Abstract: A path determination method includes: obtaining current position information and destination position information of a target vehicle; determining a candidate path of the target vehicle according to the current position information and the destination position information; acquiring road condition information of the candidate path and reference vehicle information; determining first energy consumption information required to be consumed by the target vehicle to travel on the candidate path over a unit distance according to the road condition information and the reference vehicle information; and recommending the candidate path to the target vehicle according to the first energy consumption information.

Abstract: Provided are a preparation method of a pyridazinone derivative, an intermediate thereof, and a preparation method of the intermediate. The method has the advantages of easily available raw materials, simple steps, low costs, good intermediate stability, high purity and high yield, and is suitable for large-scale industrial production.

Abstract: An anti-nuclear radiation magnetic fluid sealing device includes a magnetically conductive rotating shaft, a magnetically conductive housing, a left snap ring, a left bearing, a left magnetically isolating ring, a left pole shoe, a magnetically isolating sleeve, an outer permanent magnet, an inner permanent magnet, a right pole shoe, a right magnetically isolating ring, a right bearing, a right snap ring, an end cover, an anti-radiation coating, an anti-magnetic coating, a magnetic fluid I, and a magnetic fluid II. An outer magnetic circuit and an inner magnetic circuit are formed using the magnetically isolating sleeve. The magnetically conductive housing, the left pole shoe, the outer permanent magnet, the right pole shoe, and the magnetic fluid I forms a magnetic fluid static seal. The magnetically conductive rotating shaft, the left pole shoe, the inner permanent magnet, the right pole shoe, and the magnetic fluid II form a magnetic fluid dynamic seal.

Abstract: The exemplary embodiments disclose a method, a computer program product, and a computer system for determining that one or more model pipelines satisfy one or more constraints. The exemplary embodiments may include detecting a user uploading data, one or more constraints, and one or more model pipelines, collecting the data, the one or more constraints, and the one or more model pipelines, and determining that one or more of the model pipelines satisfies all of the one or more constraints based on applying one or more algorithms to the collected data, constraints, and model pipelines.

Abstract: A battery internal temperature information processing method, a computer device, and a storage medium that first acquire off-line testing data for off-line testing a battery module and construct an equivalent thermal network model from the off-line testing data, determine optimal model parameters of the equivalent thermal network model based on a multi-objective function fitting method; thereafter, a first battery internal temperature estimate of the battery of the vehicle at a first moment in actual operation of the vehicle is determined, in turn, based on the acquired initial state vector values of the battery of the vehicle, first operational data at a first moment in actual operation of the vehicle, and an equivalent thermal network model including the optimal model parameters.

Abstract: Use a computerized trained graph neural network model to classify an input instance with a predicted label. With a computerized graph neural network interpretation module, compute a gradient-based saliency matrix based on the input instance and the predicted label, by taking a partial derivative of class prediction with respect to an adjacency matrix of the model. With a computerized user interface, obtain user input responsive to the gradient-based saliency matrix. Optionally, modify the trained graph neural network model based on the user input; and re-classify the input instance with a new predicted label based on the modified trained graph neural network model.

Abstract: An adversarial robustness testing method, system, and computer program product include testing, via an accelerator, a robustness of a black-box system under different access settings, where the testing includes tearing down the robustness testing to a subtask of a predetermined size.

Abstract: A warning method for battery thermal runaway includes: acquiring current temperature data of each temperature sensor arranged in a battery pack, current voltage data of each voltage sensor arranged in the battery pack, and current sensor disconnection data of each temperature sensor; calculating a number of occurrences of a primary feature at a current moment according to the current temperature data; calculating a number of occurrences of a secondary feature at the current moment according to the current voltage data and the current sensor disconnection data in a case that the number of occurrences of the primary feature is greater than 0; calculating a sum of the number of occurrences of the primary feature and the number of occurrences of the secondary feature at the current moment; and sending a warning for battery thermal runaway when the sum is greater than a preset feature number threshold.

Abstract: A method including training a machine-learning model, based on historical data, with a maximization problem and one or more minimization problems to improve one or more fairness metrics. The method also can include receiving real-time data. The method additionally can include outputting a risk score generated based on the machine-learning model, as trained, and the real-time data. Other embodiments are described.

Abstract: Transfer learning in machine learning can include receiving a machine learning model. Target domain training data for reprogramming the machine learning model using transfer learning can be received. The target domain training data can be transformed by performing a transformation function on the target domain training data. Output labels of the machine learning model can be mapped to target labels associated with the target domain training data. The transformation function can be trained by optimizing a parameter of the transformation function. The machine learning model can be reprogrammed based on input data transformed by the transformation function and a mapping of the output labels to target labels.

Abstract: Provided is a device sealed with a magnetic liquid. The device includes: a rotary shaft, a tank body, a control unit, a first module, a second module, a magnetic liquid, and a pole-tooth. The first module and the second module are in the same configuration, each consists of an outer shell, a left pole-shoe, an electromagnet, a control wiring, a right pole-shoe, and a circlip. The device includes at least two modular structures; the control unit controls a first electromagnet and a second electromagnet to be magnetized to alternately bear a sealing role.

Abstract: Provided is a device sealed with a magnetic liquid. The device includes: a rotary shaft, a first bearing, a tank body, a first magnetism isolation ring, a first gasket ring, a first pole-shoe, a permanent magnet, a second pole-shoe, a second gasket ring, a second magnetism isolation ring, a second bearing, an end cover, a pole-tooth and a water delivery coating. The water delivery coating strips are coated on the an exterior circumferential surface of the rotary shaft at intervals, where each water delivery coating strip contains three parts with different water delivering directions individually.

Abstract: The present disclosure provides a risk assessment method of water inrush in tunnels constructed in water-rich grounds. The method includes the following steps: simulating a tunnel excavation process by finite element software MIDAS GTS NX and fluid-structure interaction; according to a research method of control variables, analyzing effects of a groundwater level, an elastic modulus and advanced pipe shed grouting on the stability of surrounding rock, and improving an algorithm of a radial basis function (RBF) neural network using a Grey Relation Analysis (GRA)-based Partitioning Around Medoid (PAM) clustering algorithm to assess risks of water inrush occurring in Qingdao area.

Abstract: The present disclosure provides a multi-factor quantitative analysis method for deformation of a neighborhood tunnel. The method includes the following steps: analyzing monitoring data generated at a tunnel site; simulating collapse occurring at a shallow buried section of a tunnel; determining the degree of influence of each factor on the tunnel and a stratum; and determining quantitative influence of each factor on tunnel deformation. The present disclosure can not only provide an accurate theoretical basis for the construction of the shallow buried section of the small-distance tunnel, but also guarantee safety and cost saving during tunnel construction.

Abstract: A method including training a machine-learning model, based on historical data, with a maximization problem and one or more minimization problems to improve one or more fairness metrics. The method also can include receiving real-time data. The method additionally can include generating a risk score based on the machine-learning model, as trained, and the real-time data. Other embodiments are described.

Abstract: An adversarial robustness testing method, system, and computer program product include testing, via an accelerator, a robustness of a black-box system under different access settings, where the testing includes tearing down the robustness testing to a subtask of a predetermined size.

Abstract: A hybrid-distance adversarial patch generator can be trained to generate a hybrid adversarial patch effective at multiple distances. The hybrid patch can be inserted into multiple sample images, each depicting an object, to simulate inclusion of the hybrid patch at multiple distances. The multiple sample images can then be used to train an object detection model to detect the objects.

Abstract: A battery temperature estimation method includes fitting, when a battery is in an offline state, a first function relationship according to corresponding admittances of the battery at different test temperatures, and obtaining a temperature distribution model of the battery according to the shape and the size of the battery, and determining a second function relationship corresponding to internal temperatures and a surface temperature by combining with the first function relationship. The second function relationship is used for estimating the internal temperature of the battery by using the surface temperature and the admittances of the battery.

Abstract: An adversarial robustness testing method, system, and computer program product include testing a robustness of a black-box system under different access settings via an accelerator.