A computer system for controlling exchange of data between users sharing data of a green technology project on a digital platform may include a platform device, which may store profiles of the users in a platform structure that may include layers to which the user profiles may be assigned depending on a user type. The platform device may be configured to receive project data, project criteria and basic criteria of a user having a user profile assigned to a first layer from a first terminal device, transmit the received project criteria to terminal devices, receive, from a second terminal device, a request of another user to access the project data and permit said user to access the project data if a set of project criteria and basic criteria of said user match with a set of project criteria and basic criteria of the user assigned to the first layer.

A non-transitory computer readable medium with an executable revision history integration program for causing at least one computer executes: a procedure for acquiring data on at least one document having at least one editing history including a name of an editor of the document; a procedure for collectively converting at least one name of an editor included in the editing history in the acquired data; and a procedure for deleting addition and deletion histories where a character string in the acquired data has been added and deleted by the same editor's name, as a result of the conversion of the name of the editor.

A process mining system performs process mining using visual logs generated from video streams of worker devices. Specifically, for a given worker device, the process mining system obtains a series of images capturing a screen of a worker device while the worker device processes one or more tasks related to an operation process. The process mining system determines activity labels for a plurality of images. An activity label for an image may indicate an activity performed on the worker device when the image was captured. The activity label is determined by extracting information from pixels of the image and inferring the activity of the worker device from the extracted information. The process mining system generates event logs from the visual logs of worker devices and uses the event logs for process mining.

Systems and methods thereof, of generating a unique identification code for an industrial commodity. The method includes receiving a user query indicative of at least one constructional and operational characteristic of the commodity, inspecting the user query to determine whether the user query is complete for identification of the commodity, updating the user query based on the inspection, identifying at least one attribute of the commodity from the updated user query, based on a list of predefined attributes of the commodity, mapping the at least one attribute to at least one of predefined attribute types, predefined regional standards, predefined commodity rules, and predefined commodity types, and generating the unique identification code for the commodity, based on the mapping. The predefined attribute types may be a predefined commodity group and a predefined commodity part.

Apparatuses, methods, program products, and systems are disclosed for an intelligent knowledge platform. An apparatus includes a processor and a memory. The memory stores code executable by the processor to receive data associated with a project, the data describing one or more characteristics of the project; determine, using machine learning rules and algorithms, one or more metadata tags for the data for classifying the data; match the classified data to one or more predetermined knowledge insights for the project based on the metadata tags, the one or more predetermined knowledge insights stored in a knowledge database; and present, on a digital display device, the one or more predetermined knowledge insights.

The present disclosure relates to a networked environment for incident response. In accordance with one aspect, a central system for incident response includes an electronic storage that stores an incident response template having time-relative tasks and contact information for an incident response team, a communication device configured to communicate with a plurality of devices corresponding to at least some of the contact information, one or more processors, and at least one memory storing instructions. The devices include a lead device and mobile devices. The instructions, when executed by the processor(s), cause the central system to receive via the communication device an activation of the incident response template from the lead device at an activation time, schedule an activated incident response based on the activation including scheduling the time-relative tasks based on the activation time, and communicate via the communication device with the mobile devices regarding the activated incident response.

A system for evaluating communication of a participant in a team setting including communication data of at least one participant, a computational infrastructure configured to receive the communication data and transpose the communication data into a machine-readable transcription, a communication representation platform configured to receive the machine-readable transcription wherein the communication representation platform selects at least one data set from the machine-readable transcription, applies a linear algebra technique to the at least one data set, and generates at least one score for the at least one data set, and a human-comprehensible output including at the least one score generated by the communication representation platform.

The subject matter herein provides a method, apparatus and computer program product that combines, in one intuitive interface, visualization user interfaces (UIs) as used for descriptive analytics, with workflow UIs as used for predictive analytics. These interfaces provide a visual workspace front-end. The workspace is coupled to a back-end that comprises a data processing engine that combines progressive computation, approximate query processing, and sampling, together with a focus on supporting user-defined operations, to drive the front-end efficiently and in real-time. The processing engine achieves rapid responsiveness through progressive sampling, quickly returning an initial answer, typically on a random sample of data, before continuing to refine that answer in the background. In this manner, any operation carried out in the platform immediately provides a visual response, regardless of the underlying complexity of the operation or data size.

This document describes the autonomous collection, generation, distribution, and management of online web content. The devices, systems, and methods described herein can be used to collect and generate online web content and communications in an automatic and autonomous manner. Specifically, the disclosed methods, devices, and systems may be employed to produce one or more communications and/or advertising campaigns, as well as for monitoring, managing, defining the efficiency, effectiveness, and workability of the campaign with respect to generating predicted user engagements, thereby accurately determining the cost benefits of the communication campaign. The system may track, evaluate, and provide analytic results that may then be used to better guide the system parameters for customizing autonomous communications directed one or more characteristics of a defined target audience.

Techniques to automate various aspects related to construction projects, including but not limited to, creation of schedules, verification of construction progress, estimation of costs, updating of schedules, creation and estimation of construction status, use of information generated by construction equipment, and the use of granular information to continually update the same. Data analysis can be used to refine the cost per task and calculate a cost to complete for a construction project. The cost to complete can be viewed at any time and it will be made more accurate by having the cost per task refined from historical data. Additionally, a rate of production statistic can be generated to compare workers across tasks and see if the implicit task durations used to today can be refined. A learning algorithm can be created by using reinforced learning to figure out the next best step if a project task is delayed or put on hold. This action can normalize projects in an effort for them to complete as scheduled and priced.