检索结果-内蒙古大学图书馆

3rd BenchCouncil International Symposium on Benchmarking, Measuring, and Optimizing, Bench 2020

作者： Chen, Bangduo Li, Mingzhen Yang, Hailong Luan, Zhongzhi Gan, Lin Yang, Guangwen Qian, Depei School of Computer Science and Engineering Beihang University Beijing100191 China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi Jiangsu214125 China Department of Computer Science and Technology Tsinghua University Beijing100084 China

ISBN: (纸本)9783030710576

The Sunway processor has been demonstrated with superior performance by various scientific applications, domain specific frameworks and numerical algorithms. However, the optimization techniques that can fully exploit the architecture features are usually buried deep in large code bases, which prevents average programmers to understand such optimization techniques. Thus, the existing complex software fails to provide guidance for more programs embracing the computation power of Sunway processor. In this paper, we build a benchmark suite swRodinia by porting and optimizing the well-known Rodinia benchmark on Sunway processor. Specifically, we demonstrate several optimization techniques by tailoring the benchmarks to better leverage the architecture features for higher performance. Moreover, based on the optimization experiences, we derive several useful insights from both software and hardware perspectives, that not only guide the better utilization of current Sunway processor, but also reveal the direction of hardware improvements for future Sunway processor. We open source the swRodinia benchmark suite and encourage the community to enhance the benchmark with us continuously. © 2021, Springer Nature Switzerland AG.

关键词： Open source software

来源：评论

学校读者我要写书评

暂无评论

An OFDM based interference reducing scheme with trajectory and resource optimization for UAV-powered IoT Networks 34

An OFDM based interference reducing scheme with trajectory a...

引用

34th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2021

作者： Gao, Yuan Cao, Jiang Guo, Yang Wang, Ping Yang, Siming Wang, Jing Lu, Weidang Si, Peiyuan Zhao, Ming Wu, Xiao Academy of Military Science of the PLA 100091 China College of Information Engineering Zhejiang University of Technology Hangzhou China Tsinghua University Beijing100084 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

ISBN: (纸本)9789463968027

The massive and pervasive deployment of sensors for information collecting in IoT networks result to the scarcity of energy. Unmanned aerial vehicle (UAV) enabled wireless power transfer (WPT) is a feasible solution to provide energy for pervasively deployed sensors. In this paper, we propose an orthogonal frequency division multiplexing (OFDM) based interference reducing scheme with trajectory and resource optimization for UAV-powered IoT networks. The simulation results show that our proposed scheme outperforms two benchmark schemes in sum transmission rate. © 2021 URSI.

关键词： Orthogonal frequency division multiplexing

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Loss Network for Localization of Image Manipulation 19th

A Hybrid Loss Network for Localization of Image Manipulation

引用

19th International Workshop on Digital Forensics and Watermarking, IWDW 2020

作者： Yin, Qilin Wang, Jinwei Luo, Xiangyang Nanjing University of Information Science and Technology and Engineering Research Center of Digital Forensics Ministry of Education Nanjing210044 China State Key Laboratory of Mathematical Engineering and Advanced Computing Henan450001 China Shanxi Key Laboratory of Network and System Security Xidian University Xi’an710071 China

ISBN: (纸本)9783030694487

With the development of information security, localization of image manipulations havs become a hot topic. In this paper, a hybrid loss network is proposed for the manipulated image forensics. First, the patch prediction module extracts corresponding features representing the discrepancy of the tampered region boundaries. Then, these features are constrained by the Pixel Normalization, thereby improving the classification performance for the tampered patches. Finally, multi-scale patch prediction masks and semantic information are fused to segment out the tampered regions. The experiments demonstrate the proposed model can achieve high performance. © 2021, Springer Nature Switzerland AG.

关键词： Pixels

来源：评论

学校读者我要写书评

暂无评论

Collision attack framework on RIPEMD-128 2

Collision attack framework on RIPEMD-128

引用

2nd International Conference on Artificial Intelligence and advanced Manufacture, AIAM 2020

作者： Li, Jingyu Zeng, Guang Yang, Yang State Key Laboratory of Mathematical Engineering and Advanced Computing PLA Strategic Force Information Engineering University Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing PLA Information Engineering University Zhengzhou China Trusted Computing and Information Assurance Laboratory Institute of Software Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781728199863

In the last few years, the hash functions are the very common and essential primitives implemented in lots of fields. RIPEMD-128, a member of MD-family hash function, has been found collisions on the full round. In this paper, we further analyze the property about the security against collision attack of RIPEMD-128. The collision attack framework for RIPEMD-128 is proposed in order to provide ideas for other hash functions. The framework consists of three parts namely choosing a message word difference insertion, constructing differential characteristics and collision search phase. Cryptographic techniques including message modification is also introduced to reduce the complexity. © 2020 IEEE.

关键词： Hash functions

来源：评论

学校读者我要写书评

暂无评论

Interaction-Aware Cut-In Trajectory Prediction and Risk Assessment in Mixed Traffic

引用

IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1752-1762页

作者： Xianglei Zhu Wen Hu Zejian Deng Jinwei Zhang Fengqing Hu Rui Zhou Keqiu Li Fei-Yue Wang the College of Intelligence and Computing Tianjin UniversityTianjin 300350 the China Automotive Technology and Research Center Co.Ltd. Tianjin 300300China the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body College of Mechanical and Vehicle EngineeringHunan UniversityChangsha 410082China the Department of Mechanical and Mechatronics Engineering University of WaterlooWaterlooON N2L3G1Canada the School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China the Macao University of Science and Technology MacaoChina the Waytous Inc. Qingdao 266000China IEEE the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Accurately predicting the trajectories of surrounding vehicles and assessing the collision risks are essential to avoid side and rear-end collisions caused by *** improve the safety of autonomous vehicles in the mixed traffic,this study proposes a cut-in prediction and risk assessment method with considering the interactions of multiple traffic *** integration of the support vector machine and Gaussian mixture model(SVM-GMM)is developed to simultaneously predict cut-in behavior and *** dimension of the input features is reduced through Chebyshev fitting to improve the training efficiency as well as the online inference *** on the predicted trajectory of the cut-in vehicle and the responsive actions of the autonomous vehicles,two risk measurements are introduced to formulate the comprehensive interaction risk through the combination of Sigmoid function and Softmax ***,the comparative analysis is performed to validate the proposed method using the naturalistic driving *** results show that the proposed method can predict the trajectory with higher precision and effectively evaluate the risk level of a cut-in maneuver compared to the methods without considering interaction.

关键词： Cut-in behavior interaction-aware mixed traffic risk assessment trajectory prediction

来源：评论

学校读者我要写书评

暂无评论

CRNet:3D Face Reconstruction with Contour Map Regression Network 6

CRNet:3D Face Reconstruction with Contour Map Regression Net...

引用

6th IEEE International Conference on Computer and Communications, ICCC 2020

作者： Wei, Tongxin Li, Qingbao Liu, Jinjin School of Software Zhengzhou University Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing China

ISBN: (纸本)9781728186351

2D face images represent faces with incomplete information. 3D face reconstruction from a single 2D image is a challenging problem with application value. The single feature extraction method distorts the generated 3D face image. In this paper, we use contour-based face segmentation method to reconstruct 3D face image. We focus on the edge and contour information of the face when using contour lines to segment the face. Different from the global 3D face reconstruction method, we combine the global and local face information to carry out 3D face reconstruction. Our method: First of all, we do contour segmentation for human faces and extract the features of the segmented images. Second, we learn the local binary features of each keypoint in a complete face image, then combine the features and use linear regression to detect the keypoints. Thirdly, we use Convolutional Neural Networks to learn the regression 3D Morphable Model coefficient and significantly improve the quality and efficiency of reconstruction. We regressed the coefficients of the 3D deformable model from 2D images to present face alignment for 3D face reconstruction. We carry out feature mapping between 2D face and 3D face image, and monitor and verify 3D face model through mapping relationship. Our method can not only reconstruct face images from all angles, but also reduce face deformities. We made face images fit better under different expressions and postures. © 2020 IEEE.

关键词： Mapping

来源：评论

学校读者我要写书评

暂无评论

ID-Guard: A Universal Framework for Combating Facial Manipulation via Breaking Identification

arXiv

引用

arXiv 2024年

作者： Qu, Zuomin Lu, Wei Luo, Xiangyang Wang, Qian Cao, Xiaochun School of Computer Science and Engineering Ministry of Education Key Laboratory of Information Technology Guangdong Province Key Laboratory of Information Security Technology Sun Yat-sen University Guangzhou510006 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450002 China School of Cyber Science and Engineering Wuhan University Wuhan430072 China School of Cyber Science and Technology Shenzhen Campus Sun Yat-sen University Shenzhen518107 China

The misuse of deep learning-based facial manipulation poses a significant threat to civil rights. To prevent this fraud at its source, proactive defense has been proposed to disrupt the manipulation process by adding invisible adversarial perturbations into images, making the forged output unconvincing to observers. However, the non-specific disruption against the output may lead to the retention of identifiable facial features, potentially resulting in the stigmatization of the individual. This paper proposes a universal framework for combating facial manipulation, termed ID-Guard. Specifically, this framework operates with a single forward pass of an encoder-decoder network to produce a cross-model transferable adversarial perturbation. A novel Identity Destruction Module (IDM) is introduced to degrade identifiable features in forged faces. We optimize the perturbation generation by framing the disruption of different facial manipulations as a multi-task learning problem, and a dynamic weight strategy is devised to enhance cross-model performance. Experimental results demonstrate that the proposed ID-Guard exhibits strong efficacy in defending against various facial manipulation models, effectively degrading identifiable regions in manipulated images. It also enables disrupted images to evade facial inpainting and image recognition systems. Additionally, ID-Guard can seamlessly function as a plug-and-play component, integrating with other tasks such as adversarial training. Copyright © 2024, The Authors. All rights reserved.

关键词： Multi-task learning

来源：评论

学校读者我要写书评

暂无评论

Numerical Solution for Nonlinear 4D Variational Data Assimilation (4D-Var) via ADMM

arXiv

引用

arXiv 2024年

作者： Li, Bowen Shi, Bin State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China

The four-dimensional variational data assimilation (4D-Var) has emerged as an important methodology, widely used in numerical weather prediction, oceanographic modeling, and climate forecasting. Classical unconstrained gradient-based algorithms often struggle with local minima, making their numerical performance highly sensitive to the initial guess. In this study, we exploit the separable structure of the 4D-Var problem to propose a practical variant of the alternating direction method of multipliers (ADMM), referred to as the linearized multi-block ADMM with regularization. Unlike classical first-order optimization methods that primarily focus on initial conditions, our approach derives the Euler-Lagrange equation for the entire dynamical system, enabling more comprehensive and effective utilization of observational data. When the initial condition is poorly chosen, the arg min operation steers the iteration towards the observational data, thereby reducing sensitivity to the initial guess. The quadratic subproblems further simplify the solution process, while the parallel structure enhances computational efficiency, especially when utilizing modern hardware. To validate our approach, we demonstrate its superior performance using the Lorenz system, even in the presence of noisy observational data. Furthermore, we showcase the effectiveness of the linearized multi-block ADMM with regularization in solving the 4D-Var problems for the viscous Burgers’ equation, across various numerical schemes, including finite difference, finite element, and spectral methods. Finally, we illustrate the recovery of dynamics under noisy observational data in a 2D turbulence scenario, particularly focusing on vorticity concentration, highlighting the robustness of our algorithm in handling complex physical phenomena. © 2024, CC BY-NC-ND.

关键词： Weather forecasting

来源：评论

学校读者我要写书评

暂无评论

Revocable Broadcast Encryption with Constant Ciphertext and Private key Size

引用

Chinese Journal of Electronics 2019年第4期28卷 690-697页

作者： JIA Hongyong CHEN Yue YANG Kuiwu GUO Yuanbo WANG Zhiwei Zhengzhou University State Key Laboratory of Mathematical Engineering and Advanced Computing Nanjing University of Post and Communications

In a revocable broadcast encryption scheme, the group manager can flexibly set revoked users who cannot decrypt the ciphertext. Many applications of the revocable broadcast encryption have been found in the secure cloud data sharing. An adaptively secure revocable broadcast encryption system with constant ciphertext and private key size under standard assumptions is more suitable for use in the cloud environment. Few existing revocable broadcast encryption schemes meet such a requirement. We propose a revocable broadcast encryption scheme with constant size ciphertext and private key by combining the RSA cryptographic accumulator with an efficient identity based encryption system. We prove it to be adaptively secure under standard assumptions using dual system encryption techniques.

关键词： Cryptographic accumulator Broadcast encryption Revocable Dual system encryption Cloud data sharing

来源：评论

学校读者我要写书评

暂无评论

A survey of coverage-guided greybox fuzzing with deep neural models

引用

Information and Software Technology 2025年 186卷

作者： Qiu, Junyang Jiang, Yupeng Miao, Yuantian Luo, Wei Pan, Lei Zheng, Xi State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214123 China School of Computing Macquarie University Sydney 2109 NSW Australia School of Information and Physical Sciences University of Newcastle Newcastle 2308 NSW Australia School of Information Technology Deakin University Melbourne 3125 VIC Australia

Coverage-guided greybox fuzzing (CGF) has emerged as a powerful technique for software vulnerability detection, yet traditional techniques often struggle with the increasing complexity of modern software systems and the vastness of input spaces. Deep neural networks (DNNs) have begun to fundamentally transform CGF by addressing these limitations through automated feature extraction, adaptive input generation, and intelligent path prioritization. However, despite these advancements, critical gaps persist in understanding the state-of-the-art landscape. Existing studies often lack rigorous benchmarks to evaluate scalability and generalizability, fail to address the interpretability of neural-guided decisions, and overlook the integration of emerging paradigms such as large language models (LLMs) and neurosymbolic reasoning. This survey systematically bridges these gaps by providing a comprehensive taxonomy of DNN-driven CGF techniques, analyzing their strengths and limitations across key fuzzing stages—seed generation, selection, and mutation. We find that although DNNs have significantly improved fuzzing efficiency, challenges such as semantically invalid seeds, high computational overhead, and limited cross-domain adaptability remain unresolved. Most importantly, we identify two transformative directions with the potential to redefine CGF: (1) LLM-powered fuzzing, which combines generative AI with domain-specific fine-tuning to produce context-aware inputs;and (2) neurosymbolic integration, which merges the precision of symbolic execution with the scalability of neural networks to tackle path explosion. By synthesizing these insights, this survey not only clarifies the state-of-the-art but also outlines a roadmap for developing robust, explainable, and widely applicable intelligent fuzzers. The future of CGF lies in hybrid models that integrate data-driven learning with formal methods, paving the way for autonomous vulnerability discovery in an era of increasingly c

关键词： Code coverage Deep learning Greybox fuzzing Large language models Software vulnerability

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：