Abstract: A flare monitoring and control system monitors parameters that affect the amount of smoke generated during a flaring operation. The system receives data relating to the parameters, and analyzes the data relating to the parameters. The system predicts an impending increase in the amount of smoke generated during the flaring operation, and varies a value of one or more parameters to prevent the impending increase in the amount of smoke generated during the flaring operation.

Abstract: A method for the detection of motion in video data is disclosed. In an embodiment, a method uses a background technique for the motion detection. In another embodiment, a Gaussian Mixture Model is applied to a neighborhood or block of pixels within an image frame, thereby identifying background and foreground in the image based on said blocks.

Abstract: In an embodiment, a novel, scene adaptive, robust shadow detection method has been disclosed. An adaptive division image analysis compares one or more images containing objects and shadows to a reference image that is void of the objects and shadows. Ratios are calculated comparing the frame with shadows and/or objects to the reference frame. Shadows are identified by identifying pixels that fall within a certain range of these ratios. In another embodiment, projection histograms are used to identify the penumbra region of shadows in the image.

Abstract: A fire detection system has a video sensor, a processor, and a database. The database has a statistical model representing the characteristics of a fire. The video sensor captures images, and sends the images to the processor. The processor computes statistics on the characteristics of the captured image, and compares it to the statistical model to determine if a fire is present in the captured image.

Abstract: A seasonal autoregressive moving average (SARIMA) model that represents seasonal variation and a linear regression method to reflect peak load variation due to temperature are used to forecast energy needs. In one embodiment, a Kalman filter is used for model parameter estimation. The use of the Kalman filter provides optimal parameter estimation even under noisy data conditions. It also handles iterative computations of the SARIMA model efficiently. The method provides a forecast every fifteen minutes in one embodiment for several buildings. A user specifies a building ID, number of history data and the date for which the forecast is to be done. A model underlying the data is identified, parameters are estimated for the model, and a forecast is provided for future consumption.

Abstract: Yarn arrays bonded with selected adhesives give coated abrasive products with reduced elongation under stress. Best results are obtained using epoxy resins with dicyandiamide, blocked isocyanates and/or imidazole curing agents as saturants for the yarn arrays.

Abstract: Loading resistant coated abrasives can be made without the need for a supersize coating of metal stearates or any other material by incorporating phosphoric acids, partial esters of such acids, amine salts of such acids and partial esters, and/or quarternary ammonium salts with at least one long substituent group into amino resin or glue sizing adhesives used during the manufacture of the coated abrasives. Loading resistance equal or superior to that achieved with conventional zinc stearate supersized products can be achieved in this way.