Abstract: A process for plasmonic-based high resolution color printing is provided. The process includes a) providing a nanostructured substrate surface having a reverse structure geometry comprised of nanopits and nanoposts on a support, and b) forming a conformal continuous metal coating over the nanostructured substrate surface to generate a continuous metal film, the continuous metal film defining nanostructures for the plasmonic-based high resolution color printing, wherein a periodicity of the nanostructures is equal to or less than a diffraction limit of visible light. A nanostructured metal film or metal-film coated support obtained by the process and a method for generating a color image are also provided.

Abstract: An approach is provided in which the approach builds a combination model that includes a normal status model and an abnormal status model. The normal status model is built from a set of time-sequenced normal status records and the abnormal status model is built from a set of time-sequenced abnormal status records. The approach computes a set of time-sequenced coefficient combination values of the normal status model and the abnormal status model based on applying a set of fitting coefficient characteristics to the normal status model and the abnormal status model. The approach performs goal seek analysis on a system using the combination model and the set of time-sequenced coefficient combination values.

Abstract: A method of clustering data generated by an unknown model, the method including accessing the data, wherein the data includes a prediction target and a confidence, extracting a data group with high prediction confidence from the data, wherein the data group comprises a plurality of data cases, and where each of the data cases is described by a plurality of predictors, identifying high rank predictors of each the data cases in the data group, transforming the data group into a transformed data group including only the high rank predictors for each of the data cases, wherein the high rank predictors are ranked within each of the data cases included in the transformed data group, clustering the transformed data group to generate clusters, and profiling the clusters to extract an insight about the unknown model.

Abstract: Disclosed are rare earth metal containing silicate coatings, coated articles (e.g., heaters and susceptors) or bodies of articles and methods of coating such articles with a rare earth metal containing silicate coating.

Abstract: In one embodiment, one or more computing devices receives, from a first user, a request to search for compatible users, wherein the first user is associated with a set of first expressed interests, accesses one or more sets of second expressed interests of one or more second users, respectively, normalizes the set of first expressed interests and the sets of second expressed interests to obtain a set of first normalized interests and one or more sets of second normalized interests, respectively, calculates, for each set of second expressed interests, an interest compatibility score based at least in part on a probability that a user will express one or more pairs of a first normalized interest and a second normalized interest, and sends, to the first user, information associated with one or more of the second users based on the calculated interest compatibility scores.

Abstract: Feature importance is critical to understanding how predictive models produce accurate results, and can change significantly for different models. The present invention is used to achieve a good ranking for stable feature importance. An optimized technique is presented which considers feature importance value variation within different groups of cross-trained models. Feature importance is computed for all group models with this optimized method, and then a best set of models can be selected based on classification error as well as optimized stable feature importance values.

Abstract: A cleaning device includes a host, a drag head assembly and a water spray assembly. The host includes a housing, a control device housed in the housing and a handle member fixedly connected to the housing. The housing contains a water inlet pipe for connecting to a water source. The drag head assembly is fixed on the housing and electrically connected to the control device. The control device is used to control the drag head assembly for cleaning operations. The drag head assembly includes a cleaning brush head. The water spray assembly is fixed in the drag head assembly and connected to the end of the water inlet pipe away from the water source. The water spray assembly has evenly set spray holes. The direction of the spray holes is towards the cleaning brush head.

Abstract: An approach is provided in which a method, system, and program product generate a set of bootstrap samples from a set of data records that each includes multiple fields. The method, system, and program product create a set of decision tree stumps from the set of bootstrap samples. Each one of the set of decision tree stumps includes multiple leaf nodes corresponding to one or more of the multiple fields. The method, system, and program product generate a set of new features from the set of decision tree stumps, wherein each one of the set of new features indicates at least one field interaction between two or more of the multiple fields. The method, system, and program product train a predictive model based on the set of new features.

Abstract: A method for receiving an unreduced training data in the form of a plurality of TDRs (training data sets), using a first autoencoder on the plurality of TDRs to obtain first reduced training data in the form of a plurality of TDRs, clustering, into a plurality of clusters, the plurality of TDRs of the first reduced training data so that each TDR belongs to a cluster of the plurality of clusters, assigning a cluster identification code to each cluster of the plurality of clusters, adding cluster identification codes to each TDR of the plurality of TDRs of the unreduced training data, and perform stratified sampling to form K data blocks from the TDRs of the unreduced data.

Abstract: The present invention discloses a floor cleaning apparatus includes an upper body and a lower body. The upper body includes a lower housing a roller. The roller is arranged at an internal of the lower housing and is partially exposed externally. The lower housing includes a scraper for scraping foreign objects away from the roller. The roller includes a suction vent hood used sucking foreign objects via a negative pressure, and the scraper is adjacent to the suction vent hood to allow the scraped foreign objects to be sucked away by the suction vent hood directly. The roller includes a nozzle for ejecting a water for cleaning the roller. The present invention provides a cleaning apparatus with water ejection function. The roller can be cleaned through the water ejection and dirt can be sucked away by the negative pressure system, thereby achieving the proper cleaning effect with enhanced effect.

Abstract: A processing method that is performed by one or more processor is provided. The processing method includes determining a target video frame in a currently captured video; determining an object area in the target video frame based on a box selection model; determining a category of a target object in the object area based on a classification model used to classify an object in the object area; obtaining augmented reality scene information associated with the category of the target object; and performing augmented reality processing on the object area in the target video frame and the augmented reality scene information, to obtain the augmented reality scene.

Abstract: A computing system for querying multiple data sources and a method therefor is provided. The computing system may comprise one or more nodes in communication with at least one data source of the multiple data sources to access data therefrom. The computing system may further comprise a second node in communication with the one or more nodes. The second node may be configured to receive a query instance and process the query instance to generate one or more relational query instances. The one or more relational query instances may be distributed among the one or more nodes to extract data from the at least one data source in communication therewith corresponding to the respective one or more relational query instances. The second node may be further configured to receive extracted data from each of the one or more nodes queried. The second node may be further configured to aggregate the extracted data.

Abstract: A system, computer program product, and method are presented for enriching existing legacy expert systems through refinement of existing rules therein. The method includes identifying a legacy expert system to be enriched, relevant training data, existing rules embedded within the legacy expert system, and, for each existing rule, one or more antecedent factors. The method also includes determining the existing rules do not meet a threshold value for established quality requirements, thereby identifying one or more low-quality rules. The method further includes identifying frequent sets of antecedent factors associated with each low-quality rule, where each frequent set of antecedent factors is established as a frequent set through at least meeting a threshold frequency of occurrence within the training data. The method also includes comparing the antecedent factors of each existing rule with the frequent sets of antecedent factors, and enriching the legacy expert system through refining the existing rules.

Abstract: A processing method that is performed by one or more processor is provided. The processing method includes determining a target video frame in a currently captured video; determining an object area in the target video frame based on a box selection model; determining a category of a target object in the object area based on a classification model used to classify an object in the object area; obtaining augmented reality scene information associated with the category of the target object; and performing augmented reality processing on the object area in the target video frame and the augmented reality scene information, to obtain the augmented reality scene.

Abstract: A method for identifying influential effects that contribute most to a status change of a target index for goal seeking analysis. The method includes generating a candidate list of significant changed predictors between the normal and abnormal status time periods in collected data, and building a plurality of regression models from the collected data. The method determines a first value (trend value or Pearson correlation value) for each of the significant changed predictors based on whether at least one of the significant changed predictors have a significant change trend using the regression models. The method obtains a second predictor importance value for each of the significant changed predictors from a single model built on all the collected data. The method generates a final predictor value for each of the significant changed predictors by combining the first value with the second predictor importance value for each of the significant changed predictors.

Abstract: Disclosed are rare earth metal containing silicate coatings, coated articles (e.g., heaters and susceptors) or bodies of articles and methods of coating such articles with a rare earth metal containing silicate coating.

Abstract: Methods of forming nanoceramic materials and components. The methods may include performing atomic layer deposition to form a plurality of nanoparticles, including forming a thin film coating over core particles, or sintering the nanoparticles in a mold. The nanoparticles can include a first material selected from a rare earth metal-containing oxide, a rare earth metal-containing fluoride, a rare earth metal-containing oxyfluoride or combinations thereof.

Abstract: Methods, computer program products, and/or systems are provided that perform the following operations: obtaining a series of indicator diagrams corresponding to strokes of a pumpjack over a specific time duration, dividing each indicator diagram into a plurality of location segments in a direction of location of the rod; obtaining load difference features between upstroke loads and corresponding downstroke loads in the plurality of location segments; identifying a location segment with an abnormal load difference feature based on a time series data of load difference feature corresponding to one of the plurality of location segments, the time series data of load difference feature including a series of data points of load difference feature of the one of the plurality of location segments in time order; and providing an indication of a potential problem based, at least in part, on the identification of the location segment with an abnormal load difference feature.

Abstract: A receiving structure providing real-time information as to the materials constituting its contents includes a box body, a first side plate, and a second side plate. The box body, the first side plate, and the second side plate forming a receiving space, and the receiving space receives materials. A discharge port is formed between the second side plate and the first side plate, the discharge port is in communication with the receiving space, and the discharge port is configured to take out the material. A material checking unit is provided on the first side plate, the material checking unit detects and enables real time identification of the materials in the receiving structure.

Abstract: A receiving structure providing real-time information as to the materials constituting its contents includes a box body, a first side plate, and a second side plate. The box body, the first side plate, and the second side plate forming a receiving space, and the receiving space receives materials. A discharge port is formed between the second side plate and the first side plate, the discharge port is in communication with the receiving space, and the discharge port is configured to take out the material. A material checking unit is provided on the first side plate, the material checking unit detects and enables real time identification of the materials in the receiving structure.