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On the hardness of NTRU problems

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Frontiers of Computer Science 2022年第6期16卷 135-144页

作者： Yang Wang Mingqiang wang School of Mathematics Shandong UniversityJinan250100China Key Laboratory of Cryptologic Technology and Information Security Shandong UniversityJinan250100China

The hardness of NTRU problem affects heavily on the securities of the cryptosystems based on it.However,we could only estimate the hardness of the specific parameterized NTRU problems from the perspective of actual attacks,and whether there are worst-case to average-case reductions for NTRU problems like other lattice-based problems(e.g.,the Ring-LWE problem)is still an open problem.In this paper,we show that for any algebraic number field K,the NTRU problem with suitable parameters defined over the ring of integers R is at least as hard as the corresponding Ring-LWE problem.Hence,combining known reductions of the Ring-LWE problem,we could reduce worst-case basic ideal lattice problems,e.g.,SIVPγproblem,to average-case NTRU problems.Our results also mean that solving a kind of average-case SVPγproblem over highly structured NTRU lattice is at least as hard as worst-case basic ideal lattice problems in K.As an important corollary,we could prove that for modulus q=Õ(n^(5.5)),average-case NTRU problem over arbitrary cyclotomic field K with[K:Q]=n is at least as hard as worst-case SIVP_(γ)problems over K with γ=Õ(n^(6)).

关键词： lattice-based cryptography algebraic nmber fields NTRU Problems Ring-LWE computational compleity

A characterization study on perovskite X-ray detector performance based on a digital radiography system

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Nuclear Science and Techniques 2023年第5期34卷 56-66页

作者： Yang Wang Qiong Zhang University of Electronic Science and Technology of China Chengdu 610000China

X-ray imaging technologies such as digital radiography(DR),is an important aspect of modern non-destructive testing and medical diagnosis.Innovative flexible X-ray detector technologies have recently been proposed and are now receiving increasing attention owing to their superior material flexibility compared with traditional flat-panel detectors.This work aims to study these innovative flexible X-ray detectors in terms of their effectiveness in DR imaging,such as detection efficiency and spatial resolution.To achieve this goal,first,a Monte Carlo model was developed and calibrated to an in-lab 150 kV DR imaging system containing a flat-panel X-ray detector.Second,the validated model was updated with various types of flexible X-ray detectors to assess their performance in nearly realistic conditions.Key parameters such as the detection efficiency pertaining to the crystal material and thickness were studied and analyzed across a broader energy range up to 662 keV.Finally,the imaging performance of the different detectors was evaluated and compared to that of the flat-panel detector in the 150 kV DR imaging system.The results show that the flexible detectors such as the CsPbBr3crystal detector deliver promising performance in X-ray imaging and can be applied to a wider range of application scenarios,especially those requiring accurate detection at challenging angles.

关键词： Flexible X-ray detector DR imaging system Monte Carlo simulation

Activating translation by phase separation:a novel mechanism for driving spermiogenesis

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Science China(Life Sciences) 2023年第2期66卷 418-420页

作者： Wenjing Zhang Yang Wang Institute of Cancer Stem Cell Dalian Medical UniversityDalian 116044China

Eucaryotic cells spatially organize their molecules to form various organelles by compartmentalization, thereby performing fundamental biological process. While some of those organelles are delimited by lipid membranes, others are membrane-less. Biomolecular condensates are widely existed as membrane-less cellular compartments in eukaryotic cells, which are usually formed by phase separation.

关键词： driving separation translation

Progressive learning with multi-scale attention network for cross-domain vehicle re-identification

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Science China(Information Sciences) 2022年第6期65卷 33-47页

作者： Yang Wang Jinjia PENG Huibing wang Meng wang School of Computer Science and Information Engineering Hefei University of Technology Intelligent Interconnected Systems Laboratory of Anhui Province Hefei University of Technology Information Science and Technology College Dalian Maritime University School of Cyber Security and Computer Hebei University

Vehicle re-identification(reID) aims to identify vehicles across different cameras that have nonoverlapping views. Most existing vehicle reID approaches train the reID model with well-labeled datasets via a supervised manner, which inevitably causes a severe drop in performance when tested in an unknown domain. Moreover, these supervised approaches require full annotations, which is limiting owing to the amount of unlabeled data. Therefore, with the aim of addressing the aforementioned problems, unsupervised vehicle reID models have attracted considerable attention. It always adopts domain adaptation to transfer discriminative information from supervised domains to unsupervised ones. In this paper, a novel progressive learning method with a multi-scale fusion network is proposed, named PLM, for vehicle reID in the unknown domain, which directly exploits inference from the available abundant data without any annotations. For PLM, a domain adaptation module is employed to smooth the domain bias, which generates images with similar data distribution to unlabeled target domain as “pseudo target samples”. Furthermore, to better exploit the distinct features of vehicle images in the unknown domain, a multi-scale attention network is proposed to train the reID model with the “pseudo target samples” and unlabeled samples; this network embeds low-layer texture features with high-level semantic features to train the reID model. Moreover, a weighted label smoothing(WLS) loss is proposed, which considers the distance between samples and different clusters to balance the confidence of pseudo labels in the feature learning module. Extensive experiments are carried out to verify that our proposed PLM achieves excellent performance on several benchmark datasets.

关键词： data adaptation module weighted label smoothing loss multi-scale attention network vehicle re-identification

Real-time Subsynchronous Control Interaction Monitoring Using Improved Intrinsic Time-scale Decomposition

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Journal of Modern Power Systems and Clean Energy 2023年第3期11卷 816-826页

作者： Yang Wang Hanlu yang Xiaorong Xie Xiaomei yang Guanrun Chen College of Electrical Engineering Sichuan UniversityChengduChina Department of Electrical Engineering Tsinghua UniversityBeijingChina

In recent years,subsynchronous control interaction(SSCI)has frequently taken place in renewable-connected power systems.To counter this issue,utilities have been seeking tools for fast and accurate identification of SSCI events.The main challenges of SSCI monitoring are the time-varying nature and uncertain modes of SSCI events.Accordingly,this paper presents a simple but effective method that takes advantage of intrinsic time-scale decomposition(ITD).The main purpose is to improve the accuracy and robustness of ITD by incorporating the least-squares method.Results show that the proposed method strikes a good balance between dynamic performance and estimation accuracy.More importantly,the method does not require any prior information,and its performance is therefore not affected by the frequency constitution of the SSCI.Comprehensive comparative studies are conducted to demonstrate the usefulness of the method through synthetic signals,electromagnetic temporary program(EMTP)simulations,and field-recorded SSCI data.Finally,real-time simulation tests are conducted to show the feasibility of the method for real-time monitoring.

关键词： Subsynchronous control interaction(SSCI) intrinsic time-scale decomposition(ITD) wind power system realtime monitoring

Generating high-resolution climatological precipitation data using SinGAN

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Big Earth Data 2023年第1期7卷 81-100页

作者： Yang Wang Hassan A.Karimi Geoinformatics Laboratory School of Computing and InformationUniversity of PittsburghPittsburghUSA

High-resolution(HR)climate data are indispensable for studying regional climate trends,disaster prediction,and urban development planning in the face of climate change.However,state-of-the-art long-term global climate simulations do not provide appropriate HR climate data.Deep learning models are often used to obtain high-resolution climate data.However,due to the fact that these models require sufficient low-resolution(LR)and HR data pairs for the training process,they cannot be applied to scenario with inadequate training data.In this paper,we explore the applicability of a single image generative adversarial network(SinGAN)in generating HR climate data.SinGAN relies on single LR input data to obtain the corresponding HR data.To improve the performance for extreme-value regions,we propose a SinGAN combined with the weighted patchGAN discriminator(WSinGAN).The proposed WSinGAN outperforms comparable models in generating HR precipitation data,and its results are close to real HR data with sharp gradients and more refined small-scale features.We also test the scalability of the pre-trained WSinGAN for unseen samples and show that although only a single LR sample is used to train WSinGAN,it can still produce reliable HR data for unseen data.

关键词： Climate downscaling SinGAN deep learning adversarial training

A review of research on central crack in continuous casting strand

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Journal of Iron and Steel Research(International) 2023年第6期30卷 1073-1089页

作者： Yong-kun yang Jia-yu Zhu Wei-an wang Yang Wang Jian-li wang Guan-jie wang Xiao-ming Li School of Metallurgical Engineering Xi’an University of Architecture and TechnologyXi’an 710055ShaanxiChina

Central crack is a common quality defect in continuous casting strand,which is difficult to fully weld in the rolling and forging processes,and has become a key technical problem that restricts the stable production of high-end alloy rod/forging/pipe.In recent years,the central crack control has been one of the main focuses in high quality steel research.In order to fully understand the central crack,the research status of central crack characteristics,formation mechanism,influencing factors,and control methods in the world was reviewed.The deficiencies in the research of the central crack and the key research directions in the future were pointed out,which will provide references for other scholars in this field of research.It is found that alloying elements segregation during solidification and inclusions precipitated at grain boundaries are the main reasons for the central crack formation,while the unreasonable application of production processes can also induce the initiation of central crack.The optimization of alloying element composition and production process is helpful to reduce the initiation of central cracks.In addition,the quantitative characterization mechanism based on steel grades,temperature,stress,and other factors induced central crack should be established in the further study,forming a systematic quantitative determination criterion and control strategy for coupling the composition,process and thermal/mechanical characteristic.

关键词： Central crack Continuous casting strand Formation mechanism Alloying element Control strategy

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缸内燃烧过程中缸盖表面振动信号分析与研究

振动与冲击 2021年第13期40卷 210-215,254页

作者：王洋程勇山东大学能源与动力工程学院济南250061

基于单缸柴油机台架试验和虚拟样机仿真分析,研究了缸盖表面振动加速度信号的主要激励源及其耦合关系,讨论了带通滤波技术和经验模态分解提取的燃烧激励响应信号完整性与有效性。结果表明:缸盖表面振动加速度信号主要激励源为缸内压力... 详细信息

基于单缸柴油机台架试验和虚拟样机仿真分析,研究了缸盖表面振动加速度信号的主要激励源及其耦合关系,讨论了带通滤波技术和经验模态分解提取的燃烧激励响应信号完整性与有效性。结果表明:缸盖表面振动加速度信号主要激励源为缸内压力和往复惯性力;二者的振动响应在时频域重叠,重叠部分的能量取决于缸内工作过程及发动机转速;基于相干性分析的带通滤波技术提取的燃烧激励响应曲线上,用于识别燃烧过程特征参数的特征点位置受发动机机型及缸内燃烧状态影响;经验模态分解得到的燃烧激励响应与非燃烧激励响应间存在模态混叠问题,基于往复惯性力激励响应信号描述模型可对分解得到的燃烧激励响应信号进行修正,降低燃烧激励响应曲线上与燃烧过程相关的特征点的离散度。

关键词：内燃机振动分析相干性经验模态分解(EMD)

Calibrations of Urbanization Level in China

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China CDC weekly 2022年第6期4卷 111-115页

作者： Yang Wang Jinfeng wang Yansui Liu Jie Li State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina University of Chinese Academy of Sciences BeijingChina Center for Regional Agriculture and Rural Development Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina

Urbanization is the inevitable outcome of socioeconomic development,especially after the industrial revolution in 1760(1).Since the founding of the People’s Republic of China in 1949,the urbanization of China has made great progress.The speed and mass of urbanization and notably its relevant consequences,such as resource consumption and carbon emissions,has taken place in the most populous country in the world over the past three decades,which is raising increased concerns internationally(2)(Figure 1).Urbanization rate(in this article,this indicator refers to the population urbanization rate)is a common indicator of urbanization.Many international organizations(such as the World Bank,World Health Organization,Food and Agriculture Organization of the United Nations,etc.)use urbanization as one of the important criteria for measuring productivity and economic growth in a country(1).China’s urbanization process can be described as the largest population migration in history and has also had an important impact on public health.As the national population migrates from rural to urban areas,differences in lifestyle,environmental quality,social security,and accidental injuries have all been brought about and become more and more dramatic(3).

关键词： Urbanization Figure founding