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Divide and Conquer Local Average Regression [article]

Xiangyu Chang, Shaobo Lin, Yao Wang
2016 arXiv   pre-print
The divide and conquer strategy, which breaks a massive data set into a se- ries of manageable data blocks, and then combines the independent results of data blocks to obtain a final decision, has been recognized as a state-of-the-art method to overcome challenges of massive data analysis. In this paper, we merge the divide and conquer strategy with local average regression methods to infer the regressive relationship of input-output pairs from a massive data set. After theoretically analyzing
more » ... he pros and cons, we find that although the divide and conquer local average regression can reach the optimal learning rate, the restric- tion to the number of data blocks is a bit strong, which makes it only feasible for small number of data blocks. We then propose two variants to lessen (or remove) this restriction. Our results show that these variants can achieve the optimal learning rate with much milder restriction (or without such restriction). Extensive experimental studies are carried out to verify our theoretical assertions.
arXiv:1601.06239v2 fatcat:jj37m3ddlzhq5c22ichiij3vym

Spike‐Timing‐Dependent Plasticity in Memristors [chapter]

Yao Shuai, Xinqiang Pan, Xiangyu Sun
2018 Memristor and Memristive Neural Networks  
The spike-timing-dependent plasticity (STDP) characteristic of the memristor plays an important role in the development of neuromorphic network computing in the future. The STDP characteristics were observed in diferent memristors based on diferent kinds of materials. The investigation regarding the inluences of device hysteresis characteristic, the initial conductance of the memristors, and the waveform of the voltage pulses applied to the memristor as preneuron voltage spike and postneuron
more » ... tage spike on the STDP behavior of memristors are reviewed.
doi:10.5772/intechopen.69535 fatcat:cxfl6myo4rb7ha6bd4oupvhzea

Synergy of National Agricultural Innovation Systems

Dan Wang, Xu Du, Jian Sun, Xiangyu Guo, Yao Chen
2018 Sustainability  
Synergy among the various components of national agricultural innovation systems (AISs) promotes agricultural development. This paper investigated the innovation synergy among the various innovation elements of national AISs. First, we developed a synergy analysis model consisting of three innovation variables (innovation allocation, innovation output, and innovation potentiality) and one control variable (government policy supports). Secondly, a broad set of innovation indicators was selected
more » ... o describe the innovation variables and the control variable, and the solutions of the order parameter equation were then calculated to investigate the self-organized synergistic patterns of a panel of the Group of Twenty (G20) countries. The empirical results indicated the following. (1) All of the G20 countries' national AISs had the potential to evolve into more advanced self-organized synergistic states under current government policy support. Furthermore, all of the developing countries were in the active period of synergy, showing stronger synergistic rising powers. However, most of the developed countries were in the stable or general period of synergy, in which synergistic rising powers were relatively weaker; (2) Stronger government policy supports played a positive role in promoting the interaction and collaboration among innovation elements and promoted the national AIS to evolve into a more advanced self-organized synergistic state. This study has important implications for understanding the complex innovation synergy of national AISs, as well as for the design and implementation of agricultural innovation strategies for policy-makers.
doi:10.3390/su10103385 fatcat:t3ljmd6ftrdqpidqzcugbksihy

Ultrasonic-assisted transducer for electrosurgical electrodes

Zhenlong Peng, Deyuan Zhang, Xiangyu Zhang, Guang Yao
2020 Procedia CIRP  
Yao et al.  ... 
doi:10.1016/j.procir.2019.11.004 fatcat:wkz3zelnfvb4ljeoir373tka5i

Using causality and correlation analysis to decipher microbial interactions in activated sludge [article]

Weiwei Cai, Xiangyu Han, Hong Yao
2021 bioRxiv   pre-print
Network theory is widely used to understand microbial interactions in activated sludge and numerous other artificial and natural environments. However, when using correlation-based methods, it is not possible to identify the directionality of interactions within microbiota. Based on the classic Granger test of sequencing-based time-series data, a new Microbial Causal Correlation Network (MCCN) was constructed with distributed ecological interaction on the directed, associated links. As a result
more » ... of applying MCCN to a time series of activated sludge data, we found that the hub species OTU56, classified as belonging the genus Nitrospira, was responsible for completing nitrification in activated sludge, and mainly interacted with Proteobacteria and Bacteroidetes in the form of amensal and commensal relationships, respectively. Phylogenetic tree suggested a mutualistic relationship between Nitrospira and denitrifiers. Zoogloea displayed the highest ncf value within the classified OTUs of the MCCN, indicating that it could be a foundation for activated sludge through forming the characteristic cell aggregate matrices into which other organisms embed during floc formation. Overall, the introduction of causality analysis greatly expands the ability of a network to shed a light on understanding the interactions between members of a microbial community.
doi:10.1101/2021.09.26.461882 fatcat:xsqzwamupnhpnon2qf2m2u4ivi

Critical role of rhythmic poly(A) tail regulation in circadian gene expression [article]

Xiangyu Yao, Shihoko Kojima, Jing Chen
2019 bioRxiv   pre-print
The circadian rhythmicity is deeply rooted in rhythmic regulation of gene expression. The core clock pathway that generates circadian oscillation has been well studied, but it remains unclear how this core rhythm controls rhythmic gene expression. Besides that several core clock components are transcriptional factors and mediate genome-wide rhythmic transcriptional control, mounting evidence has demonstrated the importance of rhythmic posttranscriptional controls. A recent study particularly
more » ... hlighted rhythmic control of poly(A) tail lengths in hundreds of genes in mouse liver and a strong correlation of poly(A) rhythm with protein expression rhythm. In this work we constructed a simplistic model to study the effect of rhythmic poly(A) tail regulation on circadian mRNA expression. The model depicted rhythmic control imposed upon basic mRNA expression processes, including transcription, polyadenylation, deadenylation and degradation. The model results revealed rhythmicity in deadenylation as the strongest contributor to the rhythmicity in poly(A) tail length, and the rhythmicity in abundance of the mRNA subpopulation with long poly(A) tails, which serves a rough proxy for mRNA translatability. In line with this finding, our model further demonstrated that the rhythmic patterns found in the expression of deadenylases could funnel the peak phases of poly(A) tail length and long-tailed mRNA abundance, respectively, into three distinct groups, which could allow genes within each group to coordinate their functions around the clock. Last, our model suggested factors that contribute to the experimentally observed rhythmicity in poly(A) tail length and total mRNA abundance.
doi:10.1101/700443 fatcat:yf2xatx5f5cjzmog5thsud2eua

L 1/2 regularization

ZongBen Xu, Hai Zhang, Yao Wang, XiangYu Chang, Yong Liang
2010 Science China Information Sciences  
In this paper we propose an L 1/2 regularizer which has a nonconvex penalty. The L 1/2 regularizer is shown to have many promising properties such as unbiasedness, sparsity and oracle properties. A reweighed iterative algorithm is proposed so that the solution of the L 1/2 regularizer can be solved through transforming it into the solution of a series of L 1 regularizers. The solution of the L 1/2 regularizer is more sparse than that of the L 1 regularizer, while solving the L 1/2 regularizer
more » ... much simpler than solving the L 0 regularizer. The experiments show that the L 1/2 regularizer is very useful and efficient, and can be taken as a representative of the Lp(0 < p < 1) regularizer.
doi:10.1007/s11432-010-0090-0 fatcat:rm244f5d35crve2dnkmzuvb6fu

Remarkable Daytime Sub-ambient Radiative Cooling in BaSO4 Nanoparticle Films and Paints [article]

Xiangyu Li, Joseph Peoples, Peiyan Yao, Xiulin Ruan
2020 arXiv   pre-print
Radiative cooling is a passive cooling technology that offers great promises to reduce space cooling cost, combat the urban island effect and alleviate the global warming. To achieve passive daytime radiative cooling, current state-of-the-art solutions often utilize complicated multilayer structures or a reflective metal layer, limiting their applications in many fields. Attempts have been made to achieve passive daytime radiative cooling with single-layer paints, but they often require a thick
more » ... coating or show partial daytime cooling. In this work, we experimentally demonstrate remarkable full daytime sub-ambient cooling performance with both BaSO4 nanoparticle films and BaSO4 nanocomposite paints. BaSO4 has a high electron bandgap for low solar absorptance and phonon resonance at 9 um for high sky window emissivity. With an appropriate particle size and a broad particle size distribution, BaSO4 nanoparticle film reaches an ultra-high solar reflectance of 97.6% and high sky window emissivity of 0.96. During field tests, BaSO4 film stays more than 4.5C below ambient temperature or achieves average cooling power of 117 W/m2. BaSO4-acrylic paint is developed with 60% volume concentration to enhance the reliability in outdoor applications, achieving solar reflectance of 98.1% and sky window emissivity of 0.95. Field tests indicate similar cooling performance to the BaSO4 films. Overall, our BaSO4-acrylic paint shows standard figure of merit of 0.77 which is among the highest of radiative cooling solutions, while providing great reliability, the convenient paint form, ease of use and the compatibility with commercial paint fabrication process.
arXiv:2011.01161v1 fatcat:nfhl7bbsfjbplcgli5r27z6pfq

Folded-concave penalization approaches to tensor completion

Wenfei Cao, Yao Wang, Can Yang, Xiangyu Chang, Zhi Han, Zongben Xu
2015 Neurocomputing  
The existing studies involving matrix or tensor completion problems are commonly under the nuclear norm penalization framework due to the computational efficiency of the resulting convex optimization problem. Folded-concave penalization methods have demonstrated surprising developments in sparse learning problems due to their nice practical and theoretical properties. To share the same light of folded-concave penalization methods, we propose a new tensor completion model via folded-concave
more » ... ty for estimating missing values in tensor data. Two typical folded-concave penalties, the minmax concave plus (MCP) penalty and the smoothly clipped absolute deviation (SCAD) penalty, are employed in the new model. To solve the resulting nonconvex optimization problem, we develop a local linear approximation augmented Lagrange multiplier (LLA-ALM) algorithm which combines a two-step LLA strategy to search a local optimum of the proposed model efficiently. Finally, we provide numerical experiments with phase transitions, synthetic data sets, real image and video data sets to exhibit the superiority of the proposed model over the nuclear norm penalization method in terms of the accuracy and robustness. & 2014 Elsevier B.V. All rights reserved. of the matrix X is defined by ‖X‖ F ¼ ðΣ i;j jx i;j j 2 Þ 1=2 . And the nuclear norm is defined by ‖X‖ n ¼ Σ i σ i ðXÞ. We denote the inner product of the matrix space as 〈X; Y〉 ¼ Σ i;j X i;j Y i;j . An N-order tensor to be recovered is defined by X A R I 1 ÂI 2 Â⋯ÂIN , and its elements are denoted by x i 1 ;...;iN , where 1 r i k rI k , 1r k r N; and an observed N-order tensor is defined by T . The "unfold" operation along the k-th mode on a tensor X is defined by unfold k ðX Þ≔X ðkÞ A R I k ÂðI 1 ;...;I k À 1 I k þ 1 ⋯IN Þ , and the opposite operation "fold" is defined by fold k ðX ðkÞ Þ≕X . We also denote ‖X ‖ F ¼ ð∑ i 1 ;...iN jx i 1 ;...;iN j 2 Þ 1=2 as the Frobenius norm of a tensor X . Denote r i as the rank of X ðiÞ . For more details of tensor, see an elegant review [5] . Tensor completion via the global relationship approach assumes that the tensor X is sparse in the sense that each unfolding matrix X ðkÞ is low rank. Mathematically, tensor completion can be formulated as the following optimization problem:
doi:10.1016/j.neucom.2014.10.069 fatcat:3pqnsxbqfvbg5aiw3sbmpjcfjq

Three‐phase transformerless photovoltaic inverter without common mode leakage current

Zhilei Yao, Xiangyu He, Jiwei Gan, Saijun Mao
2022 Engineering Reports  
AUTHOR CONTRIBUTIONS Xiangyu He: Writing -review and editing (equal). Jiwei Gan: Investigation (equal). Saijun Mao: Formal analysis (equal); validation (equal).  ... 
doi:10.1002/eng2.12496 fatcat:wznnuqwl3raxpbxh5pabypgqii

Polyphenylene Oxide/Ca0.7La0.2TiO3 Microwave Composite Substrate

YAO Xiaogang, PENG Haiyi, GU Zhongyuan, HE Fei, ZHAO Xiangyu, LIN Huixing
2021 Journal of Inorganic Materials  
doi:10.15541/jim20210225 fatcat:5mzan5oshnf3lejlb4yovlvuje

Cylin-Painting: Seamless 360 Panoramic Image Outpainting and Beyond with Cylinder-Style Convolutions [article]

Kang Liao, Xiangyu Xu, Chunyu Lin, Wenqi Ren, Yunchao Wei, Yao Zhao
2022 arXiv   pre-print
Image outpainting gains increasing attention since it can generate the complete scene from a partial view, providing a valuable solution to construct 360 panoramic images. As image outpainting suffers from the intrinsic issue of unidirectional completion flow, previous methods convert the original problem into inpainting, which allows a bidirectional flow. However, we find that inpainting has its own limitations and is inferior to outpainting in certain situations. The question of how they may
more » ... e combined for the best of both has as yet remained under-explored. In this paper, we provide a deep analysis of the differences between inpainting and outpainting, which essentially depends on how the source pixels contribute to the unknown regions under different spatial arrangements. Motivated by this analysis, we present a Cylin-Painting framework that involves meaningful collaborations between inpainting and outpainting and efficiently fuses the different arrangements, with a view to leveraging their complementary benefits on a consistent and seamless cylinder. Nevertheless, directly applying the cylinder-style convolution often generates visually unpleasing results as it could discard important positional information. To address this issue, we further present a learnable positional embedding strategy and incorporate the missing component of positional encoding into the cylinder convolution, which significantly improves the panoramic results. Note that while developed for image outpainting, the proposed solution can be effectively extended to other panoramic vision tasks, such as object detection, depth estimation, and image super resolution.
arXiv:2204.08563v1 fatcat:2kjswsttffggdposj54bngfo2y

A super robust and efficient DNA storage architecture based on modulation encoding and decoding [article]

Xiangzhen Zan, Ranze Xie, Xiangyu Yao, Peng Xu, Wenbin Liu
2022 bioRxiv   pre-print
Thanks to its high density and long durability, synthetic DNA has been widely considered as a promising solution to the data explosion problem. However, due to the large amount of random base insertion-deletion-substitution (IDSs) errors from sequencing, reliable data recovery remains a critical challenge, which hinders its large-scale application. Here, we propose a modulation-based DNA storage architecture. Experiments on simulation and real datasets demonstrate that it has two distinct
more » ... ages. First, modulation encoding provides a simple way to ensure the encoded DNA sequences comply with biological sequence constraints (i.e., GC balanced and no homopolymers); Second, modulation decoding is highly efficient and extremely robust for the detection of insertions and deletions, which can correct up to ~40% errors. These two advantages pave the way for future high-throughput and low-cost techniques, and will kickstart the actualization of a viable, large-scale system for DNA data storage.
doi:10.1101/2022.05.25.490755 fatcat:x5wekolffvdn3bnr26srlkllby

Automated Self-Supervised Learning for Graphs [article]

Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang
2022 arXiv   pre-print
Graph self-supervised learning has gained increasing attention due to its capacity to learn expressive node representations. Many pretext tasks, or loss functions have been designed from distinct perspectives. However, we observe that different pretext tasks affect downstream tasks differently cross datasets, which suggests that searching pretext tasks is crucial for graph self-supervised learning. Different from existing works focusing on designing single pretext tasks, this work aims to
more » ... igate how to automatically leverage multiple pretext tasks effectively. Nevertheless, evaluating representations derived from multiple pretext tasks without direct access to ground truth labels makes this problem challenging. To address this obstacle, we make use of a key principle of many real-world graphs, i.e., homophily, or the principle that "like attracts like," as the guidance to effectively search various self-supervised pretext tasks. We provide theoretical understanding and empirical evidence to justify the flexibility of homophily in this search task. Then we propose the AutoSSL framework which can automatically search over combinations of various self-supervised tasks. By evaluating the framework on 7 real-world datasets, our experimental results show that AutoSSL can significantly boost the performance on downstream tasks including node clustering and node classification compared with training under individual tasks. Code is released at https://github.com/ChandlerBang/AutoSSL.
arXiv:2106.05470v3 fatcat:mtjmmb55tfeg7a7lk5hbcv5uwu

Structural Watermarking to Deep Neural Networks via Network Channel Pruning [article]

Xiangyu Zhao, Yinzhe Yao, Hanzhou Wu, Xinpeng Zhang
2021 arXiv   pre-print
In order to protect the intellectual property (IP) of deep neural networks (DNNs), many existing DNN watermarking techniques either embed watermarks directly into the DNN parameters or insert backdoor watermarks by fine-tuning the DNN parameters, which, however, cannot resist against various attack methods that remove watermarks by altering DNN parameters. In this paper, we bypass such attacks by introducing a structural watermarking scheme that utilizes channel pruning to embed the watermark
more » ... to the host DNN architecture instead of crafting the DNN parameters. To be specific, during watermark embedding, we prune the internal channels of the host DNN with the channel pruning rates controlled by the watermark. During watermark extraction, the watermark is retrieved by identifying the channel pruning rates from the architecture of the target DNN model. Due to the superiority of pruning mechanism, the performance of the DNN model on its original task is reserved during watermark embedding. Experimental results have shown that, the proposed work enables the embedded watermark to be reliably recovered and provides a sufficient payload, without sacrificing the usability of the DNN model. It is also demonstrated that the proposed work is robust against common transforms and attacks designed for conventional watermarking approaches.
arXiv:2107.08688v2 fatcat:otl2x6cvifetjleho5zykflxxu
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