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IEEE International Conference on Big Data and Cloud computing (BdCloud)

作者： Yi Tian Guangping Xu Hongzhang Yang Yue Ni JiaXin Cao Lei Yang School of Computer Science and Engineering Tianjin University of Technology Tianjin China Tianjin Key Laboratory of Intelligence Computing Novel Software Technology Tianjin China Key Laboratory of Computer Vision and System Ministry of Education China Roycom (Tianjin) Information Technology Co. Ltd.

Regenerating codes are new network codes proposed to reduce the data required for fault repair, which can improve the recovery efficiency of faulty nodes in data storage systems. However, unlike Reed-Solomon code, which repairs at the granularity of bytes, regenerating codes require data stored in large chunks but leads to severe read amplification, which reads out excess data when degraded read objects and increases degraded read time. That reflects a mutual constraint between improving recovery efficiency and degraded read performance, as manifested in the amplification of data reads, a vital issue considered in this *** solve this problem, we propose a new type of data layout — discrete geometric, which splits the object into a series of geometric sequences of data blocks. They are placed discretely into corresponding containers on the disks at different nodes, with containers of the same size made into a strip for encoding. The discrete characteristic ensures lower repair costs for degraded reads. The geometric characteristic ensures the repair performance of regenerating codes by large blocks, and read amplification can be mitigated through small blocks. To reduce IOPS for discrete geometric, we propose Discrete Geometric-Locally Regenerating Codes (DG-LRCs), guaranteeing lower degraded read latency while improving recovery *** results show that the degraded read time of DG-LRCs compared to regenerating codes combined with geometric partitioning is 22.56% lower at 2Gbpsand 60.56% lower at 4Gbps, and the recovery performance is 7.04 times better than that of RS code.

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A MULTI-CATEGORY INVERSE DESIGN NEURAL NETWORK AND ITS APPLICATION TO DIBLOCK COPOLYMERS

arXiv

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arXiv 2022年

作者： Wei, Dan Zhou, Tiejun Huang, Yunqing Jiang, Kai Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing Ministry of Education School of Mathematics and Computational Science Xiangtan University Hunan Xiangtan411105 China

In this work, we design a multi-category inverse design neural network to map ordered periodic structure to physical parameters. The neural network model consists of two parts, a classifier and Structure-Parameter-Mapping (SPM) subnets. The classifier is used to identify structure, and the SPM subnets are used to predict physical parameters for desired structures. We also present an extensible reciprocal-space data augmentation method to guarantee the rotation and translation invariant of periodic structures. We apply the proposed network model and data augmentation method to two-dimensional diblock copolymers based on the Landau-Brazovskii model. Results show that the multi-category inverse design neural network is high accuracy in predicting physical parameters for desired structures. Moreover, the idea of multi-categorization can also be extended to other inverse design *** Codes 68T07, 35R30, 35Q68, 74E15, 03C64 Copyright © 2022, The Authors. All rights reserved.

关键词： Block copolymers

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EventTrojan: Manipulating Non-Intrusive Speech Quality Assessment via Imperceptible Events

EventTrojan: Manipulating Non-Intrusive Speech Quality Asses...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Ying Ren Kailai Shen Zhe Ye Diqun Yan Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China Juphoon System Software Co. Ltd Ningbo China Key Laboratory of Computing Power Network and Information Security Ministry of Education Qilu University of Technology (Shandong Academy of Sciences) China

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Non-Intrusive speech quality assessment (NISQA) has gained significant attention for predicting speech’s mean opinion score (MOS) without requiring the reference speech. Researchers have gradually started to apply NISQA to various practical scenarios. However, little attention has been paid to the security of NISQA models. Backdoor attacks represent the most serious threat to deep neural networks (DNNs) due to the fact that backdoors possess a very high attack success rate once embedded. However, existing backdoor attacks assume that the attacker actively feeds samples containing triggers into the model during the inference phase. This is not adapted to the specific scenario of NISQA. And current backdoor attacks on regression tasks lack an objective metric to measure the attack performance. To address these issues, we propose a novel backdoor triggering approach (EventTrojan) that utilizes an event during the usage of the NISQA model as a trigger. Moreover, we innovatively provide an objective metric for backdoor attacks on regression tasks. Extensive experiments on four benchmark datasets demonstrate the effectiveness of the EventTrojan attack. Besides, it also has good resistance to several defense methods.

关键词： Measurement Resistance Adaptation models Multimedia systems Current measurement Artificial neural networks Benchmark testing

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Deep Instruction Tuning for Segment Anything Model

arXiv

引用

arXiv 2024年

作者： Huang, Xiaorui Luo, Gen Zhu, Chaoyang Tong, Bo Zhou, Yiyi Sun, Xiaoshuai Ji, Rongrong Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China Xiamen University 361005 China Institute of Artificial Intelligence Xiamen University 361005 China The Department of Computer Science and Engineering The Hong Kong University of Science and Technology Kowloon Hong Kong

Recently, Segment Anything Model (SAM) has become a research hotspot in the fields of multimedia and computer vision, which exhibits powerful yet versatile capabilities on various (un) conditional image segmentation tasks. Although SAM can support different types of segmentation prompts, we note that, compared to point- and box-guided segmentations, it performs much worse on text-instructed tasks, e.g., referring image segmentation (RIS). In this paper, we argue that deep text instruction tuning is key to mitigate such shortcoming caused by the shallow fusion scheme in its default light-weight mask decoder. To address this issue, we propose two simple yet effective deep instruction tuning (DIT) methods for SAM, one is end-to-end and the other is layer-wise. With minimal modifications, DITs can directly transform the image encoder of SAM as a stand-alone vision-language learner in contrast to building another deep fusion branch, maximizing the benefit of its superior segmentation capability. Extensive experiments on three highly competitive benchmark datasets of RIS show that a simple end-to-end DIT can improve SAM by a large margin, while the layer-wise DIT can further boost the performance to state-of-the-art with much less data and training expenditures. Our code is released at: https://***/wysnzzzz/DIT. Copyright © 2024, The Authors. All rights reserved.

关键词： Image segmentation

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A Formal Analysis of Bluetooth Mesh Provisioning Protocol

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IEEE Internet of Things Journal 2025年

作者： Shi, Min Chen, Jing Zhao, Haoran He, Kun Du, Ruiying Wuhan University Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Cyber Science and Engineering Wuhan430072 China Wuhan University Rizhao Institute of Information Technology Rizhao276800 China Collaborative Innovation Center of Geospatial Technology Wuhan430079 China

Bluetooth Mesh is a wireless mesh networking technology based on Bluetooth Low Energy, where new devices need to be provisioned to join an existing network. Currently, security research on the Bluetooth Mesh provisioning protocol primarily focuses on the manual analysis of potential vulnerabilities, while existing formal models are too simplistic to capture all the attacks present in the protocol. In this paper, we utilize Tamarin Prover to conduct a comprehensive formal analysis of the Bluetooth Mesh provisioning protocol. Our model encompasses all phases of the protocol from beaconing to data distribution, and includes the modeling of all public key exchanges and authentication methods specified in the Bluetooth Mesh specification. Additionally, we accurately model the AES-CMAC primitive used in the protocol, with the help of deconstruction rules and built-in message theories in Tamarin. This AES-CMAC model enables the analysis of subtle behaviors that were previously beyond the scope of symbolic analysis. Our model successfully reproduces reflection and primitive misuse attacks found in previous studies and identifies two new vulnerabilities. We propose countermeasures for the aforementioned attacks and extend our provisioning model to verify the effectiveness of these countermeasures. © 2014 IEEE.

关键词： Wireless mesh networks (WMN)

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Insights into the nucleation,grain growth and phase transformation behaviours of sputtered metastableβ-W films

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Journal of Materials Science & Technology 2021年第31期90卷 66-75页

作者： Shuqun Chen Jinshu Wang Ronghai Wu Zheng Wang Yangzhong Li Yiwen Lu Wenyuan Zhou Peng Hua Hongyi Lia Key Laboratory of Advanced Functional Materials Education Ministry of ChinaFaculty of Materials and ManufacturingBeijing University of TechnologyBeijing 100124China School of Mechanics Civil Engineering and ArchitectureNorthwestern Polytechnical UniversityXi’an 710129China High Performance Computing Department National Supercomputing Center in ShenzhenShenzhen 518055China China Ship Development and Design Center Wuhan 430074China

Metastable phase in tungsten film is of great interests in recent years due to its giant spin Hall effects,however,little information has been known on its nucleation,growth and phase *** this paper,a 900 nm-thick tungsten film with double-layer structure(α-W underlayer andβ-W above it)was produced on SiO_(2)/Si substrate by high vacuum magnetron sputtering at room *** structural properties ofβ-W were systemically investigated by X-ray diffraction,transmission electron microscopy,thermodynamic calculation,first-principle and phase-field *** is found that theβ-W nucleation is energetically favoured on the SiO_(2)surface compared to theα-W *** the film thickening proceeds,β-W[211]turns to be preferred direction of growth owing to the elastic strain energy minimization,which is verified by phase-field ***,theβ→αphase transformation takes place near the film-substrate interface while the rest of the film keeps theβ-W phase,leading to a doublelayer *** localized phase transition is induced by lower Gibbs free energy ofα-W phase at larger grain sizes,which can be confirmed by thermodynamic *** in-situ heating TEM analysis of the as-deposited film reveals that theβ→αphase transformation is fulfilled byα/βinterface propagation rather than local atomic *** findings offer valuable insights into the intrinsic properties of metastable phase in tungsten.

关键词： Metastable phases Tungsten Nucleation and growth Phase field modelling Phase transformation

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A C0-continuous nonconforming virtual element method for linear strain gradient elasticity

arXiv

引用

arXiv 2024年

作者： Huang, Jianguo Yu, Yue School of Mathematical Sciences MOE-LSC Shanghai Jiao Tong University Shanghai200240 China Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education National Center for Applied Mathematics in Hunan School of Mathematics and Computational Science Xiangtan University Hunan Xiangtan411105 China

A robust C0-continuous nonconforming virtual element method (VEM) is developed for a boundary value problem arising from strain gradient elasticity in two dimensions, with the family of polygonal meshes satisfying a very general geometric assumption given in Brezzi et al. (2009) and Chen and Huang (2018). The stability condition of the VEMs is derived by establishing Korn-type inequalities and inverse inequalities. Some crucial commutative relations for locking-free analysis as in elastic problems are derived. The sharp and uniform error estimates with respect to both the microscopic parameter and the Lamé coefficient are achieved in the lowest-order case, which is also verified by numerical *** Codes 65N12, 65N15, 65N22, 65N30 © 2024, CC BY-NC-ND.

关键词： Boundary value problems

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G3BP2 regulates oscillatory shear stress-induced endothelial dysfunction

引用

Genes & Diseases 2022年第6期9卷 1701-1715页

作者： Tianhan Li Juhui Qiu Tingting Jia Yinming Liang Kun Zhang Wenhua Yan Zhengjun Hou Shiwei Yang Lushan Liu Wenhao Xiong Yaokai Chen Guixue Wang Key Laboratory for Biorheological Science and Technology of Ministry of Education State Key Laboratory of Mechanical TransmissionState and Local Joint Engineering Laboratory for Vascular ImplantsBioengineering College of Chongqing UniversityChongqing 400044PR China Laboratory of Genetic Regulators in the Immune System Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory MedicineXinxiang Medical UniversityXinxiangHenan 45003PR China Department of Vascular Surgery First Affiliated HospitalArmy Medical University(Third Military University)Chongqing 400038PR China Institute of Cardiovascular Disease Key Laboratory for Arteriosclerology of Hunan ProvinceHunan International Scientific and Technological Cooperation Base of Arteriosclerotic DiseaseHengyang Medical CollegeUniversity of South ChinaHengyangHunan 421001PR China Division of Infectious Diseases Chongqing Public Health Medical CenterChongqing 400030PR China

GTPase-activating SH3 domain-binding protein 2(G3BP2)is a mediator that responds to environmental stresses through stress granule formation and is involved in the progression of chronic ***,no studies have examined the contribution of G3BP2 in the oscillatory shear stress(OSS)-induced endothelial *** we assessed the effects of G3BP2 in endothelial cells(ECs)function and investigated the underlying *** shear stress apparatus and partial ligation model,we identified that stress granulerelated genes in ECs could be induced by OSS with RNA-seq,and then confirmed that G3BP2 was highly and specifically expressed in athero-susceptible endothelia in the OSS regions.G3bp2e/eApoee/e mice had significantly decreased atherosclerotic lesions associated with deficiency of G3BP2 in protecting endothelial barrier function,decreasing monocyte adhesion to ECs and inhibiting the proinflammatory cytokine ***,loss of G3BP2 diminished OSS-induced inflammation in ECs by increasing YAP nucleocytoplasmic shuttling and *** data demonstrate that G3BP2 is a critical OSS regulated gene in regulating ECs function and that G3BP2 inhibition in ECs is a promising atheroprotective therapeutic strategy.

关键词： Atherosclerosis Endothelial cells(ECs) G3BP2 Oscillatory shear stress(OSS) YAP

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Operator Learning Enhanced Physics-informed Neural Networks for Solving Partial Differential Equations Characterized by Sharp Solutions

arXiv

引用

arXiv 2023年

作者： Lin, Bin Mao, Zhiping Wang, Zhicheng Karniadakis, George Em School of Mathematical Sciences Fujian Provincial Key Laboratory of Mathematical Modeling and High-Performance Scientific Computing Xiamen University Xiamen361005 China Laboratory of Ocean Energy Utilization Ministry of Education School of Energy and Power Engineering Dalian University of Technology Dalian China Division of Applied Mathematics Brown University ProvidenceRI02906 United States

Physics-informed Neural Networks (PINNs) have been shown as a promising approach for solving both forward and inverse problems of partial differential equations (PDEs). Meanwhile, the neural operator approach, including methods such as Deep Operator Network (DeepONet) and Fourier neural operator (FNO), has been introduced and extensively employed in approximating solution of PDEs. Nevertheless, to solve problems consisting of sharp solutions poses a significant challenge when employing these two approaches. To address this issue, we propose in this work a novel framework termed Operator Learning Enhanced Physics-informed Neural Networks (OL-PINN). Initially, we utilize DeepONet to learn the solution operator for a set of smooth problems relevant to the PDEs characterized by sharp solutions. Subsequently, we integrate the pre-trained DeepONet with PINN to resolve the target sharp solution problem. We showcase the efficacy of OL-PINN by successfully addressing various problems, such as the nonlinear diffusion-reaction equation, the Burgers equation and the incompressible Navier-Stokes equation at high Reynolds number. Compared with the vanilla PINN, the proposed method requires only a small number of residual points to achieve a strong generalization capability. Moreover, it substantially enhances accuracy, while also ensuring a robust training process. Furthermore, OL-PINN inherits the advantage of PINN for solving inverse problems. To this end, we apply the OL-PINN approach for solving problems with only partial boundary conditions, which usually cannot be solved by the classical numerical methods, showing its capacity in solving ill-posed problems and consequently more complex inverse problems. Copyright © 2023, The Authors. All rights reserved.

关键词： Partial differential equations

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Finite-time asynchronous dissipative filtering of conic-type nonlinear Markov jump systems

引用

Science China(Information Sciences) 2021年第5期64卷 151-162页

作者： Xiang ZHANG Shuping HE Vladimir STOJANOVIC Xiaoli LUAN Fei LIU Key Laboratory of Intelligent Computing and Signal Processing (Ministry of Education) School of Electrical Engineering and Automation Anhui University Department of Automatic Control Robotics and Fluid Technique Faculty of Mechanical and Civil EngineeringUniversity of Kragujevac Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of AutomationJiangnan University

In the present study, the finite-time asynchronous dissipative filter design problem for the Markov jump systems with conic-type nonlinearity is studied. The hidden Markov model can describe the asynchronism embodied in the system modes and the filter modes reasonably. Moreover, a suitable LyapunovKrasovskii function is utilized and linear matrix inequalities are applied to obtain adequate conditions. These techniques guarantee the finite-time boundedness and strict dissipativity of the filtering error dynamic system. Furthermore, the design problems of the passive filter and the H∞ filter are studied by adjusting the three parameters U, G and V. Finally, the filter gains and the optimal index α*are obtained and the correctness and feasibility of the designed approach are verified by a simulation example.

关键词： dissipative filtering hidden Markov model finite-time boundedness Markov jump systems conic-type nonlinearity

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