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arXiv 2025年

作者： Nagib, Ahmad M. Abou-Zeid, Hatem Hassanein, Hossam S. School of Computing Queen’s University Canada Department of Electrical and Software Engineering University of Calgary Canada Faculty of Computers and Artificial Intelligence Cairo University Egypt

Deep reinforcement learning (DRL)-based slicing policies have shown significant success in simulated environments but face challenges in physical systems such as open radio access networks (O-RANs) due to simulation-to-reality gaps. These policies often lack safety guarantees to ensure compliance with service level agreements (SLAs), such as the strict latency requirements of immersive applications. As a result, a deployed DRL slicing agent may make resource allocation (RA) decisions that degrade system performance, particularly in previously unseen scenarios. Real-world immersive applications require maintaining SLA constraints throughout deployment to prevent risky DRL exploration. In this paper, we propose SafeSlice to address both the cumulative (trajectory-wise) and instantaneous (state-wise) latency constraints of O-RAN slices. We incorporate the cumulative constraints by designing a sigmoid-based risk-sensitive reward function that reflects the slices’ latency requirements. Moreover, we build a supervised learning cost model as part of a safety layer that projects the slicing agent’s RA actions to the nearest safe actions, fulfilling instantaneous constraints. We conduct an exhaustive experiment that supports multiple services, including real virtual reality (VR) gaming traffic, to investigate the performance of SafeSlice under extreme and changing deployment conditions. SafeSlice achieves reductions of up to 83.23% in average cumulative latency, 93.24% in instantaneous latency violations, and 22.13% in resource consumption compared to the baselines. The results also indicate SafeSlice’s robustness to changing the threshold configurations of latency constraints, a vital deployment scenario that will be realized by the O-RAN paradigm to empower mobile network operators (MNOs). Copyright © 2025, The Authors. All rights reserved.

关键词： Deep reinforcement learning

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The Role of AI in Predictive UX Shaping the Future of Metaverse Interactions

The Role of AI in Predictive UX Shaping the Future of Metave...

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Computational Intelligence Approaches and Applications (ICCIAA), International Conference on

作者： Nedal Nwasra Khalil Omar Zahid Hussain Qaisar Software Engineering Department University of Petra Amman Jordan Faculty of Computing & Emerging Technologies Multan Pakistan Computer Science Department University of Petra Amman Jordan

ISBN: (数字)9798331523657

ISBN: (纸本)9798331523664

The Metaverse is defined as a collectively shared, persistent, and contextualized virtual space that will drive next-generation digital interaction facilitated by enhanced extended reality (XR) and edge computing. One of the major challenges within this development area is the proper anticipation and fulfillment of user context needs, preferences, and intentions in real-time. This paper proposes the concept of Predictive User Experience through AI for a turn to solve this challenge. With enabled predictive analytics, machine learning, and real-time data processing, the proposed AI-based predictive UX model dynamically adjusts metaverse interface features, content delivery, and modes of interaction to enhance immersion, all while maximizing user satisfaction. In this paper, we discuss AI's potential for explanatory mechanics in predictive UX and how it shapes the future of metaverse interactions. We propose a conceptual framework that describes how data collection, data processing, and adaptive interface design can be integrated within a feedback-driven architecture that seamlessly predicts and adjusts to user requirements. In this paper, we present a research methodology that integrates qualitative and technical approaches-from data modeling and architecture design up to scenario-based assessments-to validate our UX framework's predictiveness. Hence, we proceed with a use case that exemplifies the applicability of AI-based predictive UX systems for ensuring user presence and interaction consistency within a metaverse educational scenario. The discussion synthesizes and finally concludes the most pertinent findings relevant to user engagement and personalization regarding privacy and ethical considerations without compromising how these technologies can be safely and effectively scaled. We conclude our paper with the opinion that XR interactions driven by AI predictive UX mark a milestone in how applications are created, not just for entertainment and gaming but also

关键词： Adaptation models Metaverse Extended reality Machine learning Computer architecture Predictive models Data collection Data models User experience Real-time systems

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CMCache: An Adaptive Cross-Level Data Placement Method for Multi-Level Cache

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IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 2025年

作者： Zeng, Zhaoyang Tan, Yujuan Ma, Zhulin Li, Jiali Zhao, Sanle Liu, Duo Chen, Xianzhang Ren, Ao Chongqing University College of Computer Science Chongqing400044 China Chongqing University Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education Chongqing400044 China Chongqing Universityof Posts and Telecommunications College of Software Engineering China Chongqing University College of Big Data and Software Engineering Chongqing China

Multi-level cache systems enhance I/O performance by optimizing data placement across various cache levels from a global perspective. However, existing methods often struggle to place data at the optimal cache level promptly due to their reliance on historical access patterns and inflexible placement strategies. These methods face two main challenges: (1) For already cached data with sufficient access history, existing approaches only optimize movement between adjacent cache levels, potentially delaying data arrival at its globally optimal cache level and leading to unnecessary bandwidth consumption and increased latency. (2) For newly entered data without access history, current methods cannot accurately predict their future hotness and simply place them at a fixed cache level (i.e. first or last level), overlooking future accesses of new data and potentially resulting in high cache miss rates or cache pollution. To address these issues, we propose CMCache, an adaptive cross-level data placement method for multi-level cache. CMCache applies distinct placement strategies for cached and new data to reach the optimal level timely, considering their different characteristics. It also logically divides cache space into two sections to manage cached and new data separately, dynamically adjusting section sizes based on access patterns. This approach significantly improves data placement efficiency, achieving up to an 89% reduction in miss rates and a 79% decrease in average response times compared to existing methods. © 2025 IEEE.

关键词： Cache memory

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Robust and digital hyper-polarization protocol of nuclear spins via magic sequential sequence

arXiv

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arXiv 2025年

作者： Li, Haiyang Liao, Hao Wang, Ping Faculty of Arts and Sciences Beijing Normal University Zhuhai519087 China National Engineering Laboratory on Big Data System Computing Technology Guangdong Province Engineering Center of China-made High Performance Data Computing System College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China

Hyper-polarization of nuclear spins is crucial for advancing nuclear magnetic resonance (NMR) and quantum information technologies, as nuclear spins typically exhibit extremely low polarization at room temperature due to their small gyro-magnetic ratios. A promising approach to achieving high nuclear spin polarization is transferring the polarization of electron to nuclear spin. The nitrogen-vacancy (NV) center in diamond has emerged as a highly effective medium for this purpose, and various hyper-polarization protocols have been developed. Among these, the pulsed polarization (PulsePol) method has been extensively studied due to its robustness against static energy shifts of the electron spin. In this study, we introduce a sequential polarization protocol and identify a series of magic and digital sequences for hyper-polarizing nuclear spins. Notably, we demonstrate that some of these magic sequences exhibit significantly greater robustness compared to the PulsePol protocol in the presence of finite half π pulse duration of the protocol. This enhanced robustness positions our protocol as a more suitable candidate for hyper-polarizing nuclear spins species with large gyromagnetic ratios and also ensures better compatibility with high-efficiency readout techniques at high magnetic fields. Additionally, the generality of our protocol allows for its direct application to other solid-state quantum systems beyond the NV center. © 2025, CC BY.

关键词： Chemical shift

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Faceswap Finder: A Fusion-Based Deepfake Detection Technique

Faceswap Finder: A Fusion-Based Deepfake Detection Technique

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International Conference on Advancements in Computational Sciences (ICACS)

作者： Nimra Basit Fatima Khalid Qurat Ul Ain Maria Andleeb Department of Software Engineering University of Engineering and Technology Taxila Pakistan Faculty of Computer Sciences and Engineeing GIKI Topi Pakistan Department of Computing Shifa Tameer-e-Millat University PRC Islamabad Pakistan

ISBN: (数字)9798331533038

ISBN: (纸本)9798331533045

The significant improvement in deepfake generation algorithms has made possible the manipulation of visual data. The advancement of GAN technology and tools has made it relatively simple to use source and target photos and build realistic deepfakes. The challenges associated with deepfakes include political defamation, impersonation, misinformation, and cyberstalking. The generation of deepfakes through faceswap approach hinders the detection oftentimes as it spans numerous artifacts – illumination, facial skin tones, and other conditions. Existing techniques do not employ robust mechanisms to detect such deepfakes either due to computational inefficiency or focusing on a few parameters for decision-making. To counteract these dangers, a robust deepfake detection model must be developed and implemented. This paper proposes Efficient-Fused Net (EF-Net) - a transfer learning approach to two EfficientNet-B5 models with partial freezing between its layers that can differentiate between real and fake images generated from faceswap implementation. We evaluated our model’s performance using the challenging deepfake subset of the extensive and varied FaceForensics++ and DFDC-Preview datasets. The proposed method outperforms state of the art methods in the detection of faceswap deepfakes, surpassing the performance by $89.19 \%$ accuracy on DFDC-Preview and $\mathbf{9 7 . 7 0 \%}$ of Deepfakes subset of FaceForensics++.

关键词： Deepfakes Visualization Computational modeling Transfer learning Decision making Lighting Focusing Skin Robustness Resilience

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Comparative Analysis of Differential Privacy Implementations on Synthetic Data

Comparative Analysis of Differential Privacy Implementations...

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IEEE Annual computing and Communication Workshop and Conference (CCWC)

作者： Huwida E. Said Qusay H. Mahmoud Mandeep Goyal Faiza Hashim Department of Computing and Applied Technolgy College of Technological Innovation Zayed University Dubai UAE Department of Electrical Computer and Software Engineering Ontario Tech University Oshawa ON Canada Department of Computer Science and Software Engineering College of Information Technology UAE University AI-Ain UAE

ISBN: (数字)9798331507695

ISBN: (纸本)9798331507701

Differential privacy offers a promising solution to balance data utility and user privacy. This paper compares two prominent differential privacy tools-PyDP and IBM's diffprivlib-that are applied to a synthetic dataset with medical attributes. We evaluate these tools based on their effectiveness in maintaining data privacy while preserving the statistical integrity of the data. Our results reveal that PyDP provides synthetic data that closely matches real-world data, making it appropriate for tasks requiring accuracy while striking a better balance between data utility and privacy. However, IBM's diffprivlib is more suitable for privacy-critical applications due to its stronger privacy guarantees, but at the cost of increased noise and decreased data utility. This paper contributes to the practical understanding of implementing differential privacy in machine learning and software applications and enhances the tools available for developers in sensitive data environments.

关键词： Differential privacy Costs Accuracy Conferences Noise Machine learning software Synthetic data

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FDC: Feature Dropout Consistency for unsupervised domain adaptation semantic segmentation

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Neural Networks 2025年 189卷 107527页

作者： Rao, Chaoyu Fan, Wanshu Wang, Cong Yang, Xin Wei, Xiaopeng Zhou, Dongsheng National and Local Joint Engineering Laboratory of Computer Aided Design School of Software Engineering Dalian University China Department of Computing The Hong Kong Polytechnic University Hong Kong School of Computer Science and Technology Dalian University of Technology China

In Unsupervised Domain Adaptation Semantic Segmentation (UDASS), while self-training techniques have become one of the most effective methods to date, the absence of target labels makes models susceptible to overfitting. To address this problem, consistency techniques regularize the model by perturbing the target domain and enforcing consistent pixel predictions before and after the perturbation. Consistency techniques are based on the idea that a well-performing model should yield consistent predictions for the target data stream before and after perturbations. In this paper, we introduce the Feature Dropout Consistency (FDC) module, a novel approach that instigates perturbations at the feature level. This is achieved by implementing random feature dropout between the encoder and decoder of the student network. Subsequently, a feature dropout consistency loss is applied to minimize discrepancies in predictions between the perturbed student network and its teacher counterpart. Notably, FDC seamlessly integrates with existing self-training methodologies and, when paired with input perturbation, delves into an even broader perturbation spectrum. Through rigorous experimentation in standard UDA settings — training with synthetic labeled and real unlabeled data — FDC consistently outperforms baseline models, establishing new benchmarks on GTAV → Cityscapes and SYNTHIA → Cityscapes. © 2025

关键词： Semantic Segmentation

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Formal Timing Analysis and Verification of the Interrupt-driven Programs for ISO26262

Formal Timing Analysis and Verification of the Interrupt-dri...

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2025 2nd International Conference on Algorithms, software engineering and Network Security (ASENS)

作者： Qing She He Huang Shenglin Bao Xin Guo National Trusted Embedded Software Engineering Technology Research Center East China Normal University / Shanghai Huayuan Chuangxin Software Co. Ltd China High end Equipment Systems Department Shanghai Huayuan Chuangxin Software Co. Ltd China Basic Software Department East China Institute of Computing Technology China National Trusted Embedded Software Engineering Technology Research Center East China Normal University China

ISBN: (数字)9798331520298

ISBN: (纸本)9798331520304

Safety-critical systems refer to software systems whose operation can affect the safety of people and facilities used in the automotive industry, aerospace, and hospital health care systems. The high level of safety of software in the aforementioned fields has often drawn attention. ISO26262 has been issued for the automotive industry, which defines standards and procedures, including software level, software development standards, and software validation standards to ensure the high level of safety of software. In high-safety automotive software, a real-time safeguard requires the analysis of interrupt-driven programming. Such analysis presents a challenging and complex task because of the uncertainty of interrupts. In ISO26262, the formalized method is suggested to verify the process of software development. To achieve the verification goals defined in ISO26262, we use a formal method instead of traditional verification methods to analyze worst-case execution time. We analyze interrupt-driven programs from the perspective of timeliness and present the Interrupt Control Flow Graph (ICFG), which is used to describe the control flow of interrupt-driven programs. The execution of interrupts may largely increase the number of program states, potentially leading to state explosion, resulting in a sizable ICFG. To solve this problem, we propose an algorithm for reducing the size of ICFG. On the basis of the reduced ICFG, the worst-case execution path can be determined and thus be used to verify whether the program execution time exceeds the expected time and identify the execution path that may cause a timeout problem.

关键词： Industries Uncertainty software algorithms software systems Timing Flow graphs Standards Automotive engineering software development management software engineering

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Improved quantum linear system solver via quantum phase discrimination

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The European Physical Journal Special Topics 2025年 1-11页

作者： Liu, Zihao Li, Guanzhong Li, Lvzhou Institute of Quantum Computing and Software School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Quantum Science Center of Guangdong-Hong Kong-Macao Greater Bay Area (Guangdong) Shenzhen China

The problem of solving linear systems is of great significance in both theory and practice, for which quantum solvers have been shown to provide an exponential speedup over the best-known classical solvers. Recently, a quantum linear system solver has been developed with the state-of-the-art complexity [1], which combines two techniques, namely, discrete adiabatic evolution and eigenstate filtering. However, the parameters of the quantum circuit for eigenstate filtering need to be precomputed classically via the discrete Fourier transform, which introduces additional computational overhead. In this paper, we improve the solver by presenting a new eigenstate filtering process termed quantum phase discrimination in which the circuit parameters are given directly in a concise and analytical form with negligible classical overhead, while maintaining the same quantum complexity.

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Heterogeneous Parallel Key-Insulated Multi-Receiver Signcryption Scheme for IoV

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IEEE Transactions on Information Forensics and Security 2025年 20卷 5123-5137页

作者： Hou, Yingzhe Cao, Yue Xiong, Hu He, Debiao Chi, Chi-Hung Lam, Kwok-Yan Wuhan University School of Cyber Science and Engineering Wuhan430000 China University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu610054 China Nanyang Technological University College of Computing and Data Science 639798 Singapore

The rapid growth of electric vehicle and autonomous vehicle populations has led to explosive expansion of IoV data being transmitted in the wireless communication infrastructure. Advances in IoV technologies also resulted in more complex and dynamic communication protocols/patterns, which are hard for the underlying wireless network to satisfy. Besides, security considerations of IoV communications require that key management must be stringently prohibit global failure mode of key management, meaning that, if a single IoV node compromises its private key, it will not lead to total security failure of the entire IoV network. To address these issues, in this paper, we propose a heterogeneous parallel key-insulated multi-receiver signcryption scheme for IoV (HPKI-MRSC). Firstly, the proposed scheme can realize one-to-many heterogeneous transmission, in which RSUs are deployed on certificateless cryptography (CLC) system, while vehicles are allocated in identity-based cryptography (IBC) system. In this manner, we observe that message transmission efficiency is improved greatly. Secondly, the parallel key-insulated mechanism can employ two helper keys to update private key periodically, and then solve key disclosure problem. Finally, when the number of receiver n is greater than or equal to 3, the proposed scheme has a lower signcryption overhead than other comparative schemes, and thus it is more suitable for IoV. © 2005-2012 IEEE.

关键词： Heterogeneous Internet of Vehicle (IoV) Parallel Key-Insulated Signcryption

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