Abstract: A method is provided for making “smart” paper and “smart” microfibers by means of nanotechnology layer-by-layer techniques. The method comprises forming an aqueous pulp of lignocellulose fibers and nanocoating it by alternatively adsorbing onto the fibers multiple consecutively-applied layers of organized ultra thin and oppositely-charged polyelectrolytes, at least one of which is an electrically conductive polymer or nanoparticle (or a magnetically active polymer or nanoparticle, or an optically active polymer or nanoparticle), and another one of which has a charge opposite of said electrically conductive polymer or nanoparticle (or magnetically active polymer or nanoparticle, or optically active polymer or nanoparticle), thereby making a modified aqueous pulp of electrically conductive (or magnetically active, or optically active) multi-layer nanocoated lignocellulose fibers.

Abstract: The invention is a new turbine structure having a housing that rotates. The housing has a sidewall, and turbine blades are attached to a sidewall portion. The turbine may be completely open in the center, allowing space for solids and debris to be directed out of the turbine without jamming the spinning blades/sidewall. The turbine may be placed in a generator for generation of electrical current.

Abstract: A method of surveying the condition of an underground enclosure including the steps of: (a) positioning at least one transmitter/receiver unit (including an antenna) within an underground, substantially nonconductive enclosure, such that a substantial air gap exists between the antenna and the inner wall of the enclosure; (b) transmitting an ultra wideband (UWB) signal toward at least a portion of the inner wall; and (c) processing the return signal in order to identify the interface between the soil and a region of conductivity different from the soil.

Abstract: A method of surveying the condition of an underground enclosure including the steps of (a) positioning at least one transmitter/receiver unit (including an antenna) within an underground, substantially nonconductive enclosure, such that a substantial air gap exists between the antenna and the inner wall of the enclosure; (b) transmitting an ultra wideband (UWB) signal toward at least a portion of the inner wall; and (c) processing the return signal in order to identify the interface between the soil and a region of conductivity different from the soil.

Abstract: A method is provided for making “smart” paper and “smart” microfibers by means of nanotechnology layer-by-layer techniques. The method comprises forming an aqueous pulp of lignocellulose fibers and nanocoating it by alternatively adsorbing onto the fibers multiple consecutively-applied layers of organized ultra thin and oppositely-charged polyelectrolytes, at least one of which is an electrically conductive polymer or nanoparticle (or a magnetically active polymer or nanoparticle, or an optically active polymer or nanoparticle), and another one of which has a charge opposite of said electrically conductive polymer or nanoparticle (or magnetically active polymer or nanoparticle, or optically active polymer or nanoparticle), thereby making a modified aqueous pulp of electrically conductive (or magnetically active, or optically active) multi-layer nanocoated lignocellulose fibers; then draining the water out of the modified aqueous pulp to form sheets of smart microfibers.

Abstract: A chipless RFID tag system having a transmitter sending an input signal and a tag substrate. The tag substrate has at least one microstrip and the microstrip has a first portion with a first impedance and a second portion with a second impedance different from the first impedance. The system further includes a receiver detecting at least two reflections from an interface of the first and second impedances and identifying relative time domain positions of the reflections to one another.

Abstract: A method of predicting a SYN flooding attack on a server. The method tracks the number of SYN signals received (or SYN+ACK signals sent) over the communications port of the server in a specified time interval, the arrival estimation window. The invention then predicts the number of anticipated ACK, RST or ACK+RST signals to be received over the communication port within a predetermined time length prediction window. The prediction may be made at multiple points within the prediction window. The prediction window is offset in time from the arrival estimation window. The prediction of ACK signals to be received is based upon the number of SYN signals received or SYN+ACK signals sent in the arrival estimation window. In one embodiment, a polynomial is fit to the data in the Arrival estimation window and extrapolated to the prediction window.

Abstract: The invention is collecting nose sweat and testing the nose sweat for levels of calcium. Testing may be done using standard laboratory procedures for calcium detection, or may be done cow-side using a suitable test for calcium levels, such as a water hardness test kit or a suitable test strip.

Abstract: The invention is a method of predicting a SYN flooding attack on a server. The method tracks the number of SYN signals received (or SYN+ACK signals sent) over the communications port of the server in a specified time interval, the arrival estimation window. The invention then predicts the number of anticipated ACK signals to be received over the communication port within a predetermined time length prediction window. The prediction may be made at multiple points within the prediction window. The prediction window is offset in time from the arrival estimation window. The prediction of ACK signals to be received is based upon the number of SYN signals received or SYN+ACK signals sent in the arrival estimation window. In one embodiment, a polynomial is fit to the data in the Arrival estimation window and extrapolated to the prediction window.

Abstract: The invention is a computer implemented technique for id entifying anomalous data in a data set. The method uses cascaded k-Means clustering and the ID3 decision tree learning methods to characterize a training data set having data points with known characterization. The k-Means clustering method first partitions the training instances into k clusters using Euclidean distance similarity. On each training cluster, representing a density region of normal or anomaly instances, the invention builds an ID3 decision tree. The decision tree on each cluster refines the decision boundaries by learning the sub-groups within the cluster. A test data point is then subjected to the clustering and decision trees constructed form the training instances. To obtain a final decision on classification, the decisions of the k-Means and ID3 methods are combined using rules: (1) the Nearest-neighbor rule, and (2) the Nearest-consensus rule.