Abstract: An embodiment includes generating an input document that includes a plurality of text fields of attribute data. The embodiment also includes extracting a set of candidate features from the attribute data using a feature extraction module that evaluates the attribute data using first and second machine learning models, where the first machine learning model scores terms in the input document and the second machine learning model includes a deep learning model. The embodiment also includes calculating feature-selection values for respective features of the set of candidate features and generating tag information for a remote computing asset using a machine learning classifier that predicts the tag information based on the feature-selection values.

Abstract: A method of atmospheric inorganic and organic nitrogen quantification is disclosed. The ambient air is sampled by drawing it through an inlet followed by a denuder to reduce positive artifacts. After artifact removal, the air sample is collected onto a filter. The filter is subjected to thermal evolution under stepwise temperature program to generate a gaseous product mixture. In the presence of oxygen-containing carrier gas, the gaseous product mixture is oxidized to form oxidized gaseous products of CO2 and nitrogen oxides. Then, the nitrogen oxides products are processed to form an NO product and reacted with ozone to form an excited NO2* molecule. By quantifying the intensity of fluorescence, the concentration of NO2* molecule is measured, which determines the nitrogen content in the aerosol sample. The differentiation of inorganic and organic nitrogen is achieved through processing the thermally evolved carbon and nitrogen signals using multivariate curve resolution data treatment.

Abstract: An embodiment includes generating an input document that includes a plurality of text fields of attribute data. The embodiment also includes extracting a set of candidate features from the attribute data using a feature extraction module that evaluates the attribute data using first and second machine learning models, where the first machine learning model scores terms in the input document and the second machine learning model includes a deep learning model. The embodiment also includes calculating feature-selection values for respective features of the set of candidate features and generating tag information for a remote computing asset using a machine learning classifier that predicts the tag information based on the feature-selection values.

Abstract: An embodiment includes generating an input document that includes a plurality of text fields of attribute data. The embodiment also includes extracting a set of candidate features from the attribute data using a feature extraction module that evaluates the attribute data using first and second machine learning models, where the first machine learning model scores terms in the input document and the second machine learning model includes a deep learning model. The embodiment also includes calculating feature-selection values for respective features of the set of candidate features and generating tag information for a remote computing asset using a machine learning classifier that predicts the tag information based on the feature-selection values.

Abstract: In a described example, an electrical apparatus includes: a metal layer formed over a non-device side of a semiconductor device die, the semiconductor device die having devices formed on a device side of the semiconductor device die opposite the non-device side; a first side of the metal layer bonded to a die mount pad on a package substrate; a second side of the metal layer formed over a roughened surface on the non-device side of the semiconductor device die, the roughened surface having an average surface roughness (Ra) between 40 nm and 500 nm; bond pads on the semiconductor device die electrically coupled to conductive leads on the package substrate; and mold compound covering at least a portion of the semiconductor device die and at least a portion of the conductive leads.

Abstract: An embodiment includes calculating an efficacy value of a context assigned to an asset, the efficacy value being based at least in part on a percentage of assets assigned to the context. The embodiment also includes calculating, responsive to the calculated efficacy value being within a predetermined range, a normalized relevance value of a first tag associated with the asset. The embodiment also includes generating relative relevance value for the first tag and a reason code associated with a basis for the relative relevance value of the first tag based at least in part on the normalized relevance value of the first tag. The embodiment also includes initiating, responsive to generating the relative relevance value and the reason code for the first tag, a database command on a training dataset stored in the database that includes the first tag.

Abstract: A continuous production device and method for a silane-modified sealing material are provided. The device includes a twin screw extruder set, a cooling unit, and a static mixing unit; where the twin screw extruder set includes at least two twin screw extruders in series, each of which is provided with at least two inlets and at least one vacuum port, the cooling unit is disposed between last two stages of the twin screw extruders, and an outlet of a last-stage twin screw extruder is connected to the static mixing unit.

Abstract: An embodiment includes calculating an efficacy value of a context assigned to an asset, the efficacy value being based at least in part on a percentage of assets assigned to the context. The embodiment also includes calculating, responsive to the calculated efficacy value being within a predetermined range, a normalized relevance value of a first tag associated with the asset. The embodiment also includes generating relative relevance value for the first tag and a reason code associated with a basis for the relative relevance value of the first tag based at least in part on the normalized relevance value of the first tag. The embodiment also includes initiating, responsive to generating the relative relevance value and the reason code for the first tag, a database command on a training dataset stored in the database that includes the first tag.

Abstract: An embodiment includes generating an input document that includes a plurality of text fields of attribute data. The embodiment also includes extracting a set of candidate features from the attribute data using a feature extraction module that evaluates the attribute data using first and second machine learning models, where the first machine learning model scores terms in the input document and the second machine learning model includes a deep learning model. The embodiment also includes calculating feature-selection values for respective features of the set of candidate features and generating tag information for a remote computing asset using a machine learning classifier that predicts the tag information based on the feature-selection values.

Abstract: In a described example, an electrical apparatus includes: a metal layer formed over a non-device side of a semiconductor device die, the semiconductor device die having devices formed on a device side of the semiconductor device die opposite the non-device side; a first side of the metal layer bonded to a die mount pad on a package substrate; a second side of the metal layer formed over a roughened surface on the non-device side of the semiconductor device die, the roughened surface having an average surface roughness (Ra) between 40 nm and 500 nm; bond pads on the semiconductor device die electrically coupled to conductive leads on the package substrate; and mold compound covering at least a portion of the semiconductor device die and at least a portion of the conductive leads.

Abstract: A page data compiling apparatus and method, the method being performed by a server, includes obtaining initial page structure data that is generated using an extended markup language, parsing the initial page structure data to generate scripting language page data comprising a page generation code and a data variable set, an input to the page generation code being a current data set that is determined according to the data variable set, and an output of the page generation code being a node tree matching the input current data set, and sending the scripting language page data to a terminal so that the terminal determines the current data set according to the data variable set, determines the matching node tree according to the current data set and the page generation code in the scripting language page data, and displays a page according to the node tree.

Abstract: In some embodiments, a method of forming an integrated circuit includes providing a semiconductor substrate having an electronic circuit formed on a front side, and having a first material layer located over a second side of the substrate and a second material layer located between the first material layer and the second side. At least a portion of the first material layer is removed using a first chemical etching process, thereby exposing the second material layer. At least a portion of the second material layer is removed using a second chemical etching process. A portion of the substrate is then mechanically removed from the second side.

Abstract: A page data compiling apparatus and method, the method being performed by a server, includes obtaining initial page structure data that is generated using an extended markup language, parsing the initial page structure data to generate scripting language page data comprising a page generation code and a data variable set, an input to the page generation code being a current data set that is determined according to the data variable set, and an output of the page generation code being a node tree matching the input current data set, and sending the scripting language page data to a terminal so that the terminal determines the current data set according to the data variable set, determines the matching node tree according to the current data set and the page generation code in the scripting language page data, and displays a page according to the node tree.

Abstract: In some embodiments, a method of forming an integrated circuit includes providing a semiconductor substrate having an electronic circuit formed on a front side, and having a first material layer located over a second side of the substrate and a second material layer located between the first material layer and the second side. At least a portion of the first material layer is removed using a first chemical etching process, thereby exposing the second material layer. At least a portion of the second material layer is removed using a second chemical etching process. A portion of the substrate is then mechanically removed from the second side.

Abstract: The present invention provides tools and methods for the systematic analysis of genetic interactions in immune cells. The present invention provides tools and methods for modulating immune cell phenotypes and compositions, combinatorial probing of cellular circuits, for dissecting cellular circuitry, for delineating molecular pathways, and/or for identifying relevant targets for therapeutics development.

Abstract: In some embodiments, a method includes wet-etching a first film layer of a plurality of film layers stacked on a semiconductor substrate, the wet-etching of the first film layer performed using a first chemical, where the first film layer is an outermost film layer stacked on the semiconductor substrate. The method further includes wet-etching a second film layer of the plurality of film layers using a second chemical. The method also includes using a mechanical grinding wheel to grind the semiconductor substrate to reduce a thickness of the semiconductor substrate.

Abstract: In some embodiments, a method includes wet-etching a first film layer of a plurality of film layers stacked on a semiconductor substrate, the wet-etching of the first film layer performed using a first chemical, where the first film layer is an outermost film layer stacked on the semiconductor substrate. The method further includes wet-etching a second film layer of the plurality of film layers using a second chemical. The method also includes using a mechanical grinding wheel to grind the semiconductor substrate to reduce a thickness of the semiconductor substrate.

Abstract: A chemical solution cleaning process for removing backside contamination prior to metallization involves selective chemistries of a mixture containing NH4OH and H2O2 that may be diluted to specific concentrations depending upon the topside metal and passivation of a semiconductor wafer, which is applied after removing a topside protection material to protect the topside circuitry.

Abstract: A chemical solution cleaning process for removing backside contamination prior to metallization involves selective chemistries of a mixture containing NH4OH and H2O2 that may be diluted to specific concentrations depending upon the topside metal and passivation of a semiconductor wafer, which is applied after removing a topside protection material to protect the topside circuitry.