Abstract: A database reconciliation system stores construction project data, including project specification data for each of a plurality of projects and contractor data for each of a plurality of contractors. A server automatically receives observational data from a set of construction devices and stores the observational data in an electronic database. Each observational datum represents an aspect of a respective construction site, such as activity by construction equipment. The server associates the observational data with contractors, and a data reconciliation module automatically associates the observational data with projects. A comparator automatically identifies a respective project specification requirement in the project specification data of the associated project for which the observational datum provides evidence that the project specification requirement has been met.

Abstract: Systems, methods, and computer-readable media are described for intelligent, real-time monitoring and managing of changes in oilfield equilibrium to optimize production of desired hydrocarbons and economic viability of the field. In some examples, a method can involve generating, based on a topology of a field of wells, a respective graph for the wells, each respective graph including computing devices coupled with one or more sensors and/or actuators. The method can involve collecting, via the computing devices, respective parameters associated with one or more computing devices, sensors, actuators, and/or models, and identifying a measured state associated with the computing devices, sensors, actuators, and/or models.

Abstract: The present disclosure provides systems, methods, and metrics that filter out online visitor behavioral data that represents a potential lead with a high likelihood to convert to a vehicle sale from online visitor behavioral data that does not represent a potential lead with a low likelihood to convert to a vehicle sale, based on a mapping of sales back to observed website and vehicle configurator data. This enables more effective lead generation and the more efficient targeting of online incentive offers and sales “nudges,” for example. Further, the present disclosure enables web analytics data to be combined with sales data for sales forecasting in general.

Abstract: The disclosed embodiments generally relate to in-store customer traffic analysis systems and methods. The system includes at least one sensor positioned within a retail store, at least one display associated with the at least one sensor, one or more memory devices storing instructions and one or more hardware processors configured to execute the instructions to perform operations. The operations include receiving a sensor signal indicating that a user device is within a proximity to the at least one sensor in the retail store, extracting a user device identifier from the sensor signal, correlating the sensor signal to the at least one display, generating a foot traffic record associated with the user device identifier and the at least one display, based on the received sensor signal, and storing the generated foot traffic record.

Abstract: A forestry management device is provided including processing circuitry configured to receive an indication of a selected tree, receive selected tree location data associated with the selected tree, receive operator location data associated with an operator, and cause information associated with the selected tree to be displayed on a wearable computing device.

Abstract: Computer tool determines target feedstock for a refinery, process complex, or plant. The tool receives a dataset of market conditions and preprocesses the data based on properties of the plant. Using the preprocessed data and machine learning, the tool trains predictive models. Each predictive model calculates a breakeven value of a candidate feedstock for the given plant under an individual market condition. Different predictive models optimize for different market conditions. A trained predictive model is selected based on a current market condition. The tool applies the selected predictive model and determines whether a candidate feedstock is a target feedstock for the refinery under the current market condition.

Abstract: Aspects described herein may allow for generating a customized price rating using a machine learning algorithm. This may have the effect of improving the display of information about merchants by including customized, personalized price ratings that better reflect the tastes and preferences of a user or group of users. According to some aspects, these and other benefits may be achieved by using a machine learning model, trained to receive input corresponding to both user data and merchant data and output an indication of customized price rating(s) for the merchant that is specific to one or more users, and then to generate information about the merchant for display that includes the customized price rating(s).

Abstract: Systems and methods are disclosed for determining segments of online users from a correlated dataset. One method includes receiving, over a network, a plurality of datasets including user-related data of a plurality of users, each dataset being transmitted from a data owner; correlating, by at least one processor, the plurality of datasets into a correlated dataset; receiving a segmentation request for determining a plurality of users that qualify for a segment, the segmentation request including a set of segment rules to apply to the correlated dataset; determining, by accessing the correlated dataset, whether each user of the plurality of users qualifies for the segment based on the segment rule; and storing an indication of the segment in the correlated dataset for each user determined to qualify for the segment.

Abstract: Provided are methods, systems, and apparatuses for improving supply chain management interfaces and functionality. A frequency of occurrence for each unique combination of a use attribute and a product attribute for various supplies may be determined. A frequency table containing each unique combination may be generated as well as one or more association rules. A level of confidence and a level of lift may be determined for each of the one or more association rules, both of which may be used to generate a score for each unique combination that may be used to rank each unique combination. The ranked unique combinations may then be provided to a supply chain management interface and a database.

Abstract: Artificial intelligence is introduced into an electronic meeting context to perform various tasks before, during, and/or after electronic meetings. The artificial intelligence may analyze a wide variety of data such as data pertaining to other electronic meetings, data pertaining to organizations and users, and other general information pertaining to any topic. Capability is also provided to create, manage, and enforce meeting rules templates that specify requirements and constraints for various aspects of electronic meetings. Embodiments include improved approaches for translation and transcription using multiple translation/transcription services. Embodiments also include using sensors in conjunction with interactive whiteboard appliances to perform person detection, person identification, attendance tracking, and improved meeting start.

Abstract: State-of-the-art techniques hardly attempt to address controlled resource access problem in context of Basic Emergent Users (BEUs). Embodiments of the present disclosure provide a method and system for Proof of Work (POW) based protection of resources. The method includes using the POW for work done by BEUs in physical world and mapping it to digital world to generate crypto currency in terms of credit score, wherein an end user is eligible or authorized to use a resource of an entity to get a desired service if accumulated credit score is above a credit threshold. Gaining points to improve the credit score is challenging as it is based on percentage of compliance achieved by the BEU through actual work in accordance with a compliance protocol. Further, the method includes authenticating the authorized user based on a set of questions with increasing difficulty, derived based on a culture graph.

Abstract: A model management system receives data for an inventory of models including data regarding issues for each of the models. The model management system determines a model risk score for each of the models based on the issues for each of the models. As the issues are opened and closed, the model management system receives updates and in real-time, updates the model risk score. The model risk score can be determined using a severity assigned to each issue for each of the open issues for a given model as well as the number of issues at each severity. Risk scores can be calculated across a line of business and across an enterprise, for example. The model management system also provides one or more of: model development, model validation, model integration, model use, model maintenance, and model retirement.

Abstract: Devices, methods, and systems for providing security and customer service using video analytics and location tracking are described herein. One device includes a memory, and a processor configured to execute executable instructions stored in the memory to identify, using video analytics, security incidents occurring in a facility and customer service opportunities occurring in the facility, determine, upon identifying a security incident occurring in the facility, a workflow sequence for responding to the security incident, determine, upon identifying a customer service opportunity occurring in the facility, a workflow sequence for responding to the customer service opportunity, display the workflow sequence for responding to the security incident on a first user interface, and display the workflow sequence for responding to the customer service opportunity on a second user interface.

Abstract: In an example method, a system obtains first data indicating a plurality of properties of a wellbore, and determines a plurality of types of completion equipment available for deployment at the wellbore. Further, the system determines, using a computerized neural network, a plurality of quality metrics based on the first data. Each of the quality metrics represents an estimated likelihood of success of operating a respective one of the types of completion equipment at the wellbore. Further, the system causes a graphical user interface to be displayed to a user. The graphical user interface includes a concurrent presentation of an indication of each of the types of completion equipment, and an indication of each of the quality metrics.

Abstract: State of the art systems that are used for time series data prediction have the disadvantage that perform only one step prediction, which has only limited application. Disadvantage of such systems is that extent of applications of such single step predictions are limited. The disclosure herein generally relates to time series data prediction, and, more particularly, to time series data prediction based on seasonal lags. The system processes collected input data and determines order of seasonality of the input data. The system further selects encoders based on the determined order of seasonality and generates input data for a decoder that forms encoder-decoder pair with each of the encoders. The system then generates time series data predictions based on seasonal lag information distributed without redundance between encoder and decoder inputs.

Abstract: A method for creating highly accurate construction and renovation estimates and proposals for a client is described. The computer implemented method includes providing a platform to include all of the items and assemblies required in a construction project that make up the construction proposal, including all labor costs, material costs, and additional costs for taxes and mark ups. The method simplifies a highly complex and usually inaccurate process of having to calculate all of the costs associated with construction and renovation, in particular for residential properties, and allows clients to select desired items and receive a highly accurate, detailed estimate and proposal very quickly. The process further includes the ability to make any changes and upgrades quickly because of the unique system which includes linked dimensions, linked line items, and linked assemblies that allows a selection to affect multiple related elements, and further includes all hidden costs for better accuracy.

Abstract: An online concierge system trains a machine learning conversion model that predicts a probability of receiving an order from a user when the user accesses the online concierge system. The conversion model predicts the probability of receiving the order based on a set of input features that include price and availability information. For each access to the online concierge system, the online concierge system applies the conversion model to a current price and availability and to an optimal price availability. The online concierge system generates a metric as the difference between the two predicted probabilities of receiving an order.

Abstract: A computer implemented method for generating digital models of relative crop yield based on nitrate values in the soil is provided. In an embodiment, nitrate measurements from soil during a particular portion of a crop's development and corresponding crop yields are received by an agricultural intelligence computing system. Based, at least in part, on the nitrate measurements and corresponding crop yields, the system determines maximum yields for each location of a plurality of locations. The system then converts each crop yield value into a relative crop yield by dividing the crop yield value by the maximum crop yield for the location. Using the relative crop yields and the corresponding nitrate values in the soil, the system generates a digital model of relative crop yield as a function of nitrate in the soil during the particular portion of the crop's development.

Abstract: Methods and systems for evaluating economic viability of a proposed microgrid, including uncertain variables are disclosed. One or more candidate distributed energy resources can be selected for use within a proposed microgrid. An investment cost and an operation cost of the one or more candidate distributed energy resources can be determined. A cost of drawing power from a main power grid can be compared to a sum of the investment cost and the operation cost of the one or more candidate distributed energy resources. The proposed microgrid can be identified for installation when the sum of the investment cost and the operation cost is less than the cost of drawing power from the main power grid.

Abstract: Aspects described herein may allow for generating a customized price rating using a machine learning algorithm. This may have the effect of improving the display of information about merchants by including customized, personalized price ratings that better reflect the tastes and preferences of a user or group of users. According to some aspects, these and other benefits may be achieved by using a machine learning model, trained to receive input corresponding to both user data and merchant data and output an indication of customized price rating(s) for the merchant that is specific to one or more users, and then to generate information about the merchant for display that includes the customized price rating(s).