3results about How to "Will not affect each other" patented technology

The invention relates to the technical field of glass processing, and discloses a modified glass kiln which comprises a mounting plate, the mounting plate is fixedly mounted at the bottom of the kiln, a flame gun is arranged on one side of the mounting plate, a sliding device is mounted between the flame gun and the mounting plate, and the sliding device is used for driving the flame gun to move transversely. A lifting mechanism is arranged on one side of the flame gun and comprises a first gear and a rack which are meshed with each other, a transmission mechanism is arranged on one side of the first gear and comprises a first chain wheel, a chain and a second chain wheel which are meshed with each other, and a rotating shaft is fixedly installed on the second chain wheel. A power device is arranged at one end of the second chain wheel; the flame gun is arranged to replace traditional coal combustion, environmental protection is achieved, the double spray guns are arranged, replacement can be achieved during long-time use, damage to the spray guns due to too high temperature is avoided, and the situation that the spray guns cannot work when blocked can be prevented.

This invention relates to the field of system interface technology, specifically to a non-intrusive interface software system interface implementation method, comprising the following steps: S1: Implementing non-intrusive API middleware by defining a middleware constructor or adding injection points to the interface methods of an object. This invention achieves data interaction through non-intrusive API middleware, protecting the stability and integrity of existing software. It avoids directly modifying the source code of existing software, thereby protecting its stability and integrity, reducing the risks that may be introduced by directly modifying the source code, preventing the introduction of new errors or damage to existing functions. Furthermore, using non-intrusive API middleware allows for faster integration and extension of existing software, accelerating development and deployment, reducing the complexity of integration and extension. Simultaneously, by introducing a middleware layer, existing software and external systems can evolve independently without affecting each other, achieving better usability.

The embodiment of the invention provides a privacy leakage detection method based on a parallel deep neural network. In the embodiment of the invention, firstly, sensitive privacy features are extracted from each piece of privacy sample data of an obtained privacy data set to obtain sensitive privacy feature vectors corresponding to the privacy sample data; afterwards, N CPU cores on the device parallelly train a corresponding DNN model based on the sensitive privacy feature vectors corresponding to the privacy sample data, so that when any detection device needs to detect any target network flow, the trained DNN model is utilized to detect whether privacy leakage occurs in the target network flow or not; therefore, detection of privacy leakage of the Internet of Things equipment is realized, and information security of the Internet of Things equipment is ensured. In the embodiment of the invention, the N CPU cores are used for training the plurality of DNN models in parallel, so that the model parameters among the DNN models do not influence each other, the coupling among the DNN models is avoided, and the performance of each DNN model is improved.