Convex decomposition of concave clouds for the ultra-short-term power prediction of distributed photovoltaic system

Concave clouds will cause miscalculation by the power prediction model based on cloud features for distributed photovoltaic (PV) plant.The algorithm for decomposing concave cloud into convex images is proposed .Adopting minimum polygonal approximation ( MPP) to demonstrate the contour of concave cloud , cloud features are described and the subdivision lines of convex decomposition for the concave clouds are determined by the centroid point scattering model and centroid angle func -tion, which realizes the convex decomposition of concave cloud .The result of MATLAB simulation indicates that the proposed algorithm can accurately detect cloud contour corners and recognize the concave points .The proposed decomposition algorithm has advantages of less time complexity and decomposition part numbers compared to traditional algorithms .So the established model can make the convex decomposition of complex concave clouds completely and quickly , which is available for the existing prediction algorithm for the ultra-short-term power output of distributed PV system based on the cloud features .     

URMG: Enhanced CBMG-Based Method for Automatically Testing Web Applications in the Cloud简

To satisfy the rapid growth of cloud technologies, a large number of web applications have been developed and deployed, and these applications are being run in clouds. Due to the scalability provided by clouds, a single web application may be concurrently visited by several millions or billions of users. Thus, the testing and performance evaluations of these applications are increasingly important. User model based evaluations can significantly reduce the manual work required, and can enable us to determine the performance of applications under real runtime environments. Hence, it has become one of the most popular evaluation methods in both industry and academia. Significant efforts have focused on building different kinds of models using mining web access logs, such as Markov models and Customer Behavior Model Graph （CBMG）. This paper proposes a new kind of model, named the User Representation Model Graph （URMG）, which is built based on CBMG. It uses an algorithm to refine CBMG and optimizes the evaluations execution process. Based on this model, an automatic testing and evaluation system for web applications is designed, implemented, and deployed in our test cloud, which is able to execute all of the analysis and testing operations using only web access logs. In our system, the error rate caused by random access to applications in the execution phase is also reduced, and the results show that the error rate of the evaluation that depends on URMG is 50% less than that which depends on CBMG.     

Contribution of cloud condensate to surface rainfall process

Contribution of cloud condensate to surface rainfall processes is investigated in a life span of tropical convection based on hourly data from a two-dimensional cloud resolving simulation. The model is forced by the large-scale vertical velocity, zonal wind and horizontal advections obtained from tropical ocean global atmosphere coupled ocean-atmosphere response experiment (TOGA COARE). The results show that during the genesis, development, and decay of tropical convection, calculations with water vapor overestimate surface rain rate, and cloud condensate plays an important role in correcting overestimation in surface rain rates. The analysis is carried out in deep convective clouds and anvil clouds during the development of tropical convection. The surface rain rates calculated with water vapor in deep convective clouds and anvil clouds have similar magnitudes, the large surface rain rate appears in deep convective clouds due to the consumption of water hydrometeors whereas the small surface rain rate occurs in anvil clouds because of the gain of ice hydrometeors. Further analysis of the grid data shows that the surface rain rates calculated with water vapor and with cloud condensate are negatively correlated with the correlation coefficient of -0.85, and the surface rain rate calculated with cloud condensate is mainly contributed to the water hydrometeors in the tropical deep convective regime.     

Entrainment-mixing parameterization in shallow cumuli and effects of secondary mixing events

Parameterization of entrainment-mixing pro- cesses in cumulus clouds is critical to improve cloud parameterization in models, but is still at its infancy. For this purpose, we have lately developed a formulation to represent a microphysical measure defined as homoge- neous mixing degree in terms of a dynamical measure defined as transition scale numbers, and demonstrated the formulation with measurements from stratocumulus clouds. Here, we extend the previous work by examining data from observed cumulus clouds and find positive cor- relations between the homogeneous mixing degree and transition scale numbers. These results are similar to those in the stratocumulus clouds, but proved valid for the first time in observed cumulus clouds. The empiricalrelationships can be used to parameterize entrainment- mixing processes in two-moment microphysical schemes. Further examined are the effects of secondary mixing events on the relationships between homogeneous mixing degree and transition scale numbers with the explicit mixing parcel model. The secondary mixing events are found to be at least partially responsible for the larger scatter in the above positive correlations based on obser- vations than that in the previous results based on numerical simulations without considering secondary mixing events.     

A Novel Design of Power management integrated circuit with 90 plus efficiency used in AC/DC converter

Recently, resonant AC/DC converter has been accepted by the industry. However, the efficiency will be decreased at light load. So, a novel topology with critical controlling mode combined with resonant ones is proposed in this paper. The new topology can correspond to a 90 plus percent of power converting. So，a novel topology of an state of art integrated circuit, which can be used as power management circuit, has been designed based on the above new topology. A simulator which is specifically suitable for the power controller has been founded in this work and it has been used for the simulation of the novel architecture and the proposed integrated circuit.     

Using Combinational Logic Function to Watermark IP Based on FPGA

In the field of digital circuit design, the extensive applications of reusable intellectual property （IP） simplify the design procedure based on very large scale field programmable gate array （FPGA）, and shorten the time to market （TTM）. However, the flexibility of reusable IP makes itself easy to be stolen and illegally distributed by intruders. The protection method proposed in this paper maps IP owner＇s signature to combinational logic functions, and then implements these functions into unused lookup tables （LUTs） in the design based on FPGA, which can be used as a strong proof of IPs ownership. The related experiment results show that this protection method has favorable characteristics such as low overhead, few effects on performance, and high security.     

Impact of cloud inhomogeneity on bi-directional reflectance

This paper uses SHDOM （Spherical Harmonics Discrete Ordinate Method） to calculate the nadir bidirectional reflectance distribution function （BRDF） of the cumulus and stratocumulus fields at the wavelengths of 0.67 μm and 2.13 μm, and discusses the impact of cloud inhomogeneity on BRDF. The cloud fields are adopted from 13RC Phase Ⅱ, which are used to compare 3D radiative transfer models. The simulation results show that the cu field has 6% abnormal BRDF values （BRDF〉1） with the increase of solar zenith angle. Further analyses show that grid cells whose BRDF is greater than one gather together at the local trough of the top of cloud. These regions can receive not only the direct incident solar beam, but also the beam scattered by the higher cloud of its neighborhood. Hence, the BRDF of those regions is enhanced. The abnormal BRDF phenomenon shows that the cloud inhomogeneity can result in inconsistency between satellite observation and plane parallel theory, implying that the reflectance observed by high resolution satellite is maybe enhanced by the cloud 3D effects. Thus one should take this fact into account when using the product retrieved by these data. The dominant solar zenith angles are quite large in the mid-high altitude area, and the impact of cloud inhomogeneity on these areas may be more significant.     

Application of the moist vorticity vector in the analysis of a heavy rainfall event in North China

The moist vorticity vector (MVV), defined as (ζa×▽qv)/ρ introduced by Gao et al. is used to study a heavy rainfall event in North China. The MVV has zonal, meridional and vertical components in a three-dimensional framework. Analysis of domain-mean and mass-integrated quantities shows that the variation of the vertical component of the MVV closely follows the variation of the cloud hydrometeors, with a linear correlation coefficient of 0.95, indicating that the vertical component of the MVV is strongly associated with midlatitude convection. Further analysis shows that the vertical component of the MVV reflects the interaction between the horizontal vorticity and the horizontal specific humidity gradient, which can associate dynamic and thermodynamic processes with cloud microphysical processes. Thus, this study can help to understand how the interaction between circulations and clouds aids the development of convection, and the MVV can be used to trace the development and evolution of heavy rainfall.     

Application of the moist vorticity vector in the analysis of a heavy rainfall event in North China

The moist vorticity vector (MVV), defined as (ζa×qv)/ρ introduced by Gao et al. is used to study a heavy rainfall event in North China. The MVV has zonal, meridional and vertical components in a three-dimensional framework. Analysis of domain-mean and mass-integrated quantities shows that the variation of the vertical component of the MVV closely follows the variation of the cloud hydrometeors, with a linear correlation coefficient of 0.95, indicating that the vertical component of the MVV is strongly associated with midlatitude convection. Further analysis shows that the vertical component of the MVV reflects the interaction between the horizontal vorticity and the horizontal specific humidity gradient, which can associate dynamic and thermodynamic processes with cloud microphysical processes. Thus, this study can help to understand how the interaction between circulations and clouds aids the development of convection, and the MVV can be used to trace the development and evolution of heavy rainfall.     

DR-Cloud: Multi-Cloud Based Disaster Recovery Service简

With the rapid popularity of cloud computing paradigm, disaster recovery using cloud resources becomes an attractive approach. This paper presents a practical multi-cloud based disaster recovery service model： DR- Cloud. With DR-Cloud, resources of multiple cloud service providers can be utilized cooperatively by the disaster recovery service provider. A simple and unified interface is exposed to the customers of DR-Cloud to adapt the heterogeneity of cloud service providers involved in the disaster recovery service, and the internal processes between clouds are invisible to the customers. DR-Cloud proposes multiple optimization scheduling strategies to balance the disaster recovery objectives, such as high data reliability, low backup cost, and short recovery time, which are also transparent to the customers. Different data scheduling strategies based on DR-Cloud are suitable for different kinds of data disaster recovery scenarios. Experimental results show that the DR-Cloud model can cooperate with cloud service providers with various parameters effectively, while its data scheduling strategies can achieve their optimization objectives efficiently and are widely applicable.     

Response of the East Asian summer monsoon to large volcanic eruptions during the last millennium

The responses of the East Asian summer monsoon （EASM） to large volcanic eruptions were analyzed using a millennial simulation with the FGOALS-gl climate system model. The model was driven by both natural （solar irradiance, volcanic eruptions） and anthro- pogenic （greenhouse gases, sulfate aerosols） forcing agents. The results showed cooling anomalies after large volcanic eruptions almost on a global scale. The cooling over the continental region is stronger than that over the ocean. The precipitation generally decreases in the tropical and subtropical regions in the first summer after large volcanic eruptions. Cooling with amplitudes up to -0.3 ℃ is seen over eastern China in the first summer after large volcanic eruptions. The East Asian continent is dominated by northeasterly wind anomalies and the corresponding summer rainfall exhibits a coherent reduction over the whole of eastern China. An analysis of the surface heat flux suggested the reduction in summer precipitation over eastern China can be attributed to a decrease of moisture vapor over the tropical oceans, and the weakening of the EASM may be attributed to the reduced land-sea thermal contrast after large volcanic eruptions.     

Temperature Prediction Model Identification Using Cyclic Coordinate Descent Based Linear Support Vector Regression

Temperature prediction plays an important role in ring die granulator control, which can influence the quantity and quality of production. Temperature prediction modeling is a complicated problem with its MIMO, nonlinear, and large time-delay characteristics. Support vector machine （SVM） has been successfnlly based on small data. But its accuracy is not high, in contrast, if the number of data and dimension of feature increase, the training time of model will increase dramatically. In this paper, a linear SVM was applied combing with cyclic coordinate descent （ CCD） to solving big data regression. It was mathematically strictly proved and validated by simulation. Meanwhile, real data were conducted to prove the linear SVM model＇s effect. Compared with other methods for big data in simnlation, this algorithm has apparent advantage not only in fast modeling but also in high fitness.     

A piecewise-integration method for simulating the influence of external forcing on climate

Climate drift occurs in most general circulation models （GCMs） as a result of incomplete physical and numerical representation of the complex climate system, which may cause large uncertainty in sensitivity experiments evaluating climate response to changes in external forcing. To solve this problem, we propose a piecewise-integration method to reduce the systematic error in climate sensitivity studies. The observations are firstly assimilated into a numerical model by using the dynamic relaxation technique to relax to the current state of atmosphere, and then the assimilated fields are continuously used to reinitialize the simulation to reduce the error of climate simulation. When the numerical model is integrated with changed external forcing, the results can be split into two parts, background and pertur- bation fields, and the background is the state before the external forcing is changed. The piecewise-integration method is used to con- tinuously reinitialize the model with the assimilated field, instead of the background. Therefore, the simulation error of the model with the external forcing can be reduced. In this way, the accuracy of climate sensitivity experiments is greatly improved. Tests with a simple low-order spectral model show that this approach can significantly reduce the uncertainty of climate sensitivity experiments.     

Experimental and modeling studies on number and size spectrum evolutions of aerosol particles within a chamber

A size-specific aerosol dynamic model is set up to predict the evolution of particle number concentration within a chamber. Particle aggregation is based on the theory of Brownian coagulation, and the model not only comprises particle loss due to coagulation, but also considers the formation of large particles by collision. To validate the model, three different groups of chamber experiments with SMPS （Scanning Mobility Particle Sizer） are conducted. The results indicate that the advantage of the model over the past simple size bin model is its provision of detailed information of size spectrum evolution, and the results can be used to analyze the variations of number concentration and CMD （Count Median Diameter）. Furthermore, some aerosol dynamic mechanisms that cannot be measured by instrument can be analyzed by the model simulation, which is significant for better understanding the removal and control mechanisms of ultrafine particles.     

Parameterization for fitting triangular mesh

In recent years, with the development of 3D data acquisition equipments, the study on reverse engineering has become more and more important. However, the existing methods for parameterization can hardly ensure that the parametric domain is rectangular, and the parametric curve grid is regular. In order to overcome these limitations, we present a novel method for parameterization of triangular meshes in this paper. The basic idea is twofold: first, because the isotherms in the steady temperature do not intersect with each other, and are distributed uniformly, no singularity (fold-over) exists in the parameterization; second, a 3D harmonic equation is solved by the finite element method to obtain the steady temperature field on a 2D triangular mesh surface with four boundaries. Therefore, our proposed method avoids the embarrassment that it is impossible to solve the 2D quasi-harmonic equation on the 2D triangular mesh without the parametric values at mesh vertices. Furthermore, the isotherms on the temperature field are taken as a set of iso-parametric curves on the triangular mesh surface. The other set of iso-parametric curves can be obtained by connecting the points with the same chord-length on the isotherms sequentially. The obtained parametric curve grid is regular, and distributed uniformly, and can map the triangular mesh surface to the unit square domain with boundaries of mesh surface to boundaries of parametric domain, which ensures that the triangular mesh surface or point cloud can be fitted with the NURBS surface.     

Fine-grained and heterogeneous proxy re-encryption for secure cloud storage

Cloud is an emerging computing paradigm. It has drawn extensive attention from both academia and industry. But its security issues have been considered as a critical obstacle in its rapid development. When data owners store their data as plaintext in cloud, they lose the security of their cloud data due to the arbitrary accessibility, specially accessed by the un-trusted cloud. In order to protect the confidentiality of data owners＇ cloud data, a promising idea is to encrypt data by data owners before storing them in cloud. However, the straightforward employment of the traditional encryption algorithms can not solve the problem well, since it is hard for data owners to manage their private keys, if they want to securely share their cloud data with others in a fine-grained manner. In this paper, we propose a fine-grained and heterogeneous proxy re-encryption （FH- PRE） system to protect the confidentiality of data owners＇ cloud data. By applying the FH-PRE system in cloud, data owners＇ cloud data can be securely stored in cloud and shared in a fine-grained manner. Moreover, the heteroge- neity support makes our FH-PRE system more efficient than the previous work. Additionally, it provides the secure data sharing between two heterogeneous cloud systems, which are equipped with different cryptographic primitives.     

Efficient View-Based 3-D Object Retrieval via Hypergraph Learning

View-based 3-D object retrieval has become an emerging topic in recent years,especially with the fast development of visual content acquisition devices,such as mobile phones with cameras.Extensive research efforts have been dedicated to this task,while it is still difficult to measure the relevance between two objects with multiple views.In recent years,learning-based methods have been investigated in view-based 3-D object retrieval,such as graph-based learning.It is noted that the graph-based methods suffer from the high computational cost from the graph construction and the corresponding learning process.In this paper,we introduce a general framework to accelerate the learning-based view-based 3-D object matching in large scale data.Given a query object Q and one object O from a 3-D dataset D,the first step is to extract a small set of candidate relevant 3-D objects for object O.Then multiple hypergraphs can be constructed based on this small set of 3-D objects and the learning on the fused hypergraph is conducted to generate the relevance between Q and O,which can be further used in the retrieval procedure.Experiments demonstrate the effectiveness of the proposed framework.     

Fault-Tolerant Mechanism of the Distributed Cluster Computers

The distributed system with high performance and stability is commonly adopted in large scale scientific and engineering computing. In this paper, we discuss a fault-tolerant mechanism under Linux circumstance to improve the fault-tolerant ability of the system, namely a scheme and frame to form the stable computing platform. In terms of the structure and function of the distributed system, active list and file invocation strategies are employed in the task management. System multilevel fault-tolerance can be achieved by repeated processes in a single node and task migration on multi-nodes. Manager node agent introduced in this paper administrates the nodes using the list, disposes of the tasks according to the nodes' performance, and hence, to be able to make full use of the cluster resources. An evaluation method is proposed to appraise the performance. The analyzed results show the usefulness of the scheme proposed except for some additional overhead of memory consumption.     

Stochastic differential equation software reliability growth model with change-point

This paper presents software reliability growth models （SRGMs） with change-point based on the stochastic differential equation （SDE）.Although SRGMs based on SDE have been developed in a large scale software system,considering the variation of failure distribution in the existing models during testing time is limited.These SDE SRGMs assume that failures have the same distribution.However,in practice,the fault detection rate can be affected by some factors and may be changed at certain point as time proceeds.With respect to this issue,in this paper,SDE SRGMs with changepoint are proposed to precisely reflect the variations of the failure distribution.A real data set is used to evaluate the new models.The experimental results show that the proposed models have a fairly accurate prediction capability.     

Estimation of Mutual Coupling Coefficient of the Array by Simulated Annealing Algorithm

We propose a method for estimating the mutual coupling coefficient among antennas in this paper which is based on the principle of signal subspace and the simulated annealing （SA） algorithm. The computer simulation has been conducted to illustrate the＇ excellent performance of this method and to demonstrate that it is statistically efficient. The benefit of this new method is that calibration signals and unknown signals can be received simultaneously, during the course of calibration.