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Teaching innovation results based on double helix teaching strategy and ADDIE model- Take the Big Data and visualization course for example 14

Teaching innovation results based on double helix teaching s...

引用

14th International Conference on information technology in Medicine and Education, ITME 2024

作者： Luo, Jia Li, Mingming Guiyang College of Humanities and Technology & Information Engineering Guiyang China

ISBN: (纸本)9798350356670

"Big Data Analysis and Visualization"course focuses on innovative teaching concepts and content, integrating key skills of data science and ideological and political education. This course not only focuses on teaching professional knowledge of big data processing, analysis and visualization, but also emphasizes the importance of ideological and political education to cultivate students' social responsibility and ethical concepts in the field of data science. According to the teaching pain points of students' weak data thinking ability, lack of practical project training and ideological and political thinking in this course, this paper proposes to reconstruct the "internal spectrum"and "external spectrum"of course design based on the double helix teaching strategy and ADDIE teaching mode, and the teaching objectives of the course clearly show its content structure and its connection with other fields of data science. Guided by the needs of enterprise talents, with the purpose of applying what we have learned and scenario-based case teaching, we will raise our teaching objectives and thinking to a higher level. Through online and offline mixed teaching, we will conduct reality training, practical projects and practical tests to create a composite, application-oriented and innovative talent training model that Adapts to the new situation and has the latest thinking and skills. Through practical teaching and case studies, students' engineering practice innovation ability has been significantly improved, and they have achieved excellent results in various national and provincial data science competitions, demonstrating the remarkable effect of the course in cultivating students' synthesis ability,Cultivate data science application talents with innovative thinking and cross-border integration. © 2024 IEEE.

关键词： Data Science

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Research on audio characteristics based on auditory characteristics and instantaneous frequency 14

Research on audio characteristics based on auditory characte...

引用

14th International Conference on information technology in Medicine and Education, ITME 2024

作者： Liu, Wencai Song, Mingming Guiyang Institute of Humanities and Technology College of Big Data and Information Engineering Guiyang China Guiyang Institute of Humanities and Technology College of Civil Engineering and Architecture Guiyang China

ISBN: (纸本)9798350356670

This paper proposes a novel audio feature extraction method that integrates auditory characteristics and instantaneous frequency, aiming to enhance the representation of audio signals. While traditional Mel-scale Frequency Cepstral Coefficient features partially capture human auditory perception, their filter shape significantly deviates from the actual auditory filters. To address this limitation, we introduce the GammaTone filter in conjunction with equivalent rectangular bandwidth scale and instantaneous frequency, resulting in two new feature sets: GammaTone Frequency Cepstral Coefficients and Instantaneous Frequency GammaTone Frequency Cepstral Coefficients. Experimental results demonstrate that both GammaTone Frequency Cepstral Coefficients and Instantaneous Frequency GammaTone Frequency Cepstral Coefficients exhibit superior capabilities in representing non-speech audio signals. © 2024 IEEE.

关键词： Wiener filtering

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Teaching innovation results based on double helix teaching strategy and ADDIE model- Take the Big Data and visualization course for example

Teaching innovation results based on double helix teaching s...

引用

IEEE International Symposium on information (IT) in Medicine and Education, ITME

作者： Jia Luo Mingming Li Guiyang College of Humanities and Technology&Information Engineering Guiyang China

ISBN: (数字)9798350356670

ISBN: (纸本)9798350356687

"Big Data Analysis and Visualization" course focuses on innovative teaching concepts and content, integrating key skills of data science and ideological and political education. This course not only focuses on teaching professional knowledge of big data processing, analysis and visualization, but also emphasizes the importance of ideological and political education to cultivate students' social responsibility and ethical concepts in the field of data science. According to the teaching pain points of students' weak data thinking ability, lack of practical project training and ideological and political thinking in this course, this paper proposes to reconstruct the "internal spectrum" and "external spectrum" of course design based on the double helix teaching strategy and ADDIE teaching mode, and the teaching objectives of the course clearly show its content structure and its connection with other fields of data science. Guided by the needs of enterprise talents, with the purpose of applying what we have learned and scenario-based case teaching, we will raise our teaching objectives and thinking to a higher level. Through online and offline mixed teaching, we will conduct reality training, practical projects and practical tests to create a composite, application-oriented and innovative talent training model that Adapts to the new situation and has the latest thinking and skills. Through practical teaching and case studies, students' engineering practice innovation ability has been significantly improved, and they have achieved excellent results in various national and provincial data science competitions, demonstrating the remarkable effect of the course in cultivating students' synthesis ability,Cultivate data science application talents with innovative thinking and cross-border integration.

关键词： Training Technological innovation Analytical models Pain Education Employment Data visualization Data science Big Data Data models

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FastDTW-Encoded Spatial-temporal Attention Dual Graph Convolutional Network for Traffic Flow Prediction 14

FastDTW-Encoded Spatial-temporal Attention Dual Graph Convol...

引用

14th International Conference on information technology in Medicine and Education, ITME 2024

作者： Shen, Bingqi Chen, Linlong Yang, Nan Guiyang Institute of Humanities and Technology College of Big Data and Information Engineering Guiyang550025 China

ISBN: (纸本)9798350356670

Addressing the insufficient extraction of traffic network topology features and inadequate topological feature extraction and spatial-temporal dependency modeling in traffic flow prediction, we construct a dual graph convolutional network algorithm based on fast Dynamic Time Warping (fastDTW) and spatial-temporal attention mechanism (STADGCN). Firstly, the spatial-temporal attention module is employed to capture the dynamic influence weights of the spatial-temporal dimensions. Secondly, fastDTW is utilized to measure similarity between nodes in the traffic network, enhancing topology-based feature extraction through adjacency matrix encoding. Subsequently, dual graph convolutional and temporal convolutional networks are constructed to algorithm spatial-temporal dependencies. Finally, the prediction performance of the STADGCN algorithm is verified by a weighted fusion of recent, daily, and weekly components based on real highway network detector data. Experimental results demonstrate that compared to ARIMA, VAR, FNN, GAT, GCN, GWNet, STGCN, and ASTGCN, STADGCN exhibits superior performance with MAPE reductions of 81.97%, 64.52%, 78.85%, 69.44%, 54.17%, 8.33%, 8.33%, and 26.67% respectively, on the pems08 dataset. © 2024 IEEE.

关键词： Network theory (graphs)

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Optimal survey line for multibeam planning based on geometric shortest path model 4

Optimal survey line for multibeam planning based on geometri...

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4rth International Conference on Applied Mathematics, Modelling, and Intelligent Computing, CAMMIC 2024

作者： Wang, Fei Li, Xingxin Pan, Chunlin Zhang, Mengwei Yang, Caiyun College of Big Data and Information Engineering Guiyang Institute of Humanities and Technology Guiyang550025 China

ISBN: (纸本)9781510681637

In view of the problem of multibeam survey line in the 2023 Higher Education Cup China Undergraduate Mathematical Contest in Modeling, this paper proposes an optimal survey line method for multibeam planning based on the geometric shortest path model. Through this method, the coverage width of multibeam survey line and the overlap rate of adjacent two survey lines are calculated, and the multibeam survey line planning is carried out for sea areas with different depths, so as to achieve the shortest path survey line coverage in the range of 10%-20%overlap rate and achieve the optimal detection effect. Through the model solving and verification results, this method can be widely used in the survey problem of the seabed slope area with inclination, so as to improve the efficiency and accuracy of the survey ship in the seabed survey task. © 2024 SPIE.

关键词： Graph theory

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Dynamic Time Warping and Spatial Attention Optimized Deep BiLSTM Model for Traffic Flow Prediction 14

Dynamic Time Warping and Spatial Attention Optimized Deep Bi...

引用

14th International Conference on information technology in Medicine and Education, ITME 2024

作者： Shen, Bingqi Chen, Linlong Yang, Nan Guiyang Institute of Humanities and Technology College of Big Data and Information Engineering Guiyang550025 China

ISBN: (纸本)9798350356670

Addressing the deficiencies in modeling temporal pattern similarities and deep nonlinear characteristics of traffic flow, we propose an optimized DSA-DBLSTM algorithm. This algorithm integrates an improved Dynamic Time Warping (FastDTW) algorithm and an attention mechanism into a Deep Bidirectional Long Short-Term Memory (DBLSTM) network, aiming to enhance the accuracy and efficiency of traffic flow prediction. We preprocess taxi GPS trajectory data using a distributed resilient dataset (RDD) and apply Kalman Filtering (KF) to remove noise. Then, we construct the DSA-DBLSTM algorithm, optimizing the DBLSTM neural network by incorporating the FastDTW algorithm and the attention mechanism. Experimental results on real taxi GPS trajectory data demonstrate that, compared with 13 benchmark algorithms including ARIMA, SVR, KNN, SAEs, BP, CNN, GRU, ANN, LSTM, BiLSTM, DBLSTM, DSA-LSTM, and DSA-BiLSTM across multi-scale datasets, the DSA-DBLSTM algorithm exhibits optimal predictive performance. © 2024 IEEE.

关键词： Long short-term memory

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Feasible Path Search Algorithm on Two Dimensional Manifold S2 14

Feasible Path Search Algorithm on Two Dimensional Manifold S...

引用

14th International Conference on information technology in Medicine and Education, ITME 2024

作者： Song, Yunyun Li, Xingxin Guiyang Institute of Humanities and Technology College of Big Data and Information Engineering Guiyang550025 China

ISBN: (纸本)9798350356670

Spherical Barrier Free RRT path search method (SBF-RRT) can be solved the problem of the feasible path search on two-dimensional manifold S2. SBF-RRT algorithm is based on RRT algorithm, an area uniform sampling model based on Monte Carlo integration method can be solved the problem of uniform random sampling on two-dimensional manifold S2. The approximate distance measurement function of two-dimensional manifold surface distance between two points on manifold S2 can be obtained by arc segment proportional segmentation method. The angle cutting method can be solved the new node generation model on S2 surface. The continuous interpolation method can be solved the directed connection problem between two points on the manifold S2. The feasibility and effectiveness of the SBF-RRT algorithm have been verified through simulation experiments. The SBF-RRT algorithm can be searched for a feasible path on the two-dimensional manifold S2. © 2024 IEEE.

关键词： Intelligent systems

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Improving One-Dimensional Four-State Modulation Continuous Variable Quantum Key Distribution with Quantum Catalysis 3

Improving One-Dimensional Four-State Modulation Continuous V...

引用

3rd International Conference on Electronic information engineering and Computer Science, EIECS 2023

作者： Yang, Chao Luo, Jia Guo, Jin Li, Chun Guiyang Institute of Humanities and Technology College of Big Data and Information Engineering Guiyang China

ISBN: (纸本)9798350316674

Quantum catalysis has been proven to be effective in improving the performance of Gaussian modulation continuous variable quantum key distribution (CVQKD) protocols, significantly enhancing secure transmission distances. However, there is currently a lack of research on utilizing quantum catalysis to improve the performance of four-state modulation protocols. This paper focuses on enhancing the one-dimensional four-state modulation continuous variable quantum key distribution protocol using quantum catalysis. While Gaussian modulation CVQKD protocols offer the advantage of higher secure key rates, their secure transmission distances are limited. On the other hand, discrete modulation protocols exhibit better performance in terms of transmission distances. Additionally, to further simplify the protocol complexity, we adopt a one-dimensional modulation approach. This not only reduces the implementation cost and complexity but also enhances the robustness, secure key rates, and transmission distances of the protocol. © 2023 IEEE.

关键词： Continuous variable four-state modulation one-dimensional quantum catalysis

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DS-ACNet: Point Cloud Classification Algorithm Exploiting Depthwise Separable Convolution and Adaptive Convolution 3

DS-ACNet: Point Cloud Classification Algorithm Exploiting De...

引用

3rd International Symposium on Computer technology and information Science, ISCTIS 2023

作者： Li, Chun Luo, Jia Guo, Jin Wang, Fei College of Big Data and Information Engineering Guiyang Institute of Humanities and Technology Guiyang China

ISBN: (纸本)9798350325386

Point cloud data serves as a vital geometric data representation and finds extensive applications in computer vision tasks such as 3D model analysis, indoor navigation, and autonomous driving. However, the high-dimensional and unstructured nature of point cloud data pose challenges for its processing and analysis. To address these issues, we propose DS-ACN et, an algorithm that combines depthwise separable convolution architecture and adaptive convolution architecture in a novel network architecture. The depthwise separable convolution effectively reduces the number of parameters and computational complexity, enabling the extraction of local features from point cloud data. Furthermore, the adaptive convolution dynamically adjusts the convolution kernel based on the input data's features, thereby adapting to the varying geometric structures of different point clouds. Additionally, to expedite model convergence, we introduce the residual connection structure of ResNet into the network architecture, which partially compensates for the accuracy loss caused by depthwise separable convolution. To evaluate the effectiveness of the DS-ACNet algorithm, we conducted experiments on ModelNet40 dataset. Comparative results with state-of-the-art point cloud classification algorithms demonstrate that DS-ACNet exhibits notable advantages in terms of classification performance. The DS-ACNet algorithm provides a novel solution for further exploration and application of point cloud data in computer vision tasks, offering technical support to practical domains like indoor navigation and autonomous driving. © 2023 IEEE.

关键词： Convolution

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Regression analysis based on driving schools in Haikou 24

Regression analysis based on driving schools in Haikou

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8th International Conference on Electronic information technology and Computer engineering, EITCE 2024

作者： Yang, Darun Yang, Daqing Yang, Dashuai Yang, Dacai College of Information Engineering Hainan Vocational University of Science and Technology Hainan Haikou China Longjie Town Tianqiao Primary School Guizhou Bijie China College of Humanities and Technology Guizhou University for Nationalities Guizhou Guiyang China Guiyang University of Information Technology Guizhou Guiyang China

ISBN: (纸本)9798400710094

With the development of society and the growth of population in Haikou city, the driving school market in Haikou faces a series of challenges such as unreasonable teaching methods, cumbersome registration processes, non-standard training sites, overly long learning periods, delayed handling of student complaints, and lack of supervision. Using univariate regression and ridge regression to analyze the relationship between the number of exam takers and the number of passers, predicting the number of passers with a certain number of exam takers, providing reference for Haikou local undergraduate students and social individuals when registering for driving schools. Also, it aims to provide scientific decision-making basis for driving school managers, decision-makers, and practitioners, and predict future trends. © 2024 Copyright held by the owner/author(s).

关键词： Students

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