One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific object...One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific objectives,measurement targets,and measurement requirements for the proposed Gas and Ion Analyzer(GIA).The GIA is designed for in-situ mass spectrometry of neutral gases and low-energy ions,such as hydrogen,carbon,and oxygen,in the vicinity of 311P.Ion sampling techniques are essential for the GIA's Time-of-Flight(TOF)mass analysis capabilities.In this paper,we present an enhanced ion sampling technique through the development of an ion attraction model and an ion source model.The ion attraction model demonstrates that adjusting attraction grid voltage can enhance the detection efficiency of low-energy ions and mitigate the repulsive force of ions during sampling,which is influenced by the satellite's surface positive charging.The ion source model simulates the processes of gas ionization and ion multiplication.Simulation results indicate that the GIA can achieve a lower pressure limit below 10-13Pa and possess a dynamic range exceeding 10~9.These performances ensure the generation of ions with stable and consistent current,which is crucial for high-resolution and broad dynamic range mass spectrometer analysis.Preliminary testing experiments have verified GIA's capability to detect gas compositions such as H2O and N2.In-situ measurements near 311P using GIA are expected to significantly contribute to our understanding of asteroid activity mechanisms,the evolution of the atmospheric and ionized environments of main-belt comets,the interactions with solar wind,and the origin of Earth's water.展开更多
The initial motivation of the lifting technique is to solve the H∞control problems. However, the conventional weighted H∞design does not meet the conditions required by lifting, so the result often leads to a misjud...The initial motivation of the lifting technique is to solve the H∞control problems. However, the conventional weighted H∞design does not meet the conditions required by lifting, so the result often leads to a misjudgement of the design. Two conditions required by using the lifting technique are presented based on the basic formulae of the lifting. It is pointed out that only the H∞disturbance attenuation problem with no weighting functions can meet these conditions, hence, the application of the lifting technique is quite limited.展开更多
For imbalanced datasets, the focus of classification is to identify samples of the minority class. The performance of current data mining algorithms is not good enough for processing imbalanced datasets. The synthetic...For imbalanced datasets, the focus of classification is to identify samples of the minority class. The performance of current data mining algorithms is not good enough for processing imbalanced datasets. The synthetic minority over-sampling technique(SMOTE) is specifically designed for learning from imbalanced datasets, generating synthetic minority class examples by interpolating between minority class examples nearby. However, the SMOTE encounters the overgeneralization problem. The densitybased spatial clustering of applications with noise(DBSCAN) is not rigorous when dealing with the samples near the borderline.We optimize the DBSCAN algorithm for this problem to make clustering more reasonable. This paper integrates the optimized DBSCAN and SMOTE, and proposes a density-based synthetic minority over-sampling technique(DSMOTE). First, the optimized DBSCAN is used to divide the samples of the minority class into three groups, including core samples, borderline samples and noise samples, and then the noise samples of minority class is removed to synthesize more effective samples. In order to make full use of the information of core samples and borderline samples,different strategies are used to over-sample core samples and borderline samples. Experiments show that DSMOTE can achieve better results compared with SMOTE and Borderline-SMOTE in terms of precision, recall and F-value.展开更多
近年来,随着智慧医疗的日益普及,在线医疗平台已逐步发展为满足大众基本医疗需求的重要渠道。为患者推荐合适的医生是在线问诊中的一个重要过程,优化推荐能力不仅可以提高患者的满意度,还能够推动在线医疗平台的发展。与传统推荐系统不...近年来,随着智慧医疗的日益普及,在线医疗平台已逐步发展为满足大众基本医疗需求的重要渠道。为患者推荐合适的医生是在线问诊中的一个重要过程,优化推荐能力不仅可以提高患者的满意度,还能够推动在线医疗平台的发展。与传统推荐系统不同,医生推荐领域受到隐私保护限制,无法查看患者曾经的诊疗历史,因此模型训练时仅能利用每位患者最近一次的就诊记录,面临严峻的数据稀疏问题。同样,模型预测时也仅能根据患者当前的疾病描述文本进行推荐,而由于患者对疾病描述方式的差异性,模型对不同患者的推荐能力也存在差异,这会使部分患者的需求无法得到满足,进而影响模型整体的推荐能力。基于此,本文提出了一种基于数据增强的医生推荐方法(sequential three-way decision with data augmentation,STWD-NA),通过引入不匹配的医患交互信息扩充训练数据,并利用序贯三支决策的思想训练模型。具体来说,该方法由两部分组成:一方面引入了不匹配交互信息的方法,以缓解训练冷启动问题;另一方面,提出了一种基于序贯三支决策的训练算法,以动态调整模型训练时的关注度。最后,通过好大夫平台上的真实数据集验证了本文所提STWD-NA方法的有效性。展开更多
基金Supported by the National Natural Science Foundation of China(42474239,41204128)China National Space Administration(Pre-research project on Civil Aerospace Technologies No.D010301)Strategic Priority Research Program of the Chinese Academy of Sciences(XDA17010303)。
文摘One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific objectives,measurement targets,and measurement requirements for the proposed Gas and Ion Analyzer(GIA).The GIA is designed for in-situ mass spectrometry of neutral gases and low-energy ions,such as hydrogen,carbon,and oxygen,in the vicinity of 311P.Ion sampling techniques are essential for the GIA's Time-of-Flight(TOF)mass analysis capabilities.In this paper,we present an enhanced ion sampling technique through the development of an ion attraction model and an ion source model.The ion attraction model demonstrates that adjusting attraction grid voltage can enhance the detection efficiency of low-energy ions and mitigate the repulsive force of ions during sampling,which is influenced by the satellite's surface positive charging.The ion source model simulates the processes of gas ionization and ion multiplication.Simulation results indicate that the GIA can achieve a lower pressure limit below 10-13Pa and possess a dynamic range exceeding 10~9.These performances ensure the generation of ions with stable and consistent current,which is crucial for high-resolution and broad dynamic range mass spectrometer analysis.Preliminary testing experiments have verified GIA's capability to detect gas compositions such as H2O and N2.In-situ measurements near 311P using GIA are expected to significantly contribute to our understanding of asteroid activity mechanisms,the evolution of the atmospheric and ionized environments of main-belt comets,the interactions with solar wind,and the origin of Earth's water.
基金Supported by the Harbin Engineering University Fund for Basic Projects (heuft06041)
文摘The initial motivation of the lifting technique is to solve the H∞control problems. However, the conventional weighted H∞design does not meet the conditions required by lifting, so the result often leads to a misjudgement of the design. Two conditions required by using the lifting technique are presented based on the basic formulae of the lifting. It is pointed out that only the H∞disturbance attenuation problem with no weighting functions can meet these conditions, hence, the application of the lifting technique is quite limited.
基金supported by the National Key Research and Development Program of China(2018YFB1003700)the Scientific and Technological Support Project(Society)of Jiangsu Province(BE2016776)+2 种基金the“333” project of Jiangsu Province(BRA2017228 BRA2017401)the Talent Project in Six Fields of Jiangsu Province(2015-JNHB-012)
文摘For imbalanced datasets, the focus of classification is to identify samples of the minority class. The performance of current data mining algorithms is not good enough for processing imbalanced datasets. The synthetic minority over-sampling technique(SMOTE) is specifically designed for learning from imbalanced datasets, generating synthetic minority class examples by interpolating between minority class examples nearby. However, the SMOTE encounters the overgeneralization problem. The densitybased spatial clustering of applications with noise(DBSCAN) is not rigorous when dealing with the samples near the borderline.We optimize the DBSCAN algorithm for this problem to make clustering more reasonable. This paper integrates the optimized DBSCAN and SMOTE, and proposes a density-based synthetic minority over-sampling technique(DSMOTE). First, the optimized DBSCAN is used to divide the samples of the minority class into three groups, including core samples, borderline samples and noise samples, and then the noise samples of minority class is removed to synthesize more effective samples. In order to make full use of the information of core samples and borderline samples,different strategies are used to over-sample core samples and borderline samples. Experiments show that DSMOTE can achieve better results compared with SMOTE and Borderline-SMOTE in terms of precision, recall and F-value.
文摘近年来,随着智慧医疗的日益普及,在线医疗平台已逐步发展为满足大众基本医疗需求的重要渠道。为患者推荐合适的医生是在线问诊中的一个重要过程,优化推荐能力不仅可以提高患者的满意度,还能够推动在线医疗平台的发展。与传统推荐系统不同,医生推荐领域受到隐私保护限制,无法查看患者曾经的诊疗历史,因此模型训练时仅能利用每位患者最近一次的就诊记录,面临严峻的数据稀疏问题。同样,模型预测时也仅能根据患者当前的疾病描述文本进行推荐,而由于患者对疾病描述方式的差异性,模型对不同患者的推荐能力也存在差异,这会使部分患者的需求无法得到满足,进而影响模型整体的推荐能力。基于此,本文提出了一种基于数据增强的医生推荐方法(sequential three-way decision with data augmentation,STWD-NA),通过引入不匹配的医患交互信息扩充训练数据,并利用序贯三支决策的思想训练模型。具体来说,该方法由两部分组成:一方面引入了不匹配交互信息的方法,以缓解训练冷启动问题;另一方面,提出了一种基于序贯三支决策的训练算法,以动态调整模型训练时的关注度。最后,通过好大夫平台上的真实数据集验证了本文所提STWD-NA方法的有效性。
