Abstract: Though Density functional theory (DFT) based approaches such as Kohn-Sham DFT (KS-DFT) are useful for calculating energetics and other physical properties of physical/chemical systems, computational time complexity bottleneck of the DFT approach has remained a cubic function of the number of electronic orbitals, hence adversely affects efficiency of calculation of the energy estimation and other parameter calculations. Method and system disclosed herein computes a computational complexity for an electron density value as received as input, by performing a Kohn-Sham Hamilton simulation of the input. Further, one or more eigen states of the input are determined, via the one or more hardware processors. Further, the one or more eigen states of the input are mapped to a recursive sequence of nonlinear least squares problem solved by executing a Quantum linear system algorithm at every step, wherein the mapping causes reduction in the computational complexity of the input.

Abstract: Systems and methods are disclosed for implementing sensitive data proxy. In certain embodiments, a method may comprise implementing a sensitive data proxy configured to prevent unintended traffic from a client system to a target domain, including receiving a message from the client system intended for the target domain, determining a security rule to apply to the message, evaluating the message for compliance with the security rule, applying a corrective action to the message to bring the message into compliance with the security rule, and forwarding the message to the target domain based on the message being in compliance with the security rule.

Abstract: A method, a system, and a computer program product for lifecycle orchestration. An input computing event generated by a computing application executing in a computing system is received. A plurality of tasks associated with the input computing event is determined. A process flow is selected from a plurality of process flows based on one or more models defining one or more states of the computing system during execution of each process flow and a plurality of executable actions for performing tasks. At least one executable action for performing at least one task is executed resulting in the computing system being transferred from one state to another. An output computing event resulting from the executing of the executable action is generated. While the computing system is in another state, another executable action for performing another task is executed, where the generated output computing event is input to the executing of another executable action.

Abstract: AI-assisted Connected Home systems for improving power efficiency at homes and offices are described. The system may perform operations including: receiving, from each of a plurality of power receptacles, power usage information of an electrical device attached to the power receptacle; determining, for each of the plurality of power receptacles, a plurality of power usage metrics of the power receptacle based on the power usage information; feeding the plurality of power usage metrics into a machine learning model to obtain a priority of the electrical device attached to the power receptacle, wherein the priority is one of a plurality of pre-configured priorities; obtaining a power management signal; and transmitting a plurality of control signals to the plurality of power receptacles based on the power management signal and respective priorities of the plurality of electrical devices attached to the plurality of power receptacles.

Abstract: Systems and methods include determination, for each of a plurality of discrete features, of statistics based on a number of occurrences of each discrete value of the discrete feature in the data, determination of first summary statistics based on the determined statistics, determine of a dissimilarity for each discrete feature based on the first summary statistics and on the statistics determined for the discrete feature, determination of candidate discrete features based on the determined dissimilarities, determination, for each of the candidate discrete features, of second summary statistics based on values of a continuous feature associated with each discrete value of the candidate discrete feature, determination of a deviation score for each of the candidate discrete features based on the second summary statistics, and transmission of the candidate discrete features for display in association with the continuous feature based on the determined deviation scores.

Abstract: Analog calibration (ACAL) circuits supporting iterative measurement of an input signal from a measured circuit, and related methods are disclosed. The ACAL circuit includes a voltage reference generation circuit and a comparator circuit. The voltage reference generation circuit is configured to provide an input reference voltage. The comparator circuit is configured to compare the input reference voltage to an input circuit voltage of a measured circuit and generate a digital measurement signal based on the comparison. To provide for the ACAL circuit to more precisely measure the input circuit voltage, the voltage reference generation circuit is programmable and is configured to a generate the input reference voltage based on a programmed reference voltage selection. In this manner, the ACAL circuit can be used to measure the input circuit voltage in an iterative manner based on different programmed input reference voltages for a more precise measurement of the input circuit voltage.

Abstract: Systems and methods are disclosed for software security discovery. In certain embodiments, a method may comprise executing a third party software security discovery system, including scanning a directory of a client computing system for executable code, and identifying a service request within the executable code. The method may further comprise decomposing the service request into constituent parts, including a target entity of the service request, and generating a catalog of the client computing system, including third party vendors for the client computing system, based on the target entity.

Abstract: Systems and methods are disclosed for software security analysis. In certain embodiments, a method may comprise identifying a set of potential security vulnerabilities, comparing the potential vulnerabilities to a catalog identifying elements on a client system, and generating risk mitigation advice based on potential security vulnerabilities matching an element in the catalog. The method may include evaluating a data field of a service request to a third party to determine an expected data type for the field, determining whether the actual data included in the service request matches the expected data type, and quarantining the service request when the actual data does not match the expected data type. The method may comprise operating as a proxy for the service request, including receiving the service request from the client system, evaluating the service request for irregularities, and forwarding the service request to the third party once the irregularities have been addressed.

Abstract: Systems and methods include determination, determine, for each of a plurality of discrete features, of statistics for each discrete value of the discrete feature based on values of a continuous feature associated with the discrete value, determination, for each discrete feature, of first summary statistics based on the statistics determined for each discrete value of the discrete feature, determination, for each discrete feature, of a dissimilarity based on the first summary statistics determined for the discrete feature and on the statistics determined for each discrete value of the discrete feature, determination of candidate discrete features of the discrete features based on the determined dissimilarities, the candidate discrete features comprising less than all of the discrete features, determination, for each of the candidate discrete features, of second summary statistics based on values of the continuous feature associated with each discrete value of the candidate discrete feature, determine of a devi

Abstract: A system and method including determining, for a specified target measure column of a first dataset including a plurality of records, the metadata of the first dataset, including a probability distribution for the specified target column and dimension scores for the dimensions for the first dataset conditioned on the specified target measure column, where the first dataset comprises a plurality of columns including the at least one target measure column and a plurality of non-numeric, dimension columns for the records of the first dataset; determining, for a subset of data of the first dataset based on one or more specified variables, dimension scores for the dimensions of the subset of data approximately derived from the determined metadata of the first dataset; and providing recommendations of top contributors based on the approximated dimension scores of dimensions of the subset of data.

Abstract: Analog calibration (ACAL) circuits supporting iterative measurement of an input signal from a measured circuit, and related methods are disclosed. The ACAL circuit includes a voltage reference generation circuit and a comparator circuit. The voltage reference generation circuit is configured to provide an input reference voltage. The comparator circuit is configured to compare the input reference voltage to an input circuit voltage of a measured circuit and generate a digital measurement signal based on the comparison. To provide for the ACAL circuit to more precisely measure the input circuit voltage, the voltage reference generation circuit is programmable and is configured to a generate the input reference voltage based on a programmed reference voltage selection. In this manner, the ACAL circuit can be used to measure the input circuit voltage in an iterative manner based on different programmed input reference voltages for a more precise measurement of the input circuit voltage.

Abstract: Systems and methods include determination, for each of a plurality of discrete features, of statistics based on a number of occurrences of each discrete value of the discrete feature in the data, determination of first summary statistics based on the determined statistics, determine of a dissimilarity for each discrete feature based on the first summary statistics and on the statistics determined for the discrete feature, determination of candidate discrete features based on the determined dissimilarities, determination, for each of the candidate discrete features, of second summary statistics based on values of a continuous feature associated with each discrete value of the candidate discrete feature, determination of a deviation score for each of the candidate discrete features based on the second summary statistics, and transmission of the candidate discrete features for display in association with the continuous feature based on the determined deviation scores.

Abstract: Systems and methods include determination, determine, for each of a plurality of discrete features, of statistics for each discrete value of the discrete feature based on values of a continuous feature associated with the discrete value, determination, for each discrete feature, of first summary statistics based on the statistics determined for each discrete value of the discrete feature, determination, for each discrete feature, of a dissimilarity based on the first summary statistics determined for the discrete feature and on the statistics determined for each discrete value of the discrete feature, determination of candidate discrete features of the discrete features based on the determined dissimilarities, the candidate discrete features comprising less than all of the discrete features, determination, for each of the candidate discrete features, of second summary statistics based on values of the continuous feature associated with each discrete value of the candidate discrete feature, determine of a devi

Abstract: A system and method including determining, for a specified target measure column of a first dataset including a plurality of records, the metadata of the first dataset, including a probability distribution for the specified target column and dimension scores for the dimensions for the first dataset conditioned on the specified target measure column, where the first dataset comprises a plurality of columns including the at least one target measure column and a plurality of non-numeric, dimension columns for the records of the first dataset; determining, for a subset of data of the first dataset based on one or more specified variables, dimension scores for the dimensions of the subset of data approximately derived from the determined metadata of the first dataset; and providing recommendations of top contributors based on the approximated dimension scores of dimensions of the subset of data.

Abstract: The present disclosure involves systems, software, and computer implemented methods for measuring successful interactions with an insight tool. One example method includes receiving a request for insights for a data point of a data visualization. Insights for the data point are identified and presented in an insights interface in a user session. User interactions with the insights interface are tracked during the user session. A determination is made that the user session has completed. At least one insights success rule is identified for determining whether user sessions with the insights interface are successful. The one or more insights success rules are evaluated to determine whether the user session was successful. In response to determining that the user session was successful, a measure of success for the user session is recorded. In response to determining that the user session was unsuccessful, a measure of failure is recorded for the user session.

Abstract: The present disclosure involves systems, software, and computer implemented methods for generating insights based on numeric and categorical data. One example method includes receiving a request for an insight analysis for a dataset that includes at least one continuous feature and at least one categorical feature. Continuous features can have any value within a range of numerical values and categorical features are enumerated features that can have a value from a predefined set of values. A selection of a first continuous feature for analysis is received, and at least one categorical feature is identified for analysis. A deviation factor and a relationship factor are determined for each identified categorical feature. An insight score is determined for each identified categorical feature that combines the deviation factor and the relationship factor for the categorical feature. The insight score is provided for at least some of the identified categorical features.

Abstract: Systems, software, techniques and apparatuses are disclosed herein for facilitating context-based possession-less access to secure information. More specifically, the systems, software, techniques and apparatuses described herein eliminate the need for enterprises to provide employees with direct access to confidential or sensitive enterprise information. Instead, the confidential or sensitive enterprise information can be indirectly provided to and hidden by an access systems used by the employees to request the information prior to being provided to a corresponding resource. For example, in some embodiments, the confidential or sensitive enterprise information is provided to an access system with formatting instructions for hiding the confidential or sensitive enterprise information in a browser session.

Abstract: An access point that implements operating modes in which beacons may be selectively disabled. Beacons may be disabled when no device is actively associated through the access point. Beacons may be enabled in response to one or more triggers, which may include events such as a client forming an association through the access point following a probe request message identifying the access point. In addition, active beaconing may be triggered by user input or may occur during periodic brief intervals that allow client devices to discover the network identifier for the access point. Selective control of beaconing may lead to more effective wireless communication, particularly in areas where users congregate with computers implementing soft APs for personal networks.

Abstract: Embodiments provide recommendations to a guest of a hotel or other type of service industry. Embodiments receive input data including demographics data and preference data for a plurality of guests of the hotel, and receive a plurality of guest interest categories. Embodiments assign one or more keywords to each of the guest interest categories and extract a plurality of attributes from the input data concerning the guest. Embodiments perform semantic analysis to map the attributes to the guest interest categories and determine a plurality of guest similarity calculations comprising a similarity value each of the plurality of guests with every other plurality of guests. Embodiments then generate a plurality of guest interest categories predictions for each of the guests based on the determined guest similarity calculations.

Abstract: Systems, software, techniques and apparatuses are disclosed herein for facilitating context-based possession-less access to secure information. More specifically, the systems, software, techniques and apparatuses described herein eliminate the need for enterprises to provide employees with direct access to confidential or sensitive enterprise information. Instead, the confidential or sensitive enterprise information can be indirectly provided to and hidden by an access systems used by the employees to request the information prior to being provided to a corresponding resource. For example, in some embodiments, the confidential or sensitive enterprise information is provided to an access system with formatting instructions for hiding the confidential or sensitive enterprise information in a browser session.