Abstract: A system includes a server associated with a resource utilization, a database storing historical data including resource utilization values over a first time period, and a processor. The processor identifies, from the historical data, a maximum resource utilization value and determines a duration of time for which the resource utilization exceeds a percentage of the maximum. The processor predicts, based on the historical data, a maximum predicted resource utilization value over a second time period, later than the first. The processor also determines, based on the historical data, an upper bound of a resource utilization confidence interval. The processor generates, based on the maximum value over the first time period, the duration of time, the maximum predicted value over the second time period, and the upper bound, a recommendation to consolidate the server with a second server and/or to release computational resources. The processor transmits the recommendation to an administrator.

Abstract: An apparatus includes a processor. The processor extracts a column from an external source for import into a database configured to store a set of columns including a first and second column. The processor splits the entries of the import column into a set of terms. The processor generates a first, second, and third vector based on the frequency of each term of the set of terms in the first, second, and import columns, respectively. The processor determines a first similarity measure between the first and third vectors and a second similarity measure between the second and third vectors. The first similarity measure is greater than the second. In response, the processor provides an indication to a user that the first column is a mapping candidate for the import column, such that entries of the import column may be stored in the database as additional entries in the first column.

Abstract: An apparatus includes a processor. The processor extracts a column from an external source for import into a database configured to store a set of columns including a first and second column. The processor splits the entries of the import column into a set of terms. The processor generates a first, second, and third vector based on the frequency of each term of the set of terms in the first, second, and import columns, respectively. The processor determines a first similarity measure between the first and third vectors and a second similarity measure between the second and third vectors. The first similarity measure is greater than the second. In response, the processor provides an indication to a user that the first column is a mapping candidate for the import column, such that entries of the import column may be stored in the database as additional entries in the first column.

Abstract: An apparatus includes a processor. The processor extracts a column from an external source for import into a database configured to store a set of columns including a first and second column. The processor splits the entries of the import column into a set of terms. The processor generates a first, second, and third vector based on the frequency of each term of the set of terms in the first, second, and import columns, respectively. The processor determines a first similarity measure between the first and third vectors and a second similarity measure between the second and third vectors. The first similarity measure is greater than the second. In response, the processor provides an indication to a user that the first column is a mapping candidate for the import column, such that entries of the import column may be stored in the database as additional entries in the first column.

Abstract: Methods, systems, and computing platforms for mobile data communication are disclosed. Processor(s) may be configured to electronically receive a plurality of user mobile interaction data and storing the user mobile interaction data in a computer readable database over a threshold period of interaction time for a mobile device. The processor(s) may be configured to electronically process the user mobile interaction data with a machine learning controller based on a set of machine learning training data including predefined user activity data so as to output at least one most probable time vector. The processor(s) may be configured to electronically output the at least one most probable time vector to a notification processing module.

Abstract: A natural language processing system that includes an artificial intelligence (AI) engine and a tagging engine. The AI engine is configured to receive a set of audio files and to identify concepts within the set of audio files. The AI engine is further configured to determine a usage frequency for each of the identified concepts and to generate an AI-defined tag for concepts with a usage frequency that is greater than a usage frequency threshold. The tagging engine is configured to receive an audio file and to identify observed concepts within the audio file. The tagging engine is further configured to compare the observed concepts to the first set of concepts, to determine one or more observed concepts matches concepts linked with AI-defined tags, and to modify metadata for the audio file to include AI-defined tags.

Abstract: Methods, systems, and apparatuses for blockchain-based automated user matching are described herein. In some arrangements, a node within a decentralized peer-to-peer (e.g., P2P) network may receive match parameters from one or more computing devices associated with supply side entities and demand side entities. The node may execute one or more artificial intelligence algorithms to match the supply side entities with the demand side entities based on the received match parameters. In some instances, the artificial intelligence algorithms may be stored in a smart contract on a blockchain and the matching may be performed through execution of the smart contract by nodes of the decentralized P2P network.

Abstract: Methods, systems, and computing platforms for mobile data communication are disclosed. Processor(s) may be configured to electronically receive a plurality of user mobile interaction data and storing the user mobile interaction data in a computer readable database over a threshold period of interaction time for a mobile device. The processor(s) may be configured to electronically process the user mobile interaction data with a machine learning controller based on a set of machine learning training data including predefined user activity data so as to output at least one most probable time vector. The processor(s) may be configured to electronically output the at least one most probable time vector to a notification processing module.

Abstract: A method for creating a common platform graphical user interface is provided. The interface may enable a user to trigger a data load job from a tool. The tool may monitor file upload events, trigger jobs and identify lists of missing or problematic file names. The tool may run on a single thread, thereby consuming relatively less system resources than a multi-thread program to perform its capabilities. The tool may enable selection of file names using wildcard variables or keyword variables. The tool may validate a list of files received against a master file list for each data load job. The tool may receive user input relating to each data load job. The tool may generate a loop within the single thread to receive information. The tool may analyze the received information and use the received information to predict future metadata associated with future data load jobs.

Abstract: Methods, systems, and apparatuses for blockchain-based property management are described herein. According to a first embodiment of the disclosure, a plurality of computing systems may be established at a plurality of points along a supply chain associated with the manufacture, shipment, and sale of a physical property item. At each of the plurality of points, the plurality of computing systems may identify data corresponding to the physical property item, which may be stored on a blockchain associated with a decentralized peer-to-peer (e.g., P2P) network. According to a second embodiment of the disclosure, content creator computing devices may transmit digital property item upload requests to a digital property management computing device, which may generate smart contracts corresponding to the requests. Through execution of the smart contracts, access may be granted to digital property items and fees may be provided to the content creator computing devices.

Abstract: Some aspects disclosed herein are directed to, for example, a system and method comprising a client device receiving an input of at least a portion of a message. The client device may transmit, to a server device, the at least the portion of the message for display via a second client device. The client device may determine an identifier for the at least the portion of the message. The client device may determine, based on a lexicon, a marker name for the at least the portion of the message. The client device may generate an association between the marker name for the at least the portion of the message and the identifier for the at least the portion of the message. The client device may store, at a storage location, the marker name for the at least the portion of the message, the identifier for the at least the portion of the message, and the association between the marker name for the at least the portion of the message and the identifier for the at least the portion of the message.

Abstract: Embodiments of the invention are directed to intelligently and dynamically controlling both changes made within EUC applications and the control rules associated with such changes. A similarity index is calculated/assigned for each data entry field (i.e., cell/intersection) and the controls implemented when a changes to data in the entry fields occurs is based on the similarity index. In other embodiments, a change to data entry fields dynamically prompts analysis of the change based on historical approval and/or denial patterns specific to the EUC application, the data entry field(s) and/or the user of the application. In response to the analysis the control rules may be dynamically updated, and applied to the current change. In other embodiments, inputs, such as reviewer's comments, are the basis for determining a need to update existing controls or add new controls associated with data entry field(s) and the conditions associated therewith are determined and applied.

Abstract: A three dimensional user experience for mobile applications includes adjusting display of simulated three dimensional objects in real time and providing tactile feedback based on user interaction. A mobile application identifies a user viewing angle of a user and an orientation of the mobile device. An image analyze calibrates coordinates of the user with respect to the mobile device position and calculates pitch and roll elements of the simulated three dimensional objects with respect to a mobile device coordinate system. Based on rotational element, images are selected and/or rendered for display in real time. The mobile application analyzes an area of contact with a touchscreen and identify an edge of a selected simulated three dimensional object based on a color or color gradient. Based on a type of object and an edge type, tactile feedback is generated by triggering a vibration motor to execute a particular vibration pattern.

Abstract: The invention utilizes a plurality of robotic process automation (RPA) bots to generate data regarding production issues within applications. The RPA bots may simulate user access to the environment (i.e. user load) to predict possible issues or failures of the application within the particular environment. The RPA bots may further be used to identify the needs of an application when migrating the application from one environment to another. To this end, the bots may perform a dynamic simulation sequence for accessing applications, which may provide a realistic simulation of user load for an application within a certain environment. In this way, bots may be used to monitor and understand the complete runtime sequence and behavior of applications that would enable administrators to select the appropriate stack of modules of the destination infrastructure.

Abstract: A three dimensional user experience for mobile applications includes adjusting display of simulated three dimensional objects in real time and providing tactile feedback based on user interaction. A mobile application identifies a user viewing angle of a user and an orientation of the mobile device. An image analyze calibrates coordinates of the user with respect to the mobile device position and calculates pitch and roll elements of the simulated three dimensional objects with respect to a mobile device coordinate system. Based on rotational element, images are selected and/or rendered for display in real time. The mobile application analyzes an area of contact with a touchscreen and identify an edge of a selected simulated three dimensional object based on a color or color gradient. Based on a type of object and an edge type, tactile feedback is generated by triggering a vibration motor to execute a particular vibration pattern.

Abstract: A natural language processing system that includes an artificial intelligence (AI) engine and a tag management engine. The AI engine is configured to receive a set of audio files and to identify concepts within the set of audio files. The AI engine is further configured to determine a usage frequency for each of the identified concepts and to generate an AI-defined tag for concepts with a usage frequency that is greater than a usage frequency threshold. The tag management engine is configured to receive an audio file, identify tags linked with the audio file, to determine an access frequency for the audio file within a predetermined time period, and to adjust the activity level of the tags based on the access frequency. The tag management engine is further configured to remove tags from the set of tags with an activity level that is less than a purge threshold.

Abstract: A data manipulation detection device that includes an alert engine configured to receive data from a data source, apply a set of rules for a threat model to the data using a first machine learning model, and to obtain an alert vector in response to applying the set of rules to the data. The device further includes an alert feedback engine configured to receive alert feedback that includes text comments for the alert vector. The device further includes a natural language processing (NLP) training engine configured to identify the text comments for the alert status and identify keywords within the text comments associated with a rule parameter value for a rule. The NLP training engine is further configured to determine a new rule parameter value based on the identified keywords and modify a rule parameter value for the rule based on the new rule parameter value.

Abstract: The invention utilizes a plurality of robotic process automation (RPA) bots to generate data regarding production issues within applications. The RPA bots may simulate user access to the environment (i.e. user load) to predict possible issues or failures of the application within the particular environment. The RPA bots may further be used to identify the needs of an application when migrating the application from one environment to another. To this end, the bots may perform a dynamic simulation sequence for accessing applications, which may provide a realistic simulation of user load for an application within a certain environment. In this way, bots may be used to monitor and understand the complete runtime sequence and behavior of applications that would enable administrators to select the appropriate stack of modules of the destination infrastructure.

Abstract: Some aspects disclosed herein are directed to, for example, a system and method comprising a client device receiving an input of at least a portion of a message. The client device may display, on a display of the client device, the at least the portion of the message. The client device may transmit, to a server device, the at least the portion of the message for display via a second client device. The client device may receive, from a user of the client device or a user of the second client device, a request to generate a marker for the at least the portion of the message. In response to the receiving the request to generate the marker, the client device may determine, based on a lexicon, a name for the marker for the at least the portion of the message.

Abstract: Some aspects disclosed herein are directed to, for example, a system and method comprising a client device receiving an input of at least a portion of a message. The client device may display, on a display of the client device, the at least the portion of the message. The client device may transmit, to a server device, the at least the portion of the message for display via a second client device. The client device may receive, from a user of the client device or a user of the second client device, a request to generate a marker for the at least the portion of the message. In response to the receiving the request to generate the marker, the client device may determine, based on a lexicon, a name for the marker for the at least the portion of the message.