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A Survey of Knowledge Graph Construction Using Machine Learning

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 225-257页

作者： Zhigang Zhao xiong luo Maojian Chen Ling Ma School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China Shunde Innovation School University of Science and Technology BeijingFoshan528399China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083China

Knowledge graph(KG)serves as a specialized semantic network that encapsulates intricate relationships among real-world entities within a structured *** framework facilitates a transformation in information retrieval,transitioning it from mere string matching to far more sophisticated entity *** this transformative process,the advancement of artificial intelligence and intelligent information services is ***,the role ofmachine learningmethod in the construction of KG is important,and these techniques have already achieved initial *** article embarks on a comprehensive journey through the last strides in the field of KG via machine *** a profound amalgamation of cutting-edge research in machine learning,this article undertakes a systematical exploration of KG construction methods in three distinct phases:entity learning,ontology learning,and knowledge ***,a meticulous dissection of machine learningdriven algorithms is conducted,spotlighting their contributions to critical facets such as entity extraction,relation extraction,entity linking,and link ***,this article also provides an analysis of the unresolved challenges and emerging trajectories that beckon within the expansive application of machine learning-fueled,large-scale KG construction.

关键词： Knowledge graph(KG) semantic network relation extraction entity linking knowledge reasoning

Damaged apple detection with a hybrid YOLOv3 algorithm

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Information Processing in Agriculture 2024年第2期11卷 163-171页

作者： Meng Zhang Huazhao Liang Zhongju Wang Long Wang Chao Huang xiong luo Schoolof Computer and Communication Engineering University of Science and Technoogy BejingBejing 1083China lShunde Innovation SchoolUniversity of Science and Technology BeijingFoshan 528399China

This paper proposes an improved You Only Look Once(YOLOv3)algorithm for automatically detecting damaged apples to promote the automation of the fruit processing *** the proposed method,a clustering method based on Rao-1 algorithm is introduced to optimize anchor box *** clustering method uses the intersection over the union to form the objective function and the most representative anchor boxes are generated for normal and damaged apple *** verify the feasibility and effectiveness of the proposed method,real apple images collected from the Internet are *** with the generic YOLOv3 and Fast Region-based Convolutional Neural Network(Fast R-CNN)algorithms,the proposed method yields the highest mean average precision value for the test ***,it is practical to apply the proposed method for intelligent apple detection and classification tasks.

关键词： Rao algorithm Apple detection Clustering Smart agriculture

Magnetic phase transition and continuous spin switching in a high-entropy orthoferrite single crystal

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Frontiers of physics 2024年第2期19卷 157-167页

作者： Wanting Yang Shuang Zhu xiong luo Xiaoxuan Ma Chenfei Shi Huan Song Zhiqiang Sun Yefei Guo Yuriy Dedkov Baojuan Kang Jin-Ke Bao Shixun Cao Department of Physics Shanghai UniversityShanghai 200444China Materials Genome Institute and International Center for Quantum and Molecular Structures Shanghai UniversityShanghai 200444China School of Physics Southeast UniversityNanjing 211189China Shanghai Key Laboratory of High Temperature Superconductors Shanghai UniversityShanghai 200444China

Rare-earth orthoferrite REFeO_(3)(where RE is a rare-earth ion)is gaining *** created a high-entropy orthoferrite(Tm_(0.2)Nd_(0.2)Dy_(0.2)Y_(0.2)Yb_(0.2))FeO_(3)(HEOR)by doping five RE ions in equimolar ratios and grew the single crystal by optical floating zone *** strongly tends to form a single-phase structure stabilized by high configurational *** the low-temperature region(11.6‒14.4 K),the spin reorientation transition(SRT)ofΓ_(2)(F_(x),C_(y),G_(z))‒Γ_(24)‒Γ_(4)(G_(x),A_(y),F_(z))*** weak ferromagnetic(FM)moment,which comes from the Fe sublattices distortion,rotates from the a-to *** two-step dynamic processes(Γ_(2)‒Γ_(24)‒Γ_(4))are identified by AC susceptibility *** in HEOR can be tuned in the range of 50‒60000 Oe,which is an order of magnitude larger than that of orthoferrites in the peer system,making it a candidate for high-field spin *** spin-switching(SSW)and continuous spin-switching(CSSW)effects occur under low magnetic fields due to the strong interactions between RE‒Fe *** CSSW effect is tunable between 20‒50 Oe,and hence,HEOR potentially can be applied to spin modulation ***,because of the strong anisotropy of magnetic entropy change()and refrigeration capacity(RC)based on its high configurational entropy,HEOR is expected to provide a novel approach for refrigeration by altering the orientations of the crystallographic axes(anisotropic configurational entropy).

关键词： high-entropy oxide rare-earth orthoferrite spin reorientation transition spin switching magnetocaloric effect

稀土对林麝采食量、血液指标和粪便微生物的影响

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野生动物学报 2024年第1期45卷 67-74页

作者：罗雄吴杰陈凤蒋桂梅成都蜀星饲料有限公司成都611600 四川省食品药品学校峨眉山614201

为探究稀土作为饲料添加剂对林麝(Moschus berezovskii)采食量、血液指标和粪便微生物的影响,选取12只年龄相同、体况良好的育成期林麝,随机分为2组,每组6只(3♀,3),对照组饲喂常规日粮,试验组饲喂常规日粮和稀土添加剂(150 mg/kg精补... 详细信息

为探究稀土作为饲料添加剂对林麝(Moschus berezovskii)采食量、血液指标和粪便微生物的影响,选取12只年龄相同、体况良好的育成期林麝,随机分为2组,每组6只(3♀,3),对照组饲喂常规日粮,试验组饲喂常规日粮和稀土添加剂(150 mg/kg精补料),预饲期15 d,正试期25 d。结果表明:(1)添加稀土对林麝基础饲粮的采食量没有显著影响(p>0.05),但试验组树叶采食量和总采食量显著高于对照组(p0.05)。(3)添加稀土后林麝血清尿素(UREA)和总胆固醇(TCH)含量较对照组低(p0.05)。(4)试验组和对照组粪便微生物的Chao1指数、Simpson指数、Shannon指数和基于ANOSIM分析的Beta多样性没有显著差异(p>0.05)。由此可见,本试验条件下添加稀土提高了林麝采食量,降低了血清UREA和TCH含量,对林麝体质量和粪便微生物多样性没有显著影响。

关键词：林麝稀土采食量血液指标粪便微生物

经腹腔入路和经腹膜后入路在腹腔镜下保留肾单位肾肿瘤切除术中的应用效果

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中国内镜杂志 2024年第4期30卷 83-88页

作者：罗雄龙家才罗兵李炜四川省巴中市中心医院泌尿外科四川巴中636000

目的比较经腹腔入路和经腹膜后入路在腹腔镜下保留肾单位手术(LNSS)中的应用效果。方法选取2018年1月-2022年12月该院行LNSS的患者100例,按照手术方法不同,分为:经腹腔入路腹腔镜下保留肾单位手术(TLNSS)组(53例)和经腹膜后入路腹腔镜... 详细信息

目的比较经腹腔入路和经腹膜后入路在腹腔镜下保留肾单位手术(LNSS)中的应用效果。方法选取2018年1月-2022年12月该院行LNSS的患者100例,按照手术方法不同,分为:经腹腔入路腹腔镜下保留肾单位手术(TLNSS)组(53例)和经腹膜后入路腹腔镜下保留肾单位手术(RLNSS)组(47例),比较两组患者围手术期相关指标、治疗前后肾功能指标、临床疗效和并发症发生情况。结果TLNSS组手术时间、热缺血时间、肠道功能恢复时间和肾动脉阻断时间明显较RLNSS组长,差异均有统计学意义(P0.05);两组患者术后血清胆碱酯酶(ChE)较术前升高,血尿素氮(BUN)和血肌酐(Scr)较术前降低,TLNSS组ChE明显低于RLNSS组,TLNSS组BUN和Scr明显高于RLNSS组,差异均有统计学意义(P<0.05);TLNSS组疾病控制率(DCR)和总体有效率(ORR)明显低于RLNSS组,差异均有统计学意义(P<0.05);TLNSS组并发症总发生率明显高于RLNSS组,差异有统计学意义(P<0.05)。结论RLNSS可明显缩短手术时间和热缺血时间,促进患者肠道功能和肾功能的恢复,提高临床疗效,降低并发症发生风险。值得临床应用。

关键词：肾肿瘤切除术经腹腔入路经腹膜后入路肾功能疗效

On fine-grained visual explanation in convolutional neural networks

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Digital Communications and Networks 2023年第5期9卷 1141-1147页

作者： Xia Lei Yongkai Fan xiong-Lin luo Department of Automation China University of Petroleum BejingBeijing102249China State Key Laboratory of Media Convergence and Communication Communication University of ChinaBeijing100024China

Existing explanation methods for Convolutional Neural Networks(CNNs)lack the pixel-level visualization explanations to generate the reliable fine-grained decision *** there are inconsistencies between the explanation and the actual behavior of the model to be interpreted,we propose a Fine-Grained Visual Explanation for CNN,namely F-GVE,which produces a fine-grained explanation with higher consistency to the decision of the original *** exact backward class-specific gradients with respect to the input image is obtained to highlight the object-related pixels the model used to make *** addition,for better visualization and less noise,F-GVE selects an appropriate threshold to filter the gradient during the calculation and the explanation map is obtained by element-wise multiplying the gradient and the input image to show fine-grained classification decision *** results demonstrate that F-GVE has good visual performances and highlights the importance of fine-grained decision ***,the faithfulness of the explanation in this paper is high and it is effective and practical on troubleshooting and debugging detection.

关键词： Convolutional neural network Explanation Class-specific gradient Fine-grained

热处理对高压气瓶封头显微组织和力学性能的影响

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金属热处理 2024年第2期49卷 220-223页

作者：魏巍罗雄范俊明陈刘斌吴明霞成都市特种设备检验检测研究院四川成都610299 成都格瑞特高压容器有限责任公司四川成都610400 四川大学机械工程学院四川成都610065

对34CrMo4无缝钢管翻板旋压成形的高压气瓶进行了淬火+亚温淬火+回火的热处理,然后采用金相观察以及拉伸试验等方法对比研究了热处理前后气瓶封头的显微组织和力学性能。研究发现,热处理可使材料的晶粒明显细化,并使气瓶封头部位较为粗... 详细信息

对34CrMo4无缝钢管翻板旋压成形的高压气瓶进行了淬火+亚温淬火+回火的热处理,然后采用金相观察以及拉伸试验等方法对比研究了热处理前后气瓶封头的显微组织和力学性能。研究发现,热处理可使材料的晶粒明显细化,并使气瓶封头部位较为粗大的铁素体+索氏体组织转变为细小的回火索氏体组织;热处理后气瓶封头位置的抗拉强度和屈服强度均有所提高,屈强比降低,且气瓶的塑性有所提升。结果表明,淬火+亚温淬火+回火的热处理工艺有利于优化34CrMo4钢高压气瓶的显微组织并提升其力学性能。

关键词： 34CrMo4钢高压气瓶热处理显微组织力学性能

完全机器人手术系统联合术中胃镜行保留幽门的中段胃切除在胃体癌的应用

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现代消化及介入诊疗 2024年第4期29卷 415-421页

作者：骆雄姚宏亮中南大学湘雅二医院胃肠外科 410011

目的探讨完全机器人手术系统联合术中胃镜行保留幽门的中段胃切除治疗中段胃体癌的可行性及安全性。方法采用描述性病例系列研究方法,回顾性收集并分析2023年5月至2023年9月期间中南大学湘雅二医院胃肠外科完成的7例完全机器人手术系统... 详细信息

目的探讨完全机器人手术系统联合术中胃镜行保留幽门的中段胃切除治疗中段胃体癌的可行性及安全性。方法采用描述性病例系列研究方法,回顾性收集并分析2023年5月至2023年9月期间中南大学湘雅二医院胃肠外科完成的7例完全机器人手术系统联合术中胃镜行双镜联合的保留幽门的中段胃体癌根治术的临床资料。术中胃镜钛夹定位病变位置,采用5孔法放置Trocar,完全机器人下行中段胃切除,行胃底胃体端端手工缝合。观察手术情况、围手术期情况和术后病理以及随访情况。计量资料采用平均数(范围)或M(范围)来表示,计数资料用频数表示。结果7例患者手术均成功实施完全机器人手术系统联合术中胃镜行双镜联合的保留幽门的中段胃体癌根治术,无中转开腹或术中输血。全组患者全组患者平均手术时间182(165~195)min,平均术中出血量45(40~60)ml,平均手术切口长度3.3(3.0~4.0)cm,平均术后排气时间为2.4(2.0~3.0)d,平均术后首次排便时间3.0(2.0~4.0)d,平均术后进流食时间为3.9(3.0~5.0)d,平均术后住院天数为7.6(7.0~9.0)d,平均术后拔出腹腔引流管时间为4.9(4.0~6.0)d,平均术后拔除尿管时间1.3(1.0~2.0)d,平均术后首次下床活动时间2.3(2.0~3.0)d,住院期间无严重手术相关并发症发生。电话随访患者术后6个月,全组术后切口愈合良好,无术后胃穿孔、术后吻合口出血、吻合口瘘、吻合口狭窄、无胃瘫或无病人出现严重营养不良,仅1例患者出现胃排空障碍导致的反酸、嗳气、腹胀轻微症状,其他患者均无严重餐后不适或胆汁反流性胃炎症状,主观整体营养评分均在A或B级,无病人发生肿瘤复发,转移或死亡,所有患者术后饮食、排便规律,生活质量满意。结论完全机器人手术系统联合术中胃镜行保留幽门的中段胃切除在胃体癌中具有独特优势,具有良好的安全性和可行性,且术后短期预后良好,有利于改善病人术后生活质量。

关键词：全机器人下保留幽门的胃切除早期胃癌

Transferable Features from 1D-Convolutional Network for Industrial Malware Classification

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Computer Modeling in Engineering & Sciences 2022年第2期130卷 1003-1016页

作者： LiweiWang Jiankun Sun xiong luo Xi Yang School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083China Shunde Graduate School University of Science and Technology BeijingFoshan528399China Beijing Intelligent Logistics System Collaborative Innovation Center Beijing101149China

With the development of information technology,malware threats to the industrial system have become an emergent issue,since various industrial infrastructures have been deeply integrated into our modern works and *** identify and classify new malware variants,different types of deep learning models have been widely explored ***,sufficient data is usually required to achieve a well-trained deep learning classifier with satisfactory generalization ***,in current practical applications,an ample supply of data is absent in most specific industrial malware detection *** learning as an effective approach can be used to alleviate the influence of the small sample size *** addition,it can also reuse the knowledge from pretrained models,which is beneficial to the real-time requirement in industrial malware *** this paper,we investigate the transferable features learned by a 1D-convolutional network and evaluate our proposed methods on 6 transfer learning *** experiment results show that 1D-convolutional architecture is effective to learn transferable features for malware classification,and indicate that transferring the first 2 layers of our proposed 1D-convolutional network is the most efficient way to reuse the learned features.

关键词： Transfer learning malware classification sequence data modeling convolutional network