105results about How to "Predict in advance" patented technology

Methods and systems utilizing the data provided by a non-contrast-enhanced CAC scan that is left unused by the “whole-heart” Agatston or volume scores. Agatston and volume scores summarize overall coronary calcium burden, but do not show the number of vessels involved, the geographic distribution of the lesions, the size and shape of the individual lesions and the distance of the lesions from the coronary ostium. The methods and systems described herein extract and use the enhanced information provided by 3-D CAC scan data and significantly increases its clinical predictive value by providing vessel and lesion specific CAC scores which are superior to the whole-heart Agatston and volume scores in predicting obstructive Coronary artery disease (CAD).

A method and apparatus for video intraprediction encoding and decoding are provided. The encoding method includes dividing an input block into at least first and second areas; performing intraprediction-encoding on pixels of the first area; reconstructing the intraprediction-encoded pixels; and predicting pixels of the second area using the intraprediction-encoded pixels of the first area according to a prediction mode of a plurality of prediction modes. The decoding method includes receiving a bitstream comprising data for pixels of a first area and direction information; determining an intraprediction mode for a current block; performing intraprediction-decoding on pixels of the first area; and predicting the pixels of a second area using the received direction information and the intraprediction-decoded pixels for the first area.

Described herein are apparatus and methods for enhancing perceived visual quality of video which has been coded using enhanced intra predictive coding referred to as boundary adaptive intra predictions (BAIP). BAIP is performed in response to the type of prediction, and the smoothness of the boundary between a current block and its neighboring pixels which have already been coded. Intra prediction is performed separately for each pixel along the left side and/or top side within a current block, which takes into account the pixel itself and multiple pixels along the left and/or top border of that current block. The BAIP technique can be applied for different block sizes, including 4×4, 8×8, and 16×16, and includes vertical, horizontal, and DC intra predictions.

A moving picture coding method according to the present invention is a moving picture coding method for coding a moving picture which includes pictures, the method including: partitioning a picture into blocks each of which includes pixels; selecting a scanning scheme from among plural scanning schemes; scanning the blocks according to the selected scanning scheme; and coding the blocks in an order in which the blocks are scanned. In doing so, in the partitioning, the picture is partitioned into rows and columns of macroblocks each of which is partitioned into the blocks. The plural scanning schemes include a first scanning scheme for scanning the blocks in the macroblock per row of blocks.

A picture encoder for encoding picture signals of a lower hierarchy representing pre-set picture signals and picture signals of an upper hierarchy similarly representing pre-set picture signals. The picture encoder includes a first encoding unit for encoding the picture signals of the lower hierarchy using reference picture signals for outputting first pre-set encoded data, a second encoding unit for encoding the picture signals of the upper hierarchy using reference picture signals for outputting second pre-set encoded data, a first decoding unit for decoding the first encoded data for generating first reference picture signals and a second decoding unit for decoding the second encoded data for generating second reference picture signals. The second encoding unit encodes the picture signals using third reference picture signals generated on adaptively switching between the first reference picture signals and the second reference picture signals on the pixel basis.

An intelligent IVR system identifies a customer based on previous customer interactions. Customer intent is predicted for an ongoing interaction and personalized services are proactively offered to the customer. A self-optimizing algorithm improves intent prediction, customer identity, and customer willingness to engage and use IVR.

Systems and methods for identifying, assembling, and transmitting content are described in the illustrative context of electronic program guides and program channels. Data is received over a network from a first user terminal that enables identification of the first user. Program information for a digital program is accessed. A determination is made as to how many interstitials are to be presented during a playback of the digital program. A prediction model is selected and executed to generate predictions of user responses to one or more placements of program interstitials. The user response predictions are used to determine positioning of interstitials with respect to the program. The interstitials are enabled to be displayed on the first user terminal in accordance with the determined positioning.

A method, apparatus and computer program product are provided to predict faults. Initially, a plurality of features are provided to a plurality of models. A subset of features is selected for each model. The plurality of features selected by a respective model is dependent upon a time scale associated with a respective model. As a result of their dependence upon different time scales, the plurality of selected features provided to a first model will differ from those provided to a second model. The plurality of models process the respective plurality of selected features. The outputs from the plurality of models are fused to generate a measure indicative of an impending fault. By providing different selected features to the models that are dependent upon the associated time scales and by then combining the outputs of the plurality of models, the resulting measure of an impending fault may accurately predict a fault well in advance of its occurrence.

A method for encoding/decoding a motion vector and an apparatus thereof are disclosed. The method includes defining a candidate motion vector set with respect to a current motion vector; selecting a predicted motion vector from the candidate motion vector set; determining a predictability of the predicted motion vector in a decoding apparatus; encoding the current motion vector by using a motion vector prediction mode for indicating the predicted motion vector and the predictability, if the predictability is determined positive; and encoding the current motion vector by using a motion vector prediction mode for indicating a default predicted motion vector and an unpredictability, if the predictability is determined negative. According to the disclosure, it becomes unnecessary to directly notify of the predicted motion vector of the current motion vector to the decoding apparatus, and instead a predetermined shared function is provided to inform of or search the predicted motion vector.

PROBLEM TO BE SOLVED: To provide a perforating pin and equipment for perforation with which an accurate piercing region and piercing direction of a guiding pin can be easily specified at the neck of the femur or its surroundings and an advancing situation of the perforating pin can be confirmed when the perforating pin is pierced.

SOLUTION: The guide 1 for the perforating pin includes a main body section 2 which is equipped with a contacting section 8, a guiding channel 3 for the perforating pin and an operation section 9, a first advancing direction of the perforating pin displaying section 5 with which the advancing direction of the perforating pin 10 inserted in the guiding channel 3 can be confirmed by X-ray fluoroscopy, and a second advancing direction of the perforating pin displaying section 6 with which the advancing direction of the perforating pin 10 inserted in the guiding channel 3 can be confirmed by X-ray fluoroscopy from the different direction than the first advancing direction of the perforating pin displaying section 5. The bone perforating pin 10 can be confirmed by X-ray fluoroscopy with the first and the second advancing direction of the perforating pin displaying sections 5 and 6 while the perforating pin 10 inserted in the guiding channel 3 is superimposed on the displaying sections 5 and 6.

An intra prediction method performed by a decoding device, according to the present invention, comprises the steps of: deriving an intra prediction mode for a current block; deriving neighboring samples of the current block; and generating a prediction sample for the current block by using at least one of the neighboring samples according to the intra prediction mode, wherein the derived neighboring samples include left neighboring samples, upper left neighboring samples, upper neighboring samples, right neighboring samples, lower right neighboring samples, and lower neighboring samples of the current block. According to the present invention, intra prediction performance can be improved by using expanded neighboring reference samples, and coding efficiency for CUs can be improved.

A visual discovery tool for automotive manufacturing with network encryption, data conditioning, and prediction can include an extraction device configured to receive data records from application-specific file source databases. The tool can further include a vehicle alert database that receives the vehicle records from the plurality of extraction databases. The visual discovery tool can include at least one hardware processor in communication with the extraction device and the vehicle alert database. The tool can be configured to selectively restrict access to an interactive display based on whether a client device receives authorization credentials.

The invention provides an epidemic disease forecasting method, system and equipment, and relates to the technical field of epidemic disease forecasting. The method comprises the steps that the epidemic disease relevant data are acquired, wherein the relevant data include the internet data, the weather data and the biological information data acquired by the intelligent terminal, and the internet data include the search data and the social network data; the data cleaning is performed on the relevant data; an integrated forecasting model is established according to the relevant data after data cleaning; and forecasting is performed according to the integrated forecasting model and the forecasting result is outputted. According to the epidemic disease forecasting method, system and equipment,the data sources are wider, the forecasting effect is better, the forecasting accuracy is higher, the cost is lower and the effectiveness is higher and the possible epidemic disease outbreak can be forecasted earlier.

An alertness prediction bio-mathematical model for use in devices such as a wearable device that improves upon previous models of predicting fatigue and alertness by gathering data from the individual being monitored to create a more accurate estimation of alertness levels. The bio-mathematical model may be a two-process algorithm which incorporates a sleep-wake homeostasis aspect and a circadian rhythm aspect. The sleep-wake homeostasis aspect of the model is improved by using actigraphy measures in conjunction with distal skin, ambient light and heart rate measures to improve the accuracy of the sleep and wake estimations. The circadian rhythm model aspect improves fatigue prediction and estimation by using distal skin, heart rate and actigraphy data. The sleep-wake homeostasis and circadian rhythm aspects may also be combined with additional objective and subjective measures as well as information from a user to improve the accuracy of the alertness estimation even further.

The invention relates to an air travel scheduling platform that incorporates turbulence forecast and other safety data into search results and flight query filters such that air travelers can choose flight options that minimize their risk of experiencing turbulence, or exposure to other hazardous events. It also allows travelers to monitor turbulence and other hazardous forecasts for specified flights.

The invention addresses confounding difficulties involving continuous sweat analyte measurement. Specifically, the present invention provides: at least one component capable of monitoring whether a sweat sensing device is in sufficient contact with a wearer's skin to allow proper device operation; at least one component capable of monitoring whether the device is operating on a wearer's skin; at least one means of determining whether the device wearer is a target individual within a probability range; at least one component capable of generating and communicating alert messages to the device user(s) related to: wearer safety, wearer physiological condition, compliance with a requirement to wear a device, device operation; compliance with a behavior requirement, or other purposes that may be derived from sweat sensor data; and the ability to utilize aggregated sweat sensor data that may be correlated with information external to the device to enhance the predictive capabilities of the device.

Systems, apparatuses and methods for determining a risk of catastrophic failure for a tree based on a mechanistic model of physical characteristics of the tree are described. The systems, apparatuses and methods include a mobile sensing platform comprising one or more sensors for obtaining data, a transport vehicle configured to transport the mobile sensing platform, a positioning sensor configured to precisely calculate geographic coordinates of the positioning sensor and the location of the positioning sensor relative to a reference object as positioning data, and a processor configured to fuse the imaging data and the positioning data in order to determine conditions for catastrophic tree failure.

An automated method and system for diagnosing sleep disorders and predicting treatment effectiveness using data collected on the user using an automated application including questionnaire, facial recognition technology, and historical user and patient data. The data can be used by a diagnostic and treatment prediction algorithm to diagnose sleep disorders, for example sleep apnea, and predict treatment effectiveness. The system is an automated, self-learning algorithm capable of assessing the risk for sleep disorders and predicting treatment effectiveness.