Abstract: A computer implemented method of synchronizing data between a central database and at least one individual database including the steps of: acquiring data from at least one external source; forming an intelligence dataset, wherein the intelligence dataset includes multiple intelligence datum; storing the intelligence dataset in a central database; applying a machine learning ML tagging algorithm to the stored dataset to assign at least one tag to each intelligence datum in the stored dataset, forming a tagged intelligence dataset including multiple tagged intelligence datum; and copying each tagged intelligence datum from the central database to at least one individual database based on the assigned tag.

Abstract: A method and system are provided for matching database records. According to one embodiment, the method includes receiving a record from a first database, and selecting a sequence of characters within the record. The method also includes identifying a key associated with a second, dissimilar database by comparing the selected sequence with a number of historical records. The comparison is performed using one or more analytical processes, where at least one analytical process is a machine-learning (ML) process. The method further includes matching, using the key, the record from the first database with another record from the second database, where the other record includes the identified key.

Abstract: A method and system are provided for training a machine learning (ML) system for predicting delays in processing pipelines. In one embodiment, the method includes receiving labelled historical data pertaining to a pipeline, the labelled data including trigger objects initiating the pipeline and one or more processing times corresponding to one or more stages of the pipeline. The method includes identifying features associated with the trigger objects, formatting the labelled data and, randomly splitting the formatted labelled data into a full training dataset and a testing dataset. Additionally, the method includes distributing the full training dataset into several partial datasets and, in an ensemble ML system, training each of several ML subsystems using a respective partial dataset to provide a respective individual inference model predicting respective processing times, and deriving and storing an ML model for prediction of delays by aggregating the individual inference models.

Abstract: A computer implemented method of synchronizing data between a central database and at least one individual database including the steps of: acquiring data from at least one external source; forming an intelligence dataset, wherein the intelligence dataset includes multiple intelligence datum; storing the intelligence dataset in a central database; applying a machine learning ML tagging algorithm to the stored dataset to assign at least one tag to each intelligence datum in the stored dataset, forming a tagged intelligence dataset including multiple tagged intelligence datum; and copying each tagged intelligence datum from the central database to at least one individual database based on the assigned tag.

Abstract: A computer implemented method of synchronizing data between a central database and at least one individual database including the steps of: acquiring data from at least one external source; forming an intelligence dataset, wherein the intelligence dataset includes multiple intelligence datum; storing the intelligence dataset in a central database; applying a machine learning ML tagging algorithm to the stored dataset to assign at least one tag to each intelligence datum in the stored dataset, forming a tagged intelligence dataset including multiple tagged intelligence datum; and copying each tagged intelligence datum from the central database to at least one individual database based on the assigned tag.

Abstract: A method and system are provided for matching database records. According to one embodiment, the method includes receiving a record from a first database, and selecting a sequence of characters within the record. The method also includes identifying a key associated with a second, dissimilar database by comparing the selected sequence with a number of historical records. The comparison is performed using one or more analytical processes, where at least one analytical process is a machine-learning (ML) process. The method further includes matching, using the key, the record from the first database with another record from the second database, where the other record includes the identified key.

Abstract: A method and system are provided for training a machine learning (ML) system for predicting delays in process pipelines. According to one embodiment, a method for training includes receiving labelled historical data pertaining to a pipeline, where the labelled data includes trigger objects initiating the pipeline and one or more processing times corresponding to one or more stages of the pipeline. The method also includes identifying one or more features associated with the trigger objects, formatting the labelled data and, using a pseudorandom generator, randomly splitting the formatted labelled data into a full training dataset and a testing dataset.

Abstract: A comprehensive scheme to detect phishing emails using features that are invariant and fundamentally characterize phishing. Multiple embodiments are described herein based on combinations of text analysis, header analysis, and link analysis, and these embodiments operate between a user's mail transfer agent (MTA) and mail user agent (MUA). The inventive embodiment, PhishNet-NLP™, utilizes natural language techniques along with all information present in an email, namely the header, links, and text in the body. The inventive embodiment, PhishSnag™, uses information extracted form the embedded links in the email and the email headers to detect phishing. The inventive embodiment, Phish-Sem™ uses natural language processing and statistical analysis on the body of labeled phishing and non-phishing emails to design four variants of an email-body-text only classifier. The inventive scheme is designed to detect phishing at the email level.

Abstract: A comprehensive scheme to detect phishing emails using features that are invariant and fundamentally characterize phishing. Multiple embodiments are described herein based on combinations of text analysis, header analysis, and link analysis, and these embodiments operate between a user's mail transfer agent (MTA) and mail user agent (MUA). The inventive embodiment, PhishNet-NLP™, utilizes natural language techniques along with all information present in an email, namely the header, links, and text in the body. The inventive embodiment, PhishSnag™, uses information extracted form the embedded links in the email and the email headers to detect phishing. The inventive embodiment, Phish-Sem™ uses natural language processing and statistical analysis on the body of labeled phishing and non-phishing emails to design four variants of an email-body-text only classifier. The inventive scheme is designed to detect phishing at the email level.

Abstract: A comprehensive scheme to detect phishing emails using features that are invariant and fundamentally characterize phishing. Multiple embodiments are described herein based on combinations of text analysis, header analysis, and link analysis, and these embodiments operate between a user's mail transfer agent (MTA) and mail user agent (MUA). The inventive embodiment, PhishNet-NLP™, utilizes natural language techniques along with all information present in an email, namely the header, links, and text in the body. The inventive embodiment, PhishSnag™, uses information extracted form the embedded links in the email and the email headers to detect phishing. The inventive embodiment, Phish-Sem™ uses natural language processing and statistical analysis on the body of labeled phishing and non-phishing emails to design four variants of an email-body-text only classifier. The inventive scheme is designed to detect phishing at the email level.

Abstract: Methods and structure are provided for managing a Serial Attached SCSI (SAS) domain via Universal Serial Bus (USB) communications. The system comprises a SAS expander. The SAS expander comprises a plurality of physical links, a USB interface, and a control unit. The control unit is operable to receive USB packets via the USB interface, to determine SAS management information based upon the received USB packets, and to alter a configuration of the SAS domain based upon the SAS management information determined from the USB packets.

Abstract: Methods and structure are provided for managing a Serial Attached SCSI (SAS) domain via Universal Serial Bus (USB) communications. The system comprises a SAS expander. The SAS expander comprises a plurality of physical links, a USB interface, and a control unit. The control unit is operable to receive USB packets via the USB interface, to determine SAS management information based upon the received USB packets, and to alter a configuration of the SAS domain based upon the SAS management information determined from the USB packets.

Abstract: The invention provides a compound comprising a target specific portion and an effector portion wherein the target specific portion comprises or consists of a monoclonal antibody having specificity for oncofoetal fibronectin, or a fragment or variant thereof which retains the antigen binding specificity of the parent monoclonal antibody and the effector portion comprises or consists of interleukin-12, or a functional fragment or variant thereof, characterized in the monoclonal antibody having specificity for oncofoetal fibronectin binds to a region of oncofoetal fibronectin other than the ED-B region. The invention further provides nucleic acids encoding the compounds of the invention, and the use of such compounds in medicine, e.g. in the treatment of cancer.

Abstract: Methods and systems for improved update of firmware for components in a storage system/network. A storage network comprising one or more initiator components coupled through one or more switching components to one or more target components may be updated by generating and distributing a package buffer comprising portions where each portion comprises firmware for a corresponding type of component. Switching and/or initiator components in the system locate a portion of the package buffer for each target component directly coupled to it and transmits the located, corresponding portion (comprising firmware) to each target component. Each initiator/switching component then also forwards the entire package buffer to each other switching component coupled with it and the process repeats until all components have received updated firmware.

Abstract: A system and method for customizing a SCSI error response received from a SCSI target in a storage network environment is disclosed. In a method for customizing a SCSI error response received from a SCSI target in a storage network environment, a SCSI command is received from a SCSI initiator by a SCSI to ATA bridge. The received SCSI command is translated to provide an ATA command. The ATA command is then sent to an ATA drive. The ATA command is executed by the ATA drive. During execution, if an error occurs, an ATA error response is sent by the ATA drive to the SCSI to ATA bridge. The received ATA error response is translated to a SCSI error response. The SCSI to ATA bridge then obtains a customized SCSI error response using an error look-up table. Further the customized SCSI error response is sent to the SCSI initiator.

Abstract: There is provided by the invention a modified antibody molecule which selectively binds to a specific target, the antibody molecule being modified at, at least one amino acid residue that forms part of a glycosylation site in the variable region of an unmodified parent antibody molecule, characterised in that the modified antibody is not glycosylated at the previous glycosylation site of which the amino acid modification forms part and the modified antibody exhibits a greater binding affinity for the specific target than the unmodified parent antibody molecule. There is also provided nucleotide sequences, amino acid sequences and expression vectors encoding the modified antibodies, and uses thereof.

Abstract: The invention provides a compound comprising a target specific portion and an effector portion wherein the target specific portion comprises or consists of a monoclonal antibody having specificity for oncofoetal fibronectin, or a fragment or variant thereof which retains the antigen binding specificity of the parent monoclonal antibody and the effector portion comprises or consists of interleukin-12, or a functional fragment or variant thereof, characterised in the monoclonal antibody having specificity for oncofoetal fibronectin binds to a region of oncofoetal fibronectin other than the ED-B region. The invention further provides nucleic acids encoding the compounds of the invention, and the use of such compounds in medicine, e.g. in the treatment of cancer.