Abstract: Systems, methods and apparatus are provided for a reusable, client-server based ecosystem designed to support content-aware, LiFi-powered transfer of large-scale, semi-structured data files. Containerized client-side applications may include a LiFi communication engine (LCE), a job control engine (JCE), and an execution hub that is configured to interface with the JCE, the LCE, job stakeholders and downstream applications. A central server may include a server-side LCE configured for two-way communication with the client-side LCE. Each LCE may be configured to cluster semi-structured data into data packets, broadcast data packets using an LED array, receive data packets using an array of photoreceptors and synchronize received data packets.

Abstract: Systems, computer program products, and methods are described herein for dynamic allocation of navigation tools based on learned user interaction. The present invention is configured to generate a training dataset based on at least the information associated with the interaction of the user with the one or more GUI grids, information associated with the one or more interactions of the one or more peers with the one or more GUI grids, information associated with the user, and information associated with the one or more peers; initiate one or more machine learning algorithms on the training dataset; receive, via the user computing device, a user selection of an unseen navigation tool for placement on the GUI; and classify the unseen navigation tool using the first set of parameters to predict a placement of the unseen navigation tool in at least one of one or more GUI grids associated with the GUI.

Abstract: A code repository stores application code. A code management determines, based at least in part on requested features selected in a graphical user interface, code requirements that include attributes of application code needed to achieve the requested features. The code management system determines, based at least in part on the determined code requirements and the metadata for each entry of application code stored in the code repository, one or more candidate application code entries from the code repository. The code management system presents the candidate application code entries for user selection in the graphical user interface. After receipt of a user selection of a selected application code, the selected application code is provided to a computing device associated with the user.

Abstract: The present invention generally relates to the field of automated and flexible information extraction and protection for graphical data. In particular, the invention provides a unique platform for analyzing, classifying, extracting, and processing information from images using deep learning image detection models. Embodiments of the inventions are configured to provide an end to end automated solution for intelligently hiding or obscuring private data from graphical displays via the use of embedded steganographic image data techniques.

Abstract: Aspects of the disclosure relate to using synthetic DNA stranding and mutant nucleotide processes to conduct enterprise market volatility predictions. In some embodiments, a computing platform may receive raw market data from a plurality of lines of business of an enterprise organization. Thereafter, the computing platform may preprocess the raw market data to obtain enterprise level market data, execute synthetic DNA stranding of the enterprise level market data to obtain synthetic DNA stranded market data, run the synthetic DNA stranded market data through one or more market volatility models, and compile results from the market volatility models on the synthetic DNA stranded market data. The computing platform may transmit results from the market volatility models on the synthetic DNA stranded market data. The transmitted results may be configured to display a market application interface that includes market volatility forecasting parameters based on results of the market volatility models.

Abstract: A code repository stores application code. A code management determines, based at least in part on requested features selected in a graphical user interface, code requirements that include attributes of application code needed to achieve the requested features. The code management system determines, based at least in part on the determined code requirements and the metadata for each entry of application code stored in the code repository, one or more candidate application code entries from the code repository. The code management system presents the candidate application code entries for user selection in the graphical user interface. After receipt of a user selection of a selected application code, the selected application code is provided to a computing device associated with the user.

Abstract: Aspects of the disclosure relate to using synthetic DNA stranding and mutant nucleotide processes to conduct enterprise market volatility predictions. In some embodiments, a computing platform may receive market data from a plurality of lines of business across an enterprise, wherein the market data is received in a raw, uncompressed format. Thereafter, the computing platform may assimilate and preprocess the market data to output vectored market data. The computing platform may perform a synthetic DNA stranding process on the vectored market data to create one or more strands of synthetic DNA market data, and output the one or more strands of synthetic DNA market data to a synthetic DNA client server, wherein the one or more stands of synthetic DNA market data is configured for input in a market volatility prediction model.

Abstract: Aspects of the disclosure relate to using synthetic DNA stranding and mutant nucleotide processes to conduct enterprise market volatility predictions. In some embodiments, a computing platform may initiate a set of instructions associated with performing an action on a synthetic DNA market data set associated with a plurality of lines of business across an enterprise organization. Thereafter, the computing platform may convert the set of instructions to a mutant nucleotide sequence, and insert the mutant nucleotide sequence into the synthetic DNA market data set. The computing platform may extract, using the mutant nucleotide sequence, target information from the synthetic DNA market data set, and validate the target information to detect one or more anomalies. The computing platform may remove the one or more data anomalies, and subsequently output a validated synthetic DNA market data set to a synthetic DNA client server.

Abstract: Systems, computer program products, and methods are described herein for generating an execution sequence using learning reinforcement. The present invention is configured to electronically receive one or more requirement modules from one or more computing devices associated with one or more resource development teams; store the one or more requirement modules in a resource development pipeline, wherein the one or more requirement modules are in a first order of execution; initiate a reinforcement learning algorithm on the one or more requirement modules; determine, using the reinforcement learning algorithm, a final order of execution for the one or more requirement modules; initiate a reordering of the one or more requirement modules from the first order of execution to a final order of execution; and initiate an execution of the one or more requirement modules in the final order of execution.

Abstract: An Automated Teller Machine (ATM) for detecting security vulnerabilities by removing noise artifacts from documents receives a transaction request when a document is inserted into the ATM, where the document contains a noise artifact at least partially obstructing a portion of the document. The ATM generates an image of the document, where the image displays at least one data item comprising a sender's name, a receiver's name, and a number representing an amount. The ATM determines whether the noise artifact obstructs at least partially one data item. In response to determining that the noise artifact obstructs at least partially one data item, the ATM generates a test clean image of the document by removing the noise artifact from the image. In response to determining that the noise artifact is removed, the ATM approves the transaction request.

Abstract: The present invention generally relates to the field of automated and flexible information extraction and protection for graphical data. In particular, the invention provides a unique platform for analyzing, classifying, extracting, and processing information from images using deep learning image detection models. Embodiments of the inventions are configured to provide an end to end automated solution for intelligently hiding or obscuring private data from graphical displays via the use of embedded steganographic image data techniques.

Abstract: An apparatus includes a processor and a memory that stores a deep Q reinforcement learning (DQN) algorithm configured to generate an action, based on a state. Each action includes a recommendation associated with a computational resource. Each state identifies at least a role within an enterprise. The processor receives information associated with a first user, including an identification of a first role assigned to the user and computational resource information associated with the user. The processor applies the DQN algorithm to a first state, which includes an identification of the first role, to generate a first action, which includes a recommendation associated with a first computational resource. In response to applying the DQN algorithm, the processor generates a reward value based on the alignment between the first recommendation and the computational resource information associated with the first user. The processor uses the reward value to update the DQN algorithm.

Abstract: A system for adapting an image noise removal model based on a device processing capability receives, from a computing device, a request to adapt an image noise removal module for the computing device. The system compares a processing capability of the computing device with a threshold processing capability. The system determines whether the processing capability is greater or smaller than the threshold processing capability. In response to determining that the processing capability is greater than the threshold processing capability, the system sends a version of the image noise removal module that is adapted for computing devices with processing capabilities less than the threshold processing capability, where the version of the image noise removal module is adapted to have a number of neural network layers less than a threshold number of neural network layers.

Abstract: A code converter uses machine learning to determine conflicts and redundancies in software code. Generally, the code converter uses machine learning to convert software code into vectors that represent the code. These vectors may then be compared with other vectors to determine similarities between code. The similarities may be used to detect conflicts and/or redundancies created during the development process (e.g., when a developer attempts to change the code).

Abstract: Systems, computer program products, and methods are described herein for preserving image and acoustic sensitivity using reinforcement learning. The present invention is configured to initiate a file editing engine on the audiovisual file to separate the audiovisual file into a video component and an audio component; initiate a convolutional neural network (CNN) algorithm on the video component to identify one or more sensitive portions in the one or more image frames; initiate an audio word2vec algorithm on the audio component to identify one or more sensitive portions in the audio component; initiate a masking algorithm on the one or more image frames and the audio component; generate a masked video component and a masked audio component based on at least implementing the masking action policy; and bind, using the file editing engine, the masked video component and the masked audio component to generate a masked audiovisual file.

Abstract: An apparatus configured to construct an email message addressed to a plurality of recipients. The apparatus is further configured to apply a cipher and a first encryption key to a first portion of the email message, which will be viewable by each of the recipients. The apparatus applies the cipher and a second encryption key to a second portion of the email message, which will be viewable by a first recipient from among the recipients. The apparatus further applies the cipher and a third encryption key to a third portion of the mail message, which will be viewable by a second recipient from among the recipients. The apparatus then transmits the email message to a server.

Abstract: A system for removing a noise artifact from an image of a document extracts a first set of features from the image, where the first set of features represents items on the image. The system identifies noise artifact features from the first set of features representing pixel values of the noise artifact. The system generates a second set of features by removing the noise artifact features from the first set of features. The system generates a test clean image of the document based on the second set of features as an input. The system determines whether a portion of the test clean image that previously displayed the noise artifact corresponds to a counterpart portion of the training clean image. If it is determined that the portion of the test clean image corresponds to the counterpart portion of the training clean image, the system outputs the test clean image.

Abstract: A method for providing graph data is described. A request for graph data based on a data graph is received, the data graph having i) nodes representing entities associated with an enterprise organization, and ii) edges between nodes representing relationships among the entities. A search embedding corresponding to the request is generated. Embeddings from a set of embeddings that are adjacent to the search embedding are identified, wherein the set of embeddings represent the data graph. Graph data corresponding to the identified embeddings is provided in response to the request.

Abstract: A code tracking system monitors usage of application code executed by one or more computing devices. Characteristics of the usage of the application code are determined. Using the characteristics of the usage of the application code, a modification to an entry of application code executed by the one or more computing devices is detected. The detected modification to the entry of application code is communicated to a code management system. The code management system presents the modification to the entry of the application code to a user of the code management system.

Abstract: A system accesses a first digital audio file that includes a plurality of spoken instructions. The system converts the first digital audio file to a first spectrogram image, applies a filter to determine whether an image quality of the first spectrogram image is below a predetermined image quality, and in response, generates a second spectrogram image from the first spectrogram image using a training model. The system converts the second spectrogram image to a second digital audio file and converts the second digital audio file into multiple vectors that each correspond to a particular spoken instruction. The system identifies related vectors and concatenates the related vectors together in order to create a plurality of concatenated vectors. The system generates, using the plurality of concatenated vectors, a third digital audio file that includes concatenated spoken instructions from the first digital audio file.