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SSRN 2025年

作者： Zhang, Qingru Chen, Guorong Zhang, Yixuan Liu, Shaofeng Wang, Jian Zhang, Jinmei School of Computer Science and Engineering Chongqing University of Science and Technology Shapingba District Chongqing401331 China State Key Laboratory of Coal Mine Disaster Prevention and Control Chongqing Research Institute China Coal Technology and Engineering Group Corp. Jiulongpo District Chongqing400039 China

Video dehazing aims to restore high-resolution and high-contrast haze-free frames, which is crucial in engineering applications such as intelligent traffic monitoring systems. These monitoring systems heavily rely on clear visual information to ensure accurate decision-making and reliable operation. However, despite significant advances achieved by deep learning methods, they still face challenges when dealing with diverse real-world scenarios. To address these issues, we propose a Multi-Scale Spatio-Temporal Fusion Network (MSTF-Net), a novel framework designed to enhance video dehazing performance in complex engineering environments. Specifically, the MainAux Encoder integrates multi-source information through a progressively enhanced feature fusion mechanism, improving the representation of both global dynamics and local details. Furthermore, the Spatio-Temporal Adaptive Fusion (STAF) module ensures robust temporal consistency and spatial clarity by leveraging multi-level spatio-temporal information fusion. To evaluate our framework, we constructed a challenging dataset named "DarkRoad," which includes low-light, uneven lighting, and dynamic outdoor scenarios, addressing the key limitations of existing datasets in video dehazing tasks. Extensive experiments demonstrate that MSTF-Net achieves state-of-the-art performance, excelling particularly in applications requiring high clarity, strong contrast, and detailed preservation, providing a reliable solution to video dehazing problems in practical engineering scenarios. © 2025, The Authors. All rights reserved.

关键词： Decision making

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A grouping approach based on non-uniform binary grid partitioning for crowd evacuation simulation

A grouping approach based on non-uniform binary grid partiti...

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作者： Liu, Hong Li, Yan Li, Wenhao Lu, Dianjie Zhang, Guijuan School of Information Science and Engineering Shandong Normal University Jinan China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan China University of South Australia Adelaide Australia

Small social groups based on kinship or friendships are ubiquitous in human crowds. Therefore, the effect of social groups on crowd evacuations and that of crowd evacuations on social groups must be investigated. To simulate the group phenomenon when an emergency occurs, we propose an improved social force model that takes into account the social group relationship among the population, and based on our proposed model, a novel grouping algorithm predicated on non-uniform binary grid partitioning is put forward. The approach initially maps the individuals into the plane space, and then it adopts top-down binary grid partitioning iteratively until the divided grid contains only the individuals with relations;then, the values of the relation and density of the non-empty grid cells are calculated, and the grids are sorted according to these values. After sorting, selecting, merging, and forming the core grids, the other grids are merged to the core grids. We have compared the algorithm with the hierarchical classification algorithm and the grid-based algorithm. The results show that the accuracy, speed, and scalability are all advantages. We also establish a simulation platform to illustrate the proposed grouping algorithm and the improved social force model for crowd evacuation simulation. © 2018 John Wiley & Sons, Ltd.

关键词： Simulation platform

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A sensor data processing and storage method for wireless body area networks 10

A sensor data processing and storage method for wireless bod...

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10th International Conference on Information technology in Medicine and Education, ITME 2019

作者： Han, Lu Xun, Lulu Liu, Jinfa Yin, Wenjun Zheng, Xiangwei Zheng, Zhuoran Shandong Normal University Ji'nan China Shandong Normal University Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Ji'nan China

ISBN: (纸本)9781728139173

This paper proposes an adaptive processing method and a dynamic storage method of pulsed wave signal based on wireless body area network. Firstly, the ZigBee star network model is adopted as the basic network architecture of the system. Secondly, an adaptive Gaussian filter model is designed to eliminate the influence of environmental and man-made factors. Finally, the dynamic storage algorithm is used to map the pulsed wave signal to a new stored sample, and the regression model is used to restore the new sample to the original signal. Simulation experiments show that: 1) The adaptive Gaussian model minimizes the signal noise and better maintains the characteristics of the pulsed wave signal. 2) On the premise of using ARIMA regression model of neural network, dynamic storage algorithm improves the regression accuracy compared with fixed storage algorithm. © 2019 IEEE.

关键词： Zigbee

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Global-to-Local neural networks for Document-Level relation extraction

arXiv

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arXiv 2020年

作者： Wang, Difeng Hu, Wei Cao, Ermei Sun, Weijian State Key Laboratory for Novel Software Technology Nanjing University China National Institute of Healthcare Data Science Nanjing University China Huawei Technologies Co. Ltd. China

Relation extraction (RE) aims to identify the semantic relations between named entities in text. Recent years have witnessed it raised to the document level, which requires complex reasoning with entities and mentions throughout an entire document. In this paper, we propose a novel model to document-level RE, by encoding the document information in terms of entity global and local representations as well as context relation representations. Entity global representations model the semantic information of all entities in the document, entity local representations aggregate the contextual information of multiple mentions of specific entities, and context relation representations encode the topic information of other relations. Experimental results demonstrate that our model achieves superior performance on two public datasets for document-level RE. It is particularly effective in extracting relations between entities of long distance and having multiple mentions. Copyright © 2020, The Authors. All rights reserved.

关键词： Encoding (symbols)

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Energy-Aware Resource Scheduling with Fault-Tolerance in Edge Computing 16th

Energy-Aware Resource Scheduling with Fault-Tolerance in Edg...

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16th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2019

作者： Xue, Yanfen Fan, Guisheng Yu, Huiqun Sun, Huaiying Department of Computer Science and Engineering East China University of Science and Technology Shanghai China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai China

ISBN: (纸本)9783030307080

Edge computing extends computation and storage resources to the edge of the network, which largely improve the performance problem of cloud computing incurred by the bandwidth limitation. And it still needs to address the challenges of energy and reliability. In this paper, we propose an energy-aware fault-tolerant resource scheduling algorithm to improve system reliability while minimizing the energy consumption. We allocate resources by reliability and energy-aware resource scheduling method for tasks firstly. Then, CPU temperature prediction and time between failures (TBF) prediction are used to trigger proactive fault tolerance mechanism (VM migration). The experimental results show that the reliability is greatly improved and energy consumption generated by VM migration is not very large compared to other methods. © 2019, IFIP International Federation for Information Processing.

关键词： Energy utilization

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A new effective and efficient measure for outlying aspect mining

arXiv

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arXiv 2020年

作者： Samariya, Durgesh Aryal, Sunil Ting, Kai Ming School of Science Engineering and Information Technology Federation University Churchill Australia School of IT Deakin University Geelong Australia National Key Laboratory for Novel Software Technology Nanjing University Nanjing China

Outlying Aspect Mining (OAM) aims to find the subspaces (a.k.a. aspects) in which a given query is an outlier with respect to a given dataset. Existing OAM algorithms use traditional distance/density-based outlier scores to rank subspaces. Because these distance/density-based scores depend on the dimensionality of subspaces, they cannot be compared directly between subspaces of different dimensionality. Z-score normalisation has been used to make them comparable. It requires to compute outlier scores of all instances in each subspace. This adds significant computational overhead on top of already expensive density estimation—making OAM algorithms infeasible to run in large and/or high-dimensional datasets. We also discover that Z-score normalisation is inappropriate for OAM in some cases. In this paper, we introduce a new score called SiNNE, which is independent of the dimensionality of subspaces. This enables the scores in subspaces with different dimensionalities to be compared directly without any additional normalisation. Our experimental results revealed that SiNNE produces better or at least the same results as existing scores;and it significantly improves the runtime of an existing OAM algorithm based on beam search. Copyright © 2020, The Authors. All rights reserved.

关键词： Statistics

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Photonic microspheres for high-capacity DNA data storage: Robust, straightforward, and scalable random access via nonfading indexes

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science Advances 2025年第25期11卷

作者： Qiu-Jun Liu Qian Liu Jie Zhang Cheng Zhang Long Qian Hao Qi Yue-Sheng Li Dong-Po Song Tianjin Key Laboratory of Composite and Functional Materials School of Materials Science and Engineering Tianjin University Tianjin 300350 China. School of Chemical Engineering and Technology Tianjin University Tianjin 300072 China. School of Computer Science Key Laboratory of High Confidence Software Technologies Peking University Beijing China. Center for Quantitative Biology Peking University Beijing China. State Key Laboratory of Synthetic Biology Tianjin University Tianjin 300072 China.

DNA-based storage offers a compelling alternative to traditional optical and magnetic devices. However, random data access usually requires additional noncoding primer DNA as indexes, which substantially reduce the physical data density. Here, we propose an alternative strategy to overcome this barrier by loading different data-encoding DNA files into porous microspheres, each distinguished by unique photonic bandgaps and diameters, allowing for 105 types of indexing. With the two features as the addressing indexes, the physical separation of subsets from a diverse pool of DNA files is achieved, thereby facilitating the selective retrieval of stored data. The interconnected nanopore arrays and uniformly distributed positive charges within the microspheres enhance DNA enrichment, achieving a storage density of up to 22.6 exabytes per gram, far exceeding that of previous random access storage methods. This work outlines a simple and scalable method for creating nonfading photonic indexes, enabling long-term random access while maintaining high storage capacity.

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C1-Conforming Quadrilateral Spectral Element Method for Fourth-Order Equations

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Communications on Applied Mathematics and Computation 2019年第3期1卷 403-434页

作者： Huiyuan Li Weikun Shan Zhimin Zhang State Key Laboratory of Computer Science/Laboratory of Parallel Computing Institute of SoftwareChinese Academy of SciencesBeijing 100190China School of Science Henan University of TechnologyZhengzhou 450001HenanChina Beijing Computational Science Research Center Beijing 100193China Department of Mathematics Wayne State UniversityDetroitMI 48202USA

This paper is devoted to Professor Benyu Guo's open question on the C1-conforming quadrilateral spectral element method for fourth-order equations which has been endeavored for years. Starting with generalized Jacobi polynomials on the reference square, we construct the C1-conforming basis functions using the bilinear mapping from the reference square onto each quadrilateral element which fall into three categories-interior modes, edge modes, and vertex modes. In contrast to the triangular element, compulsively compensatory requirements on the global C1-continuity should be imposed for edge and vertex mode basis functions such that their normal derivatives on each common edge are reduced from rational functions to polynomials, which depend on only parameters of the common edge. It is amazing that the C1-conforming basis functions on each quadrilateral element contain polynomials in primitive variables, the completeness is then guaranteed and further confirmed by the numerical results on the Petrov-Galerkin spectral method for the non-homogeneous boundary value problem of fourth-order equations on an arbitrary quadrilateral. Finally, a C1-conforming quadrilateral spectral element method is proposed for the biharmonic eigenvalue problem, and numerical experiments demonstrate the effectiveness and efficiency of our spectral element method.

关键词： Quadrilateral spectral element method Fourth-order equations Mapped polynomials C1-conforming basis Polynomial inclusion Completeness

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Rate-Distortion Modeling for Bit Rate Constrained Point Cloud Compression

arXiv

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arXiv 2022年

作者： Gao, Pan Luo, Shengzhou Paul, Manoranjan College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing211106 China MIIT Key Laboratory of Pattern Analysis and Machine Intelligence Nanjing University of Aeronautics and Astronautics Nanjing211106 China School of Software South China Normal University Foshan528225 China School of Computing and Mathematics Charles Sturt University BathurstNSW2795 Australia

As being one of the main representation formats of 3D real world and well-suited for virtual reality and augmented reality applications, point clouds have gained a lot of popularity. In order to reduce the huge amount of data, a considerable amount of research on point cloud compression has been done. However, given a target bit rate, how to properly choose the color and geometry quantization parameters for compressing point clouds is still an open issue. In this paper, we propose a rate-distortion model based quantization parameter selection scheme for bit rate constrained point cloud compression. Firstly, to overcome the measurement uncertainty in evaluating the distortion of the point clouds, we propose a unified model to combine the geometry distortion and color distortion. In this model, we take into account the correlation between geometry and color variables of point clouds and derive a dimensionless quantity to represent the overall quality degradation. Then, we derive the relationships of overall distortion and bit rate with the quantization parameters. Finally, we formulate the bit rate constrained point cloud compression as a constrained minimization problem using the derived polynomial models and deduce the solution via an iterative numerical method. Experimental results show that the proposed algorithm can achieve optimal decoded point cloud quality at various target bit rates, and substantially outperform the video-rate-distortion model based point cloud compression scheme. Copyright © 2022, The Authors. All rights reserved.

关键词： Lagrange multipliers

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Task-specific versus free-choice non-driving-related tasks: Enhancing automated driving takeover research through varied task engagement

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iscience 2025年第6期28卷

作者： Wenjun Wang Zhenyuan Wang Qingkun Li Yizi Su Chao Zeng Bo Cheng State Key Laboratory of Automotive Safety and Energy School of Vehicle and Mobility Tsinghua University Beijing 100084 China Beijing Key Laboratory of Human–Computer Interaction Institute of Software Chinese Academy of Sciences Beijing 100190 China Automotive Software Innovation Center (Chongqing) Chongqing 401331 China College of Information Science and Engineering Henan University of Technology Zhengzhou 450001 China Hami Vocational and Technical College Hami 839001 China

Level 3 automated driving systems require drivers to occasionally retake control, making it crucial to understand factors influencing takeover performance. This study investigates how single versus multiple non-driving-related tasks (NDRTs) affect driver behavior, perceptions, and takeover capability. Using a high-fidelity driving simulator with 32 participants, conditions varying NDRT types and task-switching frequency were examined. Results indicate that diverse NDRT engagement and frequent task switching significantly influence takeover performance. Moreover, our decision tree models highlighted the number of NDRT types and task-switching frequency as critical predictors of driver response effectiveness. These findings underscore the importance of accounting for task engagement diversity and switching behaviors in automated vehicle system design. This study provides practical implications for optimizing human-automation interactions and enhancing the safety of automated driving systems by managing drivers’ attentiveness for their in-cabin activities.

关键词： Applied sciences computer science Artificial intelligence

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