1201 results about "Black box" patented technology

A method for operating a sleep phase actigraphy synchronized alarm clock that communicates with a remote sleep database, such as an internet server database, and compares user physiological parameters, sleep settings, and actigraphy data with a large database that may include data collected from a large number of other users with similar physiological parameters, sleep settings, and actigraphy data. The remote server may use “black box” analysis approach by running supervised learning algorithms to analyze the database, producing sleep phase correction data which can be uploaded to the alarm clock, and be used by the alarm clock to further improve its REM sleep phase prediction accuracy.

A digital rights management (DRM) system operates on a computing device and requires a black box for performing decryption and encryption functions. To obtain the black box from a black box server, the DRM system requests such black box from such black box server. The black box server in response generates the black box, where such black box is unique and has a public/private key pair. The black box server then delivers the generated black box to the DRM system and the DRM system installs the delivered black box in such DRM system.

Disclosed are methods and apparatus for using black box data to analyze vehicular accidents. The methods include obtaining information from an event data recorder associated with a vehicle and using the data obtained therefrom in determining and analyzing the vehicular accident. Attributes to be analyzed include impact severity, change in velocity, and other desired parameters. Further disclosed are methods to securely communicate the downloaded black box information to a secure location for later analysis and processing.

Dynamical methods for obtaining the global optimal solution of general optimization problems having closed form or black box objective functions, including the steps of first finding, in a deterministic manner, one local optimal solution starting from an initial point, and then finding another local optimal solution starting from the previously found one until all the local optimal solutions starting from any initial point are found, and then finding from said points the global optimal solution.

An analytical software design system arranged to receive informal system design specifications and to convert them into verified design specifications for use in creating source code and carrying out implementation testing of the source code is described. The system comprises a verified black box specification generator arranged to process the received informal system design specifications to create formal specifications; to generate from the formal specifications mathematical models representing the system behaviour; to analyse the mathematical models to determine if they have the required behaviour; to adjust the formal specifications until the required behaviour is achieved; and to derive the required verified design specifications from the mathematical models.

A multi-model cooperative defense method facing deep learning antagonism attack comprises the following steps of: 1) performing unified modeling based on a gradient attack to provide a [Rho]-loss model; 2) according to design of a unified model, for an countering attack of a target model fpre(x), according to a generation result of a countering sample, classifying a basic expression form of an attack into two classes; 3) analyzing the parameters of the model, performing parameter optimization of the [Rho]-loss model and search step length optimization of a disturbance solution model for the countering sample; and 4) for the mystique of a black box attack, designing an experiment based on an adaboost concept, generating a plurality of different types of substitution models, used to achievethe same task, for integration, designing a multi-model cooperative defense method with high defense capability through an attack training generator of an integration model with high defense capability, and providing multi-model cooperative detection attack with weight optimal distribution. The multi-model cooperative defense method is high in safety and can effectively defense the attack of a deep learning model for the antagonism attack.

A vehicle black box includes a memory device for receiving and storing real-time data associated with the vehicle during a recording time window. Upon determining that an accident has occurred, circuitry freezes the recording time window and stores the real-time data within the frozen recording time window within a one-time programmable (OTP) memory.

A method and apparatus that utilize time-domain measurements of a nonlinear device produce or extract a behavioral model from embeddings of these measurements. The method of producing a behavioral model comprises applying an input signal to the nonlinear device, sampling the input signal to produce input data, measuring a response of the device to produce output data, creating an embedded data set, fitting a function to the embedded data set, and verifying the fitted function. The apparatus comprises a signal generator that produces an input signal that is applied to the nonlinear device, the device producing an output signal in response. The apparatus further comprises a data acquisition system that samples and digitizes the input and output signals and a signal processing computer that produces an embedded data set from the digitized signals, fits a function to the embedded data set, and verifies the fitted function.

A method and system identifies a cloud configuration for deploying a software application. A performance of a target application and workload is characterized. A set of benchmark applications is then deployed into at least one target cloud infrastructure. The target infrastructure is characterized using the set of benchmarking applications. The performance of the target application is represented with a set of bins each corresponding to a resource subsystem of a virtual machine and a performance score that is required to deploy the target application and meet the target performance. The bins are filled with performance values for selected target virtual machines. Using the filled bins, a set of virtual machines needed to satisfy the target cloud infrastructure is determined. A recommendation is provided for the set of virtual machines to use in deploying the software application.

A security and surveillance system for aircraft on the ground incorporates a plurality of strategically spaced sensors including video imaging generators, audio sensors, motion detectors, and fire and smoke detectors for monitoring critical components and critical areas of both the interior and the exterior of the a commercial transport such as an aircraft. The system is a comprehensive multi-media safety, tracking and/or surveillance system, which provides both visual and/or audio information as well as critical data such as location, direction, intrusion, fire and/or smoke detection and/or status of environmental conditions and/or asset systems status. The collected information is analyzed and prioritized according to type of event, location and nature of required response for automatically dispatching the proper response. The captured data and images are transmitted to a ground based security station for display on a monitor and may be recorded on a “black box” recorder as well as on a ground based recording system.

A security and surveillance system for aircraft on the ground incorporates a plurality of strategically spaced sensors including video imaging generators, audio sensors, motion detectors, and fire and smoke detectors for monitoring critical components and critical areas of both the interior and the exterior of the a commercial transport such as an aircraft. The captured data and images are transmitted to a ground based security station for display on a monitor and may be recorded on a “black box” recorder as well as on a ground based recording system. The multiple audio and image signals are multiplexed and sequenced utilizing split screen technology in order to minimize the recording and monitoring hardware required to process the images.

A framework to accurately and quickly verify the ownership of remotely-deployed deep learning models is provided without affecting model accuracy for normal input data. The approach involves generating a watermark, embedding the watermark in a local deep neural network (DNN) model by learning, namely, by training the local DNN model to learn the watermark and a predefined label associated therewith, and later performing a black-box verification against a remote service that is suspected of executing the DNN model without permission. The predefined label is distinct from a true label for a data item in training data for the model that does not include the watermark. Black-box verification includes simply issuing a query that includes a data item with the watermark, and then determining whether the query returns the predefined label.

A principled, probabilistic approach to meta-learning acts as a go-between for a ‘black-box’ image annotation system and its users. Inspired by inductive transfer, the approach harnesses available information, including the black-box model's performance, the image representations, and a semantic lexicon ontology. Being computationally ‘lightweight.’ the meta-learner efficiently re-trains over time, to improve and/or adapt to changes. The black-box annotation model is not required to be re-trained, allowing computationally intensive algorithms to be used. Both batch and online annotation settings are accommodated. A “tagging over time” approach produces progressively better annotation, significantly outperforming the black-box as well as the static form of the meta-learner, on real-world data.

An externally-mounted camera system for large commercial trucks. The video cameras are positioned around the outside of the vehicle and feed their video images to a control unit within a tamper-proof black box typically located within the truck's cab. The cameras are wide-angle 360 degree type cameras and only four cameras completely surrounding the truck. This system is designed to work with the Federal Motor Carrier Safety Administration and Accident Reporting regulations, standards, and protocols. The video feeds will be attached to accident reports and reviewed by the federal authorities who provide feedback in compiled statistics and enhanced safety regulations.