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CToMP: a cycle-task-oriented memory protection scheme for unmanned systems

Science China(Information Sciences) 2024年第6期67卷 399-417页

作者： Chengyan ma Ning XI Di LU Yebo FENG Jianfeng ma School of Cyber Engineering Xidian University School of Computer Science and Technology Xidian University Department of Computer and Information Science University of Oregon

Memory corruption attacks(MCAs) refer to malicious behaviors of system intruders that modify the contents of a memory location to disrupt the normal operation of computing systems, causing leakage of sensitive data or perturbations to ongoing processes. Unlike general-purpose systems, unmanned systems cannot deploy complete security protection schemes, due to their limitations in size, cost and *** in unmanned systems are particularly difficult to defend against. Furthermore, MCAs have diverse and unpredictable attack interfaces in unmanned systems, severely impacting digital and physical sectors. In this paper, we first generalize, model and taxonomize MCAs found in unmanned systems currently, laying the foundation for designing a portable and general defense approach. According to different attack mechanisms,we found that MCAs are mainly categorized into two types — return2libc and return2shellcode. To tackle return2libc attacks, we model the erratic operation of unmanned systems with cycles and then propose a cycle-task-oriented memory protection(CToMP) approach to protect control flows from tampering. To defend against return2shellcode attacks, we introduce a secure process stack with a randomized memory address by leveraging the memory pool to prevent Shellcode from being executed. Moreover, we discuss the mechanism by which CTo MP resists the return-oriented programming(ROP) attack, a novel variant of return2libc attacks. Finally, we implement CTo MP on CUAV V5+ with Ardupilot and Crazyflie. The evaluation and security analysis results demonstrate that the proposed approach CTo MP is resilient to various MCAs in unmanned systems with low footprints and system overhead.

关键词： unmanned system memory corruption attack memory protection system security randomized memory address

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Mitigate noisy data for smart IoT via GAN based machine unlearning

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Science China(Information Sciences) 2024年第3期67卷 62-78页

作者： Zhuo ma Yilong YANG Yang LIU Xinjing LIU Jianfeng ma School of Cyber Engineering Xidian University State Key Laboratory of Integrated Services Networks (ISN)

With the development of IoT applications, machine learning dramatically improves the utility of variable IoT systems such as autonomous driving. Although the pretrain-finetune framework can cope well with data heterogeneity in complex IoT scenarios, the data collected by sensors often contain unexpected noisy data, e.g., out-of-distribution(OOD) data, which leads to the reduced performance of fine-tuned models. To resolve the problem, this paper proposes Mu GAN, a method that can mitigate the side-effect of OOD data via the generative adversarial network(GAN)-based machine unlearning. Mu GAN follows a straightforward but effective idea to mitigate the performance loss caused by OOD data, i.e., “flashbacking” the model to the condition where OOD data are excluded from model training. To achieve the goal, we design an adversarial game, where a discriminator is trained to identify whether a sample belongs to the training set by observing the confidence score. Meanwhile, a generator(i.e., the target model) is updated to fool the discriminator into believing that the OOD data are not included in the training set but others do. The experimental results show that benefiting from the high unlearning rate(more than 90%) and retention rate(99%), Mu GAN succeeds in lowering the model performance degradation caused by OOD data from 5.88% to 0.8%.

关键词： machine unlearning generative adversarial network out of distribution data Internet of Thing neural network

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Unconfined compressive strength and failure behaviour of completely weathered granite from a fault zone

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Journal of Mountain Science 2024年第6期21卷 2140-2158页

作者： DU Shaohua ma Jinyin ma Liyao ZHAO Yaqian School of Civil Engineering and Architecture Henan University of Science and TechnologyLuoyang 471023China School of Resources and Safety Engineering Central South UniversityChangsha 410083China China Railway 18th Bureau Group Co. LtdTianjin 300222 China China General Nuclear Power Corporation Shenzhen 518031China

Understanding the strength characteristics and deformation behaviour of the tunnel surrounding rock in a fault zone is significant for tunnel stability *** this study,a series of unconfined compression tests were conducted to investigate the mechanical characteristics and failure behaviour of completely weathered granite(CWG)from a fault zone,considering with height-diameter(h/d)ratio,dry densities(ρd)and moisture contents(ω).Based on the experimental results,a regression mathematical model of unconfined compressive strength(UCS)for CWG was developed using the Multiple Nonlinear Regression method(MNLR).The research results indicated that the UCS of the specimen with a h/d ratio of 0.6 decreased with the increase ofω.When the h/d ratio increased to 1.0,the UCS increasedωwith up to 10.5%and then ***ρd is conducive to the improvement of the UCS at anyω.The deformation and rupture process as well as final failure modes of the specimen are controlled by h/d ratio,ρd andω,and the h/d ratio is the dominant factor affecting the final failure mode,followed byωandρ*** specimens with different h/d ratio exhibited completely different fracture mode,i.e.,typical splitting failure(h/d=0.6)and shear failure(h/d=1.0).By comparing the experimental results,this regression model for predicting UCS is accurate and reliable,and the h/d ratio is the dominant factor affecting the UCS of CWG,followed byρd and thenω.These findings provide important references for maintenance of the tunnel crossing other fault fractured zones,especially at low confining pressure or unconfined condition.

关键词： Fault fracture zone Completely weathered granite(CWG) Unconfined compression strength(UCS) Multiple nonlinear regression model

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Deterministic and Robust Volt-var Control Methods of Power System Based on Convex Deep Learning

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 719-729页

作者： Qing ma Changhong Deng the School of Electrical Engineering and Automation Wuhan UniversityWuhanChina

Volt-var control(VVC)is essentially a non-convex optimization problem due to the non-convexity of power flow(PF)constraints,resulting in the difficulty in obtaining the optimum without convexity *** existing second-order cone method for the convexity conversion often leads to a sharp increase in PF constraints and optimization variables,which in turn increases the optimization difficulty or even leads to optimization *** paper first proposes a deterministic VVC method based on convex deep learning power flow(DLPF).This method uses the input convex neural network(ICNN)to establish a single convex mapping between state parameters and node voltage to complete the convexity conversion while the optimization variables only correspond to reactive power equipment,which can ensure the global optimum with extremely fast computation *** cope with the impact brought by the uncertainty of distributed energy and omit the additional worst scenario search of traditional robust VVC,this paper proposes robust VVC method based on convex deep learning interval power flow(DLIPF),which continues to adopt ICNN to establish another convex mapping between state parameters and node voltage *** DLIPF with DLPF,this method decreases the modeling and optimization difficulty of robust VVC *** results on 30-bus,118-bus,and 200-bus systems prove the correctness and rapidity of the proposed methods.

关键词： Volt-var control convexity conversion convex deep learning power flow

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Enhancing capacitive deionization performance and cyclic stability of nitrogen-doped activated carbon by the electro-oxidation of anode materials

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Chinese Journal of Chemical Engineering 2024年第5期69卷 23-33页

作者： Xiaona Liu Baohua Zhao Yanyun Hu Luyue Huang Jingxiang ma Shuqiao Xu Zhonglin Xia Xiaoying ma Shuangchen ma School of Environmental Science and Engineering North China Electric Power UniversityBaoding 071003China Huadian Zhengzhou machinery Design and Research Institute Co. LtdZhengzhou 450002China Huadian Inner Mongolia Energy Co. Ltd.Baotou Power Generation BranchBaotou 014013China

Electrode materials with high desalination capacity and long-term cyclic stability are the focus of capacitive deionization(CDI) community. Understanding the causes of performance decay in traditional carbons is crucial to design a high-performance material. Based on this, here, nitrogen-doped activated carbon(NAC) was prepared by pyrolyzing the blend of activated carbon powder(ACP) and melamine for the positive electrode of asymmetric CDI. By comparing the indicators changes such as conductivity, salt adsorption capacity, pH, and charge efficiency of the symmetrical ACP-ACP device to the asymmetric ACP-NAC device under different CDI cycles, as well as the changes of the electrochemical properties of anode and cathode materials after long-term operation, the reasons for the decline of the stability of the CDI performance were revealed. It was found that the carboxyl functional groups generated by the electro-oxidation of anode carbon materials make the anode zero-charge potential(E_(pzc)) shift positively,which results in the uneven distribution of potential windows of CDI units and affects the adsorption capacity. Furthermore, by understanding the electron density on C atoms surrounding the N atoms, we attribute the increased cyclic stability to the enhanced negativity of the charge of carbon atoms adjacent to quaternary-N and pyridinic-oxide-N.

关键词： Anodic oxidation Capacitive deionization Cyclic stability N-doping

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Triple-path feature transform network for ring-array photoacoustic tomography image reconstruction

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Journal of Innovative Optical Health Sciences 2024年第3期17卷 23-40页

作者： Lingyu ma Zezheng Qin Yiming ma Mingjian Sun School of Astronautics Harbin Institute of Technology HarbinHeilongjiang 150000P.R.China

Photoacoustic imaging(PAI)is a noninvasive emerging imaging method based on the photoacoustic effect,which provides necessary assistance for medical *** has the characteristics of large imaging depth and high ***,limited by the equipment cost and reconstruction time requirements,the existing PAI systems distributed with annular array transducers are difficult to take into account both the image quality and the imaging *** this paper,a triple-path feature transform network(TFT-Net)for ring-array photoacoustic tomography is proposed to enhance the imaging quality from limited-view and sparse measurement ***,the network combines the raw photoacoustic pressure signals and conventional linear reconstruction images as input data,and takes the photoacoustic physical model as a prior information to guide the reconstruction *** addition,to enhance the ability of extracting signal features,the residual block and squeeze and excitation block are introduced into the *** further efficient reconstruction,the final output of photoacoustic signals uses‘filter-then-upsample’operation with a pixel-shuffle multiplexer and a max out *** results on simulated and in-vivo data demonstrate that the constructed TFT-Net can restore the target boundary clearly,reduce background noise,and realize fast and high-quality photoacoustic image reconstruction of limited view with sparse sampling.

关键词： Deep learning feature transformation image reconstruction limited-view measurement photoacoustic tomography.

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A combined Liouville integrable hierarchy associated with a fourth-order matrix spectral problem

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Communications in Theoretical Physics 2024年第07期76卷 3-10页

作者： Wen-Xiu ma Department of mathematics Zhejiang Normal University Department of mathematics King Abdulaziz University Department of mathematics and Statistics University of South Florida Tampa material Science Innovation and Modelling Department of Mathematical Sciences North-West University Mafikeng Campus

This paper aims to propose a fourth-order matrix spectral problem involving four potentials and generate an associated Liouville integrable hierarchy via the zero curvature formulation. A bi-Hamiltonian formulation is furnished by applying the trace identity and a recursion operator is explicitly worked out, which exhibits the Liouville integrability of each model in the resulting hierarchy. Two specific examples, consisting of novel generalized combined nonlinear Schr?dinger equations and modified Korteweg–de Vries equations, are given.

关键词： Hamiltonian structure integrable hierarchy Lax pair matrix spectral problem zero curvature equation

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Nuclear phylogenomics of angiosperms and insights into their relationships and evolution

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Journal of Integrative Plant Biology 2024年第3期66卷 546-578页

作者： Guojin Zhang Hong ma College of Life Sciences Hunan Normal UniversityChangsha 410081China Department of Biology 510 Mueller LaboratoryHuck Institutes of the Life SciencesThe Pennsylvania State UniversityUniversity ParkPA 16802USA

Angiosperms(flowering plants) are by far the most diverse land plant group with over 300,000 species. The sudden appearance of diverse angiosperms in the fossil record was referred to by Darwin as the “abominable mystery,”hence contributing to the heightened interest in angiosperm evolution. Angiosperms display wide ranges of morphological, physiological,and ecological characters, some of which have probably influenced their species richness. The evolutionary analyses of these characteristics help to address questions of angiosperm diversification and require well resolved phylogeny. Following the great successes of phylogenetic analyses using plastid sequences,dozens to thousands of nuclear genes from next-generation sequencing have been used in angiosperm phylogenomic analyses, providing well resolved phylogenies and new insights into the evolution of angiosperms. In this review we focus on recent nuclear phylogenomic analyses of large angiosperm clades, orders, families,and subdivisions of some families and provide a summarized Nuclear Phylogenetic Tree of Angiosperm Families. The newly established nuclear phylogenetic relationships are highlighted and compared with previous phylogenetic results. The sequenced genomes of Amborella,Nymphaea, Chloranthus, Ceratophyllum, and species of monocots, magnoliids, and basal eudicots, have facilitated the phylogenomics of relationships among five major angiosperms clades. All but one of the 64 angiosperm orders were included in nuclear phylogenomics with well resolved relationships except the placements of several orders. Most families have been included with robust and highly supported placements, especially for relationships within several large and important orders and ***, we examine the divergence time estimation and biogeographic analyses of angiosperm on the basis of the nuclear phylogenomic frameworks and discuss the differences compared with previous analyses. Furthermore,we discuss the implicatio

关键词： angiosperms evolution flowering plants nuclear gene phylogenomics phylogeny

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In silico optimization of actuation performance in dielectric elastomercomposites via integrated finite element modeling and deep learning

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Theoretical & Applied Mechanics Letters 2024年第1期14卷 48-56页

作者： Jiaxuan ma Sheng Sun materials Genome Institute Shanghai UniversityShanghai 200444China Zhejiang Laboratory Hangzhou 311100China Shanghai Frontier Science Center of Mechanoinformatics Shanghai UniversityShanghai 200444China

Dielectric elastomers(DEs)require balanced electric actuation performance and mechanical integrity under applied *** high dielectric particles as fillers provides extensive design space to optimize concentration,morphology,and distribution for improved actuation performance and material *** study presents an integrated framework combining finite element modeling(FEM)and deep learning to optimize the microstructure of DE *** first calculates actuation performance and the effective modulus across varied filler combinations,with these data used to train a convolutional neural network(CNN).Integrating the CNN into a multi-objective genetic algorithm generates designs with enhanced actuation performance and material modulus compared to the conventional optimization approach based on FEM approach within the same *** framework harnesses artificial intelligence to navigate vast design possibilities,enabling optimized microstructures for high-performance DE composites.

关键词： Dielectric elastomer composites Multi-objective optimization Finite element modeling Convolutional neural network

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登月舱上升段最优轨迹设计

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中国空间科学技术 2013年第2期33卷 54-60页

作者：马克茂陈海朋哈尔滨工业大学控制与仿真中心哈尔滨150080

为了实现登月舱上升段轨迹的优化,建立了上升段登月舱动力学模型,用单位归一化技术建立了最优控制模型,并以燃料消耗为最优指标,利用Pontryagin极小值原理,将问题转化为时间自由的两点边值问题(TPBVP)。采用了一种基于初值预估方法和向... 详细信息

为了实现登月舱上升段轨迹的优化,建立了上升段登月舱动力学模型,用单位归一化技术建立了最优控制模型,并以燃料消耗为最优指标,利用Pontryagin极小值原理,将问题转化为时间自由的两点边值问题(TPBVP)。采用了一种基于初值预估方法和向前扫描法求解TPBVP,从而设计出登月舱上升段最优轨迹,并进行了数值仿真。仿真结果表明所设计的算法收敛速度快、可靠性高。

关键词：离月段轨道轨迹设计最优控制两点边值问题登月舱

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