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Buscema
Craig W. Buscema, Lithia Springs, GA US
| Patent application number | Description | Published |
|---|---|---|
| 20110056937 | HAND FORMED REINFORCED POLYGONAL CONTAINERS AND BLANKS FOR MAKING THE SAME - A blank of sheet material for forming a polygonal container includes a bottom panel, two opposing side panels each extending from a side edge of the bottom panel, and two opposing end panels each extending from an end edge of the bottom panel. The blank also includes a foldover panel that is configured to lock the container in at least a partially formed position. The blank further includes a reinforcing panel assembly that includes an outer reinforcing corner panel extending from the first side panel, an outer reinforcing end panel extending from the outer reinforcing corner panel, an inner reinforcing end panel extending from the outer reinforcing end panel, an inner reinforcing corner panel extending from the inner reinforcing end panel, and an inner reinforcing side panel extending from the inner reinforcing corner panel. | 03-10-2011 |
Paolo Massimo Buscema, Roma IT
| Patent application number | Description | Published |
|---|---|---|
| 20100135574 | Image processing using neural network - Image processing method wherein each image is composed of an array of image points, so called pixels or voxels particularly in a two-, three-, or more dimensional space respectively each image point being univocally defined by its position within the array of image points and by one or more numerical parameters defining the image point appearance as regards characteristics of brightness, grey, colour shade or the like, and wherein each image point is considered to be a node of an artificial neural network, the image being processed as a function of parameters defining the appearance of each pixel as values of the nodes of said artificial neural network and as a function of connections of each pixel under processing with neighbouring pixels composed of pixels of a predetermined subset of pixels, particularly with neighbouring pixels of said pixel under processing, so called pixel window, while pixels of the new image i.e. of the processed image are obtained by iterative evolution steps of parameters defining the appearance such as evolution steps of the value of nodes or by iterative evolution steps of values of the set of connections or by a combination of said evolutions, wherein the processing occurs by evolution iterative steps where each step is a function also of connections of neighbouring pixels with the pixel under examination, when each of said neighbouring pixels of the pixel under examination is considered also as a neighbouring pixel of one ore more or all pixels adjacent to said neighbouring pixel, which function is an immediate feedback contribution for determining appearance values of all other pixels. | 06-03-2010 |
| 20100217145 | Method of processing multichannel and multivariate signals and method of classifying sources of multichannel and multivariate signals operating according to such processing method - A method of processing multichannel and multivariate signals as described hereinbefore, wherein the signals from each channel are subjected to a first processing step by a recirculation artificial neural network being trained to generate the recorded multichannel and multivariate signals; and a second processing step in which the weights of the connections between the knots of the recirculation neural network determined in the first processing step are processed by an artificial neural network, the recirculation neural network being preferably of the non supervised kind. A particular family of recirculation neural network which can be used according to the present invention is a so called auto-associative neural network. The method further provides, in combination, the use of a predictive and/or classification and/or clustering algorithm for determining the qualities or features of objects from the multichannel multivariate signals generated by said object, the weight matrix obtained by processing said multichannel and multivariate signals with a self-associated neural network being used as records for representing said multichannel and multivariate signals. The method is used for patients suffering from neurological disorders for analysing and evaluating the EEG patterns of these patients. | 08-26-2010 |
Paolo Massimo Buscema, Rome IT
| Patent application number | Description | Published |
|---|---|---|
| 20080256006 | Clinical Trial Phase Simulation Method and Clinical Trial Phase Simulator For Drug Trials - A clinical trial phase simulation method for drug trials, which method allows to predict the trend of the results of a clinical trial phase of a drug with the steps of providing a database comprising for each of a certain number of individuals a predefined number of independent variables each of which corresponds to a certain clinical parameter relevant or characteristic for a disease condition against which the drug to be tested is oriented and at least a further independent variable describing the specific treatment to which the individual has been subjected between at least two different treatments one with the said drug and the second with a placebo or with another known drug, the database comprising also for each individuals one or more dependent variables describing the effects of the said treatments; carryings out an input variable selection; adding to the independent variables selected as input variables the dependent variables describing the effects of the treatments; training and validating an artificial neural network with the selected variables as input variables and with the dependent variables; interrogating the said neural network by inputting the values of the variable describing one of the treatments and obtaining as an output the variable values of the effectiveness of the treatment to which the inputted values of the variable of the treatment correspond according to the trained artificial neural network. | 10-16-2008 |