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Transformation of a ceramic precursor to a biomedical (metallic) alloy: Part I – sinterability of Ta2O5 and TiO2 mixed oxides

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Materials science for Energy Technologies 2022年 5卷 181-188页

作者： Chorney, Maureen P. Hurley, Bridger P. Mondal, Kunal Khanolkar, Amey R. Downey, Jerome P. Tripathy, Prabhat K. Department of Materials Science and Engineering Montana Tech of the University of Montana ButteMT59701 United States Materials Science and Engineering Department Energy and Environment Science and Technology Directorate Idaho National Laboratory Idaho FallsID83415 United States Pyrochemistry & Molten Salt Systems Department Fuel Cycle Science and Technology Division Nuclear Science and Technology Directorate Idaho National Laboratory Idaho FallsID83415 United States

Mixed Ta2O5 – TiO2 binary system was studied by a combination of differential thermal analysis (DTA), scanning electron microscopy-energy dispersive spectrometry (SEM-EDS), X-ray diffraction (XRD) and in situ high temperature X-ray diffraction (HT-XRD) techniques. Different compositions of the mixed oxide powders were fabricated by ball–milling the powdered compositions, pelletizing the homogenized composite powders, and heating the green pellets in air at different temperatures for fixed time intervals. The sintered pellets were evaluated and characterized with respect to porosity, morphology, and phase distribution. DTA runs of the un-sintered powders indicated the onset temperatures for both exothermic and endothermic changes in the binary system. Significant amount of sintering was observed to take place at temperatures higher than 900 °C. Both room and high temperature X-ray diffraction patterns exhibited consistency in phase formation. A ternary compound (TaTiO4) and a ternary solid solution (Ti0.33Ta0.67O2) were observed to form in both room and high temperatures in addition to the respective binary phases (Ta2O5 and TiO2). A sintering temperature in the range 900–1000 °C was observed to be adequate to achieve the requisite mechanical strength and optimum internal porosity (40–48%) for subsequent electrochemical polarization experiments. © 2022

关键词： Titanium dioxide

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Extrusion-Based 3D-Printed Supercapacitors:Recent Progress and Challenges

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Energy & Environmental Materials 2022年第3期5卷 800-822页

作者： Xiao Yan Yueyu Tong Xinzhong Wang Feng Hou Ji Liang Research Centre for Information Technology Shenzhen Institute of Information TechnologyShenzhen 518172China Institute for Superconducting&Electronic Materials Australian Institute of Innovative MaterialsUniversity of WollongongNorth Wollongong NSW 2500Australia Key Laboratory of Advanced Ceramics and Machining Technology of Ministry of Education School of Materials Science and EngineeringTianjin UniversityTianjin 300072China

Supercapacitors have been regarded as promising power supplies for future electronics due to their high power density,superior stability,easy integration,and ***-based three-dimensional printing technologies hold promise to satisfy the demands for integrated and flexible supercapacitors because of their highly versatile manufacturing *** this review article,a comprehensive and timely review of these state-of-theart technologies is *** start with a brief introduction of fundamental concepts of supercapacitors,including energy storage mechanisms and device ***,the latest progress of extrusionbased three-dimensional printing technologies(e.g.,fused deposition modeling,inkjet printing,and direct ink writing)along with their applications for manufacturing supercapacitors is *** choice of printable materials(e.g.,graphene,carbon nanotubes,metal oxides,and MXenes),printing process,and the resulted electrochemical performances of supercapacitors are especially ***,the development of extrusion-based three-dimensional printing supercapacitors is summarized,with existing challenges diagnosed,possible solutions proposed,and future outlooks *** hope this review can offer insights to further improve the performance of three-dimensional-printed supercapacitors for practical applications.

关键词： 3D printing direct ink writing fused deposition modeling inkjet printing supercapacitors

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Identification of Damaged Date Palm Tree in a Farm using IoT-based Thermal Image Analysis

Identification of Damaged Date Palm Tree in a Farm using IoT...

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2023 IEEE International Conference on Computer, information, and Telecommunication systems, CITS 2023

作者： Nadeem, Adnan Ashraf, Muhammad Mehmood, Amir Siddiqui, Muhammad Shoaib Almoamari, Hani Abbasi, Qammer H. Islamic University of Madinah Faculty of Computer and Information Systems Madinah42351 Saudi Arabia Federal Urdu University of Arts Science and Technology Department of Physics Karachi75300 Pakistan Sir Syed University of Engineering and Technology Department of Computer Science and Information Technology Karachi75300 Pakistan James Watt School of Engineering University of Glasgow Glasgow United Kingdom

ISBN: (纸本)9798350336092

The Kingdom of Saudi Arabia is one of the world's leading fresh date producers. Identifying damaged date palm trees on the farm is important for saving water and stopping the spread of pest which has caused the damage. In this paper, we aim to evaluate the performance of IoT-based thermal image camera input for the automatic detection of damaged trees in a Date Tree farm. The thermal images will be obtained by an IoTbased thermal camera attached to UAV. Then the temperature histogram vector will be generated which will be fed to the SVM for identification of the damaged tree. The system will raise the alarm along with the coordinates of the damaged tree for the farmer to proactively deal with the issue. The initial results of the tested scenario are encouraging for its detailed implementation in the future. © 2023 IEEE.

关键词： Cameras

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3D Object Detection Based on Spatially Adaptive Sparse Convolution

3D Object Detection Based on Spatially Adaptive Sparse Convo...

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2024 IEEE International Conference on Future Machine Learning and Data science, FMLDS 2024

作者： Hu, Jing Jing Fan, Yu Ling Zhang, Ping Duan, Chang Zhang, Chao Chen, Si Yu Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Chengdu China School of Optoelectronic Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Electrical Engineering and Information Southwest Petroleum University Chengdu China Sichuan Police College Intelligent Policing Key Laboratory of Sichuan Province Luzhou China School of Computer Science And Technology Beijing Jiaotong University Beijing China

ISBN: (纸本)9798350391213

Autonomous driving has gradually gained attention in recent years due to its potential to reduce driver burden and improve safety, in which 3D object detection is the basis of the autonomous driving perception system, aiming at predicting the location, size, and class of 3D objects in the vicinity of an autonomous vehicle, which is an important guide for subsequent path planning, motion prediction, and so on. In particular, 3D object detection has difficulties in input point cloud data processing and multimodal fusion. Unlike the image distribution where pixels are regularly distributed in the image plane, the point cloud is a sparse and irregular 3D representation, so it is difficult to apply the traditional convolution directly on the point cloud for detection. In this paper, we carry out a method for 3D object detection for point clouds, using deformable convolution and sparse convolution as a tool to explore the feature extraction method of sparse convolution for irregular point clouds and propose a spatially adaptive sparse convolution-based method. © 2024 IEEE.

关键词： Motion planning

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2-D Digital Frequency Offset Loading Technique for Discrete Spectrum Modulated Nonlinear Frequency Division Multiplexing System

2-D Digital Frequency Offset Loading Technique for Discrete ...

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2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings, ACP/POEM 2023

作者： Yao, Donghu Bi, Yanfeng Wang, Mingjiao Gao, Hongbing Xu, Hengying Zhang, Yining Bai, Chenglin Yang, Lishan Bi, Wanxiang School of Physics Science and Information Engineering Liaocheng University Liaocheng China Shandong Provincial Key Laboratory of Optical Communication Science and Technology Liaocheng China Liaocheng Key Laboratory of Industrial-Internet Research and Application Liaocheng China

ISBN: (纸本)9798350312614

In this paper, we propose a two-dimensional digital frequency offset loading (2D-DFOL) technique for discrete spectrum modulated nonlinear frequency division multiplexing (DS-NFDM) system. It makes full use of two degrees of encoding freedom, the real part and the imaginary part of eigenvalues, to load digital frequency offsets (DFOs), with purpose of improving the transmission capacity and mitigating amplified spontaneous emission (ASE) noise of DS-NFDM system. 1 GBaud DS-NFDM simulation results reveal that after 960 km optical fiber transmission, the 2D-DFOL scheme reduces optical signal-to-noise ratio (OSNR) penalty by about 7.1 dB compared to b-coefficient 32 quadrature amplitude modulation (QAM) scheme. Moreover, the proposed scheme achieves a maximum linewidth tolerance of about 1.5 MHz. © 2023 IEEE.

关键词： ASE noise mitigation eigenvalue position encoding two-dimensional digital frequency offset loading

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MpoxMamba: A Grouped Mamba-based Lightweight Hybrid Network for Mpox Detection

MpoxMamba: A Grouped Mamba-based Lightweight Hybrid Network ...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Yue, Yubiao Xue, Jun Liang, Haihuang Li, Zhenzhang Wang, Yufeng School of Biomedical Engineering Guangzhou Medical University Guangzhou China School of Computer Science and Technology Anhui University Hefei China School of Mathematics and Systems Science Guangdong Polytechnic Normal University Guangzhou China Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur Malaysia

ISBN: (纸本)9798350368741

Due to the lack of effective mpox detection tools, the mpox virus continues to spread worldwide and has been once again declared a public health emergency of international concern by the World Health Organization. Lightweight deep learning model-based detection systems are crucial to alleviate mpox outbreaks since they are suitable for widespread deployment, especially in resource-limited scenarios. However, the key to its successful application depends on ensuring that the model can effectively model local features and long-range dependencies in mpox lesions while maintaining lightweight. Inspired by the success of Mamba in modeling long-range dependencies and its linear complexity, we proposed a lightweight hybrid architecture called MpoxMamba for efficient mpox detection. MpoxMamba utilizes depth-wise separable convolutions to extract local feature representations in mpox skin lesions and greatly enhances the model's ability to model the global contextual information by grouped Mamba modules. Notably, MpoxMamba's parameter size and FLOPs are 0.77M and 0.53G, respectively. Experimental results on two widely recognized benchmark datasets demonstrate that MpoxMamba outperforms state-of-the-art lightweight models and existing mpox detection methods. Importantly, we developed a web-based online application to provide free mpox detection. The source code of MpoxMamba and the developed online application are available at https://***/YubiaoYue/MpoxMamba. © 2025 IEEE.

关键词： Deep Leraning Lightweight Model Mpox Detection Vision Mamba

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A high-performance multi-wavelength optical switch based on multiple Fano resonances in an all-dielectric metastructure

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Optoelectronics Letters 2024年第4期20卷 193-199页

作者： CAO Shuangshuang FAN Xinye FANG Wenjing CHEN Huawei BAI Chenglin TONG Cunzhu School of Physics Science and Information Engineering Liaocheng UniversityLiaocheng 252000China Shandong Provincial Key Laboratory of Optical Communication Science and Technology Liaocheng 252000China Liaocheng Key Laboratory of Industrial-Internet Research and Application Liaocheng 252000China Institute of Semiconductors Chinese Academy of SciencesBeijing 100083China State Key Laboratory of Luminescence and Applications Changchun Institute of OpticsFine Mechanics and PhysicsChinese Academy of SciencesChangchun 130033China

The multi-wavelength optical switch based on an all-dielectric metastructure consisting of four asymmetric semi-circular rings was designed and analyzed in this *** Fano resonance modes,which can be explained by bound states in the continuum(BIC)theory,are excited in our structure with a maximum Q-factor of about 2450 and a modulation depth close to 100%.By changing the polarization direction of the incident light,the transmission amplitude of Fano resonances can get effectively *** on this tuning property,the metastructure can achieve a multi-wavelength optical switch in the near-infrared region(900—980 nm)and the maximum extinction ratio can reach 38.3 d *** addition,the results indicate that the Fano resonances are sensitive to the changes in the refractive *** sensitivity(S)and the figure of merit(FOM)are 197 nm/RIU and 492 *** proposed metastructure has promising potential in applications such as optical switches,sensors,modulators and lasers.

关键词： dielectric structure resonance

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Transformer-Based Deep Hashing Method for Multi-Scale Feature Fusion 48

Transformer-Based Deep Hashing Method for Multi-Scale Featur...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： He, Chao Wei, Hongxi Inner Mongolia University School of Computer Science Hohhot China Provincial Key Laboratory of Mongolian Information Processing Technology Hohhot China National and Local Joint Engineering Research Center of Mongolian Information Processing Technology Hohhot China

ISBN: (纸本)9781728163277

The deep image hashing aims to map the input image into simply binary hash codes via deep neural networks. Motivated by the recent advancements of Vision Transformers (ViT), many deep hashing methods based on ViT have been proposed. Nevertheless, the ViT has enormous number of model parameters and high computational complexity. Moreover, the last layer of the ViT outputs only the classification tokens as image feature vectors, while the rest of the vectors are discarded. This results in the inefficiency of the model computation and the neglect of useful image information. Therefore, this paper proposes a Transformer-based deep hashing method for multi-scale feature fusion (TDH). Specifically, we use a hierarchical Transformer backbone to capture both global and local features of images. The hierarchical Transformer utilizes a local self-attention mechanism to process image blocks in parallel, which reduces computational complexity and promotes computational efficiency. Multi-scale feature fusion module captures all image feature vectors of the hierarchical Transformer output to obtain more enriched image feature information. We perform comprehensive experiments on three widely-studied datasets: CIFAR-10, NUS-WIDE and IMAGENET. The experimental results demonstrate that the proposed method in this paper indicates superior results compared to the existing state-of-the-art work. Source code is available https://***/shuaichaochao/TDH. © 2023 IEEE.

关键词： deep hashing hash code image retrieval multi-scale feature fusion Transformer

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Mean-Square Exponential Consensus of Nonlinear Multi-Agent systems via Distributed Random Impulsive Control 49

Mean-Square Exponential Consensus of Nonlinear Multi-Agent S...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Yu, Yi He, Wangli Yang, Yanping East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Processes Ministry of Education Shanghai China Engineering Research Center of Process System Engineering Ministry of Education East China University of Science and Technology Shanghai China College of Information Science and Technology and Engineering Research Center of Digitized Donghua University Shanghai China

ISBN: (纸本)9798350331820

This paper aims to study mean-square exponential consensus of nonlinear leader-following multi-agent systems (MASs) in the presence of noise via distributed random impulsive control. The noise is driven by a second-order moment process with bounded mean power. A distributed random impulsive controller whose impulses occur at random moments is designed to ensure the desired consensus performance while enhancing security of the system. Sufficient conditions in terms of the network topology and impulsive parameter are derived, using the Lyapunov-based approach and properties of stochastic process. Finally, a numerical example is presented to demonstrate the effectiveness of our theoretical results. © 2023 IEEE.

关键词： Multi agent systems

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Poster Abstract: Enhancing Human Motion Sensing with synthesized Millimeter-Waves 23

Poster Abstract: Enhancing Human Motion Sensing with synthes...

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23rd ACM/IEEE International Conference on information Processing in Sensor Networks, IPSN 2024

作者： Zhang, Xiaotong Wang, Kun Li, Zhenjiang Zhang, Jin City University of Hong Kong Department of Computer Science Hong Kong Hong Kong Southern University of Science and Technology Res. Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering Shenzhen China Peng Cheng Laboratory Shenzhen China

ISBN: (纸本)9798350362015

This poster introduces SynMotion, a novel mmWave-based human motion sensing system addressing the scarcity of training datasets. By synthesizing mmWave signals using existing vision-based human motion datasets, this system overcomes the challenge of collecting and labeling mmWave data, facilitating wider adoption of mmWave technology for applications like activity recognition, skeleton tracking and radar placement recommendation. © 2024 IEEE.

关键词： Millimeter waves

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