Abstract: In an approach for post-modeling data visualization and analysis, a processor presents a first visualization of a training dataset in a first plot. Responsive to receiving a selection of a data group of the training dataset to analyze, a processor identifies three or fewer key model features of the data group of the training dataset. A processor ascertains a representative record of each key model feature of the three or fewer key model features using a Local Interpretable Model-Agnostic Explanation technique. A processor presents a second visualization of the three or fewer key model features and the representative record of each key model feature in a second plot.

Abstract: Systems and methods for displaying media files on a device are provided. The device provides a first mode that displays a subset of media files, determined by a user query, from a plurality of media files. Once activated, the first mode persists on the device prior to becoming inactive. A second mode of the device displays the plurality of media files. The second mode is active when the first mode is inactive. An instruction is received from a user. When the instruction specifies the first mode by inclusion of a user query, a corresponding subset of files is obtained from a remote system. The subset of files is sequentially displayed until the period of time has elapsed according to the first mode. When the instruction does not specify a query, the plurality of files is polled for from a remote device and sequentially displayed according to the second mode.

Abstract: A video encoding method includes: based on at least one of first distortion aware information about a current encoding unit and second distortion aware information about a corresponding reference encoding unit, determining a first predicted value of the current encoding unit using at least one interpolation filter, wherein the at least one type of interpolation filter may include an artificial intelligence (AI) interpolation filter; and encoding the current encoding unit based on the first predicted value of the current encoding unit.

Abstract: The present invention relates to the technical field of gas treatment, and in particular to a gas circulation apparatus for degradation of a sulfur hexafluoride gas, and a gas scrubbing mechanism, the gas circulation apparatus including: gas cylinders, gas circuits, relief valves, electromagnetic flowmeters, temperature sensors, flow sensors and electromagnetic valves, a discharge reactor, a gas scrubbing mechanism, a buffer gas bag, and a buffer gas chamber, According to the device, the tail gas can be pretreated, temporarily stored and recycled in the degradation process of SF6.

Abstract: The present disclosure is directed to a method of producing induced midbrain dopaminergic progenitor (imDAP) cells which can provide high efficiency for differentiation of imDAP cells. The present disclosure also provides a substantially homogeneous population of imDAP cells.

Abstract: A system is described for allowing a user to communicate with an agent of a listing network platform. The system receives, by a network site, a user interaction in a communication session with an agent of a listing network platform. The system analyzes, by a first machine learning model, a profile associated with the user on the listing network platform to predict a subset of information that is relevant to the user interaction with the communication session. The system combines the subset of information into a prompt and processes the prompt by a generative machine learning model to generate a message that responds to the user interaction. The system, in response to receiving the user interaction, presents the message by the agent of the listing network platform to the user in a user interface of the listing network platform.

Abstract: Determining whether synthetic data is sufficient for utilization in connection with one or more machine learning models. The computing device accesses a protected batch of data associated with a machine learning model. The computing device accesses a simulated batch of data, the simulated batch of data based upon but anonymizing the protected batch of data. The computing device accesses one or more comparisons of one or more variables in the protected batch of data and the simulated batch of data to obtain a similarity value. The computing device performs a machine learning function utilizing at least in-part the simulated batch of data if the similarity value exceeds a similarity threshold.

Abstract: An embodiment configures a plurality of parameters, the parameters being usable to generate artificial data from original data, the configuring adjusting a level of privacy in the artificial data. An embodiment fits a distribution type to a variable of the original data. An embodiment adjusts, using a desired level of privacy and the distribution type, a level of noise, wherein the level of noise corresponds to the desired level of privacy. An embodiment generates, using the distribution type and the level of noise, the artificial data, the artificial data achieving the desired level of privacy by including noise data corresponding to the level of noise.

Abstract: A computer-implemented method for anomaly detection for a time series data is provided. Aspects include receiving a time series data including a plurality of sequential data points, calculating an expected next value for the time series data based on the plurality of sequential data points, and receiving an actual next value corresponding to the time series data. Aspects also include calculating an anomaly strength estimate based on the expected next value and the actual next value, identifying one of a plurality of anomaly detection pipelines based on the anomaly strength estimate and a portrait associated with each of the plurality of anomaly detection pipelines, and obtaining an anomaly prediction by inputting the time series data and the actual next value into the one of the plurality of anomaly detection pipelines.

Abstract: Disclosed are compounds of Formula (I): or a pharmaceutically acceptable salt, a tautomer, a stereoisomer, or a deuterated analog thereof, wherein R2, R3, R4, Y1, Y2, X, and Z are as described in any of the embodiments described in this disclosure; compositions thereof; and uses thereof.

Abstract: An adhesive composition is described comprising a polyisobutylene polymer component; and up to 30 wt.-% of at least one aliphatic multifunctional component comprising at least two ethylenically unsaturated groups selected from (meth)acryl or vinyl ether. The monomer comprises a hydrocarbon moiety with greater than 12 contiguous carbon atoms. When the hydrocarbon moiety is branched, the hydrocarbon moiety comprises side chains with at least two carbon atoms. The aliphatic multifunctional component is sufficiently compatible such that crosslinked adhesive composition at a thickness of 20 microns has a haze of less than 3%. Also described are adhesive articles.

Abstract: Embodiments analyze a query pattern of an incoming query on a database, perform a semantic analysis of the query pattern of the incoming query, generate a re-write query that has an improved query performance in comparison to a query performance of the incoming query based on the analyzed query pattern and the semantic analysis; build a query model using machine learning based on at least one of the query pattern and the semantic analysis; and apply the re-write query by performing the re-write query on the database to provide the improved query performance.

Abstract: A computer-implemented method for generating an artificial data set is provided. Aspects include obtaining an input data set, calculating an association between the plurality of categorical variables of the input data set, and creating, based on the association, a plurality of clusters of categorical variables. Aspects also include identifying a key variable for each of the plurality of clusters of categorical variables, creating a key cluster for each of the plurality of clusters, and creating a cluster contingency table for each of the clusters. Aspects further include generating, based on the cluster contingency table for each of the plurality of clusters and for the key cluster, a data set for each of the plurality of clusters and the key cluster and generating the artificial data set based on a combination of the data set for each of the plurality of clusters and the key cluster.

Abstract: Adhesive articles include a substrate; and a hot melt processable pressure sensitive adhesive on the substrate. The hot melt processable pressure sensitive adhesive is a (meth)acrylate-based copolymer that is the reaction product of a reaction mixture that is free of acidic or basic monomers, and includes an alkyl (meth)acrylate, a hydroxyl-functional (meth)acrylate, and a photocrosslinker. The (meth)acrylate-based polymer is prepared in a thermoplastic package.

Abstract: Solid-state lithium ion electrolytes of lithium metal nitride based compounds are provided which contain an anionic framework capable of conducting lithium ions. Materials of specific formulae are provided and methods to alter the materials with inclusion of aliovalent ions shown. Lithium batteries containing the composite lithium ion electrolytes are provided. Electrodes containing the lithium metal nitride based composites are also provided.

Abstract: A computer-implemented method for performing data difference evaluation is provided. Aspects include obtaining a first data set and a second data set, creating a first plurality of feature vectors by inputting the first data set into each of a plurality of models, and creating a second plurality of feature vectors by inputting the second data set into each of the plurality of models. Aspects also include identifying a mapping between elements of the first plurality of vectors and elements the second plurality of feature vectors created by a same model of the plurality of models, calculating, for each of the plurality of models based at least in part on the mapping, a model distance between the first data set and the second data set, and calculating, based at least in part on the model distances, an ensemble distance between first data set and the second data set.

Abstract: An electronic device includes a transceiver and processing circuitry that is operatively coupled to the transceiver. The processing circuitry is configured to transmit, via the transceiver and to a second electronic device, a request for a wireless communication session with the second electronic device. The processing circuitry is also configured to communicate, via the transceiver, one or more first wireless signals during the wireless communication session with the second electronic device. Additionally, the processing circuitry is configured, after communicating the one or more first wireless signals, to extend the wireless communication session by transmitting, via the transceiver and to the second electronic device, one or more second wireless signals based on no wireless signals being communicated via the wireless communication session for a duration of time.