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公开(公告)号：US20190244124A1
公开(公告)日：2019-08-08
申请号：US16267360
申请日：2019-02-04
申请人： BioRealm LLC
摘要： A method for biomarker discovery for substance use disorders wherein high dimensional data containing a plurality of variables based on a sample size and a number of variables exceeding that sample size are applied to an ensemble of statistical learning models whereby biomarkers of a substance use disorder are identified.
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公开(公告)号：US20190244034A1
公开(公告)日：2019-08-08
申请号：US16266615
申请日：2019-02-04
发明人： Huayong Wang
CPC分类号： G06K9/00778 , G06F17/18 , G06K9/00248 , G06K9/00261 , G06K9/00315 , G06K9/00342
摘要： A method and device for processing video data is provided. According to some embodiments, the method includes: recognizing at least one of a face or a piece of clothing from video data representing a scene; when the recognized face does not match a preset face or the recognized clothing does not match preset clothing, determining a user corresponding to the recognized face or recognized clothing to be a customer, the preset face or preset clothing corresponding to a greeter in the scene; performing a detection of at least one of facial expression, movement, or voice of the greeter from the video data, to generate a detection result; and determining a service quality of the greeter based on the detection result, to generate an assessment result.
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公开(公告)号：US20190243937A1
公开(公告)日：2019-08-08
申请号：US16385420
申请日：2019-04-16
发明人： Eric Foreman , Ning Lu , Jeffrey Hemmett
CPC分类号： G06F17/5036 , G06F17/18 , G06F17/5045 , G06F2217/10
摘要： According to one embodiment, a method, computer system, and computer program product for creating a plurality of process parameters in a circuit design is provided. The present embodiment of the invention may include receiving one parasitic extraction per layer of a circuit is used to obtain a resistance base factor and a capacitance base factor. The embodiment may further include performing Monte Carlo simulations to determine distributions of capacitance and resistance for each metal layer of the circuit, and creating scalars that scale each of the resistance base factor and the capacitance base factor to a minimum and maximum process limit. Additionally, the embodiment may include defining at least one delay corner using the created scalars, and receiving the results of one or more timing analyses performed using the resistance base factor and the capacitance base factor, and the defined delay corner to determine a delay variability per layer.
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公开(公告)号：US20190242975A1
公开(公告)日：2019-08-08
申请号：US16118399
申请日：2018-08-30
申请人： KaiKuTek Inc.
发明人： Tsung-Ming TAI , Yun-Jie JHANG , Wen-Jyi HWANG , Chun-Hsuan KUO
CPC分类号： G06K9/6259 , G01S7/414 , G01S7/417 , G01S13/584 , G01S13/89 , G01S2007/356 , G06F3/017 , G06F9/5027 , G06F17/18 , G06K9/00335 , G06K9/6215 , G06K9/6256 , G06K9/6262 , G06K9/6267 , G06N3/08 , G06N20/00 , G06T7/20 , G06T2207/10028 , G06T2207/20056 , G06T2207/20081 , G06T2207/20084 , H03B21/02
摘要： A gesture recognition system executes a gesture recognition method which includes the following steps: receiving a sensing signal; selecting one of the sensing frames from the sensing signal; generating a sensing map by applying 2D FFT to the selected sensing frame; selecting a cell having a largest amplitude in the sensing map; calculating the velocity of the cell and setting the velocity of the selected sensing frame to be the velocity of the cell; labeling the selected sensing frame as a valid sensing frame if the velocity of the selected sensing frame exceeds a threshold value, otherwise labeling the selected sensing frame as an invalid sensing frame; using all of the sensing maps of the valid sensing frames in the sensing signal as the input data for the neural network of the gesture recognition system and accordingly performing gesture recognition and gesture event classification.
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公开(公告)号：US20190228312A1
公开(公告)日：2019-07-25
申请号：US15880339
申请日：2018-01-25
申请人： SparkCognition, Inc.
发明人： Sari Andoni , Kevin Gullikson
CPC分类号： G06N3/088 , G06F17/18 , G06K9/6218 , G06N3/0454 , G06N3/084 , G06N3/086
摘要： During training mode, first input data is provided to a first neural network to generate first output data indicating that the first input data is classified in a first cluster. The first input data includes at least one of a continuous feature or a categorical feature. Second input data is generated and provided to at least one second neural network to generate second output data. The at least one second neural network corresponds to a variational autoencoder. An aggregate loss corresponding to the second output data is determined, including at least one of evaluating a first loss function for the continuous feature or evaluating a second loss function for the categorical feature. Based on the aggregate loss, at least one parameter of at least one neural network is adjusted. During use mode, the neural networks are used to determine cluster identifications and anomaly likelihoods for received data samples.
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公开(公告)号：US20190220514A1
公开(公告)日：2019-07-18
申请号：US16363646
申请日：2019-03-25
发明人： Xu Xiang WANG
CPC分类号： G06F17/2715 , G06F17/18 , G06F17/27 , G06F17/277 , G06N3/08 , G06N20/00
摘要： A keyword extraction method is provided. The keyword extraction method is performed by at least one processor and includes: obtaining to-be-determined words of to-be-processed text; determining preceding words respectively corresponding to the to-be-determined words, where the preceding words are words appearing in the to-be-processed text and preceding the to-be-determined words; determining word sequences of the to-be-determined words according to orders in which the to-be-determined words and the preceding words respectively corresponding to the to-be-determined words appear in the to-be-processed text; inputting the word sequences of the to-be-determined words respectively into a trained cyclic neural network model; obtaining, from the trained cyclic neural network model, a probability that each of the to-be-determined words is a key word of the to-be-processed text; and determining keywords of the to-be-processed text according to the probability that each of the to-be-determined words is a keyword of the to-be-processed text and a preset threshold.
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公开(公告)号：US20190206575A1
公开(公告)日：2019-07-04
申请号：US15981036
申请日：2018-05-16
发明人： Andrew Batey , Owen Ingraham
CPC分类号： G16H70/20 , G06F16/353 , G06F17/18 , G06K9/6223 , G06K9/6262
摘要： Described herein are techniques and mechanisms for medical practice data analytics. According to various embodiments, a system may include a clinic information database, a clinic data cluster engine, and a clinic data analytics engine. The clinic information database may store clinic data characterizing each of a plurality of medical practice clinics. The clinic data cluster engine may determine a respective plurality of clinic clusters based on the clinic information for each of a plurality of clustering mechanisms. The clinic data analytics engine may evaluate the performance of each of the plurality of clustering mechanisms to produce a respective performance evaluation by determining a respective predicted outcome variable for each of the respective clustering mechanisms and each of the respective clinic clusters and comparing each of the respective predicted outcome variable with a respective observed outcome variable.
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公开(公告)号：US20190205360A1
公开(公告)日：2019-07-04
申请号：US16235387
申请日：2018-12-28
发明人： CHUNGMING CHEUNG , PALASH GOYAL , ARASH SABER TEHRANI , VIKTOR K. PRASANNA , LISA ANN BRENSKELLE
摘要： A computer-implemented method for prioritizing candidate objects on which to perform a physical process includes receiving a time series history of measurements from each of a plurality of candidate objects at a data processing framework. The method further includes reducing dimensionality of the time series history of measurements with a convolutional autoencoder to obtain latent features for each of the plurality of candidate objects. The method also includes applying a kernel regression model to the latent features to generate a predicted value of physical output for performing the physical process on each of the plurality of candidate objects. The method additionally includes generating a prioritization of the candidate objects based on the values of physical output. The method involves selecting fewer than all of the plurality of candidate objects on which to perform the physical process. The selected candidate objects are based on the prioritization.
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公开(公告)号：US20190205359A1
公开(公告)日：2019-07-04
申请号：US15862252
申请日：2018-01-04
申请人： Apple Inc.
CPC分类号： G06F17/17 , G06F3/0484 , G06F16/90344 , G06F17/18 , G06F17/246 , G06Q40/04
摘要： Embodiments are disclosed in which a process generates, receives, or both, via a graphical user interface (GUI) of a spreadsheet application, an evaluation statement. The evaluation statement includes a cell identifier, and the cell identifier specifies a modal reference cell that provides an indication of a modal attribute to be used in the evaluation statement. The indication of the modal attribute comprises a textual indicator related to the modal attribute, but has a format that is different than the modal attribute. The process evaluates the textual indicator to be used by the evaluation statement to determine a corresponding modal attribute and calculates a solution to the evaluation statement using the corresponding modal attribute as the modal attribute of the evaluation statement. The process displays the solution via the GUI.
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公开(公告)号：US20190204114A1
公开(公告)日：2019-07-04
申请号：US15862568
申请日：2018-01-04
发明人： Karl Berntorp , Stefano Di Cairano
IPC分类号： G01C25/00 , B60R16/023 , B60W40/105 , B60W40/109 , B62D15/02 , B60W40/114 , G01D18/00 , G01P21/00 , G01C21/20 , G01C23/00 , G06F17/50 , G06F17/18
CPC分类号： G01C25/00 , B60R16/0231 , B60W40/105 , B60W40/109 , B60W40/114 , B60W2520/10 , B60W2520/125 , B60W2520/14 , B60W2540/18 , B62D15/021 , G01C21/20 , G01C23/00 , G01D18/00 , G01P21/00 , G05D1/027 , G05D1/0891 , G06F17/18 , G06F17/5009 , G06F2217/16
摘要： A system for controlling a vehicle a sensor to sense measurements indicative of a state of the vehicle and a memory to store a motion model of the vehicle, a measurement model of the vehicle, and a mean and a variance of a probabilistic distribution of a state of calibration of the sensor. The motion model of the vehicle defines the motion of the vehicle from a previous state to a current state subject to disturbance caused by an uncertainty of the state of calibration of the sensor in the motion of the vehicle. The measurement model relates the measurements of the sensor to the state of the vehicle using the state of calibration of the sensor. The system includes a processor to update the probabilistic distribution of the state of calibration based on a function of the sampled states of calibration weighted with weights determined based on a difference between the state of calibration sampled on a feasible space defined by the probabilistic distribution and the corresponding state of calibration estimated based on the measurements using the motion and the measurements models. The system includes a controller to control the vehicle using the measurements of the sensor adapted using the updated probabilistic distribution of the state of calibration of the sensor.
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