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In situ preparation of Ag@AgCl/Bio-veins composites and their photocatalytic activity and recyclability

Frontiers of Chemical science and engineering 2023年第7期17卷 906-917页

作者： Min Zou Chao Tan Zhengqiu Yuan Ming Wu Jian Jian Lei Zhang Yan Zhang Zhou Ma Hu Zhou School of Resource&Environment and Safety Engineering Hunan University of Science and TechnologyXiangtan 411201China Key Laboratory of Theoretical Organic Chemistry and Functional Molecules Ministry of EducationFunctional Film Materials Engineering Research Center of Hunan ProvinceHunan Provincial Key Laboratory of Advanced Materials for New Energy Storage and ConversionSchool of Chemistry and Chemical EngineeringHunan University of Science and TechnologyXiangtan 411201China School of Information and Electrical Engineering Hunan University of Science and TechnologyXiangtan 411201China

The industrial application of nano-photocatalysts in wastewater treatment has been severely restricted for a long time due to their difficult separation,poor reusability,and low *** this work,a facile strategy was proposed to enhance the photocatalytic activity and recovery performance of Ag@AgCl *** veins(Bio-veins)with a unique 3D porous construction were used as carriers for the in-situ growth of Ag@AgCl *** electron microscopy results showed that the Ag@AgCl nanoparticles were uniformly loaded on the surface and interior of the Bio-veins,and the size of the Ag@AgCl nanoparticles immobilized on the Bio-veins(50–300 nm)was significantly smaller than Ag@AgCl obtained by the co-precipitation method(1–3μm).The Bio-veins played a vital role in the photocatalysis reaction *** degradation efficiency of the Ag@AgCl/Bio-veins(CI4)was up to 3.50 times as high as pure Ag@***,the composites also exhibited excellent recyclability and stability under both visible and solar *** work provided a suitable strategy for nano-photocatalysts for practical application and may also offer new possibilities for the high-value utilization of biomass materials.

关键词： Ag@AgCl biological veins photocatalytic activity recyclability

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GPT-4 enhanced multimodal grounding for autonomous driving:Leveraging cross-modal attention with large language models

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Communications in Transportation Research 2024年第1期4卷 5-23页

作者： Haicheng Liao Huanming Shen Zhenning Li Chengyue Wang Guofa Li Yiming Bie Chengzhong Xu State Key Laboratory of Internet of Things for Smart City and Department of Computer and Information Science University of MacaoMacao SAR999078China Department of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu610000China State Key Laboratory of Internet of Things for Smart City and Departments of Civil and Environmental Engineering and Computer and Information Science University of MacaoMacao SAR999078China State Key Laboratory of Internet of Things for Smart City and Departments of Civil and Environmental Engineering University of MacaoMacao SAR999078China College of Mechanical and Vehicle Engineering Chongqing UniversityChongqing400030China School of Transportation Jilin UniversityChangchun130000China

In the field of autonomous vehicles(AVs),accurately discerning commander intent and executing linguistic commands within a visual context presents a significant *** paper introduces a sophisticated encoder-decoder framework,developed to address visual grounding in *** Context-Aware Visual Grounding(CAVG)model is an advanced system that integrates five core encoders—Text,Emotion,Image,Context,and Cross-Modal—with a multimodal *** integration enables the CAVG model to adeptly capture contextual semantics and to learn human emotional features,augmented by state-of-the-art Large Language Models(LLMs)including *** architecture of CAVG is reinforced by the implementation of multi-head cross-modal attention mechanisms and a Region-Specific Dynamic(RSD)layer for attention *** architectural design enables the model to efficiently process and interpret a range of cross-modal inputs,yielding a comprehensive understanding of the correlation between verbal commands and corresponding visual *** evaluations on the Talk2Car dataset,a real-world benchmark,demonstrate that CAVG establishes new standards in prediction accuracy and operational ***,the model exhibits exceptional performance even with limited training data,ranging from 50%to 75%of the full *** feature highlights its effectiveness and potential for deployment in practical AV ***,CAVG has shown remarkable robustness and adaptability in challenging scenarios,including long-text command interpretation,low-light conditions,ambiguous command contexts,inclement weather conditions,and densely populated urban environments.

关键词： Autonomous driving Visual grounding Cross-modal attention Large language models Human-machine interaction

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Joint user profiling with hierarchical attention networks

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Frontiers of Computer science 2023年第3期17卷 133-143页

作者： Xiaojian LIU Yi ZHU Xindong WU Key Laboratory of Knowledge Engineering with Big Data(Hefei University of Technology) Ministry of EducationHefei 230009China School of Computer Science and Information Engineering Hefei University of TechnologyHefei 230009China School of Information Engineering Yangzhou UniversityYangzhou 225009China Mininglamp Academy of Sciences MininglampBeijing 100193China

User profiling by inferring user personality traits,such as age and gender,plays an increasingly important role in many real-world *** existing methods for user profiling either use only one type of data or ignore handling the noisy information of ***,they usually consider this problem from only one *** this paper,we propose a joint user profiling model with hierarchical attention networks(JUHA)to learn informative user representations for user *** JUHA method does user profiling based on both inner-user and inter-user *** explore inner-user features from user behaviors(e.g.,purchased items and posted blogs),and inter-user features from a user-user graph(where similar users could be connected to each other).JUHA learns basic sentence and bag representations from multiple separate sources of data(user behaviors)as the first round of data *** this module,convolutional neural networks(CNNs)are introduced to capture word and sentence features of age and gender while the self-attention mechanism is exploited to weaken the noisy *** this,we build another bag which contains a user-user ***-user features are learned from this bag using propagation information between linked users in the *** acquire more robust data,inter-user features and other inner-user bag representations are joined into each sentence in the current bag to learn the final bag ***,all of the bag representations are integrated to lean comprehensive user representation by the self-attention *** experimental results demonstrate that our approach outperforms several state-of-the-art methods and improves prediction performance.

关键词： user profiling hierarchical attention joint learning inner-user feature inter-user feature

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An Efficient and Provably Secure SM2 key-Insulated Signature Scheme for Industrial Internet of Things

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Computer Modeling in engineering & sciences 2024年第1期138卷 903-915页

作者： Senshan Ouyang Xiang Liu Lei Liu Shangchao Wang Baichuan Shao Yang Zhao School of Mechanical Engineering Northwestern Polytechnical UniversityXi’anChina Department of Process and Information Technology Chengdu Aircraft Industrial(Group)Co.Ltd.ChengduChina School of Information and Software Engineering The Network and Data Security Key Laboratory of Sichuan ProvinceUniversity of Electronic Science and Technology of ChinaChengduChina

With the continuous expansion of the Industrial Internet of Things(IIoT),more andmore organisations are placing large amounts of data in the cloud to reduce ***,the channel between cloud servers and smart equipment is not trustworthy,so the issue of data authenticity needs to be *** SM2 digital signature algorithm can provide an authentication mechanism for data to solve such ***,it still suffers from the problem of key *** order to address this concern,this study first introduces a key-insulated scheme,SM2-KI-SIGN,based on the SM2 *** scheme boasts strong key insulation and secure *** scheme uses the elliptic curve algorithm,which is not only more efficient but also more suitable for IIoT-cloud ***,the security proof of SM2-KI-SIGN is given under the Elliptic Curve Discrete Logarithm(ECDL)assumption in the random oracle.

关键词： key-insulated SM2 algorithm digital signature Industrial Internet of Things(IIoT) provable security

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An Attention-based LSTM price prediction model based on a single time series information 6

An Attention-based LSTM price prediction model based on a si...

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6th International Conference on Intelligent Control, Measurement and Signal Processing, ICMSP 2024

作者： Tian, Jiaming Dang, Yuzhuo Huang, Hongbin National University of Defense Technology Laboratory for Big Data and Decision Changsha China Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology Changsha China

ISBN: (纸本)9798331516550

With the continuous improvement of people's living standards, people's income from work has gradually increased, and their remaining savings have also gradually increased. In order to avoid the problem of currency devaluation and shrinking savings caused by inflation, investment is regarded as an indispensable asset allocation method. Among investment products, gold has always been favored for its store of value;in the past decade, the cryptocurrency Bitcoin has been limited in number due to its unique technology, causing a new wave of investment in Bitcoin. At present, most of the existing forecasting models are for forecasting stock prices, and there are multiple forecasting models. We used grayscale prediction, time series analysis method and LSTM prediction model based on Attention mechanism to predict and analyze the results of two investment products. The experiment found that the LSTM prediction model based on Attention mechanism had the best prediction performance of the two investment products. © 2024 IEEE.

关键词： Prediction models

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Decomposing Visual and Semantic Correlations for Both Fully Supervised and Few-Shot Image Classification

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第4期5卷 1658-1668页

作者： Zhang, Chunjie Zheng, Xiaolong Beijing Jiaotong University Institute of Information Science Beijing100044 China Beijing Jiaotong University Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China University of Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems The State of Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence Beijing100190 China

Most image classification methods are designed to either boost the classification accuracies with abundant supervision, or cope with the shortage of supervision information. This is often achieved by using the visual and semantic information of other sources. However, these methods use the visual and semantic information within the same class independently, leaving their intrinsic correlations unconsidered. Objects and disturbing components as well as noise exist on the same image. Besides, semantic representations also contain noisy information. To solve the problems mentioned above, we propose a novel method for both fully supervised image classification and few-shot image classification by decomposing visual and semantic correlations. We jointly explore the intrinsic correlations of visual and semantic information of images within the same class. For each class, we decompose its visual and semantic correlations using low-rank and sparse constraint respectively. The decomposed low-rank parts character the intrinsic correlations of images can be used in a linear transformation way. Using the decomposed parts of each class, Classification can be achieved by reconstruction error minimization. We conduct experiments on several datasets for both fully supervised image classification and few-shot image classification. Experimental results well show the effectiveness of the proposed method. © 2020 IEEE.

关键词： Semantics

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Spectrally resolved Franson interference

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science China(Physics,Mechanics & Astronomy) 2024年第5期67卷 11-17页

作者： Rui-Bo Jin Zi-Qi Zeng Dan Xu Chen-Zhi Yuan Bai-Hong Li You Wang Ryosuke Shimizu Masahiro Takeoka Mikio Fujiwara Masahide Sasaki Pei-Xiang Lu Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of TechnologyWuhan 430205China School of Physics and Information Science Shaanxi University of Science and TechnologyXi'an 710021China Southwest Institute of Technical Physics Chengdu 610041China Graduate School of Informatics and Engineering University of Electro-CommunicationsTokyo 182-8585Japan Department of Electronics and Electrical Engineering Keio UniversityKanagawa 223-8522Japan National Institute of Information and Communications Technology Tokyo 184-8795Japan

Franson interference can be used to test the nonlocal features of energy-time entanglement and has become a standard in quantum ***,most of the previous Franson interference experiments were demonstrated in the time domain,and the spectral properties of Franson interference have not been fully ***,we theoretically and experimentally demonstrate spectrally resolved Franson interference using biphotons with different correlations,including positive correlation,negative correlation,and *** is found that the joint spectral intensities of the biphotons can be modulated along both the signal and idler directions,which has potential applications in generating high-dimensional frequency entanglement and time-frequency grid *** work may provide a new perspective for understanding the spectral-temporal properties of the Franson interferometer.

关键词： resolved correlation spectral

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Detection of Oscillations in Process Control Loops From Visual Image Space Using Deep Convolutional Networks

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 982-995页

作者： Tao Wang Qiming Chen Xun Lang Lei Xie Peng Li Hongye Su the Department of Electronic Engineering the School of InformationYunnan UniversityKunming 650091China DAMO Academy Alibaba GroupHangzhou 311100China the State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou 310027China

Oscillation detection has been a hot research topic in industries due to the high incidence of oscillation loops and their negative impact on plant *** numerous automatic detection techniques have been proposed,most of them can only address part of the practical *** oscillation is heuristically defined as a visually apparent periodic ***,manual visual inspection is labor-intensive and prone to missed *** neural networks(CNNs),inspired by animal visual systems,have been raised with powerful feature extraction *** this work,an exploration of the typical CNN models for visual oscillation detection is ***,we tested MobileNet-V1,ShuffleNet-V2,Efficient Net-B0,and GhostNet models,and found that such a visual framework is well-suited for oscillation *** feasibility and validity of this framework are verified utilizing extensive numerical and industrial *** with state-of-theart oscillation detectors,the suggested framework is more straightforward and more robust to noise and *** addition,this framework generalizes well and is capable of handling features that are not present in the training data,such as multiple oscillations and outliers.

关键词： Convolutional neural networks(CNNs) deep learning image processing oscillation detection process industries

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Pressure-induced superconductivity in the topological crystalline insulator NaCd4As3

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Physical Review B 2024年第6期110卷 L060509-L060509页

作者： Haiyang Yang Yonghui Zhou Jing Wang Shuyang Wang Chao An Ying Zhou Xuliang Chen Lili Zhang Xiaoping Yang Zhaorong Yang Anhui Key Laboratory of Low-Energy Quantum Materials and Devices Science Island Branch of Graduate School Institute of Advanced Magnetic Materials College of Materials and Environmental Engineering Institutes of Physical Science and Information Technology Shanghai Advanced Research Institute

Recently, a united symmetry-protected topological crystalline insulator (TCI) NaCd4As3 has been discovered experimentally, which further features a temperature-driven transformation from TCI to TI due to the mirror symmetry broken across a rhombohedral-to-monoclinic structural transition. Here, we report the pressure tuning of structural property and emergence of superconductivity in TCI NaCd4As3 by comprehensive high-pressure experiments in diamond-anvil cell. Temperature-dependent Raman measurements show that the structural transition temperature gradually reduces upon compression and is completely suppressed above ∼4 GPa. The stable rhombohedral phase further undergoes amorphization evidenced by synchrotron x-ray-diffraction result, which sets in at 20.7 GPa and completes at 34.4 GPa. Along with the complete amorphization, the metallization and superconductivity with a critical temperature Tc∼2.5 K appear simultaneously, as observed in transport experiments. We argue that the sudden enhancement in Tc across 60.0 GPa is likely related to the pressure-driven amorphous polymorphism. Our finding unravels the fundamental structure-property relationship and highly tunable crystallographic symmetry in NaCd4As3 by external pressure, potentially sparking further investigations via alternative tuning strategies.

关键词： Phase transitions Pressure effects Superconductivity Crystalline systems Topological materials Pressure techniques

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DDCTrack： Dynamic Token Sampling for Efficient UAV Transformer Tracking 27th

DDCTrack： Dynamic Token Sampling for Efficient UAV Transfor...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Du, Guocai Zhou, Peiyong Yadikar, Nurbiya Aysa, Alimjan Ubul, Kurban College of Information Science and Engineering Xinjiang University Urumqi830046 China The Key Laboratory of Multilingual Information Technology Xinjiang University Urumqi830046 China

ISBN: (纸本)9783031783531

Although state-of-the-art transformer models have shown promising results in unmanned aerial vehicle (UAV) tracking, they come with high computational demands. Existing tracking methods aim to reduce computational complexity by controlling the number of tokens. However, this method is not effective for all tracking methods. Therefore, we propose a novel dynamic token sampling for an efficient UAV transformer tracking framework. Unlike previous transformer-based tracking methods, our method avoids the need for complex head networks like classification and regression. It solely employs our newly designed encoder, comprising three key components: Dynamic Position Embedding, Dynamic Token Sampler, and Convolutional Feed-Forward Network. This module enhances visual representation by scoring and dynamically sampling tokens, allowing for a flexible token count that adapts to target changes within each frame. We utilize a simple image-sequence contrastive loss as the loss function. Our approach not only simplifies the tracking framework, but also achieves state-of-the-art performance on multiple challenging datasets at real-time run speeds. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Aircraft detection

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