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Based on experiment of plastic mulching and drip irrigation in greenhouse, nine treatments of different irrigation and fertilization were evaluated with multi-factor fuzzy synthesis evaluation method. Linear function was selected as membership function in fuzzy synthesis evaluation model. The weighting of factors set which included the yield, fruit qualities, water use efficiency and fertilizer utilization efficiency was confirmed by principal component analysis method. The evaluation result showed that the optimum treatment of integral indicators that fertilizer amount was pure N 337.5 kg·ha−1 and pure K2O 337.5 kg·ha−1, lower and high limit of irrigation were respective 40 kPa and 6 kPa. [ABSTRACT FROM AUTHOR]

The probability model is introduced into classification learning in this paper. Kernel covering algorithm (KCA) and maximum likelihood principle of the statistic model combine to form a novel algorithm-the probability model of covering algorithm (PMCA) which not only introduces optimization processing for every covering domain, but offers a new way to solve the parameter problem of kernel function. Covering algorithm (CA) is firstly used to get covering domains and approximate interfaces, and then maximum likelihood principle of finite mixture model is used to fit each distributing. Experiments indicate that optimization is surely achieved, classification rate is improved and the neural cells are cut down greatly through with proper threshold value. [ABSTRACT FROM AUTHOR]

The quotient space theory uses a triplet, including the universe, its structure and attributes, to describe a problem space or simply a space. This paper improves the quotient space's model so as to absorb the methods of rough set. It also generalizes the false-preserving principle and true-preserving principle to the case of probability. Some basic operations on quotient space are introduced. The significant properties of the fuzzy quotient space family are elaborated. The main applications of quotient space theory are discussed. Keywords: quotient space, granular computing, fuzzy set, rough set, machine learning, data mining, pattern recognition, fuzzy control. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel blind adaptive multiuser detector using the recursive least squares (RLS) algorithm based on singular value decomposition (SVD) for code division multiple access systems. The new presented algorithm can overcome the disadvantages of numerical instability and divergence of the conventional RLS algorithm. Simulation results show that the novel SVD-based RLS algorithm is superior to the conventional RLS algorithm in convergence rate, numerical stability and robustness. [ABSTRACT FROM AUTHOR]

In this paper, the characteristics of Client/Server interaction behaviors under normal web access and typical DoS/DDoS attack are analyzed. A simple local rate-limiting method called Behavior-based Ingress Rate-limiting (BIR) mechanism is proposed, by which the client-end host's inbound and outbound traffics are monitored. Bursts of the traffics are suppressed by a local transmission delay mechanism. The principle and implementation are described. Simulations are performed to validate its efficacy. Finally, the approach's potential and limitations are also discussed. [ABSTRACT FROM AUTHOR]

In the paper, the clustering is investigated under the concept of granular computing, i.e.,the framework of quotient space theory. In principle, there are mainly two kinds of similarity measurement used in cluster analysis: one for measuring the similarity among objects (data, points); the other for measuring the similarity between objects and clusters (sets of objects). Therefore, there are mainly two categories of clustering corresponding to the two measurements. Furthermore, the fuzzy clustering is gained when the fuzzy similarity measurement is used. From the granular computing point of view, all these categories of clustering can be represented by a hierarchical structure in quotient spaces. From the hierarchical structures, several new characteristics ofclustering can be obtained. It may provide a new way for further investigating clustering. [ABSTRACT FROM AUTHOR]

Computational Grids, coupling geographically distributed resources, have emerged as a next generation computing platform for solving large-scale problems in scientific arena. Monitoring these Grid computing resources, which not only helps end-users monitor the status of Grid resources, but also provides quick and comprehensive information for resource scheduling and management, becomes extremely important for efficiently using Grid Computing resource. This paper presents architecture and implementation of a Grid Monitoring System based on Globus Toolkit. The Grid Monitoring System presented in this paper is flexible, extensible and, most important, secure. The architecture and implementation presented in this paper has important practical value for the monitoring of China Education and Research Grid. [ABSTRACT FROM AUTHOR]

One of the basic characteristics in human problem solving, including learning, is the ability to conceptualize the world at different granularities and translate from one abstraction level to the others easily, i.e., deal with them hierarchically[1]. But computers can only solve problems in one abstraction level generally. This is one of the reasons that human beings are superior to computers in problem solving and learning. In order to endow the computers with the human's ability, several mathematical models have been presented such as fuzzy set, rough set theories [2, 3]. Based on the models, the problem solving and machine learning can be handled at different grain-size worlds. We proposed a quotient space based model [4, 5] that can also deal with the problems hierarchically. In the model, the world is represented by a semi-lattice composed by a set of quotient spaces: each of them represents the world at a certain grain-size and is denoted by a triplet, (X, F, f) where X is a domain, F- the structure of X, f -the attribute of X. In this talk, we will discuss the hierarchical machine learning based on the proposed model. From the quotient space model point of view, a supervised learning (classification) can be regarded as finding a mapping from a low-level feature space to a high-level conceptual space, i.e., from a fine space to its quotient space (a coarse space) in the model. Since there is a big semantic gap between the low-level feature spaces and the conceptual spaces, finding the mapping is quite difficult and inefficiency. For example, it needs a large number of training samples and a huge amount of computational cost generally. In order to reduce the computational complexity in machine learning, the characteristics of human learning are adopted. In human learning, people always use a multi-level learning strategy, including multi-level classifiers and multi-level features, instead of one-level, i.e., learning at spaces with different grain-size. We call this kind of machine learning the hierarchical learning. So the hierarchical learning is a powerful strategy for improving machine learning. Taking the image retrieval as an example, we'll show how to use the hierarchical learning strategy to the field. Given a query (an image) by a user, the aim of image retrieval is to find a set of similar images from a collection of images. This is a typical classification problem and can be regarded as a supervised learning. The first problem is how to represent an image so that the similar images can be found from the collection of images precisely and entirely. So far in image retrieval, an image was represented by several forms with different grain-size. The finest representation of an image is by an n(n matrix, each of its elements represents a pixel. Using this representation to image retrieval, the precision will be high but the robustness (recall) will be low. Since it has the precise detail of an image, it is sensitive to noises. Therefore, the pixel-based representation was used in image retrieval rarely. The common used representation in image retrieval is the coarsest one, i.e., so called global visual features [6]. Here, an image is represented by a visual feature (a vector) such as color moments, color correlograms, wavelet transforms, Gabor transform, etc. In the coarsest representations, most of the details in an image lose so that the retrieval precision decreases but the robustness (recall) increases. The coarsest representations are suitable for seeking a class of similar images due to their robustness. Therefore, the global visual features were used for image retrieval widely. In order to overcome the low precision introduced by the coarsest representations, global features, the middle-size representation of an image was presented recently such as region-based representation [7].… [ABSTRACT FROM AUTHOR]

Under large scale data, machine learning becomes inefficient. In order to enhance its performances, new methodologies should be adopted. Taking video retrieval as an example, we discuss its two basic problems: representation and classification problems. [ABSTRACT FROM AUTHOR]

Three dimensional Large Eddy Simulation (LES) is performed to predict the unsteady turbulent flow and pressure fluctuation in an axial-flow pump with two different Subgrid-Scale (SGS) models. The specific speed of the axial-flow pump is 518. The calculated flow rates are Q/Qd =0.7, 0.8, 0.9 and 1.0, where Qd is the flow design point. Both the classical Smagorinsky-Lily SGS model [1] and the dynamic Smagorinsky-Lily SGS model [2] are used as the turbulent eddy viscosity model of LES with finite volume method and slide-mesh methodology, and the constant Cs in the later model is dynamically computed based on the information provided by the resolved scales of motion. The computational domain includes the rotator, the fixed guide-vane and the diffuser of the axial-flow pump (See Figure 1). The total head, shaft power and efficiency of the pump are obtained by the simulation and compared with the experimental measurements. The prediction results of the two SGS models are also compared. Both the SGS models successfully resolve the turbulent flow in the pump, and have good agreements with the experimental data. The pressure fluctuation of the flow in pump is predicted too, and the results show that the pressure fluctuation may be the leading role in unsteady hydraulic force generation. The simulation indicates that the numerical method presented in this paper has its potential capability to predict 3D unsteady turbulent flow and pressure fluctuation in axial-flow pumps, and the method can extend to other similar hydraulic machine too. [ABSTRACT FROM AUTHOR]

We presented a quotient space model that can represent a problem at different granularities; each model has three components: the universe X, property f and structure T. So a multi-granular analysis can be implemented based on the model. The basic properties among different quotient spaces such as the falsity preserving, the truth preserving properties are discussed. There are three quotient-space model construction approaches, i.e., the construction based on universe, based on property and based on structure. Four examples are given to show how a quotient space model can be constructed from a real problem and how benefit we can get from the multi-granular analysis. First, by adding statistical inference method to heuristic search, a statistical heuristic search approach is presented. Due to the hierarchical and multi-granular problem solving strategy, the computational complexity of the new search algorithm is reduced greatly. Second, in the collision-free paths planning in robotics, the topological model is constructed from geometrical one. By using the truth preserving property between these two models, the paths planning can be implemented in the coarser and simpler topological space so that the computational cost is saved. Third, we discuss the quotient space approximation and the multi-resolution signal analysis. And the second-generation wavelet analysis can be obtained from quotient-space based function approximation. It shows the equivalence relation between the quotient space model based analysis and wavelet transform. Fourth, in the automatic assembly sequence planning of mechanical product, we mainly show how a quotient structure can be constructed from the original one. By using the simpler quotient structure, the assembly sequence planning can be simplified greatly. In conclusion, the quotient-space model enables us to implement a multi-granular analysis. And we can get great benefit from the analysis. [ABSTRACT FROM AUTHOR]