Abstract: A coherent beam combination (CBC) system (10) includes an array of beam sources (12a, 12b and 12c) generating coherent beams directed towards a target (T). The phase modulators (14a, 14b and 14c) allow adjustment of relative phase offsets of the beams. A detector (16) monitors an intensity of the radiation impinging on an area of the target (T). A controller (18) receives the intensity parameter and controls a phase adjustment of the beams according to a deterministic (i.e., quantitative) measurement of a phase offset of each beam relative to a representative phase of the sum of all the other beams. This is achieved by using interferometric techniques, referred to herein as Target In-the-Loop Interferometry (TILI).

Abstract: An electronic automatic injection device including a housing configured to receive an injection module containing a material to be injected, an electric motor having a rotary drive output, at least one forward driving spring and a multifunctional electric motor driven drive assembly responsive to the rotary drive output of the electric motor and being operative in a first mode of operation, when the injection module includes a prefilled syringe, to enable the at least one forward driving spring to displace the prefilled syringe in a forward direction and in a second mode of operation, when the injection module includes a needleless cartridge, to eject the injectable liquid from the prefilled syringe through a needle.

Abstract: Methods for anomaly detection using dictionary based projection (DBP), and system for implementing such methods. In an embodiment, a method comprises receiving input data including a plurality n of multidimensional data points (MDDPs) with dimension m, applying DBP iteratively to the input data to construct a dictionary D, receiving a newly arrived MDDP (NAMDDP), calculating a score S associated with the NAMDDP as a distance of the NAMDDP from dictionary D, and classifying the NAMDDP as normal or as an anomaly based on score S, wherein classification of the NAMDDP as an anomaly is indicative of detection of an unknown undesirable event.

Abstract: Detection systems, methods and computer program products comprising a non-transitory tangible storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method for anomaly detection, a detected anomaly being indicative of an undesirable event. A detection system comprises a computer and an anomaly detection engine executable by the computer, the anomaly detection engine configured to perform a method comprising receiving data comprising a plurality m of multidimensional data points (MDDPs), each data point having n features, constructing a dictionary D based on the received data, embedding dictionary D into a lower dimension embedded space and classifying, based in the lower dimension embedded space, a MDDP as an anomaly or as normal.

Abstract: Detection systems, methods and computer program products comprising a non-transitory tangible storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method for anomaly detection, a detected anomaly being indicative of an undesirable event. A detection system comprises a computer and an anomaly detection engine executable by the computer, the anomaly detection engine configured to perform a method comprising receiving data comprising a plurality m of multidimensional data points (MDDPs), each data point having n features, constructing a dictionary D based on the received data, embedding dictionary D into a lower dimension embedded space and classifying, based in the lower dimension embedded space, a MDDP as an anomaly or as normal.

Abstract: A computer program product for performing anomaly detection, a detected anomaly being indicative of an undesirable event, the computer program product comprising: a non-transitory tangible storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising: receiving data comprising a plurality m of multidimensional datapoints (MDDPs), each data point having n features; constructing a dictionary D based on the received data; embedding dictionary D into a lower dimension embedded space; and classifying, based in the lower dimension embedded space, an MDDP as an anomaly or as normal.

Abstract: A computer program product for performing anomaly detection, a detected anomaly being indicative of an undesirable event, the computer program product comprising: a non-transitory tangible storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising: receiving data comprising a plurality m of multidimensional datapoints (MDDPs), each data point having n features; constructing a dictionary D based on the received data; embedding dictionary D into a lower dimension embedded space; and classifying, based in the lower dimension embedded space, an MDDP as an anomaly or as normal.

Abstract: A system for detecting an unknown undesirable event comprises an input device configured to receive a dataset comprising a plurality n of multidimensional datapoints (MDDPs), a processor configured to embed the MDDPs in an lower dimension embedded space to obtain embedded MDDPs, and a detection engine configured to calculate distributions of distances Dnni, i=1, . . . , n of each embedded MDDP from a plurality of nearest-neighbors (nn) to compute a threshold Dnnt and to classify a particular MDDP of the dataset or a newly arrived MDDP (NAMDDP) as an abnormal MDDP based on comparison with threshold Dnnt, wherein the classification is automatic and unsupervised without relying on a signature, rules or domain expertise and wherein the particular MDDP classified as abnormal is indicative of the unknown undesirable event.

Abstract: Detection systems, methods and computer program products comprising a non-transitory tangible storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method for anomaly detection, a detected anomaly being indicative of an undesirable event. A detection system comprises a computer and an anomaly detection engine executable by the computer, the anomaly detection engine configured to perform a method comprising receiving data comprising a plurality m of multidimensional data points (MDDPs), each data point having n features, constructing a dictionary D based on the received data, embedding dictionary D into a lower dimension embedded space and classifying, based in the lower dimension embedded space, a MDDP as an anomaly or as normal.

Abstract: Method and system for detecting an unknown undesirable event, such as (but not limited to) a cyber-threat, a cyber-intrusion, a financial fraud event or a monitored process malfunction of breakdown. An exemplary method embodiment comprises obtaining a dataset comprising a plurality n of multidimensional data points with a dimension m?2 wherein each data point is a vector of m features, processing the MDPs using measure-based diffusion maps to embed the MDPs into a lower dimension embedded space, and detecting in the embedded space an abnormal MDP without relying on a signature of a threat, the abnormal MDP being indicative of the unknown undesirable event.

Abstract: A computer program product for performing anomaly detection, a detected anomaly being indicative of an undesirable event, the computer program product comprising a non-transitory tangible storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising receiving data comprising a plurality m of multidimensional datapoints (MDDPs), each data point having n features, constructing a dictionary D based on the received data, embedding dictionary D into a reduced dimension embedded space and classifying, based in the reduced dimension embedded space, an MDDP as an anomaly or as normal.

Abstract: A system for detecting an unknown undesirable event comprises an input device configured to receive a dataset comprising a plurality n of multidimensional datapoints (MDDPs), a processor configured to embed the MDDPs in an lower dimension embedded space to obtain embedded MDDPs, and a detection engine configured to calculate distributions of distances Dnni, i=1, . . . , n of each embedded MDDP from a plurality of nearest-neighbors (nn) to compute a threshold Dnnt and to classify a particular MDDP of the dataset or a newly arrived MDDP (NAMDDP) as an abnormal MDDP based on comparison with threshold Dnnt, wherein the classification is automatic and unsupervised without relying on a signature, rules or domain expertise and wherein the particular MDDP classified as abnormal is indicative of the unknown undesirable event.

Abstract: A computer program product for performing anomaly detection, a detected anomaly being indicative of an undesirable event, the computer program product comprising a non-transitory tangible storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising receiving data comprising a plurality m of multidimensional datapoints (MDDPs), each data point having n features, constructing a dictionary D based on the received data, embedding dictionary D into a lower dimension embedded space and classifying, based in the lower dimension embedded space, an MDDP as an anomaly or as normal.

Abstract: Method and system for detecting an unknown undesirable event, such as (but not limited to) a cyber-threat, a cyber-intrusion, a financial fraud event or a monitored process malfunction of breakdown. An exemplary method embodiments comprises obtaining a dataset comprising a plurality n of multidimensional data points with a dimension m?2 wherein each data point is a vector of m features, processing the MDPs using measure-based diffusion maps to embed the MDPs into a lower dimension embedded space, and detecting in the embedded space an abnormal MDP without relying on a signature of a threat, the abnormal MDP being indicative of the unknown undesirable event.

Abstract: The present invention relates to a novel delivery system for delivering therapeutic agents into living cells, and more particularly, to novel chemical moieties that are designed capable of targeting and/or penetrating cells or other targets of interest and further capable of binding therapeutic agents to be delivered to these cells, and to delivery systems containing same.

Abstract: The present invention relates to a novel delivery system for delivering therapeutic agents into living cells, and more particularly, to novel chemical moieties that are designed capable of targeting and/or penetrating cells or other targets of interest and further capable of binding therapeutic agents to be delivered to these cells, and to delivery systems containing same.

Abstract: The present invention relates to a novel delivery system for delivering therapeutic agents into living cells, and more particularly, to novel chemical moieties that are designed capable of targeting and/or penetrating cells or other targets of interest and further capable of binding therapeutic agents to be delivered to these cells, and to delivery systems containing same.

Abstract: The present invention relates to a novel delivery system for delivering therapeutic agents into living cells, and more particularly, to novel chemical moieties that are designed capable of targeting and/or penetrating cells or other targets of interest and further capable of binding therapeutic agents to be delivered to these cells, and to delivery systems containing same.

Abstract: The present invention relates to a novel delivery system for delivering therapeutic agents into living cells, and more particularly, to novel chemical moieties that are designed capable of targeting and/or penetrating cells or other targets of interest and further capable of binding therapeutic agents to be delivered to these cells, and to delivery systems containing same.

Abstract: A novel class of oligomeric compounds designed for forming conjugates with biologically active substances and delivering these substances to a desired bodily target are disclosed. Novel conjugates of these oligomeric compounds and biologically active moieties, pharmaceutical compositions containing such conjugates, and uses thereof as delivery systems for delivering the biologically active substances to a desired target are further disclosed. Processes of preparing the conjugates and the oligomeric compounds and novel intermediates designed for and used in these processes are also disclosed.