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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

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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Journal of Shanghai jiaotong university(science) 2024年第3期29卷 480-491页

作者：王丽张旭毅姚亚兵尉雪龙 library Northwest Normal UniversityLanzhou 730070China department of Criminal science and technology Henan Police CollegeZhengzhou 450046China school of computer and Communication Lanzhou University of TechnologyLanzhou 730050China school of computer science and Engineering Northeastern UniversityShenyang 110169China

This study mainly focused on the dynamic self-similar k_(c)-center network as a result of information distribution through social *** attraction with various preferences was characterized in the model as a result of reciprocal attraction among individuals and human ***,the model incorporated the community network structure and network evolution mechanism,and a dynamic self-similar k_(c)-center network generation model was *** with the classical scale-free network generation algorithm,the generated network embodied not only the characteristics of the small-world and scale-free,but also the characteristics of dynamic self-similar k_(c)-center *** experimental results were verified by comparing the real data with the experimental *** results showed that there are dynamic self-similar k_(c)-center networks and their internal network relationship dynamics in the micro scale,meso scale and global perspective based on information dissemination.

关键词： edge state evolutionary network self-similarity ke-center network

Brain-inspired artificial intelligence research: A review

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science china(Technological sciences) 2024年第8期67卷 2282-2296页

作者： wang GuoYin BAO HuaNan liU Qun ZHOU TianGang WU Si HUANG TieJun YU ZhaoFei LU CeWu GONG YiHong ZHANG ZhaoXiang HE Sheng Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and TelecommunicationsChongqing 400065China Key Laboratory of Cyberspace Big data Intelligent Security Chongqing University of Posts and TelecommunicationsChongqing 400065China College of computer and information science Chongqing Normal UniversityChongqing 401331China State Key Laboratory of Brain and Cognitive science Institute of BiophysicsChinese Academy of SciencesBeijing 100101China school of Psychological and Cognitive sciences Peking UniversityBeijing 100871China State Key Laboratory of Multimedia information Processing School of Computer SciencePeking UniversityBeijing 100871China department of computer science School of ElectronicsInformation and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China Faculty of Electronic and information Engineering Xi’an Jiaotong UniversityXi’an 710049China The center for Research on Intelligent Perception and Computing Institute of AutomationChinese Academy of SciencesBeijing 100190China Institute of Biophysics Chinese Academy of SciencesBeijing 100101China

Artificial intelligence(AI) systems surpass certain human intelligence abilities in a statistical sense as a whole, but are not yet the true realization of these human intelligence abilities and behaviors. There are differences, and even contradictions, between the cognition and behavior of AI systems and humans. With the goal of achieving general AI, this study contains a review of the role of cognitive science in inspiring the development of the three mainstream academic branches of AI based on the three-layer framework proposed by David marr, and the limitations of the current development of AI are explored and analyzed. The differences and inconsistencies between the cognition mechanisms of the human brain and the computation mechanisms of AI systems are analyzed. They are found to be the cause of the differences and contradictions between the cognition and behavior of AI systems and humans. Additionally, eight important research directions and their scientific issues that need to focus on braininspired AI research are proposed: highly imitated bionic information processing, a large-scale deep learning model that balances structure and function, multi-granularity joint problem solving bidirectionally driven by data and knowledge, AI models that simulate specific brain structures, a collaborative processing mechanism with the physical separation of perceptual processing and interpretive analysis, embodied intelligence that integrates the brain cognitive mechanism and AI computation mechanisms,intelligence simulation from individual intelligence to group intelligence(social intelligence), and AI-assisted brain cognitive intelligence.

关键词： artificial intelligence cognitive science brain science intelligence science large language model

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基于超声影像的下腔静脉自动识别与定位

海军军医大学学报 2024年第9期45卷 1107-1112页

作者：杨敬涵陈子叶孙景源曹文吕朝阳李硕李明秋张普徐径舟周昌杨宇祥张甫李庆利郭瑞君陈建刚华东师范大学上海市多维度信息处理重点实验室上海200241 西交利物浦大学智能工程学院苏州215123 利物浦大学计算机科学系利物浦L693BX 首都医科大学附属北京朝阳医院超声医学科北京100020 保定骨科医院普外科保定071000 湖南师范大学工程与设计学院电子工程系长沙410081

目的探究基于下腔静脉(IVC)超声影像的IVC自动识别与直径测量方法。方法提出一种基于拓扑结构与自动跟踪算法的IVC自动识别与定位方法,采用跟踪方式对数据集进行IVC识别和连续定位,以提高测量的效率和准确性。以超声医师的人工测量结果... 详细信息

目的探究基于下腔静脉(IVC)超声影像的IVC自动识别与直径测量方法。方法提出一种基于拓扑结构与自动跟踪算法的IVC自动识别与定位方法,采用跟踪方式对数据集进行IVC识别和连续定位,以提高测量的效率和准确性。以超声医师的人工测量结果作为金标准,在采集自ICU的18例患者的18组超声数据集上进行测试。结果自动化算法识别准确率为94.44%(17/18),IVC直径自动测量误差在±1.96s(s为标准差)范围内,表明自动测量方法可替代人工测量方法。结论本研究提出的基于拓扑结构与自动跟踪算法的IVC自动识别与定位算法具有较高的识别成功率及IVC直径测量准确性,可以辅助临床医师进行IVC的识别定位与直径测量。

关键词：超声图像下腔静脉血管识别与定位自动化测量

Scale‐wise interaction fusion and knowledge distillation network for aerial scene recognition

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CAAI Transactions on Intelligence technology 2023年第4期8卷 1178-1190页

作者： Hailong ning Tao Lei Mengyuan An Hao Sun Zhanxuan Hu Asoke K.Nandi school of computer science and technology Xi'an University of Posts and TelecommunicationsShaanxi Key Laboratory of Network Data Analysis and Intelligent ProcessingXi'anChina Xi'an Key Laboratory of Big data and Intelligent Computing Xi'anChina school of Electronic information and Artificial Intelligence Shaanxi University of Science and TechnologyXi'anChina school of computer Central China Normal UniversityWuhanChina department of Electronic and Electrical Engineering Brunel University LondonLondonUK Xi'an jiaotong university Xi'anChina

Aerial scene recognition(ASR)has attracted great attention due to its increasingly essential *** of the ASR methods adopt the multi‐scale architecture because both global and local features play great roles in ***,the existing multi‐scale methods neglect the effective interactions among different scales and various spatial locations when fusing global and local features,leading to a limited ability to deal with challenges of large‐scale variation and complex background in aerial scene *** addition,existing methods may suffer from poor generalisations due to millions of to‐belearnt parameters and inconsistent predictions between global and local *** tackle these problems,this study proposes a scale‐wise interaction fusion and knowledge distillation(SIF‐KD)network for learning robust and discriminative features with scaleinvariance and background‐independent *** main highlights of this study include two *** the one hand,a global‐local features collaborative learning scheme is devised for extracting scale‐invariance features so as to tackle the large‐scale variation problem in aerial scene ***,a plug‐and‐play multi‐scale context attention fusion module is proposed for collaboratively fusing the context information between global and local *** the other hand,a scale‐wise knowledge distillation scheme is proposed to produce more consistent predictions by distilling the predictive distribution between different scales during *** experimental results show the proposed SIF‐KD network achieves the best overall accuracy with 99.68%,98.74%and 95.47%on the UCM,AID and NWPU‐RESISC45 datasets,respectively,compared with state of the arts.

关键词： deep learning image analysis image classification information fusion

Detection of defect on navel orange using hyperspectral reflectance image

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Detection of defect on navel orange using hyperspectral refl...

The 2011 International Conference on Key Engineering materials and computer science(KEMCS 2011)

作者： Jing li Long xuE Muhua liU Xiao wang Chunsheng LUO Optics-Electrics Application of Biomaterials Lab Jiangxi Agricultural University school of Mechanical and Electrical Engineering departments East China Jiaotong University Key lab of nondestructive testing ministry of educationNanchang Hangkong University

A hyperspectral imaging system for detecting defect on navel orange was demonstratedThe hyperspectral imaging system, which was a line-scan imaging system, consisted of a hyperspectral camera, a halogen lighting unit, a computer and a translation stageThe imaging system operated from 400 to 1000 nmPrincipal component analysis（PCA） was performed using the hyperspectral images data（from 500 to 700nm）;2nd principal component（PC） image exhibited differential responses between normal and defect spots on the surface of navel orangeThe combined use of the PC-2 images demonstrated the detection of defect spots with minimal false positivesBased on the PC-2 weighing coefficients, the dominant wavelengths were 528,529,530,673,674 and 675 nmThis research demonstrated the potential of multispectral image for online applications for detection of defect on navel oranges.

关键词： Hyperspectral reflectance image principal component analysis defect detection navel orange

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空间和地理计算与计算社会学的融合路径

武汉大学学报（信息科学版） 2022年第1期47卷 1-18页

作者：乐阳刘瑜陈云松贺力陈晨李文雯秦昆贾涛许刚王法辉王静远谢幸徐丰力徐阳苏世亮桂志鹏游兰张明达张丰张晓祥赵博赵耀龙周钰伦黄波曹凯深圳大学建筑与城市规划学院广东深圳518060 北京大学地球与空间科学学院北京100871 南京大学社会学院江苏南京210023 西安交通大学人文社会科学学院陕西西安710049 亚利桑那州立大学地理科学与城市规划学院美国亚利桑那州坦佩AZ 8528 武汉大学遥感信息工程学院湖北武汉430079 路易斯安那州立大学地理与人类学系美国路易斯安那州巴吞鲁日LA 70802 北京航空航天大学计算机学院北京100191 微软亚洲研究院北京100080 芝加哥大学知识实验室与曼苏埃托城市创新研究所美国芝加哥IL 60637 香港理工大学土地测量及地理资讯学系中国香港武汉大学资源与环境科学学院湖北武汉430079 湖北大学计算机与信息工程学院湖北武汉430062 湖北大学资源环境学院湖北武汉430062 浙江大学地球科学学院浙江杭州310027 河海大学水文水资源学院江苏南京210098 华盛顿大学地理系美国西雅图WA 98195 华南师范大学地理科学学院广东广州510631 香港大学建筑学院中国香港香港中文大学地理与资源管理系中国香港华东师范大学地理科学学院上海200241

空间和地理数据及空间计算是大数据和人工智能(artificial intelligence,AI)研究的一个主要组成领域,也为社会科学从本体论、方法论和认识论层面提供了一个进行定量和定性研究的重要维度。但是空间如何与计算社会科学结合仍处于探索阶... 详细信息

空间和地理数据及空间计算是大数据和人工智能(artificial intelligence,AI)研究的一个主要组成领域,也为社会科学从本体论、方法论和认识论层面提供了一个进行定量和定性研究的重要维度。但是空间如何与计算社会科学结合仍处于探索阶段。通过邀请实证社会研究、地理信息科学、计算机科学等多个领域在计算社会学方向的代表学者,对大数据和AI时代新的研究和技术范式下空间和地理计算与社会计算相结合的重要议题或实现路径等阐述各自观点,希望能够对空间社会计算的发展提供研究思路。讨论认为,空间与地理研究和社会研究具有相同的底层原理,基于空间大数据的新范式为重启宏观社会学空间研究带来了重要机遇,而且空间大数据的可获得性使得中国学者能以更为主动的姿态和清晰的视野来审视和参与影响人类命运共同体的重大现实问题。但是在此过程中,还需进一步思考基础理论和框架,解决数据、计算和伦理等一系列问题,需要社会科学、地理信息科学和计算科学的共同合作和努力,以学科的进步促进社会的健康发展。

关键词：空间计算空间社会计算计算社会学社会计算社会地理计算

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针对域内流量均衡的二维路由方案

西安交通大学学报 2017年第6期51卷 129-137页

作者：赵成安王文东徐明伟陈文龙北京邮电大学软件学院北京100876 清华大学计算机系北京100084 首都师范大学信息工程学院北京100048

针对域内流量均衡问题,提出了一种二维开放式最短路径优先(OSPF)路由方案TOL。在控制层面,通过对传统链路状态通告(LSA)的扩展,实现包括目的前缀和源前缀的二维路由信息的传递,路由器根据二维路由信息进行计算,生成二维路由表项。在数... 详细信息

针对域内流量均衡问题,提出了一种二维开放式最短路径优先(OSPF)路由方案TOL。在控制层面,通过对传统链路状态通告(LSA)的扩展,实现包括目的前缀和源前缀的二维路由信息的传递,路由器根据二维路由信息进行计算,生成二维路由表项。在数据转发层面,设计了一种基于传统一维转发表实现二维数据转发的方案,这种转发方案能够有效解决引入源前缀造成的转发表存储空间增长问题,兼容传统转发,为TOL提供保障。为了验证TOL的有效性和可行性,在商用路由器上实现了原型系统,测试和实验结果表明,TOL方案能够在传统IP网络结构和协议的基础上,有效实现流量均衡,减少链路拥塞,且不会带来较大的额外负荷。

关键词：二维路由协议二维转发流量均衡