Abstract: A control system of an electronic-controlled oil-gas dual fuel engine includes electronic control pumps, fuel gas injection electromagnetic valves, a fuel gas control device and a fuel oil control device. The fuel gas control device and the fuel oil control device are electrically connected with a control device of the engine. The fuel gas control device is electrically connected with the fuel gas injection electromagnetic valves and controls the opening time and the opening duration of each fuel gas injection electromagnetic valve installed on a pipeline between a natural gas rail and a cylinder cover air inlet channel of the engine. The fuel oil control device is electrically connected with the electronic control pumps, and controls the starting time and the operation duration of the electronic control pump, and the electronic control pumps are installed on a pipeline between an engine fuel oil rail and a cylinder cover fuel injector.

Abstract: A computer implemented method for machine learning model training. A number of processor units creates a cluster model comprising labeled samples and unlabeled samples. The number of processor units identifies cluster information for the labeled samples from the cluster model. The number of processor units adds a set of new features to a set of original features for the labeled samples using the cluster information to form an extended set of features for the labeled samples, wherein the labeled samples with the set of original features and the set of new features form a training data set for training a machine learning model.

Abstract: An electronic device receives an indication of a number of physical resource blocks and subcarrier spacing of at least a portion of a transmission channel and determines a dynamic transmission bandwidth, or receives an indication of a modulation coding scheme of the transmission channel and determines a modulation order. The electronic device transmits, using a transmitter, a signal over at least the portion of the transmission channel based on the dynamic transmission bandwidth being less than or equal to a threshold bandwidth, or the modulation order not corresponding to an additional power backoff, using a first power based on a maximum output power capacity of the electronic device and a maximum power reduction. Otherwise, the electronic device transmits the signal over at least the portion of the transmission channel at a second power based on the maximum output power capacity, the maximum power reduction and the additional power backoff.

Abstract: Embodiments of the present disclosure relate to methods, systems, and computer program products for classification based on imbalanced dataset. In a method, a plurality of predictive models are generated based on a plurality of positive samples included in an imbalanced dataset, respectively, an amount of the plurality of positive samples being below an amount of a plurality of negative samples that are included in the imbalance dataset, and each sample in the plurality of positive and negative samples including a plurality of parameters. A plurality of influential parameter groups are identified from the plurality of parameters for the plurality of positive samples, respectively. A final predictive model is determined based on the plurality of predictive models and the plurality of influential parameter groups, the final predictive model being used for classifying a sample into one of a positive type and a negative type.

Abstract: The invention relates to the field of health food technologies, and particularly to a composition and an application thereof in preparing a product for protecting mitochondria. The invention provides a composition, the raw materials of which include Haematococcus pluvialis, Lycium ruthenicum, Cordyceps militaris and nicotinamide. The composition has the effects of improving an oxidative stress level under a mitochondrial dysfunction and delaying mitochondrion-related aging. Compared with a single constituent, constituents in the composition cooperate with each other to produce a synergistic effect, which significantly improves an effect of protecting a mitochondrial function.

Abstract: Polymer composite materials and methods of preparation are discussed. The composite material may comprise a polyurethane foam and a plurality of inorganic particles dispersed in the polyurethane foam. The composite material may have moisture movement properties, such that (a) a sample of the composite material having a length of 48 inches has a moisture movement of less than 0.15% along the length, and/or (b) a sample having a length of 6 inches has a moisture movement of less than 0.8% along the length, when submerged in 45° C. distilled water for 14 days.

Abstract: Embodiments herein describe computer-implemented methods, computer program products, and computer systems for determining record importance. The methods may include providing a first trained model having a first trained model accuracy. Further, the methods may include clustering the training data to generate clustered data groups, extracting a first clustered data group from the clustered data groups to identify first model test data, processing the first model test data using the first trained model to generate first trained model output data having first test data accuracy, and labeling the first clustered data group with a first record importance level based on a first comparison between the first trained model accuracy and the first test data accuracy. Further, the methods may include clustering the training data by processing the training data using hierarchical clustering to group the training data into the clustered data groups based on features corresponding to a hierarchy of importance.

Abstract: A method includes: receiving, by a computing device, an issue definition of an issue with software; generating, by the computing device and based on the issue definition, an urgency score for the issue, the urgency score representing an urgency of resolving the issue; generating, by the computing device and based on the issue definition, a complexity score for the issue, the complexity score representing a complexity of the issue; identifying, by the computing device using natural language processing and based on the urgency score and the complexity score, an assignee to address the issue, the assignee being a team member of a plurality of team members; recommending, by the computing device, to a user the assignee for assignment to address the issue; and tracking, by the computing device, progress of resolving the issue.

Abstract: An embodiment includes parsing conversation data to extract a message dataset and a user dataset. The embodiment classifies the message dataset into a category using machine learning processing and identifies the category as a top category based at least in part on an amount of the conversation data associated with the category. The embodiment generates impact data associated with the user dataset based on actions in the conversation data by the user. The embodiment generates role data associated with the user by applying a rule to the conversation data for the user. The embodiment generates key index data associated with the message dataset by identifying interactions with a message represented by the message dataset. The embodiment generates output data arranged according to a specified data format that is compatible with a user interface.

Abstract: Solid-state lithium ion electrolytes of lithium silicate based composites are provided which contain an anionic framework capable of conducting lithium ions. An activation energy for lithium ion migration in the solid state lithium ion electrolytes is 0.5 eV or less and room temperature conductivities are greater than 100.5 S/cm. Composites of specific formulae are provided and methods to alter the composite materials with inclusion of aliovalent ions shown. Lithium batteries containing the composite lithium ion electrolytes are also provided.

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 method for receiving an audiovisual data set that includes audio and/or visual content, receiving a topical data set that includes an indication of, at least, the plurality of topics and the plurality of subtopics, receiving a time mapping data set that maps each topic and subtopic to an associated time point in the audio and/or visual content, creating a mind map diagram, and presenting the mind map to a user.

Abstract: Performing predictive analysis on running batch jobs is provided. A series of batch end time predictive models is retrieved according to a sequence of milestone jobs in a batch of jobs. Retrieved batch end time predictive models are assembled into an aggregate batch end time predictive model to increase accuracy and stability of an end time prediction of the batch of jobs. The aggregate batch end time predictive model is utilized to predict an end time of the batch of jobs during running of the batch of jobs to form a predicted end time of the batch of jobs.

Abstract: Aspects are described for a user equipment (UE) comprising a transceiver configured to enable wireless communication with a base station; and a processor communicatively coupled to the transceiver. The processor is configured to receive a sounding reference signal (SRS) resource configuration from the base station, wherein the SRS resource configuration indicates at least a first SRS resource and a second SRS resource. The processor is further configured to transmit a first SRS via the first SRS resource to the base station using a first antenna coupled to the transceiver and transmit a second SRS via the second SRS resource to the base station using a second antenna coupled to the transceiver.

Abstract: An article comprises a body and a conformal protective layer on at least one surface of the body. The conformal protective layer is a plasma resistant rare earth oxide film having a thickness of less than 1000 ?m, wherein the plasma resistant rare earth oxide film is selected from a group consisting of an Er—Y composition, an Er—Al—Y composition, an Er—Y—Zr composition, and an Er—Al composition.

Abstract: An article comprises a body and a conformal protective layer on at least one surface of the body. The conformal protective layer is a plasma resistant rare earth oxide film having a thickness of less than 1000 ?m, wherein the plasma resistant rare earth oxide film consists essentially of 40 mol % to less than 100 mol % of Y2O3, over 0 mol % to 60 mol % of ZrO2, and 0 mol % to 9 mol % of Al2O3.

Abstract: An article comprises a body and a conformal protective layer on at least one surface of the body. The conformal protective layer is a plasma resistant rare earth oxide film having a thickness of less than 1000 ?m, wherein the plasma resistant rare earth oxide is selected from a group consisting of YF3, Er4Al2O9, ErAlO3, and a ceramic compound comprising Y4Al2O9 and a solid-solution of Y2O3—ZrO2.

Abstract: A method for visually tracking a gaze point of a human eye includes: periodically obtaining position coordinates of a human eye of a driver of a host vehicle and coordinates of a gaze point of a sightline of the human eye on ab inner side of a current projection screen; in combination with a refractive index and a curvature of the current projection screen, coordinates of a gaze point of the sightline on an outer side of the current projection screen and a corresponding refracted light path formed by outward refraction of the sightline are obtained, and in combination with a preset normal viewing distance of the human eye, a final gaze point of the sightline on the refracted light path and coordinates of the final gaze point are obtained.

Abstract: A method includes training a plurality of different types of machine learning models using a training dataset to produce a set of trained machine learning models and determining a lift of each trained machine learning model in the set of trained machine learning models using a validation dataset. The method also includes selecting a trained machine learning model from the set of trained machine learning models that has a highest lift of the set of trained machine learning models and predicting a likelihood that a person will perform an action by applying the selected trained machine learning model to data about the person.

Abstract: A technique for determining an adaptive quantization parameter offset for a block of encoded video includes obtaining a rate control factor for the quantization parameter, determining a content-based quantization parameter factor for the quantization parameter, determining an adaptive variance based quantization offset based on content-based quantization parameter factors for a frame prior to the current frame, and combining the rate control factor, the content-based quantization parameter factor, and the adaptive offset to generate the quantization parameter.