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PBCounter:weighted model counting on pseudo-boolean formulas

Frontiers of Computer science 2025年第3期19卷 55-63页

作者： Yong LAI Zhenghang XU Minghao YIN College of Computer Science and Technology Jilin UniversityChangchun 130012China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin UniversityChangchun 130012China School of Computer Science and Information Technology Northeast Normal UniversityChangchun 130017China

In Weighted Model Counting(WMC),we assign weights to literals and compute the sum of the weights of the models of a given propositional formula where the weight of an assignment is the product of the weights of its *** current WMC solvers work on Conjunctive Normal Form(CNF)***,CNF is not a natural representation for human-being in many *** by the stronger expressive power of Pseudo-Boolean(PB)formulas than CNF,we propose to perform WMC on PB *** on a recent dynamic programming algorithm framework called ADDMC for WMC,we implement a weighted PB counting tool *** compare PBCounter with the state-of-the-art weighted model counters SharpSAT-TD,ExactMC,D4,and ADDMC,where the latter tools work on CNF with encoding methods that convert PB constraints into a CNF *** experiments on three domains of benchmarks show that PBCounter is superior to the model counters on CNF formulas.

关键词： weighted model counting pseudo-boolean constraint algebraic decision diagrams preprocessing techniques

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Multi-View Graph Embedding Learning for Image Co-Segmentation and Co-Localization

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IEEE Transactions on Circuits and systems for Video technology 2024年第6期34卷 4942-4956页

作者： Huang, Aiping Li, Lijian Zhang, Le Niu, Yuzhen Zhao, Tiesong Lin, Chia-Wen Fuzhou University Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information College of Physics and Information Engineering Fuzhou350108 China Fuzhou University Fujian Key Laboratory of Network Computing and Intelligent Information Processing College of Computer and Data Science Fuzhou350108 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Fuzhou University Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information College of Physics and Information Engineering The Fujian Science and Technology Innovation Laboratory for Optoelectronic Information Fuzhou350108 China Institute of Communications Engineering National Tsing Hua University Department of Electrical Engineering Hsinchu30013 Taiwan

Image co-segmentation and co-localization exploit inter-image information to identify and extract foreground objects with a batch mode. However, they remain challenging when confronted with large object variations or complex backgrounds. This paper proposes a multi-view graph embedding (MV-Gem) learning scheme which integrates diversity, robustness and discernibility of object features to alleviate this phenomenon. To encourage the diversity, the deep co-information containing both low-layer general representations and high-layer semantic information is generated to form a multi-view feature pool for comprehensive co-object description. To enhance the robustness, a multi-view adaptive weighted learning is formulated to fuse the deep co-information for feature complementation. To ensure the discernibility, the graph embedding and sparse constraint are embedded into the fusion formulation for feature selection. The former aims to inherit important structures from multiple views, and the latter further selects important features to restrain irrelevant backgrounds. With these techniques, MV-Gem gradually recovers all co-objects through optimization iterations. Extensive experimental results on real-world datasets demonstrate that MV-Gem is capable of locating and delineating co-objects in an image group. © 1991-2012 IEEE.

关键词： Semantics

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Deep Learning Based Signal Detector for OFDM systems

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China Communications 2023年第12期20卷 66-77页

作者： Guangliang Pan Wei Wang Minglei Li Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information TechnologyCollege of Electronic and Information EngineeringNanjing University of Aeronautics and AstronauticsNanjing 211106China College of Control Science and Engineering China University of Petroleum(East China)Qingdao 266580China

In this paper,we propose a novel deep learning(DL)-based receiver design for orthogonal frequency division multiplexing(OFDM)*** entire process of channel estimation,equalization,and signal detection is replaced by a neural network(NN),and hence,the detector is called a NN detector(N^(2)D).First,an OFDM signal model is *** analyze both temporal and spectral characteristics of OFDM signals,which are the motivation for ***,the generated data based on the simulation of channel statistics is used for offline training of bi-directional long short-term memory(Bi-LSTM)***,a discriminator(F)is added to the input of Bi-LSTM NN to look for subcarrier transmission data with optimal channel gain(OCG),which can greatly improve the performance of the ***,the trained N^(2)D is used for online recovery of OFDM *** performance of the proposed N^(2)D is analyzed theoretically in terms of bit error rate(BER)by Monte Carlo simulation under different parameter *** simulation results demonstrate that the BER of N^(2)D is obviously lower than other algorithms,especially at high signal-to-noise ratios(SNRs).Meanwhile,the proposed N^(2)D is robust to the fluctuation of parameter values.

关键词： channel estimation deep learning OFDM optimal channel gain signal detection

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Metal-based inorganic nanocrystals for biological sonodynamic therapy applications:recent progress and perspectives

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Rare Metals 2024年第2期43卷 413-430页

作者： Dong Wang Jia-Tao Zhang Institute of Medical-Industrial Integration Beijing Key Laboratory of Structurally Controllable Advanced Functional Materials and Green ApplicationsSchool of Materials Science and EngineeringBeijing Institute of TechnologyBeijing100081China Key Laboratory of Medical Molecule Science and Pharmaceutics Engineering Ministry of Industry and Information TechnologySchool of Chemistry and Chemical EngineeringBeijing Institute of TechnologyBeijing100081China

With the fast development of technology for the treatment of tumor and bacteria,photo-therapeutic strate-gies emerge as a kind of highly effective and common treatment,but the low tissue penetration depth of light limits their *** therapy(SDT),as an efficient and non-invasive treatment,attracts more people's attention due to the inherent property of high tissue *** soft tissue penetration depth of ultrasound(US)can even reach more than 10 cm,which has great advantage over that of ***,many sonosensitizers are studied and applied to SDT-based ***-based inorganic nanocrystals are able to generate more reactive oxygen species(ROS)due to the special composition and band *** representative achievements and the specific functions of the nanocrystals sonosensitizers are summarized in this work,and the relationship of structure/composition-SDT performance and the internally regulated composite is ***-gistic effects of SDT in combination with other therapeutic modalities are mainly *** the same time,the critical and potential issues and future perspectives are addressed.

关键词： Metal-based inorganic nanocrystals Sonodynamic therapy(SDT) Tumor treatment Antibacteria

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Speckle-free laser display enabled by self-assembled supraparticles of semiconductor nanoplatelets

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Nano Research 2025年第2期18卷 769-775页

作者： Chenlin Wang Haixiao Zhao Xian Zhao Baoqing Sun Yuan Gao School of Information Science and Engineering Shandong UniversityQingdao 266237China Key Laboratory of Laser&Infrared System(Shandong University) Ministry of EducationShandong UniversityQingdao 266237China Center for Optics Research and Engineering(CORE) Shandong UniversityQingdao 266237China

Laser-based light sources are highly desirable for display applications due to their narrow emission linewidth and exceptional ***,the coherence inherent in lasers often leads to the formation of unwanted speckles,which can significantly degrade display ***,there is a critical need for light sources that retain the narrow emission and high brightness of lasers while minimizing spatial coherence to reduce speckle *** lasing has emerged as a promising strategy to address this issue,though its random emission directions can lead to energy *** overcome this challenge,we propose a novel approach in which CdSe nanoplatelets,known for their efficient optical gain properties,are self-assembled into supraparticles(SPs),serving as both scattering centers and gain *** configuration enables random lasing,and by coupling the random gain medium to a Fabry-Perot(FP)cavity,we successfully direct the typically omnidirectional random lasing into a controlled,low-coherence *** experimental results,comparing conventional lasers(e.g.,He:Ne lasers)with our SP-based laser for a projector,demonstrate effective suppression of speckle formation,reducing speckle contrast from 0.5 to *** findings offer a promising solution for improving the performance and quality of laser-based displays.

关键词： CdSe nanoplatelet self-assembly cavity coupled random lasing speckle-free display

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Resource Allocation for Cloud-Edge-End Simulation system 3

Resource Allocation for Cloud-Edge-End Simulation System

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3rd International Conference on Modeling, Simulation, Optimization and Algorithm, ICMSOA 2021

作者： Yan, Guoqiang Mao, Shaojie Li, Yuping Science and Technology on Information System Engineering Laboratory Jiangsu Nanjing China

Aiming at the problem of simulating service requests and optimal scheduling during the operation of the cloud computing/edge computing environment, the real-time optimization scheduling technology of computing resources is studied, and elastic resource optimization scheduling is realized through data feature mining analysis, service load prediction, and collaborative resource management. Ensure that the simulation service quality meets the mission requirements and provide support. © Published under licence by IOP Publishing Ltd.

关键词： Resource allocation

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Observation of dark edge states in parity-time-symmetric quantum dynamics

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National science Review 2023年第8期10卷 156-165页

作者： Peng Xue Xingze Qiu Kunkun Wang Barry C. Sanders Wei Yi Beijing Computational Science Research Center Key Laboratory of Quantum Information University of Science and Technology of China Chinese Academy of Sciences Synergetic Innovation Center in Quantum Information and Quantum Physics University of Science and Technology of China Chinese Academy of Sciences School of Physics and Optoelectronic Engineering Anhui University Shanghai Branch National Laboratory for Physical Sciences at MicroscaleUniversity of Science and Technology of China Institute for Quantum Science and Technology University of Calgary Program in Quantum Information Science Canadian Institute for Advanced Research

Topological edge states arise in non-Hermitian parity-time(PT)-symmetric systems, and manifest themselves as bright or dark edge states, depending on the imaginary components of their eigenenergies. As the spatial probabilities of dark edge states are suppressed during the non-unitary dynamics, it is a challenge to observe them experimentally. Here we report the experimental detection of dark edge states in photonic quantum walks with spontaneously broken PT symmetry, thus providing a complete description of the topological phenomena therein. We experimentally confirm that the global Berry phase in PT-symmetric quantum-walk dynamics unambiguously defines topological invariants of the system in both the PT-symmetry-unbroken and-broken regimes. Our results establish a unified framework for characterizing topology in PT-symmetric quantum-walk dynamics, and provide a useful method to observe topological phenomena in PT-symmetric non-Hermitian systems in general.

关键词： parity-time symmetry photonic quantum walks dark edge states topological invariants

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Optimized online filter stack spectrometer for ultrashort X-ray pulses

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Nuclear science and Techniques 2024年第5期35卷 85-98页

作者： Jia-Xing Wen Ge Ma Ming-Hai Yu Yu-Chi Wu Yong-Hong Yan Shao-Yi Wang Huai-Zhong Gao Lu-Shan Wang Yu-Gang Zhou Qiang Li Yue Yang Fang Tan Xiao-Hui Zhang Jie Zhang Wen-Bo Mo Jing-Qin Su Wei-Min Zhou Yu-Qiu Gu Ming Zeng Zong-Qing Zhao Science and Technology on Plasma Physics Laboratory Laser Fusion Research CenterCAEPMianyang 621900China Department of Engineering Physics Tsinghua UniversityBeijing 100084China Key Laboratory of Particle and Radiation Imaging(Tsinghua University) Ministry of EducationBeijing 100084China School of Information Engineering Southwest University of Science and TechnologyMianyang 621010China

Currently,with the advent of high-repetition-rate laser-plasma experiments,the demand for online diagnosis for the X-ray spectrum is increasing because the laser-plasma-generated X-ray spectrum is very important for characterizing electron dynamics and *** this study,scintillators and silicon PIN(P-type–intrinsic-N-type semiconductor)diodes were used to construct a wideband online filter stack *** X-ray sensor and filter arrangement was optimized using a genetic algorithm to minimize the condition number of the response ***,the unfolding error was significantly reduced based on numerical *** detector responses were quantitatively calibrated by irradiating the scintillator and PIN diode with various nuclides and comparing the measuredγ-ray peaks.A prototype 15-channel spectrometer was developed by integrating an X-ray detector with front-and back-end *** prototype spectrometer could record X-ray pulse signals at a repetition rate of 1 ***,an optimized spectrometer was employed to record the real-time spectra of laser-driven bremsstrahlung *** optimized spectrometer offers a compact solution for spectrum diagnostics of ultrashort X-ray pulses,exhibiting improved accuracy in terms of spectrum measurements and repetition rates,and could be widely used in next-generation high-repetition-rate high-power laser facilities.

关键词： Filter stack spectrometer Laser plasma diagnostics X-ray diagnostics Scintillator PIN diode

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A Tibetan Sentence Boundary Disambiguation Model Considering the Components on information on Both Sides of Shad

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Tsinghua science and technology 2023年第6期28卷 1085-1100页

作者： Fenfang Li Hui Lv Yiming Gao Dolha Yan Li Qingguo Zhou School of Information Science and Engineering Lanzhou UniversityLanzhou 730000China Key Laboratory of China’s National Linguistic Information Technology Northwest Minzu UniversityLanzhou 730030China

Sentence Boundary Disambiguation(SBD)is a preprocessing step for natural language *** text into sentences is essential for Deep Learning(DL)and pretraining language *** punctuation marks may involve ambiguity about the sentences’beginnings and ***,the ambiguous punctuation marks must be distinguished,and the sentence structure must be correctly encoded in language *** study proposed a component-level Tibetan SBD approach based on the DL *** models can reduce the error amplification caused by word segmentation and part-of-speech *** most SBD methods have only considered text on the left side of punctuation marks,this study considers the text on both *** this study,465669 Tibetan sentences are adopted,and a Bidirectional Long Short-Term Memory(Bi-LSTM)model is used to perform *** experimental results show that the F1-score of the Bi-LSTM model reached 96%,the most efficient among the six *** are performed on low-resource languages such as Turkish and Romanian,and high-resource languages such as English and German,to verify the models’generalization.

关键词： Sentence Boundary Disambiguation(SBD) punctuation marks ambiguity Bidirectional Long Short-Term Memory(Bi-LSTM)model

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D2SFormer: Dual attention-dynamic bidirectional Transformer for semantic segmentation of urban remote sensing images

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年 18卷 12248-12262页

作者： Yan, Yi Li, Jiafeng Zhang, Jing Wang, Liuqian Zhuo, Li Beijing University of Technology School of Information Science and Technology Chaoyang Beijing100124 China Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System China

Semantic segmentation of urban remote sensing images (URSIs) is crucial for the development of smart cities and the acceleration of urban information. In view of the characteristics of URSIs with intricate backgrounds, dense distributions of feature objects, and varying object scales, we propose a dual attention-dynamic bidirectional Transformer (D2SFormer) for semantic segmentation of URSIs. First, a dual attention Transformer encoder has a global branch of cross-shaped window self-attention (CWSA) and a local branch of convolutional channel attention block (CCAB), which helps to enhance pixel-level semantic discrimination. Then, CCAB combines the local sensitivity of Conv with the non-local modeling capability of ECA for overlapping region resolution. Finally, the decoder dynamically fuses multiscale features to reconstruct boundaries and suppress artifacts by using a bidirectional feature pyramid network (BiFPN) and dysampling. Experimental results demonstrate that our D2SFormer achieves mIoUs of 87.84%, 81.24%, and 53.19% on the Potsdam, Vaihingen, and LoveDA datasets, respectively, which is highly competitive with existing methods. © 2008-2012 IEEE.

关键词： Semantic Segmentation

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