A specific uniform map is constructed as a homeomorphism mapping chaotic time series into [0,1] to obtain sequences of standard uniform distribution. With the uniform map, a chaotic orbit and a sequence orbit obtained...A specific uniform map is constructed as a homeomorphism mapping chaotic time series into [0,1] to obtain sequences of standard uniform distribution. With the uniform map, a chaotic orbit and a sequence orbit obtained are topologically equivalent to each other so the map can preserve the most dynamic properties of chaotic systems such as permutation entropy. Based on the uniform map, a universal algorithm to generate pseudo random numbers is proposed and the pseudo random series is tested to follow the standard 0-1 random distribution both theoretically and experimentally. The algorithm is not complex, which does not impose high requirement on computer hard ware and thus computation speed is fast. The method not only extends the parameter spaces but also avoids the drawback of small function space caused by constraints on chaotic maps used to generate pseudo random numbers. The algorithm can be applied to any chaotic system and can produce pseudo random sequence of high quality, thus can be a good universal pseudo random number generator.展开更多
This paper models the complex simultaneous localization and mapping（SLAM） problem through a very flexible Markov random field and then solves it by using the iterated conditional modes algorithm. Markovian models al...This paper models the complex simultaneous localization and mapping（SLAM） problem through a very flexible Markov random field and then solves it by using the iterated conditional modes algorithm. Markovian models allow to incorporate： any motion model; any observation model regardless of the type of sensor being chosen; prior information of the map through a map model; maps of diverse natures; sensor fusion weighted according to the accuracy. On the other hand, the iterated conditional modes algorithm is a probabilistic optimizer widely used for image processing which has not yet been used to solve the SLAM problem. This iterative solver has theoretical convergence regardless of the Markov random field chosen to model. Its initialization can be performed on-line and improved by parallel iterations whenever deemed appropriate. It can be used as a post-processing methodology if it is initialized with estimates obtained from another SLAM solver. The applied methodology can be easily implemented in other versions of the SLAM problem, such as the multi-robot version or the SLAM with dynamic environment. Simulations and real experiments show the flexibility and the excellent results of this proposal.展开更多
In this research the fault parameters causing the September 27, 2010 Kazeron Earthquake with a magnitude of MW = 5.8 (BHRC) were determined using the random finite fault method. The parameters were recorded by 27 acce...In this research the fault parameters causing the September 27, 2010 Kazeron Earthquake with a magnitude of MW = 5.8 (BHRC) were determined using the random finite fault method. The parameters were recorded by 27 accelerometer stations. Simulation of strong ground motion is very useful for areas about which little information and data are available. Considering the distribution of earthquake records and the existing relationships, for the fault plane causing the September 27, 2010 Kazeron Earthquake the length of the fault along the strike direction and the width of the fault along the dip direction were determined to be 10 km and 7 km, respectively. Moreover, 10 elements were assumed along the length and 7 were assumed along the width of the plane. Research results indicated that the epicenter of the earthquake had a geographic coordination of 29.88N - 51.77E, which complied with the results reported by the Institute of Geophysics Tehran University (IGTU). In addition, the strike and dip measured for the fault causing the Kazeron Earthquake were 27 and 50 degrees, respectively. Therefore, the causing fault was almost parallel to and coincident with the fault. There are magnetic discontinuities on the analytical signal map with a north-south strike followed by a northwest-southeast strike. The discontinuities are consistent with the trend of Kazeron fault but are several kilometers away from it. Therefore, they show the fault depth at a distance of 12 km from the fault surface.展开更多
This work was to generate landslide susceptibility maps for the Three Gorges Reservoir(TGR) area, China by using different machine learning models. Three advanced machine learning methods, namely, gradient boosting de...This work was to generate landslide susceptibility maps for the Three Gorges Reservoir(TGR) area, China by using different machine learning models. Three advanced machine learning methods, namely, gradient boosting decision tree(GBDT), random forest(RF) and information value(InV) models, were used, and the performances were assessed and compared. In total, 202 landslides were mapped by using a series of field surveys, aerial photographs, and reviews of historical and bibliographical data. Nine causative factors were then considered in landslide susceptibility map generation by using the GBDT, RF and InV models. All of the maps of the causative factors were resampled to a resolution of 28.5 m. Of the 486289 pixels in the area,28526 pixels were landslide pixels, and 457763 pixels were non-landslide pixels. Finally, landslide susceptibility maps were generated by using the three machine learning models, and their performances were assessed through receiver operating characteristic(ROC) curves, the sensitivity, specificity,overall accuracy(OA), and kappa coefficient(KAPPA). The results showed that the GBDT, RF and In V models in overall produced reasonable accurate landslide susceptibility maps. Among these three methods, the GBDT method outperforms the other two machine learning methods, which can provide strong technical support for producing landslide susceptibility maps in TGR.展开更多
Kernel-based slow feature analysis(SFA)methods have been successfully applied in the industrial process fault detection field.However,kernel-based SFA methods have high computational complexity as dealing with nonline...Kernel-based slow feature analysis(SFA)methods have been successfully applied in the industrial process fault detection field.However,kernel-based SFA methods have high computational complexity as dealing with nonlinearity,leading to delays in detecting time-varying data features.Additionally,the uncertain kernel function and kernel parameters limit the ability of the extracted features to express process characteristics,resulting in poor fault detection performance.To alleviate the above problems,a novel randomized auto-regressive dynamic slow feature analysis(RRDSFA)method is proposed to simultaneously monitor the operating point deviations and process dynamic faults,enabling real-time monitoring of data features in industrial processes.Firstly,the proposed Random Fourier mappingbased method achieves more effective nonlinear transformation,contrasting with the current kernelbased RDSFA algorithm that may lead to significant computational complexity.Secondly,a randomized RDSFA model is developed to extract nonlinear dynamic slow features.Furthermore,a Bayesian inference-based overall fault monitoring model including all RRDSFA sub-models is developed to overcome the randomness of random Fourier mapping.Finally,the superiority and effectiveness of the proposed monitoring method are demonstrated through a numerical case and a simulation of continuous stirred tank reactor.展开更多
采用证据图梳理近六年中医药治疗糖尿病肾脏病(DKD)的相关临床研究,系统评估该领域的证据现状,以期为现存问题及后续研究方向提供科学依据和决策参考。系统检索中国知网(CNKI)、万方(Wanfang)、维普(VIP)、中国生物医学文献服务系统(Sin...采用证据图梳理近六年中医药治疗糖尿病肾脏病(DKD)的相关临床研究,系统评估该领域的证据现状,以期为现存问题及后续研究方向提供科学依据和决策参考。系统检索中国知网(CNKI)、万方(Wanfang)、维普(VIP)、中国生物医学文献服务系统(SinoMed)、PubMed、EMbase、Web of Science、Cochrane Library等数据库中医药治疗DKD的文献,经过多次筛选,共纳入310篇文献,其中随机对照试验(RCTs)289篇,系统评价/Meta分析13篇,指南/专家共识8篇。整体发文量呈上升趋势,其中干预方式以口服为主,疗程多在2~3个月,样本量集中在50~100例。涉及30种中药汤剂、39种中成药,以参芪地黄汤、益肾化湿颗粒发文量最多。纳入中医证型以气阴两虚、脾肾两虚为主。结局指标纳入较多的有临床有效率、血糖相关、肾功能等指标,缺少对长期结局检测等问题。方法学质量评估方面,多数RCT在分配隐藏、盲法实施等存在严重缺陷,整体质量不高。系统评价/Meta分析的质量评估等级也均为“极低级”。指南/专家共识整体质量尚可,在严谨性和临床应用等方面待进一步完善。后续应重视以上问题,提升临床研究质量,发挥中医药优势,为中医药防治DKD的临床决策提供更可靠的循证依据。展开更多
[目的]运用证据图谱系统分析中医药治疗注意缺陷多动障碍(ADHD)的临床研究现状。[方法]计算机检索PubMed、Web of Science、Cochrane Library、EMbase、PsycINFO、中国知网、万方数据知识服务平台、维普网、SinoMed数据库。检索从建库至...[目的]运用证据图谱系统分析中医药治疗注意缺陷多动障碍(ADHD)的临床研究现状。[方法]计算机检索PubMed、Web of Science、Cochrane Library、EMbase、PsycINFO、中国知网、万方数据知识服务平台、维普网、SinoMed数据库。检索从建库至2025年1月中医药治疗ADHD的相关研究。采用Cochrane手册的风险偏倚评估工具、AMSTAR 2、AGREEⅡ分别对纳入的随机对照试验(RCTs)、系统评价/Meta分析和专家共识/指南进行质量评价。采用文字结合折线图、气泡图、条形堆积图、三线表等形式呈现临床研究证据分布特征。[结果]1)研究热度在2005年达到峰值后呈波动下降趋势,近年来有所回升,趋于历史高峰水平。样本量集中在51~100例。RCTs和nonRCTs的干预周期分别以8~12周和4~8周为主。2)热点干预措施集中于单纯中药口服(59.2%),高频干预措施为中药复方(50.0%)。高频运用经方为甘麦大枣汤(46.2%)、高频运用时方为六味地黄丸和归脾汤(均为15.2%)。核心证型以肝肾阴虚证(19.8%)、心脾两虚证(19.0%)为主。3)结局指标偏重临床疗效与中医证候评估,而在主要及次要指标区分、功能损害及共病情况、量表使用及报告规范、经济学评价指标等方面关注不足。4)方法学质量亟待提升,RCTs因随机化方法、分配隐藏及盲法实施等方面存在问题而偏倚风险较高,Meta分析/系统评价主要在研究前方案注册、文献排除清单及原因、纳入研究资金来源及利益冲突等方面存在问题,专家共识/指南在制定严谨性、应用性、编辑独立性等方面存在不足。[结论]中医药治疗ADHD具有一定优势,但现有研究质量普遍不高。未来临床研究需着眼于顶层设计,规范并优化研究内容,提高研究质量,充分挖掘中医药治疗优势,为中医药治疗ADHD提供更高级别的循证证据。展开更多
基金supported by the National Natural Science Foundation of China (Grant No.10871168)
文摘A specific uniform map is constructed as a homeomorphism mapping chaotic time series into [0,1] to obtain sequences of standard uniform distribution. With the uniform map, a chaotic orbit and a sequence orbit obtained are topologically equivalent to each other so the map can preserve the most dynamic properties of chaotic systems such as permutation entropy. Based on the uniform map, a universal algorithm to generate pseudo random numbers is proposed and the pseudo random series is tested to follow the standard 0-1 random distribution both theoretically and experimentally. The algorithm is not complex, which does not impose high requirement on computer hard ware and thus computation speed is fast. The method not only extends the parameter spaces but also avoids the drawback of small function space caused by constraints on chaotic maps used to generate pseudo random numbers. The algorithm can be applied to any chaotic system and can produce pseudo random sequence of high quality, thus can be a good universal pseudo random number generator.
基金supported by the National Council for Scientific and Technological Research(CONICET)the National University of San Juan(UNSJ)
文摘This paper models the complex simultaneous localization and mapping（SLAM） problem through a very flexible Markov random field and then solves it by using the iterated conditional modes algorithm. Markovian models allow to incorporate： any motion model; any observation model regardless of the type of sensor being chosen; prior information of the map through a map model; maps of diverse natures; sensor fusion weighted according to the accuracy. On the other hand, the iterated conditional modes algorithm is a probabilistic optimizer widely used for image processing which has not yet been used to solve the SLAM problem. This iterative solver has theoretical convergence regardless of the Markov random field chosen to model. Its initialization can be performed on-line and improved by parallel iterations whenever deemed appropriate. It can be used as a post-processing methodology if it is initialized with estimates obtained from another SLAM solver. The applied methodology can be easily implemented in other versions of the SLAM problem, such as the multi-robot version or the SLAM with dynamic environment. Simulations and real experiments show the flexibility and the excellent results of this proposal.
文摘In this research the fault parameters causing the September 27, 2010 Kazeron Earthquake with a magnitude of MW = 5.8 (BHRC) were determined using the random finite fault method. The parameters were recorded by 27 accelerometer stations. Simulation of strong ground motion is very useful for areas about which little information and data are available. Considering the distribution of earthquake records and the existing relationships, for the fault plane causing the September 27, 2010 Kazeron Earthquake the length of the fault along the strike direction and the width of the fault along the dip direction were determined to be 10 km and 7 km, respectively. Moreover, 10 elements were assumed along the length and 7 were assumed along the width of the plane. Research results indicated that the epicenter of the earthquake had a geographic coordination of 29.88N - 51.77E, which complied with the results reported by the Institute of Geophysics Tehran University (IGTU). In addition, the strike and dip measured for the fault causing the Kazeron Earthquake were 27 and 50 degrees, respectively. Therefore, the causing fault was almost parallel to and coincident with the fault. There are magnetic discontinuities on the analytical signal map with a north-south strike followed by a northwest-southeast strike. The discontinuities are consistent with the trend of Kazeron fault but are several kilometers away from it. Therefore, they show the fault depth at a distance of 12 km from the fault surface.
基金This work was supported in part by the National Natural Science Foundation of China(61601418,41602362,61871259)in part by the Opening Foundation of Hunan Engineering and Research Center of Natural Resource Investigation and Monitoring(2020-5)+1 种基金in part by the Qilian Mountain National Park Research Center(Qinghai)(grant number:GKQ2019-01)in part by the Geomatics Technology and Application Key Laboratory of Qinghai Province,Grant No.QHDX-2019-01.
文摘This work was to generate landslide susceptibility maps for the Three Gorges Reservoir(TGR) area, China by using different machine learning models. Three advanced machine learning methods, namely, gradient boosting decision tree(GBDT), random forest(RF) and information value(InV) models, were used, and the performances were assessed and compared. In total, 202 landslides were mapped by using a series of field surveys, aerial photographs, and reviews of historical and bibliographical data. Nine causative factors were then considered in landslide susceptibility map generation by using the GBDT, RF and InV models. All of the maps of the causative factors were resampled to a resolution of 28.5 m. Of the 486289 pixels in the area,28526 pixels were landslide pixels, and 457763 pixels were non-landslide pixels. Finally, landslide susceptibility maps were generated by using the three machine learning models, and their performances were assessed through receiver operating characteristic(ROC) curves, the sensitivity, specificity,overall accuracy(OA), and kappa coefficient(KAPPA). The results showed that the GBDT, RF and In V models in overall produced reasonable accurate landslide susceptibility maps. Among these three methods, the GBDT method outperforms the other two machine learning methods, which can provide strong technical support for producing landslide susceptibility maps in TGR.
基金supported by the Program of National Natural Science Foundation of China(U23A20329,62163036)Youth Academic and Technical Leaders Reserve Talent Training project(202105AC160094)Industrial Innovation Talent Special Project of Xingdian Talent Support Program(XDYC-CYCX-2022-0010).
文摘Kernel-based slow feature analysis(SFA)methods have been successfully applied in the industrial process fault detection field.However,kernel-based SFA methods have high computational complexity as dealing with nonlinearity,leading to delays in detecting time-varying data features.Additionally,the uncertain kernel function and kernel parameters limit the ability of the extracted features to express process characteristics,resulting in poor fault detection performance.To alleviate the above problems,a novel randomized auto-regressive dynamic slow feature analysis(RRDSFA)method is proposed to simultaneously monitor the operating point deviations and process dynamic faults,enabling real-time monitoring of data features in industrial processes.Firstly,the proposed Random Fourier mappingbased method achieves more effective nonlinear transformation,contrasting with the current kernelbased RDSFA algorithm that may lead to significant computational complexity.Secondly,a randomized RDSFA model is developed to extract nonlinear dynamic slow features.Furthermore,a Bayesian inference-based overall fault monitoring model including all RRDSFA sub-models is developed to overcome the randomness of random Fourier mapping.Finally,the superiority and effectiveness of the proposed monitoring method are demonstrated through a numerical case and a simulation of continuous stirred tank reactor.
文摘采用证据图梳理近六年中医药治疗糖尿病肾脏病(DKD)的相关临床研究,系统评估该领域的证据现状,以期为现存问题及后续研究方向提供科学依据和决策参考。系统检索中国知网(CNKI)、万方(Wanfang)、维普(VIP)、中国生物医学文献服务系统(SinoMed)、PubMed、EMbase、Web of Science、Cochrane Library等数据库中医药治疗DKD的文献,经过多次筛选,共纳入310篇文献,其中随机对照试验(RCTs)289篇,系统评价/Meta分析13篇,指南/专家共识8篇。整体发文量呈上升趋势,其中干预方式以口服为主,疗程多在2~3个月,样本量集中在50~100例。涉及30种中药汤剂、39种中成药,以参芪地黄汤、益肾化湿颗粒发文量最多。纳入中医证型以气阴两虚、脾肾两虚为主。结局指标纳入较多的有临床有效率、血糖相关、肾功能等指标,缺少对长期结局检测等问题。方法学质量评估方面,多数RCT在分配隐藏、盲法实施等存在严重缺陷,整体质量不高。系统评价/Meta分析的质量评估等级也均为“极低级”。指南/专家共识整体质量尚可,在严谨性和临床应用等方面待进一步完善。后续应重视以上问题,提升临床研究质量,发挥中医药优势,为中医药防治DKD的临床决策提供更可靠的循证依据。
文摘[目的]运用证据图谱系统分析中医药治疗注意缺陷多动障碍(ADHD)的临床研究现状。[方法]计算机检索PubMed、Web of Science、Cochrane Library、EMbase、PsycINFO、中国知网、万方数据知识服务平台、维普网、SinoMed数据库。检索从建库至2025年1月中医药治疗ADHD的相关研究。采用Cochrane手册的风险偏倚评估工具、AMSTAR 2、AGREEⅡ分别对纳入的随机对照试验(RCTs)、系统评价/Meta分析和专家共识/指南进行质量评价。采用文字结合折线图、气泡图、条形堆积图、三线表等形式呈现临床研究证据分布特征。[结果]1)研究热度在2005年达到峰值后呈波动下降趋势,近年来有所回升,趋于历史高峰水平。样本量集中在51~100例。RCTs和nonRCTs的干预周期分别以8~12周和4~8周为主。2)热点干预措施集中于单纯中药口服(59.2%),高频干预措施为中药复方(50.0%)。高频运用经方为甘麦大枣汤(46.2%)、高频运用时方为六味地黄丸和归脾汤(均为15.2%)。核心证型以肝肾阴虚证(19.8%)、心脾两虚证(19.0%)为主。3)结局指标偏重临床疗效与中医证候评估,而在主要及次要指标区分、功能损害及共病情况、量表使用及报告规范、经济学评价指标等方面关注不足。4)方法学质量亟待提升,RCTs因随机化方法、分配隐藏及盲法实施等方面存在问题而偏倚风险较高,Meta分析/系统评价主要在研究前方案注册、文献排除清单及原因、纳入研究资金来源及利益冲突等方面存在问题,专家共识/指南在制定严谨性、应用性、编辑独立性等方面存在不足。[结论]中医药治疗ADHD具有一定优势,但现有研究质量普遍不高。未来临床研究需着眼于顶层设计,规范并优化研究内容,提高研究质量,充分挖掘中医药治疗优势,为中医药治疗ADHD提供更高级别的循证证据。
