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Autism Spectrum Disorder Classification with Interpretability in Children Based on Structural MRI Features Extracted Using Contrastive Variational Autoencoder

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Big Data Mining and Analytics 2024年第3期7卷 781-793页

作者： Ruimin Ma Ruitao Xie Yanlin Wang Jintao Meng Yanjie Wei Yunpeng Cai Wenhui Xi Yi Pan Shenzhen Institute of Advanced Technology Chinese Academy of SciencesShenzhen 518055China University of Chinese Academy of Sciences Beijing 100049China Shenzhen Key Laboratory of Intelligent Bioinformatics and with Center for High Performance ComputingShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China

Autism Spectrum Disorder(ASD)is a highly disabling mental disease that brings significant impairments of social interaction ability to the patients,making early screening and intervention of ASD *** the development of the machine learning and neuroimaging technology,extensive research has been conducted on machine classification of ASD based on structural Magnetic Resonance Imaging(s-MRI).However,most studies involve with datasets where participants'age are above 5 and lack *** this paper,we propose a machine learning method for ASD classification in children with age range from 0.92 to 4.83 years,based on s-MRI features extracted using Contrastive Variational AutoEncoder(CVAE).78 s-MRIs,collected from Shenzhen Children's Hospital,are used for training CVAE,which consists of both ASD-specific feature channel and common-shared feature *** ASD participants represented by ASD-specific features can be easily discriminated from Typical Control(TC)participants represented by the common-shared *** case of degraded predictive accuracy when data size is extremely small,a transfer learning strategy is proposed here as a potential ***,we conduct neuroanatomical interpretation based on the correlation between s-MRI features extracted from CVAE and surface area of different cortical regions,which discloses potential biomarkers that could help target treatments of ASD in the future.

关键词： Autism Spectrum Disorder(ASD)classification Contrastive Variational AutoEncoder(CVAE) transfer learning neuroanatomical interpretation

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Thermal conductivity of GeTe crystals based on machine learning potentials

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Chinese Physics B 2024年第4期33卷 104-107页

作者：张健张昊春李伟峰张刚 School of Energy Science and Engineering Harbin Institute of TechnologyHarbin 150001China Institute of High Performance Computing Agency for ScienceTechnology and ResearchSingapore 138632Singapore School of Physics&State Key Laboratory of Crystal Materials Shandong UniversityJinan 250100China

GeTe has attracted extensive research interest for thermoelectric *** this paper,we first train a neuroevolution potential(NEP)based on a dataset constructed by ab initio molecular dynamics,with the Gaussian approximation potential(GAP)as a *** phonon density of states is then calculated by two machine learning potentials and compared with density functional theory results,with the GAP potential having higher ***,the thermal conductivity of a GeTe crystal at 300 K is calculated by the equilibrium molecular dynamics method using both machine learning potentials,and both of them are in good agreement with the experimental results;however,the calculation speed when using the NEP potential is about 500 times faster than when using the GAP ***,the lattice thermal conductivity in the range of 300 K-600 K is calculated using the NEP *** lattice thermal conductivity decreases as the temperature increases due to the phonon anharmonic *** study provides a theoretical tool for the study of the thermal conductivity of GeTe.

关键词： machine learning potentials thermal conductivity molecular dynamics

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Qualitative and Quantitative Model Checking Against Recurrent Neural Networks

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Journal of Computer Science & technology 2024年第6期39卷 1292-1311页

作者： Zhen Liang Wan-Wei Liu Fu Song Bai Xue Wen-Jing Yang Ji Wang Zheng-Bin Pang Institute for Quantum Information&State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China College of Computer Science and Technology National University of Defense TechnologyChangsha 410073China School of Information Science and Technology ShanghaiTech UniversityShanghai 201210China Institute of Software Chinese Academy of SciencesBeijing 100190China

Recurrent neural networks (RNNs) have been heavily used in applications relying on sequence data such as time series and natural languages. As a matter of fact, their behaviors lack rigorous quality assurance due to the black-box nature of deep learning. It is an urgent and challenging task to formally reason about the behaviors of RNNs. To this end, we first present an extension of linear-time temporal logic to reason about properties with respect to RNNs, such as local robustness, reachability, and some temporal properties. Based on the proposed logic, we formalize the verification obligation as a Hoare-like triple, from both qualitative and quantitative perspectives. The former concerns whether all the outputs resulting from the inputs fulfilling the pre-condition satisfy the post-condition, whereas the latter is to compute the probability that the post-condition is satisfied on the premise that the inputs fulfill the pre-condition. To tackle these problems, we develop a systematic verification framework, mainly based on polyhedron propagation, dimension-preserving abstraction, and the Monte Carlo sampling. We also implement our algorithm with a prototype tool and conduct experiments to demonstrate its feasibility and efficiency.

关键词： recurrent neural network model checking temporal logic qualitative/quantitative verification

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Research on performance optimization of virtual data space across WAN

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Frontiers of Computer Science 2024年第6期18卷 167-187页

作者： Jiantong HUO Zhisheng HUO Limin XIAO Zhenxue HE State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China High Performance Computing Center Beihang UniversityBeijing 100191China Hebei Key Laboratory of Agricultural Big Data Hebei Agricultural UniversityBaoding 071001China

For the high-performance computing in a WAN environment,the geographical locations of national supercomputing centers are scattered and the network topology is complex,so it is difficult to form a unified view of *** aggregate the widely dispersed storage resources of national supercomputing centers in China,we have previously proposed a global virtual data space named GVDS in the project of“high performance computing Virtual Data Space”,a part of the National key Research and Development Program of *** GVDS enables large-scale applications of the high-performance computing to run efficiently across ***,the applications running on the GVDS are often data-intensive,requiring large amounts of data from multiple supercomputing centers across *** this regard,the GVDS suffers from performance bottlenecks in data migration and access across *** solve the above-mentioned problem,this paper proposes a performance optimization framework of GVDS including the multitask-oriented data migration method and the request access-aware IO proxy resource allocation *** a WAN environment,the framework proposed in this paper can make an efficient migration decision based on the amount of migrated data and the number of multiple data sources,guaranteeing lower average migration latency when multiple data migration tasks are running in *** addition,it can ensure that the thread resource of the IO proxy node is fairly allocated among different types of requests(the IO proxy is a module of GVDS),so as to improve the application’s performance across *** experimental results show that the framework can effectively reduce the average data access delay of GVDS while improving the performance of the application greatly.

关键词： storage aggregation across WANs large-scale applications GVDS data migration allocation of IO proxy resource

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Ultra-low power MoS2 optoelectronic synapse with wavelength sensitivity for color target recognition

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Science China(Information Sciences) 2025年第4期68卷 187-196页

作者： Bo WEI Yabo CHEN Xiaotong HAN Yan KANG Bujia LIANG Cheng LI Xiaokuo YANG Liang FANG Yuanxi PENG Institute for Quantum Information & State Key Laboratory of High Performance Computing College of ComputerNational University of Defense Technology Fundamentals Department Air Force Engineering University College of Advanced Interdisciplinary Studies National University of Defense Technology Institute of Quantum Information Science and Technology College of ScienceNational University of Defense Technology College of Computer National University of Defense Technology

Optoelectronic synapses that integrate visual perception and pre-processing hold significant potential for neuromorphic vision systems（NVSs）. However, due to a lack of wavelength sensitivity, existing NVS mainly focuses on gray-scale image processing, making it challenging to recognize color images. Additionally, the high power consumption of optoelectronic synapses, compared to the 10 fJ energy consumption of biological synapses, limits their broader application. To address these challenges, an energy-efficient NVS capable of color target recognition in a noisy environment was developed,utilizing a MoS2optoelectronic synapse with wavelength sensitivity. Benefiting from the distinct photon capture capabilities of 450, 535, and 650 nm light, the optoelectronic synapse exhibits wavelength-dependent synaptic plasticity, including excitatory postsynaptic current（EPSC）, paired-pulse facilitation（PPF）, and long-term plasticity（LTP）. These properties can effectively mimic the visual memory and color discrimination functions of the human vision system. Results demonstrate that the NVS, based on MoS2optoelectronic synapses, can eliminate the color noise at the sensor level, increasing color image recognition accuracy from 50% to 90%. Importantly, the optoelectronic synapse operates at a low voltage spike of0.0005 V, consuming only 0.075 fJ per spike, surpassing the energy efficiency of both existing optoelectronic and biological synapses. This ultra-low power, color-sensitive device eliminates the need for color filters and offers great promise for future deployment in filter-free NVS.

关键词： optoelectronic synapse neuromorphic vision system color recognition 2D materials image pre-processing

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A Stable Arbitrarily high Order Time-Stepping Method for Thermal Phase Change Problems

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Communications in Computational Physics 2023年第2期33卷 477-510页

作者： Weiwen Wang Chuanju Xu School of Mathematical Sciences and Fujian Provincial Key Laboratory of MathematicalModeling and High Performance Scientific Computing Xiamen UniversityXiamen 361005P.R.China.

Thermal phase change problems are widespread in mathematics,nature,and *** are particularly useful in simulating the phenomena of melting and solidification in materials *** this paper we propose a novel class of arbitrarily high-order and unconditionally energy stable schemes for a thermal phase changemodel,which is the coupling of a heat transfer equation and a phase field *** unconditional energy stability and consistency error estimates are rigorously proved for the proposed schemes.A detailed implementation demonstrates that the proposed method requires only the solution of a system of linear elliptic equations at each time step,with an efficient scheme of sufficient accuracy to calculate the solution at the first *** is observed from the comparison with the classical explicit Runge-Kutta method that the new schemes allow to use larger time *** time step size strategies can be applied to further benefit from this unconditional *** experiments are presented to verify the theoretical claims and to illustrate the accuracy and effectiveness of our method.

关键词： Thermal phase change problem gradient flows unconditional energy stability auxiliary variable Runge-Kutta methods phase field

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An Energy Stable Filtered Backward Euler Scheme for the MBE Equation with Slope Selection

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Numerical Mathematics(Theory,Methods and Applications) 2023年第1期16卷 165-181页

作者： Jiexin Wang Hong-Lin Liao Ying Zhao School of Mathematics Nanjing University of Aeronautics and AstronauticsNanjing 211106China Key Laboratory of Mathematical Modelling and High Performance Computing of Air Vehicles(NUAA) MIITNanjing 211106China

As a promising strategy to adjust the order in the variable-order BDF algorithm,a time filtered backward Euler scheme is investigated for the molecular beam epitaxial equation with slope *** temporal second-order convergence in the L^(2)norm is established under a convergence-solvability-stability(CSS)-consistent time-step *** CSS-consistent condition means that the maximum stepsize limit required for convergence is of the same order to that for solvability and stability(in certain norms)as the small interface parameterε→0^(+).Similar to the backward Euler scheme,the time filtered backward Euler scheme preserves some physical properties of the original problem at the discrete levels,including the volume conservation,the energy dissipation law and L^(2)norm *** tests are included to support the theoretical results.

关键词： MBE model time filter energy dissipation law error estimate

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swDarknet: A Heterogeneous Parallel Deep Learning Framework Suitable for SW26010 Pro Processor 20th

swDarknet: A Heterogeneous Parallel Deep Learning Framework ...

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20th IFIP WG 10.3 International Conference on Network and Parallel computing, NPC 2024

作者： Liu, Huazeng Tian, Min Wu, Xiaoming Yang, Meihong Ren, Zenghui Li, Yanlong Jinan China Jinan Key Laboratory of High Performance Computing Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (纸本)9789819628292

As the size of AI models grows dramatically to achieve higher accuracy, more and more models are trained on supercomputers with massive computing and memory. However, it is still challenging to accelerate deep learning applications on supercomputer systems with many-core architectures. In this paper, we propose swDarknet: a Darknet-based heterogeneous parallel deep learning framework on the SW26010 Pro processor. First, We designed three heterogeneous parallel DNN layers: adaptive block-splitting strategy for matrix-multiplication layer, optimized memory access for convolutional layer, and block-based parallel pooling layer. Second, we proposed a model averaging (MA) method to efficiently scale swDarknet across many processors. Finally, we evaluated the performance of swDarknet on a core group. As compared with darknet, the convolutional layers achieved an average speedup of 32x. When training AlexNet and VGG-16, swDarknet can achieve up to 36.79× and 181.35× speedup, respectively. © IFIP International Federation for Information Processing 2025.

关键词： Supercomputers

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THE GLOBAL EXISTENCE OF BV SOLUTIONS OF THE ISENTROPIC p-SYSTEM WITH LARGE INITIAL DATA

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Acta Mathematica Scientia 2023年第4期43卷 1668-1674页

作者：吴菲王泽军陈芳启 Department of Mathematics Nanjing University of Aeronautics and AstronauticsNanjing 211106China Key Laboratory of Mathematical Modelling and High Performance Computing of Air Vehicles(NUAA) MIITNanjing 211106China

In this paper,we study the global existence of BV solutions of the initial value problem for the isentropic p-system,where the state equation of the gas is given by P=Av^(-γ).Forγ>1,the general existence result for large initial data has not been *** using the Glimm scheme,Nishida,Smoller and Diperna successively obtained the global existence results for(γ-1)TV(v_(0)(x),u_(0)(x))being *** the present paper,by adopting a rescaling technique,we improve these results and obtain the global existence result under the condition that(γ-1)^(γ+1)(TV(v_(0)(x)))~(γ-1)(TV(u_(0)(x)))^(2) is small,which implies that,for fixedγ>1,either TV(v_(0)(x))or TV(u_(0)(x))can be arbitrarily large.

关键词： conservation laws p-system vanishing viscosity method BV solutions

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Dynamic Task Allocation for Heterogeneous Multi-Robot System under Communication Constraints 6

Dynamic Task Allocation for Heterogeneous Multi-Robot System...

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6th IEEE Information technology, Networking, Electronic and Automation Control Conference, ITNEC 2023

作者： Li, Jun Cai, Zhongxuan Li, Minglong Huang, Wanrong Zhang, Yongjun National University of Defense Technology Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer China

ISBN: (纸本)9781665460033

Multi-robot system has important application potential in disaster rescue and other dangerous scenarios, in which task allocation is the basis for multi-robot cooperation to complete tasks. Due to the limited ability of individual robots, many complex scenarios requires coordination of different types of robot, e.g. robots for search, communication, rescue and so on. At the same time, communication is often limited in a wide range of scenarios. This brings two challenges in the realistic environment: heterogeneous multi-robot cooperation problem and communication constraint problem. This paper proposes a task allocation method based on hierarchical auction and dynamic grouping. By introducing a dynamic grouping algorithm to the general allocation procedure, we simultaneously optimize the number of robots in each group and the communication distance between robots. Then the communication loss rate can be reduced to improve task execution efficiency. Simulations of a communication constrained search and rescue scenario are conducted to verify the proposed algorithm, which are compared with the vanilla auction algorithm and a hierarchical approach on static grouping. The results show that our method surpasses the baseline on both task achievement and communication performance. © 2023 IEEE.

关键词： Multipurpose robots

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