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11th International Conference on information Systems and Computing technology, ISCTech 2023

作者： Liu, Yingli Zhang, Guangtao Shen, Tao Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650093 China Kunming University of Science and Technology Yunnan Key Laboratory of Computer Technologies Application Kunming650500 China

ISBN: (纸本)9798350342406

Table, as an information carrier with high information density and direct display form, are widely used in scientific literature and social production documents. Accurately identifying tables from various documents will significantly promote the intelligent application of documents. The table's structural information is crucial for comprehending how the text content in the table relates to one another, but teaching a computer to fully understand a table's structure is still a very difficult undertaking. In this research work, we provided a unique edge-based method to recognize table structures. Specifically, we define the inter-cell relationships as an edge prediction problem and leverage graph convolutional networks to learn representations of the cells. These learned representations are then utilized to directly predict the connections between the cells. The experimental results conducted on three publicly available datasets for table structure recognition provide compelling evidence supporting the feasibility and usefulness of our presented methodology. © 2023 IEEE.

关键词： Forecasting

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Multi-objective performance prediction based on a self-constructed Al-Si alloy dataset 11

Multi-objective performance prediction based on a self-const...

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11th International Conference on information Systems and Computing technology, ISCTech 2023

作者： Hu, Dan Liu, Yingli Shen, Tao Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650093 China Kunming University of Science and Technology Yunnan Key Laboratory of Computer Technologies Application Kunming650500 China

ISBN: (纸本)9798350342406

The combination of data-driven approaches and machine learning techniques has changed the design approach for new materials, propelling materials science research into the realm of the fourth paradigm. Researchers in the field of materials science have increasingly focused on utilizing machine learning methods to uncover the underlying nonlinear relationships within material data. However, there is currently limited research in the field of aluminum-silicon alloys regarding the prediction of alloy performance based on the composition-process-structure relationship. Additionally, there is a lack of data sharing in the aluminum-silicon alloy domain. Therefore, this study proposes a methodology. Firstly, an aluminum-silicon alloy dataset is constructed by mining relevant information from materials literature. Then, high-dimensional features in the dataset are subjected to feature selection techniques for dimensionality reduction. Subsequently, a multilayer perceptron model is applied to investigate the relationship between input features such as alloy composition, preparation process, and microstructural parameters, and output features such as yield strength, ultimate tensile strength, and elongation, enabling performance prediction. © 2023 IEEE.

关键词： Feature Selection

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Research on Handwritten Marking Localization Method for Hot Rolled Steel Coils 3

Research on Handwritten Marking Localization Method for Hot ...

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3rd International Conference on Image Processing, Computer Vision and Machine Learning, ICICML 2024

作者： Jia, Bowen Kunming University of Science and Technology School of Information Engineering and Automation Kunming China

ISBN: (纸本)9798350355413

Aiming at the problem that the handwritten markings of steel coils in the natural scenario of hot rolled steel coils warehouse in the travelling link using the existing text localization method have serious distortion and blurring, thus leading to a high leakage rate, a precise localization method for the handwritten markings of hot rolled steel coils is proposed. The method is based on Nanodet-m improved Coord-Nano steel coil handwritten labeling localization model. First, the backbone network perceives the spatial information of the feature map by introducing CoordConv and SAConc, which improves the adaptability and accuracy of the network in dealing with features of different scales and complexities. Then, the PfAAMLayer attention mechanism is introduced to produce a self-focusing effect on the features, which improves the architectural performance. Finally, the bottom-up path enhancement module is utilized to propagate the strong localization features in the shallow network to the deep network, so as to accurately locate the handwritten marking region of the steel roll from the complex environment. Experimental results show that the network model proposed in this paper achieves 97.7% localization accuracy for steel roll handwritten markers by training and validation on real steel roll handwritten markers image *** with the basic Nanodet-m, YOLOv7tiny and YOLOv8n, the localization accuracy of handwritten marks on steel rolls is improved by 1.6%, 0.8% and 0.2%. © 2024 IEEE.

关键词： component CoordConv NanoDet-m Object detection steel coil labeling

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Linguistic feature template integration for Chinese-Vietnamese neural machine translation

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Frontiers of Computer science 2022年第4期16卷 223-225页

作者： Zhiqiang YU Yantuan XIAN Zhengtao YU Yuxin HUANG Junjun GUO Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming 650500China School of Mathematics and Computer Science Yunnan Minzu UniversityKunming 650500China Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and TechnologyKunming 650500China

1 Introduction and main contributions Template-based approaches have achieved significant progress in low-resource neural machine translation(NMT)recently[1],such as the efficient works,NMT-GTM[2],SoftPrototype[3],***,most previous works only retrieve target sentence as template to generate translation,neglecting the utilization of linguistic feature that contained in the source sentence and template.

关键词： translation template such

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A Research on Intelligent Recommendation Algorithms Based on Federated Learning 3

A Research on Intelligent Recommendation Algorithms Based on...

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3rd International Conference on Advanced Algorithms and Neural Networks, AANN 2023

作者： Wu, Yue School of Information Engineering and Automation Kunming University of Science and Technology Yunnan Kunming650504 China

ISBN: (纸本)9781510668355

Federated learning is a promising new paradigm for privacy protection. By dispersing training data storage locally rather than centrally constructing large-scale datasets, federated learning provides a mechanism for training models that protects privacy for various data-hungry applications, such as recommendation algorithms for mitigating information overload. This article implements a family of algorithms with common characteristics in a federated learning framework for model parameter transfer. Through comparative experiments, the performance differences of these algorithms under this federated learning framework are examined, and their model performance is compared and analyzed under their respective centralized learning forms. The conclusion is that the algorithm family combined with neural networks has higher performance and is more stable in this federated learning framework, with less performance loss. © 2023 SPIE.

关键词： Large dataset

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A Multi-objective Antenna Optimization Method Based on Preferred Parameter Spaces

A Multi-objective Antenna Optimization Method Based on Prefe...

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2024 Photonics and Electromagnetics Research Symposium, PIERS 2024

作者： Dou, Jiangling Lin, Siyu Song, Jian Wang, Qingwang Shen, Tao Kunming University of Science and Technology School of Information Engineering and Automation Kunming650500 China Kunming University of Science and Technology Yunnan Key Laboratory of Computer Technologies Application Kunming650500 China Kunming University of Science and Technology Graduate School Kunming650500 China

ISBN: (纸本)9798350375909

Machine learning has been successfully used in the field of multi-objective antenna design, enabling the enhancement of antenna performance and optimizing efficiency. However, the prediction within an exceptionally vast parameter space imposes significant demands on machine learning algorithms. Moreover, minor adjustments in dimensions can bring about significant alterations in antenna performance, which renders simultaneous optimization for all objectives exceedingly challenging. To solve the multi-objective antenna optimization problem, a multi-objective antenna optimization method based on a preferred parameter space is proposed. Specifically, this method utilizes the KNN algorithm to preliminarily optimize the antenna and acquire a high-quality dataset. Subsequently, the sensitivity of ten selected parameters based on the electromagnetic (EM) simulation results is calculated by the XGBoost algorithm. The value of the parameter sensitivity is acquired by averaging ten calculations. The top four ranked parameters are designated as variables while the rest are fixed as constants. This approach reduces the number of parameters for subsequent optimization, thus greatly improving the subsequent prediction accuracy while ensuring the antenna performance. Finally, the variables derived from XGBoost are input into the fruit-fly optimization algorithm (FOA) to find the near-optimal solution. Hence, the task of parameter optimization under the multi-objectives of the impedance bandwidth and circular polarization characteristics can be effectively accomplished. To further validate its performance, the proposed algorithm is applied to optimize the S-band miniaturized broadband circularly polarized antenna. Compared to the results obtained by electromagnetic simulation only, the optimized results exhibit a 17.95% improvement of impedance bandwidth and a 42.86% enhancement of axial ratio bandwidth. Numerical outcomes validate that the proposed method achieves multi-objective o

关键词： Circular polarization

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Analysis of Temperature Distribution in Microwave Heating Based on Finite Difference Method

Analysis of Temperature Distribution in Microwave Heating Ba...

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2024 International Conference on Energy and Electrical engineering, EEE 2024

作者： Yang, Biao Liu, Bingyan Yang, Ying Kunming University of Science and Technology Faculty of Information Engineering and Automation Key Laboratory of Unconventional Metallurgy of Ministry of Education Kunming China Kunming University of Science and Technology The Higher Educational Key Laboratory for Industrial Intelligence and Systems of Yunnan Province Kunming China

ISBN: (纸本)9798350341768

Microwave heating entails the interaction of multiple, interconnected physical fields. Traditional numerical methods cannot directly compute the temperature distribution of materials during microwave heating. This paper analyzes two calculation methods: the explicit Euler difference method and the Crank-Nicolson difference method. The performance of these two methods in simulating the temperature distribution of deionized water under microwave heating is compared. Through simulation experiments, it is demonstrated that both methods yield results within a high accuracy range. The explicit Euler difference method has slightly lower computational accuracy but is simple and fast, while the Crank-Nicolson difference method offers higher precision at the expense of greater computational complexity. Depending on specific requirements, the suitable method can be selected to simulate the microwave heating process, thereby supporting the application of this technology. © 2024 IEEE.

关键词： Deionized water

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An Exposure Meter of Lijiang Fiber-fed High-Resolution Spectrograph

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Research in Astronomy and Astrophysics 2023年第11期23卷 60-66页

作者： Xiao-Guang Yu Kai-Fan Ji Xi-Liang Zhang Liang Chang Yun-Fang Cai Ying Qin Zhen-Hong Shang Yunnan Observatories Chinese Academy of SciencesKunming 650011China Key Laboratory for the Structure and Evolution of Celestial Objects Chinese Academy of SciencesKunming 650216China University of Chinese Academy of Sciences Beijing 100049China Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming 650500China

In 2016,an exposure meter was installed on the Lijiang Fiber-fed High-Resolution Spectrograph to monitor the coupling of starlight to the science fiber during *** on it,we investigated a method to estimate the exposure flux of the CCD in real time by using the counts of the photomultiplier tubes(PMT)of the exposure meter,and developed a piece of software to optimize the control of the exposure ***,by using flat-field lamp observations,we determined that there is a linear and proportional relationship between the total counts of the PMT and the exposure flux of the ***,using historical observations of different spectral types,the corresponding relational conversion factors were determined and obtained ***,the method was validated using actual observation data,which showed that all values of the coefficient of determination were greater than ***,software was developed to display the counts of the PMT and the estimated exposure flux of the CCD in real-time during the observation,providing a visual reference for optimizing the exposure time control.

关键词： telescopes instrumentation:spectrographs instrumentation:photometers

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Design of P Band Filter Antenna with High Out-of-Band Suppression

Design of P Band Filter Antenna with High Out-of-Band Suppre...

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2024 Photonics and Electromagnetics Research Symposium, PIERS 2024

作者： Dou, Jiangling Yuan, Yinsu Song, Jian Wang, Qingwang Shen, Tao Kunming University of Science and Technology School of Information Engineering and Automation Kunming650500 China Kunming University of Science and Technology Yunnan Key Laboratory of Computer Technologies Application Kunming650500 China Kunming University of Science and Technology Graduate School Kunming650500 China

ISBN: (纸本)9798350375909

P-band antennas offer tremendous potential in various fields, including remote sensing, communication, and radar applications. However, It is crucial to enhance their effectiveness in these domains that the current challenges in the P-band, particularly wide bandwidth and exceptional out-of-band suppression be achieved. This paper aims to introduce an efficient design scheme for a high-efficiency, high out-of-band suppression P-band filter antenna. The antenna structure comprises a Y-shaped feeding network, upper and lower parallel dielectric plates, a vertical dielectric plate, a central metal plate, and a pair of microstrip patches. The bottom feeding network employs a Y-shaped feeding network. The coupling of the antenna was effectively controlled and the good bandwidth and impedance matching have been achieved. In order to achieve a wider bandwidth and lower return loss for the antenna, slotting technology was employed on the semi-circular radiation patch. The introduction of a vertical metal plate enhances filtering performance of antenna. Additionally, there are radiation zeros at 0.68 GHz and 1.43 GHz, high-frequency selectivity is imparted and signal reflection losses are effectively reduced. Key performance indicators include a filter antenna center frequency of 0.75 GHz, a -10 dB impedance bandwidth of 32.9% (0.89 GHz-1.24 GHz). In the upper stopband (0.5 GHz-0.8 GHz), the suppression level exceeds 20 dB, while in the lower stopband (1.1 GHz-1.8 GHz), suppression level exceeds 15 dB. Significant suppression characteristics are observed in the 0.5 GHz-0.8 GHz and 1.1 GHz-1.8 GHz frequency ranges. Design elements such as the semi-circular radiating patch, slotting technology, and rectangular slots on the substrate have been employed in the antenna. The suppression level, frequency selectivity had been enhance of antenna. Simulation results indicate a gain of 7.06 dB, overall efficiency beyond 95%, co-pol superior to cross-pol by more than 35 dB, and antenna

关键词： Slotting

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Research RSA Accumulator-Based Stateless Blockchain Optimisation for Smart Contracts

Research RSA Accumulator-Based Stateless Blockchain Optimisa...

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2023 International Conference on Cyber Security, Artificial Intelligence, and Digital Economy, CSAIDE 2023

作者： Zhuang, Jinyu Fan, Hongbo Li, Xiang Faculty of Information Engineering and Automation Kunming University of Science and Technology Yunnan Kunming650500 China Yunnan Key Laboratory of computer technology application Kunming University of Science and Technology Yunnan Kunming650500 China

ISBN: (纸本)9781510666597

Scalability has grown more important as blockchain technology is adopted. This study introduces RSA-accumulator-based stateless blockchain performance optimization. Verifiable computing technology and distributed design compress node state data and prove smart contract validity, while a new smart contract execution logic and transaction verification scheme solve the problem of transaction verification and execution under stateless conditions, increasing system throughput. The technique reduces consensus node storage and improves throughput compared to Ethereum blockchains, according to experiments. This study examines the scheme's concept, implementation, and blockchain scalability potential. © 2023 SPIE.

关键词： Smart contract

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