In infrastructure as a service(IaaS)cloud mode equipment simulated training,to keep the resource utilization ratio in a rational high level,improve the training effect and reduce the system running cost,the problem of...In infrastructure as a service(IaaS)cloud mode equipment simulated training,to keep the resource utilization ratio in a rational high level,improve the training effect and reduce the system running cost,the problem of training virtual machine(TVM)placement needs to be resolved first.We make analysis to the problem and give the mathematical formulation to the problem.Then,we figure out the principle and target of the TVM placement.Based on above analysis,we propose a constrained immune memory and immunodominance clone(CIMIC)TVM placement optimization algorithm.By reverse optimization of the initial antibody population,the searching range is reduced.The common antibody population and the immunodominance antibody population evolve simultaneously,which realizes the simultaneous progressing of global searching and local searching of solutions.Further,local optimal is avoided by this means.Memory antibody makes ful use of the unfeasible solutions and the diversity of antibody population is maintained.The constraint information of the problem is utilized to improve the optimization effect.Experiment results show that the CIMIC algorithm improves the overall optimization effect of TVM placement,reduces the server number and improves the resource utilization and system stability.展开更多
Based on normalized six-hourly black body temperature （TBB） data of three geostationary meteorological satellites,the leading modes of the mei-yu cloud system between 1998 and 2008 were extracted by the Empirical Or...Based on normalized six-hourly black body temperature （TBB） data of three geostationary meteorological satellites,the leading modes of the mei-yu cloud system between 1998 and 2008 were extracted by the Empirical Orthogonal Function （EOF） method,and the transition processes from the first typical leading mode to other leading modes were discussed and compared.The analysis shows that,when the southern mode （EOF1） transforms to the northeastern mode （EOF3）,in the mid-troposphere,a low trough develops and moves southeastward over central and eastern China.The circulation pattern is characterized by two highs and one low in the lower troposphere.A belt of low pressure is sandwiched between the weak high over central and western China and the strong western North Pacific subtropical high （WNPSH）.Cold air moves southward along the northerly flow behind the low,and meets the warm and moist air between the WNPSH and the forepart of the low trough,which leads to continuous convection.At the same time,the central extent of the WNPSH increases while its ridge extends westward.In addition,transitions from the southern mode to the dual centers mode and the tropical-low-influenced mode were found to be atypical,and so no common points could be concluded.Furthermore,the choice of threshold value can affect the number of samples discussed.展开更多
For the multi-mode radar working in the modern electronicbattlefield, different working states of one single radar areprone to being classified as multiple emitters when adoptingtraditional classification methods to p...For the multi-mode radar working in the modern electronicbattlefield, different working states of one single radar areprone to being classified as multiple emitters when adoptingtraditional classification methods to process intercepted signals,which has a negative effect on signal classification. A classificationmethod based on spatial data mining is presented to address theabove challenge. Inspired by the idea of spatial data mining, theclassification method applies nuclear field to depicting the distributioninformation of pulse samples in feature space, and digs out thehidden cluster information by analyzing distribution characteristics.In addition, a membership-degree criterion to quantify the correlationamong all classes is established, which ensures classificationaccuracy of signal samples. Numerical experiments show that thepresented method can effectively prevent different working statesof multi-mode emitter from being classified as several emitters,and achieve higher classification accuracy.展开更多
This study concerns a Ka-band solid-state transmitter cloud radar, made in China, which can operate in three different work modes, with different pulse widths, and coherent and incoherent integration numbers, to meet ...This study concerns a Ka-band solid-state transmitter cloud radar, made in China, which can operate in three different work modes, with different pulse widths, and coherent and incoherent integration numbers, to meet the requirements for cloud remote sensing over the Tibetan Plateau. Specifically, the design of the three operational modes of the radar（i.e., boundary mode M1, cirrus mode M2, and precipitation mode M3） is introduced. Also, a cloud radar data merging algorithm for the three modes is proposed. Using one month＇s continuous measurements during summertime at Naqu on the Tibetan Plateau,we analyzed the consistency between the cloud radar measurements of the three modes. The number of occurrences of radar detections of hydrometeors and the percentage contributions of the different modes＇ data to the merged data were estimated.The performance of the merging algorithm was evaluated. The results indicated that the minimum detectable reflectivity for each mode was consistent with theoretical results. Merged data provided measurements with a minimum reflectivity of -35 dBZ at the height of 5 km, and obtained information above the height of 0.2 km. Measurements of radial velocity by the three operational modes agreed very well, and systematic errors in measurements of reflectivity were less than 2 dB. However,large discrepancies existed in the measurements of the linear depolarization ratio taken from the different operational modes.The percentage of radar detections of hydrometeors in mid- and high-level clouds increased by 60% through application of pulse compression techniques. In conclusion, the merged data are appropriate for cloud and precipitation studies over the Tibetan Plateau.展开更多
Human resource management service faced the challenges of promoting efficiency, costs saving, quick responding and so on. In order to face these challenges, this paper puts forward a “6 + 1” structure of human resou...Human resource management service faced the challenges of promoting efficiency, costs saving, quick responding and so on. In order to face these challenges, this paper puts forward a “6 + 1” structure of human resource management service combined with some characteristics of cloud computing, elaborates the service mode of the cloud service platform based on this structure, the characteristics and challenges of the platform, and hopes to provide a new service perspective to human resource management.展开更多
In this paper, we adopt cloud computing in a specific scientific computing field for its virtualization, distribution and dynamic extendibility as follows: We obtain high-energy parabolic self-similar pulses by numeri...In this paper, we adopt cloud computing in a specific scientific computing field for its virtualization, distribution and dynamic extendibility as follows: We obtain high-energy parabolic self-similar pulses by numerical simulation using our non-distributed passively mode-locked Er-doped fiber laser model. For researching characteristics of these wave-breaking-free self-similar pulses, chirp of them must be extracted. We propose several time-frequency analysis methods adopted in chirp extraction of ultra-short optical pulses for the first time and discuss the advantages and disadvantages of them in this particular application.展开更多
In order to overcome the disadvantages of low accuracy rate, high complexity and poor robustness to image noise in many traditional algorithms of cloud image detection, this paper proposed a novel algorithm on the bas...In order to overcome the disadvantages of low accuracy rate, high complexity and poor robustness to image noise in many traditional algorithms of cloud image detection, this paper proposed a novel algorithm on the basis of Markov Random Field (MRF) modeling. This paper first defined algorithm model and derived the core factors affecting the performance of the algorithm, and then, the solving of this algorithm was obtained by the use of Belief Propagation (BP) algorithm and Iterated Conditional Modes (ICM) algorithm. Finally, experiments indicate that this algorithm for the cloud image detection has higher average accuracy rate which is about 98.76% and the average result can also reach 96.92% for different type of image noise.展开更多
基金Equipment Pre-research Fund of China under Grant No.9140A04030214JB34058.
文摘In infrastructure as a service(IaaS)cloud mode equipment simulated training,to keep the resource utilization ratio in a rational high level,improve the training effect and reduce the system running cost,the problem of training virtual machine(TVM)placement needs to be resolved first.We make analysis to the problem and give the mathematical formulation to the problem.Then,we figure out the principle and target of the TVM placement.Based on above analysis,we propose a constrained immune memory and immunodominance clone(CIMIC)TVM placement optimization algorithm.By reverse optimization of the initial antibody population,the searching range is reduced.The common antibody population and the immunodominance antibody population evolve simultaneously,which realizes the simultaneous progressing of global searching and local searching of solutions.Further,local optimal is avoided by this means.Memory antibody makes ful use of the unfeasible solutions and the diversity of antibody population is maintained.The constraint information of the problem is utilized to improve the optimization effect.Experiment results show that the CIMIC algorithm improves the overall optimization effect of TVM placement,reduces the server number and improves the resource utilization and system stability.
基金supported by the National Natural Science Foundation of China (Grant No. 40975023)the Special Promotion Program for Meteorology (Grant No. GYHY201406011 and No. GYHY201106044)the National High Technology Research and Development Project of China (Grant No. 2012AA120903)
文摘Based on normalized six-hourly black body temperature （TBB） data of three geostationary meteorological satellites,the leading modes of the mei-yu cloud system between 1998 and 2008 were extracted by the Empirical Orthogonal Function （EOF） method,and the transition processes from the first typical leading mode to other leading modes were discussed and compared.The analysis shows that,when the southern mode （EOF1） transforms to the northeastern mode （EOF3）,in the mid-troposphere,a low trough develops and moves southeastward over central and eastern China.The circulation pattern is characterized by two highs and one low in the lower troposphere.A belt of low pressure is sandwiched between the weak high over central and western China and the strong western North Pacific subtropical high （WNPSH）.Cold air moves southward along the northerly flow behind the low,and meets the warm and moist air between the WNPSH and the forepart of the low trough,which leads to continuous convection.At the same time,the central extent of the WNPSH increases while its ridge extends westward.In addition,transitions from the southern mode to the dual centers mode and the tropical-low-influenced mode were found to be atypical,and so no common points could be concluded.Furthermore,the choice of threshold value can affect the number of samples discussed.
基金supported by the National Natural Science Foundation of China(61371172)the International S&T Cooperation Program of China(2015DFR10220)+1 种基金the Ocean Engineering Project of National Key Laboratory Foundation(1213)the Fundamental Research Funds for the Central Universities(HEUCF1608)
文摘For the multi-mode radar working in the modern electronicbattlefield, different working states of one single radar areprone to being classified as multiple emitters when adoptingtraditional classification methods to process intercepted signals,which has a negative effect on signal classification. A classificationmethod based on spatial data mining is presented to address theabove challenge. Inspired by the idea of spatial data mining, theclassification method applies nuclear field to depicting the distributioninformation of pulse samples in feature space, and digs out thehidden cluster information by analyzing distribution characteristics.In addition, a membership-degree criterion to quantify the correlationamong all classes is established, which ensures classificationaccuracy of signal samples. Numerical experiments show that thepresented method can effectively prevent different working statesof multi-mode emitter from being classified as several emitters,and achieve higher classification accuracy.
基金funded by the National Sciences Foundation of China(Grant No.91337103)the China Meteorological Administration Special Public Welfare Research Fund(Grant No.GYHY201406001)
文摘This study concerns a Ka-band solid-state transmitter cloud radar, made in China, which can operate in three different work modes, with different pulse widths, and coherent and incoherent integration numbers, to meet the requirements for cloud remote sensing over the Tibetan Plateau. Specifically, the design of the three operational modes of the radar（i.e., boundary mode M1, cirrus mode M2, and precipitation mode M3） is introduced. Also, a cloud radar data merging algorithm for the three modes is proposed. Using one month＇s continuous measurements during summertime at Naqu on the Tibetan Plateau,we analyzed the consistency between the cloud radar measurements of the three modes. The number of occurrences of radar detections of hydrometeors and the percentage contributions of the different modes＇ data to the merged data were estimated.The performance of the merging algorithm was evaluated. The results indicated that the minimum detectable reflectivity for each mode was consistent with theoretical results. Merged data provided measurements with a minimum reflectivity of -35 dBZ at the height of 5 km, and obtained information above the height of 0.2 km. Measurements of radial velocity by the three operational modes agreed very well, and systematic errors in measurements of reflectivity were less than 2 dB. However,large discrepancies existed in the measurements of the linear depolarization ratio taken from the different operational modes.The percentage of radar detections of hydrometeors in mid- and high-level clouds increased by 60% through application of pulse compression techniques. In conclusion, the merged data are appropriate for cloud and precipitation studies over the Tibetan Plateau.
文摘Human resource management service faced the challenges of promoting efficiency, costs saving, quick responding and so on. In order to face these challenges, this paper puts forward a “6 + 1” structure of human resource management service combined with some characteristics of cloud computing, elaborates the service mode of the cloud service platform based on this structure, the characteristics and challenges of the platform, and hopes to provide a new service perspective to human resource management.
基金supported by National Natural Science Foundation of China and Scientific Forefront and Interdisciplinary Innovation Project, Jilin University under Grants No. 60372061,200903296
文摘In this paper, we adopt cloud computing in a specific scientific computing field for its virtualization, distribution and dynamic extendibility as follows: We obtain high-energy parabolic self-similar pulses by numerical simulation using our non-distributed passively mode-locked Er-doped fiber laser model. For researching characteristics of these wave-breaking-free self-similar pulses, chirp of them must be extracted. We propose several time-frequency analysis methods adopted in chirp extraction of ultra-short optical pulses for the first time and discuss the advantages and disadvantages of them in this particular application.
基金Supported by the National Natural Science Foundation of China (No. 61172047)
文摘In order to overcome the disadvantages of low accuracy rate, high complexity and poor robustness to image noise in many traditional algorithms of cloud image detection, this paper proposed a novel algorithm on the basis of Markov Random Field (MRF) modeling. This paper first defined algorithm model and derived the core factors affecting the performance of the algorithm, and then, the solving of this algorithm was obtained by the use of Belief Propagation (BP) algorithm and Iterated Conditional Modes (ICM) algorithm. Finally, experiments indicate that this algorithm for the cloud image detection has higher average accuracy rate which is about 98.76% and the average result can also reach 96.92% for different type of image noise.
