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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Li, Zhishuai Xiong, Gang Zhang, Yu Zheng, Meng Dong, Xisong Lv, Yisheng Institute of Automation Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing Municipal Institute of City Planning and Design Traffic Planning Department Beijing China

ISBN: (纸本)9781665433372

The four-step transportation model plays an important role in urban planning. The quality of the first phase, i.e. trip generation, determines the performance of the global course. The majority of trip generation forecasting models highly rely on mathematical derivation and have many predictor variables during the prediction, which leads to low accuracy of results and requires laboriously hand-crafted design of input vectors. This paper is the first to introduce the gradient boosting decision tree (GBDT) algorithm for trip generation prediction, and harmonizes such a powerful machine learning method with traditional urban planning requirements to achieve better prediction performance. Unlike the commonly used linear regression method, GBDT can automatically perform feature selection and model the non-linear relationships between input and output variables. Experimental results on real-world residential travel census in Beijing prove that the GBDT model significantly outperforms the baseline and can forecast the trip generation more accurately. © 2021 IEEE.

关键词： Decision trees

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Investigation on Material Removal of the Sub-Aperture Tool Used for Polishing Riblet Surfaces

SSRN

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SSRN 2022年

作者： Wang, Guilian Lv, Bingrui Liu, Bin Fang, Fengzhou Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin 300384 China School of Mechanical and Materials Engineering University College Dublin Belfield D04 V1W8 Ireland Key Laboratory of Advanced Ceramics and Machining Technology Ministry of Education Tianjin University Tianjin300072 China Tianjin Laboratory of Control Theory and Applications in Complicated System School of Electrical and Electronic Engineering Tianjin University of Technology Tianjin 300384 China Tianjin University Tianjin 300072 China

Riblet surfaces find wide applications owing to their excellent performance such as drag reduction. In this study, sub-aperture tool is investigated to polish the riblet surfaces, two main different curvatures at any point of this kind of tool surface are proposed. A series of simulation studies are conducted to investigate the effect of key parameters on the material removal, such as tool radius, inclination angle, polishing pressure, and tool speed. The results show that a higher difference between the tool radius values in two directions increases the difference between the major and minor axes of the contact area. Based on experimental tests and simulation analysis, it is conluded that the profile and depth of material removal distribution both increase with an increase in polishing pressure, the material removal profile remains constant but the removal detpth increases with an increase in polishing speed, and the parameter K is a time-dependent. © 2022, The Authors. All rights reserved.

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Anomalous Polarization-Switching Phenomena and Noteworthy Pyroelectricity in Ferroelectric Hf0.5zr0.5o2 Polycrystalline Films

SSRN

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SSRN 2023年

作者： Wang, Xudong Zhou, Yong Xiong, Ke Wu, Shuyu Tu, Luqi Chen, Yan Wu, Shuaiqin Zeng, Jinhua Zheng, Yuqing Gu, Shiqun Luo, Man Lin, Tie Shen, Hong Meng, Xiangjian Liu, Qi Chu, Junhao Wang, Jianlu State Key Laboratory of Infrared Physics Shanghai Institute of Technical Physics Chinese Academy of Sciences Shanghai200083 China Key Laboratory of Microelectronics Device and Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China Frontier Institute of Chip and System Fudan University Shanghai200433 China Shanghai Frontier Base of Intelligent Optoelectronics and Perception Institute of Optoelectronics Fudan University Shanghai200433 China Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Chinese Academy of Sciences Hangzhou330106 China BirenTech Shanghai201114 China Jiangsu Key Laboratory of ASIC Design School of Information Science and Technology Nantong University Jiangsu Nantong226019 China

Hafnia-based oxide thin films exhibit unconventional robust ferroelectricity at the nanoscale, paving the way for advancements in next-generation nanoelectronics. However, the stability and dynamics of ferroelectric polarization in hafnia-based oxides films, particularly at the nanoscale, warrant further exploration. In this study, we delve into the factors influencing the formation of the ferroelectric phase. Our findings illuminate that the confinement effect of the capped layer enhances the stabilization of the metastable orthorhombic phase, thereby bolstering its ferroelectricity and endurance. Furthermore, we identify an unprecedented polarization-switching behavior in HfO2-based ferroelectric films, characterized by a decrease in the remanent polarization and an increase in the coercive field as the temperature drops. This peculiar phenomenon can be ascribed to the reduction in the long-range interaction of polarization dipoles upon cooling, as evidenced by the dielectric spectrum. The diminished long-range interaction results in the emergence of nanodomains and a re-entrant relaxer behavior, offering novel insights into the origin of ferroelectricity and the stability of ferroelectric polarization in hafnia-based thin films. Given the commendable compatibility of Hf0.5Zr0.5O2 films with Si substrates and a pyroelectric coefficient of -62.1 μC/m2·K, they emerge as a prime candidate for sensor device applications. © 2023, The Authors. All rights reserved.

关键词： Thin films

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Interactive Mixed Reality Cooking Assistant for Unskilled Operating Scenario 12th

Interactive Mixed Reality Cooking Assistant for Unskilled Op...

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12th International Conference on Virtual, Augmented and Mixed Reality, VAMR 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020

作者： Zhai, Ke-yu Cao, Yi-ming Hou, Wen-jun Li, Xue-ming School of Digital Media and Design Arts Beijing University of Posts and Telecommunications Beijing100876 China Beijing Key Laboratory of Network and Network Culture Beijing University of Posts and Telecommunications Beijing100876 China Digital Media and Intelligent Computing Laboratory Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9783030496975

As the further development of virtual reality technology, mixed reality (MR) promotes the innovation of human-computer interaction. It can integrate virtual information (objects, pictures, videos, etc.) into the real environment, and directly interact with people. It can greatly improve the efficiency of information reception, reduce the cost of understanding and learning, and improve the fluency and accuracy of operational tasks. In the kitchen scene, when the novices cook according to the recipe, they usually do not perform well in memory and learning, which causes many problems in the cooking process. Therefore, we propose an interactive intelligent cooking system design, which focuses on the five kinds of information that novices need most help in the cooking process, and subverts the traditional recipe with MR presentation. The experiment also shows that the intelligent cooking system can make up for the guidance to novice which is easy to be ignored by traditional recipes, and can effectively improve the user experience of novices. © 2020, Springer Nature Switzerland AG.

关键词： Mixed reality

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design of an Active Battery Equalization Circuit with DC-DC Converter

Design of an Active Battery Equalization Circuit with DC-DC ...

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IEEE Asia Power and Energy Engineering Conference (APEEC)

作者： Kun Li Xiao Zong Qing Liu Yanfang Sun Fengjun Xue Tianjin Key Laboratory of Film Electronic and Communication Device Tianjin University of Technology Tianjin PR China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin PR China Wuhan Running Education Research Institute Wuhan PR China

ISBN: (纸本)9781665425513;9781665430791

An active balanced topology circuit based on DC-DC converter is proposed in this paper. It uses the energy of the whole battery pack to charge the lowest voltage cell. In the control strategy, starting and stopping the equalization is well controlled by setting the appropriate thresholds of voltage difference between each cell. Experiment board which can sample and equalize 16 batteries is manufactured, and the experimental results verify the effectiveness of the proposed equalization system.

关键词： Electrical engineering Energy exchange Asia DC-DC power converters Threshold voltage Batteries Topology

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Exploring the role of visual content in fake news detection

arXiv

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arXiv 2020年

作者： Cao, Juan Qi, Peng Sheng, Qiang Yang, Tianyun Guo, Junbo Li, Jintao Key Laboratory of Intelligent Information Processing Center for Advanced Computing Research Institute of Computing Technology CAS China University of Chinese Academy of Sciences China

The increasing popularity of social media promotes the proliferation of fake news, which has caused significant negative societal effects. Therefore, fake news detection on social media has recently become an emerging research area of great concern. With the development of multimedia technology, fake news attempts to utilize multimedia content with images or videos to attract and mislead consumers for rapid dissemination, which makes visual content an important part of fake news. Despite the importance of visual content, our understanding about the role of visual content in fake news detection is still limited. This chapter presents a comprehensive review of the visual content in fake news, including the basic concepts, effective visual features, representative detection methods and challenging issues of multimedia fake news detection. This chapter can help readers to understand the role of visual content in fake news detection, and effectively utilize visual content to assist in detecting multimedia fake news. Copyright © 2020, The Authors. All rights reserved.

关键词： Social networking (online)

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Significant Wave Height Prediction Based on VMD-SA-MLP-BP

Significant Wave Height Prediction Based on VMD-SA-MLP-BP

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Chinese Automation Congress (CAC)

作者： Yining Wu Runfeng Zhang Fang Liu Zhenzhong Liu Jianguo Wu Haonan Dong Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Yichang Research Institute of Testing Technology Yichang China Tianjin Hanhailanfan Marine Technology Co. Ltd. Tianjin China School of Computer Science and Engineering Tianjin University of Technology Tianjin China

Waves seriously impact port construction, worldwide route planning, military activities, and wave power generation. To improve the accuracy of significant wave height prediction, we proposed a novel prediction method, a multi-layer perceptron combined with a backpropagation adjustment (MLP-BP) prediction model that combines mutation mode decomposition (VMD) and a simulated annealing optimization algorithm (SA). Firstly, we use the variable modulus method to decompose the significant wave height sequence data and transform the wave height sequence into multiple different sub-modes (IMF) to reduce the complexity and non-stationarity of the data. Secondly, the simulated annealing algorithm (SA) is used to optimize the weight and bias of the MLP-BP neural network to find the optimal parameter configuration and improve the performance and generalization ability of the prediction model. Finally, the decomposed sub-modal components of each significant wave height sequence are inserted into the MLP-BP neural network and the predicted values of each element are summed to obtain the final significant wave height prediction. The prediction results of the SSA-MLP-BP, PSO-MLP-BP, SA-MLP-BP, and VMD-SA-MLP-BP were compared and demonstrated that the VMD-SA-MLP-BP model performed best. The MAE, MAPE, MSE, RMSE, and R2 of the prediction evaluation indexes were 0.036 m, 11.7%, 0.004 m 2 , 0.067 m, and 0.983, respectively, which performed well in predicting significant wave height.

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The Temporal Structural Pattern in Scientific Collaborative Behavior from the Perspective of Complex Network 23rd

The Temporal Structural Pattern in Scientific Collaborative...

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23rd International Symposium on Knowledge and Systems Sciences, KSS 2024

作者： Zholdoshbaeva, Elina Zhang, Shuang Liu, Feifan Xia, Haoxiang Institute of Systems Engineering Dalian University of Technology No. 2 Linggong Road Liaoning Dalian116024 China Center for Big Data and Intelligent Decision-Making Dalian University of Technology Linggong Road Liaoning Dalian116024 China School of Business East China University of Science and Technology 130 Meilong Road Xuhui District Shanghai200237 China Institute for Advanced Intelligence Dalian University of Technology Linggong Road Liaoning Dalian116024 China Key Laboratory of Social Computing and Cognitive Intelligence Ministry of Education of China Linggong Road Liaoning Dalian116024 China

ISBN: (纸本)9789819601776

The rapid advancement of science has underscored the importance of collaboration among scientists. While many studies have explored the structure of collaboration networks, there is a lack of comprehensive quantitative research on the temporal patterns of these collaborations. This study addresses this gap by analyzing temporal scientific collaboration networks in physics, spanning from 1960 to 2021, using complex network theories and methods. By constructing five-year temporal collaborative networks and employing metrics such as network diameter, shortest path, and clustering coefficient, this research reveals an increase in connectivity and small-world characteristics over time. Additionally, community detection highlights a shift towards specialized collaboration patterns and increased cross-community interactions. The study also uncovers growing centrality and social stratification within the research system, with the "rich club" phenomenon indicating strong and dynamic collaborations among highly connected scientists. Temporal analysis shows that while ultra-high connectivity scientists engage in fluctuating relationships, medium-high connectivity scientists maintain more stable collaborations. These findings provide insights into the evolution of collaborative behaviors and inform science policy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Collaborative learning

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Science as Exploration in a Knowledge Landscape: Tracing Hotspots or Seeking Opportunity?

arXiv

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arXiv 2023年

作者： Liu, Feifan Zhang, Shuang Xia, Haoxiang Institute of Systems Engineering Dalian University of Technology No.2 Linggong Road Liaoning Dalian116024 China Center for Big Data and Intelligent Decision-Making Dalian University of Technology Linggong Road Liaoning Dalian116024 China Institute for Advanced Intelligence Dalian University of Technology Linggong Road Liaoning Dalian116024 China Key Laboratory of Social Computing and Cognitive Intelligence Ministry of Education of China Linggong Road Liaoning Dalian116024 China

The selection of research topics by scientists can be viewed as an exploration process conducted by individuals with cognitive limitations traversing a complex cognitive landscape influenced by both individual and social factors. While existing theoretical investigations have provided valuable insights, the intricate and multifaceted nature of modern science hinders the implementation of empirical experiments. This study leverages advancements in deep learning techniques to investigate the patterns and dynamic mechanisms of topic-transition among scientists. By constructing the knowledge space across 6 large-scale disciplines, we depict the trajectories of scientists' topic transitions within this space, measuring the flow and distance of research regions across different sub-spaces. Our findings reveal a predominantly conservative pattern of topic transition at the individual level, with scientists primarily exploring local knowledge spaces. Furthermore, simulation modeling analysis identifies research intensity, driven by the concentration of scientists within a specific region, as the key facilitator of topic transition. Conversely, the knowledge distance between fields serves as a significant barrier to exploration. Notably, despite potential opportunities for breakthrough discoveries at the intersection of subfields, empirical evidence suggests that these opportunities do not exert a strong pull on scientists, leading them to favor familiar research areas. Our study provides valuable insights into the exploration dynamics of scientific knowledge production, highlighting the influence of individual cognition, social factors, and the intrinsic structure of the knowledge landscape itself. These findings offer a framework for understanding and potentially shaping the course of scientific progress. © 2023, CC BY-NC-ND.

关键词： Deep learning

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Optimization of Experiment Teaching in the Course of Mechanical Principle 2020

Optimization of Experiment Teaching in the Course of Mechani...

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2020 3rd International Conference on Education Technology Management

作者： Pujun Hao Jingna Liu Wenpeng Ma Ruiqin Wu Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin and National Demonstration Center for Experimental Mechanical and Electrical Engineering Education (Tianjin University of Technology) China

ISBN: (纸本)9781450388757

Based on experience of former teaching reformation and philosophy of "Emerging Engineering Education", an experimental teaching reformation program that includes restructured knowledge system, modularization of experimental teaching process and diversified evaluation system is proposed. It is found that students have deeper and comprehensive understanding on knowledge and more enthusiasm in experimental process. Finally students have definite self-cognition about their division of labor in teamwork. Through gathering statistics, the effectiveness of reformation program is verified and this program can enrich practical experience of experimental teaching reformation.

关键词： experiment teaching diversified evaluation modular teaching process Mechanical principle

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