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UniMoCo: Unsupervised, Semi-Supervised and Full-Supervised Visual Representation Learning [article]

Zhigang Dai, Bolun Cai, Yugeng Lin, Junying Chen
2021 arXiv   pre-print
Momentum Contrast (MoCo) achieves great success for unsupervised visual representation. However, there are a lot of supervised and semi-supervised datasets, which are already labeled. To fully utilize the label annotations, we propose Unified Momentum Contrast (UniMoCo), which extends MoCo to support arbitrary ratios of labeled data and unlabeled data training. Compared with MoCo, UniMoCo has two modifications as follows: (1) Different from a single positive pair in MoCo, we maintain multiple
more » ... sitive pairs on-the-fly by comparing the query label to a label queue. (2) We propose a Unified Contrastive(UniCon) loss to support an arbitrary number of positives and negatives in a unified pair-wise optimization perspective. Our UniCon is more reasonable and powerful than the supervised contrastive loss in theory and practice. In our experiments, we pre-train multiple UniMoCo models with different ratios of ImageNet labels and evaluate the performance on various downstream tasks. Experiment results show that UniMoCo generalizes well for unsupervised, semi-supervised and supervised visual representation learning.
arXiv:2103.10773v1 fatcat:r6jrpp7zp5hljkuaubfedkbnva

Fast LLMMSE filter for low-dose CT imaging [article]

Fengling Wang, Bowen Lin, Shujun Fu, Shiling Xie, Zhigang Zhao, Yuliang Li
2019 arXiv   pre-print
Low-dose X-ray CT technology is one of important directions of current research and development of medical imaging equipment. A fast algorithm of blockwise sinogram filtering is presented for realtime low-dose CT imaging. A nonstationary Gaussian noise model of low-dose sinogram data is proposed in the low-mA (tube current) CT protocol. Then, according to the linear minimum mean square error principle, an adaptive blockwise algorithm is built to filter contaminated sinogram data caused by
more » ... starvation. A moving sum technique is used to speed the algorithm into a linear time one, regardless of the block size and thedata range. The proposedfast filtering givesa better performance in noise reduction and detail preservation in the reconstructed images,which is verified in experiments on simulated and real data compared with some related filtering methods.
arXiv:1903.09745v1 fatcat:jufiulbswzderbyhiarpmhpe74

Surrogate-assisted cooperative signal optimization for large-scale traffic networks [article]

Yongsheng Liang, Zhigang Ren, Lin Wang, Hanqing Liu, Wenhao Du
2021 arXiv   pre-print
Reasonable setting of traffic signals can be very helpful in alleviating congestion in urban traffic networks. Meta-heuristic optimization algorithms have proved themselves to be able to find high-quality signal timing plans. However, they generally suffer from performance deterioration when solving large-scale traffic signal optimization problems due to the huge search space and limited computational budget. Directing against this issue, this study proposes a surrogate-assisted cooperative
more » ... al optimization (SCSO) method. Different from existing methods that directly deal with the entire traffic network, SCSO first decomposes it into a set of tractable sub-networks, and then achieves signal setting by cooperatively optimizing these sub-networks with a surrogate-assisted optimizer. The decomposition operation significantly narrows the search space of the whole traffic network, and the surrogate-assisted optimizer greatly lowers the computational burden by reducing the number of expensive traffic simulations. By taking Newman fast algorithm, radial basis function and a modified estimation of distribution algorithm as decomposer, surrogate model and optimizer, respectively, this study develops a concrete SCSO algorithm. To evaluate its effectiveness and efficiency, a large-scale traffic network involving crossroads and T-junctions is generated based on a real traffic network. Comparison with several existing meta-heuristic algorithms specially designed for traffic signal optimization demonstrates the superiority of SCSO in reducing the average delay time of vehicles.
arXiv:2103.02107v1 fatcat:5otzjlzdcbdkle4mjdy5f3vzty

Electron-phonon coupling induced intrinsic Floquet electronic structure

Zhigang Song, Lin-Wang Wang
2020 npj Quantum Materials  
Floquet states are a topic of intense contemporary interest, which is often induced by coherent external oscillating perturbation (e.g., laser, or microwave) which breaks the continuous time translational symmetry of the systems. Usually, electron–phonon coupling modifies the electronic structure of a crystal as a non-coherent perturbation and seems difficult to form Floquet states. Surprisingly, we found that the thermal equilibrium electron–phonon coupling in M(MoS)3 and M(MoSe)3 (where M is
more » ... metallic element) exhibits a coherent behavior, and the electronic structure can be described by the Floquet theorem. Such a coherent Floquet state is caused by a selective giant electron–phonon coupling, with thermodynamic phonon oscillation serving as a driving force on the electronic part of the system. The quasi-1D Dirac cone at the Fermi energy has its band gap open and close regularly. Similarly, the electric current will oscillate even under a constant voltage.
doi:10.1038/s41535-020-00284-4 fatcat:rpvzroc7jneh7mbhi5zgdi6bs4

Salidroside downregulates microRNA‑133a and inhibits endothelial cell apoptosis induced by oxidized low‑density lipoprotein

Yongjie Zhang, Fei Lin, Zhigang Yan, Zhigang Chen, Yingen Chen, Yilin Zhao, Guoan Zhao
2020 International Journal of Molecular Medicine  
Vascular endothelial cell apoptosis is regulated by microRNA‑133a (miR‑133a), which participates in the formation of atherosclerotic (AS) plaques, leading to the development of several cardiovascular diseases. Salidroside (SAL), the main component of Rhodiola, is considered to exert anti‑AS effect; however, its mode of action remains unclear. Thus, the present study aimed to determine whether SAL inhibits endothelial cell apoptosis through the miR‑133a pathway. Cultured human coronary artery
more » ... othelial cells (HCAECs) were exposed to oxidized low‑density lipoprotein (ox‑LDL). Cell viability and cytotoxicity were monitored by MTT assay. In parallel, the mRNA expression levels of miR‑133a and Bcl‑xL, and the protein levels of anti‑apoptotic Bcl‑xL and activated caspase‑3 were measured. The apoptotic levels were examined by flow cytometry. Furthermore, the effects of silencing and overexpressing miR‑133a on the parameters mentioned above were evaluated. Exposure to ox‑LDL induced an increase in the expression of miR‑133a, with a concomitant decrease in the level of Bcl‑xL in the HCAECs; these effects were reversed by treatment with SAL. Importantly, the effects of SAL were impaired upon the silencing of miR‑133a, whereas the overexpression of miR‑133a partly restored the effects of SAL. On the whole, the findings of the present study demonstrate that SAL inhibits the ox‑LDL‑induced upregulation of miR‑133a expression, while promoting the expression of Bcl‑xL, thereby preventing endothelial cell apoptosis.
doi:10.3892/ijmm.2020.4691 pmid:32945356 pmcid:PMC7447316 fatcat:ed7iryjohbegtjz65hggdxvabq

A Gradient-based Kernel Optimization Approach for Parabolic Distributed Parameter Control Systems [article]

Zhigang Ren, Chao Xu, Qun Lin, Ryan Loxton
2016 arXiv   pre-print
This paper proposes a new gradient-based optimization approach for designing optimal feedback kernels for parabolic distributed parameter systems with boundary control. Unlike traditional kernel optimization methods for parabolic systems, our new method does not require solving non-standard Riccati-type or Klein-Gorden-type partial differential equations (PDEs). Instead, the feedback kernel is parameterized as a second-order polynomial whose coefficients are decision variables to be tuned via
more » ... adient-based dynamic optimization, where the gradient of the system cost functional (which penalizes both kernel and output magnitude) is computed by solving a so-called costate PDE instandard form. Special constraints are imposed on the kernel coefficients to ensure that, under mild conditions, the optimized kernel yields closed-loop stability. Numerical simulations demonstrate the effectiveness of the proposed approach.
arXiv:1603.04562v1 fatcat:e4uwce5dcvanxaykgtvumgm6y4

Spectrum Allocation Based on an Improved Gravitational Search Algorithm

Liping Liu, Ning Wang, Zhigang Chen, Lin Guo
2018 Algorithms  
In cognitive radio networks (CRNs), improving system utility and ensuring system fairness are two important issues. In this paper, we propose a spectrum allocation model to construct CRNs based on graph coloring theory, which contains three classes of matrices: available matrix, utility matrix, and interference matrix. Based on the model, we formulate a system objective function by jointly considering two features: system utility and system fairness. Based on the proposed model and the
more » ... problem, we develop an improved gravitational search algorithm (IGSA) from two aspects: first, we introduce the pattern search algorithm (PSA) to improve the global optimization ability of the original gravitational search algorithm (GSA); second, we design the Chebyshev chaotic sequences to enhance the convergence speed and precision of the algorithm. Simulation results demonstrate that the proposed algorithm achieves better performance than traditional methods in spectrum allocation. Introduction With the massive growth of wireless devices, the conventional method of resource allocation aggravates the spectrum-scarcity situation, which significantly degrades the utilization of spectrum. However, the spatial and temporal variations in the licensed spectrum utilization range from 15% to 85%, according to a report by Federal Communications Commission [1] . In this condition, cognitive radio (CR) techniques are studied and developed [2] . CR is a promising technology for improving the traditional spectrum allocation methods, which enables access to the underutilized licensed spectrum to mitigate the spectrum-scarcity problem in the unlicensed band. Furthermore, cognitive radio networks (CRNs) [3] are vital wireless communication systems to utilize the spectrum resource efficiently. In these networks, the cognitive users, namely secondary users (SUs) can use licensed spectrum without interfering with the licensed users or primary users (PUs) [4] . Based on this feature, CRNs implement four main objectives of dynamic spectrum management [5]: spectrum sensing, spectrum assignment, spectrum mobility, and spectrum sharing. Spectrum sensing [6] is mainly to achieve the detection and analysis of the spectrum hole characteristics which are time distribution, required bandwidth, noise, transmission power, and so on. Spectrum assignment [7] refers to the selection of suitable operating bands for data transmission according to the requirements of the quality of service (QoS) and determines the carrier frequency, communication system, communication parameters, and emission level. Spectrum mobility means that once the PU is found to return to this channel, the SU who using the band would move immediately and establish a new communication connection for data transmission. The purpose of spectrum sharing is to solve the problem of how to choose the spectrum between multiple SUs and ensure the maximization of spectrum utilization. Spectrum assignment is a key issue for maximizing the spectrum utilization. The scholars have done a lot of work in spectrum allocation.
doi:10.3390/a11030027 fatcat:e5ylfy2hffdujnwx76iz5m2ep4

Prediction of Suitable Harvest Time in Aquaculture

Zhaotang Shang, Lin Cheng, Mengsen Luo, Lang He, Zhigang Lu
2013 Natural Resources  
A model is provided to predict the prawn's harvest in aquaculture through analytical research in agrometeorology, mathematical statistics, synoptic meteorology and et al. It is found out that the Benefit Analysis of the Best Harvest is one of the most ideal ways. The models for the breeding objects, climate prediction and analysis of market quotation should be set up and perfected continuously. Only when the dynamic numerical simulation of the growth is accurate and the short-term weather
more » ... st and the market quotation are reliable, will the suitable harvest time be predicted precisely. We used to write this paper with the foundation on ideologies.
doi:10.4236/nr.2013.42024 fatcat:rtxygssydzdjpetqnpkkgzkqzm

Low-Temperature Synthesis of Superconducting NanocrystallineMgB2

Jun Lu, Zhili Xiao, Qiyin Lin, Helmut Claus, Zhigang Zak Fang
2010 Journal of Nanomaterials  
Magnesium diboride (MgB2) is considered a promising material for practical application in superconducting devices, with a transition temperature near 40 K. In the present paper, nanocrystalline MgB2with an average particle size of approximately 70 nm is synthesized by reacting LiBH4with MgH2at temperatures as low as 450°C. This synthesis approach successfully bypasses the usage of either elemental boron or toxic diborane gas. The superconductivity of the nanostructures is confirmed by
more » ... ion measurements, showing a superconducting critical temperature of 38.7 K.
doi:10.1155/2010/191058 fatcat:npc5cwcjm5a6fjq3etqi7ax2oa

Condition based maintenance optimization considering multiple objectives

Zhigang Tian, Daming Lin, Bairong Wu
2009 Journal of Intelligent Manufacturing  
Lin et al. (2006) proposed the application of a principal components proportional hazards regression model in condition based maintenance (CBM) optimization.  ... 
doi:10.1007/s10845-009-0358-7 fatcat:kcjzxvjvxzabvaizhlsbx5oela

The Yangtze finless porpoise: On an accelerating path to extinction?

Zhigang Mei, Xinqiao Zhang, Shiang-Lin Huang, Xiujiang Zhao, Yujiang Hao, Lin Zhang, Zhengyi Qian, Jinsong Zheng, Kexiong Wang, Ding Wang
2014 Biological Conservation  
For the conservation of endangered animals to be effective, information on population distribution and abundance requires regular updating from census efforts. The Yangtze finless porpoise (Neophocaena asiaeorientalis asiaeorientalis) has recently been reclassified as critically endangered (CR) due to a rapid decline in abundance. Baseline measures currently used for identifying extinction risk and implementing conservation actions may lag behind the actual demographic trend of a population
more » ... thus, should be updated frequently. In this study, we report the results of a line transect survey of porpoises conducted in the middle and lower reaches of the Yangtze River in 2012. Five hundred and five porpoises (95% CI = 348 to À662, CV = 15.86%) remain in the main stem of the Yangtze River, mostly concentrated between Ezhou and Zhenjiang. Our results reveal that the decline in the Yangtze finless porpoise population is more rapid than previously estimated. The porpoise distribution has become more restricted and fragmented with two new gaps in their distribution. We show that the extinction risk for the Yangtze finless porpoise population has increased substantially and, hence, the expected time to extinction has moved closer. Current conservation methods are insufficient and ineffective, and need to be revised. More active conservation actions, such as enforcing year-long fishing bans in the in situ reserves and building more ex situ reserves, should be implemented urgently.
doi:10.1016/j.biocon.2014.02.033 fatcat:bxcdeeajifhw3d34zjkgyjbkwa

A pharmaceutical hydrogen-bonded covalent organic polymer for enrichment of volatile iodine

Lin Lin, Heda Guan, Donglei Zou, Zhaojun Dong, Zhi Liu, Feifan Xu, Zhigang Xie, Yangxue Li
2017 RSC Advances  
A pharmaceutical hydrogen-bonded covalent organic polymer (pha-HCOP-1) is constructed with the formation of two types of bonds using the pharmaceutical isoniazid as a bifunctional linker. The as-synthesised pha-HCOP-1 exhibits good adsorption ability for iodine molecules.
doi:10.1039/c7ra09414k fatcat:tpc33cn5cvhzngfzpqy7a3626u

Lattice-Based 3-Dimensional Wireless Sensor Deployment

Zhigang Wang, Liqin Tian, Lianhai Lin, Yinghua Tong, Xavier Vilanova
2021 Journal of Sensors  
With the wide application of wireless sensor networks (WSNs) in real space, there are numerous studies on 3D sensor deployments. In this paper, the k -connectivity theoretical model of fixed and random nodes in regular lattice-based deployment was proposed to study the coverage and connectivity of sensor networks with regular lattice in 3D space. The full connectivity range and cost of the deployment with sensor nodes fixed in the centers of four regular lattices were quantitatively analyzed.
more » ... e optimal single lattice coverage model and the ratio of the communication range to the sensing range r c / r s were investigated when the deployment of random nodes satisfied the k -connectivity requirements for full coverage. In addition, based on the actual sensing model, the coverage, communication link quality, and reliability of different lattice-based deployment models were determined in this study.
doi:10.1155/2021/2441122 fatcat:ykf2iugg2fezzd4r2zvjtnmmqy

Learning Dynamic Context Augmentation for Global Entity Linking [article]

Xiyuan Yang, Xiaotao Gu, Sheng Lin, Siliang Tang, Yueting Zhuang, Fei Wu, Zhigang Chen, Guoping Hu, Xiang Ren
2019 arXiv   pre-print
Despite of the recent success of collective entity linking (EL) methods, these "global" inference methods may yield sub-optimal results when the "all-mention coherence" assumption breaks, and often suffer from high computational cost at the inference stage, due to the complex search space. In this paper, we propose a simple yet effective solution, called Dynamic Context Augmentation (DCA), for collective EL, which requires only one pass through the mentions in a document. DCA sequentially
more » ... lates context information to make efficient, collective inference, and can cope with different local EL models as a plug-and-enhance module. We explore both supervised and reinforcement learning strategies for learning the DCA model. Extensive experiments show the effectiveness of our model with different learning settings, base models, decision orders and attention mechanisms.
arXiv:1909.02117v1 fatcat:3ijbckrazjfwnkfvetytgg5nqu

A Novel Spectrum Scheduling Scheme with Ant Colony Optimization Algorithm

Liping Liu, Ning Wang, Zhigang Chen, Lin Guo
2018 Algorithms  
Cognitive radio is a promising technology for improving spectrum utilization, which allows cognitive users access to the licensed spectrum while primary users are absent. In this paper, we design a resource allocation framework based on graph theory for spectrum assignment in cognitive radio networks. The framework takes into account the constraints that interference for primary users and possible collision among cognitive users. Based on the proposed model, we formulate a system utility
more » ... n to maximize the system benefit. Based on the proposed model and objective problem, we design an improved ant colony optimization algorithm (IACO) from two aspects: first, we introduce differential evolution (DE) process to accelerate convergence speed by monitoring mechanism; then we design a variable neighborhood search (VNS) process to avoid the algorithm falling into the local optimal. Simulation results demonstrate that the improved algorithm achieves better performance.
doi:10.3390/a11020016 fatcat:l3a5ivbrd5befowheamfrouyuy
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