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SSRN 2023年

作者： Shi, Ling Wang, Jiang Xu, Songzhe Li, Jingjing Chen, Chaoyue Hu, Tao Sundar, Hari Ren, Zhongming State Key Laboratory of Advanced Special Steels School of Materials Science and Engineering Shanghai University Shanghai China School of Computing University of Utah Salt Lake City United States

Single crystal (SX) nickel-based superalloys have been used for turbine blades fabrication in recent years because of their superior mechanical performance at high temperature. The restoration of SX blades is significant considering the high cost to re-manufacture the blade. Direct energy deposition (DED), as a laser additive manufacturing technique, is a promising method for repairing the SX blades. Continuous epitaxial growth from the substrate to deposited layers is vital for successful restoration of SX blades. In this work, a novel single crystal texture cellular automata (SITCA) method is developed to simultaneously predict the columnar to equiaxed transition (CET) and crystal growth direction at the molten pool scale. Based on the grain envelope simplification, the SITCA method introduces a random variable to trace the growth trajectory, and therefore indicates the partition of the growth regions in the molten pool. A continuous nucleation model is introduced for nucleation simulation, and the crystal growth is simulated using the KurzGiovanola-Trivedi (KGT) model. The validation of SITCA model is performed by casting solidification cases under uniform temperature and uniform temperature gradient. The SITCA method is then integrated with a thermo-fluid molten pool simulation using finite element method to comprehensively compute the epitaxial growth. SX remelting experiments are carried out with different laser scanning speeds using a flat top laser source, and compared with the numerical results. The experimental and numerical results both indicate that increasing laser scanning speed will increase the ratio of crystals growing in the [001] direction while facilitate the CET on the other hand. This work shows the capacity of the SITCA method to predict epitaxial growth in DED process, and we anticipate to deploy the SITCA method to complex SX additive manufacturing. © 2023, The Authors. All rights reserved.

关键词： Epitaxial growth

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4DRGS: 4D Radiative Gaussian Splatting for Efficient 3D Vessel Reconstruction from Sparse-View Dynamic DSA Images

arXiv

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arXiv 2024年

作者： Liu, Zhentao Zha, Ruyi Zhao, Huangxuan Li, Hongdong Cui, Zhiming School of Biomedical Engineering State Key Laboratory of Advanced Medical Materials and Devices ShanghaiTech University Shanghai China School of Computing Australian National University Canberra Australia School of Computer Science Wuhan University Wuhan China

Reconstructing 3D vessel structures from sparse-view dynamic digital subtraction angiography (DSA) images enables accurate medical assessment while reducing radiation exposure. Existing methods often produce suboptimal results or require excessive computation time. In this work, we propose 4D radiative Gaussian splatting (4DRGS) to achieve high-quality reconstruction efficiently. In detail, we represent the vessels with 4D radiative Gaussian kernels. Each kernel has time-invariant geometry parameters, including position, rotation, and scale, to model static vessel structures. The time-dependent central attenuation of each kernel is predicted from a compact neural network to capture the temporal varying response of contrast agent flow. We splat these Gaussian kernels to synthesize DSA images via X-ray rasterization and optimize the model with real captured ones. The final 3D vessel volume is voxelized from the well-trained kernels. Moreover, we introduce accumulated attenuation pruning and bounded scaling activation to improve reconstruction quality. Extensive experiments on real-world patient data demonstrate that 4DRGS achieves impressive results in 5 minutes training, which is 32× faster than the state-of-the-art method. This underscores the potential of 4DRGS for real-world clinics. Copyright © 2024, The Authors. All rights reserved.

关键词： Gaussian distribution

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Cluster-Based Routing Algorithm for WSN Based on Subtractive Clustering 16

Cluster-Based Routing Algorithm for WSN Based on Subtractive...

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16th IEEE International Wireless Communications and Mobile computing Conference, IWCMC 2020

作者： Chen, Ling Liu, Wenwen Gong, Daofu Chen, Yan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450002 China

ISBN: (纸本)9781728131290

The Cluster-based Routing Algorithm for Wireless Sensor Network based on Subtractive Clustering (SCC algorithm) generates nodes of cluster head in dense area of the node by relying on subtractive clustering. The application of this algorithm effectively solves the attribution problem of non-cluster head node in conventional algorithms, and consumption is evenly distributed throughout the network. Through simulation experiments, it can be found that the application of the SCC algorithm can map the distribution of nodes of cluster head reasonably and delay the death time of the first node to prolong the lifetime of network and balance the energy consumption of nodes. © 2020 IEEE.

关键词： Routing algorithms

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Clustering and Routing Optimization Algorithm for Heterogeneous Wireless Sensor Networks 16

Clustering and Routing Optimization Algorithm for Heterogene...

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16th IEEE International Wireless Communications and Mobile computing Conference, IWCMC 2020

作者： Chen, Ling Liu, Wenwen Gong, Daofu Chen, Yan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450002 China

ISBN: (纸本)9781728131290

Wireless sensor network (WSN) is the cutting-edge technology of modern monitoring technology. There is a direct relationship between the length of its lifetime and its performance. Efficient and reasonable clustering and routing algorithm can reduce the energy loss in the network, which is of great significance for prolonging the network lifetime. The traditional WSN protocol has been difficult to meet the needs of the contemporary society. This paper focuses on the advantages and disadvantages of the traditional WSN protocol, and puts forward relevant improvement measures to optimize the traditional WSN protocol and extend the network life time. © 2020 IEEE.

关键词： Wireless sensor networks

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Research on the Protection Mechanism of Cisco IOS Exploit 4

Research on the Protection Mechanism of Cisco IOS Exploit

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4th International Conference on Data Mining, Communications and Information Technology, DMCIT 2020

作者： Wang, Jinzhu Cai, Ruijie Liu, Shengli State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

Cisco IOS is an operating system that runs on Cisco routing and switching equipment. Its security is important to the entire network. Since vulnerability attacks have become one of the main sources of threat to Cisco IOS security, it is necessary to analyze the defense mechanism of IOS against vulnerability attacks. The purpose of this paper is to find out the deficiencies of IOS vulnerability defense mechanism in time and put forward improvement methods and preventive measures. Firstly, this paper introduces the protection mechanism of Cisco IOS vulnerability, including CheckHeaps, DEP, ASLR. The principle of these mechanisms and the idea of vulnerability protection are analyzed. And then, after analyzing the shortcomings of these protection mechanisms, the basic idea of bypassing these protection mechanisms is proposed. Finally, in view of the shortcomings of Cisco IOS vulnerability defense mechanism and the proposed bypass methods, some advices about how to better protect Cisco IOS from vulnerability exploitation are given. © Published under licence by IOP Publishing Ltd.

关键词： Network security

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Network representation learning based extended matrix factorization for recommendation 6th

Network representation learning based extended matrix factor...

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6th International Conference on Artificial Intelligence and Security,ICAIS 2020

作者： Xu, Jinmao Gong, Daofu Liu, Fenlin Tan, Lei State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

ISBN: (纸本)9789811581007

The growing heterogeneous data in the Internet effectively improves the performance of recommender systems (RS). The main problem faced by the traditional matrix factorization (MF) is how to fuse more heterogeneous information data in MF to improve the performance of RS. In view of this, this paper proposes an Extended Matrix Factorization (EMF) based on network representation learning. EMF integrates multiple types of data in Heterogeneous Information Network (HIN) to improve the accuracy of prediction rating. The nodes in HIN are first mapped to a low-dimensional representation vector by network representation learning (NRL). Then the representation vector is used as the input of the EMF, the parameters are optimized by the gradient descent, and finally the prediction model is obtained. The experiments on two real data sets show the effectiveness of the EMF. Compared with the baseline algorithms, the EMF model can obtain more accurate prediction rating. © Springer Nature Singapore Pte Ltd 2020.

关键词： Recommender systems

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Dynamic Network Change Detection via Dynamic Network Representation Learning 14th

Dynamic Network Change Detection via Dynamic Network Represe...

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14th EAI International Conference on Communications and Networking in China, ChinaCom 2019

作者： Feng, Hao Liu, Yan Zhou, Ziqiao Chen, Jing China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9783030411138

The structure of the network in the real world is very complex, as the dynamic network structure evolves in time dimension, how to detect network changes accurately and further locate abnormal nodes is a research hotspot. Most current feature learning methods are difficult to capture a variety of network connectivity patterns, and have a high time complexity. In order to overcome this limitation, we introduce the network embedding method into the field of network change detection, we find that node-based egonet can better reflect the connectivity patterns of the node, so a dynamic network embedding model Egonet2Vec is proposed, which is based on extracting the connectivity patterns of the node-based egonets. After the dynamic network representation learning, we use a dynamic network change detection strategy to detect network change time points and locate abnormal nodes. We apply our method to real dynamic network datasets to demonstrate the validity of this method. © 2020, ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Change detection

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Defense method of ruby code injection attack based on instruction set randomization 20

Defense method of ruby code injection attack based on instru...

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8th International Conference on Computer and Communications Management, ICCCM 2020

作者： Wang, Jiang Yao, Yuan Zhang, Gaofei Li, Fangyun State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

ISBN: (纸本)9781450387668

Code injection attack is a major security threat to applications, especially web applications. This type of attack stems from the attacker's ability to use the vulnerability/backdoor of the application to inject a malicious program into the server and execute it, or the application's lack of verification and filtering of user input parameters, resulting in the input being executed as a malicious program to achieve the attack aims. The existing defense methods, such as source program analysis and input rule matching, have inherent defects in the face of code injection attacks. In order to improve the defense effect of web applications against code injection attacks, a method against code injection based on instruction set randomization was proposed. The defense method does not depend on the attack method adopted by the attacker, and can resist unknown code injection attacks. Based on this technology, the concept of dynamic transformation is introduced to improve the defense ability. Even if the attacker obtains the randomization method, it is difficult to break through the system. Although this method requires randomized transformation of the application source code, the processing process is completely automated. Experiments show that this method can effectively resist code injection attacks and achieve active defense against attacks. © 2020 ACM.

关键词： Network security

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Network security assessment based on full host-based attack graph

Network security assessment based on full host-based attack ...

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2020 International Conference on Cyberspace Innovation of advanced Technologies, CIAT 2020

作者： Wang, Xiao-Fan Zhou, Tian-Yang Zhu, Jun-Hu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Henan China

ISBN: (纸本)9781450387828

Network security assessment is an important method of evaluating network security. The existing researches of network security assessment have the problem that the method is not comprehensive and accurate. In order to solve this problem, we proposed a method of network security assessment based on a full host-based attack graph from the "point"and "plane"perspective. This method constructed a full host-based attack graph model, and proposed a splitting algorithm for weakly connected components of the full host-based attack graph. The algorithm is used to evaluate the network security from the "plane"perspective. Meanwhile, based on the full host-based attack graph and the theory of degree centrality and betweenness centrality, the key nodes in the network are evaluated. Therefore, this method accomplished the comprehensive and accurate security measurement of the network. The experimental results showed the effectiveness of the method. © 2020 ACM.

关键词： Network security

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Deep generative network for image inpainting with gradient semantics and spatial-smooth attention

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Journal of Visual Communication and Image Representation 2024年 98卷

作者： Sheng, Ziqi Xu, Wenbo Lin, Cong Lu, Wei Ye, Long School of Computer Science and Engineering Guangdong Province Key Laboratory of Information Security Technology Ministry of Education Key Laboratory of Machine Intelligence and Advanced Computing Sun Yat-sen University Guangzhou510006 China Applied Laboratory of Dig Data and Education Statistics School of Statistics and Mathematics Guangdong University of Finance and Economics Guangzhou510320 China State Key Laboratory of Media Convergence and Communication Communication University of China Beijing100024 China

As a powerful forgery operation in the image content security area, image inpainting based on deep generative networks can yield visually appealing outputs but often produces ambiguous artifacts, especially in boundary and high semantic areas. To address this issue, a novel end-to-end network with gradient semantics and spatial-smooth attention (GS-SSA) is proposed, which combines a gradient learning network and an image inpainting network. The gradient learning network is meant to properly anticipate the gradient semantics in the hole region and get a complete gradient semantic map. The image inpainting network utilizes the complete gradient semantic map to better repair the missing pixels and obtain the final inpainting results. Moreover, spatial-smooth attention is introduced into the image inpainting network, considering both the spatial structural relations and the surrounding information in the hole region. Experimental results on public datasets show the superiority of the proposed method, especially in large-hole region tasks. © 2023 Elsevier Inc.

关键词： Semantics

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