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Facial expression recognition via weighted group sparsity

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Frontiers of Computer Science 2017年第2期11卷 266-275页

作者： Hao ZHENG Xin GENG Key Laboratory of Trusted cloud computing and big data Analysis School of Information Engineering Nanjing Xiaozhuang University Nanjing 211171 China School of Computer Science and Engineering Southeast University Nanjing 211189 China

Considering the distinctiveness of different group features in the sparse representation, a novel joint multi- task and weighted group sparsity （JMT-WGS） method is pro- posed. By weighting popular group sparsity, not only the rep- resentation coefficients from the same class over their asso- ciate dictionaries may share some similarity, but also the rep- resentation coefficients from different classes have enough di- versity. The proposed method is cast into a multi-task frame- work with two-stage iteration. In the first stage, representa- tion coefficient can be optimized by accelerated proximal gra- dient method when the weights are fixed. In the second stage, the weights are computed via the prior information about their entropy. The experimental results on three facial expres- sion databases show that the proposed algorithm outperforms other state-of-the-art algorithms and demonstrate the promis- ing performance of the proposed algorithm.

关键词： facial expression recognition multi-task learning group sparsity

Unsupervised feature selection based on Markov blanket and particle swarm optimization

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Journal of Systems Engineering and Electronics 2017年第1期28卷 151-161页

作者： Yintong Wang Jiandong Wang Hao Liao Haiyan Chen College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Key Laboratory of Trusted cloud computing and big data Analysis Nanjing Xiaozhuang University College of Computer Science and Software Engineering Shenzhen University

Feature selection plays an important role in data mining and recognition, especially in the large scale text, image and biological data. Specifically, the class label information is unavailable to guide the selection of minimal feature subset in unsupervised feature selection, which is challenging and interesting. An unsupervised feature selection based on Markov blanket and particle swarm optimization is proposed named as UFSMB-PSO. The proposed method seeks to find the high-quality feature subset through multi-particles' cooperation of particle swarm optimization without using any learning algorithms. Moreover, the features' relevance will be computed based on an information metric of relevance gain, which provides an information theoretical foundation for finding the minimization of the redundancy between features. Our results on several benchmark datasets demonstrate that UFSMB-PSO can achieve significant improvement over state of the art unsupervised methods. © 1990-2011 Beijing Institute of Aerospace Information.

关键词： Character recognition data mining Feature extraction Information theory

Anti-Interference High-Speed Modulation Decoder for Quantum Key Distribution

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Chinese Physics Letters 2025年第1期42卷 34-39页

作者： Hua-Xing Xu Shao-Hua Wang Chang-Lei Wang Ping Zhang National Engineering Research center for Public Safety Risk Perception and Control by big data China Academic of Electronics and Information TechnologyBeijing 100041China CETC Academy of Electronics and Information Technology Group Co. Ltd.Beijing 100041China

Quantum key distribution is increasingly transitioning toward network applications,necessitating advancements in system performance,including photonic integration for compact designs,enhanced stability against environmental disturbances,higher key rates,and improved *** this letter,we propose an orthogonal polarization exchange reflector Michelson interferometer model to address quantum channel disturbances caused by environmental *** on this model,we designed a Sagnac reflector-Michelson interferometer decoder and verified its performance through an interference *** interference fringe visibility exceeded 98%across all four coding phases at 625 *** results indicate that the decoder effectively mitigates environmental interference while supporting high-speed modulation *** addition,the proposed anti-interference decoder,which does not rely on magneto-optical devices,is well-suited for photonic integration,aligning with the development trajectory for next-generation quantum communication devices.

关键词： decoder interferometer polarization

UCat: heterogeneous memory management for unikernels

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Frontiers of Computer Science 2023年第1期17卷 51-61页

作者： Chong TIAN Haikun LIU Xiaofei LIAO Hai JIN National Engineering Research center for big data Technology and System Services Computing Technology and System Lab/Cluster and Grid Computing LabSchool of Computing Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China

Unikernels provide an efficient and lightweight way to deploy cloud computing services in application-specialized and single-address-space virtual machines (VMs). They can efficiently deploy hundreds of unikernel-based VMs in a single physical server. In such a cloud computing platform, main memory is the primary bottleneck resource for high-density application deployment. Recently, non-volatile memory (NVM) technologies has become increasingly popular in cloud data centers because they can offer extremely large memory capacity at a low expense. However, there still remain many challenges to utilize NVMs for unikernel-based VMs, such as the difficulty of heterogeneous memory allocation and high performance overhead of address *** this paper, we present UCat, a heterogeneous memory management mechanism that support multi-grained memory allocation for unikernels. We propose front-end/back-end cooperative address space mapping to expose the host memory heterogeneity to unikernels. UCat exploits large pages to reduce the cost of two-layer address translation in virtualization environments, and leverages slab allocation to reduce memory waste due to internal memory fragmentation. We implement UCat based on a popular unikernel--OSv and conduct extensive experiments to evaluate its efficiency. Experimental results show that UCat can reduce the memory consumption of unikernels by 50% and TLB miss rate by 41%, and improve the throughput of real-world benchmarks such as memslap and YCSB by up to 18.5% and 14.8%, respectively.

关键词： unikernel virtualization non-volatile memory heterogeneous memory large page slab allocation

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Anomalous open orbits in Hofstadter spectrum of Chern insulator

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Science China(Physics,Mechanics & Astronomy) 2025年第3期68卷 139-144页

作者： Haijiao Ji Peng Zhou Noah F.Q.Yuan Hua Jiang Haiwen Liu X.C.Xie center for Advanced Quantum Studies Department of PhysicsBeijing Normal UniversityBeijing100875China Tsung-Dao Lee Institute Shanghai Jiao Tong UniversityShanghai201210China Department of Mathematics UC BerkeleyBerkeley94720USA Institute for Nanoelectronic Devices and Quantum computing Fudan UniversityShanghai200433China International center for Quantum Materials School of PhysicsPeking UniversityBeijing100871China Hefei National Laboratory Hefei230088China

The nontrivial band topology of Chern insulator can enrich the content of its Hofstadter butterfly spectra,which is closely related to recent experiments in twisted bilayer graphene and cold atom *** investigate the Hofstadter spectrum for various models of Chern insulators under a rational fluxφ_(0)/q,hereφ_(0)=h/e and q being an *** find the number of splitting subbands is|q-C|with C denoting the Chern number of parent ***,anomalous open-orbital subbands with Chern numbers q-1 and-q-1 emerge unexpectedly,which are beyond the parameter window(-q/2,q/2)of the Diophantine equation studied by Thouless-Kohmoto-Nightingale-den Nijs[***.49,405(1982)].The emergence of anomalous open orbits can be traced by analyzing the evolution of the Hofstadter spectrum,identifying as a new type of topological phase *** novel findings not only pinpoint the peculiar Hofstadter spectrum of Chern insulator,but also provide routes to study exotic characteristics beyond the Landau level physics.

关键词： Hofstadter spectrum topological phase transition open orbit

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An Algorithm for cloud-based Web Service Combination Optimization Through Plant Growth Simulation

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系统仿真学报 2025年第2期37卷 462-473页

作者： Li Qiang Qin Huawei Qiao Bingqin Wu Ruifang School of big data Shanxi Finance&Taxation CollegeTaiyuan 030027China School of Finance and Economics Taiyuan University of TechnologyTaiyuan 030027China

In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling *** model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system ***,a light-induced plant growth simulation algorithm was *** performance of the algorithm was compared through several plant types,and the best plant model was selected as the setting for the *** results show that when the number of test cloud-based web services reaches 2048,the model being 2.14 times faster than PSO,2.8 times faster than the ant colony algorithm,2.9 times faster than the bee colony algorithm,and a remarkable 8.38 times faster than the genetic algorithm.

关键词： cloud-based service scheduling algorithm resource constraint load optimization cloud computing plant growth simulation algorithm

Video-Based Detection of Epileptic Spasms in IESS:Modeling,Detection,and Evaluation

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Journal of Shanghai Jiaotong university(Science) 2025年第1期30卷 1-9页

作者： DING Lihui FU Lijun YANG Guang WAN Lin CHANG Zhijun Shenyang Institute of computing Technology Chinese Academy of SciencesShenyang110168China University of Chinese Academy of Sciences Beijing100049China Laboratory of big data and Artificial Intelligence Technology Shandong UniversityJinan250100China Senior Department of Pediatrics The Seventh Medical Center of Chinese PLA General HospitalBeijing100700China Department of Pediatrics The First Medical Center of Chinese PLA General HospitalBeijing100853China The Second School of Clinical Medicine Southern Medical UniversityGuangzhou510280China The National Science Library Chinese Academy of SciencesBeijing100190China

Behavioral scoring based on clinical observations remains the gold standard for screening,diagnosing,and evaluating infantile epileptic spasm syndrome(IESS).The accurate identification of seizures is crucial for clinical diagnosis and *** this study,we propose an innovative seizure detection method based on video feature recognition of patient *** capture the temporal characteristics of the spasm behavior presented in the videos effectively,we incorporate asymmetric convolutions and convolution–batch normalization–ReLU(CBR)*** within the 3D-ResNet residual blocks,we split the larger convolutional kernels into two asymmetric 3D convolutional *** kernels are connected in series to enhance the ability of the convolutional layers to extract key local features,both horizontally and *** addition,we introduce a 3D convolutional block attention module to enhance the spatial correlations between video frame channels *** improve the generalization ability,we design a composite loss function that combines cross-entropy loss with triplet loss to balance the classification and similarity *** train and evaluate our method using the PLA IESS-VIDEO dataset,achieving an average seizure recognition accuracy of 90.59%,precision of 90.94%,and recall of 87.64%.To validate its generalization capability further,we conducted external validation using six different patient monitoring videos compared with assessments by six human experts from various medical *** final test results demonstrate that our method achieved a recall of 0.6476,surpassing the average level achieved by human experts(0.5595),while attaining a high F1-score of *** findings have substantial significance for the long-term assessment of patients with IESS.

关键词： infantile epileptic spasm syndrome video-based seizure analysis asymmetric convolution 3D-ResNet attention mechanism

HMvisor: dynamic hybrid memory management for virtual machines

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Science China(Information Sciences) 2021年第9期64卷 74-89页

作者： Dang YANG Haikun LIU Hai JIN Yu ZHANG National Engineering Research center for big data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing LabSchool of Computer Science and Technology Huazhong University of Science and Technology

Emerging non-volatile memory(NVM) technologies promise high density, low cost and dynamic random access memory(DRAM)-like performance, at the expense of limited write endurance and high write energy consumption. It is more practical to use NVM combining with the traditional DRAM. However, the hybrid memory management such as page migration becomes more challenging in a virtualization environment because virtual machines(VMs) are unaware of the memory heterogeneity. In this paper, we propose HMvisor, a hypervisor and VM coordinated hybrid memory management mechanism to better utilize DRAM and NVM resources. HMvisor exposes the memory heterogeneity to VMs by mapping virtual NUMA nodes to different physical NUMA nodes. We propose a lightweight and efficient page migration mechanism by decoupling page hotness tracking from page migration. HMvisor performs those operations in the hypervisor and VMs separately, without disrupting the execution of VMs. We also propose a memory resource trading policy to adjust the capacity of DRAM and NVM for each VM, with the monetary cost unchanged. We implement our prototype system based on QEMU/KVM and evaluate it with several benchmarks. Experimental results show that HMvisor can reduce 50% of write traffic to NVM with less than 5% performance overhead. Moreover, the hybrid memory adjustment scheme in HMvisor can significantly improve application performance by up to 30×.

关键词： hypervisor virtual machine non-volatile memory hybrid memory management

Optimizing the Copy-on-Write Mechanism of Docker by Dynamic Prefetching

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Tsinghua Science and Technology 2021年第3期26卷 266-274页

作者： Yan Jiang Wei Liu Xuanhua Shi Weizhong Qiang National Engineering Research center for big data Technology and System Services Computing Technology and System LabHuazhong University of Science and TechnologyWuhan 430074China

Docker,as a mainstream container solution,adopts the Copy-on-Write(CoW)mechanism in its storage *** mechanism satisfies the need of different containers to share the same ***,when a single container performs operations such as modification of an image file,a duplicate is created in the upper readwrite layer,which contributes to the runtime *** the accessed image file is fairly large,this additional overhead becomes *** we present the concept of Dynamic Prefetching Strategy Optimization(DPSO),which optimizes the Co W mechanism for a Docker container on the basis of the dynamic prefetching *** the beginning of the container life cycle,DPSO pre-copies up the image files that are most likely to be copied up later to eliminate the overhead caused by performing this operation during application *** experimental results show that DPSO has an average prefetch accuracy of greater than 78%in complex scenarios and could effectively eliminate the overhead caused by the CoW mechanism.

关键词： Docker container Copy-on-Write(CoW) storage driver prefetch strategy