New degradation feature extraction method of planetary gearbox based on alpha stable distribution

Wenxin Qiao,Xianglong Ni,Lei Wang,Xin Lv,Liwei Chen,Fucheng Sun 대한기계학회 2021 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.35 No.1

The planetary transmission system has been widely used in industry because of its various advantages. And the study on degradation feature extraction method of planetary gearbox is of major significance for mechanical system prognostics and health management (PHM). In this paper, the alpha stable distribution characteristics of planetary gearbox vibration signals in performance degradation process are verified. By observing the change of alpha stable distribution for planetary gearbox degradation experiment data, a new degradation feature extraction method based on alpha stable distribution is proposed, which is called the height of probability distribution (HPD). Through comparative analysis, it is determined that HPD has better linearity and less fluctuation compared with conventional degradation features in planetary gearbox accelerated degradation stage. Moreover, in the accelerated degradation stage, the degradation trend prediction result based on HPD is closer to the actual data than conventional degradation features no matter using Wiener-based or LSSVM-based prediction method. These conclusions indicate that the newly proposed HPD works well and gives accurate estimates for condition monitoring and degradation trend prediction of planetary gearbox.

Reliability‐aware service chaining mapping in NFV‐enabled networks

Yicen Liu,Yu Lu,Wenxin Qiao,Xingkai Chen 한국전자통신연구원 2019 ETRI Journal Vol.41 No.2

Network function virtualization can significantly improve the flexibility and effectiveness of network appliances via a mapping process called service function chaining. However, the failure of any single virtualized network function causes the breakdown of the entire chain, which results in resource wastage, delays, and significant data loss. Redundancy can be used to protect network appliances; however, when failures occur, it may significantly degrade network efficiency. In addition, it is difficult to efficiently map the primary and backups to optimize the management cost and service reliability without violating the capacity, delay, and reliability constraints, which is referred to as the reliability‐aware service chaining mapping problem. In this paper, a mixed integer linear programming formulation is provided to address this problem along with a novel online algorithm that adopts the joint protection redundancy model and novel backup selection scheme. The results show that the proposed algorithm can significantly improve the request acceptance ratio and reduce the consumption of physical resources compared to existing backup algorithms.

Smart Anti-jamming Mobile Communication for Cloud and Edge-Aided UAV Network

( Zhiwei Li ),( Yu Lu ),( Zengguang Wang ),( Wenxin Qiao ),( Donghao Zhao ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.12

The Unmanned Aerial Vehicles (UAV) networks consisting of low-cost UAVs are very vulnerable to smart jammers that can choose their jamming policies based on the ongoing communication policies accordingly. In this article, we propose a novel cloud and edge-aided mobile communication scheme for low-cost UAV network against smart jamming. The challenge of this problem is to design a communication scheme that not only meets the requirements of defending against smart jamming attack, but also can be deployed on low-cost UAV platforms. In addition, related studies neglect the problem of decision-making algorithm failure caused by intermittent ground-to-air communication. In this scheme, we use the policy network deployed on the cloud and edge servers to generate an emergency policy tables, and regularly update the generated policy table to the UAVs to solve the decision-making problem when communications are interrupted. In the operation of this communication scheme, UAVs need to offload massive computing tasks to the cloud or the edge servers. In order to prevent these computing tasks from being offloaded to a single computing resource, we deployed a lightweight game algorithm to ensure that the three types of computing resources, namely local, edge and cloud, can maximize their effectiveness. The simulation results show that our communication scheme has only a small decrease in the SINR of UAVs network in the case of momentary communication interruption, and the SINR performance of our algorithm is higher than that of the original Q-learning algorithm.

A Dynamic Placement Mechanism of Service Function Chaining Based on Software-defined Networking

( Yicen Liu ),( Yu Lu ),( Xingkai Chen ),( Xi Li ),( Wenxin Qiao ),( Liyun Chen ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.10

To cope with the explosive growth of Internet services, Service Function Chaining (SFC) based on Software-defined Networking (SDN) is an emerging and promising technology that has been suggested to meet this challenge. Determining the placement of Virtual Network Functions (VNFs) and routing paths that optimize the network utilization and resource consumption is a challenging problem, particularly without violating service level agreements (SLAs). This problem is called the optimal SFC placement problem and an Integer Linear Programming (ILP) formulation is provided. A greedy heuristic solution is also provided based on an improved two-step mapping algorithm. The obtained experimental results show that the proposed algorithm can automatically place VNFs at the optimal locations and find the optimal routing paths for each online request. This algorithm can increase the average request acceptance rate by about 17.6% and provide more than 20-fold reduction of the computational complexity compared to the Greedy algorithm. The feasibility of this approach is demonstrated via NetFPGA-10G prototype implementation.

Ketohexokinase-dependent metabolism of cerebral endogenous fructose in microglia drives diabetes-associated cognitive dysfunction

Li Yansong,Jiang Tao,Du Mengyu,He Shuxuan,Ning Huang,Cheng Bo,Yan Chaoying,Tang Wenxin,Gao Wei,Guo Hongyan,Li Qiao,Wang Qiang 생화학분자생물학회 2023 Experimental and molecular medicine Vol.55 No.-

Dementia, as an advanced diabetes-associated cognitive dysfunction (DACD), has become the second leading cause of death among diabetes patients. Given that little guidance is currently available to address the DACD process, it is imperative to understand the underlying mechanisms and screen out specific therapeutic targets. The excessive endogenous fructose produced under high glucose conditions can lead to metabolic syndrome and peripheral organ damage. Although generated by the brain, the role of endogenous fructose in the exacerbation of cognitive dysfunction is still unclear. Here, we performed a comprehensive study on leptin receptor-deficient T2DM mice and their littermate m/m mice and revealed that 24-week-old db/db mice had cognitive dysfunction and excessive endogenous fructose metabolism in the hippocampus by multiomics analysis and further experimental validation. We found that the rate-limiting enzyme of fructose metabolism, ketohexokinase, is primarily localized in microglia. It is upregulated in the hippocampus of db/db mice, which enhances mitochondrial damage and reactive oxygen species production by promoting nicotinamide adenine dinucleotide phosphate oxidase 4 (NOX4) expression and mitochondrial translocation. Inhibiting fructose metabolism via ketohexokinase depletion reduces microglial activation, leading to the restoration of mitochondrial homeostasis, recovery of structural synaptic plasticity, improvement of CA1 pyramidal neuron electrophysiology and alleviation of cognitive dysfunction. Our findings demonstrated that enhanced endogenous fructose metabolism in microglia plays a dominant role in diabetes-associated cognitive dysfunction and could become a potential target for DACD.