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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Wenpeng Xing Jie Chen Zaifeng Yang Xin Tong Changting Lin Meng Han Zhejiang University Hong Kong Baptist University Hangzhou China Department of Computer Science Hong Kong Baptist University Hong Kong SAR Institute for High-Performance Computing Agency for Science Technology and Research Singapore People's Public Security University of China Beijing China Zhejiang University GenTel.io Hangzhou China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Novel view synthesis typically requires a comprehensive set of multi-view images for either image-based rendering or scene representation-based optimization. However, achieving high-fidelity novel view rendering often demands a large number of images. To address this limitation, we propose NCDI-Diffusion, a novel diffusion-based view synthesis method that reduces the number of required images by leveraging the prior knowledge embedded in pre-trained diffusion models. Specifically, NCDI-Diffusion encapsulates both the contextual and directional information of a scene by utilizing neural descriptors, which are inversely derived from a limited set of positioned multi-view training images. These descriptors guide the diffusion model's image synthesis process, enabling the generation of high-quality novel views. Empirical results on the Forward-facing Dataset demonstrate the effectiveness of our approach to novel view synthesis.

关键词： Training Image synthesis Pipelines Signal processing Diffusion models Rendering (computer graphics) Acoustics Speech processing Optimization Convergence

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AF-MCDC: Active Feedback-Based Malicious Client Dynamic Detection

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Computer Networks 2025年 263卷

作者： Du, Hongyu Zhang, Shouhui Xv, Xi Ji, Yimu Shao, Sisi Wu, Fei Liu, Shangdong School of Computer Science Nanjing University of Posts and Telecommunications Nanjing210023 China College of Automation Nanjing University of Posts and Telecommunications Nanjing210023 China School of Internet of Things Nanjing University of Posts and Telecommunications Nanjing210023 China Institute of High Performance Computing and Bigdata Nanjing University of Posts and Telecommunications Nanjing210003 China Nanjing Center of HPC China Nanjing210003 China

Federated Learning (FL) has long been known for separating the training and model construction processes, ensuring the privacy of participating clients. However, this separation also introduces a new attack surface. Due to the decentralization feature, Federal Learning is prone to Byzantine attacks. Attackers can deliberately corrupt or malfunction one or more participants in the federated network, disrupting the overall model training process. Researchers have proposed many defense mechanisms to mitigate Byzantine attacks. Their main ideas include eliminating malicious updates that deviate from the overall distribution through similarity detection and avoiding malicious parameters using statistical characteristics. Yet, these defense mechanisms are usually passive, detection only happens on the central server, neglecting the important role of clients. Thus we propose AF-MCDC: Active Feedback-Based Malicious Client Dynamic Detection, a byzantine-robust federated learning method taking advantage of valid clients. What sets AF-MCDC apart from existing robust federated learning methods is its three-pronged defense approach. First, a detection mechanism is deployed on each client to verify the integrity of the distributed global model. If the model fails the integrity check, it will not be used to initialize the local model. On the server side, a decision is made based on the detection results uploaded by the clients, followed by performance scoring using cosine similarity among federated clients. Finally, a dynamic weighting mechanism based on client score rankings is applied to weigh the local models uploaded by all clients, effectively filtering out malicious clients Evaluation of two datasets, MNIST and CIFAR-10, demonstrates that AF-MCDC is robust against a significant portion of malicious clients. Furthermore, even when over half of the clients are malicious, AF-MCDC can still train a global model with performance comparable to the global model learned by FedAvg u

关键词： Federated learning

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F2UE-NET: An Uncertainty-Driven Dynamic Expert Network for Long-Tail Retinal Disease Classification

F2UE-NET: An Uncertainty-Driven Dynamic Expert Network for L...

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IEEE International Symposium on Biomedical Imaging

作者： Junyong Zhao Tian Lin Meng Wang Liang Sun Haoyu Chen Daoqiang Zhang Huazhu Fu MOE Key Laboratory of Brain Computer Intelligence Technology College of Artificial Intelligence Nanjing University of Aeronautics and Astronautics Nanjing China Joint Shantou International Eye Center Shantou University and the Chinese University of Hong Kong Shantou Guangdong China Department of Ophthalmology Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore Agency for Science Technology and Research (A*STAR) Institute of High Performance Computing (IHPC) Singapore Singapore

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

The automatic diagnosis of retinal diseases presents a significant challenge in medical image analysis, primarily due to the long-tail distribution in existing retinal datasets. This imbalance creates substantial difficulties in model training and performance. To address this issue, we propose an uncertainty-driven dynamic expert network for long-tail retinal disease classification, called $\mathrm{F}^performance\text{UE}$ -Net. Specifically, we apply Low-Rank Adaptation (LoRA) technology to fine-tune the foundation model, enhancing its feature extraction capabilities and overall performance. Additionally, we introduce an uncertainty-driven dynamic expert participation strategy, which assigns appropriate weights to different categories during training, ensuring high accuracy even for rare, tail-end diseases. Experimental results on a long-tail fundus disease dataset demonstrate that $\mathrm{F}^performance$ UE outperforms state-of-the-art methods in long-tail retinal disease classification.

关键词： Training Heavily-tailed distribution Image analysis Foundation models Biological system modeling Tail Retina Feature extraction Medical diagnostic imaging Diseases

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Attainability of quantum state discrimination bounds with collective measurements on finite copies

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Physical Review A 2025年第2期111卷 022438-022438页

作者： Lorcán O. Conlon Jin Ming Koh Biveen Shajilal Jasminder Sidhu Ping Koy Lam Syed M. Assad Institute of Materials Research and Engineering Agency for Science Technology and Research (ASTAR) 2 Fusionopolis Way 08-03 Innovis 138634 Republic of Singapore Institute of High Performance Computing Agency for Science Technology and Research (ASTAR) 1 Fusionopolis Way #16-16 Connexis Singapore 138632 Republic of Singapore Department of Physics Harvard University Cambridge Massachusetts 02138 USA SUPA Department of Physics The University of Strathclyde Glasgow G4 0NG United Kingdom Centre for Quantum Computation and Communication Technology Department of Quantum Science Australian National University Canberra ACT 2601 Australia

One of the fundamental tenets of quantum mechanics is that nonorthogonal states cannot be distinguished perfectly. When distinguishing multiple copies of a mixed quantum state, a collective measurement, which generates entanglement between the different copies of the unknown state, can achieve a lower error probability than nonentangling measurements. The error probability that can be attained using a collective measurement on a finite number of copies of the unknown state is given by the Helstrom bound. In the limit where we can perform a collective measurement on asymptotically many copies of the quantum state, the quantum Chernoff bound gives the attainable error probability. It is natural to ask, then, what strategies can be employed to reach these two bounds—is entanglement across all available modes always necessary or can other, experimentally more simple measurements saturate these bounds? In this work we address this question. We find analytic expressions for the Helstrom bound for arbitrarily many copies of the unknown state in simple qubit examples. Using these analytic expressions, we investigate whether the quantum Chernoff bound can be saturated by repeatedly implementing the M-copy Helstrom measurement. We also investigate the necessary conditions to saturate the M-copy Helstrom bound. It is known that a collective measurement on all M copies of the unknown state is always sufficient to saturate the M-copy Helstrom bound. However, general conditions for when such a measurement is necessary to saturate the Helstrom bound remain unknown. We investigate specific measurement strategies which involve entangling operations on fewer than all M copies of the unknown state. For many regimes we find that a collective measurement on all M copies of the unknown state is necessary to saturate the M-copy Helstrom bound.

关键词： Quantum entanglement

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JASMIN: a parallel software infrastructure for scientific computing

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中国计算机科学前沿 2010年第4期4卷 480-488页

作者： Zeyao MO Aiqing ZHANG Xiaolin CAO Qingkai LIU Xiaowen XU Hengbin AN Wenbing PEI Shaoping ZHU Laboratory of Computational Physics High Performance Computing CenterInstitute of Applied Physics and Computational MathematicsBeijing 100088China

The exponential growth of computer power in the last 10 years is now creating a great challenge for parallel programming toward achieving realistic performance in the field of scientific computing. To improve on the traditional program for numerical simulations of laser fusion in inertial confinement fusion (ICF), the institute of Applied Physics and Computational Mathematics (IAPCM) initializes a software infrastructure named J Adaptive Structured Meshes applications INfrastructure (JASMIN) in 2004. The main objective of JASMIN is to accelerate the development of parallel programs for large scale simulations of complex applications on parallel computers. Now, JASMIN has released version 1.8 and has achieved its original objectives. Tens of parallel programs have been reconstructed or developed on thousands of processors. JASMIN promotes a new paradigm of parallel programming for scientific computing. In this paper, JASMIN is briefly introduced.

关键词： J Adaptive Structured Meshes applications INfrastructure (JASMIN) parallel computing scientific computing

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HIDING SHARED MEMORY REFERENCE LATENCY ON THE GALACTICA NET DISTRIBUTED SHARED MEMORY ARCHITECTURE

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JOURNAL OF PARALLEL AND DISTRIBUTED computing 1992年第4期15卷 351-367页

作者： WILSON, AW LAROWE, RP Center for High Performance Computing Worcester Polytechnic Institute Marlborough Massachusetts 01752 USA

In order to provide shared memory in large-scale multiprocessors, techniques to hide the latency of shared memory accesses must be developed. In this paper, we describe the latency hiding mechanisms employed by the Galactica Net scalable distributed shared memory architecture being developed at the center for high performance computing. We introduce our novel technique for maintaining the coherence of shared data caches, based on a flexible hardware-supported but software-controlled mechanism supporting both update and invalidate based protocols. We also consider the use of alternative memory consistency models, and find that the use of weaker consistency models is an effective way to hide memory reference latency in the Galactica Net architecture. Preliminary performance evaluations indicate that together these mechanisms are able to hide a significant amount of the memory reference latency, thus increasing the scalability of the architecture.

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Hypervelocity impact induced shock acoustic emission waves for quantitative damage evaluation using in situ miniaturized piezoelectric sensor network

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Chinese Journal of Aeronautics 2019年第5期32卷 1059-1070页

作者： Menglong LIU Qiang WANG Qingming ZHANG Renrong LONG Fangsen CUI Zhongqing SU Institute of High Performance Computing A*STAR (Agency for Science Technology and Research) School of Automation Nanjing University of Posts and Telecommunications State Key Laboratory of Explosion Science and Technology Beijing Institute of Technology Institute of High Performance Computing (A*STAR Agency for Science Technology and Research) Department of Mechanical Engineering The Hong Kong Polytechnic University

Manmade debris and natural meteoroids, travelling in the Low Earth Orbit at a speed of several kilometers per second, pose a severe safety concern to the spacecraft in service through the HyperVelocity Impact(HVI). To address this issue, an investigation of shock Acoustic Emission(AE) waves induced by HVI to a downscaled two-layer Whipple shielding structure is performed,to realize a quantitative damage evaluation. Firstly a hybrid numerical model integrating smoothparticle hydrodynamics and finite element is built to obtain the wave response. The projectiles, with various impact velocities and directions, are modelled to impact the shielding structure with different thicknesses. Then experimental validation is carried out with built-in miniaturized piezoelectric sensors to in situ sense the HVI-induced AE waves. A quantitative agreement is obtained between numerical and experimental results, demonstrating the correctness of the hybrid model and facilitating the explanation of obtained AE signals in experiment. Based on the understanding of HVI-induced wave components, assessment of the damage severity, i.e., whether the outer shielding layer is perforated or not, is performed using the energy ratio between the regions of ‘‘high frequency" and ‘‘low frequency" in the acquired AE signals. Lastly, the direct-arrival fundamentalsymmetric wave mode is isolated from each sensing signal to be input into an enhanced delay-andsum algorithm, which visualizes HVI spots accurately and instantaneously with different sensor network configuration. All these works demonstrate the potential of quantitative, in situ, and real time HVI monitoring using miniaturized piezoelectric sensor network.

关键词： Acoustic Emission(AE) Damage detection Hypervelocity impact Piezoelectric sensor Whipple shielding assembly

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OPTIMAL CONTROL OF QUASILINEAR PARABOLIC PDES WITH GRADIENT TERMS AND POINTWISE CONSTRAINTS ON THE GRADIENT OF THE STATE

arXiv

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arXiv 2025年

作者： Bonifacius, Lucas Hoppe, Fabian Meinlschmidt, Hannes Neitzel, Ira Institute of Software Technology High-Performance Computing Linder Höhe Cologne Germany Department of Mathematics Friedrich-Alexander-Universität Erlangen-Nürnberg Cauerstraße 11 Erlangen91058 Germany Institut für Numerische Simulation Rheinische Friedrich-Wilhelms-Universität Bonn Friedrich-Hirzebruch-Allee 7 Bonn53115 Germany

MSC Codes 49J20, 49K20, 35K59, 35K90, 35B65, 35R05, 49K27We derive existence results and first order necessary optimality conditions for optimal control problems governed by quasilinear parabolic PDEs with a class of first order nonlinearities that include for instance quadratic gradient terms. Pointwise in space and time or averaged in space and pointwise in time constraints on the gradient of the state control the growth of the nonlinear terms. We rely on and extend the improved regularity analysis for quasilinear parabolic PDEs on a whole scale of function spaces from [28]. In case of integral in space gradient-constraints we derive first-order optimality conditions under rather general regularity assumptions for domain, coefficients, and boundary conditions, similar to e.g. [8]. In the case of pointwise in time and space gradient-constraints we use slightly stronger regularity assumptions leading to a classical smoother W2,p-setting similar to [12]. © 2025, CC BY-NC-ND.

关键词： Optimal control systems

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Charge-state dependent spin-orbit coupling and quantum phase transitions in Ir-Ru oxides

arXiv

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arXiv 2025年

作者： Kargeti, Kuldeep Mallick, Bidyut Borisov, Vladislav Ali, S.K. Soyeb Hellsvik, Johan Eriksson, Olle Panda, S.K. Department of Physics Bennett University Uttar Pradesh Greater Noida201310 India Department of Applied Sciences Galgotias College of Engineering and Technology Greater Noida India Department of Physics and Astronomy Uppsala University Box 516 UppsalaSE-751 20 Sweden PDC Center for High Performance Computing KTH Royal Institute of Technology StockholmSE-100 44 Sweden Wallenberg Initiative Materials Science for Sustainability Uppsala University UppsalaSE-751 21 Sweden

The competition between kinematic, relativistic, and Coulombic interactions has spurred intense experimental and theoretical investigations in iridium-based oxides. Its electronic structure is mostly understood in terms of the spin-orbital coupled effective J-state (Jef f). However, the role of the Ir charge state in shaping the strength of effective spin-orbit coupling and defining the stability of the Jef f ground state has not been thoroughly explored. We argue here that the Iridium-Ruthenium triple perovskites, Ba3MRuIrO9 (M = Li, Mg and In), are of particular interest in this regard. Using ab-initio theory, we show here that the nominal charge states of Ir can be tuned from +6 (5d3) to +4 (5d5) by choosing non-magnetic’M’ ions as Li (+1), Mg(+2) and In (+3), while the Ru ions always remain in nominal +5 (4d3) charge-state. This variation modulates the influence of the spin-orbit coupling (SOC) which is found to be negligible in Ba3LiRuIrO9, moderate in Ba3MgRuIrO9 and determining in Ba3InRuIrO9. Our analysis classifies Ba3LiRuIrO9 as a band-insulator, Ba3MgRuIrO9 as a SOC and correlation driven insulator that does not conform to the commonly expected J = 0 ground state and Ba3InRuIrO9 as Jeff = 1/2 Mott-Hubbard insulator. In the data reported here, the correlational electronic structure theory results in sizeable magnetic moments of both Ru and Ir atoms in these systems and atomistic spin-dynamics simulations capture the experimental Néel temperature for Ba3LiRuIrO9 and Ba3MgRuIrO9 and provide evidence for a phase transition for Ba3InRuIrO9 when T → 0 K, to a multi-valley magnetic state with strong magnetic frustration. The theory identifies that strong SOC in Ba3InRuIrO9 induces bond-dependent magnetic couplings with significant Dzyaloshinskii-Moriya (DM) interaction, strong symmetric anisotropic exchange, and finite in-plane single-ion anisotropy. The realization of such strong anisotropic interactions helps to stabilize a particularly complex energy landscap

关键词： Ground state

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AI-Powered Earth Disaster Management: A Collaborative Innovation Platform 24

AI-Powered Earth Disaster Management: A Collaborative Innova...

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8th International Conference on Innovation in Artificial Intelligence, ICIAI 2024

作者： Huang, Chung-I Sun, Chen-Kai Chang, Jih-Sheng Chang, Wen-Yi Lin, Fang-Pang Wu, Jyh-Horng Chen, Wei-Yu Data Science and Technology Division National Center for High Performance Computing Taiwan High Performance Computing Division National Center for High-performance Computing Taiwan

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