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Risk factors for early progression of diffuse low-grade glioma in adults

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Chinese Neurosurgical Journal 2023年第1期9卷 9-17页

作者： Long Wang Xuegang Li Tunan Chen Chao Zhang jiantao shi Hua Feng Fei Li Department of Neurosurgery Southwest HospitalThird Military Medical University(Army Medical University)Chongqing 400038China

Background:To explore the risk factors for early progression of diffuse low-grade glioma in adults.Methods:A retrospective analysis of pathologic and clinical data of patients diagnosed with diffuse low-grade gliomas at Southwest Hospital between January 2010 and December 2014.The progression-free survival(PFS)less than 60 months was classified as the early progress group,and the PFS greater than 60 months was the control group for comparative analysis.Results:A total of 138 patients were included in this study,including 94 cases of astrocytoma and 44 cases of oligodendroglioma.There were 63 cases with 100%resection,56 cases with 90-100%resection degree,and 19 cases with resection degree60 months.The two groups were compared for statistical analysis.In univariate analysis,there were significant differences in tumor subtype(p=0.005),range(p=0.011),volume(p=0.005),location(p=0.000),and extent of resection(p=0.000).Multifactor analysis shows tumor location(HR=4.549,95%CI:1.324-15.634,p=0.016)and tumor subtype(HR=3.347,95%CI=1.373-8.157,p=0.008),and imcomplete resection is factors influencing early progression of low-grade glioma.Conclusions:Low-grade gliomas involving deep location such as basal ganglia,inner capsule,and corpus callosum are more likely to progress early,while incomplete resection is a risk factor in early progression of astrocytoma.

关键词： Risk factors Early progression Low-grade glioma

基于深度学习的装备剩余寿命区间预测研究进展

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工程科学学报 2024年第4期46卷 723-734页

作者：陈闯李先锋史建涛南京工业大学电气工程与控制科学学院南京211816

深度学习因其强大的特征提取能力,在装备剩余寿命预测中得到了广泛应用.然而,深度学习的预测结果往往受到随机噪声、建模参数等因素影响,极大降低了点预测的可信度,进而引发甚至导致装备运行崩溃.因此,精确的剩余寿命区间预测对于理解... 详细信息

深度学习因其强大的特征提取能力,在装备剩余寿命预测中得到了广泛应用.然而,深度学习的预测结果往往受到随机噪声、建模参数等因素影响,极大降低了点预测的可信度,进而引发甚至导致装备运行崩溃.因此,精确的剩余寿命区间预测对于理解装备退化过程的随机性以及进行可靠的风险分析和维护决策至关重要.本文面向深度学习背景下装备剩余寿命预测建模中不确定性量化的现实需求,重点介绍并归纳了自举深度学习、局部不确定性、随机过程深度学习、贝叶斯深度学习以及深度学习分位数回归5种先进剩余寿命区间预测模型的发展动态、优势和缺点,进而探讨了基于深度学习的装备剩余寿命区间预测研究中面临的挑战性问题以及未来潜在的研究方向.

关键词：寿命预测区间预测不确定性深度学习维护决策

Fault tolerant multivehicle formation control framework with applications in multiquadrotor systems

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Science China(Information Sciences) 2018年第12期61卷 178-180页

作者： jiantao shi Donghua ZHOU Yuhao YANG Jun SUN Nanjing Research Institute of Electronic Technology Key Laboratory of Intellisense Technology China Electronics Technology Group Corporation College of Electrical Engineering and Automation Shandong University of Science and Technology

Compared with the traditional monolithic systems, a group of vehicles operating cooperatively in a formation can achieve greater efficiency and capability [1, 2]. However, faults may occur more frequently in multivehicle formations because a large number of controllers, sensors, and communication equipment exist [3]. Occasionally, a fault occurring in one vehicle of the formation may deteriorate the system performance or even

关键词： FTC Fault tolerant multivehicle formation control framework with applications in multiquadrotor systems Figure

Abnormal Event Correlation and Detection Based on Network Big Data Analysis

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Computers, Materials & Continua 2021年第10期69卷 695-711页

作者： Zhichao Hu Xiangzhan Yu jiantao shi Lin Ye School of Cyberspace Science Harbin Institute of TechnologyHarbin150001China Department of Computer and Information Science Temple UniversityPhiladelphia42101USA

With the continuous development of network technology,various large-scale cyber-attacks continue to emerge.These attacks pose a severe threat to the security of systems,networks,and data.Therefore,how to mine attack patterns from massive data and detect attacks are urgent problems.In this paper,an approach for attack mining and detection is proposed that performs tasks of alarm correlation,false-positive elimination,attack mining,and attack prediction.Based on the idea of CluStream,the proposed approach implements a flow clustering method and a two-step algorithm that guarantees efficient streaming and clustering.The context of an alarm in the attack chain is analyzed and the LightGBM method is used to perform falsepositive recognition with high accuracy.To accelerate the search for the filtered alarm sequence data to mine attack patterns,the PrefixSpan algorithm is also updated in the store strategy.The updated PrefixSpan increases the processing efficiency and achieves a better result than the original one in experiments.With Bayesian theory,the transition probability for the sequence pattern string is calculated and the alarm transition probability table constructed to draw the attack graph.Finally,a long-short-term memory network and embedding word-vector method are used to perform online prediction.Results of numerical experiments show that the method proposed in this paper has a strong practical value for attack detection and prediction.

关键词： Attack scene false positive alarm correlation sequence mining multi-step attack

Distributed self-triggered formation control for multi-agent systems

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Science China(Information Sciences) 2020年第10期63卷 276-278页

作者： jiantao shi Jun SUN Yuhao YANG Donghua ZHOU Nanjing Research Institute of Electronic Technology Key Laboratory of Intellisense Technology China Electronics Technology Group Corporation College of Electrical Engineering and Automation Shandong University of Science and Technology

Dear editor,Recently,the cooperative control of multi-agent systems (MASs) has stirred a significant amount of research effort [1,2].Within the realm of MASs,formation control is a very attractive topic with the aim of driving multiple agents to achieve prescribed constraints on their states/outputs.For MASs,time-scheduled control is commonly

关键词： Self-triggered formation control multi-agent system state estimation decentralized observers

Skipping Undesired High-Frequency Content to Boost DPI Engine

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Computers, Materials & Continua 2020年第5期63卷 649-661页

作者： Likun Liu jiantao shi Xiangzhan Yu Hongli Zhang Dongyang Zhan School of Computer Science and Technology Harbin Institute of TechnologyHarbin150001China Department of Computer Science and Engineering The Ohio State UniversityColumbus43202USA

Deep Packet Inspection(DPI)at the core of many monitoring appliances,such as NIDS,NIPS,plays a major role.DPI is beneficial to content providers and censorship to monitor network traffic.However,the surge of network traffic has put tremendous pressure on the performance of DPI.In fact,the sensitive content being monitored is only a minority of network traffic,that is to say,most is undesired.A close look at the network traffic,we found that it contains many undesired high frequency content(UHC)that are not monitored.As everyone knows,the key to improve DPI performance is to skip as many useless characters as possible.Nevertheless,researchers generally study the algorithm of skipping useless characters through sensitive content,ignoring the high-frequency non-sensitive content.To fill this gap,in this literature,we design a model,named Fast AC Model with Skipping(FAMS),to quickly skip UHC while scanning traffic.The model consists of a standard AC automaton,where the input traffic is scanned byte-by-byte,and an additional sub-model,which includes a mapping set and UHC matching model.The mapping set is a bridge between the state node of AC and UHC matching model,while the latter is to select a matching function from hash and fingerprint functions.Our experiments show promising results that we achieve a throughput gain of 1.3-2.6 times the original throughput and 1.1-1.3 times Barr’s double path method.

关键词： Deep packet inspection pattern matching algorithm AC

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云南省卫星定位基准站网速度场分析

城市勘测 2024年第2期 84-87,92页

作者：史珂李建涛云南省基础测绘技术中心云南昆明650034 乌鲁木齐市城市勘察测绘院新疆乌鲁木齐830017

利用云南省卫星导航定位基准站网系统(YNCORS)2016至2020年近5年99个基准站观测数据,采用GAMIT/GLOBK软件处理,解算得到了基准站的坐标时间序列和不同框架下的速度场。结果表明,云南省基准站ITRF2014框架下东方向平均运动速度31.84 mm/a... 详细信息

利用云南省卫星导航定位基准站网系统(YNCORS)2016至2020年近5年99个基准站观测数据,采用GAMIT/GLOBK软件处理,解算得到了基准站的坐标时间序列和不同框架下的速度场。结果表明,云南省基准站ITRF2014框架下东方向平均运动速度31.84 mm/a,南方向平均运动速度为13.09 mm/a,整体运动方向为东偏南方向。以欧亚板块为运动背景场框架下的东方向平均运动速度6.83 mm/a,南方向平均运动速率3.91 mm/a;滇西南运动速率较小并且有着左旋的趋势,滇西区域运动速率较大并且明显存在着右旋的趋势。

关键词：卫星定位基准站时间序列噪声框架速度场

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燃煤烟气湿法协同脱硫脱碳技术研究进展

化工进展 2024年第5期43卷 2324-2342页

作者：高凡翔刘阳张贵泉秦锋姚建涛金辉师进文西安交通大学动力工程多相流国家重点实验室陕西西安710049 西安热工研究院有限公司陕西西安710054 中海石油气电集团有限责任公司技术研发中心北京100028

燃煤烟气中SO_(2)和CO_(2)的处理逐渐向协同脱除方向发展,基于湿法脱硫和脱碳的组合技术因此获得了广泛关注。本文首先系统梳理了梯级(依次)脱硫脱碳技术的重点研究方向,认为SO_(2)的胺降解作用是该类技术面对的核心问题,但其影响机理... 详细信息

燃煤烟气中SO_(2)和CO_(2)的处理逐渐向协同脱除方向发展,基于湿法脱硫和脱碳的组合技术因此获得了广泛关注。本文首先系统梳理了梯级(依次)脱硫脱碳技术的重点研究方向,认为SO_(2)的胺降解作用是该类技术面对的核心问题,但其影响机理尚未形成统一共识。从控制排放和预防降解两个角度出发,分析了强化脱硫技术和胺降解抑制剂对缓解SO_(2)不利影响的作用。与梯级处理相比,联合(同步)脱硫脱碳技术可基于单一溶剂实现循环吸收-解吸。然后总结了钙法、氨法、胺法等联合脱硫脱碳(联脱)技术的最新进展,梳理并对比了各类吸收体系的原理和工艺设计,其中基于氨水的联脱工艺研究最为成熟。还简述了两类协同脱除技术的优缺点和发展前景。最后,建议对于梯级脱硫脱碳技术未来应重点关注SO_(2)的胺降解机理及其在开发预防降解措施中的作用,对于联脱技术应加强反应理论和集成工艺建模研究等。

关键词：煤燃烧烟气二氧化碳捕集脱硫集成

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基于泛化熵随机森林的雷达目标航迹起始方法

空间电子技术 2024年第1期21卷 7-12页

作者：刘安宁史建涛南京工业大学电气工程与控制科学学院南京211816 中国电子科技集团公司第十四研究所南京210039

文章提出了一种基于泛化熵随机森林的雷达目标航迹起始方法,通过引入一种泛化熵可调参数,解决了传统随机森林算法对差异数据集泛化能力和适应性差且难以确定全局最优解的难题。首先利用雷达多周期回波数据构建随机森林算法决策模型,其... 详细信息

文章提出了一种基于泛化熵随机森林的雷达目标航迹起始方法,通过引入一种泛化熵可调参数,解决了传统随机森林算法对差异数据集泛化能力和适应性差且难以确定全局最优解的难题。首先利用雷达多周期回波数据构建随机森林算法决策模型,其次基于设计的泛化熵处理规则对实测数据进行分类处理得到所需测试样本,最后将测试样本输入完成模型训练的随机森林进行迭代寻优和自主决策以获取雷达目标的航迹起始结果。雷达实测数据验证表明,文章所提出的方法相比于传统随机森林方法具有更为优越的目标航迹起始性能。

关键词：目标跟踪航迹起始随机森林泛化熵