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9th International Conference on Computer and Communications, ICCC 2023

作者： Dong, Shuhan Lu, Yijun Wang, Yu Dong, Jiong Hanyang University Department of Physical Education Seoul Korea Republic of Muroran Institute of Technology Department of Sciences and Informatics Muroran Japan Zhejiang University College of Control Science and Engineering Hangzhou China Xuchang University Department of Information Engineering Xuchang China

ISBN: (纸本)9798350317251

The increasing popularity of VR games has sparked a notable surge in interest toward VR exergames, particularly in the context of the COVID-19 pandemic. To uphold the quality of VR exergames and provide valuable feedback to developers, it is imperative to consider the perspectives and concerns of players regarding VR exergames and conduct a comprehensive analysis of their reviews. This study employs the Latent Dirichlet Allocation (LDA) algorithm to effectively discern various topics within reviews, thus elucidating players' reservations concerning VR exergames. Empirical investigations were conducted using a dataset comprising 15,917 English-language reviews of 16 VR exergames on the Steam platform. The experimental findings unequivocally indicate that players exhibit a favorable disposition toward VR exergames (88.31% vs. 11.69%). The analysis encompasses eight distinct topics including user experience, graphics, music, and gameplay. © 2023 IEEE.

关键词： Virtual reality

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Student modeling considering learning behavior history with deep factorization machines 27

Student modeling considering learning behavior history with ...

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27th International Conference on Knowledge Based and Intelligent information and engineering Sytems, KES 2023

作者： Kakizaki, Toma Oeda, Shinichi Advanced Course of Control and Information Engineering National Institute of Technology Kisarazu College 11-1 Kiyomidaihigashi 2-chome Chiba Kisarazu City Japan Department of Information and Computer Engineering National Institute of Technology Kisarazu College 11-1 Kiyomidaihigashi 2-chome Chiba Kisarazu City Japan

To use an intelligent tutoring system (ITS) in an educational setting effectively, it is necessary to understand the skill status of students and recommend appropriate questions. Existing studies focused on improving the performance of ITS using student modeling to estimate the skill status of students. Knowledge tracing (KT) is the mainstream student modeling method, and deep learning approaches such as deep knowledge tracing and self-attentive knowledge tracing have been studied extensively in recent years. These models take only the questions solved by the student and the correct or incorrect answers to those questions as input;they do not assume the use of other features. In this study, we perform student modeling using DeepFM and FiBiNET that combines factorization machines and deep learning. Our results indicate that these models are more accurate than KT because of their ability to cope with sparse data and consider pairwise feature interactions, and more suited for real-world applications than KT. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： DeepLearning Educational data mining Factorization machines Intelligent tutoring system Knowledge tracing Student modeling

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Using Big Data Processing for Forming the information Model of the Mining and Geological Area

Using Big Data Processing for Forming the Information Model ...

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2023 IEEE International Conference on Smart information Systems and Technologies, SIST 2023

作者： Irbulat, Utepbergenov Yavorskiy, Vladimir Klyuyeva, Yelena Almaty University of Power Engineering and Telecommunications Named after Gumarbek Daukeyev Department of Automation and Control Almaty Kazakhstan Abylkas Saginov Karaganda Technical University Department of Information Technology and Security Karaganda Kazakhstan

ISBN: (纸本)9798350335040

The article presents the results of the study in the field of information and analytical modeling of territorial objects. The raw data used in the study was obtained using unmanned aerial vehicles (UAV). Big Data technologies such as Apache Hadoop and Apache Spark were used for data storage and analysis. The Delaunay triangulation algorithm was used to construct the surface skeleton. Algorithm A∗ was implemented to find the shortest paths in the resulting graph. © 2023 IEEE.

关键词： Big data

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Insights into photocatalytic mechanism over a novel Cu_(2)WS_(4)/MoS_(2) S-scheme heterojunction

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Rare Metals 2024年第7期43卷 3118-3133页

作者： Wei Zhao Ji-Hui Cao Jun-Jie Liao Yun Liu Xiao-Jun Zeng Jun-Yu Shen Xue-Kun Hong Yang Guo He-Hua Zeng Ya-Zi Liu School of Materials Engineering Jiangsu Key Laboratory of Advanced Functional MaterialsSchool of Electronic and Information EngineeringChangshu Institute of TechnologyChangshu215500China School of Chemistry and Chemical Engineering Changji UniversityChangji 831100China State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control Ministry of Ecology and EnvironmentNanjing Institute of Environmental SciencesNanjing 210023China School of Environment Jiangsu Engineering Lab of Water and Soil Eco-RemediationNanjing Normal UniversityNanjing 210023China Department of Chemical Engineering Curtin UniversityPerthWA6845Australia

A novel efficient Cu_(2)WS_(4)/MoS_(2) step-scheme(S-scheme)heterojunction photocatalyst was constructed for the first time and applied in the removal of environmental *** the as-prepared photocatalysts,the Cu_(2)WS_(4)/MoS_(2)-8%heterojunc tion photoc atalyst demonstrates the optimal photocatalytic performance,with the catalytic oxidation efficiency of tetracycline(TC)and the catalytic reduction efficiency of Cr^(6+)reaching 93.3%and 82.1%,*** excellent catalytic properties of Cu_(2)WS_(4)/MoS_(2) heterojunction photocatalysts are attributed to the effective separation pathways of charges and the presence of S-scheme heterojunctions,together with stronger redox *** is speculated that the photogenerated carrier migration path of the Cu_(2)WS_(4)/MoS_(2) catalyst follows the typical S-scheme photocatalytic mechanism,which is verified by the in-depth experimental study and simulated calculations including the electron paramagnetic resonance(EPR)analysis,free radical quenching experiments,charge density distribution,and simulated built-in electric field formation at the interface,which acts as driving force to promote the separation of photoinduced electrons and ***,the photocatalytic mechanism of S-scheme photogenerated carrier migration for the Cu_(2)WS_(4)/MoS_(2) catalyst is revealed based on the systematic experimental techniques and simulated calculations,accounting for its superior photocatalytic oxidation and reduction *** study provides inspiring implications to develop high-efficient S-scheme photocatalytic systems for versatile applications in solarenergy conversion.

关键词： Cu_(2)WS_(4)/MoS_(2) S-scheme Heterojunction Photocatalysis

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A student modeling method combining Deep Learning and forgetting models with Knowledge Tracing 27

A student modeling method combining Deep Learning and forget...

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27th International Conference on Knowledge Based and Intelligent information and engineering Sytems, KES 2023

作者： Oeda, Shinichi Hasegawa, Shunichi Department of Information and Computer Engineering National Institute of Technology Kisarazu College 11-1 Kiyomidaihigashi 2-chome Chiba Kisarazu City Japan Advanced Course of Control and Information Engineering National Institute of Technology Kisarazu College 11-1 Kiyomidaihigashi 2-chome Chiba Kisarazu City Japan

Educational Data Mining (EDM) aims to enhance education by analyzing learners' skills and question difficulty levels using machine learning methods. Knowledge Tracing (KT), a subfield of EDM, utilizes Hidden Markov Models to estimate learners' abilities and predict their performance on unseen questions. While deep learning methods, such as bi-directional RNNs, have improved KT's accuracy, they may lack interpretability from an educational psychology perspective. Item Response Theory (IRT), widely used in educational statistics, offers greater explanatory potential. This study proposes a model that integrates the concept of forgetting into IRT for improved accuracy and explainability in Knowledge Tracing using bi-directional RNNs. The forgetting concept is based on Ebbinghaus' forgetting curve theory. Three experiments were conducted using synthetic data to compare a model from a previous study, a model based on the proposed method, and a model that combines the previous study's model with IRT but excludes the forgetting concept. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： Deep Learning Educational Data Mining Intelligent Tutoring System Item Response Theory Knowledge Tracing Student Modeling

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A Multi-Stage Goal-Driven Network for Pedestrian Trajectory Prediction 5

A Multi-Stage Goal-Driven Network for Pedestrian Trajectory ...

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5th International Conference on Computer Vision, Image and Deep Learning, CVIDL 2024

作者： Wu, Xiuen Wang, Tao Cai, Yuanzheng Liang, Lingyu Papageorgiou, George Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fuzhou China Fuzhou University College of Computer and Data Science Fuzhou China South China University of Technology School of Electronic and Information Engineering Guangzhou China European University Cyprus Department of Computer Science and Engineering Nicosia Cyprus

ISBN: (纸本)9798350373820

Pedestrian trajectory prediction plays a pivotal role in ensuring the safety and efficiency of various applications, including autonomous vehicles and traffic management systems. This paper proposes a novel method for pedestrian trajectory prediction, called multi-stage goal-driven network (MGNet). Diverging from prior approaches relying on stepwise recursive prediction and the singular forecasting of a long-term goal, MGNet directs trajectory generation by forecasting intermediate stage goals, thereby reducing prediction errors. The network comprises three main components: a conditional variational autoencoder (CVAE), an attention module, and a multi-stage goal evaluator. Trajectories are encoded using conditional variational autoencoders to acquire knowledge about the approximate distribution of pedestrians' future trajectories, and combined with an attention mechanism to capture the temporal dependency between trajectory sequences. The pivotal module is the multi-stage goal evaluator, which utilizes the encoded feature vectors to predict intermediate goals, effectively minimizing cumulative errors in the recursive inference process. The effectiveness of MGNet is demonstrated through comprehensive experiments on the JAAD and PIE datasets. Comparative evaluations against state-of-the-art algorithms reveal significant performance improvements achieved by our proposed method. © 2024 IEEE.

关键词： Trajectories

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Advancing Ultra-Short-Term Wind Power Forecasting with Multi-Channel ML Techniques 6

Advancing Ultra-Short-Term Wind Power Forecasting with Multi...

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6th International Conference on Energy Systems and Electrical Power, ICESEP 2024

作者： Ren, Jiapin Zhu, Chenlin Huang, Zeyu Chen, Ruihan Xu, Shurui You, Peng Xuhai College China University of Mining and Technology Department of Information and Electrical Engineering Xuzhou China Metropolitan College Boston University Boston United States School of Information Engineering China Jiliang University Hangzhou China School of Mathematical Sciences Zhejiang Normal University Jinhua China Beijing Meishi Cha Technology Co. Ltd. Cognitive Neuroscience Laboratory Beijing China China University of Mining and Technology National and Local Joint Engineering Laboratory of Internet Applied Technology on Mines China School of Information and Control Engineering China University of Mining and Technology China Xuhai College China University of Mining and Technology Xuzhou China

ISBN: (纸本)9798350353563

To address the inherent unpredictability of wind speeds and directions, which significantly affect wind turbine output, this paper presents a multi-channel feature combination strategy for ultra-short term wind power prediction. The research utilises a number of data sources, including meteorological observations, historical power data and geographical inputs, to create a robust feature set for prediction models. By using advanced machine learning techniques, in particular deep learning models such as Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks, the study effectively captures the complex dynamics of wind power generation. The novel approach of reclassifying data sets and refining model features through task-specific channels significantly improves prediction accuracy. Experimental results show significant improvements in prediction accuracy, highlighting the potential of the proposed method to optimise grid operation and energy management in real-time scenarios. © 2024 IEEE.

关键词： Wind forecasting

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A polarization sensitive interferometer:Delta interferometer

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Chinese Physics B 2024年第3期33卷 369-377页

作者：卫超奇刘建彬董翼飞孙雨农周宇郑淮斌刘严严闫秀生李福利徐卓 Key Laboratory of Multifunctional Materials and Structures Ministry of Education & International Center for Dielectric ResearchSchool of Electronic Science and EngineeringXi'an Jiaotong UniversityXi'an 710049China MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter Department of Applied PhysicsXi'an Jiaotong UniversityXi'an 710049China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin 300308China

A new type of polarization sensitive interferometer is proposed,named the Delta interferometer,inspired by its geometry resembling the Greek letter *** main difference between the Delta interferometer and other existing interferometers,such as Michelson,Mach-Zehnder and Young's double-slit interferometers,is that the two interfering paths are asymmetrical in the Delta *** visibility of the first-order interference pattern observed in the Delta interferometer is dependent on the polarization of the incidental *** coherence theory is employed to interpret this phenomenon and single-mode continuous-wave laser light is employed to verify the theoretical *** theoretical and experimental results are *** Delta interferometer is a perfect tool to study the reflection of electromagnetic fields in different polarizations and may find applications in polarization-sensitive scenarios.

关键词： phase sensitive interferometer Fresnel formula first-order interference

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Symplectic analysis for regulating wave propagation in a one-dimensional nonlinear graded metamaterial

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Applied Mathematics and Mechanics(English Edition) 2023年第5期44卷 745-758页

作者： Yunping ZHAO Xiuhui HOU Kai ZHANG Zichen DENG Department of Applied Mathematics Northwestern Polytechnical UniversityXi’an 710072China School of Mechanics Civil Engineering and ArchitectureNorthwestern Polytechnical UniversityXi’an 710072China Ministry of Industry and Information Technology Key Laboratory of Dynamics and Control of Complex SystemsNorthwestern Polytechnical UniversityXi’an 710072China State Key Laboratory of Structural Analysis for Industrial Equipment Dalian University of TechnologyDalian 116024China

An analytical method,called the symplectic mathematical method,is proposed to study the wave propagation in a spring-mass chain with gradient arranged local resonators and nonlinear ground *** with the linearized perturbation approach,the symplectic transform matrix for a unit cell of the weakly nonlinear graded metamaterial is derived,which only relies on the state *** results of the dispersion relation obtained with the symplectic mathematical method agree well with those achieved by the Bloch *** is shown that wider and lower frequency bandgaps are formed when the hardening nonlinearity and incident wave intensity ***,the displacement response and transmission performance of nonlinear graded metamaterials with finite length are *** dual tunable effects of nonlinearity and gradation on the wave propagation are explored under different excitation *** small excitation frequencies,the gradient parameter plays a dominant role compared with the *** reason is that the gradient tuning aims at the gradient arrangement of local resonators,which is limited by the critical value of the local resonator *** contrast,for larger excitation frequencies,the hardening nonlinearity is dominant and will contribute to the formation of a new bandgap.

关键词： symplectic mathematical method nonlinear graded metamaterial tunable bandgap

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An Adaptive control Method Based on Radial Basis Function Neural Network for Variable Stiffness Actuator

An Adaptive Control Method Based on Radial Basis Function Ne...

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IEEE International Conference on Industrial technology (ICIT)

作者： Xiujun Wu Chen Wang Changxian Xu Keping Liu Gang Wang Zhongbo Sun Department of Control Science and Engineering Changchun University of Technology Changchun China Department of Control Science and Engineering School of Electrical and Information Engineering Jilin Engineering Normal University Changchun China

ISBN: (数字)9798350340266

ISBN: (纸本)9798350340273

Rehabilitation robots based on variable stiffness elastic actuators exhibit strong human-robot interaction char-acteristics due to the specific features of the actuators, including flexible drive and variable stiffness output capabilities. However, to ensure the robot can achieve rehabilitation actions smoothly, safely, and precisely, accurate modeling and control of the variable stiffness elastic actuators becomes a burning question. In order to address this challenge, a dynamic model is established considering the actuator's own gravity factor and the influence of disturbances, and a nominal dynamic model is designed. Accurate tracking of output location and stiffness is reached by designing a radial basis function (RBF) network to approximate the actual dynamic model. Through simulation experiments, it is verified that the block approximation RBF network adaptive controller designed in this article has lower actuator tracking error and higher control accuracy than the proportional integral derivative (PID) controller.

关键词： Actuators Adaptation models Torque Uncertainty Simulation Human-robot interaction Radial basis function networks

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