Abstract: Mobile management method, system and client. Method includes receiving a DNS query for a host name from an application on client; retrieving reputation data associated with host name from a local cache on client; and determining a policy based on host name and the reputation data. Based on determined policy for the host name, blocking attempted network flows to a host corresponding to host name to produce blocked attempted network flows. Method also includes sending attempted network flow metadata related to the blocked attempted network flows to a collector on client; transmitting the attempted network flow metadata from the collector to a VPN server pool via a VPN tunnel; and producing an anomaly report from the transmitted attempted network flow metadata. The anomaly report includes at least one of anomalies, cohorts, trends, location boundaries, detected network security issues, detected compromised clients and/or optimized network usage.

Abstract: Mobile management method, system and client. The method includes receiving a DNS query for a host name from an application on a client; retrieving reputation data associated with the host name from a local cache on the client; determining a policy for the host name, which is associated with the host name and the reputation data associated with the host name; based on the determined policy for the host name, blocking attempted network flows to a host corresponding to the host name; sending at least attempted network flow metadata related to the blocked attempted network flows to a collector on the client; and transmitting the attempted network flow metadata in the collector to a VPN server pool via a VPN tunnel.

Abstract: A device cleaning system cycles a fluid by a clogged or non-functioning device to remove the substances that are built-up on it. The fluid could be heated to facilitate removal and it is considered of importance to use a fluid that is safe environmentally. A clean and functioning verification device is run in the system to compare readings from the non-functioning device. The system is intended to run until the provide similar readings.

Abstract: Mobile management method and system. The method includes receiving from an application on a client a DNS query for a host name; retrieving reputation data associated with the host name from a local cache on the client; determining whether a policy associated with the host name and the reputation data associated with the host name exists; and one of: sending network flows one of: through a VPN tunnel to a server or out a local proxy on the client to a private or public network; or blocking the network flow based on the determined policy for the host name.

Abstract: Mobile management method and system. The method includes receiving from an application on a client a DNS query for a host name; retrieving reputation data associated with the host name from a local cache on the client; determining whether a policy associated with the host name and the reputation data associated with the host name exists; and one of: sending network flows one of: through a VPN tunnel to a server or out a local proxy on the client to a private or public network; or blocking the network flow based on the determined policy for the host name.

Abstract: Methods, systems, and devices are described that provide for a voter-verified digital voting audit trail. One or more votes cast by a voter may be identified at a voting system, and a digital image that lists the identified votes may be generated. The digital image may be stored in a memory and displayed to the voter. The voter may be prompted to provide a voter verification of the displayed votes. Upon receiving the verification from the voter, the voter verification of the digital image containing the votes may be stored to provide a voter-verified digital audit trail. A cast vote record is generated based on the verified votes, and linked to the stored digital image and voter verification. The cast vote record may be provided to a tabulation system that may tabulate votes from multiple voters.

Abstract: Embodiments may include machine learning, including decision tree machine learning. Predictive variables may be selected for the machine learning through an iterative process. Predictive power of the predictive variables and collinearity between the predictive variables may be considered when selecting a set of the predictive variables for the machine learning.

Abstract: A system for database management and presentation processing of a graphical user interface includes a network interface interfacing with multiple data sources comprising internal systems and external systems, one or more processors, and an application service integration and communication layer to receive data including a live data feed. A data storage device stores schemas of data structures, and the data structures may include tables based on types and fields. The application service integration and communication layer normalizes and formats the live data feed according to the predetermined schemas, and stores the normalized and formatted procurement data in the database. A graphical user interface of true conditions assigned to procurement data in the live data feed is displayed.

Abstract: A system, method and computer program for tabulating votes and creating an audit trail is provided. A ballot processing device may include a paper feed mechanism, a computer, a ballot processing application loaded on the computer, and a digital scanning device linked to the computer. The ballot processing application may process the digital image to establish a series of processing results definning one or more voting results for the paper ballot, and also an audit trail. The ballot processing application may process the digital image to define the voting results based on criteria established by election officials, including ambiguous mark criteria. The audit trail enables election officials to verify that particular paper ballots have been processed correctly in accordance with these criteria.

Abstract: A system, method and computer program for tabulating votes and creating an audit trail is provided. A ballot processing device may include a paper feed mechanism, a computer, a ballot processing application loaded on the computer, and a digital scanning device linked to the computer. The ballot processing application may process the digital image to establish a series of processing results defining one or more voting results for the paper ballot, and also an audit trail. The ballot processing application may process the digital image to define the voting results based on criteria established by election officials, including ambiguous mark criteria. The audit trail enables election officials to verify that particular paper ballots have been processed correctly in accordance with these criteria.

Abstract: A machine learning based procurement system comprises a machine learning classifier to classify bids. The procurement system determines a price risk score and a supplier risk score for each of the bids based on the classifications, and determines if any of the bids are associated with a high-risk procurement based on comparing the price risk score and the supplier risk score to the respective threshold. The procurement system includes a graphical user interface that can display bid evaluation links, which are accessible to provide information explaining high-risk procurements.

Abstract: A machine learning based procurement system comprises a machine learning classifier to classify bids. The procurement system determines a price risk score and a supplier risk score for each of the bids based on the classifications, and determines if any of the bids are associated with a high-risk procurement based on comparing the price risk score and the supplier risk score to the respective threshold. The procurement system includes a graphical user interface that can display bid evaluation links, which are accessible to provide information explaining high-risk procurements.

Abstract: A system, method and computer program for tabulating votes and creating an audit trail is provided. A ballot processing device may include a paper feed mechanism, a computer, a ballot processing application loaded on the computer, and a digital scanning device linked to the computer. The ballot processing application may process the digital image to establish a series of processing results defining one or more voting results for the paper ballot, and also an audit trail. The ballot processing application may process the digital image to define the voting results based on criteria established by election officials, including ambiguous mark criteria. The audit trail enables election officials to verify that particular paper ballots have been processed correctly in accordance with these criteria.

Abstract: A machine learning classifier based procurement system determines a price risk score, a supplier risk score, and an item risk score for bids based on classifications performed by a machine learning classifier. The scores are compared to respective thresholds to determine if any of the bids are associated with a high-risk procurement.

Abstract: A machine learning classifier system includes a data set processing subsystem to generate a training set and a validation set from multiple data sources. Classifier hardware induces a classifier according to the training set, and tests the classifier according to the validation set. A buffer connected to the classifier hardware stores data objects to be classified, and a register connected to the classifier hardware stores outputs of the classifier, including classified data objects.

Abstract: A machine learning classifier system includes a data set processing subsystem to generate a training set and a validation set from multiple data sources. Classifier hardware induces a classifier according to the training set, and tests the classifier according to the validation set. A buffer connected to the classifier hardware stores data objects to be classified, and a register connected to the classifier hardware stores outputs of the classifier, including classified data objects.

Abstract: Embodiments may include machine learning, including decision tree machine learning. Predictive variables may be selected for the machine learning through an iterative process. Predictive power of the predictive variables and collinearity between the predictive variables may be considered when selecting a set of the predictive variables for the machine learning.

Abstract: A machine learning classifier system includes a data set processing subsystem to generate a training set and a validation set from multiple data sources. Classifier hardware induces a classifier according to the training set, and tests the classifier according to the validation set. A buffer connected to the classifier hardware stores data objects to be classified, and a register connected to the classifier hardware stores outputs of the classifier, including classified data objects.

Abstract: A system for database management and presentation processing of a graphical user interface includes a network interface interfacing with multiple data sources comprising internal systems and external systems, one or more processors, and an application service integration and communication layer to receive data including a live data feed. A data storage device stores schemas of data structures, and the data structures may include tables based on types and fields. The application service integration and communication layer normalizes and formats the live data feed according to the predetermined schemas, and stores the normalized and formatted procurement data in the database. A graphical user interface of true conditions assigned to procurement data in the live data feed is displayed.