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6th Asian Conference on Artificial Intelligence Technology, ACAIT 2022

作者： Fang, Baofu Zhou, Shuai Wang, Hao Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology School of Computer Science and Information Engineering Hefei China

ISBN: (纸本)9781665453110

Most of the existing slam algorithms are designed based on the assumption of a static environment, this strong assumption limits the practical application of most slam systems. The main reason is that moving objects will cause feature mismatch in the pose estimation process, which in turn affects the accuracy of localization and mapping. In this paper, we propose a SLAM algorithm in a dynamic environment. First, we use the BlendMask network to detect potential moving objects to generate masks for dynamic objects. The geometrically constrained joint optical flow method is used to detect dynamic feature points. Secondly, aiming at the failure of semantic segmentation network segmentation, a missed detection compensation algorithm based on the invariance of adjacent frame speed is proposed. Finally, a keyframe selection strategy is proposed to construct a semantic octree graph containing only static objects. We evaluate our algorithm on TUM RGB-D and real scene datasets. The experimental results show that the algorithm has high accuracy and real-time performance. © 2022 IEEE.

关键词： Semantics

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Improved Self-Attention for Spodoptera Frugiperda Larval Instar Stages Identification 7

Improved Self-Attention for Spodoptera Frugiperda Larval Ins...

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7th International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2024

作者： Wang, Mingyang Lu, Ying Xu, Quanyuan College of Big Data and Intelligent Engineering Southwest Forestry University Kunming China Big Data State Forestry Administration on Southwest Forestry University Key Laboratory of Forestry and Ecological Kunming China

ISBN: (纸本)9798350350890

Spodoptera frugiperda (fall armyworm, FAW) is a pest that poses a significant threat to global agriculture, with its larvae exhibiting unique morphological characteristics and varying degrees of harm at different instar stages. This study proposes a method that incorporates an improved self-attention mechanism to achieve rapid and accurate identification of FAW larval instars. This method can be seamlessly integrated into convolutional neural networks (CNNs), enhancing recognition performance by focusing on the global features of images. Furthermore, this research has constructed an image dataset of FAW larvae at various developmental stages under field and laboratory conditions to validate the effectiveness of the proposed method. Experimental results demonstrate that our method improves the recognition accuracy across various CNN architectures, achieving accuracy enhancements of 5.49%, 7.38%, 5.79%, and 5.59% on Alexnet, vgg16, resnet50, and resnet101, respectively. Our approach provides technicians with a convenient, intelligent, and precise tool to identify FAW larval instar stages. © 2024 IEEE.

关键词： Invertebrates

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Scale-up Efficient Synthesis of α-Poly(L-lysine)

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Chinese Journal of Chemistry 2023年第19期41卷 2488-2492页

作者： Wenxiu Lv Maosheng Li Youhua Tao Key Laboratory of Polymer Ecomaterials Changchun Institute of Applied ChemistryChinese Academy of SciencesRenmin Street 5625ChangchunJilin130022 China School of Applied Chemistry and Engineering University of Science and Technology of ChinaHefeiAnhui230026 China

α-Poly(_(L)-lysine)(α-PLL)is a water-soluble cationic biopolymer containing the monomeric unitα-_(L)-lysine,which not only possesses excellent intrinsic properties but also can be modified via facile reactions between the side amine groups and many other functional ***-opening polymerization(ROP)is the most prevalently used technique for the synthesis of PL_(L)-based polypeptides,which involves initial conversion of theε-primary amine-protectedα-_(L)-lysine to the _(L)-lysine NCA ***,obtaining N-carboxyanhydrides(NCAs)in high purity has been a formidable challenge for over 50 years,let alone the large-scale ***,we show an unprecedented scale-up synthesis of _(L)-Cbz-LysNCA monomer and its polymers,generating linearα-poly(_(L)-lysine)with molecular weight(MW)up to 13.4 *** easy operated scale-up strategy will lay the foundations for the industrial preparation of _(L)-Cbz-LysNCA and its polymers,and further extend the realm of existing applications,offering a paradigm for scale-up synthesis of other polypeptides.

关键词： Scale-up _(L)-Cbz-LysNCA α-Poly(_(L)-lysine) Easy operation

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Rockburst prediction using artificial intelligence techniques:A review

Rock Mechanics Bulletin

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Rock Mechanics Bulletin 2024年第3期3卷 1-13页

作者： Yu Zhang Kongyi Fang Manchao He Dongqiao Liu Junchao Wang Zhengjia Guo School of Electrical and Information Engineering Beijing University of Civil Engineering and ArchitectureBeijing100044China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and ArchitectureBeijing100044China State Key Laboratory for Geomechanics and Deep Underground Engineering China University of Mining and TechnologyBeijing100083China Thomas Lord Department of Computer Science University of Southern CaliforniaLos Angeles90007CAUSA

Rockburst is a phenomenon where sudden,catastrophic failure of the rock mass occurs in underground deep regions or areas with high tectonic stress during the excavation *** disasters endanger the safety of people's lives and property,national energy security,and social interests,so it is very important to accurately predict *** rockburst prediction has not been able to find an effective prediction method,and the study of the rockburst mechanism is facing a *** the development of artificial intelligence(AI)techniques in recent years,more and more experts and scholars have begun to introduce AI techniques into the study of the rockburst *** previous research,several scholars have attempted to summarize the application of AI techniques in rockburst ***,these studies either are not specifically focused on reviews of the application of AI techniques in rockburst prediction,or they do not provide a comprehensive *** on the advantages of extensive interdisciplinary research and a deep understanding of AI techniques,this paper conducts a comprehensive review of rockburst prediction methods leveraging AI ***,pertinent definitions of rockburst and its associated hazards are ***,the applications of both traditional prediction methods and those rooted in AI techniques for rockburst prediction are summarized,with emphasis placed on the respective advantages and disadvantages of each ***,the strengths and weaknesses of prediction methods leveraging AI are summarized,alongside forecasting future research trends to address existing challenges,while simultaneously proposing directions for improvement to advance the field and meet emerging demands effectively.

关键词： Rockburst Rockburst prediction Artificial intelligence techniques

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Empowering Biomedical Named Entity Recognition Through Multi-Tagger Collaboration 27

Empowering Biomedical Named Entity Recognition Through Multi...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Zhao, Jin Xie, Jian Zhu, Tinghui Guo, Qian Li, Zhixu Xiao, Yanghua Shanghai Key Laboratory of Data Science School of Computer Science Fudan University China Department of Computer Science and Engineering East China University of Science and Technology China

ISBN: (纸本)9781643685489

Biomedical Named Entity Recognition (BioNER) plays a crucial role in automatically identifying specific categories of entities from biomedical texts. Currently, region-based methods have shown promising performance in BioNER. However, existing paradigms in the region-based methods suffer from inherent limitations, including the generation of negative samples, and the ignorance of token dependencies. To overcome these limitations, we propose a new paradigm, implemented as Token Cascade Tagger (TCT), which combines span identification and category classification. The TCT utilizes category information to enhance the correlation between the heads and tails of entities, effectively reducing the generation of negative samples. Additionally, we introduce a Token Dependency Tagger (TDT) that captures token dependencies within entity spans by identifying the longest span in a sentence. The TDT filters out incorrect spans and further improves the accuracy of span detection obtained from the TCT. Furthermore, we employ a multi-task learning framework to optimize both the TCT and TDT, leading to superior performance in BioNER. Extensive experiments on publicly available biomedical datasets demonstrate our method outperforms the previous state-of-the-art methods, achieving 92.44%, 92.54%, and 81.26% on NCBI-Disease, BC5CDR, and GENIA, respectively, in terms of F1 score. © 2024 The Authors.

关键词： Multi-task learning

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Towards next-generation diagnostic pathology:AIempowered label-free multiphoton microscopy

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Light(Science & Applications) 2024年第12期13卷 2887-2911页

作者： Shu Wang Junlin Pan Xiao Zhang Yueying Li Wenxi Liu Ruolan Lin Xingfu Wang Deyong Kang Zhijun Li Feng Huang Liangyi Chen Jianxin Chen School of Mechanical Engineering and Automation Fuzhou UniversityFuzhou 350108China Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education Fujian Provincial Key Laboratory of Photonics TechnologyFujian Normal UniversityFuzhou 350007China College of Computer and Data Science Fuzhou UniversityFuzhou 350108China Department of Radiology Fujian Medical University Union HospitalFuzhou 350001China Department of Pathology The First Affiliated Hospital of Fujian Medical UniversityFuzhou 350005China Department of Pathology Fujian Medical University Union HospitalFuzhou 350001China New Cornerstone Laboratory State Key Laboratory of Membrane BiologyBeijing Key Laboratory of Cardiometabolic Molecular MedicineInstitute of Molecular MedicineNational Biomedical Imaging CenterSchool of Future TechnologyPeking UniversityBeijing 100091China

Diagnostic pathology,historically dependent on visual scrutiny by experts,is essential for disease *** digital pathology and developments in computer vision technology have led to the application of artificialintelligence(AI)in this *** these advancements,the variability in pathologists’subjective interpretations ofdiagnostic criteria can lead to inconsistent *** meet the need for precision in cancer therapies,there is anincreasing demand for accurate pathological ***,traditional diagnostic pathology is evolvingtowards“next-generation diagnostic pathology”,prioritizing on the development of a multi-dimensional,intelligentdiagnostic *** nonlinear optical effects arising from the interaction of light with biological tissues,multiphoton microscopy(MPM)enables high-resolution label-free imaging of multiple intrinsic components acrossvarious human pathological ***-empowered MPM further improves the accuracy and efficiency of diagnosis,holding promise for providing auxiliary pathology diagnostic methods based on multiphoton diagnostic *** review,we systematically outline the applications of MPM in pathological diagnosis across various human diseases,and summarize common multiphoton diagnostic ***,we examine the significant role of AI inenhancing multiphoton pathological diagnosis,including aspects such as image preprocessing,refined differentialdiagnosis,and the prognostication of *** also discuss the challenges and perspectives faced by theintegration of MPM and AI,encompassing equipment,datasets,analytical models,and integration into the existingclinical ***,the review explores the synergy between AI and label-free MPM to forge novel diagnosticframeworks,aiming to accelerate the adoption and implementation of intelligent multiphoton pathology systems inclinical settings.

关键词： multiphoton refined diagnosis

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Electrochemical response of MoS_(2) nanosheets/SiO_(2)-NH_(2) nanoparticles modified glassy carbon electrode to phenylacetic acid

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Rare Metals 2023年第12期42卷 4142-4152页

作者： Tian-Yao Qi Zhen-Yu Yuan Fan-Li Meng College of Information Science and Engineering Northeastern UniversityShenyang 110819China Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology Qinhuangdao 066004China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern UniversityShenyang 110819China Key Laboratory of Data Analytics and Optimization for Smart Industry(Northeastern University) Ministry of EducationShenyang 110819China

Phenylacetic acid(PAA)is a primary raw material for illegal Methamphetamine(MATM)synthesis under the strong precursor chemicals supervisions of safrole and ***,trace detection of PAA at ultra-low concentration is a strategic technique and an urgent issue in the field of drug *** this paper,trace determination of PAA at sub-nmol-L-1 concentration level is achieved by hydrogen bond adsorption and electrochemical catalysis through the prepared aminated SiO_(2)nanoparticles(SiO_(2)-NH_(2) NPs)and MoS_(2) nanosheets(NSs)modified glassy carbon electrode(GCE).The prepared MoS_(2) NS s/SiO_(2)-NH_(2) NPs modified electrode represents a detecting limit of 0.0989 nmol·L^(-1)and an obvious increasing linear range before the concentration increasement up to 60 nmol·L^(-1)in square wave voltammetry(SWV)responses of *** SWV response of the modified electrode to PAA in the concentration range within 100 nmol·L^(-1)is higher than phenol,acetic acid(HOAc)and benzoic Acid(BEN).This electrochemical method for trace detection of PAA in aqueous solution with desired performance provides a feasible scheme for the detection of other drugs and aromatic precursor chemicals.

关键词： Phenylacetic acid detection Modified electrode MoS_(2)nanosheet Square wave voltammetry

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Corrosion-Resistant Polymer-Derived SiOC Membrane for Effective Organic Removal via Synergistic Adsorption and Peroxymonosulfate Activation

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Transactions of Tianjin university 2024年第3期30卷 238-249页

作者： Jiankun Ji Yarong Gu Jianning Zhang Chongwen Yu Xiao Hu Yueping Bao Yujie Song School of Materials Science and Chemical Engineering Ningbo UniversityNingbo 315211China Zhejiang Key Laboratory of Data-Driven High-Safety Energy Materials and Applications Ningbo Key Laboratory of Special Energy Materials and ChemistryCenter for Advanced Organosilicon PrecursorsNingbo Institute of Materials Technology and EngineeringChinese Academy of SciencesNingbo 315201China Qianwan Institute of CNITECH Ningbo 315336China University of Chinese Academy of Sciences Beijing 100049China School of Materials Science and Engineering Nanyang Technological UniversitySingapore 639798Singapore College of Environmental Science and Engineering Nankai UniversityTianjin 300350China Advanced Energy Science and Technology Guangdong Laboratory Huizhou 516029China

A major challenge is to construct ceramic membranes with tunable structures and functions for water ***,a novel corrosion-resistant polymer-derived silicon oxycarbide(SiOC)ceramic membrane with designed architectures was fabricated by a phase separation method and was applied in organic removal via adsorption and oxidation for the first *** pore structure of the as-prepared SiOC ceramic membranes was well controlled by changing the sintering temperature and polydimethylsiloxane content,leading to a pore size of 0.84–1.62μm and porosity of 25.0–43.8%.Corrosion resistance test results showed that the SiOC membranes sustained minimal damage during 24 h exposure to high-intensity acid–base conditions,which could be attributed to the chemical inertness of *** rhodamine 6G(R6G)as the model pollutant,the SiOC membrane demonstrated an initial eff ective removal rate of 99%via adsorption;however,the removal rate decreased as the system approached adsorption *** peroxymonosulfate was added into the system,efficient and continuous degradation of R6G was observed throughout the entire period,indicating the potential of the as-prepared SiOC membrane in oxidation-related ***,this work provides new insights into the construction of novel polymer-derived ceramic membranes with well-defined structures and functions.

关键词： Polymer-derived ceramics Membrane Corrosion resistance Adsorption Oxidation

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SlagNet: A Real-Time Slag Segmentation Model Based on Context and Edge Fusion 16th

SlagNet: A Real-Time Slag Segmentation Model Based on Conte...

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16th International Conference on Modelling, Identification and Control, ICMIC 2024

作者： Liu, Kecheng Li, Jiangyun Yuan, Li School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education Beijing100083 China

ISBN: (纸本)9789819617760

In the process of iron and steel smelting, steel slag is inevitably produced as a byproduct. Accurately identifying steel slag is a prerequisite for controlling the content of steel slag. Conventional vision-based steel slag processing solutions are constrained by real-time performance or robustness against disturbances, rendering them directly applied in industrial sites. To address these issues, SlagNet, a steel slag segmentation network with real-time performance and strong disturbance resistance, is designed in this paper. By designing a lightweight branch to extract rich context information, and combining edge branches to supplement the slag edge information, 77.69 mIOU and 13.25 FPS are achieved in the field collection of slagging data set. The results indicate that SlagNet achieves the optimal balance between real-time performance and accuracy in comparison with other segmentation methods, thereby meeting the requirements of industrial sites. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Slags

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Description of elastic scattering for 7Li-induced reactions on 1p-shell nuclei

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Chinese Physics C 2024年第2期48卷 153-161页

作者：徐永丽苏新武孙志豪韩银录孙小军张冬红蔡崇海 College of Physics and Electronic Science Shanxi Datong UniversityDatong 037009China Graduate School of China Academy of Engineering Physics Beijing 100088China Key Laboratory of Nuclear Data China Institute of Atomic EnergyBeijing 102413China College of Physics Guangxi Normal UniversityGuilin 541004China Department of Physics Nankai UniversityTianjin 300071China

The experimental data of elastic scattering angular distributions for 9Be,10B,11B,12C,13C,15N,and 16O targets from 4.5 to 131.8 MeV and 7Li target from 8.0 to 42.0 MeV are fitted to realize the global phenomenological optical potentials(GPOPs)for the 7Li-induced reactions on 1p-shell ***,the 7Li elastic scattering from the 1p-shell nuclei can be systematically described using the established *** elastic scattering angular distributions are also reanalyzed using a microscopic method within the framework of the new version of double folding S?o Paulo potential(SPP2).To better describe the elastic scattering at backward angles,the contribution of elastic transfer is further estimated by the distorted wave Born approximation(DWBA)*** on the obtained GPOPs,the inelastic scattering angular distributions are also obtained through the coupled channels(CC)method for the different excited states.

关键词： optical potential elastic scattering nuclear reaction mechanisms

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