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30th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2025

作者： Chen, Wei Zhang, Zhi Zhang, Xin Shen, Qingni Yarom, Yuval Genkin, Daniel Yan, Chen Wang, Zhe Peking University Beijing China University of Western Australia Perth Australia Ruhr University Bochum Bochum Germany Georgia Institute of Technology Atlanta United States Sklp Institute of Computing Technology Chinese Academy of Sciences Beijing China Zhongguancun Laboratory Beijing China

ISBN: (纸本)9798400710797

Hardware-assisted virtualization is a key enabler of the modern cloud. It decouples virtual machine execution from the hardware it runs on, allowing increased flexibility through services such as dynamic hardware provisioning and live migration. Underlying this flexibility is the security promise that guest virtual machines are isolated from each other. However, due to the level of sharing between VMs, hardware vulnerabilities present a serious threat to this usage. One such vulnerability is Rowhammer, which allows attackers to modify the contents of memory to which they have no access. While the attack has been known for over a decade, published applications against such environments are limited, compromising only co-resident VMs, but not the hypervisor. Moreover, due to security concerns, a key component enabling their attack has been disabled. Hence, this attack is no longer applicable in a contemporary virtualized environment. In this paper, we examine how Rowhammer can affect virtualized systems. We present HyperHammer, a Rowhammer attack that breaks hypervisor-enforced memory isolation and further compromises the hypervisor. Due to the highly specific system requirements for leveraging Rowhammer bit flips, HyperHammer is demonstrated on a very particular system configuration. Therefore, as demonstrated, HyperHammer is more a proof-of-concept than an immediate threat to computer systems. Nonetheless, our work demonstrates that hardware-assisted virtualization does not fully protect the hypervisor, and that with sufficient engineering a determined attacker might achieve complete hypervisor compromise. © 2025 ACM.

关键词： Virtual environments

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Mitigating Algorithmic Bias in Multiclass CNN Classifications Using Causal Modeling

arXiv

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arXiv 2025年

作者： Byun, Min Sik Hui, Wendy Wan Yee Lau, Wai Kwong InfoComm Custer Singapore Institute of Technology Singapore Sch. of Physics Mathematics and Computing University of Western Australia Australia

This study describes a procedure for applying causal modeling to detect and mitigate algorithmic bias in a multiclass classification problem. The dataset was derived from the FairFace dataset, supplemented with emotional labels generated by the DeepFace pre-trained model. A custom Convolutional Neural Network (CNN) was developed, consisting of four convolutional blocks, followed by fully connected layers and dropout layers to mitigate overfitting. Gender bias was identified in the CNN model’s classifications: Females were more likely to be classified as "happy" or "sad," while males were more likely to be classified as "neutral." To address this, the one-vs-all (OvA) technique was applied. A causal model was constructed for each emotion class to adjust the CNN model’s predicted class probabilities. The adjusted probabilities for the various classes were then aggregated by selecting the class with the highest probability. The resulting debiased classifications demonstrated enhanced gender fairness across all classes, with negligible impact—or even a slight improvement—on overall accuracy. This study highlights that algorithmic fairness and accuracy are not necessarily tradeoffs. All data and code for this study are publicly available for download. © 2025, CC BY-NC-ND.

关键词： Convolutional neural networks

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WOMBAT v2.S: A Bayesian inversion framework for attributing global CO2 flux components from multiprocess data

arXiv

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arXiv 2025年

作者： Jacobson, Josh Bertolacci, Michael Zammit-Mangion, Andrew Schuh, Andrew Cressie, Noel School of Mathematics and Applied Statistics University of Wollongong Australia School of Physics Mathematics and Computing University of Western Australia Australia Colorado State University United States Jet Propulsion Laboratory California Institute of Technology United States

Contributions from photosynthesis and other natural components of the carbon cycle present the largest uncertainties in our understanding of carbon dioxide (CO2) sources and sinks. While the global spatiotemporal distribution of the net flux (the sum of all contributions) can be inferred from atmospheric CO2 concentrations through flux inversion, attributing the net flux to its individual components remains challenging. The advent of solar-induced fluorescence (SIF) satellite observations provides an opportunity to isolate natural components by anchoring gross primary productivity (GPP), the photosynthetic component of the net flux. Here, we introduce a novel statistical flux-inversion framework that simultaneously assimilates observations of SIF and CO2 concentration, extending WOMBAT v2.0 (WOllongong Methodology for Bayesian Assimilation of Trace-gases, version 2.0) with a hierarchical model of spatiotemporal dependence between GPP and SIF processes. We call the new framework WOMBAT v2.S, and we apply it to SIF and CO2 data from NASA’s Orbiting Carbon Observatory-2 (OCO-2) satellite and other instruments to estimate natural fluxes over the globe during a recent six-year period. In a simulation experiment that matches OCO-2’s retrieval characteristics, the inclusion of SIF improves accuracy and uncertainty quantification of component flux estimates. Comparing estimates from WOMBAT v2.S, v2.0, and the independent FLUXCOM initiative, we observe that linking GPP to SIF has little effect on net flux, as expected, but leads to spatial redistribution and more realistic seasonal structure in natural flux components. © 2025, CC BY.

关键词： NASA

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Text-Driven Video Style Transfer with State-Space Models: Extending StyleMamba for Temporal Coherence

arXiv

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arXiv 2025年

作者： Li, Chao Park, Minsu Rossi, Cristina Li, Zhuang Dept. of Computer Science Eastern Asia Institute of Technology Beijing China AI Research Center Seoul National Technical Labs Seoul Korea Republic of School of Computing University of South Europe Rome Italy Department of Data Science Western Frontier University CA United States

StyleMamba has recently demonstrated efficient text-driven image style transfer by leveraging state-space models (SSMs) and masked directional losses. In this paper, we extend the StyleMamba framework to handle video sequences. We propose new temporal modules, including a Video State-Space Fusion Module to model inter-frame dependencies and a novel Temporal Masked Directional Loss that ensures style consistency while addressing scene changes and partial occlusions. Additionally, we introduce a Temporal Second-Order Loss to suppress abrupt style variations across consecutive frames. Our experiments on DAVIS and UCF101 show that the proposed approach outperforms competing methods in terms of style consistency, smoothness, and computational efficiency. We believe our new framework paves the way for real-time text-driven video stylization with state-of-the-art perceptual results. Copyright © 2025, The Authors. All rights reserved.

关键词： Video recording

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Towards sustainable sand resource management - Best governance practices and alternatives to river sand in India

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Environmental Science and Pollution Research 2025年 1-28页

作者： Bhatawdekar, Ramesh Murlidhar Mohamad, Edy Tonnizam Singh, Trilok Nath Chengong, Dato Hock Soon Kainthola, Ashutosh Khandelwal, Manoj Chihi, Feten Rathinasamy, Vynotdni Arthur, Clement Kweku Deshpande, Anand Ravi Nigam, Sanjay Kwon, Sangki Ralegaonkar, Rahul Azad, Md Alquamar Universiti Teknologi Malaysia Johor Bahru Skudai Malaysia Deparment of Mining Engineering Indian Institute of Technology Kharagpur India Indian Institute of Technology Bihar Patna India Malaysia Quarry Association Selangor Kuala Lumpur Malaysia Geoengineering & Computing Laboratory Department of Geology Banaras Hindu University Varanasi India Institute of Innovation Science and Sustainability Federation University Australia BallaratVIC3350 Australia Faculty of Civil Engineering Budapest University of Technology and Economics Budapest Hungary School of Civil Engineering Universiti Sains Malaysia Penang Malaysia Department of Mining Engineering Faculty of Mining and Minerals Technology University of Mines and Technology Western Region Tarkwa Ghana SURU09 Business Services Thane India Department of Energy Resources Engineering Inha University Incheon Korea Republic of Department of Civil Engineering Visvesvaraya National Institute of Technology Nagpur India

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VULNERABILITY OF COMMUNICATION-NETWORKS

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NETWORKS 1984年第1期14卷 141-146页

作者： CACCETTA, L School of Mathematics and Computing Western Australian Institute of Technology Bentley 6102 Western Australia

AbstractBoesch, Harary, and Kabell recently introduced two measures of network vulnerability. They defined the persistence (edge persistence) of a graph as the minimum number of vertices (edges) whose deletion increases the diameter. In their paper they posed questions relating the existence of graphs with a prescribed number of edges, number of vertices, diameter, and persistence (edge persistence). In this paper we consider this extremal problem.

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EVALUATION OF A CAL PACKAGE FOR MODELING

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COMPUTERS & EDUCATION 1984年第1期8卷 69-76页

作者： HARTLEY, RJ Computing Centre Western Australian Institute of Technology Kent Street Bentley Western Australia

This paper describes some work done in evaluating a computer package called MODL, for development of mathematical models. The package is described briefly with an example of typical graphical output and the inputs required (i.e. lines typed) to produce such a model. After a study of student use of the package, attention is focused on the way a lecturer used it. Simulation programs have been in use in the classroom for some time. MODL compares with these pre-written simulations as an individual trek through the Himalayas would relate to a pre-planned package tour through India. In one the tourist is taken through selected experiences, mostly on a well beaten path. In the other he is entirely free to direct his own affairs, which implies almost no limit to what can be seen and done, though there may be traps for the unwary. MODL may well open doors for teachers, and even the students, who wish to experiment with models in their own discipline, without waiting for programmers and mathematicians to develop simulations. Some teachers could be waiting for the opportunity to exercise their creativity, providing it proves feasible for them to build models with the package. Modelling, as distinct from using a model, is such a new, though potentially important area, that we must not prejudge it.

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Generative AI for Lyapunov Optimization Theory in UAV-based Low-Altitude Economy Networking

arXiv

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arXiv 2025年

作者： Liu, Zhang Niyato, Dusit Wang, Jiacheng Sun, Geng Huang, Lianfen Gao, Zhibin Wang, Xianbin Department of Informatics and Communication Engineering Xiamen University Fujian361102 China College of Computing and Data Science Nanyang Technological University Singapore College of Computer Science and Technology Jilin University Changchun130012 China Navigation Institute Jimei University Fujian Xiamen361021 China Department of Electrical and Computer Engineering Western University LondonONN6A 5B9 Canada

Lyapunov optimization theory has recently emerged as a powerful mathematical framework for solving complex stochastic optimization problems by transforming long-term objectives into a sequence of real-time short-term decisions while ensuring system stability. This theory is particularly valuable in unmanned aerial vehicle (UAV)-based low-altitude economy (LAE) networking scenarios, where it could effectively address inherent challenges of dynamic network conditions, multiple optimization objectives, and stability requirements. Recently, generative artificial intelligence (GenAI) has garnered significant attention for its unprecedented capability to generate diverse digital content. Extending beyond content generation, in this paper, we propose a framework integrating generative diffusion models with reinforcement learning to address Lyapunov optimization problems in UAV-based LAE networking. We begin by introducing the fundamentals of Lyapunov optimization theory and analyzing the limitations of both conventional methods and traditional AI-enabled approaches. We then examine various GenAI models and comprehensively analyze their potential contributions to Lyapunov optimization. Subsequently, we develop a Lyapunov-guided generative diffusion model-based reinforcement learning framework and validate its effectiveness through a UAV-based LAE networking case study. Finally, we outline several directions for future research. Copyright © 2025, The Authors. All rights reserved.

关键词： Stochastic systems

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FTA-FTL: A Fine-Tuned Aggregation Federated Transfer Learning Scheme for Lithology Microscopic Image Classification

arXiv

引用

arXiv 2025年

作者： RahimiZadeh, Keyvan Taheri, Ahmad Baumbach, Jan Makarian, Esmael Dehghani, Abbas Ravaei, Bahman Javadi, Bahman Beheshti, Amin School of Computing Macquarie University SydneyNSW2109 Australia Institute of Computational Systems Biology University of Hamburg Notkestrasse 9 Hamburg22607 Germany Department of Mining Engineering Sahand University of Technology Tabriz513351996 Iran Department of Computer Engineering School of Engineering Yasouj University Yasouj*** Iran School of Computer Data and Mathematical Sciences Western Sydney University NSW2751 Australia

Lithology discrimination is a crucial activity in characterizing oil reservoirs, and processing lithology microscopic images is an essential technique for investigating fossils and minerals and geological assessment of shale oil exploration. In this way, Deep Learning (DL) technique is a powerful approach for building robust classifier models. However, there is still a considerable challenge to collect and produce a large dataset. Transfer-learning and data augmentation techniques have emerged as popular approaches to tackle this problem. Furthermore, due to different reasons, especially data privacy, individuals, organizations, and industry companies often are not willing to share their sensitive data and information. Federated Learning (FL) has emerged to train a highly accurate central model across multiple decentralized edge servers without transferring sensitive data, preserving sensitive data, and enhancing security. This study involves two phases;the first phase is to conduct Lithology microscopic image classification on a small dataset using transfer learning. In doing so, various pre-trained DL model architectures are comprehensively compared for the classification task. In the second phase, we formulated the classification task to a Federated Transfer Learning (FTL) scheme and proposed a Fine-Tuned Aggregation strategy for Federated Learning (FTA-FTL). In order to perform a comprehensive experimental study, several metrics such as accuracy, f1 score, precision, specificity, sensitivity (recall), and confusion matrix are taken into account. The results are in excellent agreement and confirm the efficiency of the proposed scheme, and show that the proposed FTA-FTL algorithm is capable enough to achieve approximately the same results obtained by the centralized implementation for Lithology microscopic images classification task. © 2025, CC BY.

关键词： Sensitive data

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Stability criteria for stochastic singular systems with time-varying delays and uncertain parameters

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Science China(Information Sciences) 2018年第11期61卷 256-258页

作者： Shuanyun XING Feiqi DENG Weixing ZHENG College of Science Shenyang Jianzhu University Systems Engineering Institute South China University of Technology School of Computing Engineering and Mathematics Western Sydney University

Dear editor,It is well known that singular systems can better describe physical systems and they are widely used in chemical processes, microelectronic circuits, economic systems, and network control systems [1]. We can effectively model singular systems as stochastic singular systems when the structure of singular systems is unexpectedly altered by the environment. Several meaningful contributions were reported in [2–4].

关键词： PTA ATP Stability criteria for stochastic singular systems with time-varying delays and uncertain parameters

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