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Superhydrophobic self-extinguishing cotton fabrics for electromagnetic interference shielding and human motion detection

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Journal of Materials Science & Technology 2023年第1期132卷 59-68页

作者： Lei Liu Zhewen Ma Menghe Zhu Lina Liu Jinfeng Dai Yongqian Shi Jiefeng Gao Toan Dinh Thanh Nguyen Long-Cheng Tang Pingan Song College of Environment and Safety Engineering Qingdao University of Science and TechnologyQingdao 266061China School of Chemistry and Materials Engineering Zhejiang A&F UniversityHangzhou 311300China College of Environment and Safety Engineering Fuzhou UniversityFuzhou 350116China School of Chemistry and Chemical Engineering Yangzhou UniversityYangzhou 225002China Centre for Future Materials University of Southern QueenslandSpringfield 4300Australia School of Engineering University of Southern QueenslandSpringfield 4300Australia College of Material Chemistry and Chemical EngineeringKey Laboratory of Organosilicon Chemistry and Material Technology of MoEHangzhou Normal UniversityHangzhou 311121China School of Agriculture and Environmental Science University of Southern QueenslandSpringfield 4300Australia

Multifunctional intelligent fire-safe cotton fabric promises next-generation fire-fighting uniform and sen-sor ***,cotton fabrics’hygroscopicity and intrinsic flammability significantly impede their potential applications in ***,we report a superhydrophobic fireproof cotton fabric(PEI-APP-PEI-MXene)generated via sequential layer-by-layer deposition of polyethyleneimine(PEI),am-monium polyphosphate(APP),and titanium carbide(MXene),followed by hydrophobic treatment with silicone *** to untreated cotton,the treated cotton fabric with 10 polymolecular layers exhibits∼43%and∼42%reductions in the peak heat release rate and total heat release,respectively,a desired UL-94 V-0 rating,and a high limiting oxygen index(LOI)value of 39.5 vol.%.In addition to that,the treated fabrics displayed improved electromagnetic interference(EMI)shielding and motion-sensing *** presented work provides a facile and effective surface modification approach to generate multifunctional cotton fabrics with promising practical applications.

关键词： Cotton fabric Super-hydrophobicity Flame retardancy Electromagnetic interference shielding motion sensor MXene

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Flexible visualization framework for head-mounted display with gesture interaction interface

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International Journal of Modeling, Simulation, and Scientific Computing 2018年第3期9卷 22-41页

作者： Pierre J.Jarsaillon Naohisa Sakamoto Akira Kageyama Computer Science Department INSA Lyon 20 avenue Albert EinsteinVilleurbanne Cedex 69621France Graduate School of System Informatic Kobe University 1-1 Rokko-daiNada-ku Kobe 657-8501Japan Department of Computational Science Kobe University 1-1 Rokko-dai Nada-kuKobe 657-8501Japan

As the development of new visualization systems,within the field of simulation,offers their users more insights from their simulations,immersive systems are becoming a part of the visualization *** the recent advancements of the Head-Mounted Displays(HMDs)and popularity of motion sensors,human beings and computer become more *** study aims to evaluate the potential of such systems as a visualization tool through the development of a new flexible framework for visualization within virtual reality(VR)environment,using an Oculus Rift and a Leap *** approaches are then compared:high-3D object rendering within the virtual scene approach and a user experience-oriented system with an intuitive *** assess the quality of the interface and its relevance for the user,different types of gestures are implemented and *** an experiment on users to evaluate the developed system as a proper visualization tool,the HMDs,paired with a motion sensor to make a gesture-controlled interface seem to be promising mediums despite various constraints on development regarding the technology limitations.

关键词： Virtual reality motion sensor interactive tool user experience immersive visualization.

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Identity Authentication Based on sensors of Smartphone and Neural Networks

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Journal of Computer and Communications 2022年第7期10卷 90-102页

作者： Jingyong Zhu Hanbing Fan Yichen Huang Miaomiao Lin Tao Xu Junqiang Cai Zhengjie Wang College of Electronic and Information Engineering Shandong University of Science and Technology Qingdao China

The smartphone has become an indispensable electric device for most people since it can assist us in finishing many tasks such as paying and reading. Therefore, the security of smartphones is the most crucial issue to illegal users who cannot access legal users’ privacy information. This paper studies identity authentication using user action. This scheme does not rely on the password or biometric identification. It checks user identity just by user action features. We utilize sensors installed in smartphones and collect their data when the user waves the phone. We collect these data, process them and feed them into neural networks to realize identity recognition. We invited 13 participants and collected about 350 samples for each person. The sampling frequency is set at 200 Hz, and DenseNet is chosen as the neural network to validate system performance. The result shows that the neural network can effectively recognize user identity and achieve an authentication accuracy of 96.69 percent.

关键词： Identity Authentication Smartphone motion sensor Neural Network

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