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A Survey on Chinese Sign Language Recognition:From Traditional Methods to Artificial Intelligence

Computer Modeling in Engineering & Sciences 2024年第7期140卷 1-40页

作者： Xianwei Jiang Yanqiong zhang Juan Lei yudong zhang School of Mathematics and Information Science Nanjing Normal University of Special EducationNanjing210038China School of Computing and Mathematical Sciences University of LeicesterLeicesterLE17RHUK Department of Information Technology Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia

Research on Chinese Sign Language(CSL)provides convenience and support for individuals with hearing impairments to communicate and integrate into *** article reviews the relevant literature on Chinese Sign Language Recognition(CSLR)in the past 20 *** Markov Models(HMM),Support Vector Machines(SVM),and Dynamic Time Warping(DTW)were found to be the most commonly employed technologies among traditional *** from the rapid development of computer vision and artificial intelligence technology,Convolutional Neural Networks(CNN),3D-CNN,YOLO,Capsule Network(CapsNet)and various deep neural networks have sprung *** Neural Networks(DNNs)and their derived models are integral tomodern artificial intelligence *** addition,technologies thatwerewidely used in the early days have also been integrated and applied to specific hybrid models and customized identification *** language data collection includes acquiring data from data gloves,data sensors(such as Kinect,LeapMotion,etc.),and high-definition ***,facial expression recognition,complex background processing,and 3D sign language recognition have also attracted research interests among *** to the uniqueness and complexity of Chinese sign language,accuracy,robustness,real-time performance,and user independence are significant challenges for future sign language recognition ***,suitable datasets and evaluation criteria are also worth pursuing.

关键词： Chinese Sign Language Recognition deep neural networks artificial intelligence transfer learning hybrid network models

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Noise-tolerate and adaptive coefficient zeroing neural network for solving dynamic matrix square root

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 167-177页

作者： Xiuchun Xiao Chengze Jiang Qixiang Mei yudong zhang School of Electronics and Information Engineering Guangdong Ocean UniversityZhanjiangChina School of Cyber Science and Engineering Southeast UniversityNanjingChina School of Computing and Mathematical Sciences University of LeicesterLeicesterUK

The solving of dynamic matrix square root(DMSR)problems is frequently encountered in many scientific and engineering *** the original zeroing neural network is powerful for solving the DMSR,it cannot vanish the influence of the noise perturbations,and its constant-coefficient design scheme cannot accelerate the convergence ***,a noise-tolerate and adaptive coefficient zeroing neural network(NTACZNN)is raised to enhance the robust noise immunity performance and accelerate the conver-gence speed ***,the global convergence and robustness of the pro-posed NTACZNN are theoretically analysed under an ideal environment and noise-perturbed ***,some illustrative simulation examples are designed and performed in order to substantiate the efficacy and advantage of the NTACZNN for the DMSR problem *** with some existing ZNNs,the proposed NTACZNN possesses advanced performance in terms of noise tolerance,solution accuracy,and convergence rate.

关键词： adaptive intelligent systems neural network real-time systems

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Gaussian Backbone-Based Spherical Evolutionary Algorithm with Cross-search for Engineering Problems

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Journal of Bionic Engineering 2024年第2期21卷 1055-1091页

作者： Yupeng Li Dong Zhao Ali Asghar Heidari Shuihua Wang Huiling Chen yudong zhang College of Computer Science and Technology Changchun Normal UniversityChangchun130032JilinChina School of Surveying and Geospatial Engineering College of EngineeringUniversity of TehranTehranIran School of Computing and Mathematical Sciences University of LeicesterLeicesterLE17RHUK Department of Biological Sciences Xi’an Jiaotong-Liverpool UniversitySuzhou215123JiangsuChina Key Laboratory of Intelligent Informatics for Safety and Emergency of Zhejiang Province Wenzhou UniversityWenzhou325035China School of Computer Science and Engineering Southeast UniversityNanjing210096China

In recent years,with the increasing demand for social production,engineering design problems have gradually become more and more *** novel and well-performing meta-heuristic algorithms have been studied and developed to cope with this *** them,the Spherical Evolutionary Algorithm(SE)is one of the classical representative methods that proposed in recent years with admirable optimization ***,it tends to stagnate prematurely to local optima in solving some specific ***,this paper proposes an SE variant integrating the Cross-search Mutation(CSM)and Gaussian Backbone Strategy(GBS),called *** this study,the CSM can enhance its social learning ability,which strengthens the utilization rate of SE on effective information;the GBS cooperates with the original rules of SE to further improve the convergence effect of *** objectively demonstrate the core advantages of CGSE,this paper designs a series of global optimization experiments based on IEEE CEC2017,and CGSE is used to solve six engineering design problems with *** final experimental results fully showcase that,compared with the existing well-known methods,CGSE has a very significant competitive advantage in global tasks and has certain practical value in real ***,the proposed CGSE is a promising and first-rate algorithm with good potential strength in the field of engineering design.

关键词： Meta-heuristic algorithms Engineering optimization Spherical evolution algorithm Global optimization

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Manipulation of magnetocaloric and elastocaloric effects in Ni-Mn-In alloys by lattice volume and magnetic variation:Effect of Co and Fe co-doping

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Journal of Materials Science & Technology 2024年第5期172卷 156-165页

作者： Xinzeng Liang Chi zhang Jing Bai Jianglong Gu yudong zhang Claude Esling Xiang Zhao Liang Zuo School of Materials Science and Engineering Shenyang University of TechnologyShenyang 110870China Key Laboratory for Anisotropy and Texture of Materials Northeastern UniversityShenyang 110819China School of Resources and Materials Northeastern University at QinhuangdaoQinhuangdao 066004China State Key Laboratory of Metastable Materials Science and Technology Yanshan UniversityQinhuangdao 066004China Laboratoire d’Étude des Microstructures et de Mécanique des Matériaux LEM3 CNRSUMR 7239University of Lorraine57045 MetzFrance

The effects of Co and Fe co-doping Ni-Mn-In alloy on the phase stability,lattice parameters,mag-netic properties,and electronic structures are systematically investigated by using the first-principles *** indicate that Fe atoms replace the excess Mn2 atoms by direct and indirect coex-istence(Fe→Mn 2 and Fe→In→Mn2);Co substitutes the Ni atoms by direct substitution(Co→Ni)for the Ni-Mn-In *** austenites all exhibit the ferromagnetic(FM)state for the studied *** NM martensites are in the ferrimagnetic(FIM-1)state for the Ni_(2)Mn_(1.5)In_(0.5),Ni_(2)Mn_(1.25)In_(0.5)Fe 0.25,Ni_(1.75)Mn_(1.5)In_(0.5)Co_(0.25),and Ni_(1.75)Mn_(1.25)In_(0.5)Co_(0.25)Fe 0.25 alloys,while the other compositions are in the FM *** phase stability of austenite and martensite decreases with increasing Co and Fe co-doping.A magnetic-structural coupling transition occurs at x<0.25 and y<*** Ni_(1.91)Mn_(1.5)In_(0.5)Co_(0.08)and Ni_(1.91)Mn_(1.42)In_(0.5)Co_(0.08)Fe_(0.08)alloys exhibit an A→6M→NM transformation,accompanied by a magnetic *** Co and Fe are co-doped,the hybridization strength between Co and Fe is greater than that between Co/Fe and *** enhancement of magnetocaloric and elastocaloric effects is favored by larger magnetization difference(△M)and lattice volume change(△V/V_(0)).Based on the calculated phase stability,magneto-structure coupling,△V/V 0 and c/a ratio,one can predict that the Ni_(2)-x Mn_(1.5)-y In_(0.5)Co x Fe y alloy with Co content 0≤x≤0.25 and Fe content 0≤y≤0.05 is predicted to have good magneto-controlled functional behavior.

关键词： Ni-Mn-In-Co-Fe Phase stability Magnetocaloric effect Elastocaloric effect

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Efficient Ship:A Hybrid Deep Learning Framework for Ship Detection in the River

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工程与科学中的计算机建模(英文) 2024年第1期138卷 301-320页

作者： Huafeng Chen Junxing Xue Hanyun Wen Yurong Hu yudong zhang School of Computer Engineering Jingchu University of TechnologyJingmen448000China School of Computer Science Yangtze UniversityJingzhou434023China School of Computing and Mathematic Sciences University of LeicesterLeicesterLE17RHUK

Optical image-based ship detection can ensure the safety of ships and promote the orderly management of ships in offshore *** deep learning researches on optical image-based ship detection mainly focus on improving one-stage detectors for real-time ship detection but sacrifices the accuracy of *** solve this problem,we present a hybrid ship detection framework which is named EfficientShip in this *** core parts of the EfficientShip are DLA-backboned object location(DBOL)and CascadeRCNN-guided object classification(CROC).The DBOL is responsible for finding potential ship objects,and the CROC is used to categorize the potential ship *** also design a pixel-spatial-level data augmentation(PSDA)to reduce the risk of detection model *** compare the proposed EfficientShip with state-of-the-art(SOTA)literature on a ship detection dataset called *** show our ship detection framework achieves a result of 99.63%(mAP)at 45 fps,which is much better than 8 SOTA approaches on detection accuracy and can also meet the requirements of real-time application scenarios.

关键词： Ship detection deep learning data augmentation object location object classification

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ThyroidNet:A Deep Learning Network for Localization and Classification of Thyroid Nodules

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 361-382页

作者： Lu Chen Huaqiang Chen Zhikai Pan Sheng Xu Guangsheng Lai Shuwen Chen Shuihua Wang Xiaodong Gu yudong zhang Ultrasonic Department Zhongda Hospital Affiliated to Southeast UniversityNanjing210009China School of Physics and Information Engineering Jiangsu Second Normal UniversityNanjing211200China School of Computing and Mathematical Sciences University of LeicesterLeicesterLE17RHUK Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia State Key Laboratory of MillimeterWaves Southeast UniversityNanjing210096China Jiangsu Province Engineering Research Center of Basic Education Big Data Application Jiangsu Second Normal UniversityNanjing211200China School of Software Engineering Quanzhou Normal UniversityQuanzhou362000China Department of Biological Sciences Xi’an Jiaotong-Liverpool UniversitySuzhou215123China

Aim:This study aims to establish an artificial intelligence model,ThyroidNet,to diagnose thyroid nodules using deep learning techniques ***:A novel method,ThyroidNet,is introduced and evaluated based on deep learning for the localization and classification of thyroid ***,we propose the multitask TransUnet,which combines the TransUnet encoder and decoder with multitask ***,we propose the DualLoss function,tailored to the thyroid nodule localization and classification *** balances the learning of the localization and classification tasks to help improve the model’s generalization ***,we introduce strategies for augmenting the ***,we submit a novel deep learning model,ThyroidNet,to accurately detect thyroid ***:ThyroidNet was evaluated on private datasets and was comparable to other existing methods,including U-Net and *** results show that ThyroidNet outperformed these methods in localizing and classifying thyroid *** achieved improved accuracy of 3.9%and 1.5%,***:ThyroidNet significantly improves the clinical diagnosis of thyroid nodules and supports medical image analysis *** research directions include optimization of the model structure,expansion of the dataset size,reduction of computational complexity and memory requirements,and exploration of additional applications of ThyroidNet in medical image analysis.

关键词： ThyroidNet deep learning TransUnet multitask learning medical image analysis

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Improving iconic memory through contrast detection training with HOA-corrected vision

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Fundamental Research 2024年第1期4卷 95-102页

作者： Ling Gong Junlei Zhao Yun Dai Zili Wang Fang Hou yudong zhang Zhong-Lin Lu Jiawei Zhou State Key Laboratory of Ophthalmology Optometry and Vision ScienceEye HospitalSchool of Ophthalmology and OptometryWenzhou Medical UniversityWenzhou 325027China Institute of Optics and Electronics Chinese Academy of SciencesChengdu 610209China The Key Laboratory of Adaptive Optics Chinese Academy of SciencesChengdu 610209China Chengdu University of Traditional Chinese Medicine Chengdu 610075China Division of Arts and Sciences New York University ShanghaiShanghai 200126China Center for Neural Science Department of PsychologyNew York UniversityNew York 10003United States NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai Shanghai 200062China

Iconic memory and short-term memory are not only crucial for perception and cognition,but also of great importance to mental ***,we first showed that both types of memory could be improved by improving limiting processes in visual processing through perceptual *** adults were trained in a contrast detection task for ten days,with their higher-order aberrations(HOA)corrected in *** found that the training improved not only their contrast sensitivity function(CSF),but also their iconic memory and baseline information maintenance for short-term memory,and the relationship between memory and CSF improvements could be well-predicted by an observer *** results suggest that training the limiting component of a cognitive task with visual perceptual learning could improve visual *** may also provide an empirical foundation for new therapies to treat people with poor sensory memory.

关键词： Perceptual learning Iconic memory Higher-order aberrations Contrast sensitivity Short-term memory

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Homogenous coating of Li^(+)conductive Li_(5)AlO_(4)on single-crystalline nonstoichiometric Li_(1.04)Ni_(0.92)Al_(0.04)O_(2)for rechargeable lithium-ion batteries

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Journal of Energy Chemistry 2024年第8期95卷 651-659,I0014页

作者： Guoyu Ding Shizhou Wang Jinhan Li Ziyan Wu Jiayu Chen Jiayong Du Xinhui Huang Kuiming Liu yudong zhang Zhonghan Wu Yiyang Peng Qiancheng Zhao Meng Yu Fangyi Cheng Key Laboratory of Advanced Energy Materials Chemistry(Ministry of Education) Engineering Research Center of High-efficiency Energy Storage(Ministry of Education)College of ChemistryNankai UniversityTianjin 300071China State Key Laboratory of Advanced Chemical Power Sources Nankai UniversityTianjin 300071China Haihe Laboratory of Sustainable Chemical Transformations Tianjin 300192China

Cobalt-free,nickel-rich LiNi_(1-x)Al_(x)O_(2)(x≤0.1)is an attractive cathode material because of high energy density and low cost but suffers from severe structural degradation and poor rate *** this study,we propose a molten salt-assisted synthesis in combination with a Li-refeeding induced aluminum segregation strategy to prepare Li_(5)AlO_(4)-coated single-crystalline slightly Li-rich Li_(1.04)Ni_(0.92)Al_(0.04)O_(2).The symbiotic formation of Li_(5)AlO_(4)from reaction between molten lithium hydroxide and doped aluminum in the bulk ensures a high lattice matching between the Ni-rich oxide and the homogenous conductive Li_(5)AlO_(4)that permits high Li^(+)*** from mitigated undesirable side reactions and phase evolution,the Li_(5)AlO_(4)-coated single-crystalline Li_(1.04)Ni_(0.92)Al_(0.04)O_(2)delivers a high specific capacity of220.2 mA h g^(-1)at 0.1 C and considerable rate capability(182.5 mA h g^(-1)at 10 C).Besides,superior capacity retention of 90.8%is obtained at 1/3 C after 100 cycles in a 498.1 mA h pouch full ***,the particulate morphology of Li_(1.04)Ni_(0.92)Al_(0.04)O_(2)remains intact after cycling at a cutoff voltage of 4.3 V,whereas slightly Li-deficient Li_(0.98)Ni_(0.97)Al_(0.05)O_(2)features intragranular cracks and irreversible lattice *** results highlight the value of molten salt-assisted synthesis and Li-refeeding induced elemental segregation strategy to upgrade Ni-based layered oxide cathode materials for advanced Li-ion batteries.

关键词： Aluminum segregation Surface coating Nonstoichiometric oxides Molten synthesis Cathode materials

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Nano friction behaviour between magnetic materials and copper considering the inter-diffusion effect

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Friction 2024年第7期12卷 1532-1547页

作者： Zilin LI Lisha DOU Shiyu YANG Huajiang OUYANG Qichen ZHU Xiaoyang CHEN Xin JIA Shuaiwei DOU Xiaolong CUI yudong zhang Jingjiang QIU Guochen QI Bangbang NIE Pan LIU Ronghan WEI School of Mechanics and Safety Engineering Zhengzhou UniversityZhengzhou 450001China Engineering Technology Research Center of Henan Province for MEMS Manufacturing and Application Zhengzhou UniversityZhengzhou 450001China Institute of Intelligent Sensing Zhengzhou UniversityZhengzhou 450001China School of Engineering University of LiverpoolLiverpool L693GHUK School of Cyber Science and Engineering&Hanwei Institute of Internet of Things Zhengzhou UniversityZhengzhou 450001China

Copper,permalloy,cobalt,and silicon are the materials that have been widely utilised in magnetic *** the size of interest is down to the nanoscale,the inter-diffusion between certain materials becomes *** paper studies the nanoscale friction characteristics between frictional pairs with and without inter-diffusion properties through the atomic force *** distinct evolution features of nanoscale friction force when inter-diffusion is involved are discovered experimentally,which is also confirmed through theoretical ***,through the thin film deposition method,four pairs of contact materials(Cu–Ni_(81)Fe_(19),Si–Ni_(81)Fe_(19),Cu–Co,Cu–Si)are designed for friction tests,in which diffusion occurs at the interface of Cu–Ni_(81)Fe_(19)***,the effects of sliding velocity and loading force on the nano friction of each pair are *** is found that regardless of the diffusion phenomenon:(1)the adhesion force values exhibit a notable correlation to the values of the friction force;(2)the friction force in all four material pairs consistently increases with the growth of the normal loading force,although the growth rate may *** terms of the sliding velocity effect,the friction forces of immiscible materials(Si–Ni_(81)Fe_(19),Cu–Co,and Cu–Si)are found to increase with the increasing sliding ***,the friction force of Cu–Ni_(81)Fe_(19),decreases with the increasing sliding ***,a compositive friction model considering both the velocity and the normal force effect was proposed,which shows good agreement with the experimental results and explains the nano friction behaviour of both miscible and immiscible metals.

关键词： atomic force microscope friction force normal load sliding velocity

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基于末位淘汰GSGA算法的平顶光束整形研究

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中国激光 2024年第6期51卷 142-148页

作者：张昱冬赵秋烨方振张祖兴南京邮电大学电子与光学工程学院、柔性电子(未来技术)学院江苏南京210023

激光技术发展迅速,在医疗、生物、军事和材料等领域应用广泛,但激光光强的高斯型分布限制了激光的进一步应用。平顶光束整形技术应运而生并受到广泛关注。针对该问题,提出了基于末位淘汰制(LPE)、Gerchberg-Saxton(GS)算法和遗传算法(GA... 详细信息

激光技术发展迅速,在医疗、生物、军事和材料等领域应用广泛,但激光光强的高斯型分布限制了激光的进一步应用。平顶光束整形技术应运而生并受到广泛关注。针对该问题,提出了基于末位淘汰制(LPE)、Gerchberg-Saxton(GS)算法和遗传算法(GA)的LPE-GSGA算法,优化空间光调制器的相位分布函数,将高斯光束整形为平顶光束。仿真结果表明,LPE-GSGA算法输出光束指标优于GS、广义自适应加性(GAA)、加权GS(GSW)和GSGA算法。与GS算法比较,LPE-GSGA算法的误差平方和(SSE)指标降低10.1%、拟合系数η提升0.85%,对相位初值的依赖程度约降低1个数量级,输出光束顶部光强突变点更少、旁瓣减少且幅度更低。LPE-GSGA算法减少了对初值的依赖程度,使高能量利用率、高光束顶部均匀度的平顶光束整形成为可能。

关键词：激光光学光束整形平顶光束 LPE-GSGA算法

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