Abstract: A data-driven data management system and data management method are provided. The data-driven data management system includes a storage device and a processor. The storage device is configured to store multiple process models. The processor is coupled to the storage device and configured to receive a setting data set. The processor performs a second compilation on the multiple assembly data sets to combine the multiple assembly data sets into multiple process data sets. The data-driven data management system and data management method of the disclosure are adapted to automatically perform two compilations on the setting data set according to the multiple process models, and then combine assembly data corresponding to the setting data set into the multiple process data sets.

Abstract: A method and Graphic User Interface (GUI) system of data analysis for training a discriminative machine learning model are provided. One or more sets of data are provided to a large language model (LLM) for a predefined task with or without prompts provided by a user; the results output by the LLM is compared with a set of initial human-supplied ground truth data generated by the user to produce performance metrics, the user may provide or update one or more prompts for the LLM based on the performance metrics till the performance metrics reach a threshold. The set of initial human-supplied ground truth data and the results of the LLM can be used to train a discriminative machine learning model.

Abstract: The disclosure provides a data simulation system and a data simulation method. The data simulation system includes an execution engine and a database. The execution engine includes a type matcher, an executor, and an analyzer. The type matcher receives a simulation command and generates a simulation logic group according to a simulation type in the simulation command. The executor executes simulation processing on data according to the simulation logic group to generate a simulation result. The analyzer determines a matching degree between the simulation result and a preset result according to the simulation type. When the matching degree is less than a threshold value, the analyzer adjusts the simulation logic group and commands the executor to execute the simulation processing repeatedly. When the matching degree is greater than the threshold value, the analyzer stores the simulation logic group.

Abstract: In one general aspect, a method may include selecting eligible row-versions for inspection. The method may also include inspecting the selected row-versions, where the inspection results in a classification of eligible row-versions as unneeded or reliant. The method may furthermore include marking row-versions classified as unneeded as approved for immediate removal. The method may, in addition, include adding row-versions classified as reliant on cleaner structures. The method may moreover include upon detection of removal of all point-in-times (PiTs) related to a reliant row-version, deleting the reliant row-version, where the detection is performed by monitoring the cleaner structures. Other embodiments of this aspect include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods.

Abstract: Methods, devices, and computer-program products are provided for adding data to a digital video signal in a visually imperceptible manner. For example, a region of pixels can be identified in a video frame, and one or more pixel characteristics of the region of pixels can be determined. Based on the one or more pixel characteristics of the region of pixels, at least one pixel characteristic of a subset of pixels from the region of pixels can be modified in order to encode a set of data into the region of pixels. An output frame can be provided that includes the modified at least one pixel characteristics for the subset of pixels.

Abstract: There is provided a method of monitoring performance of a machine learning model externally to the machine learning model, comprising: monitoring data elements being fed into a machine learning model trained on a training dataset of historical training data elements, wherein the data elements are each associated with a respective time after the time associated with the training dataset, analyzing the data elements for identifying shift(s) between at least two subsets of the data elements, computing according to the shift(s), measurement(s) denoting an expected effect on output of the model, and detecting a misclassification event by the model when the measurement(s) exceeds a threshold of the model, wherein the monitoring, the analyzing, the computing, and the detecting are performed externally to the model, without accessing at least one of: data stored within the machine learning model, an implementation of the model, and data structures of the model.

Abstract: Portable blockchain mining systems and methods of use are discussed here. Systems include a portable building; a plurality of blockchain mining processors mounted within, or a plurality of blockchain mining processor mounts located within, an interior of the portable building; an air inlet defined in the portable building; and an air outlet defined in the portable building. Air outlets may be above the air inlet and oriented to direct exhaust air in an upward direction out of the portable building. A cooling fan may be connected to convey air through the air inlet, across the plurality of blockchain mining processors and out the air outlet. The cooling fan may simultaneously cool a genset and processors 72. Compact, stackable mining modules are discussed.

Abstract: A data displaying system and a data displaying method are provided. The data displaying system includes a storage device and a processor. The processor executes a plurality of modules in the storage device. A collection module accesses a database to retrieve historical display data. The historical display data include a plurality of fields. An analysis module calculates a plurality of length values of the historical display data in the respective fields to generate length data. The analysis module counts a distribution of the length data and generates target field widths corresponding to the fields based on a threshold and the distribution of the length data. An interface module outputs the target field widths to an electronic device, which allows the electronic device to display current display data in the electronic device based on the target field widths and thus improve user experience.

Abstract: A method for responding to access requests, the method may include (a) detecting, by a controller of a local storage system (LSS), a read pattern that (i) is associated with a requestor that is in communication with the LSS, and (ii) is estimated to comprise future read requests that are aimed to a remote part of a file system entity (FSE) that is stored at a remote storage system (RSS); wherein there is a latency difference between a remote latency associated with the remote part of the FSE and a LSS latency that is associated with the requestor; and (b) performing a prefetch process of remote sub-parts of the remote part of the FSE in order to support the read pattern while maintaining a desired latency.

Abstract: A multi-language conversion device and a multi-language conversion method are provided. The multi-language conversion device includes a storage device and a processor. The storage device is configured to store a multi-language template configuration. The processor is coupled to the storage device and configured to receive a request instruction. The processor obtains aggregated data corresponding to the request instruction according to the request instruction. The processor performs type matching on a calling type and the multi-language template configuration according to the calling type of the request instruction, so as to obtain a corresponding multi-language template. The processor performs multi-language conversion on the aggregated data according to the multi-language template to obtain converted data.

Abstract: The present disclosure is directed to systems and methods for extracting unstructured data from a data source in a structure manner. Embodiments provide ways to retrieve unstructured data along from data sources not optimized for automated retrieval. For example, embodiments may generate a branched tree for each data source that maps out paths to individual sites of, for example, a healthcare provider listing the unstructured data. Using this branched tree, tasks can be generated to navigate along a path with the data source to each site and extract the unstructured data from the data source. In this way, embodiments provide the ability to navigate through a site from a base site to a site that has the relevant data.

Abstract: A method for fetching a content from a web server to a client device is disclosed, using tunnel devices serving as intermediate devices. The client device accesses an acceleration server to receive a list of available tunnel devices. The requested content is partitioned into slices, and the client device sends a request for the slices to the available tunnel devices. The tunnel devices in turn fetch the slices from the data server, and send the slices to the client device, where the content is reconstructed from the received slices. A client device may also serve as a tunnel device, serving as an intermediate device to other client devices. Similarly, a tunnel device may also serve as a client device for fetching content from a data server. The selection of tunnel devices to be used by a client device may be in the acceleration server, in the client device, or in both.

Abstract: Techniques are disclosed to detect, isolate, and/or mitigate an attack on a file system, for example, by malicious software, human actors, and/or compromised Internet-connected devices (bots). A processor of a data processing system detects an abnormal file system access pattern to a file system by applying statistical process control to network layer packets. Based on detecting the abnormal file system access pattern, the processor temporarily suspends file system access by at least one user ID contributing to the abnormal file system access pattern. The processor provides a notification identifying one or more file system object accessed in the abnormal file system access pattern.

Abstract: A setting tool is disclosed for setting an acoustic telemetry unit in tubing, such as wellbore tubing. The setting tool comprises an anchor motor for driving an expandable anchor, a control unit for controlling the anchor motor, and an acoustic receiver. The control unit is arranged to determine whether an acoustic signal is successfully received by the acoustic receiver and to control the anchor motor in dependence thereon. By providing the setting tool with the acoustic receiver and determining whether an acoustic signal is successfully received by the acoustic receiver, it can be judged whether an acoustic signal from another acoustic telemetry unit in the tubing can be successfully received by the acoustic telemetry unit which is being set. This may facilitate deployment of a repeater unit at an optimum distance from another acoustic telemeter unit which is already in the tubing.

Abstract: Apparatuses, systems, methods, and program products are disclosed for techniques for distributed computing and storage. An apparatus includes a processor and a memory that includes code that is executable to receive a request to perform a processing task, transmit at least a portion of the processing task to a plurality of user node devices, receive results of the at least a portion of the processing task from at least one of the plurality of user node devices, and transmit the received results.

Abstract: A system designed for increasing network communication speed for users, while lowering network congestion for content owners and ISPs. The system employs network elements including an acceleration server, clients, agents, and peers, where communication requests generated by applications are intercepted by the client on the same machine. The IP address of the server in the communication request is transmitted to the acceleration server, which provides a list of agents to use for this IP address. The communication request is sent to the agents. One or more of the agents respond with a list of peers that have previously seen some or all of the content which is the response to this request (after checking whether this data is still valid).

Abstract: A system, method, device, and data platform for generating a tax return utilizing a data platform. Client data is aggregated for a client from available source to generate a client profile. A relevant tax return strategy is determined based on the client data. A template tax return is automatically created based on the relevant tax return strategy. The template tax return is populated with the client data to generate the tax return for the client.

Abstract: Techniques and systems are provided for identifying a video segment displayed on a screen of a remote television system, and providing an option to switch to an alternative or related version of the video program that includes the video segment. For example, video segments displayed on a screen of a television system can be identified, and contextually-targeted content or contextually-related alternative content can be provided to a television system based on the identification of a video segment. The alternative or related version of the video program can include the currently displayed program in an on-demand format that can be viewed off-line and can be started over from a beginning portion of the program.

Abstract: The present invention relates to a method of concurrently storing visible grey scale or color information of an image and additional digital information on a data carrier.

Abstract: The present invention relates to methods and devices for high-speed reading out information from an at least partially transparent data carrier.