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FlowGANAnomaly: Flow-Based Anomaly Network Intrusion Detection with Adversarial Learning

Chinese Journal of Electronics 2024年第1期33卷 58-71页

作者： Zeyi LI Pan wang Zixuan wang School of Computer Science Nanjing University of Posts and Telecommunications School of Modern Posts Nanjing University of Posts and Telecommunications School of Internet of Things Nanjing University of Posts and Telecommunications

In recent years, low recall rates and high dependencies on data labelling have become the biggest obstacle to developing deep anomaly detection(DAD) techniques. Inspired by the success of generative adversarial networks(GANs) in detecting anomalies in computer vision and imaging, we propose an anomaly detection model called Flow GANAnomaly for detecting anomalous traffic in network intrusion detection systems(NIDS). Unlike traditional GAN-based approaches, which are composed of a flow encoder, a convolutional encoder-decoder-encoder, a flow decoder and a convolutional encoder, the architecture of this model consists of a generator(G) and a discriminator(D).Flow GANAnomaly maps the different types of traffic feature data from separate datasets to a uniform feature space,thus can capture the normality of network traffic data more accurately in an adversarial manner to mitigate the problem of the high dependence on data labeling. Moreover, instead of simply detecting the anomalies by the output of D, we proposed a new anomaly scoring method that integrates the deviation between the output of two Gs’ convolutional encoders with the output of D as weighted scores to improve the low recall rate of anomaly detection. We conducted several experiments comparing existing machine learning algorithms and existing deep learning methods(Auto Encoder and VAE) on four public datasets(NSL-KDD, CIC-IDS2017, CIC-DDo S2019, and UNSW-NB15). The evaluation results show that Flow GANAnomaly can significantly improve the performance of anomaly-based NIDS.

关键词： Anomaly detection Unsupervised learning Generative adversarial network Intrusion detection system

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Framework for Preventive Control of Power Systems to Defend Against Extreme Events

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 856-870页

作者： Yuwei Xiang Tong wang Zengping wang State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityBeijing 102206China

Enhancing power system resilience against extreme events is becoming increasingly critical. This paper discusses a unified framework for preventive control of power systems to enhance system resilience, which includes three parts: resilience assessment, resilience grading, and resilience enhancement. First, the resilience assessment contains facility-level and system-level resilience assessment. The concept of fragility curve is used in the facility-level resilience assessment. Various resilience indices are developed in system-level resilience assessment to roundly depict the impacts of extreme events on power systems and determine the system resilience. On this basis, the resilience is divided into different levels by resilience grading strategy, which can efficiently quantify the severity of the impact of extreme events and provide decision-making for the resilience enhancement strategies. Then, control strategies for enhancing power system resilience are also divided according to different resilience levels. A controlled islanding based preventive control is proposed to enhance system resilience, which aims to strengthen the first defensive line of power systems to deal with extreme events. Finally, taking the typhoon disaster in extreme events as an example, two tests carried out with two typhoons demonstrate the efficiency of the proposed method.

关键词： Controlled islanding extreme events power system resilience preventive control

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Toward tunable shape memory effect of NiTi alloy by grain size engineering:A phase field study

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Journal of Materials Science & Technology 2024年第1期168卷 276-289页

作者： Bo Xu Chong wang Qingyuan wang Failure Mechanics and Engineering Disaster Prevention Key Laboratory of Sichuan ProvinceSichuan UniversityChengdu 610065China Department of Mechanical Science and Engineering College of Architecture and EnvironmentSichuan UniversityChengdu 610065China Key Laboratory of Deep Underground Science and Engineering (Sichuan University)Ministry of EducationChengdu 610065China

The inelastic deformations of shape memory alloys(SMAs)always show poor controllability due to the avalanche-like martensite transformation,and the effective control for the deformation of precision de-vices has been not yet mature.In this work,the phase field method was used to investigate the shape memory effects(SMEs)of NiTi SMAs undergoing grain size(GS)engineering,to obtain tunable one-way and stress-assisted two-way SMEs(OWSME and SATWSME).The OWSME and SATWSME of the systems with various gradient-nanograin structures and bimodal grain structure,as well as that with geometric gradients were simulated.The simulated results indicate that due to the GS dependences of martensite transformation and reorientation,the occurrence and expansion of martensite reorientation,martensite transformation and its reverse can be efficaciously controlled via the GS engineering.When combining the GS engineering and geometric gradient design,since the effects of GS and stress gradient can be su-perimposed or competing,and the responses of martensite reorientation,martensite transformation and its reverse to this are different,the OWSME and SATWSME of the geometrically graded systems with various nanograin structures can exhibit different improvements in controllability.In short,the reorienta-tion hardening modulus during OWSME is increased and the transformation temperature window during SATWSME is widened by GS engineering,indicating the improved controllability of SMEs.The optimal GS engineering schemes revealed in this work provide the basic reference and guidance for designing tun-able SMEs and producing NiTi-based driving devices catering to desired functional performance in various engineering fields.

关键词： Phase field NiTi Shape memory effect Grain size engineering Geometric gradient

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Deciphering the Shared and Specific Drug Resistance Mechanisms of Anaplastic Lymphoma Kinase via Binding Free Energy Computation

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Research 2024年第1期2023卷 663-674页

作者： Yang Yu Zhe wang Lingling wang Qinghua wang Rongfan Tang Sutong Xiang Qirui Deng Tingjun Hou Huiyong Sun Department of Medicinal Chemistry China Pharmaceutical UniversityNanjing 210009JiangsuP.R.China Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University College of Pharmaceutical SciencesZhejiang UniversityHangzhou 310058ZhejiangP.R.China

Anaplastic lymphoma kinase(ALK),a tyrosine receptor kinase,has been proven to be associated with the occurrence of numerous malignancies.Although there have been already at least 3 generations of ALK inhibitors approved by FDA or in clinical trials,the occurrence of various mutations seriously attenuates the effectiveness of the drugs.Unfortunately,most of the drug resistance mechanisms still remain obscure.Therefore,it is necessary to reveal the bottom reasons of the drug resistance mechanisms caused by the mutations.In this work,on the basis of verifying the accuracy of 2 main kinds of binding free energy calculation methodologies[end-point method of Molecular Mechanics with Poisson-Boltzmann/Generalized Born and Surface Area(MM/PB(GB)SA)and alchemical method of Thermodynamic Integration(TI)],we performed a systematic analysis on the ALK systems to explore the underlying shared and specific drug resistance mechanisms,covering the one-drug-multiple-mutation and multiple-drug-onemutation cases.

关键词： drugs Anaplastic clinical

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A novel triple periodic minimal surface-like plate lattice and its data-driven optimization method for superior mechanical properties

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Applied Mathematics and Mechanics(English Edition) 2024年第2期45卷 217-238页

作者： Yanda wang Yanping LIAN Zhidong wang Chunpeng wang Daining FANG State Key Laboratory for Turbulence and Complex Systems&Center for Applied Physics and Technology College of EngineeringPeking UniversityBeijing 100871China Institute of Advanced Structure Technology Beijing Institute of TechnologyBeijing 100081China

Lattice structures can be designed to achieve unique mechanical properties and have attracted increasing attention for applications in high-end industrial equipment,along with the advances in additive manufacturing(AM)technologies.In this work,a novel design of plate lattice structures described by a parametric model is proposed to enrich the design space of plate lattice structures with high connectivity suitable for AM processes.The parametric model takes the basic unit of the triple periodic minimal surface(TPMS)lattice as a skeleton and adopts a set of generation parameters to determine the plate lattice structure with different topologies,which takes the advantages of both plate lattices for superior specific mechanical properties and TPMS lattices for high connectivity,and therefore is referred to as a TPMS-like plate lattice(TLPL).Furthermore,a data-driven shape optimization method is proposed to optimize the TLPL structure for maximum mechanical properties with or without the isotropic constraints.In this method,the genetic algorithm for the optimization is utilized for global search capability,and an artificial neural network(ANN)model for individual fitness estimation is integrated for high efficiency.A set of optimized TLPLs at different relative densities are experimentally validated by the selective laser melting(SLM)fabricated samples.It is confirmed that the optimized TLPLs could achieve elastic isotropy and have superior stiffness over other isotropic lattice structures.

关键词： lattice structure triple periodic minimal surface(TPMS) plate lattice structural optimization machine learning

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reeding maize of ideal plant architecture for high-density planting tolerance through modulating shade avoidance response and beyond

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Journal of Integrative Plant Biology 2024年第5期66卷 849-864页

作者： Fereshteh Jafari Baobao wang Haiyang wang Junjie Zou Biotechnology Research Institute Chinese Academy of Agricultural SciencesBeijing 100081China Graduate School of Chinese Academy of Agricultural Sciences Beijing 100081China National Nanfan Research Institute CAASSanya 572025China State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources College of Life SciencesSouth China AgriculturalUniversityGuangzhou 510642China

Maize is a major staple crop widely used as food,animal feed,and raw materials in industrial production.High-density planting is a major factor contributing to the continuous increase of maize yield.However,high planting density usually triggers a shade avoidance response and causes increased plant height and ear height,resulting in lodging and yield loss.Reduced plant height and ear height,more erect leaf angle,reduced tassel branch number,earlier flowering,and strong root system architecture are five key morphological traits required for maize adaption to high-density planting.In this review,we summarize recent advances in deciphering the genetic and molecular mechanisms of maize involved in response to high-density planting.We also discuss some strategies for breeding advanced maize cultivars with superior performance under high-density planting conditions.

关键词： flowering time high-density planting leaf angle maize plant architecture plant height/ear height root architecture tasselbranch

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A novel electro-Fenton hybrid system for enhancing the interception of volatile organic compounds in membrane distillation desalination

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Journal of Environmental Sciences 2024年第4期138卷 189-199页

作者： Hongxin Liu Kuiling Li Kunpeng wang Zhiyong wang Zimou Liu Sichao Zhu Dan Qu Yu Zhang Jun wang State Key Laboratory of Environmental Aquatic Chemistry Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China University of Chinese Academy of Sciences Beijing 100049China State Key Laboratory of Environment Simulation and Pollution Control School of Environment Tsinghua UniversityBeijing 100084China School of Chemical and Environmental Engineering Beijing CampusChina University of Mining and TechnologyBeijing 100083China Beijing Key Lab for Source Control Technology of Water Pollution College of Environmental Science and EngineeringBeijing Forestry UniversityBeijing 100083China

Membrane distillation(MD)is a promising alternative desalination technology,but the hydrophobic membrane cannot intercept volatile organic compounds(VOCs),resulting in aggravation in the quality of permeate.In term of this,electro-Fenton(EF)was coupled with sweeping gas membrane distillation(SGMD)in a more efficient way to construct an advanced oxidation barrier at the gas-liquid interface,so that the VOCs could be trapped in this layer to guarantee the water quality of the distillate.During the so-called EF-MD process,an interfacial interception barrier containing hydroxyl radical formed on the hydrophobic membrane surface.It contributed to the high phenol rejection of 90.2% with the permeate phenol concentration lower than 1.50 mg/L.Effective interceptions can be achieved in a wide temperature range,even though the permeate flux of phenol was also intensified.The EF-MD system was robust to high salinity and could electrochemically regenerate ferrous ions,which endowed the long-term stability of the system.This novel EF-MD configuration proposed a valuable strategy to intercept VOCs in MD and will broaden the application of MD in hypersaline wastewater treatment.

关键词： Membrane distillation VOC interception Interfacial oxidation Electro-Fenton Hypersaline wastewater

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Microsnoop: A generalist tool for microscopy image representation

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The Innovation 2024年第1期5卷 109-117页

作者： Dejin Xun Rui wang Xingcai Zhang Yi wang Pharmaceutical Informatics Institute College of Pharmaceutical SciencesZhejiang UniversityHangzhou 310058China State Key Lab of Computer-Aided Design&Computer Graphics Zhejiang UniversityHangzhou 310058China John A.Paulson School of Engineering and Applied Sciences Harvard UniversityCambridgeMA 02138USA Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University Hangzhou 310018China National Key Laboratory of Chinese Medicine Modernization Innovation Center of Yangtze River DeltaZhejiang UniversityJiaxing 314100China

Accurate profiling of microscopy images from small scale to high throughput is an essential procedure in basic and applied biological research.Here,we present Microsnoop,a novel deep learning–based representation tool trained on large-scale microscopy images using masked self-supervised learning.Microsnoop can process various complex and heterogeneous images,and we classified images into three categories:single-cell,full-field,and batch-experiment images.Our benchmark study on 10 high-quality evaluation datasets,containing over 2,230,000 images,demonstrated Microsnoop’s robust and state-ofthe-art microscopy image representation ability,surpassing existing generalist and even several custom algorithms.Microsnoop can be integrated with other pipelines to perform tasks such as superresolution histopathology image and multimodal analysis.Furthermore,Microsnoop can be adapted to various hardware and can be easily deployed on local or cloud computing platforms.We will regularly retrain and reevaluate the model using communitycontributed data to consistently improve Microsnoop.

关键词： hardware image representation

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Adaptive Barrier-Lyapunov-Functions Based Control Scheme of Nonlinear Pure-Feedback Systems with Full State Constraints and Asymptotic Tracking Performance

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Journal of Systems Science & Complexity 2024年第3期37卷 965-984页

作者： NIU Ben wang Xiaoan wang Xiaomei wang Xinjun LI Tao Faculty of Electronic Information and Electrical Engineering Dalian University of TechnologyDalian 116024China School of Information Science and Engineering Shandong Normal UniversityJinan 250014China School of Mathematics Southeast UniversityNanjing 211189China School of Automation Nanjing University of Information Science and TechnologyNanjing 210044China

In this paper,the authors propose an adaptive Barrier-Lyapunov-Functions(BLFs)based control scheme for nonlinear pure-feedback systems with full state constraints.Due to the coexist of the non-affine structure and full state constraints,it is very difficult to construct a desired controller for the considered system.According to the mean value theorem,the authors transform the pure-feedback system into a system with strict-feedback structure,so that the well-known backstepping method can be applied.Then,in the backstepping design process,the BLFs are employed to avoid the violation of the state constraints,and neural networks(NNs)are directly used to online approximate the unknown packaged nonlinear terms.The presented controller ensures that all the signals in the closed-loop system are bounded and the tracking error asymptotically converges to zero.Meanwhile,it is shown that the constraint requirement on the system will not be violated during the operation.Finally,two simulation examples are provided to show the effectiveness of the proposed control scheme.

关键词： Asymptotic tracking control barrier Lyapunov functions full state constraints nonlinear pure-feedback systems

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Functional Optical Fiber Sensors Detecting Imperceptible Physical/Chemical Changes for Smart Batteries

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Nano-Micro Letters 2024年第8期16卷 268-308页

作者： Yiding Li Li wang Youzhi Song Wenwei wang Cheng Lin Xiangming He Institute of Nuclear and New Energy Technology Tsinghua UniversityBeijing 100084People’s Republic of China National Engineering Research Center of Electric Vehicles Beijing Institute of Technology(BIT)Beijing 100081People’s Republic of China Shenzhen Automotive Research Institute of BIT(Shenzhen Research Institute of National Engineering Research Center of Electric Vehicles) Shenzhen 518118People’s Republic of China

The battery technology progress has been a contradictory process in which performance improvement and hidden risks coexist.Now the battery is still a“black box”,thus requiring a deep understanding of its internal state.The battery should“sense its internal physical/chemical conditions”,which puts strict requirements on embedded sensing parts.This paper summarizes the application of advanced optical fiber sensors in lithium-ion batteries and energy storage technologies that may be mass deployed,focuses on the insights of advanced optical fiber sensors into the processes of one-dimensional nano-micro-level battery material structural phase transition,electrolyte degradation,electrode-electrolyte interface dynamics to three-dimensional macro-safety evolution.The paper contributes to understanding how to use optical fiber sensors to achieve“real”and“embedded”monitoring.Through the inherent advantages of the advanced optical fiber sensor,it helps clarify the battery internal state and reaction mechanism,aiding in the establishment of more detailed models.These advancements can promote the development of smart batteries,with significant importance lying in essentially promoting the improvement of system consistency.Furthermore,with the help of smart batteries in the future,the importance of consistency can be weakened or even eliminated.The application of advanced optical fiber sensors helps comprehensively improve the battery quality,reliability,and life.

关键词： Smart battery Advanced embedded optical fiber sensor Battery internal physical/chemical state Quality-reliability-life characteristic

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