Abstract: Concepts and technologies are disclosed herein for providing a network virtualization policy management system. An event relating to a service can be detected. A first policy that defines allocation of hardware resources to host the virtual network functions can be obtained, as can a second policy that defines deployment of the virtual network functions to the hardware resources. The hardware resources can be allocated based upon the first policy and the virtual network functions can be deployed to the hardware resources based upon the second policy.

Abstract: Systems and methods of rendering effects are described herein. A computing device can receive a user selection of an effect to be applied during gameplay of a computer game. The computing device can initiate a framework with which to apply the effect during the gameplay. The computing device can determine scenes during the gameplay to apply the effect through the framework. The computing device can determine graphical elements in the scenes that correspond to non-user interface elements through the framework. The computing system can apply the effect to the graphical elements through the framework.

Abstract: A computer-implemented method of anomaly detection associated with graphical data includes receiving as input one or more input data sets, wherein the input data sets includes one or more graphs, utilizing a plurality of graph neural networks (GNNs) to identify an aggregate loss including a first loss and second loss associated with the input data set, wherein the aggregate loss is associated with embedding's of the GNNs, and outputting a notification associated with an anomaly detection when the first and second loss exceeds an anomaly-detection threshold.

Abstract: A device control system includes a controller. The controller may be configured to, receive a data set of N samples that includes normal and unlabeled unidentified anomalous data samples, process, via a model, the data set to produce an anomaly score associated with each sample in the data set, rank the normal and anomalous data samples according to the anomaly score associated with each data sample to produce a ranked order, label a fraction ? of the N samples that have the highest scores with an anomaly label and the remaining samples with a normal label, retrain the model using all N samples, the labels, and a joint loss function, repeat the process, rank, label, and retrain steps until the ranked order and labels for all of the N samples do not change, and operate the device control system based on the trained model.

Abstract: A method of controlling a device includes receiving data from a first sensor, encoding, via parameters of an encoder, the data to obtain a latent observation (wt) for the data and an uncertainty vector (?wt) for the latent observation, processing the latent observation with a recurrent neural network to obtain a switching variable (st) which determines weights (?t) of a locally linear Kalman filter, processing the latent observation and the uncertainty vector with said locally linear Kalman filter to obtain updated mean of latent representation (?zt) and covariance of latent representation (?zt) of the Kalman filter, decoding the latent representation to obtain mean (?xt) and covariance of a reconstruction of the data (?xt) and outputting the reconstruction at a time t.

Abstract: A anomalous region detection method includes receiving time series data being grouped in patches, encoding, via parameters of an encoder, the data to obtain local latent representations, determining a representation loss from the local latent representations, transforming the local latent representations associated with each patch, via at least two local neural transformations, to a series of diverse transformed vector representations, determining a dynamic deterministic contrastive loss (DDCL) from the series of diverse transformed vector representations, combining the representation loss and the DDCL to obtain updated parameters, updating the parameters of the encoder with the updated parameters, scoring each of the series of the diverse transformed vector representations, via the DDCL, to obtain a diverse semantic requirement score associated with each patch, smoothing the diverse semantic requirement score to obtain a loss region, masking data associated with the loss region to obtain verified data, and o

Abstract: An optical transmitting apparatus is disclosed, in the apparatus, an array light source include M*N light sources, and an included angle between any column of light sources in the N columns of light sources and any row of light sources in the M rows of light sources is a preset angle. The array light source is located on a first side of a collimating lens, a plane on which the array light source is located is perpendicular to an optical axis of the collimating lens, and a distance between the plane on which the array light source is located and a center point of the collimating lens is a focal length of the collimating lens. An rotatable scanning mirror is located on a second side of the collimating lens, and a center point of a reflective surface of the scanning mirror is on the optical axis of the collimating lens.

Abstract: A computer-implemented method and system for training an anomaly detector to distinguish outlier data from inlier data on which the anomaly detector is trained. The anomaly detector comprises a set of learnable data transformations and a learnable feature extractor. The set of learnable data transformations and the learnable feature extractor are jointly trained based on a trained objective, which training objective comprises a function serving as anomaly scoring function which may also be used at test time to determine the anomaly score of test data samples. Evaluation results show that the anomaly detector is well-applicable to detect anomalies in non-image data, e.g., in data timeseries and in tabular data, and straightforward to apply at test time.

Abstract: A computer-implemented method for training a machine learning system. The method includes: providing at least one training data set that includes a number of numerical vectors; propagating numerical values of the at least one training data set by a parameterizable generic flow-based model, the parameterizable generic flow-based model including a concatenation of at least two parameterizable submodules, each submodule being one parameterizable function each; and learning the model parameter of the parameterizable generic flow-based model; parameterizations of each parameterizable submodule being learned successively in the flow direction and being fixed before parameterizations of the parameterizable submodule next in the flow direction are learned, and the learning being directed at output data of each submodule being distributed according to a predetermined probability distribution.

Abstract: A stealthy conductor that may be placed inside a fascicle in the peripheral nervous system (PNS) is described. The conductor is placed using a targeted-fascicle or targeted-axon approach to improve specificity and signal to noise ratio (SNR). The conductor is part of a targeted fascicular interface device and is placed using an insertion tool in a manner that reduces nerve damage as compared to conventional systems. The conductor is so small (e.g., <10 ?m diameter) and so flexible (e.g., approximates flexibility of surrounding neuronal material) that biological reactions (e.g., recruitment of macrophages, edema) to the presence of the conductor may be reduced. The targeted fascicular interface device has an insulated portion and a non-insulated portion that may act as an electrode. The insulated portion may include materials that promote healing at the entry/exit site and that adhere to the perineurium.

Abstract: The present invention relates to a massage apparatus. More particularly, the invention relates to a massage apparatus which maintains the applied force of a massage head. The apparatus has massage head that is attached to a movable block. The movable block can be repositioned to apply force to a subject. A force sensor constantly transmits applied force readings to a microprocessor which maintains the applied force by adjusting the position of the movable block relative the subject's body.

Abstract: A computer-implemented method for training a deep state space model using machine learning. The deep state space model includes a generative model and a multi-modal inference model. The generative model includes a transition model, and an emission model. The method includes: a) receiving a training data set comprising a sequence of observation vectors. For a plurality of observation vectors, the method iterates between b), c), and d) in sequence: b) inferring, using the multi-modal inference model, a current latent state of the generative model; c) constructing, using the multi-modal inference model, a posterior approximation of the current latent state as a mixture density network. For a plurality of observation vectors comprised in the sequence of observation vectors, d) decoding, using the emission model, the plurality of approximated latent state vectors to provide a plurality of synthetic observations; and e) outputting the trained deep state space model.

Abstract: A computer-implemented method for enabling control or monitoring of a computer-controlled entity operating in an environment by predicting a future state of the computer-controlled entity and/or its environment using sensor data which is indicative of a current state of the computer-controlled entity and/or its environment. The method includes using a first neural network for approximating a drift component of a stochastic differential equation and a second neural network for approximating a diffusion component of the stochastic differential equation, and discretizing the stochastic differential equation into time steps, and obtaining time-evolving mean and covariance functions based on the discretization and determining a probability distribution of a second state of the computer-controlled entity and/or its environment therefrom.

Abstract: The present invention relates to a massage apparatus. More particularly, the invention relates to a massage apparatus which maintains the applied force of a massage head. The apparatus has massage head that is attached to a movable block. The movable block can be repositioned to apply force to a subject. A force sensor constantly transmits applied force readings to a microprocessor which maintains the applied force by adjusting the position of the movable block relative the subject's body.

Abstract: A stealthy conductor that may be placed inside a fascicle in the peripheral nervous system (PNS) is described. The conductor is placed using a targeted-fascicle or targeted-axon approach to improve specificity and signal to noise ratio (SNR). The conductor is part of a targeted fascicular interface device and is placed using an insertion tool in a manner that reduces nerve damage as compared to conventional systems. The conductor is so small (e.g., <10 ?m diameter) and so flexible (e.g., approximates flexibility of surrounding neuronal material) that biological reactions (e.g., recruitment of macrophages, edema) to the presence of the conductor may be reduced. The targeted fascicular interface device has an insulated portion and a non-insulated portion that may act as an electrode. The insulated portion may include materials that promote healing at the entry/exit site and that adhere to the perineurium.

Abstract: An on-chip optical interconnection structure and network, where the on-chip optical interconnection structure includes M levels of optical switches, and mth-level optical switches in the M levels of optical switching devices include 2m-1 optical switches. Each optical switch in (i-1)th-level optical switches in the M levels of optical switches is coupled to two optical switches in ith-level optical switches. Two optical switches in the ith-level optical switches coupled to a same optical switch in the (i-1)th-level optical switches are coupled. The on-chip optical interconnection network is divided into levels, and switches coupled in a grid manner are formed such that hierarchical switching may be performed, and conflicts and delays in communication are reduced.

Abstract: An on-chip optical interconnection structure and network, where the on-chip optical interconnection structure includes M levels of optical switches, and mth-level optical switches in the M levels of optical switching devices include 2m-1 optical switches. Each optical switch in (i-1)th-level optical switches in the M levels of optical switches is coupled to two optical switches in ith-level optical switches. Two optical switches in the ith-level optical switches coupled to a same optical switch in the (i-1)th-level optical switches are coupled. The on-chip optical interconnection network is divided into levels, and switches coupled in a grid manner are formed such that hierarchical switching may be performed, and conflicts and delays in communication are reduced.

Abstract: A wavelength routing device is disclosed, wherein the device includes: a primary circuit, and a secondary circuit, where the primary circuit includes N 2×2 wavelength switches, the secondary circuit includes two N×N wavelength routers, and each N×N wavelength router includes at least one 2×2 wavelength switch, where a value of N is 2n, n being a positive integer; and an input port of each 2×2 wavelength switch in the primary circuit is connected to an input stage, an output port of each 2×2 wavelength switch is connected to an input port of an N×N wavelength router of the secondary circuit, and an output port of the N×N wavelength router of the secondary circuit is connected to an output stage.

Abstract: A stealthy conductor that may be placed inside a fascicle in the peripheral nervous system (PNS) is described. The conductor is placed using a targeted-fascicle or targeted-axon approach to improve specificity and signal to noise ratio (SNR). The conductor is part of a targeted fascicular interface device and is placed using an insertion tool in a manner that reduces nerve damage as compared to conventional systems. The conductor is so small (e.g., <10 ?m diameter) and so flexible (e.g., approximates flexibility of surrounding neuronal material) that biological reactions (e.g., recruitment of macrophages, edema) to the presence of the conductor may be reduced. The targeted fascicular interface device has an insulated portion and a non-insulated portion that may act as an electrode. The insulated portion may include materials that promote healing at the entry/exit site and that adhere to the perineurium.