30results about How to "Reduce expertise" patented technology

The invention discloses a picture color filling method and device, which relate to the field of computer technology, and the main purpose is to solve the problem by selecting a graphics object to be processed in a page editor and filling the graphics object with a color by using the graphics editor. The existing page editor cannot directly fill the color of the pictures on the page. The main technical solution of the present invention is: obtain the outline information of the color block with a single color in the picture to be edited in the page editor; determine the graphic object to be processed according to the outline information of the color block; use the graphic editor in the page editor Fill the graphics object to be processed with color. The invention is mainly used for filling the pictures in the page with color during the page editing process.

The invention discloses an automatic security testing method based on the OSPF protocol, belonging to the technical field of router security testing. This method accesses the routing network through serial access or bypass access, listens to the interactive OSPF protocol, automatically obtains various parameters required for security testing, and performs maximum age, maximum serial number, and DD reporting as required. Security test methods such as document forgery and LSU message tampering are used to test the defense capability of routers. The invention realizes the automatic acquisition of test parameters by using the idea of ​​automation, can automatically acquire the test parameters after accessing the network, avoids learning a large number of routing professional skills for operators, and simplifies the process of router security testing.

The invention relates to a method that serves to control a machine (10) for processing plastics and other plasticisable materials such as powdered and / or ceramic substances. The machine has a mould opening and closing unit (12) for opening and closing an injection mould (14) having at least one mould cavity (16) for producing an injection moulded part (18) corresponding to the shape of the mould cavity (16); an injection moulding unit (20) having means for plasticising and for injection of the plasticisable material in the mould cavity (16); and a machine controller (22) which is connected to an expert knowledge source (34) and if required can be operated by the operator by means of an interactive contact. Information concerning the geometry of the injection moulded part (18) and / or the mould cavity (16) and the sprue geometry (24) are provided to the machine controller (22), in order to calculate at least one injection process taking the geometric information into consideration. Because the injection process is calculated, taking into consideration the geometric information, at least one progressive volume growth profile of the injection moulded part (18) in the filling direction of the mould cavity (16) is calculated, and taking into consideration the progressive volume growth profile at least one injection process is calculated, a simplified, fast and effective parameterisation of the injection moulding machine is made possible, the operator is relieved by the implemented expert knowledge, and the quality of the injection moulded part (18) is improved.

An embodiment of the present invention provides a fiber channel model simulation method, device, electronic equipment, and storage medium, the method comprising: acquiring signal data for simulated transmission of optical fiber; inputting the signal data and fiber length parameters into a preset The deep neural network model, according to the output result of the deep neural network model, determines the signal data output by the optical fiber channel of the optical fiber length; wherein, the deep neural network model, according to the determined optical fiber length and the sample signal of the channel output result data, obtained after training. A trained deep neural network network enables high-speed and robust fiber channel emulation of signal data. Compared with the current method, it has lower complexity, which greatly reduces the expertise and complexity required for modeling fiber channels. As long as sufficient input and output data and distance parameters are obtained, any fiber channel can be modeled , and the time required for modeling and model running is relatively short.