Abstract: A method for machine learning based ultrasound image reconstruction can include receiving, at a reconstruction engine, imaging data; generating an initial estimate for a transmission image via a neural network trained (machine or self-learning) on paired transmission ultrasound and reflection ultrasound data; and performing image reconstruction using the initial estimate to generate transmission ultrasound images. The image reconstruction can generate higher quality transmission ultrasound when carried out by using the initial estimate as the starting point for iterative image reconstruction and using transmission data obtained via conventional transmission ultrasound frequencies (e.g. from 0.8 MHz to 1.5 MHz).

Abstract: A method for machine learning based ultrasound image reconstruction can include receiving, at a reconstruction engine, imaging data; generating an initial estimate for a transmission image via a neural network trained (machine or self-learning) on paired transmission ultrasound and reflection ultrasound data; and performing image reconstruction using the initial estimate to generate transmission ultrasound images. The image reconstruction can generate higher quality transmission ultrasound when carried out by using the initial estimate as the starting point for iterative image reconstruction and using transmission data obtained via conventional transmission ultrasound frequencies (e.g. from 0.8 MHz to 1.5 MHz).

Abstract: Techniques are provided for implementing a probabilistic system and architecture to predict and optimize particular user activity. In one technique, opportunity application data that indicates multiple applications to multiple opportunities is stored. Tracking data that indicates, for each opportunity, a number of reviewer actions with respect to applications to the opportunity is stored. Based on the tracking data, one or more machine learning techniques are used to learn parameters of a model that takes, as input, a number of weighted applications of an opportunity and generates, as output, a prediction of a confirmed hire for the opportunity. A particular opportunity is identified and a first number of reviewer actions with respect to the particular opportunity is determined. A second number of weighted applications for the particular opportunity is generated based on the first number. The second number is input into the model to generate a score for the particular opportunity.

Abstract: The disclosed embodiments provide a system for predicting successful outcomes. During operation, the system determines interaction features characterizing interaction between a moderator of a job and one or more applicants for the job. Next, the system applies a machine learning model to the interaction features to produce a score representing a likelihood of a positive outcome for the job. The system then applies a threshold to the score to generate a predicted outcome for the job. Finally, the system outputs the predicted outcome in association with the job.

Abstract: A system that generates an item-to-item similarity for a category that includes a plurality of products receives attribute values for each product in the category and product-store-week sales units for each product in the category. The system estimates attribute weights. The system then determines the item-to-item similarity as a weighted attribute match score.

Abstract: A demand transference forecast system receives for a category of merchandise de-promoted sales data for each of a plurality of stock keeping units (“SKUs”), similarities between each pair of SKUs in the category, and SKU-store ranging information. The system determines a sales indices of all SKUs in the category across the de-promoted sales data for the category. The system determines Total Assortment Effect (“TAE”) variable quantities for the SKUs across share intervals in the de-promoted sales data based on the sales indices and the similarities. The system then generates a single parameter based demand transference model based on the similarities, the sales indices, and ratios of the share intervals.

Abstract: A method, system and computer program product for securing and tracking restricted files stored in a data processing system is provided. The data processing system is connected to a server for sharing information. An entity requesting to access a restricted file is authenticated, based on certain policies defined by a system administrator. Further, the system maintains a log of operations executed on the restricted file, and sends a record of the log to the server.

Abstract: A system generates a consumer decision tree (“CDT”). The system receives customer purchasing data that includes transactions of a plurality of products each having at least one product attribute. For a product category, the system identifies a plurality of similar products from the purchasing data and one or more attributes corresponding to each similar product. The system assigns the product category as a current level of the CDT, and determines a most significant attribute of the plurality of attributes for the current level. The system forms a next level of the CDT by dividing the most significant attribute into a plurality of sub-sections, where each sub-section corresponds to an attribute value of the most significant attribute. The system then forms a next level of the CDT for each sub-section until a terminal node is identified.

Abstract: A system generates a consumer decision tree (“CDT”). The system receives customer purchasing data that includes transactions of a plurality of products each having at least one product attribute. For a product category, the system identifies a plurality of similar products from the purchasing data and one or more attributes corresponding to each similar product. The system assigns the product category as a current level of the CDT, and determines a most significant attribute of the plurality of attributes for the current level. The system forms a next level of the CDT by dividing the most significant attribute into a plurality of sub-sections, where each sub-section corresponds to an attribute value of the most significant attribute. The system then forms a next level of the CDT for each sub-section until a terminal node is identified.

Abstract: A method, system and computer program product for securing and tracking restricted files stored in a data processing system is provided. The data processing system is connected to a server for sharing information. An entity requesting to access a restricted file is authenticated, based on certain policies defined by a system administrator. Further, the system maintains a log of operations executed on the restricted file, and sends a record of the log to the server.

Abstract: A method, system and computer program product for securing and tracking restricted files stored in a data processing system is provided. The data processing system is connected to a server for sharing information. An entity requesting to access a restricted file is authenticated, based on certain policies defined by a system administrator. Further, the system maintains a log of operations executed on the restricted file, and sends a record of the log to the server.

Abstract: A workflow system that automates work processes. The workflow system uses an open architecture to support multiple platforms and includes Application Programming Interfaces (APIs) enabling applications to communicate with a workflow engine. The workflow system supports Relational DataBase Management System (RDBMS) databases and allows routing of any kind of work (forms, images, executables). In addition, its flexible architecture is designed to facilitate changes to a workflow dynamically and to support integration with an existing infrastructure. The workflow system links software components to enable participants to work on shared data and ensures that business processes follows predetermined rules. Each task in the process is regulated such that the appropriate people have access to the appropriate data and are instructed to perform the task at the appropriate time. A developer can use a workflow system provided client to get an application up and running relatively quickly.

Abstract: A workflow system that automates work processes. The workflow system uses an open architecture to support multiple platforms and includes Application Programming Interfaces (APIs) enabling applications to communicate with a workflow engine. The workflow system supports Relational DataBase Management System (RDBMS) databases and allows routing of any kind of work (forms, images, executables). In addition, its flexible architecture is designed to facilitate changes to a workflow dynamically and to support integration with an existing infrastructure.