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User Clustering Scheme for Downlink of NOMA System
( Li Li ),( Zhenghui Feng ),( Yanzhi Tang ),( Zhangjie Peng ),( Lisen Wang ),( Weilu Shao ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.3
An improved clustering scheme based on user group is proposed. Every two users are grouped among N-users in the allowed system according to their link gain from large to small. Each user group is numbered sequentially. Two user clusters are obtained according to the principle of maximizing link gain difference for the users in the first and last user groups. The remaining user groups are added to the two existing user clusters according to the parity of the group number. The clustering should be clustered again among the users in either user cluster if the throughput summation of a user cluster in NOMA is less than that of these users in orthogonal multiple access. The simulation results show that the proposed clustering scheme can increase the system throughput by about 8% compared with the hybrid clustering scheme when the number of users requiring service is 12.
Li Zhang,Dong Li,Min Lu,Zechi Wu,Chaotian Liu,Yingying Shi,Mengyu Zhang,Zhangjie Nan,Weixiang Wang 한국식물병리학회 2023 Plant Pathology Journal Vol.39 No.4
In plant-pathogen interactions, Magnaporthe oryzae causes blast disease on more than 50 species of 14 monocot plants, including important crops such as rice, millet, and most 15 recently wheat. M. oryzae is a model fungus for studying plant-microbe interaction, and the main source for fungal pathogenesis in the field. Here we report that MoJMJD6 is required for conidium germination and appressorium formation in M. oryzae. We obtained MoJMJD6 mutants (ΔMojmjd6) using a target gene replacement strategy. The MoJMD6 deletion mutants were delayed for conidium germination, glycogen, and lipid droplets utilization and consequently had decreased virulence. In the ΔMojmjd6 null mutants, global histone methyltransferase modifications (H3K- 4me3, H3K9me3, H3K27me3, and H3K36me2/3) of the genome were unaffected. Taken together, our results indicated that MoJMJD6 function as a nuclear protein which plays an important role in conidium germination and appressorium formation in the M. oryzae. Our work provides insights into MoJMJD6-mediated regulation in the early stage of pathogenesis in plant fungi.
Meshing analysis and optimization for plane-generated enveloping toroid hourglass worm drive
Zhi Liu,Hong Lu,Qingmeng Wang,Zhangjie Li,Qianju Cheng 대한기계학회 2021 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.35 No.7
Optimal design parameter combination and transmission optimization for planegenerated enveloping toroid hourglass worm drive are proposed. The modeling frame and mathematical model of the worm were constructed first to provide a perfect transmission. Then, the mathematical representations of transmission performance, including lubrication angle, induced normal curvature, and length of meshing line for worm drive, were derived according to differential geometry and coordinate transformation approach. In addition, the influence of various design parameters on transmission performance was associated with main parameters, and the influence of the main parameters on transmission was evaluated. Next, a multivariate transmission optimization considering lubrication effect, bearing capacity and contact strength was conducted in view of the whole meshing cycle. The optimal global solution of the multivariate optimization model was also evaluated using a genetic algorithm. Calculation and experimental results indicated the optimization study was in good agreement with experimental results. Finally, the comprehensive transmission performance of the worm drive has an increase of 9.2 %.
De-cloaking Malicious Activities in Smartphones Using HTTP Flow Mining
( Xin Su ),( Xuchong Liu ),( Jiuchuang Lin ),( Shiming He ),( Zhangjie Fu ),( Wenjia Li ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.6
Android malware steals users` private information, and embedded unsafe advertisement (ad) libraries, which execute unsafe code causing damage to users. The majority of such traffic is HTTP and is mixed with other normal traffic, which makes the detection of malware and unsafe ad libraries a challenging problem. To address this problem, this work describes a novel HTTP traffic flow mining approach to detect and categorize Android malware and unsafe ad library. This work designed AndroCollector, which can automatically execute the Android application (app) and collect the network traffic traces. From these traces, this work extracts HTTP traffic features along three important dimensions: quantitative, timing, and semantic and use these features for characterizing malware and unsafe ad libraries. Based on these HTTP traffic features, this work describes a supervised classification scheme for detecting malware and unsafe ad libraries. In addition, to help network operators, this work describes a fine-grained categorization method by generating fingerprints from HTTP request methods for each malware family and unsafe ad libraries. This work evaluated the scheme using HTTP traffic traces collected from 10778 Android apps. The experimental results show that the scheme can detect malware with 97% accuracy and unsafe ad libraries with 95% accuracy when tested on the popular third-party Android markets.