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8th International Conference on Intelligent Computing and Signal Processing, ICSP 2023

作者： Li, Yao Huang, ZhangQin Gao, Han Huang, Ling Beijing University of Technology Beijing Engineering Research Center for IoT Software and System Beijing China

ISBN: (纸本)9798350302455

Deformation monitoring data can most intuitively reflect the current movement process of the landslide and is likewise the most essential and effective warning feature of the landslide warning model. To solve the current problem that it is difficult to identify the uniform deformation phase and adjust it dynamically in time, which leads to the high false alarm and leakage rate of the early warning algorithm, we adopt the Pauta criterion and the Lagrange interpolation method fused with the improved adaptive Kalman filter to improve the accuracy of the original monitoring data, propose a real-time determination method of uniform deformation phase based on statistical analysis, and construct a process-oriented dynamic early warning algorithm by examining the normal distribution of the second-order derivative values of the cumulative displacement curve and the changing trend of the linear regression coefficient of determination. The experimental results show that the research method can effectively reduce the abnormal fluctuation interference of data, accurately discriminate the uniform deformation phase, improve the early warning accuracy of the creep tangent angle warning model, and has excellent application value for the subsequent realization of systematic and automated real-time monitoring and warning. © 2023 IEEE.

关键词： Landslides

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3D Visualization of Forest Fire Spread Model Based on Cellular Automata 8

3D Visualization of Forest Fire Spread Model Based on Cellul...

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8th International Conference on Computer and Communication Systems, ICCCS 2023

作者： Hou, Zeqing Sun, Yu Cai, Mingyu Beijing University of Technology Beijing Engineering Research Center for IOT Software and Systems Beijing China

ISBN: (纸本)9781665456128

Whereas the traditional forest fire spread model cannot clearly and dynamically display the fire spread process, this paper optimizes the cell structure and evolution rules of cellular automata (CA) in the traditional forest fire spread model to improve the simulation accuracy and develops a forest fire spread simulation system using Unity 3D technology, which realizes the dynamically display and 3D visualization of forest fire spread process. It plays an important role in forest fire prevention and extinguishing. © 2023 IEEE.

关键词： Cellular automata

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Deletion and Recovery Scheme of Electronic Health Records Based onMedical Certificate Blockchain

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Computers, Materials & Continua 2023年第7期76卷 849-859页

作者： Baowei Wang Neng Wang Yuxiao Zhang Zenghui Xu Junhao Zhang School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044JiangsuChina Engineering Research Center of Digital Forensics Ministry of EducationNanjing210044JiangsuChina

The trusted sharing of Electronic Health Records(EHRs)can realize the efficient use of medical data *** speaking,EHRs are widely used in blockchain-based medical data *** are valuable private assets of patients,and the ownership belongs to *** recent research has shown that patients can freely and effectively delete the EHRs stored in hospitals,it does not address the challenge of record sharing when patients revisit *** order to solve this problem,this paper proposes a deletion and recovery scheme of EHRs based on Medical Certificate *** paper uses cross-chain technology to connect the Medical Certificate Blockchain and the Hospital Blockchain to real-ize the recovery of deleted *** the same time,this paper uses the Medical Certificate Blockchain and the InterPlanetary File System(IPFS)to store Personal Health Records,which are generated by patients visiting different medical *** addition,this paper also combines digital watermarking technology to ensure the authenticity of the restored electronic medical *** the combined effect of blockchain technology and digital watermarking,our proposal will not be affected by any other rights throughout the *** analysis and security analysis illustrate the completeness and feasibility of the scheme.

关键词： Electronic health records cross-chain medical certificate blockchain data deletion and recovery

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Design of Real-time Centroid Extraction System for Shack-Hartmann Sensor Based on FPGA 3

Design of Real-time Centroid Extraction System for Shack-Har...

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3rd IEEE International Conference on Electronic technology, Communication and Information, ICETCI 2023

作者： Xiaocui, Shen Zhangqin, Huang Han, Gao Beijing University of Technology Beijing Engineering Research Center for IoT Software and Systems Beijing China

ISBN: (纸本)9798350398410

Hartmann wavefront sensor is applied widely in adaptive optics systems. Considering the real-time performance requirements and processing amount of Hartmann sensors in computing the centroids of points, this article proposes an FPGA-based real-time image processing and centroid extraction system. The system adopts FPGA as the core processor and uses the connected domain labeling algorithm and the gray centroid method to complete the centroid calculation. In addition, the calculation results are output simultaneously through multiple DAs to drive the device under test to achieve image wavefront restoration. At the same time, the image data is uploaded to the host computer in real-time through the Ethernet interface. The system has excellent performance in real-time image processing, image output quality, and system control stability. Experiments show that it is an efficient technical means of providing real-time wavefront processing measurement for the Hartmann sensor in various application scenarios, such as adaptive optical correction. © 2023 IEEE.

关键词： Field programmable gate arrays (FPGA)

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GAPSR: Monocular 3D Pose and Shape Reconstruction Based on Graph Networks and Attention Predictive Modeling 4

GAPSR: Monocular 3D Pose and Shape Reconstruction Based on G...

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4th International Conference on Artificial Intelligence and Computer engineering, ICAICE 2023

作者： Yue, Shuolei Beijing Engineering Research Center for IoT Software and Systems Beijing University of Technology Beijing China

ISBN: (纸本)9798400708831

Reconstructing urban traffic dynamics in three dimensions is crucial for effective traffic management. However, current research often neglects the posture and shape reconstruction of vehicles within traffic scenes. This paper introduces GAPSR, an innovative method addressing the challenge of monocular 3D pose and shape reconstruction, with a focus on vehicle-related information. Utilizing graph networks, our approach extracts unstructured logical topological features to enhance the expressiveness of 2D features. Attention prediction modeling is then introduced, considering the correlation between detected objects and vehicle shapes, as well as the scene context and road environment. In summary, our proposed method advances monocular 3D pose and shape reconstruction, as evidenced by experiments demonstrating its effectiveness across diverse datasets. This work provides substantial support for future research in traffic scene understanding and autonomous driving. © 2023 ACM.

关键词： Vehicles

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Research on Ink Style Image Generation Based on Deep Learning

Research on Ink Style Image Generation Based on Deep Learnin...

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2023 International Conference on Electronic Information engineering and Data Processing, EIEDP 2023

作者： Zheng, Tianyi Huang, Zhangqin Zhang, Runmin Beijing Engineering Research Center for IoT Software and Systems Beijing University of Technology Beijing China

ISBN: (纸本)9781510666160

Most of the current existing style transfer methods are based on photographs or Western paintings. Due to the inherent differences between Chinese and Western paintings, direct application of existing algorithms cannot generate satisfactory style transfer results for Chinese ink paintings. Accordingly, I propose a new feedforward style transfer method [1], called inkStyle, which uses a draw Network to transfer global style patterns at low resolution and a higher resolution details Networks to modify local style patterns in a pyramidal manner based on the multi-level Laplacian filtering output of the content image. The experimental results show that the method in the paper performs better and produces better visual results. © 2023 SPIE.

关键词： Deep learning

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Efficient Relaxed Functional Dependency Discovery with Minimal Set Cover 40

Efficient Relaxed Functional Dependency Discovery with Minim...

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40th IEEE International Conference on Data engineering, ICDE 2024

作者： Ding, Xiaoou Liu, Yida Wang, Hongzhi Wang, Chen Song, Yichen Yang, Donghua Wang, Jianmin School of Computer Science and Technology Harbin Institute of Technology China National Engineering Research Center for Big Data Software EIRI Tsinghua University China

ISBN: (纸本)9798350317152

Assessing data quality through Functional Depen-dencies (FDs) is a crucial aspect of data governance. However, with the diverse range of data sources and the exponential growth in data volume, exact FDs can sometimes be impractical for real-world applications. In contrast, relaxed functional dependencies (RFDs), which allows for some flexibility in attribute value comparisons, demonstrates greater adaptability and flexibility for big data scenarios. To address the efficient discovery of RFDs, this paper proposes a novel mining method to supplement the current research gaps. By establishing a difference table for tuples, we transform the problem into a specialized minimal set covering problem. Additionally, we introduce two optimization strategies: reducing the time complexity of enumerating the left-hand side of the base RFDs to 0 (1) and decreasing the search complexity for feasible LHS attributes and threshold candidates from O(2m-l) to O(1.5m-1). We rigorously proof that our mining approach guarantees the identification of validity and minimal RFDs. Experiments on nine real-world datasets reveal that our method significantly improves efficiency compared to existing techniques. Furthermore, it uncovers more concise and higher-quality RFDs. Importantly, the RFDs extracted through our methodology exhibit better performance in downstream cleaning tasks. © 2024 IEEE.

关键词： Quality management

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Design and Performance Analysis of LoRa for Smart Forestry Video Services 8

Design and Performance Analysis of LoRa for Smart Forestry V...

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8th International Conference on Intelligent Computing and Signal Processing, ICSP 2023

作者： Huang, Zhangqin Gao, Han Yang, Huapeng Huang, Ling Beijing University of Technology Beijing Engineering Research Center for IoT Software and System Beijing China

ISBN: (纸本)9798350302455

Camera monitoring is more intuitive than other environmental sensors, and it is of great significance for predicting, preventing, and tracing fire events in smart forestry. This paper analyzes the data transmission tasks and capabilities of LoRa in video services at the network edge, based on a practical smart forestry project. We propose the design method of intelligent hardware at the network edge and the optimization method of LoRa communication. We demonstrate the communication performance between LoRa terminals and LoRa gateways through practical deployment experiments, proving that the use of LoRa with a higher rate for wireless communication networking and reporting of video analysis results can meet the requirements of smart forestry and achieve beneficial effects. © 2023 IEEE.

关键词： Internet of things

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Transformer-based Siamese Neural Network Face Verification Method 8

Transformer-based Siamese Neural Network Face Verification M...

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8th International Conference on Intelligent Computing and Signal Processing, ICSP 2023

作者： Qiu, Shen Yang, HuaPeng Huang, ZhangQin Shen, DiYuan Beijing University of Technology Beijing Engineering Research Center for IoT Software and System Beijing China

ISBN: (纸本)9798350302455

Face verification, as a key part of person intelligence tracing, aims to determine whether the same person is in two face photos, which can be approximately transformed into a binary classification problem. In this paper, the siamese neural network architecture is adopted as the overall structure of the method, and the traditional bacbone network generally uses a convolutional neural network, this paper will use Vision Transformer as the backbone network as the method. Compared with convolutional neural network, its multi-headed attention mechanism can better focus on the larger sensory field and extract face features, which can then better perform face verification, while Binary cross-entropy is used as the loss function. After the validation of the private dataset, the model can recognize faces well and has excellent validation effect, which is of great value for the field of human intelligence tracing. © 2023 IEEE.

关键词： Convolutional neural networks

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TSDDISCOVER: Discovering Data Dependency for Time Series Data 40

TSDDISCOVER: Discovering Data Dependency for Time Series Dat...

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40th IEEE International Conference on Data engineering, ICDE 2024

作者： Ding, Xiaoou Li, Yingze Wang, Hongzhi Wang, Chen Liu, Yida Wang, Jianmin School of Computer Science and Technology Harbin Institute of Technology China Tsinghua University National Engineering Research Center for Big Data Software EIRI China

ISBN: (纸本)9798350317152

Intelligent devices often produce time series data that suffer from significant data quality issues. While the utilization of data dependency in error detection and data repair has been somewhat beneficial, it remains inadequate in accurately representing the data quality of time series datasets. In recognition of the obvious characteristics inherent in time series data, we introduce a novel data dependency, termed TSDD. It effectively captures the contextual relationships embedded within multivariate time series, thereby enhancing the semantic richness of data quality representations. We analyze the complexity of both implication and consistency problems for TSDD reasoning, and develop TSDD discovery algorithm TSDDISCOVER, which consists of functional structure discovery, allowable error bound determination, and validation of TSDD patterns. Experimental results on real-life datasets verify TSDDISCOVER efficiently discovers high-quality TSDD patterns. In comparing the performance of TSDD-based error detection with several leading data quality constraints, our findings reveal that the former achieves an average improvement of 12% in accuracy and 30% in the F1 score over other dependency-based detection methods. © 2024 IEEE.

关键词： Semantics

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