An efficient selectivity estimation method for spatial query optimization with topological relationships

Many commercial database systems maintain histograms to summarize the contents of relations and permit the efficient estimation of query result sizes and the access plan cost. In spatial database systems,most spatial query predicates are consisted of topological relationships between spatial objects,and it is very important to estimate the selectivity of those predicates for spatial query optimizer. In this paper, we propose a selectivity estimation scheme for spatial topological predicates based on the multidimensional histogram and the transformation scheme. Proposed scheme applies two-partition strategy on transformed object space to generate spatial histogram and estimates the selectivity of topological predicates based on the topological characteristics of the transformed space. Proposed scheme provides a way for estimating the selectivity without too much memory space usage and additional I/Os in most spatial query optimizers.     

A Voronoi-based spatial algebra for spatial relations

Spatial relation between spatial objects is a very important topic for spatial reasoning, query and analysis in geographical information systems (GIS). The most popular models in current use have fundamental deficiencies in theory. In this paper, a generic algebra for spatial relations is presented, in which (i) appropriate operators from set operators (i.e. union, intersection, difference, difference by, symmetric difference, etc.) are utilized to distinguish the spatial relations between neighboring spatial objects; (ii) three types of values are used for the computational results of set operations-content, dimension and number of connected components; and (iii) a spatial object is treated as a whole but the Voronoi region of an object is employed to enhance its interaction with its neighbours. This algebra overcomes the shortcomings of the existing models and it can effectively describe the relations of spatial objects.     

An Index mechanism for multi-scale view in spatial databases

There are numerous geometric objects stored in the spatial databases. An importance function in a spatial database is that users can browse the geometric objects as a map efficiently. Thus the spatial database should display te geometric objects users concern about swiftly onto the display window. This process includes two operations：retrieve data from database and then draw them onto screen. Accordingly,to improve the efficiency,we should try to reduce time of both retrieving object and displaying them. The former can be achieved with the aid of spatial index such as R-tree,the latter require to simplify the objects. Simplification means that objects are shown with sufficient but not with unnecessary detail which depend on the scale of browse. So the major problem is how to retrieve data at different detail level efficiently. This paper intrrduces the implementation of a multi-scale index in the spatial database SISP (Spatial Information Shared Platform ) which is generalized from R-tree. The difference between the generalization and the R-tree lies on two facets ： One is that every node and geometric object in the generalization is assigne+ with a importance value which +enote the importance of them,and every vertex in the objects are assigned with a importance value,too. The importance value can be use to decide which data should be retrieve from disk in a query. The other difference is that geometric objects in the generalization are divided into one or more sub-blocks,and vertexes are total ortiered by their importance value. With the help of the generalized R-tree,one can easily rtrieve data at differnt detail levels. Some experiments are performed on real-life data to evaluate the performance of solutions that separately use normal spatial index and multi-scale spatial index. The results show that the solution using multi-scale index in SISP is satisfying.     

The Differences Between Aesthetic Emotions and Life Emotions

This essay talks mainly about the differences between aesthetic emotions and everyday emotions.Firstly we need to be sure that the work of art has something to do with emotions both of artists and audience.The paper tries to prove this from the perspectives of expressionism,formalism and representationalism.Then the paper differentiates the two kinds of emotions from three aspects.Audience need to keep psychical distance from arts,contemplating art in a disinterested way and use imagination to arouse the aesthetic emotions.Although aesthetic emotions are different from everyday emotions,there are some relations between them.The meaning of appreciating works of art is mainly to realize much more delicate or significant emotions that we could not or do not want to acquire in our limited and realistic daily life,through which we broaden our lives and know more about ourselves and the world we live in.     

Solving Topological and Geometrical Constraints in Bridge Feature Model

The capacity that computer can solve more complex design problem was gradually increased. Bridge designs need a breakthrough in the current development limitations, and then become more intelligent and integrated. This paper proposes a new parametric and feature-based computer aided design (CAD) models which can represent families of bridge objects, includes knowledge representation, three-dimensional geometric topology relationships. The realization of a family member is found by solving first the geometric constraints, and then the topological constraints. From the geometric solution, constraint equations are constructed. Topology solution is developed by feature dependencies graph between bridge objects. Finally, feature parameters are proposed to drive bridge design with feature parameters. Results from our implementation show that the method can help to facilitate bridge design.     

Linguistic Politeness and Impoliteness Analysis

This paper aims to interrogate the relationship between politeness and impoliteness for pragmatics study. Away from the model whereby individual speech acts are considered to be inherently polite or impolite, one argument is that stereotypes of gender may play a role in the decisions that such communities make about politeness.     

How to Improve Communicative Competence of EFL Teacher in the Classroom

The modern teaching principles regard teaching process as the one of teacher-student communication,interaction and development. Some scholars therefore suggest that communication is the essence of teaching. Classroom communication is of great practical significance for education. However,a present empirical study shows that the current situation of teacher-student relations and communication in the EFL classroom is not satisfied enough. The teachers’communicative competence in the classroom needs to be improved. Based on factors that affect the teacher-student communication and the suggestion of the present empirical study,this paper suggests 5 ways to improve the classroom communicative competence of EFL teachers: 1) Teachers need to reconstruct and internalize the notion of modern educational communication; 2) Teachers need to apply appropriate teaching methods and teaching techniques; 3) Teachers need to well harmonize the relations between democracy and authority; 4) Teachers need to equally com-municate with all students and respect them; 5) Teachers need to create a communicative teaching environment. In this way we can facilitate the overall development of students.     

Research on spatial association rules mining in two direction

In data mining from transaction DB, the relationships between the attributes have been focused, but the relationships between the tuples have not been taken into account. In spatial database, there are relationships between the attributes and the tuples, and most of the associations occur between the tuples, such as adjacent, intersection, overlap and other topological relationships. So the tasks of spatial data association rules mining include mining the relationships between attributes of spatial objects, which are called as vertical direction DM, and the relationships between the tuples, which are called as horizontal direction DM. This paper analyzes the storage models of spatial data, uses for reference the technologies of data mining in transaction DB, defines the spatial data association rule, including vertical direction association rule, horizontal direction association rule and twodirection association rule, discusses the measurement of spatial association rule interestingness, and puts forward the work flows of spatial association rule data mining. During twodirection spatial association rules mining, an algorithm is proposed to get nonspatial itemsets. By virtue of spatial analysis, the spatial relations were transferred into nonspatial associations and the nonspatial itemsets were gotten. Based on the nonspatial itemsets, the Apriori algorithm or other algorithms could be used to get the frequent itemsets and then the spatial association rules come into being. Using spatial DB, the spatial association rules were gotten to validate the algorithm, and the test results show that this algorithm is efficient and can mine the interesting spatial rules.     

Communication Styles and Business English Teaching

Nowadays,more and more people in the business community realize an urgent need to use English to cope with increasing economic globalization.Some people claim that they cannot communicate well because they do not learn English vocabulary and grammar well.However,we should understand that linguistic capability and communicative competency are two different things.Communicative competency is in fact largely affected by the culture that a language represents.This paper will focus on differences between the ways in which Chinese English speakers and native English speakers communicate in business situations,and furthermore,analyze their cultural roots.The purpose of this paper is to make people be more aware of the difficulties or problems that may occur when using English in business activities,and therefore,improve the ability to reduce or avoid misunderstandings,embarrassment and even conflicts in cross-cultural communication.     

A probabilistic paradigm for handling uncertain objects in GIS by randomized graph algebra

Probability theory faces difficulties when it is applied to describing uncertain objects in geographic information system (GIS). This is mainly due to the fact that an object in GIS is normally described by a series of discrete vertexes. Modeling uncertainty objects should be therefore based on error of the composed vertexes. This type of model is normally complex and relatively difficult to implement because of many unknown factors, such as the number of vertexes of a polygon, error nature of each individual vertex and error correlation among the vertexes. In this paper, a probabilistic paradigm for handling uncertain objects in GIS by randomized graph algebra is presented. The theoretical basis for this paradigm is the randomized graph algebra-a probability theory for graph-which is newly proposed in this study. Classical probability theory is based on numerical algebra and is also an extension of numerical algebra by further defining probability density within a numerical domain. In the same token, this study begins with defining graph algebra as the basis for probability theory for graph. First, we adopt the theory of graph algebra and further refine the theory by defining the modulo operation for graph. As a result, a graph can thereafter be treated as a "number" and operated by "addition", "subtraction" and others. Second, we construct a measure space by generating sigma-algebra and defining measurable function upon it. The measure space becomes a probability space when the measurable function is a probability density function. Third, we propose the probabilistic paradigm for describing and inferring the uncertainty of geometric objects in GIS by applying the developed randomized graph algebra.     

Development operators on 4D moving object databases

In this paper we propose four-dimensional (4D) operators,which can be used to deal with sequential changes of topological relationships between 4D moving objects and we call them 4D development operators. In contrast to the existing operators,we can apply the operators to real applications on 4D moving objects. We also propose a new approach to define them. The approach is based on a dimension-separated method,which considers x-y coordinates and ( coordinates separately. In order to show the applicability of our operators,we show the algorithms for the proposed operators and development graph between 4D moving objects.     

Development of an Accurate Urban Modeling System Using CAD/GIS Data for Atmosphere Environmental Simulation

This paper presents an urban modeling system using CAD/GIS data for atmosphere environmental simulation, such as wind flow and contaminant spread in urban area. The CAD data is used for the shape modeling for the high-storied buildings and civil structures with complicated shape since the data for that is not included in the 3D-GIS data accurately. The unstructured mesh based on the tetrahedron element is employed in order to express the urban structures with complicated shape accurately. It is difficult to understand the quality of shape model and mesh by the conventional visualization technique. In this paper, the stereoscopic visualization using virtual reality (VR) technology is employed for the verification of the quality of shape model and mesh. The present system is applied to the atmosphere environmental simulation in urban area and is shown to be an useful planning and design tool to investigate the atmosphere environmental problem.     

Content-Based Image Retrieval: Near Tolerance Rough Set Approach

<正>The problem considered in this paper is how to detect the degree of similarity in the content of digital images useful in image retrieval,i.e.,to what extent is the content of a query image similar to content of other images.The solution to this problem results from the detection of subsets that are rough sets contained in covers of digital images determined by perceptual tolerance relations(PTRs).Such relations are defined within the context of perceptual representative spaces that hearken back to work by J.H.Poincare on representative spaces as models of physical continua.Classes determined by a PTR provide content useful in content-based image retrieval(CBIR).In addition,tolerance classes provide a means of determining when subsets of image covers are tolerance rough sets(TRSs).It is the nearness of TRSs present in image tolerance spaces that provide a promising approach to CBIR,especially in cases such as satellite images or aircraft identification where there are subtle differences between pairs of digital images,making it difficult to quantify the similarities between such images.The contribution of this article is the introduction of the nearness of tolerance rough sets as an effective means of measuring digital image similarities and,as a significant consequence,successfully carrying out CBIR.     

Automated detection of lunar craters based on object-oriented approach

The object-oriented approach is a powerful method in making classification. With the segmentation of images to objects, many features can be calculated based on the objects so that the targets can be distinguished. However, this method has not been applied to lunar study. In this paper we attempt to apply this method to detecting lunar craters with promising results. Craters are the most obvious fea- tures on the moon and they are important for lunar geologic study. One of the important questions in lunar research is to estimate lunar surface ages by examination of crater density per unit area. Hence, proper detection of lunar craters is necessary. Manual crater identification is inefficient, and a more efficient and effective method is needed. This paper describes an object-oriented method to detect lunar craters using lunar reflectance images. In the method, many objects were first segmented from the image based on size, shape, color, and the weights to every layer. Then the feature of ＂contrast to neighbor objects＂ was selected to identify craters from the lunar image. In the next step, by merging the adjacent objects belonging to the same class, almost every crater can be taken as an independent object except several very big craters in the study area. To remove the crater rays diagnosed as craters, the feature of ＂length/width＂ was further used with suitable parameters to finish recognizing craters. Finally, the result was exported to ArcGIS for manual modification to those big craters and the number of craters was acquired.     

Query through heterogeneous ontologies using association matrix

This paper introduces the definition and calculation of the association matrix between ontologies, h uses the association matrix to describe the relations between concepls ill different ontologics and uses concept vectors to represent queries; then computes the vectors with the association matrix in order to rewrite queries, This paper proposes a simple method of querying through heterogeneous Ontology using association matrix. This method is based on the correctness of approximate information filtering theory; and it is simple to be implemented and expected to run quite fast.     

Consortium for the Human Information and Neurocognitive Endophenotype （CHINE） in mainland China： An example from neurological soft signs for neuropsychiatric disorders

Increasing efforts to identify alternate expressions of neuropsychiatric disorders that are broader than the DSM or ICD diagnostic criteria needed to diagnose them reflects a growing consensus that multidimensional expressions of neuropsychiatric disorders may advance the search for underlying etiological or modulatory factors. Endophenotypic research can be considered to be one of the most promising strategies to bridge the gap between genomic complexity and the phenotypic heterogeneity observed in neuropsychiatric disorders. However, the majority of endophenotype studies were limited to our western counterparts, very little has been done and initiated by scholars in mainland China. In this paper, we urge the need to establish a potential central consortium for endophenotypes to study neuropsychiatric disorders in mainland China. In particular, we illustrate a potential example of neurological soft signs in following the steps for building the consortium.     

Dual effects of spatial updating in both real and virtual environments

When people move around in their environment, spatial updating, which is an automatic cognitive process, is essential to ensuring people can keep track of their relations between them and the surrounding objects, and to "recalculating" the relative position and orientation of those objects with regard to the current position of the persons. Despite the facilitating effect of spatial updating to people’s mental representation in most circumstances as demonstrated in most of the existing literature, the effect sometimes can be adversarial. For instance, some research suggested that even though people were asked to ignore their locomotion, it is difficult to suppress updating of the spatial representation during movement. The current two studies were conducted to systematically investigate the dual effects of spatial updating in both real and virtual environments. We used a typical spatial updating paradigm to explore the effects of scene familiarity (familiar vs. novel) and person’s locomotion (stationary vs. moving) on change detection accuracy (target object moved or not). The results indicated a facilitating effect of spatial updating in the novel scene condition, but an adversarial effect in the familiar scene condition-the dual effects, in both real and virtual environments.     

Community Detection in Disease-Gene Network Based on Principal Component Analysis

The identification of communities is imperative in the understanding of network structures and functions.Using community detection algorithms in biological networks, the community structure of biological networks can be determined, which is helpful in analyzing the topological structures and predicting the behaviors of biological networks. In this paper, we analyze the diseasome network using a new method called disease-gene network detecting algorithm based on principal component analysis, which can be used to investigate the connection between nodes within the same group. Experimental results on real-world networks have demonstrated that our algorithm is more efficient in detecting community structures when compared with other well-known results.     

Bow-tie topological features of metabolic networks and the functional significance

Exploring the structural topology of genome-based large-scale metabolic network is essential for in- vestigating possible relations between structure and functionality.Visualization would be helpful for obtaining immediate information about structural organization.In this work,metabolic networks of 75 organisms were investigated from a topological point of view.A spread bow-tie model was proposed to give a clear visualization of the bow-tie structure for metabolic networks.The revealed topological pattern helps to design more efficient algorithm specifically for metabolic networks.This coarse- grained graph also visualizes the vulnerable connections in the network,and thus could have important implication for disease studies and drug target identifications.In addition,analysis on the reciprocal links and main cores in the GSC part of bow-tie also reveals that the bow-tie structure of metabolic networks has its own intrinsic and significant features which are significantly different from those of random networks.