This paper studies the problem of robust H∞ control of piecewise-linear chaotic systems with random data loss. The communication links between the plant and the controller are assumed to be imperfect （that is, data ...This paper studies the problem of robust H∞ control of piecewise-linear chaotic systems with random data loss. The communication links between the plant and the controller are assumed to be imperfect （that is, data loss occurs intermittently, which appears typically in a network environment）. The data loss is modelled as a random process which obeys a Bernoulli distribution. In the face of random data loss, a piecewise controller is designed to robustly stabilize the networked system in the sense of mean square and also achieve a prescribed H∞ disturbance attenuation performance based on a piecewise-quadratic Lyapunov function. The required H∞ controllers can be designed by solving a set of linear matrix inequalities （LMIs）. Chua＇s system is provided to illustrate the usefulness and applicability of the developed theoretical results.展开更多
Widely used in clinical research, the database is a new type of data management automation technology and the most efficient tool for data management. In this article, we first explain some basic concepts, such as the...Widely used in clinical research, the database is a new type of data management automation technology and the most efficient tool for data management. In this article, we first explain some basic concepts, such as the definition, classification, and establishment of databases. Afterward, the workflow for establishing databases, inputting data, verifying data, and managing databases is presented. Meanwhile, by discussing the application of databases in clinical research, we illuminate the important role of databases in clinical research practice. Lastly, we introduce the reanalysis of randomized controlled trials(RCTs) and cloud computing techniques, showing the most recent advancements of databases in clinical research.展开更多
This paper presents the principle of the fuzzy associate memory controlled leaky bucket (FAMLB) and several concepts for Usage Parameter Control (UPC) in ATM networks. The multiplex weight and random fuzzy rules adjus...This paper presents the principle of the fuzzy associate memory controlled leaky bucket (FAMLB) and several concepts for Usage Parameter Control (UPC) in ATM networks. The multiplex weight and random fuzzy rules adjustment method in the system architecture are introdued. The conclusions show that the FAMLB is a better dynamic method of UPC than the traditional ones.展开更多
为了提高电力集控系统安全隐患数据处理的效果,提出一种基于来自变换器的双向编码器表示-双向长短期记忆网络-条件随机场(Bidirectional Encoder Representations from Transformers-Bidirectional Long Short Term Memory-Conditional ...为了提高电力集控系统安全隐患数据处理的效果,提出一种基于来自变换器的双向编码器表示-双向长短期记忆网络-条件随机场(Bidirectional Encoder Representations from Transformers-Bidirectional Long Short Term Memory-Conditional Random Fields,BERT-BiLSTM-CRF)的电力集控安全隐患数据处理方法。构建电力集控隐患数据检测模型,应用改进长短时记忆网络(Long Short Term Memory,LSTM)来构建电力集控安全隐患数据修复网络,实现电力集控安全隐患数据处理。实验结果表明,采用所提方法能够更好地完成电力集控安全隐患数据检测与修复,应用效果较好。展开更多
目的利用机器学习随机森林(random forest,RF)算法,建立一种准确识别检测小偏移的实时质控方法,并以浮动异常值之和的方法(moving sum of outlier,MovSO)作为参比方法,评价新算法效能。方法收集来自航空总医院实验室信息系统导出的2016...目的利用机器学习随机森林(random forest,RF)算法,建立一种准确识别检测小偏移的实时质控方法,并以浮动异常值之和的方法(moving sum of outlier,MovSO)作为参比方法,评价新算法效能。方法收集来自航空总医院实验室信息系统导出的2016年1月至2021年8月在罗氏化学发光E601设备检测的hs-cTnT项目检测结果,按照规定的数据清洗规则筛选出54243个结果作为无偏数据,人为引入10个不同大小的偏移,生成相应的有偏数据,每种偏移下用RF与MovSO两种算法进行实验。采用分类模型标准及临床指标对算法进行评价。结果RF算法在浮动窗口大小为10时,对10个小偏移均能检出,假阳性率(FPR)为4.0%~4.7%,受影响的患者样本数中位数(MNPed)在12以下。除了在±1 ng/L偏移时准确度为85%,其余8个偏移检出准确度均在90%以上;MovSO算法的最优浮动窗口大小为200,除了在1 ng/L时偏移无法检出,对其他9个偏移均可检出,FPR在3.5%~4.6%之间,MNPed均在100以上,仅在5 ng/L偏移时识别准确度方可达89%。RF算法总体显著优于MovSO,RF可准确识别hs-cTnT的测量小偏移。结论基于机器学习RF算法建立的质控方法可以改进类似hs-cTnT等临床对检测质量要求较高的项目的测量准确度,为实验室质控方案提供了新思路。展开更多
基金Project partially supported by the Young Scientists Fund of the National Natural Science Foundation of China(Grant No.60904004)the Key Youth Science and Technology Foundation of University of Electronic Science and Technology of China (Grant No.L08010201JX0720)
文摘This paper studies the problem of robust H∞ control of piecewise-linear chaotic systems with random data loss. The communication links between the plant and the controller are assumed to be imperfect （that is, data loss occurs intermittently, which appears typically in a network environment）. The data loss is modelled as a random process which obeys a Bernoulli distribution. In the face of random data loss, a piecewise controller is designed to robustly stabilize the networked system in the sense of mean square and also achieve a prescribed H∞ disturbance attenuation performance based on a piecewise-quadratic Lyapunov function. The required H∞ controllers can be designed by solving a set of linear matrix inequalities （LMIs）. Chua＇s system is provided to illustrate the usefulness and applicability of the developed theoretical results.
基金supported by Fundamental Research Funds of State Key Laboratory of Ophthalmology (Grant No.2015QN01)Young Teacher Top-Support project of Sun Yat-sen University(Grant No.2015ykzd11)+4 种基金the Cultivation Projects for Young Teaching Staff of Sun Yat-sen University(Grant No.12ykpy61) from the Fundamental Research Funds for the Central Universitiesthe Pearl River Science and Technology New Star(Grant No.2014J2200060)Project of Guangzhou City,the Guangdong Provincial Natural Science Foundation for Distinguished Young Scholars of China(Grant No. 2014A030306030)Youth Science and Technology Innovation Talents Funds in Special Support Plan for High Level Talents in Guangdong Province(Grant No. 2014TQ01R573)Key Research Plan for National Natural Science Foundation of China in Cultivation Project (No.91546101)
文摘Widely used in clinical research, the database is a new type of data management automation technology and the most efficient tool for data management. In this article, we first explain some basic concepts, such as the definition, classification, and establishment of databases. Afterward, the workflow for establishing databases, inputting data, verifying data, and managing databases is presented. Meanwhile, by discussing the application of databases in clinical research, we illuminate the important role of databases in clinical research practice. Lastly, we introduce the reanalysis of randomized controlled trials(RCTs) and cloud computing techniques, showing the most recent advancements of databases in clinical research.
文摘This paper presents the principle of the fuzzy associate memory controlled leaky bucket (FAMLB) and several concepts for Usage Parameter Control (UPC) in ATM networks. The multiplex weight and random fuzzy rules adjustment method in the system architecture are introdued. The conclusions show that the FAMLB is a better dynamic method of UPC than the traditional ones.
文摘为了提高电力集控系统安全隐患数据处理的效果,提出一种基于来自变换器的双向编码器表示-双向长短期记忆网络-条件随机场(Bidirectional Encoder Representations from Transformers-Bidirectional Long Short Term Memory-Conditional Random Fields,BERT-BiLSTM-CRF)的电力集控安全隐患数据处理方法。构建电力集控隐患数据检测模型,应用改进长短时记忆网络(Long Short Term Memory,LSTM)来构建电力集控安全隐患数据修复网络,实现电力集控安全隐患数据处理。实验结果表明,采用所提方法能够更好地完成电力集控安全隐患数据检测与修复,应用效果较好。
文摘目的利用机器学习随机森林(random forest,RF)算法,建立一种准确识别检测小偏移的实时质控方法,并以浮动异常值之和的方法(moving sum of outlier,MovSO)作为参比方法,评价新算法效能。方法收集来自航空总医院实验室信息系统导出的2016年1月至2021年8月在罗氏化学发光E601设备检测的hs-cTnT项目检测结果,按照规定的数据清洗规则筛选出54243个结果作为无偏数据,人为引入10个不同大小的偏移,生成相应的有偏数据,每种偏移下用RF与MovSO两种算法进行实验。采用分类模型标准及临床指标对算法进行评价。结果RF算法在浮动窗口大小为10时,对10个小偏移均能检出,假阳性率(FPR)为4.0%~4.7%,受影响的患者样本数中位数(MNPed)在12以下。除了在±1 ng/L偏移时准确度为85%,其余8个偏移检出准确度均在90%以上;MovSO算法的最优浮动窗口大小为200,除了在1 ng/L时偏移无法检出,对其他9个偏移均可检出,FPR在3.5%~4.6%之间,MNPed均在100以上,仅在5 ng/L偏移时识别准确度方可达89%。RF算法总体显著优于MovSO,RF可准确识别hs-cTnT的测量小偏移。结论基于机器学习RF算法建立的质控方法可以改进类似hs-cTnT等临床对检测质量要求较高的项目的测量准确度,为实验室质控方案提供了新思路。
