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: In an approach for detecting web browsing subject-oriented event interactions and intelligently organizing web pages based on insights from important interactions for better exploration and efficient management, a processor extracts time series data associated with a plurality of web browsing events based on browsing historical actions of a user. A processor identifies the subject of each web browsing event. A processor determines major events based on the time series data and subjects of the plurality of web browsing events. A processor organizes the plurality of web browsing events based on subject hierarchy and timeline from the time series data. A processor highlights one or more uniform resource locators based on the subject hierarchy and timeline.

Abstract: Techniques for optimizing machine learning models are provided. A first model in a first format is received. A second model is generated by applying one or more optimization techniques to the first model; the second model is an optimized version of the first model. The second model is converted into a common intermediate format. The second model is converted into binary data representing the second model. The binary data representing the second model is outputted.

Abstract: One or more computer processors calculate a cache prediction for a received inference request within an inference cache structured as a self-learning tree, wherein the inference request comprises a set of input values. The one or more computer processors responsive to the retrieved cache prediction exceeding a cache prediction threshold, transmit the cache prediction. The one or more computer processors parallel compute a model prediction for the received inference request utilizing a trained model. The one or more computer processors responsive to the retrieved model prediction exceeding a model prediction threshold, convert the trained model into a tree structure. The one or more computer processors update the inference cache with the converted train model. The one or more computer processors transmit the model prediction.

Abstract: In an approach for detecting web browsing subject-oriented event interactions and intelligently organizing web pages based on insights from important interactions for better exploration and efficient management, a processor extracts time series data associated with a plurality of web browsing events based on browsing historical actions of a user. A processor identifies the subject of each web browsing event. A processor determines major events based on the time series data and subjects of the plurality of web browsing events. A processor organizes the plurality of web browsing events based on subject hierarchy and timeline from the time series data. A processor highlights one or more uniform resource locators based on the subject hierarchy and timeline.

Abstract: A method includes determining a plurality of performance metrics for a plurality of sub-models forming a first machine learning model and clustering the plurality of sub-models based on the plurality of performance metrics to produce a plurality of clusters of sub-models. The method also includes removing, from the first machine learning model, sub-models assigned to a first cluster of the plurality of clusters to produce a second machine learning model formed by the sub-models remaining in the first machine learning model and in response to determining that a performance of the second machine learning model is below a performance threshold, adding a subset of the removed sub-models to the second machine learning model to produce a third machine learning model. The method further includes, in response to determining that a performance of the third machine learning model meets the performance threshold, selecting the third machine learning model to be applied.

Abstract: Systems and computer-implemented methods select a subset of methods to generate data schemas for input data from a list of methods for generating data schemas, based on output of a regression model; generate a candidate schema for each method in the subset of methods to generate data schemas; and generate a master data schema for the input data by merging the candidate schema for each method in the subset of methods to generate data schemas, utilizing predetermined rules.

Abstract: A method for instantiating a first specific model, as one record, based on a model scoring template, clustering a plurality of models into a plurality of groups to obtain a plurality of clusters, computing a model contribution weight value for the given cluster, choosing a set of top model(s) from the plurality of models, and updating the model(s) of the set of top model(s) dynamically.

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: This disclosure provides a solution for processing outliers in a time series. In the method, a time series model is obtained based on a first set of observed values. Outliers are identified from the first set of observed values based on the differences between the first set of observed values and a first set of predicted values. The first set of predicted values is obtained from the first set of observed values by using the time series model. A model evaluation measure representing differences between a second set of observed values and a second set of predicted values is calculated. The second set of predicted values is obtained from the second set of observed values by using the time series model. And replacement values for the outliers are determined in response to the model evaluation measure not meeting a predefined criterion.

Abstract: A high adhesion composite film includes a thermoplastic elastomer layer and a modified adhesive layer. The thermoplastic elastomer layer includes a first surface and a second surface, and the second surface is opposite to the first surface. The modified adhesive layer is disposed on the first surface of the thermoplastic elastomer layer. By this way, the adhesion strength of the composite film can be enhanced significantly. Furthermore, the present disclosure can manufacture the high adhesion composite film without the use of solvents, which meets the requirements of environmental protection.

Abstract: A scanner is disclosed. The scanner includes a light source to emit light of a first color during a first turn-on period and emit light of a second color during a second turn-on period; a sensor to receive light from a scanning area, in response to the light of the first color directed to the scanning area, during a first sensing period, and receive light from the scanning area, in response to the light of the second color directed to the scanning area, during a second sensing period; and a controller to control the timing of the first turn-on period within the first sensing period and the second turn-on period within the second sensing period.

Abstract: A traffic management device (TMD), system, and processor-readable storage medium directed towards automatically configuring an AAA proxy device (also referred to herein as “the proxy”) to load-balance AAA request messages across a plurality of AAA server devices. In one embodiment the proxy receives an AAA handshake message from an AAA client device. The proxy forwards the handshake message to each of the plurality of server devices and, in reply, receives an AAA handshake response message from each of the plurality of server devices. The proxy extracts attributes from each of the handshake response messages and automatically configures itself based on the extracted attributes. The proxy then load-balances, modifies and/or routes subsequently received AAA request messages based on the extracted attributes.

Abstract: A scanner is disclosed. The scanner includes a light source to emit light of a first color during a first turn-on period and emit light of a second color during a second turn-on period; a sensor to receive light from a scanning area, in response to the light of the first color directed to the scanning area, during a first sensing period, and receive light from the scanning area, in response to the light of the second color directed to the scanning area, during a second sensing period; and a controller to control the timing of the first turn-on period within the first sensing period and the second turn-on period within the second sensing period.

Abstract: A high adhesion composite film includes a thermoplastic elastomer layer and a modified adhesive layer. The thermoplastic elastomer layer includes a first surface and a second surface, and the second surface is opposite to the first surface. The modified adhesive layer is disposed on the first surface of the thermoplastic elastomer layer. By this way, the adhesion strength of the composite film can be enhanced significantly. Furthermore, the present disclosure can manufacture the high adhesion composite film without the use of solvents, which meets the requirements of environmental protection.

Abstract: A traffic management device (TMD), system, and processor-readable storage medium directed towards automatically configuring an AAA proxy device (also referred to herein as “the proxy”) to load-balance AAA request messages across a plurality of AAA server devices. In one embodiment the proxy receives an AAA handshake message from an AAA client device. The proxy forwards the handshake message to each of the plurality of server devices and, in reply, receives an AAA handshake response message from each of the plurality of server devices. The proxy extracts attributes from each of the handshake response messages and automatically configures itself based on the extracted attributes. The proxy then load-balances, modifies and/or routes subsequently received AAA request messages based on the extracted attributes.

Abstract: A method for making controlled-release ammonium phosphate fertilizer has the following acts of: cracking, pulverizing, blending, aging, drying, and adding release-controlling materials into an ammonium phosphate slurry during preparing processes or adding release-controlling materials in achieved ammonium phosphate powder. Selectively, sulfuric acid is added into the mixture of the release-controlling materials and the ammonium phosphate slurry or ammonium phosphate powder to acidify the mixture. In this method, the release-controlling material combines with the ammonium phosphate by chemical bonding to control the release of nitrogen and phosphorus nutrients to enhance the use efficiency and elongate fertilization effect of the controlled-release ammonium phosphate fertilizer.

Abstract: A method for making controlled-release ammonium phosphate fertilizer has the following acts of: cracking, pulverizing, blending, aging, drying, and adding release-controlling materials into an ammonium phosphate slurry during preparing processes or adding release-controlling materials in achieved ammonium phosphate powder. Selectively, sulfuric acid is added into the mixture of the release-controlling materials and the ammonium phosphate slurry or ammonium phosphate powder to acidify the mixture. In this method, the release-controlling material combines with the ammonium phosphate by chemical bonding to controll the release of nitrogen and phosphorus nutrients to enhance the use efficiency and elongate fertilization effect of the controlled-release ammonium phosphate fertilizer.