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TSCND:Temporal Subsequence-Based Convolutional Network with Difference for Time Series Forecasting

Computers, Materials & Continua 2024年第3期78卷 3665-3681页

作者： Haoran Huang Weiting Chen Zheming fan MOE Research Center of Software/Hardware Co-Design Engineering East China Normal UniversityShanghai200062China

Time series forecasting plays an important role in various fields, such as energy, finance, transport, and weather. Temporal convolutional networks (TCNs) based on dilated causal convolution have been widely used in time series forecasting. However, two problems weaken the performance of TCNs. One is that in dilated casual convolution, causal convolution leads to the receptive fields of outputs being concentrated in the earlier part of the input sequence, whereas the recent input information will be severely lost. The other is that the distribution shift problem in time series has not been adequately solved. To address the first problem, we propose a subsequence-based dilated convolution method (SDC). By using multiple convolutional filters to convolve elements of neighboring subsequences, the method extracts temporal features from a growing receptive field via a growing subsequence rather than a single element. Ultimately, the receptive field of each output element can cover the whole input sequence. To address the second problem, we propose a difference and compensation method (DCM). The method reduces the discrepancies between and within the input sequences by difference operations and then compensates the outputs for the information lost due to difference operations. Based on SDC and DCM, we further construct a temporal subsequence-based convolutional network with difference (TSCND) for time series forecasting. The experimental results show that TSCND can reduce prediction mean squared error by 7.3% and save runtime, compared with state-of-the-art models and vanilla TCN.

关键词： Difference data prediction time series temporal convolutional network dilated convolution

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Semisymmetric Graphs of Order 2p^(3)with Valency p^(2)

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Algebra Colloquium 2024年第2期31卷 199-208页

作者： Li Wang Songtao Guo Genghua fan School of Mathematics and Information Science Henan Polytechnic University JiaozuoHenan 454000China School of Mathematics and Statistics Henan University of Science and Technology LuoyangHenan 471023China 不详

A simple undirected regular graph is said to be semisymmetric if it is edge-transitive but not *** a semisymmetric graphΓof order 2p^(3),p a prime,it is well known thatΓis bipartite with two biparts having equal *** complete classification of such graphs has been given for the full automorphism group Aut(Γ)acting unfaithfully on at least one bipart ofΓ,which shows that there is only one infinite family of such graphs with valency p^(2).The graphs of this kind have been determined when Aut(Γ)acts faithfully and primitively on at least one bipart ofΓ,and thus there is only one remaining case for classifying such graphs of valency p^(2),Aut(Γ)acting faithfully and imprimitively on both biparts ofΓ,which is dealt with in this *** a result,there is only one infinite family of semisymmetric graphs of order 2p^(3)with valency p^(2).

关键词： semisymmetric graph semitransitive graph bi-coset graph

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Inferring the spin distribution of binary black holes using deep learning

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Chinese Physics C 2024年第10期48卷 275-283页

作者： Li Tang Xi-Long fan School of Math and Physics Mianyang Teachers'CollegeMianyang 621000China School of Physics and Technology Wuhan UniversityWuhan 430072 China

The spin characteristics of black holes offer valuable insights into the evolutionary pathways of their progenitor *** is crucial for understanding the broader population properties of black *** hierarchical Bayesian inference techniques employed to discern these properties often demand substantial time,and consensus regarding the spin distribution of binary black hole(BBH)systems remains *** this study,leveraging observations from GWTC-3,we adopted a machine learning approach to infer the spin distribution of black holes within BBH ***,we developed a deep neural network(DNN)and trained it using data generated from a Beta *** training strategy,involving the segregation of data into 10 bins,not only expedites model training but also enhances the versatility and adaptability of the DNN to accommodate the growing volume of gravitational wave *** Monte Carlo-bootstrap(MC-bootstrap)to generate observation-simulated samples,we derived spin distribution parameters:α=1.3_(-0.18)^(+0.25),β=1.70_(-0.29)^(+0.24)for the larger BH sample and α=1.37_(-0.20)^(+0.31),β=1.63_(-0.20)^(+0.30) for the smaller BH *** our constraints,the distributions of component spin magnitudes suggest the likelihood of both black holes in the BBH merger possessing non-zero spin.

关键词： gravitational wave black hole merges deep learning

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Some Simple Groups Which are Determined by Their Orders and Degree-Patterns

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Algebra Colloquium 2024年第2期31卷 341-346页

作者： Qinghong Guo Weijun Liu Genghua fan School of Mathematics and Statistics HNP-LAMACentral South University Changsha 410083China College of General Education Guangdong University of Science and Technology DongguanGuangdong 523083China 不详

Let G be a finite group and Irr(G)the set of all irreducible complex characters of *** cd(G)be the set of all irreducible complex character degrees of G and denote byρ(G)the set of all primes which divide some character degree of *** character-prime graphΓ(G)associated to G is a simple undirected graph whose vertex set isρ(G)and there is an edge between two distinct primes p and q if and only if the product p q divides some character degree of *** show that the finite nonabelian simple groups A_(7),J_(1),J_(3),J_(4),L_(3)(3)and U_(3)(4)are uniquely determined by their degree-patterns and orders.

关键词： irreducible complex character character-prime graph finite nonabelian simple group

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A Systematic Review and Performance Evaluation of Open-Source Tools for Smart Contract Vulnerability Detection

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Computers, Materials & Continua 2024年第7期80卷 995-1032页

作者： Yaqiong He Jinlin fan Huaiguang Wu School of Computer Science and Technology Zhengzhou University of Light IndustryZhengzhou450001China

With the rise of blockchain technology,the security issues of smart contracts have become increasingly *** the availability of numerous smart contract vulnerability detection tools,many face challenges such as slow updates,usability issues,and limited installation *** challenges hinder the adoption and practicality of these *** paper examines smart contract vulnerability detection tools from 2016 to 2023,sourced from the Web of Science(WOS)and Google *** systematically collecting,screening,and synthesizing relevant research,38 open-source tools that provide installation methods were selected for further *** a developer’s perspective,this paper offers a comprehensive survey of these 38 open-source tools,discussing their operating principles,installation methods,environmental dependencies,update frequencies,and installation *** on this,we propose an Ethereum smart contract vulnerability detection *** framework enables developers to easily utilize various detection tools and accurately analyze contract security *** validate the framework’s stability,over 1700 h of testing were ***,a comprehensive performance test was performed on the mainstream detection tools integrated within the framework,assessing their hardware requirements and vulnerability detection *** results indicate that the Slither tool demonstrates satisfactory performance in terms of system resource consumption and vulnerability detection *** study represents the first performance evaluation of testing tools in this domain,providing significant reference value.

关键词： Blockchain security ethereum smart contracts detection tools evaluation

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Weakly Supervised Network with Scribble-Supervised and Edge-Mask for Road Extraction from High-Resolution Remote Sensing Images

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Computers, Materials & Continua 2024年第4期79卷 549-562页

作者： Supeng Yu Fen Huang Chengcheng fan College of Artificial Intelligence Nanjing Agricultural UniversityNanjing210095China Innovation Academy for Microsatellites of CAS Shanghai201210China Shanghai Engineering Center for Microsatellites Shanghai201210China Key Laboratory of Satellite Digital Technology Shanghai201210China

Significant advancements have been achieved in road surface extraction based on high-resolution remote sensingimage processing. Most current methods rely on fully supervised learning, which necessitates enormous humaneffort to label the image. Within this field, other research endeavors utilize weakly supervised methods. Theseapproaches aim to reduce the expenses associated with annotation by leveraging sparsely annotated data, such asscribbles. This paper presents a novel technique called a weakly supervised network using scribble-supervised andedge-mask (WSSE-net). This network is a three-branch network architecture, whereby each branch is equippedwith a distinct decoder module dedicated to road extraction tasks. One of the branches is dedicated to generatingedge masks using edge detection algorithms and optimizing road edge details. The other two branches supervise themodel’s training by employing scribble labels and spreading scribble information throughout the image. To addressthe historical flaw that created pseudo-labels that are not updated with network training, we use mixup to blendprediction results dynamically and continually update new pseudo-labels to steer network training. Our solutiondemonstrates efficient operation by simultaneously considering both edge-mask aid and dynamic pseudo-labelsupport. The studies are conducted on three separate road datasets, which consist primarily of high-resolutionremote-sensing satellite photos and drone images. The experimental findings suggest that our methodologyperforms better than advanced scribble-supervised approaches and specific traditional fully supervised methods.

关键词： Semantic segmentation road extraction weakly supervised learning scribble supervision remote sensing image

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A Robust Framework for Multimodal Sentiment Analysis with Noisy Labels Generated from Distributed Data Annotation

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 2965-2984页

作者： Kai Jiang Bin Cao Jing fan School of Computer Science and Technology Zhejiang University of TechnologyHangzhou310023China

Multimodal sentiment analysis utilizes multimodal data such as text,facial expressions and voice to detect people’s *** the advent of distributed data collection and annotation,we can easily obtain and share such multimodal ***,due to professional discrepancies among annotators and lax quality control,noisy labels might be *** research suggests that deep neural networks(DNNs)will overfit noisy labels,leading to the poor performance of the *** address this challenging problem,we present a Multimodal Robust Meta Learning framework(MRML)for multimodal sentiment analysis to resist noisy labels and correlate distinct modalities ***,we propose a two-layer fusion net to deeply fuse different modalities and improve the quality of the multimodal data features for label correction and network ***,a multiple meta-learner(label corrector)strategy is proposed to enhance the label correction approach and prevent models from overfitting to noisy *** conducted experiments on three popular multimodal datasets to verify the superiority of ourmethod by comparing it with four baselines.

关键词： Distributed data collection multimodal sentiment analysis meta learning learn with noisy labels

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WEAK-STRONG UNIQUENESS FOR THREE DIMENSIONAL INCOMPRESSIBLE ACTIVE LIQUID CRYSTALS

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Acta Mathematica Scientia 2024年第4期44卷 1415-1440页

作者： fan YANG Congming LI School of Mathematical Sciences CMA-ShanghaiShanghai Jiao Tong UniversityShanghai 200240China

The hydrodynamics of active liquid crystal models has attracted much attention in recent years due to many applications of these *** this paper,we study the weak-strong uniqueness for the Leray-Hopf type weak solutions to the incompressible active liquid crystals in R^(3).Our results yield that if there exists a strong solution,then it is unique among the Leray-Hopf type weak solutions associated with the same initial data.

关键词： analysis of parabolic and elliptic types weak-strong uniqueness active liquid crystals weak solution energy equality

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Grain yield and N uptake of maize in response to increased plant density under reduced water and nitrogen supply conditions

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Journal of Integrative Agriculture 2024年第1期23卷 122-140页

作者： Jingui Wei Qiang Chai Wen Yin Hong fan Yao Guo Falong Hu Zhilong fan QimingWang State Key Laboratory of Aridland Crop Science Lanzhou 730070China College of Agronomy Gansu Agricultural UniversityLanzhou 730070China College of Life Sciences Northwest Normal UniversityLanzhou 730070China

The development of modern agriculture requires the reduction of water and chemical N fertilizer *** the planting density can maintain higher yields,but also consumes more of these restrictive ***,whether an increased maize density can compensate for the negative effects of reduced water and N supply on grain yield and N uptake in the arid irrigated areas remains *** study is part of a long-term positioning trial that started in 2016.A split-split plot field experiment of maize was implemented in the arid irrigated area of northwestern China in 2020 to *** treatments included two irrigation levels:local conventional irrigation reduced by 20%(W1,3,240 m^(3)ha^(-1))and local conventional irrigation(W2,4,050 m^(3)ha^(-1));two N application rates:local conventional N reduced by 25%(N1,270 kg ha^(-1))and local conventional N(360 kg ha^(-1));and three planting densities:local conventional density(D1,75,000 plants ha^(-1)),density increased by 30%(D2,97,500 plants ha-1),and density increased by 60%(D3,120,000 plants ha^(-1)).Our results showed that the grain yield and aboveground N accumulation of maize were lower under the reduced water and N inputs,but increasing the maize density by 30% can compensate for the reductions of grain yield and aboveground N accumulation caused by the reduced water and N *** water was reduced while the N application rate remained unchanged,increasing the planting density by 30% enhanced grain yield by 13.9% and aboveground N accumulation by 15.3%.Under reduced water and N inputs,increasing the maize density by 30% enhanced N uptake efficiency and N partial factor productivity,and it also compensated for the N harvest index and N metabolic related enzyme *** with W2N2D1,the N uptake efficiency and N partial factor productivity increased by 28.6 and 17.6%under W1N1D2.W1N2D2 had 8.4% higher N uptake efficiency and 13.9% higher N partial factor productivity than W2N2D1.W1N2D2 improv

关键词： water and N reduction plant density maize grain yield N uptake compensation effect

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Ternary layered boride MoAlB:A novel thermo-regulation microwave absorbing ceramic material

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Journal of Advanced Ceramics 2024年第5期13卷 699-710页

作者： Zhangjue Wang fan Zhang Nannan Wang Wei Li Yongqiang Chen Hailong Wang Rui Zhang Yanqiu Zhu Bingbing fan School of Material Science and Engineering Zhengzhou UniversityZhengzhou 450001China Henan Academy of Sciences Zhengzhou 450046China State Key Laboratory of Featured Metal Materials and Life Cycle Safety for Composite Structures MOE Key Laboratory of New Processing Technology for Nonferrous Metals MaterialsSchool of ResourcesEnvironment and MaterialsGuangxi UniversityNanning 530004China Department of Materials and Earth Sciences Technical University of DarmstadtDarmstadt 64287Germany School of Material Science and Engineering Luoyang Institute of Science and TechnologyLuoyang 471023China Department of Engineering Faculty of EnvironmentScience and EconomyUniversity of ExeterExeter EX44QFUK

In the context of the fifth-generation(5G)smart era,the demand for electromagnetic wave(EMW)-absorbing materials has become increasingly prominent,so it is necessary to explore promising candidate *** work focuses on the exploration of the material absorbing properties of a MoAlB MAB(MAB represents a promising group of alternatives,where M stands for a transition metal,A typically denotes Al,and B is boron)phase ***,the first-principles calculations were performed to reveal the unique crystal and layered structure of the MoAlB ceramics and to predict their potential for use as an EMW absorption ***,a series of MoAlB ceramics were synthesized at temperatures ranging from 800 to 1300℃,and the influence of temperature on the phase compositions and microstructures of the obtained MoAlB ceramics was characterized and ***,the practical EMW absorption performance of the prepared MoAlB ceramics was evaluated via a combination of experiments and radar cross-sectional *** MoAlB sample synthesized at 900℃ exhibits superior EMW absorption performance,achieving an impressive minimum reflection loss(RL)of−50.33 *** unique layered structure and good electrical conductivity of the MoAlB samples are the main reasons for their enhanced wave absorption performance,which provides interfacial polarization and multiple dielectric loss ***,this study not only contributes to the understanding of the preparation of MoAlB materials but also provides potential guidance for their utilization in the realm of electromagnetic wave absorption.

关键词： MoAlB electronic band structure electromagnetic wave(EMW)absorption layered ternary boride density of states

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