Abstract: A method, system and computer program product for performing computations on sensitive data while guaranteeing privacy. A service provider receives a first and a second ciphertext from a medical provider that homomorphically encrypts matrices A and B, respectively, using an encryption key, where the matrices A and B include medical data encoded as vectors. The service provider performs a homomorphic matrix multiplication on the first and second ciphertexts without decrypting the first and second ciphertexts. An encrypted result from the performed homomorphic matrix multiplication on the first and second ciphertexts is generated and transmitted to the medical provider to decrypt which matches a result of performing a matrix multiplication on unencrypted matrices A and B thereby enabling computations to be performed on the medical data in a secure manner.

Abstract: A method, system and computer program product for performing computations on sensitive data while guaranteeing privacy. A service provider receives a first and a second ciphertext from a medical provider that homomorphically encrypts matrices A and B, respectively, using an encryption key, where the matrices A and B include medical data encoded as vectors. The service provider performs a homomorphic matrix multiplication on the first and second ciphertexts without decrypting the first and second ciphertexts. An encrypted result from the performed homomorphic matrix multiplication on the first and second ciphertexts is generated and transmitted to the medical provider to decrypt which matches a result of performing a matrix multiplication on unencrypted matrices A and B thereby enabling computations to be performed on the medical data in a secure manner.

Abstract: A method selects a subset of training points near a query point from a set of training points. The subset of training points near the query point is determined from a the set of training points such that a cumulative similarity is maximized, wherein the cumulative similarity measures a similarity of the query point to each point in the subset and a similarity of points in the subset to each other.

Abstract: The present invention is a system and method that captures hand geometry, full-length fingerprints, and/or palm prints from a frontal view of a freely posed hand using contactless photography. A system and method for capturing biometric data of a hand includes the steps of and means for (a) digitally photographing a designated contactless capture area not having any predefined hand-positioning structures or platen for receiving a hand, to obtain a captured image of the capture area that includes a naturally-posed hand; (b) extracting a frontal hand image of the naturally-posed hand by applying an Active Appearance Model (AAM) to the captured image; (c) computing a plurality of hand geometry measurements of the frontal hand image; and (d) comparing the plurality of hand geometry measurements from the frontal hand image to corresponding existing hand geometry measurements, wherein the comparison results in a best match.

Abstract: A method predicts nonlinear seasonal time series data. More particularly, the method predicts short term power demand. The method uses an exponential smoothing technique and dynamic modeling of seasonal time series data with kernels. The kernels are used to predict future values of the time series from past values using nonlinear functions such as a least-squares radial basis function or support vector regression using a Gaussian kernel.

Abstract: A method selects a subset of training points near a query point from a set of training points. The subset of training points near the query point is determined from a the set of training points such that a cumulative similarity is maximized, wherein the cumulative similarity measures a similarity of the query point to each point in the subset and a similarity of points in the subset to each other.

Abstract: The present invention is a system and method that captures hand geometry, full-length fingerprints, and/or palm prints from a frontal view of a freely posed hand using contactless photography. A system and method for capturing biometric data of a hand includes the steps of and means for (a) digitally photographing a designated contactless capture area not having any predefined hand-positioning structures or platen for receiving a hand, to obtain a captured image of the capture area that includes a naturally-posed hand; (b) extracting a frontal hand image of the naturally-posed hand by applying an Active Appearance Model (AAM) to the captured image; (c) computing a plurality of hand geometry measurements of the frontal hand image; and (d) comparing the plurality of hand geometry measurements from the frontal hand image to corresponding existing hand geometry measurements, wherein the comparison results in a best match.