Abstract: An exemplary system, method, and computer-accessible medium can include, for example, receiving an original dataset(s), receiving a synthetic dataset(s), training a model(s) using the original dataset(s) and the synthetic dataset(s), and evaluating the synthetic dataset(s) based on the training of the model(s). The model(s) can include a first model and a second model, and the first model can be trained using the original dataset(s) and the second model can be trained using the synthetic dataset(s). The synthetic dataset(s) can be evaluated by comparing first results from the training of the first model to second results from the training of the second model.

Abstract: Disclosed are examples for adjusting screen brightness based on screen content being presented on a display screen of a mobile device. The described examples may determine a time at which the screen content is to be evaluated. The screen content is categorized based on the evaluation. A category of the screen content may be input into a machine learning algorithm that may be used to determine whether a screen brightness adjustment is appropriate. If a screen brightness adjustment is appropriate, a degree of the screen brightness adjustment may be determined.

Abstract: Various embodiments for a system to utilize user's location pattern as an authentication parameter are disclosed. An embodiment operates by retrieving a location history of a user based on past locations of a user equipment (UE) device at various times and traffic data associated with the location history. A request to access a protected application is received and a present location of the UE device at a time associated with the request is determined. A locational pattern is generated based on both the location history of the user and the traffic data. The present location of the UE device is compared with the locational pattern, and it is determined that a level of authentication necessary to grant access to the protected application is satisfied based on both the comparing and a determination that the present location falls within the locational range generated based on the traffic data.

Abstract: Example embodiments of systems and methods for providing a video call between a first party and a second party. The method includes detecting an attempt to establish the video call by monitoring a voice call between the first party and the second party; authenticating the first and second parties; receiving from the first and second parties respective voice acceptances to invitations to establish the video call; retrieving video call identifications of the first and second parties; and establishing the video call without revealing the video call identification of the first party to the second party and the video call identification of the second party to the first party.

Abstract: In some implementations, a training platform may receive data for generating synthetic models of a body part, such as a hand. The data may include information relating to a plurality of potential poses of the hand. The training platform may generate a set of synthetic models of the hand based on the information, where each synthetic model, in the set of synthetic models, representing a respective pose of the plurality of potential poses. The training platform may derive an additional set of synthetic models based on the set of synthetic models by performing one or more processing operations with respect to at least one synthetic model in the set of synthetic models, and causing the set of synthetic models and the additional set of synthetic models to be provided to a deep learning network to train the deep learning network to perform image segmentation, object recognition, or motion recognition.

Abstract: A system for determining candidate answers during an interview. The system may include a memory storing executable instructions, and at least one processor configured to execute the instructions to perform operations. The operations may include capturing, by an image sensor, a plurality of images comprising a plurality of candidate answers; detecting, based on the captured images, a first bounding box comprising the plurality of the candidate answers; detecting, based on the captured images, a second bounding box comprising a plurality of alphanumeric characters, a first one of the alphanumeric characters being located on a line of software code; calculating a distance from a side of a first bounding box to a side of a second bounding box; and determining, based on the calculated distance, a source code alignment.

Abstract: A computer-implemented method includes tracking, by a computing device, user browsing activity of a first page having known elements; mapping, by the computing device, the user browsing activity to the known elements; storing, by the computing device, mapping information that maps the user browsing activity to the known elements; tracking, by the computing device, user browsing activity of a second page having unknown elements; identifying, by the computing device, the unknown elements based on the mapping information and the user browsing activity of the second page; and executing, by the computing device, one or more computer-based instructions based on the determining the unknown elements that were identified.

Abstract: Logic may assign a customer identification to a model to associate a first customer with the model to detect fraudulent transactions. Logic may determine one or more clusters to associate with the first customer based on characteristics associated with the first customer. Logic may associate one or more cluster identifications with the first customer. Each cluster identification may identify one cluster of the one or more clusters. Each cluster may identify a group of customers based on characteristics associated with the group of customers. Logic may cause the model to transmit to a customer device associated with the first customer. Logic may receive transaction data for a transaction for one customer of the group of customers associated with a first cluster. And logic may communicate modified transaction data to customer devices of more than one customer of the group of customers associated with the first cluster.

Abstract: A system and method of generating one or more integration tests are disclosed herein. A computing system receives a URL from a client device. The URL corresponds to a website hosted by a third party server. The computing system generates a recurrent neural network model for testing of the website. The one or more variables associated with the recurrent neural network model are defined by a genetic algorithm. The computing system inputs code associated with the website into the recurrent neural network model. The recurrent neural network model learns a plurality of possible paths through the website by permutating through each possible set of options on the website. The recurrent neural network mode generates, as output, a plurality of integration tests for at least the test website. The computing system compiles the plurality of integration tests into a format compatible with a testing service specified by the client device.

Abstract: An example described herein may involve receiving a temperature measurement associated with an input component, wherein the temperature measurement is received from a temperature sensor, and wherein the temperature measurement indicates a temperature of an input element of the input component; determining that the temperature of the input element satisfies a threshold temperature; and causing an infrared element to emit infrared light in association with a position of the input component. While the infrared element is emitting the infrared light, capture information associated with a user interacting with the input component may be obfuscated.

Abstract: Systems and methods for clustering data are disclosed. For example, a system may include one or more memory units storing instructions and one or more processors configured to execute the instructions to perform operations. The operations may include receiving data from a client device and generating preliminary clustered data based on the received data, using a plurality of embedding network layers. The operations may include generating a data map based on the preliminary clustered data using a meta-clustering model. The operations may include determining a number of clusters based on the data map using the meta-clustering model and generating final clustered data based on the number of clusters using the meta-clustering model. The operations may include and transmitting the final clustered data to the client device.

Abstract: A server device may receive information identifying a user of a first device participating in a screen sharing session with a second device and associate the information identifying the user of the first device with information indicating a sequence of interactions with an application at the first device. The server device may determine one or more user interface elements that correspond to a current view of the application at the first device based on the sequence of interactions, and transmit, to the second device, information identifying the one or more user interface elements that correspond to the current view to permit the second device to reconstruct the current view based on the information identifying the one or more user interface elements that correspond to the current view and stored information related to a plurality of views associated with the application.

Abstract: Exemplary embodiments may use word embeddings to enhance scanning of programming code scripts for sensitive subject matter, such as confidential subject matter. The scanning may be performed by a neural network in some exemplary embodiments. The neural network initially may be trained on a corpus of programming code scripts to identify keywords relating to sensitive subject matter, such as passwords, tokens or credentials. The neural network may not only identify instances of the keywords but also may identify related terms as well. The output of the scan may be a ranked list of terms in the programming code script that may relate to sensitive subject matter.

Abstract: Techniques for providing a real-time service that protects personal data of clients from customer service agents are provided. Customer data that includes personal data indicative of sensitive information of a customer can be received from the customer. The personal data within the received customer data can be detected and a token that does not include the sensitive information of the customer can be generated. The personal data and the generated token can be stored along with data indicating a relationship between the token and the personal data. The personal data in the received customer data can be replaced by the token to form modified customer data. The modified customer data can be provided to a customer service representative. The token within the modified customer data can later be detected and associated with the personal data without revealing the personal data to the customer service representative.

Abstract: A non-transitory computer-readable storage medium storing computer-readable program code executable by a processor to receive a transaction request from a user interface, and receive a user-identifier from the user interface, and the user-identifier associated with a user. The program code may be executable to send a first non-audible sound signal to initiate a multifactor authentication process during a first interval, and send a second non-audible sound signal during a second interval, where the second non-audible sound signal comprises a predetermined frequency pattern, associated with the user. The program code may also be executable to receive a third non-audible sound signal, where the third non-audible sound signal, at least in part, is utilized to determine whether to complete the transaction request or not. The first non-audible sound signal, the second non-audible sound signal, and the third non-audible sound signal may comprise a frequency greater than 15 kHz.

Abstract: Systems as described herein may label data to preserve privacy. An annotation server may receive a document comprising a collection of text representing a plurality of confidential data from a first computing device. The annotation server may convert the document to a plurality of text embeddings. The annotation server may input the text embeddings into a machine learning model to generate a plurality of synthetic images, and receive a label for each of the plurality of synthetic images from a third-party labeler. Accordingly, the annotation server may send the confidential data and the corresponding labels to a second computing device.

Abstract: Various embodiments are generally directed to provide a semi-local authentication scheme. A server can transmit one or more encryption mechanisms to a user device, which in turn can transmit the encrypted mechanisms to one or more secondary devices associated with the user device, where the user device and the secondary devices share a local connection. The secondary devices can transmit the one or more encrypted mechanism utilizing one or more one or more decryption mechanisms supplied by the server, and then transmit the result of the decryption, e.g. decrypted codes, back to the user device, which in turn can then transmit a final decrypted code or codes to the server. Upon confirming receipt of the decryption from the user device, the server can authorize access (via the user device) to one or more devices, networks, applications, and/or components.

Abstract: Systems and methods for dynamically concealing sensitive information in a shared screen session of a video conference are disclosed. The system may establish communication with one or more computing devices active in a video conference in which each computing device may switch between a screen share mode and a video mode. The system may determine that one or more articles of sensitive information are visible in a graphical user interface associated with a first computing device of the plurality of computing devices. The system may receive a first signal from the first computing device that indicates a first intent of a host associated with the first computing device to switch the screen share mode which includes sharing the first graphical user interface with the one or more computing devices during the video conference. In response to the first signal, the system may execute one or more privacy actions.

Abstract: System and devices for live captioning events is disclosed. The system may receive event calendar data and a first plurality of caption files and preselect a first caption file based on the event calendar data. The system may then access an audiovisual recorder of a user device, and receive a first feedback from the recorder. The system may then determine whether the first caption file matches the first feedback. When there is a match, the system may determine a first synchronization between the caption file and the feedback. When there is no match, the system may determine if there is a match with a second caption file of the first plurality of caption files and determine a second synchronization. When the second caption file does not match, the system may receive at least a third caption file over a mobile network and determine a third synchronization for display.

Abstract: Logic may adjust communications between customers. Logic may cluster customers into a first group associated with a first subset of synonyms and a second group associated with a second subset of the synonyms. Logic may associate a first tag with the first group and with each of the synonyms of the first subset. Logic may associate a second tag with the second group and with each of the synonyms of the second subset. Logic may associate one or more models with pairs of the groups. A first pair may comprise the first group and the second group. The first model associated with the first pair may adjust words in communications between the first group and the second group, based on the synonyms associated with the first pair, by replacement of words in a communication between customers of the first subset and customers of the second sub set.