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Simulation and optimization of the effect of surface grooves on mineral particle separating behaviour of spiral concentrator 4

Simulation and optimization of the effect of surface grooves...

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4th international conference on Mechanical engineering, Intelligent Manufacturing, and Automation technology, MEMAT 2023

作者： Liu, Huizhong Wen, Chengyu Zhong, Junwei Wang, Zhiyan Zhu, Hejun Jiangxi University of Science and Technology Mechanical and Electrical Engineering Ganzhou341000 China Jiangxi Mining and Metallurgical Mechanical and Electrical Engineering Technology Research Center Ganzhou341000 China

ISBN: (纸本)9781510674820

the spiral concentrator is a kind of gravity separation equipment. the structure optimization of mineral processing equipment is the research focus and development direction of today's mineral processing field. In order to improve the sorting efficiency of the spiral concentrator, this paper proposes the optimization method of adding certain structural forms of grooves to the groove surface of the spiral chute. the RNG turbulence model, VOF multiphase flow model, and discrete-phase particle orbital model are used to carry out orthogonal simulation experiments on the sorting process of the spiral chute engraved groove model. the results show that the optimal solution for adding grooves to the spiral chute is 45 grooves, a 30° angle, 5 mm width, and 2 mm depth, which has the most significant sorting effect. In order to verify the feasibility of the optimal scheme, a prototype of the optimal structural scheme was fabricated in this study. Comparison experiments show that the average concentrate grade obtained from the experimental prototype is 2.92% higher, and the average concentrate recovery is 3.08% higher, which verifies the feasibility of the scheme. © 2024 SPIE.

关键词： Concentration (process)

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Research on factors influencing tennis winning probability: Using a LSTM model 5

Research on factors influencing tennis winning probability: ...

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5th international conference on Signal Processing and Computer Science, SPCS 2024

作者： Su, Chunxi Wang, Yuxuan School of Mathematics and Statistics Shandong University Shandong Weihai264209 China School of Economics and Management Beijing University of Technology Beijing100124 China

ISBN: (数字)9781510686731

ISBN: (纸本)9781510686724

In our paper, we developed a Long Short-Term Memory Model to explore the role of momentum in tennis performance, particularly within the context of the 2023 Wimbledon Championships. the Long Short-Term Memory Model describes changes in on-court situations through the difference in performance between the two sides, focusing on predicting changes in tennis matches. the model begins with a correlation analysis to identify effective indicators, then introducesa new dimension called "state" and employs a state- corrected LSTM network. It enhances the understanding of match dynamics and aids in more accurate player performance predictions. Based on this, the model further predicts the scoring rate for both sides and offers player suggestions. Our model accuracy up to 69.654%, which makes a more accurate predictions about the winning rate of the game than previous model (the Support Vector Machine model). through the model, our thesis presents a multifaceted view of momentum’s role in tennis, offering strategies for improving player performance and decision-making. the evaluation of these models demonstrates their practical applicability and effectiveness in a competitive sports environment. © 2025 SPIE.

关键词： Tennis

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Two Quality Control Algorithms for Echocardiographic Report Text Based on Natural Language Processing 5

Two Quality Control Algorithms for Echocardiographic Report ...

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5th international conference on Control, Robotics, and Intelligent System, CCRIS 2024

作者： Gan, Jianhong Yin, Yiduo Xie, Shenghua School of Software Engineering Chengdu University of Information Technology Chengdu610500 China Cardiovascular Ultrasound and Non-invasive Cardiology Department Sichuan Academy of Medical Sciences Sichuan Provincial People's Hospital Chengdu610072 China

ISBN: (数字)9781510685871

ISBN: (纸本)9781510685864

Effective quality control of ultrasound examination report provides guarantee for the accuracy of clinical ultrasound diagnosis. Two quality control methods of ultrasound diagnosis report text are presented in this paper to detect abnormal words and evaluate completeness of report text, respectively. One is the detection of abnormal words in report text based on deep learning model of Chinese word segmentation (CWS), which realizes the detection of various abnormal words in the report text, such as misspelled words, unwanted repeated words and non-professional words. In this paper, a BILSTM-CRF model combining character similarity features is proposed. the character similarity matrix is calculated by cosine similarity, and then the matrix is connected with the character encoding direction as the input data of the BiLSTM input layer. the other is Chinese sentence segment (CSS) in the ultrasonic report, mainly to cluster the clauses according to tissue and function of the *** experiment results show: (1) the improved deep learning model in this paper can accurately segment the text of echocardiography reports. the model with the most comprehensive effect on the verification set was selected as the final model of this paper based on the models trained with multiple sets of parameters. the accuracy rate of this model was 0.945, the recall rate was 0.939, and the F1 value was 0.947, all at a relatively high level. Can effectively detect abnormal words in the report. (2) the segmentation algorithm in this paper was used to test the results of automatic segmentation of echocardiographic reports combined with the results of manual segmentation by doctors. the accuracy of the dynamic segmentation method is above 90%, which can effectively segment the original echocardiogram report text according to the structure and function of the heart, and then be used to evaluate the completeness of the report description. © 2024 SPIE.

关键词： Echocardiography

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A Tool that Forms the Optimal Properties of the Surfaces of Sliding Contacts of Electrical Machines 5

A Tool that Forms the Optimal Properties of the Surfaces of ...

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5th IEEE international conference on Modern Electrical and Energy System, MEES 2023

作者： Drahobetskyi, Volodymyr Kostin, Viktor Arhat, Roman Moloshtan, Dmytro Pieieva, Iryna Mirokhin, Oleksiy Kremenchuk Mykhailo Ostrohradskyi National University Department of Mechanical Engineering Technology Kremenchuk Ukraine Kremenchuk Mykhailo Ostrohradskyi National University Department of Transport Technologies Kremenchuk Ukraine

ISBN: (纸本)9798350359787

the formation of the optimal properties of the surfaces of sliding contacts of electrical machines is extremely important. the solution to this problem provides an increase in the durability and operational reliability of modern machines. To the greatest extent, this applies to electric machines and electric vehicles, the operation of which is associated with the use of high-current sliding contacts. Brush-collector and brush-slip ring are two modifications of the sliding contacts of electrical machines. the integrated use of scientific and design and technical solutions makes it possible to provide a given resource for sliding contacts brush-slip ring. Electrodynamic processes, friction and wear processes to the greatest extent affect the operational reliability of the collector-slip ring assembly. Improving the design, the optimal choice of materials and the method of forming the surface layer are the main directions for ensuring a given resource of electrical machines. the latter is ensured by forming the optimal quality of the surfaces and material properties of the wear elements of the structure. To solve these problems, target functions and the structure of physical processes are formed. In addition, a relationship has been established between controlled and uncontrolled parameters. the defining parameters and response parameters are taken into account. this made it possible to formulate specifications for the design and development of a tool for finishing friction surfaces. the developed tool combines a combination of impact and friction processes on the surface being machined. © 2023 IEEE.

关键词： Friction

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Blind Image Super-Resolution Reconstruction Based on Dual Regression Network 5

Blind Image Super-Resolution Reconstruction Based on Dual Re...

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5th international conference on Computer Information Science and Artificial Intelligence, CISAI 2022

作者： Tian, Hongpeng Jiang, Shengzhou College of Computer Science and Technology Xi'an University of Science and Technology Xi'an China

ISBN: (纸本)9781510662520

Existing deep learning-based Super Resolution (SR) reconstruction algorithms achieve remarkable performance on images with known degradation. Most of the degradation models exists problems in self-adaptations when facing with the deviation of the degradation model of the image of the real scene, and the effect is not good. therefore, this paper proposes a blind image super-resolution reconstruction algorithm based on dual regression, which aims to solve the problem of poor performance of super-resolution networks in real scenes. Firstly, the closed-loop network is used to constrain the mapping space, and the optimal reconstruction function is found to improve the network reconstruction performance. Secondly, the attention mechanism is adopted into the residual block of feature extraction to expand the receptive field of the feature map, improve the reuse of features, and strengthen the reconstruction of high-frequency information. Finally, the frequency-domain blur kernel map estimates the downsampling kernel and reconstructs the low-resolution image, adaptively extracts the feature expression, enhances the ability to restore texture details, and reconstructs the real-world image better. © 2023 SPIE.

关键词： Textures

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Multi-scale network combined with multi-loss optimization for low-light image super-resolution reconstruction 5

Multi-scale network combined with multi-loss optimization fo...

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5th international conference on Computer Vision and data Mining, ICCVDM 2024

作者： Liu, Bofeng Yu, Haiyang Hu, Xiaojuan Li, Yanfeng School of Computer Science and Technology Changchun University of Science and Technology Jilin Changchun130022 China Key Laboratory of Photoelectric Measurement & Control and Optical Information Transfer Technology Ministry of Education Changchun University of Science and Technology Jilin Changchun130022 China

ISBN: (纸本)9781510682863

the proposed super resolution reconstruction method aims to address the issues of missing detailed information in low light environments and poor recovery of high frequency details in reconstructed images. To fully extract the retained features of low-light images, a multi-scale feature fusion learning network is introduced, which utilizes convolution to extract shallow features and then extracts deep features through multiple cascaded multi-scale feature extraction modules. Additionally, an attention mechanism is incorporated to adaptively learn the importance of each channel and finally fuse the obtained shallow and multi-scale features. Furthermore, perceptual loss and edge loss are integrated into the loss function to optimize the network for high frequency texture details in the recovered image. Experimental results demonstrate that this method yields clearer edge structures and texture details after super-resolution reconstruction of images acquired in low light environments, outperforming other existing methods both visually and objectively. © 2024 SPIE.

关键词： Convolutional neural networks

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Research on Visual Question Answering System Based on Deep Neural Network Model 5

Research on Visual Question Answering System Based on Deep N...

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5th international conference on Computer Information Science and Artificial Intelligence, CISAI 2022

作者： Tang, Xushuo Dept. of Electrical Information Shandong University of Science and Technology 17 Shengli Zhuang Road Jinan250031 China

ISBN: (纸本)9781510662520

With the rapid development of deep learning, computer vision, natural semantic processing and other technologies, Visual Question Answering (VQA) has gradually become to be an important research direction in the multimodal field. VQA technology has a wide range of application scenarios, such as multi-modal search, medical consultation, intelligent driving and so on, and has become the research hotspot and focus of scholars. Based on the classical CLEVR dataset, this paper builds different VQA prediction models by using the BilSTM model and different deep learning algorithms, including modnet, VGG and ResNet models. the results show that the hybrid model of ResNet and BiLSTM has the highest prediction accuracy, reaching 0.978. Compared with other algorithms, the accuracy is 1.3%, 2.5% and 2.7% higher than that of MobileMet, VGG19 and VGG16 models, which means that the hybrid model of resnet50 and BiLSTM is more effective in VQA tasks. At the same time, some problems and deficiencies of our model are analyzed and the future improvement direction is given. © 2023 SPIE.

关键词： Learning algorithms

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Research on X-Ray Film Identification Information Recognition Algorithm Based on Adaptive Spatial Feature Fusion 4

Research on X-Ray Film Identification Information Recognitio...

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4th international conference on Image Processing and Intelligent Control, IPIC 2024

作者： Liu, Chuan Lv, Zhigang Li, Liangliang Xu, Yuntao Wang, Bin Gao, Hui School of Weapon Science and Technology Xi'an Technological University Xi'an710021 China School of Electronic and Information Engineering Xi'an Technological University Xi'an710021 China School of Mechanical and Electrical Engineering Xi'an Technological University Xi'an710021 China

ISBN: (纸本)9781510682313

the identification information on industrial X-ray films is crucial for film classification and management. In order to solve the problem of low detection accuracy and high missed detection rate, this paper proposes a model for X-ray film identification information recognition, named XRF-YOLOv5 (X-ray Film-YOLOv5), based on Adaptive Spatial Feature Fusion (ASFF). Experimental findings indicate a notable enhancement in the efficacy of the XRF-YOLOv5 model in detecting identification data on industrial X-ray films. In practical application scenarios, compared to the original YOLOv5 model, it exhibits higher recognition accuracy, higher confidence in recognition, and greater robustness. therefore, XRFYOLOv5 meets the basic requirements for industrial X-ray film identification information recognition. © 2024 SPIE.

关键词： X ray films

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4th international conference on big data and Security, ICBDS 2022

4th International Conference on Big Data and Security, ICBDS...

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4th international conference on big data and Security, ICBDS 2022

ISBN: (纸本)9789819932993

the proceedings contain 54 papers. the special focus in this conference is on big data and Security. the topics include: Research on the Evolution of New Energy Industry Financing Ecosystem Under the Background of big data;a Survey of the State-of-the-Art and Some Extensions of Recommender System Based on big data;an Innovative AdaBoost Process Using Flexible Soft Labels on Imbalanced big data;Feature Fusion Based IPSO-LSSVM Fault Diagnosis of On-Load Tap Changers;graphlet-Based Measure to Assess Institutional Research Teams;Logical Relationship Extraction of Multimodal South China Sea big data Using BERT and Knowledge Graph;research on Application of Knowledge Graph in War Archive Based on big data;Semi-supervised Learning Enabled Fault Analysis Method for Power Distribution Network Based on LSTM Autoencoder and Attention Mechanism;fault Detection Method for Power Distribution Network Based on Ensemble Learning;Research on data-Driven AGC Instruction Execution Effect Recognition Method;factors Influencing Chinese Users’ Willingness to Pay for O2O Knowledge Products Based on Information Adoption Model;a Survey of Integrating Federated Learning with Smart Grids: Application Prospect, Privacy Preserving and Challenges Analysis;application of the Fusion Access technology of Carrier and 5G in Power Communication;Muscle Fatigue Classification Based on GA Optimization of BP Neural Network;research on Typical Scenario Generation Based on Distribution Network data Mining and Improved Policy Clustering;a data-Driven and Deep Learning-Based Economic Evaluation Method for New Power System Distribution Grid;study on Random Generation of Virtual Avatars Based on big data;an Explainable Optimization Method for Assembly Process Parameter.

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Design and application of an intelligent monitoring and early warning system for bioremediation of coking contaminated sites 8

Design and application of an intelligent monitoring and earl...

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8th international conference on Electronic technology and Information Science, ICETIS 2023

作者： Wang, XiaoWen Wang, WenSi Yang, NiYun Wang, XiaoWei Wang, FuYang Wei, XiaoShu Ji, YanPing Chen, WangXin Zheng, MengYi Faculty of Information Technology BJUT China Chinese Academy of Environmental Sciences China School of Sociology China University of Political Science and Law China

ISBN: (纸本)9781510666535

the soil bioremediation process of coking sites is complex, the site environment is harsh, and the project period is long. Compared with the fields of water and air pollution monitoring, the informatization level of soil bioremediation project is low, and it is urgent to improve the digitalization and intelligence. through the design of an online monitoring and electronic inspection system for the bioremediation process of coke contaminated soil and the development of intelligent early warning software, a study of information-specific technologies and data models for coke contamination remediation has been conducted. this paper focuses on three core elements of this field, including multidimensional data collection technologies such as Internet of things and image recognition, big data processing technologies realized by relying on communication modules and cloud platform databases, and the construction of a neural network computational model for the soil bioremediation process. the information system has been tried out in the pilot process of soil bioremediation, realizing information management functions such as monitoring the operation status of sensors, inspection management, equipment's own status management, online monitoring and alarming of soil bioremediation parameters, and trend prediction of future soil parameters, forming a new generation of intelligent supervision system for soil bioremediation sites. © 2023 SPIE.

关键词： Soils

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