“慧眼”硬X射线调制望远镜(简称慧眼卫星,英文名为Insight Hard X-ray Modulation Telescope,简称Insight-HXMT或HXMT),于2017年6月15日发射升空,标志着我国自主研发的首个天文台级X射线望远镜的诞生.慧眼卫星凭借其大面积、宽波段、...“慧眼”硬X射线调制望远镜(简称慧眼卫星,英文名为Insight Hard X-ray Modulation Telescope,简称Insight-HXMT或HXMT),于2017年6月15日发射升空,标志着我国自主研发的首个天文台级X射线望远镜的诞生.慧眼卫星凭借其大面积、宽波段、高时间分辨率和高能量分辨率的综合优势,为黑洞与中子星系统的硬X射线快速变化和宽波段能谱研究领域开辟了新的研究窗口.超出设计寿命的慧眼卫星已稳定运行超过8yr,目前状态良好,且有望进一步延长其在轨服务时间.截至2024年10月,慧眼卫星已7次向全球科学界公开征集观测提案,共收到334份有效的观测提案,并据此制定了2368个观测计划.此外,慧眼卫星已向公众发布数据13批次,累计数据量达到40 TB,数据公开比率高达94%.慧眼卫星还向用户提供了不同版本的数据分析软件和标定数据库,在轨标定精度在2%左右,满足科学分析的要求.来自全球17家及国内36家研究机构的学者使用慧眼数据开展了科学研究,发表了约300多篇高质量学术论文,累计引用次数约7300次.展开更多
With the arrival of the ＂housing stock＂ in first - tier cities, the second - handhousing^market will become the dominant property market. This ardcle aim to the first - tiercities of second - hand housing prices and...With the arrival of the ＂housing stock＂ in first - tier cities, the second - handhousing^market will become the dominant property market. This ardcle aim to the first - tiercities of second - hand housing prices and new home price index for the empirical analysis, thedata related to the cointegration analysis found that the result of the first -tier cities real estatemarket in China, the new home price index is the significant factors influencing the second -hand house price indexi For Beijing, Shanghai second - hand housing and new home price in-dex time series johans test, found that there exists cointegration relationship between two varia-bles,the new city real estate market prices out of a line on the secondary market have clearguide. Therefore, the real estate market regulation aiming at the first -tier cities and the＂housing stock＂ should take the second - hand housing market as the main direction, startingwith the sale price and influencing factors of new houses. At the same time, in different cities,we should adhere to the city＇ s policies, reflect the policy differentiation, promote the reformof the real estate supply side, and promote the return of housing properties.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
为了提高太阳电池阵多变量预测的精度,解决阳电池阵遥测参数存在周期波动与增长性互相耦合的问题,提出一种基于STL-Prophet-Informer模型的太阳电池阵多变量预测算法.该算法首先应用局部加权周期趋势分解算法(seasonal and trend decomp...为了提高太阳电池阵多变量预测的精度,解决阳电池阵遥测参数存在周期波动与增长性互相耦合的问题,提出一种基于STL-Prophet-Informer模型的太阳电池阵多变量预测算法.该算法首先应用局部加权周期趋势分解算法(seasonal and trend decomposition procedure based on loess,STL)对太阳电池阵的多个参数分解为趋势分量、周期分量和残差分量,然后采用对趋势性数据预测效果较好的Prophet预测趋势分量,Informer模型预测周期分量和残差分量,最后将各分量预测结果相加后得到总的太阳电池阵参数预测值.以某卫星太阳电池阵实际遥测数据做算例分析,提出算法的各项误差评价指标和单一的Informer模型、LSTM模型等相比有明显减小,将该组合预测模型用于太阳电池阵多变量参数预测中,可以提高参数预测精度,提升卫星自主运行性能.展开更多
The dissociation between data management and data ownership makes it difficult to protect data security and privacy in cloud storage systems.Traditional encryption technologies are not suitable for data protection in ...The dissociation between data management and data ownership makes it difficult to protect data security and privacy in cloud storage systems.Traditional encryption technologies are not suitable for data protection in cloud storage systems.A novel multi-authority proxy re-encryption mechanism based on ciphertext-policy attribute-based encryption（MPRE-CPABE） is proposed for cloud storage systems.MPRE-CPABE requires data owner to split each file into two blocks,one big block and one small block.The small block is used to encrypt the big one as the private key,and then the encrypted big block will be uploaded to the cloud storage system.Even if the uploaded big block of file is stolen,illegal users cannot get the complete information of the file easily.Ciphertext-policy attribute-based encryption（CPABE）is always criticized for its heavy overload and insecure issues when distributing keys or revoking user＇s access right.MPRE-CPABE applies CPABE to the multi-authority cloud storage system,and solves the above issues.The weighted access structure（WAS） is proposed to support a variety of fine-grained threshold access control policy in multi-authority environments,and reduce the computational cost of key distribution.Meanwhile,MPRE-CPABE uses proxy re-encryption to reduce the computational cost of access revocation.Experiments are implemented on platforms of Ubuntu and CloudSim.Experimental results show that MPRE-CPABE can greatly reduce the computational cost of the generation of key components and the revocation of user＇s access right.MPRE-CPABE is also proved secure under the security model of decisional bilinear Diffie-Hellman（DBDH）.展开更多
Outlier detection is an important task in data mining. In fact, it is difficult to find the clustering centers in some sophisticated multidimensional datasets and to measure the deviation degree of each potential outl...Outlier detection is an important task in data mining. In fact, it is difficult to find the clustering centers in some sophisticated multidimensional datasets and to measure the deviation degree of each potential outlier. In this work, an effective outlier detection method based on multi-dimensional clustering and local density(ODBMCLD) is proposed. ODBMCLD firstly identifies the center objects by the local density peak of data objects, and clusters the whole dataset based on the center objects. Then, outlier objects belonging to different clusters will be marked as candidates of abnormal data. Finally, the top N points among these abnormal candidates are chosen as final anomaly objects with high outlier factors. The feasibility and effectiveness of the method are verified by experiments.展开更多
The Soil Conservation Monitorins Information System (SCMIS) presented in this paper is oriented to soil erosion control, resources exploitation, utilization, planning and management for a small watershed (about 10 sq....The Soil Conservation Monitorins Information System (SCMIS) presented in this paper is oriented to soil erosion control, resources exploitation, utilization, planning and management for a small watershed (about 10 sq. km.) on the Loess Plateau. It sums up Remote sensing (RS), Geographical Information System (GIS) and Expert System (ES) and consists of a integrated system. As a basic level information system of Loess Plateau, its perfection and psreading will bring about a great advance in resources exploitation and management of Loess Plateau.展开更多
To get the high compression ratio as well as the high-quality reconstructed image, an effective image compression scheme named irregular segmentation region coding based on spiking cortical model（ISRCS） is presented...To get the high compression ratio as well as the high-quality reconstructed image, an effective image compression scheme named irregular segmentation region coding based on spiking cortical model（ISRCS） is presented. This scheme is region-based and mainly focuses on two issues. Firstly, an appropriate segmentation algorithm is developed to partition an image into some irregular regions and tidy contours, where the crucial regions corresponding to objects are retained and a lot of tiny parts are eliminated. The irregular regions and contours are coded using different methods respectively in the next step. The other issue is the coding method of contours where an efficient and novel chain code is employed. This scheme tries to find a compromise between the quality of reconstructed images and the compression ratio. Some principles and experiments are conducted and the results show its higher performance compared with other compression technologies, in terms of higher quality of reconstructed images, higher compression ratio and less time consuming.展开更多
基金Supported by National Natural Science Foundation of China （61304079, 61125306, 61034002）, the Open Research Project from SKLMCCS （20120106）, the Fundamental Research Funds for the Central Universities （FRF-TP-13-018A）, and the China Postdoctoral Science. Foundation （201_3M_ 5305_27）_ _ _
文摘为有致动器浸透和未知动力学的分离时间的系统的一个班的一个新奇最佳的追踪控制方法在这份报纸被建议。计划基于反复的适应动态编程(自动数据处理) 算法。以便实现控制计划，一个 data-based 标识符首先为未知系统动力学被构造。由介绍 M 网络，稳定的控制的明确的公式被完成。以便消除致动器浸透的效果， nonquadratic 表演功能被介绍，然后一个反复的自动数据处理算法被建立与集中分析完成最佳的追踪控制解决方案。为实现最佳的控制方法，神经网络被用来建立 data-based 标识符，计算性能索引功能，近似最佳的控制政策并且分别地解决稳定的控制。模拟例子被提供验证介绍最佳的追踪的控制计划的有效性。
文摘With the arrival of the ＂housing stock＂ in first - tier cities, the second - handhousing^market will become the dominant property market. This ardcle aim to the first - tiercities of second - hand housing prices and new home price index for the empirical analysis, thedata related to the cointegration analysis found that the result of the first -tier cities real estatemarket in China, the new home price index is the significant factors influencing the second -hand house price indexi For Beijing, Shanghai second - hand housing and new home price in-dex time series johans test, found that there exists cointegration relationship between two varia-bles,the new city real estate market prices out of a line on the secondary market have clearguide. Therefore, the real estate market regulation aiming at the first -tier cities and the＂housing stock＂ should take the second - hand housing market as the main direction, startingwith the sale price and influencing factors of new houses. At the same time, in different cities,we should adhere to the city＇ s policies, reflect the policy differentiation, promote the reformof the real estate supply side, and promote the return of housing properties.
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.
文摘为了提高太阳电池阵多变量预测的精度,解决阳电池阵遥测参数存在周期波动与增长性互相耦合的问题,提出一种基于STL-Prophet-Informer模型的太阳电池阵多变量预测算法.该算法首先应用局部加权周期趋势分解算法(seasonal and trend decomposition procedure based on loess,STL)对太阳电池阵的多个参数分解为趋势分量、周期分量和残差分量,然后采用对趋势性数据预测效果较好的Prophet预测趋势分量,Informer模型预测周期分量和残差分量,最后将各分量预测结果相加后得到总的太阳电池阵参数预测值.以某卫星太阳电池阵实际遥测数据做算例分析,提出算法的各项误差评价指标和单一的Informer模型、LSTM模型等相比有明显减小,将该组合预测模型用于太阳电池阵多变量参数预测中,可以提高参数预测精度,提升卫星自主运行性能.
基金supported by the National Natural Science Foundation of China(6120200461472192)+1 种基金the Special Fund for Fast Sharing of Science Paper in Net Era by CSTD(2013116)the Natural Science Fund of Higher Education of Jiangsu Province(14KJB520014)
文摘The dissociation between data management and data ownership makes it difficult to protect data security and privacy in cloud storage systems.Traditional encryption technologies are not suitable for data protection in cloud storage systems.A novel multi-authority proxy re-encryption mechanism based on ciphertext-policy attribute-based encryption（MPRE-CPABE） is proposed for cloud storage systems.MPRE-CPABE requires data owner to split each file into two blocks,one big block and one small block.The small block is used to encrypt the big one as the private key,and then the encrypted big block will be uploaded to the cloud storage system.Even if the uploaded big block of file is stolen,illegal users cannot get the complete information of the file easily.Ciphertext-policy attribute-based encryption（CPABE）is always criticized for its heavy overload and insecure issues when distributing keys or revoking user＇s access right.MPRE-CPABE applies CPABE to the multi-authority cloud storage system,and solves the above issues.The weighted access structure（WAS） is proposed to support a variety of fine-grained threshold access control policy in multi-authority environments,and reduce the computational cost of key distribution.Meanwhile,MPRE-CPABE uses proxy re-encryption to reduce the computational cost of access revocation.Experiments are implemented on platforms of Ubuntu and CloudSim.Experimental results show that MPRE-CPABE can greatly reduce the computational cost of the generation of key components and the revocation of user＇s access right.MPRE-CPABE is also proved secure under the security model of decisional bilinear Diffie-Hellman（DBDH）.
基金Project(61362021)supported by the National Natural Science Foundation of ChinaProject(2016GXNSFAA380149)supported by Natural Science Foundation of Guangxi Province,China+1 种基金Projects(2016YJCXB02,2017YJCX34)supported by Innovation Project of GUET Graduate Education,ChinaProject(2011KF11)supported by the Key Laboratory of Cognitive Radio and Information Processing,Ministry of Education,China
文摘Outlier detection is an important task in data mining. In fact, it is difficult to find the clustering centers in some sophisticated multidimensional datasets and to measure the deviation degree of each potential outlier. In this work, an effective outlier detection method based on multi-dimensional clustering and local density(ODBMCLD) is proposed. ODBMCLD firstly identifies the center objects by the local density peak of data objects, and clusters the whole dataset based on the center objects. Then, outlier objects belonging to different clusters will be marked as candidates of abnormal data. Finally, the top N points among these abnormal candidates are chosen as final anomaly objects with high outlier factors. The feasibility and effectiveness of the method are verified by experiments.
文摘The Soil Conservation Monitorins Information System (SCMIS) presented in this paper is oriented to soil erosion control, resources exploitation, utilization, planning and management for a small watershed (about 10 sq. km.) on the Loess Plateau. It sums up Remote sensing (RS), Geographical Information System (GIS) and Expert System (ES) and consists of a integrated system. As a basic level information system of Loess Plateau, its perfection and psreading will bring about a great advance in resources exploitation and management of Loess Plateau.
基金supported by the National Science Foundation of China(60872109)the Program for New Century Excellent Talents in University(NCET-06-0900)
文摘To get the high compression ratio as well as the high-quality reconstructed image, an effective image compression scheme named irregular segmentation region coding based on spiking cortical model（ISRCS） is presented. This scheme is region-based and mainly focuses on two issues. Firstly, an appropriate segmentation algorithm is developed to partition an image into some irregular regions and tidy contours, where the crucial regions corresponding to objects are retained and a lot of tiny parts are eliminated. The irregular regions and contours are coded using different methods respectively in the next step. The other issue is the coding method of contours where an efficient and novel chain code is employed. This scheme tries to find a compromise between the quality of reconstructed images and the compression ratio. Some principles and experiments are conducted and the results show its higher performance compared with other compression technologies, in terms of higher quality of reconstructed images, higher compression ratio and less time consuming.
