on the first semiconductor chip.

A wall assembly includes at least two panel elements which are configured for contiguous placement adjacent to one another. Each of the panel elements defines a hollow internal passageway. The panels are configured to permit a contiguous placement whereby the respective passageways of the panels are brought into registration with one another. A connection element is positioned within one of the passageways. The connection element is accessible through a slot defined within the sidewall of the panel wherein the connection element resides. The connection element is slidable whereby it may be displaced partially into the second panel element. The connection element is thereafter actuatable whereby its lateral dimension is decreased to form a pressure fit union with the interior sidewalls of the two passageways. In its spatially decreased configuration, the connection element provides a means of interconnecting the two panel elements together.

A method and system is provided for a virtual game world in which multiple players may play a plurality of games. Each player has a persistent and dynamic virtual identity that is relevant to and affected by the player's activity in each of the games. The games provide the opportunity for the various players to interact with each other, regardless of the actual physical location of the respective players. Preferably, the games provide the opportunity for players to cheat, including conspiring to cheat among multiple players, and accuse other players of cheating. Cheating and accusation of cheating may have positive or negative consequences to the respective players. The games, which are located at specific locations in the virtual world, are preferably provided with location-specific information from corresponding locations in the real world.

A system and associated methods for performing spinal fusion, involving the use of a graft holder assembly, a locking assembly, and a pair of bone graft implants to simultaneously introduce the bone graft implants into a disc space to thereafter effect spinal fusion.

A voice controlled voice-messaging systems permits manipulation of voice messages over the telephone without the need for keypressed commands. Manipulation includes playback of messages, deletion of messages, saving messages, and sending a new message to a recipient from a user-defined list. Access to the messaging system is by spoken password. Voice input also allows the following functions: enrollment of a spoken password; granting or refusing user access to the system based on verification of the user speaking a password; recognition of spoken utterances of "yes" and "no" in response to prompts by the VMS; recognition of "stop" to interrupt and stop a voice message during playback; enrollment of a spoken personal directory of names of potential message recipients; and recognition of names in the spoken personal directory. The invention uses speaker verification, speaker-independent recognition (SIR) of "yes/no", speaker-independent recognition of "stop" during message playback, and speaker-dependent recognition (SDR) of a limited vocabulary of short phrases such as a list of message recipients' names.

The present invention enables execution of the processing using metadata such as content recommendation in consideration to cooccurrence relation among metadata. A matrix generating section generates a metadata matrix having N rows corresponding to N metadata (N: integral number of 1 or more) respectively and M columns corresponding to M metadata (M: integral number of 1 or more). A LSA computing section generated an approximated matrix of a metadata matrix by subjecting the metadata matrix to singular value decomposition. The metadata extracting section computes, for each of the N metadata, an index value such as a feature difference indicating importance of metadata corresponding to the metadata above, and extracts important metadata or unnecessary metadata from among the N metadata. The present invention may be applied to an information processing apparatus for content recommendation.

Method and apparatus are disclosed for distracting tissue and particularly spinal tissue. The device and method may include insertion of at least one elongated member and an augmenting member to form a structure between the tissues to be distraction, such that a dimensional aspect of the structure is augmented upon movement of the augmenting structure.

A computer-implemented method and system for keyword bidding are disclosed. A particular embodiment includes identifying a keyword searched by a buyer on a host site just prior to their purchase transaction; recording a host site category associated with the purchase transaction; correlating the keyword with the host site category; determining a revenue per click value associated with the keyword; obtaining bidding information associated with the keyword; and automatically generating a bid value for the keyword based on the revenue per click value, the bidding information, and the host site category.

The invention claims an electroencephalogram recognizing method combing a convolutional neural network (CNN) with a long and short time memory network (LSTM). The method comprises the following steps:firstly, acquiring electroencephalogram signal data by using an Emotive acquiring instrument, and carrying out pretreatment such as mean removal, filtering and normalization on the acquired electroencephalogram signals; secondly, inputting pretreated data into a convolution layer and a pooling layer to extract space features; and finally, directly connecting the rear of the pooling layer to LSTM,extracting temporal order information of electroencephalogram data, and finishing a classifying task through Dropout and a fully connected layer. The temporal and spatial features of electroencephalogram signals can be fully utilized, the space and temporal order information of the electroencephalogram data are extracted, thus, the classifying accuracy of the electroencephalogram signals is improved, and a new way is provided for research on electroencephalogram recognition.

The invention discloses a traveler home-work location identification and trip chain depicting method based on mobile phone signaling data, and belongs to the field of analysis of transportation planning data. The method comprises the steps of: triggering an information database by communication network records provided by a mobile network operator; after cleaning, integrating and calculating by using a position conversion algorithm, converting the data of the operator into a reference dataset; aiming at each user, converting the dataset into a mobile time-space trajectory, identifying stopover points, high frequency points and long time points in the mobile time-space trajectory, and on the basis, identifying home-work locations, activity target locations and insignificant stopover points; and finally depicting a closed trip chain of the user by being combined with the mobile time-space trajectory. The traveler home-work location identification and trip chain depicting method based on mobile phone signaling data has the advantages of being conductive to reducing trip survey costs of residents, obtaining more precision trip characteristics of crowds with different identities, and thereby allowing the traffic demand forecasting to be more accurate; and 2, being conductive to improving scientificity of planning layout construction, such as transport corridors, public transit networks and traffic facilities, in urban traffic planning.

A method for tracking pedestrians in a video sequence, where each image frame of the video sequence corresponds to a time step, includes using marginal space learning to sample a prior probability distribution p(x_t|Z^t−1) of multi-person identity assignments given a set of feature measurements from all previous image frames, using marginal space learning to estimate an observation likelihood distribution p(z_t|x_t) of the set of features given a set of multi-person identity assignments sampled from the prior probability distribution, calculating a posterior probability distribution p(x_t|Z^t) from the observation likelihood distribution p(z_t|x_t) and the prior probability distribution p(x_t|Z^t−1), and using marginal space learning to estimate the prior probability distribution p(x_t+1|Z^t) for a next image frame given the posterior probability distribution p(x_t|Z^t) and a probability p(x_t+1|x_t), where the posterior probability distribution of multi-person identity assignments corresponds to a set of pedestrian detection hypotheses for the video sequence.