Abstract: A full-electric drive cementing control system is disclosed.

Abstract: The present teaching relates to ranking search content. In one example, a plurality of documents is received to be ranked with respect to a query. Features are extracted from the query and the plurality of documents. The plurality of documents is ranked based on a ranking model and the extracted features. The ranking model is derived to remove one or more documents from the plurality of documents that are less relevant to the query and order remaining documents based on their relevance to the query. The ordered remaining documents are provided as a search result with respect to the query.

Abstract: The present teaching relates to ranking search content. In one example, a plurality of documents is received to be ranked with respect to a query. Features are extracted from the query and the plurality of documents. The plurality of documents is ranked based on a ranking model and the extracted features. The ranking model is derived to remove one or more documents from the plurality of documents that are less relevant to the query and order remaining documents based on their relevance to the query. The ordered remaining documents are provided as a search result with respect to the query.

Abstract: Provided is a membrane for cell culture and differentiation. The membrane comprises a base portion and an array of protrusions consisting of a plurality of protrusions. The protrusions are substantially evenly distributed on the base portion. The plurality of protrusions has dimensions on the order of micrometers. In particular, the membrane consists of particles of different particle sizes of two or more types. One type of particles has an average particle size of 1 ?m to 50 ?m. Two or more types of particles of different particle sizes include nanoscale particles, 10-900 nm. One type of particle is selected from the group consisting of inorganic compound microspheres. The other type of particles of the two or more types of particles of different particle sizes is selected from the group consisting of organic polymer nanospheres. Also provided is a method for maintaining, culturing and/or differentiating cells using such membrane.

Abstract: A computing device for distributed power system model calibration is provided. The computing device is programmed to receive event data and model response data associated with a model to simulate, wherein the model includes a plurality of parameters, divide the event data into a plurality of sets, wherein each set includes associated parameters, and transmit the plurality of sets of event data to a plurality of client nodes. Each client node of the plurality of client nodes is programmed to analyze a corresponding set of event data to determine updated parameters for the model. The computing device is further programmed to receive a plurality of updated parameters for the model from the plurality of client nodes and analyze the received plurality of updated parameters to determine at least one adjusted parameter.

Abstract: Provided is a membrane for cell culture and differentiation. The membrane has a base portion and an array of protrusions consisting of a plurality of protrusions. The protrusions are substantially evenly distributed on the base portion. The plurality of protrusions has dimensions on the order of micrometers. In particular, the membrane consists of particles of different particle sizes of two or more kinds. One kind of particles have an average particle size of 1 ?m to 50 ?m. Two or more kinds of particles of different particle sizes include nanoscale particles, 10-900 nm. One kind of particles are selected from the group consisting of inorganic compound microspheres. The other kind of particles of the two or more kinds of particles of different particle sizes are selected from the group consisting of organic polymer nanospheres. Also provided is a method for maintaining, culturing and/or differentiating cells using such membrane.

Abstract: A computing device for distributed power system model calibration is provided. The computing device is programmed to receive event data and model response data associated with a model to simulate, wherein the model includes a plurality of parameters, divide the event data into a plurality of sets, wherein each set includes associated parameters, and transmit the plurality of sets of event data to a plurality of client nodes. Each client node of the plurality of client nodes is programmed to analyze a corresponding set of event data to determine updated parameters for the model. The computing device is further programmed to receive a plurality of updated parameters for the model from the plurality of client nodes and analyze the received plurality of updated parameters to determine at least one adjusted parameter.

Abstract: Systems, devices, and methods are disclosed for determining the quality of traffic received from different web page publishers, and setting a pricing structure for the different traffic based on the determined quality of traffic. Accurately determining the quality of traffic and/or clicks from different publishers allows the network system described herein to offer a fair marketplace with just return on investments (ROI) for advertisers, and offer a robust and accurate traffic quality based pricing model for publishers. Internet based technology, and in particular deep learning techniques available through a neural network, are utilized to determine the pricing structure based on click and/or web page traffic quality measurements generated through the deep learning techniques.

Abstract: Systems and methods for tracking brand reputation and market share are provided. The system includes one or more devices having a processor and a non-transitory storage medium accessible to the hardware processor. The device is programmed to obtain an awareness index at a plurality of levels at least partially based on the brand data. The device is programmed to obtain a favorability index as a ratio of user numbers based on the brand data. The device is programmed to obtain a branding index by combining the awareness index and the favorability index. The device is programmed to obtain an affinity score for a group of users at least partially based on the brand data and recommend the group of users based on the affinity score to increase the branding index.

Abstract: Systems, devices, and methods are disclosed for determining the quality of traffic received from different web page publishers, and setting a pricing structure for the different traffic based on the determined quality of traffic. Accurately determining the quality of traffic and/or clicks from different publishers allows the network system described herein to offer a fair marketplace with just return on investments (ROI) for advertisers, and offer a robust and accurate traffic quality based pricing model for publishers. Internet based technology, and in particular deep learning techniques available through a neural network, are utilized to determine the pricing structure based on click and/or web page traffic quality measurements generated through the deep learning techniques.

Abstract: The present teaching relates to ranking search content. In one example, a plurality of documents is received to be ranked with respect to a query. Features are extracted from the query and the plurality of documents. The plurality of documents is ranked based on a ranking model and the extracted features. The ranking model is derived to remove one or more documents from the plurality of documents that are less relevant to the query and order remaining documents based on their relevance to the query. The ordered remaining documents are provided as a search result with respect to the query.

Abstract: Systems and methods for are provided for measuring treatment effect of advertisement campaigns. The system includes a processor and a non-transitory storage medium accessible to the processor. The system includes a memory storing a database including historical advertisement data. A computer server is in communication with the memory and the database, the computer server programmed to obtain a tree-based model using the historical advertisement data, where the tree-based model include a plurality of leaf nodes. Within at least one leaf node of the tree-based model, the computer server obtains a number of subjects and estimates a treatment effect for a treatment. The computer server calculates a final treatment effect for the tree-based model using the number of subjects and the treatment effect. The computer server then determines a parameter for future advertising strategy using the final treatment effect.

Abstract: Systems and methods for managing advertisement campaign are provided. The system includes one or more devices having a processor and a non-transitory storage medium accessible to the hardware processor. The system includes a memory storing a database including campaign data. The system also includes a server computer in communication with the database. The server computer is programmed to receive a budget to be spent on a plurality of websites. The server computer is programmed to estimate a parameter for a non-linear model based on the campaign data. The server computer is programmed to estimate an expected number of conversions for each of the plurality of websites using the non-linear model with the estimated parameter. The server computer is programmed to determine an allocation of impressions for the plurality of websites that maximizes an estimated total number of conversions.

Abstract: Systems and methods for tracking brand reputation and market share are provided. The system includes one or more devices having a processor and a non-transitory storage medium accessible to the hardware processor. The device is programmed to obtain an awareness index at a plurality of levels at least partially based on the brand data. The device is programmed to obtain a favorability index as a ratio of user numbers based on the brand data. The device is programmed to obtain a branding index by combining the awareness index and the favorability index. The device is programmed to obtain an affinity score for a group of users at least partially based on the brand data and recommend the group of users based on the affinity score to increase the branding index.

Abstract: Methods, systems and programming for measuring user treatment effectiveness. First information related to activities of each user in a first user set in response to a first treatment is received. Second information related to activities of each user in a second user set in response to a second treatment is received. A model with respect to features is obtained based on the first and second information. Each user is associated with the features. A weighing factor for each user is estimated based on the model and each user's features. A first success rate is computed based on the first information and the weighting factors for each user in the first user set. A second success rate is computed based on the second information and the weighting factors for each user in the second user set. A metric of effectiveness is measured based on the first and second success rates.