Research on the development of carrier intelligent cloud network under the background of IPv6+

With the increasingly mature 5G technology in our country, the government has comprehensively promoted IPv6 scale deployment, the rapid improvement of network quality of the three operators, and gradually transformed to IPv6+, the carrying network is more fl exible, and the user opening service is more convenient, which has promoted the development of intelligent cloud network of China’s carriers. Operators should actively respond to the challenges of IPv6+ era, based on their own intelligent cloud network development needs, the use of SRv6 technology, promote cloud network integration, carrying a variety of online services; Provide integrated cloud network products and services, build an intelligent operation and maintenance system, and improve user satisfaction; To build IPv6 networking capability of the whole network and build intelligent cloud network; Do a good job in the construction of IPv6 network information security, improve the security defense capability of intelligent cloud network, ensure the smooth operation of network, and inject new vitality into the 2B industry market for operators

Vehicle Routing Problem with Time Windows and Simultaneous Delivery and Pick-Up Service Based on MCPSO

This paper considers two additional factors of the widely researched vehicle routing problem with time windows (VRPTW). The two factors, which are very common characteristics in realworld, are uncertain number of vehicles and simultaneous delivery and pick-up service. Using minimization of the total transport costs as the objective of the extension VRPTW, a mathematic model is constructed. To solve the problem, an efficient multiswarm cooperative particle swarm optimization (MCPSO) algorithm is applied. And a new encoding method is proposed for the extension VRPTW. Finally, comparing with genetic algorithm (GA) and particle swarm optimization (PSO) algorithm, the MCPSO algorithm performs best for solving this problem

Tibetan Sentiment Classification Method Based on Semi-Supervised Recursive Autoencoders

We apply the semi-supervised recursive autoencoders (RAE) model for the sentiment classification task of Tibetan short text, and we obtain a better classification effect. The input of the semi-supervised RAE model is the word vector. We crawled a large amount of Tibetan text from the Internet, got Tibetan word vectors by using Word2vec, and verified its validity through simple experiments. The values of parameter α and word vector dimension are important to the model effect. The experiment results indicate that when α is 0.3 and the word vector dimension is 60, the model works best. Our experiment also shows the effectiveness of the semi-supervised RAE model for Tibetan sentiment classification task and suggests the validity of the Tibetan word vectors we trained

Deep Learning on Abnormal Chromosome Segments: An Intelligent Copy Number Variants Detection System Design

Gene testing emerged as a business in the last two decades, and the testing cost has been reduced from 100 million to 1000 dollars for the development of technologies. Preimplantation genetic screening (PGS) is a popular genetic profiling of embryos prior to implantation in gene testing. Copy number variants (CNVs) detection is a key task in PGS which still needs the manual operation and evaluation. At the same time, deep learning technology earns a booming development and wide application in recent years for its strong computing and learning capability. This research redesigns the PGS workflow with the intelligent CNVs detection system, and proposes the corresponding system framework. Deep learning is selected as the proper technology in the system design for CNVs detection, which also fit the task of denoising. The evaluation is conducted on simulation dataset with high accuracy and low time cost, which may achieve the requirements of clinical application and reduce the workload of bioinformatics experts. Moreover, the redesigned process and proposed framework may enlighten the intelligent system design for gene testing in following work, and provide a guidance of deep learning application in AI healthcar

Surface Coating of Cyclotetramethylenetetranitramine (HMX) Particles and Its Property Investigation

To improve the safety of cyclotetramethylenetetranitramine (HMX) particles, the polymer thermoplastic polyurethane elastomer (TPU) and nitrocellulose (NC) were introduced to coat HMX powder by water-solution suspension method and internal solution method, respectively. Scanning electron microscope (SEM) and X-ray photo-electron spectrometry (XPS) were employed to characterize the HMX samples and the role of NC and TPU in the coating processes were discussed. The impact sensitivity, friction sensitivity, and the thermal decomposition of coated HMX particles were investigated, and compared to the unprocessed ones. The results indicate that both TPU and NC can improve the wetting ability of the coating materials on HMX surface and reinforce the connection between HMX and the coating materials. The impact sensitivity and friction sensitivity of HMX samples decrease obviously after they have been surface coated; the drop height (H50) is increased from 35.24 cm to 50.08 cm, and the friction probability is reduced from 93.2 % to 58.3%. The activation energy (Ea) and the self-ignition temperature increase by 10.46 KJ·mol-1 and 1.8, respectively

Spin-orbit coupling mediated photon-like resonance for a single atom trapped in a symmetric double well

We employ a method involving coherent periodic modulation of Raman laser intensity to induce resonance transitions between energy levels of a spin-orbit coupled atom in a symmetric double-well trap. By integrating photon-assisted tunneling (PAT) technique with spin-orbit coupling (SOC), we achieve resonance transitions between the predefined energy levels of the atom, thereby enabling further precise control of the atom's dynamics. We observe that such photon-like resonance can induce a transition from a localized state to atomic Rabi oscillation between two wells, or effectively reduce tunneling as manifested by a quantum beating phenomenon. Moreover, such resonance transitions have the potential to induce spin flipping in a spin-orbit coupled atom. Additionally, the SOC-mediated transition from multiphoton resonance to fundamental resonance and the SOC-induced resonance suppression are also discovered. In these cases, the analytical results of the effective coupling coefficients of the resonance transition derived from a four-level model can account for the entire dynamics, demonstrating surprisingly good agreement with the numerically exact results based on the realistic continuous model.Comment: 13 pages, 13 figure