Abstract: Embodiments include systems for determining one or more properties of an object. In an embodiment, a system includes a gripping element, a light source, a probe element including an optical fiber, a spectrometer, and a processor. The gripping element is configured to grasp the object. The light source is configured to illuminate the object. The probe element is operatively coupled to the gripping element. The optical fiber is configured to transmit reflected light from the object. The spectrometer configured to: (i) receive the transmitted reflected light from the optical fiber and (ii) generate spectral data based on the received transmitted reflected light. The processor is configured to: (i) receive the generated spectral data from the spectrometer and (ii) determine one or more properties of the object based on the received generated spectral data.

Abstract: A system for automated construction of an artificial neural network architecture is provided. The system includes a set of interfaces and data links configured to receive and send signals, wherein the signals include datasets of training data, validation data and testing data, wherein the signals include a set of random number factors in multi-dimensional signals X, wherein part of the random number factors are associated with task labels Y to identify, and nuisance variations S. The system further includes a set of memory banks to store a set of reconfigurable deep neural network (DNN) blocks, hyperparameters, trainable variables, intermediate neuron signals, and temporary computation values including forward-pass signals and backward-pass gradients.

Abstract: Embodiments herein provide a non-invasive tracking system that accurately predicts the location of tumors, such as lung tumors, in real time, while allowing patients to breathe naturally. This is accomplished by using Electrical Impedance Tomography (EIT), in conjunction with spirometry, strain gauge and infrared sensors, and by using sophisticated patient-specific mathematical models that incorporate the dynamics of tumor motion. With the direction and speed of lung tumor movement successfully tracked, radiation may be effectively delivered to the lung tumor and not to the surrounding healthy tissue, thus increased radiation dosage may be directed to improving local tumor control without compromising functional parenchyma.

Abstract: Systems and methods are provided for controlling a multiple degree-of-freedom system. Plural stimuli are provided to a user, and steady state visual evoked response potential (SSVEP) signals are obtained from the user. The SSVEP signals are processed to generate a system command. Component commands are generated based on the system command, the plurality of components commands causing the multiple degree-of-freedom system to implement the system command.

Abstract: Methods and apparatus are provided for dividing an image into a plurality of image chips for presentation on a display. Potential objects of interest are detected within an image by detecting features therein that correspond to objects of interest. The image is uniformly divided into a plurality of preliminary image chips. Triage image chips are generated by automatically adjusting each preliminary image chip such that the potential objects of interest detected within each preliminary image chip are at least substantially centered in each preliminary image chip.

Abstract: Embodiments of the disclosed technology provide reliable and fast communication of a human through a direct brain interface which detects the intent of the user. An embodiment of the disclosed technology comprises a system and method in which least one sequence of a plurality of stimuli is presented to an individual (using appropriate sensory modalities), and the time course of at least one measurable response to the sequence(s) is used to select at least one stimulus from the sequence(s). In an embodiment, the sequence(s) may be dynamically altered based on previously selected stimuli and/or on estimated probability distributions over the stimuli. In an embodiment, such dynamic alteration may be based on predictive models of appropriate sequence generation mechanisms, such as an adaptive or static sequence model.

Abstract: Methods and apparatus are provided for dividing an image into a plurality of image chips for presentation on a display. Potential objects of interest are detected within an image by detecting features therein that correspond to objects of interest. The image is uniformly divided into a plurality of preliminary image chips. Triage image chips are generated by automatically adjusting each preliminary image chip such that the potential objects of interest detected within each preliminary image chip are at least substantially centered in each preliminary image chip.

Abstract: Embodiments herein provide a non-invasive tracking system that accurately predicts the location of tumors, such as lung tumors, in real time, while allowing patients to breathe naturally. This is accomplished by using Electrical Impedance Tomography (EIT), in conjunction with spirometry, strain gauge and infrared sensors, and by using sophisticated patient-specific mathematical models that incorporate the dynamics of tumor motion. With the direction and speed of lung tumor movement successfully tracked, radiation may be effectively delivered to the lung tumor and not to the surrounding healthy tissue, thus increased radiation dosage may be directed to improving local tumor control without compromising functional parenchyma.

Abstract: A system and method of efficiently and effectively triaging an image that may include one or more target entities are provided. The image is divided into a plurality of individual image chips that each have a determinable image complexity. The image complexity of each image chip is determined, and each image chip is successively displayed to a user for a presentation time period that, for each image chip, varies based on the determined image complexity of the image chip.

Abstract: A method of building a model for a physical plant in the presence of noise can include initializing the model of the physical plant, wherein the model is characterized by a parameter vector, estimating an output of the model, and computing a composite cost comprising a weighted average of an error between the estimated output from the model and an actual output of the physical plant, and a derivative of the error. The method further can include determining a step size and a model update direction. The model of the physical plant can be updated. The updating step can be dependent upon the step size. Another embodiment can include the steps of determining a Kalman gain and determining an error vector comprised of two entries weighted by a scalar parameter.

Abstract: An iterative method of equalizing an input signal received over a digital communication channel can include (a) using a kernel density estimate where different values of a kernel size are indicative of either a blind or a decision-directed equalization mode, (b) processing a received signal using a blind equalization mode, and (c) evaluating, on a block or sample basis, an error measure based on a distance among a distribution of an equalizer output and a constellation. The method also can include (d) updating the kernel size based upon the error measure thereby facilitating automatic switching between the blind and decision-directed equalization modes, where the kernel size is initially set to a value indicative of the blind equalization mode. The method additionally can include (e) selectively applying blind equalization or decision-directed equalization to the input signal according to the updated kernel size for subsequent iterations of steps (c)-(e).

Abstract: A method of building a model for a physical plant in the presence of noise can include initializing the model of the physical plant, wherein the model is characterized by a parameter vector, estimating an output of the model, and computing a composite cost comprising a weighted average of an error between the estimated output from the model and an actual output of the physical plant, and a derivative of the error. The method further can include determining a step size and a model update direction. The model of the physical plant can be updated. The updating step can be dependent upon the step size. Another embodiment can include the steps of determining a Kalman gain and determining an error vector comprised of two entries weighted by a scalar parameter.

Abstract: An iterative method of equalizing an input signal received over a digital communication channel can include (a) using a kernel density estimate where different values of a kernel size are indicative of either a blind or a decision-directed equalization mode, (b) processing a received signal using a blind equalization mode, and (c) evaluating, on a block or sample basis, an error measure based on a distance among a distribution of an equalizer output and a constellation. The method also can include (d) updating the kernel size based upon the error measure thereby facilitating automatic switching between the blind and decision-directed equalization modes, where the kernel size is initially set to a value indicative of the blind equalization mode. The method additionally can include (e) selectively applying blind equalization or decision-directed equalization to the input signal according to the updated kernel size for subsequent iterations of steps (c)-(e).