虚构的东西 发表于 2025-3-30 08:40:35
http://reply.papertrans.cn/15/1486/148522/148522_51.pngFibrinogen 发表于 2025-3-30 13:10:34
http://reply.papertrans.cn/15/1486/148522/148522_52.pngVEN 发表于 2025-3-30 17:34:43
J. S. R. Chisholm,R. S. Farwelltrol management mode and flow management mode. This not only improves the design efficiency of state machine to some extent but also enhances the portability of system sub-modules. Moreover, the article also provides a new thought for state machine design process. Different from the traditional statPeculate 发表于 2025-3-31 00:33:51
http://reply.papertrans.cn/15/1486/148522/148522_54.pngobsession 发表于 2025-3-31 04:50:41
http://reply.papertrans.cn/15/1486/148522/148522_55.pngVolatile-Oils 发表于 2025-3-31 05:45:04
http://reply.papertrans.cn/15/1486/148522/148522_56.pngmyalgia 发表于 2025-3-31 09:55:43
Monogenic and Holomorphic Functionsomparing to traditional methods, deep learning could achieve better performances. Challenges of this work include changes of illumination, foreground objects shadows, dynamic background motion, camera motion, camouflage, or subtle regions. In addition, the postures of the workers are flexible, the wInfiltrate 发表于 2025-3-31 15:51:15
Wiesław Królikowski,R. Michael Portercult task. In this paper, we proposed a Q&A Information Retrieval system for computer textbooks based on the Pattern Matching method, called the PM-IR system, which achieves accurate retrieval of textbook information and intelligent Q&A. Firstly, the Term Frequency-Inverse Document Frequency-Inverse树胶 发表于 2025-3-31 17:39:21
https://doi.org/10.1007/978-1-4612-1368-0wer monitoring system network security. How to understand and evaluate the security of the network has become the focus of the power monitoring system network. In response to this problem, this article proposes a vulnerability assessment method. The purpose is to find out the hidden security risks iIntact 发表于 2025-4-1 00:00:01
Rafał Abłamowicz,Bertfried Fauserprovement such as its results easily affected by the assigned initial values and prone to fall into a local optimum. In this paper, a clustering algorithm based on an improved Antlion optimization algorithm with K-means concepts (IALO-K) is proposed. First, the elite strategy of the Antlion Optimiza