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19th CCF Conference on Computer Supported Cooperative Work and Social computing, ChineseCSCW 2024

作者： Li, Hong Wu, Ling Guo, Kun College of Computer and Data Science Fuzhou University Fuzhou350108 China Engineering Research Center of Big Data Intelligence Ministry of Education Fuzhou350108 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou350108 China

ISBN: (纸本)9789819623723

Unified stream and batch computing (USBC) aims to incorporate stream and batch computation into a unified framework, thereby enabling the development of a one-stop solution for stream and batch data processing and enhancing the generalization of the framework. However, research on unified graph computing models (UGCMs) faces several challenges. First, existing UGCMs need to consider all graph information in the cache during the incremental update phase, thus leading to decreased execution efficiency. Second, existing UGCMs use fixed bytes to store nodes without considering the actual space occupied by nodes resulting in wasted memory when dealing with large graphs. This paper proposes a UGCM with Local Updates for community detection (UGCM-LU). We first implement a local update strategy to consider partial information of the graph to achieve incremental updates. Secondly, we also designed a byte-compression-based module to store graph data according to the space occupied by nodes. The experimental results show the effectiveness and efficiency of the model in real-world and artificial networks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Lutetium alloys

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Community Evolution Tracking Based on High-Order Neighbor Consideration and Node Change Identification 19th

Community Evolution Tracking Based on High-Order Neighbor C...

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19th CCF Conference on Computer Supported Cooperative Work and Social computing, ChineseCSCW 2024

作者： Zhang, Yunan Wang, Chaohui Wu, Ling Guo, Kun College of Computer and Data Science Fuzhou University Fuzhou350108 China Engineering Research Center of Big Data Intelligence Ministry of Education Fuzhou350108 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou350108 China

ISBN: (纸本)9789819623723

Community evolution tracking is widely used in complex network analysis, which analyzes and identifies how communities evolve over time based on dynamic community detection. However, the current incremental dynamic community detection method has the phenomenon of ’concept drift’, which leads to inaccurate tracking of community evolution. Although some studies on dynamic community detection have proposed to perform global community detection on the network by timing or when the error information accumulates to a certain extent, this method will lead to a sudden change in community division, which will interrupt the evolution sequence of some communities and bring great difficulties to the continuous tracking of community evolution. In addition, the current community evolution tracking methods match the communities of two adjacent snapshots, and it is difficult to capture the fine-grained evolution process within the community. This paper proposes a community evolution tracking algorithm based on high-order neighbor consideration and node change identification. Firstly, based on an incremental update strategy that considers high-order neighbors, we adaptively expand the scope of incremental updates to reduce the accumulation of error information. Secondly, through the node change identification strategy to mine fine-grained community evolution events. Experiments show that our method can effectively track the evolution of communities in dynamic networks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Community evolution Complex network Dynamic network Evolution tracking

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High-precision end-to-end adaptive optics aided orbital angular momentum wireless communication with XFTC-Net

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Optics Letters 2025年第10期50卷 3265-3268页

作者： Panpan Xu Huan Chang Fei Wang Ran Gao Dong Guo Lei Zhu Zhipei Li Sitong Zhou Qi Xu Jing Chen Xiangjun Xin School of Information and Electronics Beijing Institute of Technology (BIT) Beijing 100081 China National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing China School of Electronic Engineering Beijing University of Posts and Telecommunications (BUPT) Beijing 100876 China Key Laboratory of Computing Power Network and Information Security Ministry of Education Qilu University of Technology 250353 China

In this Letter, we demonstrate high-precision end-to-end adaptive optics (AO) technique based on the X-Shape Fusion Transformer-convolutional neural network (XFTC-Net) without an additional probe path to compensate for distortions caused by atmospheric turbulence (AT) in orbital angular momentum (OAM) optical wireless communication links. The experimental results show that the XFTC-Net effectively extracts the intensity distribution features of distorted OAM beams, predicting AT phase screens and identifying OAM modes. After XFTC-Net-aided AO compensation, the bit error rate of the OAM optical communication system remains below 3.8 × 10 −3 , staying within $C_{n}^2=1 \times 10^{-15}$ –1 × 10 −13 m −2/3 . Moreover, the optical power with l = 3 increases from 5.08 dBm to 8.23 dBm at a transmission distance of 800 m. These experimental results indicate that the proposed XFTC-Net AO technique effectively compensates for OAM beam distortion in both single- and multiplexed-channel OAM links, which effectively balances the system complexity and transmission performance of OAM-based free space optical (FSO) communication systems, opening up new avenues for enhancing the performances of high-capacity optical communication.

关键词： Adaptive optics Bit error rate Neural networks Optical wireless communication Polarization division multiplexing Space division multiplexing

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Shape Recognition and Retrieval Based on Edit Distance and Dynamic Programming

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Tsinghua Science and Technology 2009年第6期14卷 739-745页

作者：潘鸿飞梁栋唐俊王年李薇 Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University

An important aim in pattern recognition is to cluster the given shapes. This paper presents a shape recognition and retrieval algorithm. The algorithm first extracts the skeletal features using the medial axis transform. Then, the features are transformed into a string of symbols with the similarity among those symbols computed based on the edit distance. Finally, the shapes are identified using dynamic programming. Two public datasets are analyzed to demonstrate that the present approach is better than previous approaches.

关键词： skeletal features medial axis transform edit distance dynamic programming

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Human-like conceptual representations emerge from language prediction

arXiv

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arXiv 2025年

作者： Xu, Ningyu Zhang, Qi Du, Chao Luo, Qiang Qiu, Xipeng Huang, Xuanjing Zhang, Menghan School of Computer Science Fudan University Shanghai China Institute of Modern Languages and Linguistics Fudan University Shanghai China Shanghai Key Laboratory of Intelligent Information Processing Shanghai China Research Institute of Intelligent Complex Systems Fudan University Shanghai China Shanghai Collaborative Innovation Center of Intelligent Visual Computing Shanghai China Ministry of Education Key Laboratory of Contemporary Anthropology Fudan University Shanghai China

People acquire concepts through rich physical and social experiences and use them to understand the world. In contrast, large language models (LLMs), trained exclusively through next-token prediction over language data, exhibit remarkably human-like behaviors. Are these models developing concepts akin to humans, and if so, how are such concepts represented and organized? To address these questions, we reframed the classic reverse dictionary task to simulate human concept inference in context and investigated the emergence of human-like conceptual representations within LLMs. Our results demonstrate that LLMs can flexibly derive concepts from linguistic descriptions in relation to contextual cues about other concepts. The derived representations converged towards a shared, context-independent structure that effectively predicted human behavior across key psychological phenomena, including computation of similarities, categories and semantic scales. Moreover, these representations aligned well with neural activity patterns in the human brain, even in response to visual rather than linguistic stimuli, providing evidence for biological plausibility. These findings establish that structured, human-like conceptual representations can naturally emerge from language prediction without real-world grounding. More broadly, our work positions LLMs as promising computational tools for understanding complex human cognition and paves the way for better alignment between artificial and human intelligence. Copyright © 2025, The Authors. All rights reserved.

关键词： Semantics

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On the error coefficients of asymptotic frame error rate optimal binary linear codes

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IEEE Transactions on Information Theory 2025年

作者： Li, Shitao Luo, Gaojun Shi, Minjia Ling, San Anhui University Key Laboratory of Intelligent Computing Signal Processing Ministry of Education School of Mathematical Sciences Anhui Hefei230601 China Nanjing University of Aeronautics and Astronautics School of Mathematics Jiangsu Province Nanjing211106 China Nanyang Technological University School of Physical and Mathematical Sciences 637371 Singapore

A binary linear code is called asymptotic frame error rate (AFER)-optimal if it achieves the maximum possible value of the minimum distance while having the smallest value of the corresponding error coefficient. Over the additive white Gaussian noise channel and under maximum-likelihood decoding, AFER-optimal codes attain the best possible asymptotic frame error rate at high signal-to-noise ratio. In this paper, we present several bounds on the smallest error coefficients of binary linear codes and give several constructions of AFER-optimal binary linear codes. Many examples confirm that our bounds are sharp on numerous occasions. In addition, we give two families of AFER-optimal codes that respectively attain the proposed bounds with equality. © 1963-2012 IEEE.

关键词： Asymptotic analysis

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Counting extreme U1 matrices and characterizing quadratic doubly stochastic operators

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Frontiers of Mathematics in China 2016年第3期11卷 647-659页

作者： Quanbing ZHANG Shangjun YANG Key Laboratory of Intelligent Computing & Signal Processing Ministry of EducationAnhui University Hefei 230039 China

The U1 matrix and extreme U1 matrix were successfully used to study quadratic doubly stochastic operators by R. Ganikhodzhaev and F. Shahidi [Linear Algebra Appl., 2010, 432： 24-35], where a necessary condition for a U1 matrix to be extreme was given. S. Yang and C. Xu [Linear Algebra Appl., 2013, 438： 3905-3912] gave a necessary and sufficient condition for a symmetric nonnegative matrix to be an extreme U1 matrix and investigated the structure of extreme U1 matrices. In this paper, we count the number of the permutation equivalence classes of the n × n extreme U1 matrices and characterize the structure of the quadratic stochastic operators and the quadratic doubly stochastic operators.

关键词： Extreme U1 matrix quadratic doubly stochastic operator,majorized permutation similar irreducible matrix

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Point Pattern Matching Based on Spectra of Directed Graphs

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电子学报(英文版) 2011年第4期20卷 662-666页

作者： LIANG Dong ZHU Ming FAN Yizheng YAN Pu Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei China

We present a novel algorithm for point pattern matching by means of spectra of directed graphs. Given a feature point-set, we construct a weighted directed graph and skew-symmetric matrix associated with the graph. By using spectral decomposition of the matrix, we give a spectral representation of the feature points with half of the eigenvectors. We theoretically analyze that our method can well deal with the matching problem under affine transformation. The expreiments applied to synthetic data and real-world images show the effectiveness of our method.

关键词：点模式匹配图的谱反对称矩阵特征向量匹配问题仿射变换显示方法谱分解

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An Effective Method to Solve the Induced Surface Current for Arbitrary Conducting Objects at Resonant Frequencies

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电子学报(英文版) 2010年第1期19卷 66-68页

作者： SONG Kaihong WU Xianliang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China

A novel scheme is developed to compute correctly the induced current based on the Electric field integral equation (EFIE) by the Method of moments (MOM) at resonant frequencies. As a First step, the inaccurate induced current is obtained by solving the EFIE. Then, the scattered magnetic field due to the inaccurate induced current is calculated at any given point on the surface of the object. Finally, the accurate induced current at any given point is determined through the total magnetic field. The proposed approach is applied to the case of the infinitely Perfectly electric conducting (PEC) cylinder and PEC sphere to check its accuracy and efficiency. It is found that the numerical results match the analytical solution or the Combined field integral equation (CFIE) solution.

关键词：感应电流共振频率导体目标表面诱导电场积分方程数值结果总磁场

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Single-side-band optical modulation in SCM systems for high-speed optical transmission

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Optoelectronics Letters 2009年第1期5卷 48-50页

作者：李忠义廖同庆 Key Laboratory on Intelligent Computing & Signal Processing of Ministry of Education Anhui University

In order to decrease dispersion penalty and increase the optical bandwidth efficiency,an optical single-side-band modulation(SSBM) scheme in sub-carrier multiplexing(SCM) is *** principle of the SSBM is analytically presented,and a configuration for generating optical SSB signal is proposed using a balanced Mach-Zehnder electro-optic modulator.

关键词： Electrooptical devices

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