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This paper proposes to evaluate the adaptability risk in money laundering using Bitmap Index-based Decision Tree (BIDT) technique. Initially, the Bitmap Index-based Decision Tree learning is used to induce the knowledge tree which helps to determine a company's money laundering risk and improve scalability. A bitmap index in BIDT is used to effectively access large banking databases. In a BIDT bitmap index, account in a table is numbered in sequence with each key value, account number and a bitmap (array of bytes) used instead of a list of row ids. Subsequently, BIDT algorithm uses the ‘‘select” query performance to apply count and bit-wise logical operations on AND. Query result coincides exactly to build a decision tree and more precisely to evaluate the adaptability risk in the money laundering operation. For the root node, the main account of the decision tree, the population frequencies are obtained by simply counting the total number of ‘‘1” in the bitmaps constructed on the attribute to predict money laundering and evaluate the risk factor rate. The experiment is conducted on factors such as regulatory risk rate, false positive rate, and risk identification time. [ABSTRACT FROM AUTHOR]

Given a grid of cells each having an associated cost value, a raster version of the least-cost path problem seeks a sequence of cells connecting two specified cells such that its total accumulated cost is minimized. Identifying least-cost paths is one of the most basic functions of raster-based geographic information systems. Existing algorithms are useful if the path width is assumed to be zero or negligible compared to the cell size. This assumption, however, may not be valid in many real-world applications ranging from wildlife corridor planning to highway alignment. This paper presents a method to solve a raster-based least-cost path problem whose solution is a path having a specified width in terms of Euclidean distance (rather than by number of cells). Assuming that all cell values are positive, it does so by transforming the given grid into a graph such that each node represents a neighborhood of a certain form determined by the specified path width, and each arc represents a possible transition from one neighborhood to another. An existing shortest path algorithm is then applied to the graph. This method is highly efficient, as the number of nodes in the transformed graph is not more than the number of cells in the given grid and decreases with the specified path width. However, a shortcoming of this method is the possibility of generating a self-intersecting path which occurs only when the given grid has an extremely skewed distribution of cost values. [ABSTRACT FROM PUBLISHER]

The virtual globe is the default visualization for Digital Earth applications, but it can only show one half of the Earth. This article introduces user-adjustable, on-the-fly projection of georeferenced raster images for web mapping and web GIS applications. This technique allows users to center a map on arbitrary locations, while still seeing the entire Earth surface. Modern web mapping libraries can apply map projection transformations to vector data in the browser, but they do not currently support the projection of raster images at interactive frame rates. We use the cross-platform WebGL (Web Graphics Library) graphics pipeline for hardware-accelerated projection of raster data in web browsers. Two algorithmic techniques – inverse per-fragment projection, and combined forward per-triangle and inverse per-fragment projection – for georeferenced raster imagery are documented. The resulting raster maps combine the ease of use and flexibility of interactive virtual globes with the ability to show the entire Earth. The adjustable projection of raster imagery allows users to observe global phenomena that are difficult to visualize on virtual globes or traditional maps with static projections. [ABSTRACT FROM PUBLISHER]

In this paper, we introduced a modified version of backpropagation algorithm which is able to converge faster than the traditional backpropagation for multilayer perceptron neural networks. We also proposed a dynamic technique for specifying the number of hidden layers and number of neuron in each hidden layer along with an initialization technique to set start values of the synaptic weights. A novel two activation functions have been proposed, which are proved experimentally that they accelerate convergence of neural networks while maintaining the accuracy of the trained network. Experimental results showed that the average number of epochs required to reach approximation using exponential hyperbolic tangent is less than the half of average number using traditional sigmoid function. Finally, a case study is performed on converting alphanumeric character bit-mapped pixel image to its ASCII equivalent code. [ABSTRACT FROM AUTHOR]

The neighborhood definition, which determines the influence on a cell from its nearby cells within a localized region, plays a critical role in the performance of a cellular automaton (CA) model. Raster CA models use a cellular grid to represent geographic space, and are sensitive to the cell size and neighborhood configuration. However, the sensitivity of vector-based CAs, an alternative to the raster-based counterpart, to neighborhood type and size remains uninvestigated. The present article reports the results of a detailed sensitivity analysis of an irregular CA model of urban land use dynamics. The model uses parcel data at the cadastral scale to represent geographic space, and was implemented to simulate urban growth in Central Texas, USA. Thirty neighborhood configurations defined by types and sizes were considered in order to examine the variability in the model outcome. Results from accuracy assessments and landscape metrics confirmed the model’s sensitivity to neighborhood configurations. Furthermore, the centroid intercepted neighborhood with a buffer of 120 m produced the most accurate simulation result. This neighborhood produced scattered development while the centroid extent-wide neighborhood resulted in a clustered development predominantly near the city center. [ABSTRACT FROM AUTHOR]

The demand for parallel geocomputation based on raster data is constantly increasing with the increase of the volume of raster data for applications and the complexity of geocomputation processing. The difficulty of parallel programming and the poor portability of parallel programs between different parallel computing platforms greatly limit the development and application of parallel raster-based geocomputation algorithms. A strategy that hides the parallel details from the developer of raster-based geocomputation algorithms provides a promising way towards solving this problem. However, existing parallel raster-based libraries cannot solve the problem of the poor portability of parallel programs. This paper presents such a strategy to overcome the poor portability, along with a set of parallel raster-based geocomputation operators (PaRGO) designed and implemented under this strategy. The developed operators are compatible with three popular types of parallel computing platforms: graphics processing unit supported by compute unified device architecture, Beowulf cluster supported by message passing interface (MPI), and symmetrical multiprocessing cluster supported by MPI and open multiprocessing, which make the details of the parallel programming and the parallel hardware architecture transparent to users. By using PaRGO in a style similar to sequential program coding, geocomputation developers can quickly develop parallel raster-based geocomputation algorithms compatible with three popular parallel computing platforms. Practical applications in implementing two algorithms for digital terrain analysis show the effectiveness of PaRGO. [ABSTRACT FROM PUBLISHER]

Spatial index is a key component of Geographic Information Systems (GISystems). To date, an increasing number of spatial indexes have been developed to enhance the efficiency of spatial analysis and spatial query. Approximate expressions are adopted in the foundation of spatial index construction, to assist data organisation, e.g., bounding box of vector elements can be employed to build R-tree index. However, R-tree index using such bounding box expresses elements approximately, which usually results in redundancy and excessiveness due to inherent roughness of this method. This study proposes a characteristic bitmap coding method, termed the QCODE method, which generates approximate expressions of vector elements based on self-adaptive gridding. Based on the sizes of vector elements, this method selects the grid at an appropriate level in a self-adaptive manner, discretises the vector elements into grids through a rasterisation operation, as well as compresses and encodes this information as the code of a characteristic bitmap, i.e., the QCODE. The ‘bit’ data type is used in the design of QCODE to restrict the approximate expression of vector elements into finite bytes, providing more precise filtering as compared to the case in which only bounding box is used. With its distinct characteristics, the QCODE is introduced for the improvement of R-tree index. The results of experiments show that, combined with R-tree index, this method can reduce the filtering amount of vector elements as required for spatial analysis, and accelerate the execution efficiency of the entire process of GIS spatial analysis. [ABSTRACT FROM PUBLISHER]

Afin de réduire le temps d’exécution des requêtes décisionnelles, l’administrateur a la possibilité de sélectionner des index de jointure binaires (). Cette sélection demeure une tâche difficile vue la complexité de l’espace de recherche à parcourir. De ce fait, un grand intérêt est porté à la mise en oeuvre d’algorithmes de sélection. Cependant, ces algorithmes sont statiques. Dans cet article, nous centrons nos travaux sur la sélection des index de jointures binaires définis sur plusieurs attributs appartenant à des tables de dimension en utilisant des algorithmes génétiques. Nous présentons deux types d’algorithmes: des algorithmes de sélection statiques et des algorithmes de sélection incrémentales qui prévoient l’adaptation des index sélectionnés à l’arrivée de nouvelles requêtes. Nous concluons nos travaux par une étude expérimentale démontrant l’apport de notre sélection des index de jointure binaires en comparaison avec les travaux de sélection statiques et incrémentales existants. Bitmap join indexes (BJI) have been widely advocated by administrators as a solution to optimize complex queries. Their selection remains hard, since it needs to explore a large search space. Only a few classes of algorithms were proposed to deal with the problem of BJI selection. These algorithms are static and do not take into account the changes of data warehouses in terms of query arrival. In this paper, we propose a genetic algorithm to select BJI defined on multiple attributes belonging to various dimension tables in the static way. This algorithm is extended to deal with the incremental aspect. An intensive experiment was conducted to show the efficiency of our proposal and to compare it with the most important existing studies. [ABSTRACT FROM PUBLISHER]

Discusses a study which proposed an approach to color image compression which involves the absolute moment block truncation coding (AMBTC) and the single bitmap generation scheme. Planes that compose a color image; Focus of AMBTC; Advantages and disadvantages of the use of AMBTC; Process of using two-layer absolute moment block truncation coding.

Personal workstations with bitmap displays and window systems are becoming a widely used computing tool. This article describes some of the capabilities of an experimental package for drawing scatterplots and histograms that has been implemented on such a workstation. An example illustrates how those capabilities can be used in the graphical analysis of a data set. [ABSTRACT FROM AUTHOR]

The article focuses on issues relating to quality and quantity in the visual arts. It talks about advancements in technology which involves the capture, storage, transmission and analysis of images. Machines such as scanners, optical disks, optical fibers and bit-mapped screens have been useful in these processes. The compression of data in order to take advantage of certain regularities in a digitized image is discussed. The article also discusses systematic ways of processing digitized images.