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Real-time instance segmentation based on contour learning

Journal of Measurement Science and Instrumentation 2024年第3期15卷 328-337页

作者： GE Rui LIU Dengfeng zhou Haojie CHAI zhilei WU Qin School of Artificial Intelligence and Computer Science Jiangnan UniversityWuxi 214122China Jiangsu Provincial Engineering Laboratory Pattern Recognition and Computational Intelligence Jiangnan UniversityWuxi 214122China

Instance segmentation plays an important role in image *** Deep Snake algorithm based on contour iteration deforms an initial bounding box to an instance contour end-to-end,which can improve the performance of instance segmentation,but has defects such as slow segmentation speed and sub-optimal initial *** solve these problems,a real-time instance segmentation algorithm based on contour learning was ***,ShuffleNet V2 was used as backbone network,and the receptive field of the model was expanded by using a 5×5 convolution ***,a lightweight up-sampling module,multi-stage aggregation(MSA),performs residual fusion of multi-layer features,which not only improves segmentation speed,but also extracts effective features more ***,a contour initialization method for network learning was designed,and a global contour feature aggregation mechanism was used to return a coarse contour,which solves the problem of excessive error between manually initialized contour and real ***,the Snake deformation module was used to iteratively optimize the coarse contour to obtain the final instance *** experimental results showed that the proposed method improved the instance segmentation accuracy on semantic boundaries dataset(SBD),Cityscapes and Kins datasets,and the average precision reached 55.8 on the SBD;Compared with Deep Snake,the model parameters were reduced by 87.2%,calculation amount was reduced by 78.3%,and segmentation speed reached 39.8 frame·s−1 when instance segmentation was performed on an image with a size of 512×512 pixels on a 2080Ti *** proposed method can reduce resource consumption,realize instance segmentation tasks quickly and accurately,and therefore is more suitable for embedded platforms with limited resources.

关键词： instance segmentation ShuffleNet V2 lightweight network contour initialization

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Consecutive narrow and broad quasi-periodic fast-propagating wave trains associated with a flare

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Science China(Physics,Mechanics & Astronomy) 2024年第5期67卷 200-211页

作者： Xinping zhou Yuandeng Shen Chengrui zhou Zehao Tang Ahmed Ahmed Ibrahim College of Physics and Electronic Engineering Sichuan Normal UniversityChengdu 610068China State Key Laboratory of Space Weather Chinese Academy of SciencesBeijing 100190China Yunnan Observatories Chinese Academy of SciencesKunming 650216China Department of Physics and Astronomy College of ScienceKing Saud UniversityP.O.Box 2455Riyadh 11451Saudi Arabia

The excitation mechanism of coronal quasi-period fast-propagating(QFP)wave trains remains *** Atmospheric Imaging Assembly onboard the Solar Dynamics Observatory observations,we study a narrow and a broad QFP wave trains excited one after another during the successive eruptions of filaments hosted within a fan-spine magnetic system on October 20,*** consecutive occurrence of these two types of QFP wave trains in the same event provides an excellent opportunity to explore their excitation mechanisms and compare their physical *** observational results reveal that narrow and broad QFP wave trains exhibit distinct speeds,periods,energy fluxes,and relative intensity amplitudes,although originating from the same active region and being associated with the same GOES C2.9 *** wavelet analysis,we find that the narrow QFP wave train shares a similar period with the flare itself,suggesting its possible excitation through the pulsed energy release in the magnetic reconnection process that generated the accompanying *** the other hand,the broad QFP wave train appears to be associated with the energy pulses released by the successive expansion and unwinding of filament ***,it is plausible that the broad QFP wave train was also excited by the sequential stretching of closed magnetic field lines driven by the erupting *** findings shed light on the different excitation mechanisms and origins of the QFP wave trains.

关键词： narrow wave excitation

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Efficient Penetration Testing Path Planning Based on Reinforcement Learning with Episodic Memory

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2613-2634页

作者： Ziqiao zhou Tianyang zhou Jinghao Xu Junhu Zhu Henan Key Laboratory of Information Security National Engineering Technology Research Center of the Digital Switching SystemZhengzhou450000China School of Cryptographic Engineering Information Engineering UniversityZhengzhou450000China

Intelligent penetration testing is of great significance for the improvement of the security of information systems,and the critical issue is the planning of penetration test *** view of the difficulty for attackers to obtain complete network information in realistic network scenarios,Reinforcement Learning(RL)is a promising solution to discover the optimal penetration path under incomplete information about the target *** RL-based methods are challenged by the sizeable discrete action space,which leads to difficulties in the ***,most methods still rely on experts’*** address these issues,this paper proposes a penetration path planning method based on reinforcement learning with episodic ***,the penetration testing problem is formally described in terms of reinforcement *** speed up the training process without specific prior knowledge,the proposed algorithm introduces episodic memory to store experienced advantageous strategies for the first ***,the method offers an exploration strategy based on episodic memory to guide the agents in *** design makes full use of historical experience to achieve the purpose of reducing blind exploration and improving planning ***,comparison experiments are carried out with the existing RL-based *** results reveal that the proposed method has better convergence *** running time is reduced by more than 20%.

关键词： Intelligent penetration testing penetration testing path planning reinforcement learning episodic memory exploration strategy

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Predicting the International Roughness Index of JPCP and CRCP Rigid Pavement:A Random Forest(RF)Model Hybridized with Modified Beetle Antennae Search(MBAS)for Higher Accuracy

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1557-1582页

作者： zhou Ji Mengmeng zhou Qiang Wang Jiandong Huang College of Civil and Environmental Engineering Hunan University of Science and EngineeringYongzhou425006China School of Mines China University of Mining and TechnologyXuzhou221116China School of Civil Engineering Guangzhou UniversityGuangzhou510006China

To improve the prediction accuracy of the International Roughness Index(IRI)of Jointed PlainConcrete Pavements(JPCP)and Continuously Reinforced Concrete Pavements(CRCP),a machine learning approach is developed in this study for the modelling,combining an improved Beetle Antennae Search(MBAS)algorithm and Random Forest(RF)*** 10-fold cross-validation was applied to verify the reliability and accuracy of the model proposed in this *** importance scores of all input variables on the IRI of JPCP and CRCP were analysed as *** results by the comparative analysis showed the prediction accuracy of the IRI of the newly developed MBAS and RF hybrid machine learning model(RF-MBAS)in this study is higher,indicated by the RMSE and R values of 0.2732 and 0.9476 for the JPCP as well as the RMSE and R values of 0.1863 and 0.9182 for the *** accuracy of this obtained result far exceeds that of the IRI prediction model used in the traditional Mechanistic-Empirical Pavement Design Guide(MEPDG),indicating the great potential of this developed *** importance analysis showed that the IRI of JPCP and CRCP was proportional to the corresponding input variables in this study,including the total joint faulting cumulated per KM(TFAULT),percent subgrade material passing the 0.075-mm Sieve(P_(200))and pavement surface area with flexible and rigid patching(all Severities)(PATCH)which scored higher.

关键词： Cement pavement JPCP CRCP RF-MBAS IRI

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Spatial Distribution Feature Extraction Network for Open Set Recognition of Electromagnetic Signal

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 279-296页

作者： Hui Zhang Huaji zhou Li Wang Feng zhou The Ministry Key Laboratory of Electronic Information Countermeasure and Simulation Xidian UniversityXi’an710071China Science and Technology on Communication Information Security Control Laboratory Jiaxing314033China

This paper proposes a novel open set recognition method,the Spatial Distribution Feature Extraction Network(SDFEN),to address the problem of electromagnetic signal recognition in an open *** spatial distribution feature extraction layer in SDFEN replaces convolutional output neural networks with the spatial distribution features that focus more on inter-sample information by incorporating class center *** designed hybrid loss function considers both intra-class distance and inter-class distance,thereby enhancing the similarity among samples of the same class and increasing the dissimilarity between samples of different classes during ***,this method allows unknown classes to occupy a larger space in the feature *** reduces the possibility of overlap with known class samples and makes the boundaries between known and unknown samples more ***,the feature comparator threshold can be used to reject unknown *** signal open set recognition,seven methods,including the proposed method,are applied to two kinds of electromagnetic signal data:modulation signal and real-world *** experimental results demonstrate that the proposed method outperforms the other six methods overall in a simulated open ***,compared to the state-of-the-art Openmax method,the novel method achieves up to 8.87%and 5.25%higher micro-F-measures,respectively.

关键词： Electromagnetic signal recognition deep learning feature extraction open set recognition

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Hot Compression Behavior and Tensile Property of a Novel Ni-Co-Based Superalloy Prepared by Electron Beam Smelting Layered Solidification Technology

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Acta Metallurgica Sinica(English Letters) 2024年第2期37卷 283-292页

作者： Yong-Chao Gai Rui Zhang Chuan-Yong Cui Zi-Jian zhou Yi Tan Yi-zhou zhou Xiao-Feng Sun Key Laboratory of Materials Modification by Laser Ionand Electron Beams(Ministry of Education)School of Materials Science and EngineeringDalian University of TechnologyDalian116024China Shi-Changxu Innovation Center for Advanced Materials Institute of Metal ResearchChinese Academy of SciencesShenyang110016China

The hot compression behavior and tensile strength after compression of a new Ni-Co-based superalloy produced using electron beam smelting layered(EBSL)solidification technology were *** compression tests were performed at temperatures of 1120℃and 1150℃,with strain rates of 1 s^(-1) and 0.01 s^(-1),reaching a true strain of *** strength was evaluated at room *** results revealed that this EBSL technology accelerates dynamic recrystallization(DRX),without compromising the strength of alloy.A significant correlation between the volume fraction of DRX and the strain rate was observed,with higher fractions at lower strain rates,leading to higher tensile ***,at the same strain rate,the specimens compressed at 1120℃exhibited higher tensile strength due to undissolvedγ′*** solution and aging heat treatment,the alloy maintained high tensile *** results suggested that the EBSL Ni-Co-based superalloy offers excellent prospects for practical applications.

关键词： Ni-Co-based superalloy Hot deformation Electron beam smelting Tensile strength

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Patterns and mechanisms of belowground carbon responses to changes in precipitation

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JOURNAL OF PLANT ECOLOGY 2024年第2期17卷 1-17页

作者： Chen, Hongyang Zhang, Qi zhou, Lingyan zhou, Xuhui Northeast Forestry Univ Sch Forestry Key Lab Sustainable Forest Ecosyst Management Minist Educ Harbin 150040 Peoples R China Shanghai Engn Res Ctr Sustainable Plant Innovat Res Ctr Shanghai Bot Garden Shanghai 200231 Peoples R China

It is well known that aboveground productivity usually increases with precipitation. However, how belowground carbon (C) processes respond to changes in precipitation remains elusive, although belowground net primary productivity (BNPP) represents more than one-half of NPP and soil stores the largest terrestrial C in the biosphere. This paper reviews the patterns of belowground C processes (BNPP and soil C) in response to changes in precipitation from transect studies, manipulative experiments, modeling and data integration and synthesis. The results suggest the possible existence of nonlinear patterns of BNPP and soil C in response to changes in precipitation, which is largely different from linear response for aboveground productivity. C allocation, root turnover time and species composition may be three key processes underlying mechanisms of the nonlinear responses to changes in precipitation for belowground C processes. In addition, microbial community structure and long-term ecosystem processes (e.g. mineral assemblage, soil texture, aggregate stability) may also affect patterns of belowground C processes in response to changes in precipitation. At last, we discuss implications and future perspectives for potential nonlinear responses of belowground C processes to changes in precipitation.

关键词： belowground processes BNPP nonlinear precipitation soil C NET PRIMARY PRODUCTIVITY SOIL ORGANIC-CARBON MICROBIAL COMMUNITY STRUCTURE PLANT-SPECIES RICHNESS CLIMATE-CHANGE ROOT TURNOVER TERRESTRIAL ECOSYSTEMS BIOMASS ALLOCATION GLOBAL PATTERNS ELEVATED CO2

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An Environment‑Tolerant Ion‑Conducting Double‑Network Composite Hydrogel for High‑Performance Flexible Electronic Devices

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Nano-Micro Letters 2024年第5期16卷 352-369页

作者： Wenchao Zhao Haifeng zhou Wenkang Li Manlin Chen Min zhou Long Zhao State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhan 430074People’s Republic of China School of Chemistry and Chemical Engineering Huazhong University of Science and TechnologyWuhan 430074People’s Republic of China

High-performance ion-conducting hydrogels(ICHs)are vital for developing flexible electronic ***,the robustness and ion-conducting behavior of ICHs deteriorate at extreme tempera-tures,hampering their use in soft *** resolve these issues,a method involving freeze–thawing and ionizing radiation technology is reported herein for synthesizing a novel double-network(DN)ICH based on a poly(ionic liquid)/MXene/poly(vinyl alcohol)(PMP DN ICH)*** well-designed ICH exhibits outstanding ionic conductivity(63.89 mS cm^(-1) at 25℃),excellent temperature resistance(-60–80℃),prolonged stability(30 d at ambient temperature),high oxidation resist-ance,remarkable antibacterial activity,decent mechanical performance,and ***,the ICH performs effectively in a flexible wireless strain sensor,thermal sensor,all-solid-state supercapacitor,and single-electrode triboelectric nanogenerator,thereby highlighting its viability in constructing soft electronic *** highly integrated gel structure endows these flexible electronic devices with stable,reliable signal output *** particular,the all-solid-state supercapacitor containing the PMP DN ICH electrolyte exhibits a high areal specific capacitance of 253.38 mF cm^(-2)(current density,1 mA cm^(-2))and excellent environmental *** study paves the way for the design and fabrication of high-performance mul-tifunctional/flexible ICHs for wearable sensing,energy-storage,and energy-harvesting applications.

关键词： Ionic liquids Double-network hydrogels Temperature tolerance Multifunctionality Flexible electronic devices

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Simulation of urban expansion using geographical similarity transition rules and neighbourhood sizes

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Journal of Geographical Sciences 2024年第7期34卷 1394-1414页

作者： LI Yinqi AN Yue zhou zhou REN Hui TAN Xuelan College of Resources Hunan Agricultural UniversityChangsha410128China College of Geographical Sciences Hunan Normal UniversityChangsha410081China

Most existing cellular automata(CA)models impose strict requirements on the number and spatial distribution of *** makes it a challenge to capture spatial heterogeneity in urban dynamics and meet the modeling needs of large and complex geographic *** paper presents a CA model based on geographically optimal similarity(GOS)transition rules and similarly sized neighborhoods(SSN).By comparing the similarity in geographical configuration between samples and predicted points,the model enables a comprehensive characterization of the driving mechanism behind urban expansion and its self-organizing *** helps to mitigate the impact of sample selection and assumptions about spatial stationarity on simulation *** performance of GOS-SSN-CA simulation was tested by taking the urban expansion in the Changsha-Zhuzhou-Xiangtan urban agglomeration in China as an *** results show that GOS can derive more accurate and reliable urban transition rules with fewer samples,thereby significantly reducing spatial prediction errors compared with logistic ***,SSN selects different neighborhood sizes to represent the difference between the local self-organizing range and surrounding cells,thus further improving the simulation accuracy and restricting urban expansion ***,GOS-SSN-CA effectively characterizes the geographical similarity of urban expansion,improves simulation accuracy while constraining the urban expansion form,and enhances the practical application value of CA.

关键词： urban growth cellular automata geographic similarity model optimization spatial nonstationarity

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Historical Changes and Multi-scenario Prediction of Land Use and Terrestrial Ecosystem Carbon Storage in China

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Chinese Geographical Science 2024年第3期34卷 487-503页

作者： AN Yue TAN Xuelan REN Hui LI Yinqi zhou zhou College of Resources Hunan Agricultural UniversityChangsha 410128China School of Geographic Science Hunan Normal UniversityChangsha 410081China

Terrestrial carbon storage(CS)plays a crucial role in achieving carbon balance and mitigating global climate *** study employs the Shared Socioeconomic Pathways and Representative Concentration Pathways(SSPs-RCPs)published by the Intergovernmental Panel on Climate Change(IPCC)and incorporates the Policy Control Scenario(PCS)regulated by China’s land management *** Future Land Use Simulation(FLUS)model is employed to generate a 1 km resolution land use/cover change(LUCC)dataset for China in 2030 and *** on the carbon density dataset of China’s terrestrial ecosystems,the study analyses CS changes and their relationship with land use changes spanning from 1990 to *** findings indicate that the quantitative changes in land use in China from 1990 to 2020 are characterised by a reduction in the area proportion of cropland and grassland,along with an increase in the impervious surface and forest *** changing trend is projected to continue under the PCS from 2020 to *** the SSPs-RCPs scenario,the proportion of cropland and impervious surface predominantly increases,while the proportions of forest and grassland continuously *** loss in China’s carbon storage from 1990 to 2020 amounted to 0.53×10^(12)kg,primarily due to the reduced area of cropland and *** the SSPs-RCPs scenario,more significant carbon loss occurs,reaching a peak of8.07×10^(12)kg in the SSP4-RCP3.4 *** loss is mainly concentrated in the southeastern coastal area and the Beijing-TianjinHebei(BTH)region of China,with urbanisation and deforestation identified as the primary *** the future,it is advisable to enhance the protection of forests and grassland while stabilising cropland areas and improving the intensity of urban *** research findings offer valuable data support for China’s land management policy,land space optimisation,and the achievement of dual-carbon targets.

关键词： land use change Future Land Use Simulation(FLUS)model carbon storage carbon density dataset land use scenario China

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