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: 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 routing information management method adapted for a layer-3 switch is proposed. For each ARP entry in an ARP table, a processor assigns to the ARP entry an aging reference parameter that is identical to a quantity of those routing entries in an IP routing table whose next hop IP addresses are identical to the IP address of the ARP entry, and removes those ARP entries whose aging reference parameters are zero. For each routing entry in the IP routing table, when the next hop IP address of the routing entry is absent from the ARP table, the processor makes the routing entry serve as an inactive routing entry, proactively sends an ARP request for the inactive routing entry, and updates the ARP table based on a piece of ARP information received externally.

Abstract: Detecting anomalous data by applying a plurality of models to a data set to yield detection results including anomalous data, applying evaluation methods to the detection results for each of the plurality of models, determining a combined score for the detection results according to the evaluation methods, determining a combined score threshold, and defining a set of detected anomalies according to the combined score and the combined score threshold.

Abstract: A computer-implemented method includes receiving an initial request from a client, splitting the initial request into a plurality of split requests based on a business logic, acquiring mapping information associated with the plurality of split requests, determining, based, at least in part, on the mapping information, respective split requests included in the plurality of split requests that are candidates for merger into a merged request, merging the respective split requests that are determined to be candidates for merger into one or more merged requests, and sending the one or more merged requests to one or more nodes capable of processing the one or more merged requests.

Abstract: An approach is provided in which the approach generates a parallel chart based on multiple records that includes a set of variable values corresponding to a set of variables. To generate the parallel chart, the approach arranges the set of variables on the parallel chart in a variable order based on at least one variable arrangement rule. The approach arranges an initial variable value order for each one of the set of variables, and computes a lucidity score based on the variable order and the initial variable value order of each of the set of variables. The lucidity score is a measurement of the clarity of the parallel chart. The approach adjusts the variable value order of at least one of the set of variables to increase the lucidity score and optimizes the clarity of the parallel chart based on the adjusted variable value order.

Abstract: Automated development and training of deep forest models for analyzing data by growing a random forest of decision trees using data, determining Out-of-bag (OOB) predictions for the forest, appending the OOB predictions to the data set, and growing an additional forest using the data set including the appended OOB predictions, and combining the output of the additional forest, then utilizing the model to classify data outside the training data set.

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: Disclosed are an intelligent bionic human body part model detection device and a method for manufacturing same. The device comprises: a bionic human body part model (1); and multiple optical fiber grating sensing units (5) which are integrated on an optical fibre and arranged at multiple pre-determined positions of the bionic human body part model (1). The device can improve the accuracy of the detection of pressure applied to the intelligent bionic human body part model.

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: Embodiments of the present disclosure relate to a method, system, and computer program product for predictive models. According to the method, a processor may provide a first list including at least one input variable of a predictive model and a second list including a plurality of variables of the predictive model. For each of input variables in the second list, the processor may determine contribution of the input variable to prediction of the predictive model with respect to the at least one input variable in the first list. The processor may update the first list by moving an input variable in the second list into the first list based on the determined contribution of the plurality of input variables. The processor may render one or more of input variables in the updated first list based on an order of the input variables in the updated first list.

Abstract: Provided are a computer-implemented method, a system, and a computer program product. The method comprises extracting features from a plurality of base models in an ensemble model. The plurality of base models are configured to provide respective prediction results. The ensemble model is configured to provide an overall prediction result from the prediction results of the plurality of base models. The features are associated with time performance of the base models. The method further comprises clustering the plurality of base models into a plurality of clusters based on the extracted features. The method further comprises assigning the plurality of base models to a plurality of parallel computation units based on the plurality of clusters.

Abstract: Disclosed are a computer-implemented method, a system and a computer program product for model exploration. Model feature importance of each model of a plurality of models can be obtained, the plurality of models can be grouped into a plurality of model clusters based on the model feature importance of each model, and the model feature importance can be presented by box-plot or confidence interval.

Abstract: The present disclosure relates to privacy protection in a search process. According to a method, a target emotion vector is extracted from a search interaction, the target emotion vector representing emotional information in the search interaction. Respective emotion distances between the target emotion vector and respective emotion vectors associated with a plurality of text clusters are determined. The plurality of text clusters is clustered from a dictionary of text elements. A first number of text clusters are selected from the plurality of text clusters based on the determined respective emotion distances. The first number of text clusters have emotion distances larger than at least one unselected text cluster among the plurality of text clusters. A plurality of confused search interactions are constructed for the search interaction based on the first number of text clusters, and the plurality of confused search interactions are performed.

Abstract: Disclosed are methods of forming a chamber component for a process chamber. The methods may include filling a mold with nanoparticles or plasma spraying nanoparticles, where at least a portion of the nanoparticles include a core particle and a thin film coating over the core particle. The core particle and thin film are formed of, independently, a rare earth metal-containing oxide, a rare earth metal-containing fluoride, a rare earth metal-containing oxyfluoride, or combinations thereof. The nanoparticles may have a donut-shape having a spherical form with indentations on opposite sides. The methods also may include sintering the nanoparticles to form the chamber component and materials. Further described are chamber components and coatings formed from the described nanoparticles.

Abstract: Examples described herein provide a computer-implemented method that includes determining a kernel width for the machine learning model. The method further includes building a local interpretable linear model using the kernel width. The method further includes computing a contribution and confidence for a feature of the local interpretable linear model. The method further includes updating the local interpretable linear model to generate a final model and computing an overall confidence for the final model.

Abstract: A system may port a data model into a strict schema system, translate the data model into a transformation rule definition, fit the transformation rule definition to a transform action, receive strict schema data, perform the transform action on the strict schema data based on the transformation rule definition to form rough data, and execute filtering and enriching operations on the rough data to form loose schema data.

Abstract: A method, computer program, and computer system are provided for training a machine learning model. A feature associated with training data derived from a dataset is identified. A machine learning model is generated based on the training data. At least a portion of the training data associated with maximizing an importance value associated with the identified feature is selected. The importance value corresponds to a need associated with the machine learning model. One or more weight values is assigned to the selected portion of the training data. The machine learning model is updated based on the assigned weight values.

Abstract: A method, computer system, and a computer program product for performing an interactive outcome analysis is provided. The present invention may include generating, by a computer, a first estimation outcome from a first plurality of input conditions. The present invention may include generating, by the computer, a parallel estimation outcome from a second plurality of input conditions, wherein at least one of said input conditions in said first plurality of input conditions is different from any of said second plurality of input conditions. The present invention may include selecting, by the computer, either said first or said parallel estimation outcome by analyzing said outcomes with one another and with a target goal outcome.

Abstract: An assembling equipment for performing asynchronous process on a first workpiece and a second workpiece. The assembling equipment includes a base and a conveying mechanism on the base. The conveying mechanism transports a first positioning assembly carrying a first workpiece and a second positioning assembly carrying a second workpiece to a first station synchronously, and a first attaching mechanism attaches a first component to the first workpiece at the first station. Then the conveying mechanism transports the first positioning assembly and the second positioning assembly to a second station synchronously, a second attaching mechanism attaches a second component to the second workpiece, and a first processing mechanism processes first workpiece that has been attached with the first component according to a preset requirement at the same time. The assembling equipment improves efficiency of production.