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: Apparatuses, systems and methods are described herein for separately collecting and storing form contents. Different information may be collected from a user on a form. Based on determining that portions of the form request a first type of information, an extended reality (XR) environment may be provided to the user. The user may provide the first type information via an input method in the XR environment. The user may provide a second type of information using a different input method outside of the XR environment. The first type of information may be processed and stored in a different database as compared to the second type of information. The database storing the first type of information may have a higher security standard than the database storing second type of information.

Abstract: A method includes receiving, with a computing system, data representing a video item into a buffer. The method further includes outputting the video item from the buffer to a display system. The method further includes determining that utilization of the buffer falls below a predetermined threshold. The method further includes, in response to determining that the utilization of the buffer falls below the predetermined threshold, determining that there is a specified rebuffering point within a predetermined time frame. The method further includes pausing with the computing system, the video item at the specified rebuffering point in response to determining that there is the specified rebuffering point within the predetermined time frame.

Abstract: A device detects a communication involving a user associated with an account and a service representative, and sends, to a user device associated with the account, an authentication notification that causes the user device to display an authentication field for the user. The device sends, to a service representative device associated with the service representative, a message that indicates that the service representative is to request, via the communication, the user to enter personal information associated with the user into the authentication field, where the user device is configured to generate a first authentication code based on a user input received from the user device in the authentication field. The device generates a second authentication code based on personal information associated with the account from a data structure, receives the first authentication code, and performs an action based on the first authentication code and the second authentication code.

Abstract: Randomizations of a web page may be generated in advance and provided to a client. The client may store the randomizations in its cache. Multiple randomizations for the same web page may be provided to the client and stored in the client's cache. When a request for a web page is made, it is determined if the client has any cached randomizations. Randomizations for the probable next web page to be requested by the client may be provided to the client for storage in the cache. For example, the probability that a link will be clicked or a website visited may be determined. Those web pages and websites with higher probabilities may be determined. Randomizations for those web pages are then provided to the client for use.

Abstract: Disclosed herein are system, method, and apparatus for generating labels for k-means clusters. The method includes accessing a plurality of data records from a database repository, and storing the plurality of data records into at least one of primary or secondary memory associated with at least one computer processor performing the method, along with a cluster number for each data record. All data records having a same cluster number form a cluster, and each record has been categorized or designated a cluster number out of a total K number of clusters. The method includes for each of a plurality of classification features, performing cluster-based analysis for a first cluster with respect to a single feature to generate a single feature overlap score. The method includes sorting, grouping, and generating a naming label for the first cluster based on the predetermined number of features having the lowest overlap scores.

Abstract: A playback application seamlessly advances playback of and interactive media title in response to user selections in a manner that minimizes latency and preserves user immersion in a narrative. The playback application buffers an interstitial segment included in the interactive media title and feeds portions of the interstitial segment to a media player only when those portions are needed for display. When the user selects an option displayed during the interstitial segment, the playback application begins buffering a subsequent media segment and stops feeding portions of the interstitial segment to the media player. The playback application starts feeding blocks of the subsequent media segment to the media player and then seamlessly advances playback to the subsequent media segment.

Abstract: Systems and methods for determining neural network brittleness are disclosed. For example, the 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 a modeling request comprising a preliminary model and a dataset. The operations may include determining a preliminary brittleness score of the preliminary model. The operations may include identifying a reference model and determining a reference brittleness score of the reference model. The operations may include comparing the preliminary brittleness score to the reference brittleness score and generating a preferred model based on the comparison. The operations may include providing the preferred model.

Abstract: Systems and methods for distorting CAPTCHA images with generative adversarial networks include an image distortion interface that can select an image record from a database, determine the size of the selected image, and apply an adversarial attack algorithm to create an array of pixels that is the same size as the selected image so that the majority of the pixels in the array are zero values and the remaining pixels in the array are in the red-green-blue value range. The image distortion interface can merge the array of pixels with the selected image to form a distorted image. A server can include a CAPTCHA test interface that can select a set of images having the same label, retrieve corresponding distorted images, and provide a CAPTCHA test using the distorted images. The CAPTCHA test can use distorted images with different applied adversarial attack algorithms.

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: Methods and systems disclosed herein describe using machine learning to lock and unlock a device. Machine learning may be trained to recognize one or more features. Once the device has been trained to recognize one or more features, a user may define an unlock condition for the device using the one or more trained features. After defining the unlock condition, the device may be locked by verifying the one or more features that the user defined as the unlock condition using machine learning. When verification is successful, the device may be unlocked and the user allowed to access the device.

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: A spectrometer is provided. In one implementation, for example, a spectrometer comprises an excitation source, a focusing lens, a movable mirror, and an actuator assembly. The focusing lens is adapted to focus an incident beam from the excitation source. The actuator assembly is adapted to control the movable mirror to move a focused incident beam across a surface of the sample.

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: Systems and methods mediate permissions for applications on user devices using predictive models. Data communications are monitored on a user device for permission requests and responses. A predictive model is trained with these permission requests and responses until a threshold is met. Then, a default permission response is provided on behalf of the user device in response to a permission request.

Abstract: A method includes receiving, with a computing system, data representing a video item into a buffer. The method further includes outputting the video item from the buffer to a display system. The method further includes determining that utilization of the buffer falls below a predetermined threshold. The method further includes, in response to determining that the utilization of the buffer falls below the predetermined threshold, determining that there is a specified rebuffering point within a predetermined time frame. The method further includes pausing with the computing system, the video item at the specified rebuffering point in response to determining that there is the specified rebuffering point within the predetermined time frame.

Abstract: In certain embodiments, presentation of candidate inputs may be facilitated based on a user interface location of a related candidate input. In some embodiments, a text input may be obtained via a user interface (e.g., via a virtual keyboard). A first candidate input related to the text input may be presented at a first location of the user interface. A first user selection with respect to the first candidate input may be obtained, and a candidate input set related to the first candidate input may be presented on the user interface based on the first user selection. As an example, the candidate input set may be presented such that a second candidate input is presented closer to the first location than a third candidate input based on the second candidate input being associated with a higher likelihood of being selected by a user than the third candidate input.

Abstract: In various embodiments, a localized video encoding application encodes localized videos. In operation, the localized video encoding application computes a prediction frame based on a target frame of a localized video and at least a portion of a reference frame of a decoded original video. The localized video encoding application computes a residual frame based on the prediction frame and the target frame of the localized video. The localized video encoding application performs one or more encoding operations on the residual frame to generate a frame of an encoded localization layer. The frame of the encoded localization layer and at least one frame of an encoded original video are subsequently transmitted to another device for decoding.

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.