Abstract: An appliance heating control method and apparatus for user customizable vaping. The method comprises: acquiring appliance environment information and cigarette parameter information, and selecting, from a cigarette heating temperature curve library corresponding to the cigarette parameter information, an initial heating temperature curve that matches the appliance environment information; generating parameter adjustment guidance information on the basis of the initial heating temperature curve, and displaying the initial heating temperature curve and the parameter adjustment guidance information; and receiving a parameter adjustment instruction, adjusting the initial heating temperature curve on the basis of the parameter adjustment instruction, so as to obtain an adjusted heating temperature curve, and controlling, according to the adjusted heating temperature curve, an appliance to perform heating.

Abstract: A temperature control method and apparatus for a magnetic heat-emitting body, and an electronic device. The temperature control method comprises: acquiring parameter information of at least one heat-emitting body in a cigarette to be smoked; calculating a first intensity of a magnetic field that corresponds to a Curie temperature, and controlling a first intensity of current, which passes through a coil inside a smoking set, such that the intensity of a magnetic field that is generated by the coil is constant at the first intensity of the magnetic field; and receiving a temperature adjustment instruction, determining a required temperature corresponding to the temperature adjustment instruction, calculating a second intensity of current on the basis of the required temperature and a resistance temperature coefficient, and controlling the intensity of current, which passes through the heat-emitting body, to be the second intensity of current.

Abstract: The present disclosure relates to the technical field of protective coatings, and provides a graphene oxide (GO)-modified styrene-acrylic Pickering emulsion and a composite emulsion, and preparation methods and use. In the present disclosure, GO is added during polymerization of a styrene-acrylic monomer, and the GO is attached to an interface of a styrene-acrylic core while forming the styrene-acrylic core; and the GO is “stitched” at the interface of the styrene-acrylic core by a silane coupling agent, thus giving the GO a better dispersion effect. After adding a shell phase emulsion, a part of the styrene-acrylic core that is not completely wrapped by a GO sheet may be grafted with a shell phase, and cross-linking between a core phase and the shell phase can further enhance a steric stability of the GO; and the GO can fully connect the styrene-acrylic core with a siloxane shell, improving the molecular configuration of a siloxane component.

Abstract: Methods for training a process model and determining ranking of simulated patterns (e.g., corresponding to hot spots). A method involves obtaining a training data set including: (i) a simulated pattern associated with a mask pattern to be printed on a substrate, (ii) inspection data of a printed pattern imaged on the substrate using the mask pattern, and (iii) measured values of a parameter of the patterning process applied during imaging of the mask pattern on the substrate; and training a machine learning model for the patterning process based on the training data set to predict a difference in a characteristic of the simulated pattern and the printed pattern. The trained machine learning model can be used for determining a ranking of hot spots. In another method a model is trained based on measurement data to predict ranking of the hot spots.

Abstract: The present disclosure provides a styrene acrylate-siloxane composite emulsion with a core-shell structure, and a preparation method and use thereof, and relates to the technical field of protective coatings. In the present disclosure, a core emulsion is prepared through two-step emulsification with styrene, an acrylate monomer, a first emulsifying agent, a first initiator, a second initiator, an alkaline reagent, and water as raw materials; then a shell emulsion is prepared with a siloxane monomer, a hydroxyl-containing acrylate monomer, an emulsifying agent, and water as raw materials; and then the core emulsion, the shell emulsion, and an initiator are subjected to a grafting reaction to obtain the styrene acrylate-siloxane composite emulsion with a core-shell structure.

Abstract: A U-shaped e-cigarette peristaltic pump includes: a carrier; a drive assembly; a transmission assembly; and a peristaltic assembly. The drive assembly is arranged on the carrier. The peristaltic assembly and the drive assembly are arranged side by side on a same side of the carrier. A first accommodating space is provided between the drive assembly and the carrier. A second accommodating space is provided between the peristaltic assembly and the carrier. The transmission assembly is respectively in the first accommodating space and the second accommodating space. The drive assembly is connected to the peristaltic assembly through the transmission assembly.

Abstract: An apparatus and method of feature extraction for identifying a pattern. An improved method includes obtaining data representative of a pattern instance, dividing the pattern instance into a plurality of zones, determining a representative characteristic of a zone of the plurality of zones, generating a representation of the pattern instance using a feature vector, wherein the feature vector includes an element corresponding to the representative characteristic, wherein the representative characteristic is indicative of a spatial distribution of one or more features of the zone. The method may also include classifying and/or selecting pattern instances based on the feature vector.

Abstract: Methods for training a process model and determining ranking of simulated patterns (e.g., corresponding to hot spots). A method involves obtaining a training data set including: (i) a simulated pattern associated with a mask pattern to be printed on a substrate, (ii) inspection data of a printed pattern imaged on the substrate using the mask pattern, and (iii) measured values of a parameter of the patterning process applied during imaging of the mask pattern on the substrate; and training a machine learning model for the patterning process based on the training data set to predict a difference in a characteristic of the simulated pattern and the printed pattern. The trained machine learning model can be used for determining a ranking of hot spots. In another method a model is trained based on measurement data to predict ranking of the hot spots.

Abstract: A free-bending forming apparatus for a tubular component using differential temperatures and a method thereof are disclosed. The apparatus includes an isothermal heating device and a heating device for the differential temperatures. The isothermal heating device is configured to preheat an inside and an outside of a bending section of the tubular component to a predetermined temperature to form a preheated bending section before bending and forming. The heating device for the differential temperatures is configured to heat the inside and the outside of the preheated bending section of the tubular component respectively to different temperatures, and the temperature at the outside is higher than that at the inside. The heating device for the differential temperatures is provided between a pressing device and a guiding mechanism, and the isothermal heating device is provided between the pressing device and the heating device for the differential temperatures.

Abstract: Methods for training a process model and determining ranking of simulated patterns (e.g., corresponding to hot spots). A method involves obtaining a training data set including: (i) a simulated pattern associated with a mask pattern to be printed on a substrate, (ii) inspection data of a printed pattern imaged on the substrate using the mask pattern, and (iii) measured values of a parameter of the patterning process applied during imaging of the mask pattern on the substrate; and training a machine learning model for the patterning process based on the training data set to predict a difference in a characteristic of the simulated pattern and the printed pattern. The trained machine learning model can be used for determining a ranking of hot spots. In another method a model is trained based on measurement data to predict ranking of the hot spots.

Abstract: Methods for training a process model and determining ranking of simulated patterns (e.g., corresponding to hot spots). A method involves obtaining a training data set including: (i) a simulated pattern associated with a mask pattern to be printed on a substrate, (ii) inspection data of a printed pattern imaged on the substrate using the mask pattern, and (iii) measured values of a parameter of the patterning process applied during imaging of the mask pattern on the substrate; and training a machine learning model for the patterning process based on the training data set to predict a difference in a characteristic of the simulated pattern and the printed pattern. The trained machine learning model can be used for determining a ranking of hot spots. In another method a model is trained based on measurement data to predict ranking of the hot spots.

Abstract: A cable-direction-adaptive ROV winch applied to non-DP-equipped motherships, includes a non-DP-equipped mothership, an A-shaped support and a winch cable-drawing roller provided on the non-DP-equipped mothership, and an underwater vehicle. A pulley is rotatably connected to the A-shaped support, the underwater vehicle is connected to an umbilical cable, the umbilical cable passes around the pulley to be connected to the winch cable-drawing roller, and a locating unit for guiding the umbilical cable is provided on the non-DP-equipped mothership. The A-shaped support is provided with a rod. The pulley includes a sliding section and a rotating section, and the sliding section is annular and slides on the rod along a direction of the rod. The rod has a groove, and a bulge portion is formed on the sliding section. The rotating section is rotatably connected to an outer circle of the sliding section via a shaft bearing.

Abstract: A cable-direction-adaptive ROV winch applied to non-DP-equipped motherships, includes a non-DP-equipped mothership, an A-shaped support and a winch cable-drawing roller provided on the non-DP-equipped mothership, and an underwater vehicle. A pulley is rotatably connected to the A-shaped support, the underwater vehicle is connected to an umbilical cable, the umbilical cable passes around the pulley to be connected to the winch cable-drawing roller, and a locating unit for guiding the umbilical cable is provided on the non-DP-equipped mothership. The A-shaped support is provided with a rod. The pulley includes a sliding section and a rotating section, and the sliding section is annular and slides on the rod along a direction of the rod. The rod has a groove, and a bulge portion is formed on the sliding section. The rotating section is rotatably connected to an outer circle of the sliding section via a shaft bearing.

Abstract: Disclosed is a method for identifying driving fatigue based on a CNN-LSTM deep learning model including: collecting electroencephalograph signals of a subject during simulated driving; randomly issuing an operating command during simulated driving, and dividing the electroencephalograph signals into fatigue data and non-fatigue data according to a reaction time for the subject to complete the operating command; performing band-pass filtering and mean removal preprocessing on the electroencephalograph signals, and respectively extracting N minutes of fatigue electroencephalograph signal data and N minutes of non-fatigue electroencephalograph signal data to be detected; performing independent component analysis on the electroencephalograph signal data to remove interference signals; establishing a CNN-LSTM model and setting network parameters of the CNN-LSTM model; transmitting the electroencephalograph signal data with interference signals removed to a CNN network for feature extraction; and reshaping data of

Abstract: A network topology service receives a request to validate a plurality of network connections of a network topology specified by an administrator or other network technician. The network topology service evaluates the network topology to determine the structure of the network topology, which is used to select an algorithm for organizing the network connections into one or more groups. The network topology service uses these groups to perform one or more non-destructive tests on network devices associated with the plurality of network connections in a manner that does not cause disruption to the network connections. The network topology service compiles the results of these one or more tests and provides these results to the administrator or other network technician.

Abstract: A network testing device is provided in order to validate network topology information and test various other attributes of a network. The network testing device may, in response to a command, obtain connection information from a network indicated in the command. The connection information may be compared to network topology information corresponding to the network. The network topology information may indicate which interfaces of a network device should be to be connected to which interfaces of other network devices. The network testing device may then return, in response to the command, a result of the comparison. Furthermore, the network testing device may return result of other network test performed by the network testing device on the network device.

Abstract: A network testing device is provided in order to validate network topology information and test various other attributes of a network. The network testing device may, in response to a command, obtain connection information from a network indicated in the command. The connection information may be compared to network topology information corresponding to the network. The network topology information may indicate which interfaces of a network device should be to be connected to which interfaces of other network devices. The network testing device may then return, in response to the command, a result of the comparison. Furthermore, the network testing device may return result of other network test performed by the network testing device on the network device.

Abstract: A network testing device is provided in order to validate network topology information and test various other attributes of a network. The network testing device may, in response to a command, obtain connection information from a network indicated in the command. The connection information may be compared to network topology information corresponding to the network. The network topology information may indicate which interfaces of a network device should be to be connected to which interfaces of other network devices. The network testing device may then return, in response to the command, a result of the comparison. Furthermore, the network testing device may return result of other network test performed by the network testing device on the network device.

Abstract: A method for controlling access to an electronic device, the electronic device activates a motion sensor to detect movement parameters, of a spatial moving operation of the electronic device, when a display device of the electronic device awakes from a sleep mode. once the movement parameters detected by the motion sensor match predetermined reference parameters, the electronic device is unlocked.