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International Conference on High Performance computing

作者： Abrar Hossain Abdel-Hameed A. Badawy Mohammad A. Islam Tapasya Patki Kishwar Ahmed Department of Electrical Engineering and Computer Science The University of Toledo Department of Electrical and Computer Engineering New Mexico State University Department of Computer Science and Engineering The University of Texas at Arlington Lawrence Livermore National Laboratory Center for Applied Scientific Computing

ISBN: (数字)9798331509095

ISBN: (纸本)9798331509101

The growing necessity for enhanced processing capabilities in edge devices with limited resources has led us to develop effective methods for improving high-performance computing (HPC) applications. In this paper, we introduce LASP (Lightweight Autotuning of scientific Application Parameters), a novel strategy designed to address the parameter search space challenge in edge devices. Our strategy employs a multi-armed bandit (MAB) technique focused on online exploration and exploitation. Notably, LASP takes a dynamic approach, adapting seamlessly to changing environments. We tested LASP with four HPC applications: Lulesh, Kripke, Clomp, and Hypre. Its lightweight nature makes it particularly well-suited for resource-constrained edge devices. By employing the MAB framework to efficiently navigate the search space, we achieved significant performance improvements while adhering to the stringent computational limits of edge devices. Our experimental results demonstrate the effectiveness of LASP in optimizing parameter search on edge devices.

关键词： Performance evaluation Analytical models Navigation High performance computing Computational modeling Data models Computational efficiency

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SQLstateGuard: statement-Level SQL Injection Defense Based on Learning-Driven Middleware 15

SQLStateGuard: Statement-Level SQL Injection Defense Based o...

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15th Annual ACM Symposium on Cloud computing, SoCC 2024

作者： Liu, Xin Huang, Yuanyuan Wang, Tianyi Li, Song Niu, Weina Shen, Jun Zhou, Qingguo Zhou, Xiaokang School of Information Science and Engineering Lanzhou University Gansu Lanzhou China The State Key Laboratory of Blockchain and Data Security Zhejiang University Zhejiang Hangzhou China School of Computer Science and Engineering University of Electronic Science and Technology of China Sichuan Chengdu China School of Computing and Information Technology University of Wollongong WollongongNSW Australia Kansai University Osaka Suita Japan

ISBN: (纸本)9798400712869

SQL injection is a significant and persistent threat to web services. Most existing protections against SQL injections rely on traffic-level anomaly detection, which often results in high false-positive rates and can be easily bypassed by attackers. This paper introduces SQLstateGuard, the world's first middleware-driven statement-level SQL injection defense approach, to address these issues. The SQLstateGuard uses a custom SQL middleware based on the idea of Runtime Application Self-Protection to capture raw SQL statements. These statements are then analyzed by SQLSG-Net, a database-oriented detection network based on gated linear units. If SQLSG-Net detects malicious SQL statements, the SQL middleware will block them. Experiments show that the detection accuracy of SQLstateGuard exceeds 99%, outperforming existing approaches, and it can identify the type of a specific SQL injection. Additionally, SQLstateGuard has no fingerprint and does not respond to SQL syntax errors, making it more challenging for attackers to gather information. This paper also presents a novel dataset generation process for SQLstateGuard and shares two statement-level SQL injection datasets with the research community, including over 145,000 malicious SQL statements categorized by the type of SQL injection. © 2024 ACM.

关键词： Middleware

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Microstructural impacts on ionic conductivity of oxide solid electrolytes from a combined atomistic-mesoscale approach

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npj Computational Materials 2021年第1期7卷 1959-1973页

作者： Tae Wook Heo Andrew Grieder Bo Wang Marissa Wood Tim Hsu Sneha A.Akhade Liwen F.Wan Long-Qing Chen Nicole Adelstein Brandon C.Wood Materials Science Division Lawrence Livermore National LaboratoryLivermoreCA 94550USA Department of Chemistry and Biochemistry San Francisco State UniversitySan FranciscoCA 94132USA Department of Materials Science and Engineering The Pennsylvania State UniversityUniversity ParkPA 16802USA Center for Applied Scientific Computing Lawrence Livermore National LaboratoryLivermoreCA 94550USA

Although multiple oxide-based solid electrolyte materials with intrinsically high ionic conductivities have emerged,practical processing and synthesis routes introduce grain boundaries and other interfaces that can perturb primary conduction *** directly probe these effects,we demonstrate an efficient and general mesoscopic computational method capable of predicting effective ionic conductivity through a complex polycrystalline oxide-based solid electrolyte microstructure without relying on simplified equivalent circuit *** parameterize the framework for Li_(7-x)La_(3)Zr_(2)0_(12)(LLZO)gamet solid electrolyte by combining synthetic microstructures from phase-field simulations with diffusivities from molecular dynamics simulations of ordered and disordered *** designed simulations reveal an interdependence between atomistic and mesoscopic microstructural impacts on the effective ionic conductivity of polycrystalline LLZO,quantified by newly defined metrics that characterize the com plex ionic transport *** results provide fundamental understanding of the physical origins of the reported variability in ionic conductivities based on an extensive analysis of literature data,while simultaneously outlining practical design guidance for achieving desired ionic transport properties based on conditions for which sensitivity to microstructural features is *** implications of our results are discussed,including a possible connection between ion conduction behavior and dendrite formation.

关键词： microstructure solid conductivity

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Modelization and analysis of dynamic heterogeneous redundant system

Modelization and analysis of dynamic heterogeneous redundant...

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作者： Wang, Wei Li, Guangsong Gai, Keke Tang, Yazhe Yang, Benchao Si, Xueming State Key Laboratory of Mathematical Engineering and Advanced Computing Information Engineering University Zhengzhou China School of Computer Science and Technology Beijing Institute of Technology Beijing China School of Computer Science and Technology Xi'an Jiaotong University Xi'an China Shanghai Key Laboratory of Data Science Fudan University Shanghai China

With the development and popularization of Internet technology, network security has become the focus of attention. Vulnerabilities and back doors are regarded as two of the main reasons of network security problems. Dynamic heterogeneous redundant (DHR) architecture is a typical framework of cyberspace mimic defense. It can make use of untrusted hardware and software components to construct a high reliable and high security information system. In this article, a mathematical model is set up for the DHR architecture, and the system security is characterized by vulnerability consistency rate and success rate of system attack. The antiattack ability of the DHR system is analyzed using the mathematical model. © 2020 John Wiley & Sons, Ltd.

关键词： Network security

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FIRE: a dataset for feedback integration and refinement evaluation of multimodal models 24

FIRE: a dataset for feedback integration and refinement eval...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Pengxiang Li Zhi Gao Bofei Zhang Tao Yuan Yuwei Wu Mehrtash Harandi Yunde Jia Song-Chun Zhu Qing Li Beijing Key Laboratory of Intelligent Information Technology School of Computer Science & Technology Beijing Institute of Technology and State Key Laboratory of General Artificial Intelligence BIGAI State Key Laboratory of General Artificial Intelligence BIGAI and State Key Laboratory of General Artificial Intelligence Peking University State Key Laboratory of General Artificial Intelligence BIGAI Beijing Key Laboratory of Intelligent Information Technology School of Computer Science & Technology Beijing Institute of Technology and Guangdong Laboratory of Machine Perception and Intelligent Computing Shenzhen MSU-BIT University Department of Electrical and Computer System Engineering Monash University Guangdong Laboratory of Machine Perception and Intelligent Computing Shenzhen MSU-BIT University and Beijing Key Laboratory of Intelligent Information Technology School of Computer Science & Technology Beijing Institute of Technology State Key Laboratory of General Artificial Intelligence BIGAI and State Key Laboratory of General Artificial Intelligence Peking University and Department of Automation Tsinghua University

ISBN: (纸本)9798331314385

Vision language models (VLMs) have achieved impressive progress in diverse applications, becoming a prevalent research direction. In this paper, we build FIRE, a feedback-refinement dataset, consisting of 1.1M multi-turn conversations that are derived from 27 source datasets, empowering VLMs to spontaneously refine their responses based on user feedback across diverse tasks. To scale up the data collection, FIRE is collected in two components: FIRE-100K and FIRE-1M, where FIRE-100K is generated by GPT-4V, and FIRE-1M is freely generated via models trained on FIRE-100K. Then, we build FIRE-Bench, a benchmark to comprehensively evaluate the feedback-refining capability of VLMs, which contains 11K feedback-refinement conversations as the test data, two evaluation settings, and a model to provide feedback for VLMs. We develop the FIRE-LLaVA model by fine-tuning LLaVA on FIRE-100K and FIRE-1M, which shows remarkable feedback-refining capability on FIRE-Bench and outperforms untrained VLMs by 50%, making more efficient user-agent interactions and underscoring the significance of the FIRE dataset.

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SUMI-IFL: An Information-Theoretic Framework for Image Forgery Localization with Sufficiency and Minimality Constraints 39

SUMI-IFL: An Information-Theoretic Framework for Image Forge...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Sheng, Ziqi Lu, Wei Luo, Xiangyang Zhou, Jiantao Cao, Xiaochun School of Computer Science and Engineering MoE Key Laboratory of Information Technology Guangdong Province Key Laboratory of Information Security Technology Sun Yat-sen University China State Key Laboratory of Mathematical Engineering and Advanced Computing China State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science University of Macau China School of Cyber Science and Technology Shenzhen Campus of Sun Yat-sen University China

ISBN: (纸本)157735897X

Image forgery localization (IFL) is a crucial technique for preventing tampered image misuse and protecting social safety. However, due to the rapid development of image tampering technologies, extracting more comprehensive and accurate forgery clues remains an urgent challenge. To address these challenges, we introduce a novel information-theoretic IFL framework named SUMI-IFL that imposes sufficiency-view and minimality-view constraints on forgery feature representation. First, grounded in the theoretical analysis of mutual information, the sufficiency-view constraint is enforced on the feature extraction network to ensure that the latent forgery feature contains comprehensive forgery clues. Considering that forgery clues obtained from a single aspect alone may be incomplete, we construct the latent forgery feature by integrating several individual forgery features from multiple perspectives. Second, based on the information bottleneck, the minimality-view constraint is imposed on the feature reasoning network to achieve an accurate and concise forgery feature representation that counters the interference of task-unrelated features. Extensive experiments show the superior performance of SUMI-IFL to existing state-of-the-art methods, not only on in-dataset comparisons but also on cross-dataset comparisons. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Correlation theory

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Minimalist optical system image restoration based on deep attention Wiener network 14

Minimalist optical system image restoration based on deep at...

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Optical Design and Testing XIV 2024

作者： Wang, Ziyang Zhou, Yan Shi, Runzhou Bai, Jian College of Optical Science and Engineering Zhejiang University Hangzhou310027 China ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang University Hangzhou311215 China State Key Laboratory of Extreme Photonics and Instrumentation Zhejiang University Hangzhou310027 China Tianjin Jinhang Institute of Technical Physics Tianjin300308 China

ISBN: (纸本)9781510682023

Aberrations in minimalist optical imaging systems pose significant challenges to achieving high-quality imaging. Traditional Wiener filtering methods, though effective, are constrained by their dependency on precise blur kernels and noise models, and their performance degrades with spatial variations in these parameters. On the other hand, deep learning techniques often fail to fully utilize prior information about aberrations and suffer from limited interpretability. To address these limitations, we propose a novel deep attention Wiener network (DAWN). This approach integrates deep learning with Wiener filtering to enhance image restoration while reducing computational complexity. By using optical simulations to generate blur kernels and noise models that closely mirror real conditions, our method fits distinct point spread function (PSF) for different fields of view (FOV), creating a robust dataset for training. The DAWN model first employs a convolutional neural network (CNN) for feature extraction, followed by sequential Wiener filtering applied in half FOV block length steps. To further improve image restoration, a nonlinear activation free net (NAFNet) is used to correct discrepancies introduced by simulated blur kernels and noise models. The model is trained end-to-end, and to streamline the process, Wiener filtering is confined to 4 × 4 FOV blocks. A weighting matrix within the Wiener filtering layer mitigates seams between adjacent blocks. Simulation and experiment results demonstrate that our approach outperforms the mainstream image restoration methods. © 2024 SPIE.

关键词： Wiener filtering

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Encoding Temporal Change of Longitudinal EBV DNA for Dynamic Risk Prediction of Nasopharyngeal Carcinoma 7

Encoding Temporal Change of Longitudinal EBV DNA for Dynamic...

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7th International Conference on Biological Information and Biomedical engineering, BIBE 2024

作者： Yang, Fangfang Zhen, Zicheng Lin, Li Liu, Yuyu Gao, Rui Zhang, Taoyu Lu, Lijun Lv, Wenbing School of Information Yunnan University Yunnan Kunming650504 China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Yunnan Kunming650504 China Department of Radiation Oncology Sun Yat-sen University Cancer Center State Key Laboratory of Oncology in South China Collaborative Innovation Center for Cancer Medicine Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy Guangzhou510060 China School of Software Yunnan University Yunnan Kunming650504 China School of Biomedical Engineering Southern Medical University 1023 Shatai Road Guangzhou510515 China

ISBN: (纸本)9783800762910

—To accurately predict the risk of recurrence and metastasis of nasopharyngeal carcinoma (NPC) patients, an image-encoded risk prediction model was proposed. 752 patients (training vs. testing: 527 vs. 225) were retrospectively collected, and the plasma EBV DNA copies were tested 13 times during treatment. Based on 13 times plasma EBV DNA copies, three kinds of image encoding methods were employed to characterize the linear and nonlinear dynamic change of longitudinal EBV DNA, i.e. Gramian Angular Summation Field (GASF), Gramian Angular Difference Field (GADF), and Recurrence Plot (RP). The Cox proportional hazard regression model was constructed by incorporating both image and clinical features as covariates to determine the risk factors and prediction models for disease-free survival (DFS). On the test set, the proposed model combining image and clinical features achieved C-index and AUC of 0.777 and 0.776, respectively outperforming the model relying solely on clinical features (C-index = 0.667, AUC = 0.675). In conclusion, the dynamic risk prediction model with image encoding can monitor changes in plasma EBV DNA copies during treatment, aiding doctors in assessing whole-body tumor burden, accurately predicting the dynamic risk of recurrence and metastasis, and planning individualized treatments in NPC patients. © VDE VERLAG GMBH.

关键词： Gene encoding

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Reinforcement Learning-Based Optimal Control for Continuous-Time Quantized Systems via Adaptive Dynamic Programming

Reinforcement Learning-Based Optimal Control for Continuous-...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Omar Qasem Weinan Gao Omar R. Daoud Electrical and Computer Engineering Department School of Engineering and Computing American International University Al-Jahra Kuwait State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang Lianning China

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

Ahstract- This paper presents a comprehensive investigation into the stability analysis and design conditions for quantizers to ensure the closed-loop stability of continuous-time linear quantized systems, under the conditions derived by the small-gain theorem. The study begins by deriving explicit bounds on the quantizer parameters required for maintaining system stability. Building on this foundation, an optimal controller is designed using the linear quadratic regulator (LQR) framework, providing an efficient data-driven control strategy. To further enhance the system's performance, an adaptive dynamic programming (ADP) algorithm, referred to as the hybrid iteration (HI) method, is developed. This algorithm effectively learns the optimal control policy by leveraging the trajectories of the quantized states and inputs, thereby addressing the challenges posed by quantization constraints. The proposed HI approach combines the advantages of adaptive learning and optimization, making it well-suited for continuous-time systems with limited information. The simulation results confirm that the ADP approach with the provided conditions not only stabilizes the quantized system but also achieves optimal control performance under the specified quantization conditions. This study offers valuable insights and a robust methodological framework for addressing stability and control challenges, with insights to be expanded to continuous-time nonlinear quantized systems, with potential applications in various engineering domains, such as networked systems, robotics and autonomous systems.

关键词： Quantization (signal) Adaptive systems Regulators Simulation Heuristic algorithms Optimal control Stability analysis Dynamic programming Trajectory Thermal stability

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Disclosing the intrinsic nature of efficient removal of antibiotics in N/S dual-doped porous carbon-based materials: The manipulation of internal electric field

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Chemosphere 2024年 355卷 141788页

作者： Wang, Tao He, Yujie Zhao, Zhongjing Zhao, Zhonghua Guo, Xiaochun Lu, Shaoyong Zhang, Lu State Key Laboratory of Lake Science and Environment Nanjing Institute of Geography and Limnology Chinese Academy of Sciences Nanjing210008 China Environmental and Biological Engineering Nanjing University of Science and Technology Nanjing210094 China National Engineering Laboratory for Lake Pollution Control and Ecological Restoration State Environment Protection Key Laboratory for Lake Pollution Control State Environmental Protection Scientific Observation and Research Station for Lake Dongtinghu-SEPSORSLD State Key Laboratory of Environmental Criteria and Risk Assessment Chinese Research Academy of Environmental Sciences Beijing100012 China

N/S co-doping has emerged as a prevailing strategy for carbon-based adsorbents to facilitate the antibiotic removal efficiency. Nevertheless, the underlying interplay among N, S, and their adjacent vacancy defects remains overlooked. Herein, we present a novel in situ strategy for fabricating pyridinic-N dominated and S dual-doped porous carbon adsorbent with rich vacancy defects (VNSC). The experimental results revealed that N (acting as the electron donor) and S (acting as the electron acceptor) form an internal electric field (IEF), with a stronger IEF generated between pyridinic-N and S, while their adjacent vacancy defects activate carbon π electrons, thus enhancing the charge transfer of the IEF. Density functional theory (DFT) calculations further demonstrated that the rich charge transfer in the IEF facilitated the π-π electron donor-acceptor (EDA) interaction between VNSC and tetracycline (TC) as well as norfloxacin (NOR), and thus is the key to adsorption performance of VNSC. Consequently, VNSC exhibited high adsorption capacities toward TC (573.1 mg g−1) and NOR (517.0 mg g−1), and its potential for environmental applications was demonstrated by interference, environmentally relevant concentrations, fixed-bed column, and regeneration tests. This work discloses the natures of adsorption capacity for N/S dual-doped carbon-based materials for antibiotics. © 2024 Elsevier Ltd

关键词： Antibiotics

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