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An innovative and simple design for a weaving loom was proposed to simplify the pattern design and the decoding process of weaving. Using the structural analysis of the existing looms and based on the concepts of weaving, a creative open-type rigid heald was developed to replace the traditional one and generate warp shedding. Corresponding to the raster graphics of the designed pattern, the heald shape had convex–concave features to control warping in shedding. The pattern design was integrated into the heald design using mechanical coding. [ABSTRACT FROM AUTHOR]

This paper proposes a method for changing pixel shape by converting a CMYK raster image (pixel) to an HSB vector image, replacing the square cells of the CMYK pixels with different vector shapes. The replacement of a pixel by the selected vector shape is done depending on the detected color values for each pixel. The CMYK values are first converted to the corresponding RGB values and then to the HSB system, and the vector shape is selected based on the obtained hue values. The vector shape is drawn in the defined space, according to the row and column matrix of the pixels of the original CMYK image. Twenty-one vector shapes are introduced to replace the pixels depending on the hue. The pixels of each hue are replaced by a different shape. The application of this conversion has its greatest value in the creation of security graphics for printed documents and the individualization of digital artwork by creating structured patterns based on the hue. [ABSTRACT FROM AUTHOR]

Today, the objective of applying shadow theory to architectural drawing is usually to obtain one (or several) bitmap images. This a priori innocuous fact leads to vector images being conspicuous by their absence when lighting factors come into play during the modelling and parametric design of architecture and its environment. The present article sets out a methodology to calculate shadows by placing vector drawing not only at the heart of the process but also of the obtained results. We found that in today's context of university excellence, it is essential to apply knowledge, control, as well as possible editing and postproduction of the effects generated by rendering process lighting calculations. Such interventions are also generally useful and effective in our profession. [ABSTRACT FROM AUTHOR]

In this paper, we present two approaches for recording a quasi-hologram on the steel surface by femtosecond laser pulses. The recording process is done by rotating the polarization of the laser beam by a half-wave plate or a spatial light modulator (SLM), so we can control the spatial orientation of the formed laser-induced periodic surface structures (LIPSS). Two different approaches are shown, which use vector and bitmap images to record the hologram. For the first time to our knowledge, we managed to record a hologram of a bitmap image by continuously adjusting the laser beam polarization by SLM during scanning. The developed method can substantially improve hologram recording technology by eliminating complex processing procedures, which can lead to increasing the fabrication speed and reducing the cost. [ABSTRACT FROM AUTHOR]

There is growing interest in voxelated matter that is designed and fabricated voxel by voxel.sup.1-4. Currently, inkjet-based three-dimensional (3D) printing is the only widely adopted method that is capable of creating 3D voxelated materials with high precision.sup.1-4, but the physics of droplet formation requires the use of low-viscosity inks to ensure successful printing.sup.5. By contrast, direct ink writing, an extrusion-based 3D printing method, is capable of patterning a much broader range of materials.sup.6-13. However, it is difficult to generate multimaterial voxelated matter by extruding monolithic cylindrical filaments in a layer-by-layer manner. Here we report the design and fabrication of voxelated soft matter using multimaterial multinozzle 3D (MM3D) printing, in which the composition, function and structure of the materials are programmed at the voxel scale. Our MM3D printheads exploit the diode-like behaviour that arises when multiple viscoelastic materials converge at a junction to enable seamless, high-frequency switching between up to eight different materials to create voxels with a volume approaching that of the nozzle diameter cubed. As exemplars, we fabricate a Miura origami pattern.sup.14 and a millipede-like soft robot that locomotes by co-printing multiple epoxy and silicone elastomer inks of stiffness varying by several orders of magnitude. Our method substantially broadens the palette of voxelated materials that can be designed and manufactured in complex motifs. Voxelated soft matter is designed and fabricated using multimaterial multinozzle three-dimensional printing, which switches between different viscoelastic inks along the same print filament to print multiple materials simultaneously., Author(s): Mark A. Skylar-Scott [sup.1] [sup.2] , Jochen Mueller [sup.1] [sup.2] , Claas W. Visser [sup.1] [sup.2] , Jennifer A. Lewis [sup.1] [sup.2] Author Affiliations: (1) Harvard John A. Paulson [...]

Glaciers depicted on old maps reveal their historical extents, before the advent of aerial and satellite remote sensing. Digital glacier inventories produced from these maps can be employed in assessments of centennial-scale glacier change. This study reconstructs the ~1899 (covering the period 1882–1916) glacier extent in Nordland, northern Norway, from historical gradteigskart maps, with an emphasis on examining the accuracy of the mapped glaciers. Glacier outlines were digitised from georectified scans of the analogue maps in a raster graphics editor and were subsequently inventoried in a GIS. The accuracy of the historical glacier extent was established from written descriptions and landscape photographs created during the original field surveys, and further validated against independent glacier outlines of (1) the maximum Little Ice Age extent derived from geomorphological evidence, and (2) the 1945 extent derived from vertical aerial photographs. An overall uncertainty of ±17% is associated with our inventory. Nordland's glaciers covered an area of 1712 ± 291 km2 in 1899. By 2000, total ice cover had decreased by 47% (807 ± 137 km2) at a rate of 6% 10 a−1 (80 ± 14 km2 10 a−1). The approach presented here may serve as a blueprint for future studies intending to derive glacier inventories from historical maps. [ABSTRACT FROM AUTHOR]

We report the preliminary results of a meta-analysis conducted to examine possible biases in the uncertainty values published in papers by ATLAS and CMS experiments. We have performed this analysis using two independent techniques: a vectoral analysis of the vector graphics files and a bitmap analysis of the raster graphic files of the exclusion plots from various physics searches. In both procedures, the aim is to compute the percentages of the data points scattered within 1σ and 2σ bands of the plots and verify whether the measured percentages agree with statistical norms, assuming unbiased estimations of the uncertainties. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Technology & Information Education is the property of Palacky University in Olomouc and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper describes the collection of a large dataset (6930 measurements) on dimensional error in the fused deposition modeling (FDM) additive manufacturing process for full-density parts. Three different print orientations were studied, as well as seven raster angles (0°, 15°, 30°, 45°, 60°, 75°, and 90°) for the rectilinear infill pattern. All measurements were replicated ten times on ten different samples to ensure a comprehensive dataset. Eleven polymer materials were considered: acrylonitrile butadiene styrene (ABS), polylactic acid (PLA), high-temperature PLA, wood-composite PLA, carbon-fiber-composite PLA, copper-composite PLA, aluminum-composite PLA, high-impact polystyrene (HIPS), polyethylene terephthalate glycol-enhanced (PETG), polycarbonate, and synthetic polyamide (nylon). The samples were ASTM-standard impact-testing samples, since this geometry allows the measurement of error on three different scales; the nominal dimensions were 3.25mmthick, 63.5 mm long, and 12.7 mm wide. This dataset is intended to give engineers and product designers a basis for judging the accuracy and repeatability of the FDM process for use in manufacturing of end-user products. [ABSTRACT FROM AUTHOR]

Bitmap-based indexes are known to be the most effective indexing method for retrieving and answering selective queries in a read-only environment. Various types of encoding bitmap indexes significantly improve query time efficiency by utilizing fast Boolean operations directly on the index before retrieving the raw data. In particular, the dual bitmap index improves the performance of equality queries in terms of the space vs. time trade-off. However, the performance of range queries is unsatisfactory. In this paper, an optimizing algorithm is proposed to improve the range query processing for the dual bitmap index. The results of the experiment conducted show that the proposed algorithm, called Dual-simRQ, reduces the number of bitmap vectors scanned and the Boolean operations performed, which impacts the overall performance for range query processing. [ABSTRACT FROM AUTHOR]

Novel fault leveling techniques based on address remapping (AR) are proposed in this paper. We can change the logical-to-physical address mapping of the page buffer such that faulty cells within a flash page can be evenly distributed into different codewords. Therefore, the adopted ECC scheme can correct them effectively. Based on the production test or on-line BIST results, the fault bitmap can be used for executing the heuristic fault leveling analysis (FLA) algorithm and evaluating control words used to steer fault leveling. A new page buffer architecture suitable for address remapping is also proposed. According to experimental results, repair rate, yield, and reliability can be improved significantly with negligible hardware overhead. [ABSTRACT FROM AUTHOR]

Scalability is a key issue in datacenter multicast as it needs to support a large number of groups in commodity switches with limited fast memory. Previous in-packet Bloom filter-based datacenter multicast schemes have been proposed to address the scalability issue. They encode a multicast tree in a Bloom filter carried in each packet. However, these schemes induce high bandwidth overhead due to the false positives inherent in Bloom filters, and cannot scale well to the increasing variety of group sizes. In this paper, we propose an in-packet bitmap-based approach towards scalable datacenter multicast, improving the bandwidth efficiency. We use a bitmap to encode switch ports of a multicast tree in the packet header, eliminating false positive forwarding. In addition, we use a clustered Golomb coding method to compress in-packet bitmaps for further reducing the bandwidth overhead. Experimental results on simulations and a Click-based switch prototype demonstrate that our scheme achieves up to several orders of magnitude reductions in bandwidth overhead compared to previous schemes. [ABSTRACT FROM AUTHOR]

Raster map viewers can be used by various entities, including public administration units. They are used in particular when there is no economic justification for creating extended and comprehensive mapping services, or when there is a need to quickly publish the given map. These viewers can be made using one of many available components. However, not all of them are optimal for such applications. Selected raster map viewers may be inefficient, which may make it difficult or even impossible to view the map. The aim of the present work was to conduct a comparative analysis of the performance of selected raster map viewers. The prototype applications were used to test the implementation of selected designing tools. The efficiency measurement was made using tools for test automation. The value of the ESSCORE (Estimated Speed Score) synthetic performance meta-index has been determined. It has been shown that the application created with the use of the ImageViewer component (jQuery JavaScript) was objectively the best of the tests tested for the presentation of raster graphics (according to the adopted testing scheme). [ABSTRACT FROM AUTHOR]

Computer architectures have evolved into parallel and heterogeneous systems with multi-core CPUs, many-core GPUs, and vector instructions. Meanwhile, advances in data collection technologies have led to a rapid increase in the spatial and temporal resolution of geographic data. Efficiently dealing with large volumes of geographic data demands, now more than ever, an effective use of modern parallel computers. However, parallel programming is distinctly more challenging than writing sequential scripts. Moreover, parallelism is not the only issue; data locality is critical, too. This work addresses the issues of data escalation and parallel transition using a compiler approach to map algebra. More specifically, we design and implement a framework that uses compiler techniques to automatically speed up raster spatial analysis. In this way, users simply write sequential map algebra scripts in Python, which are translated into a graph where optimizations are applied. Then the scripts are parallelized, reordered for locality, and executed on OpenCL devices such as multi-core CPUs and GPUs. The novelty of our approach resides in the efficient organization of the execution, which we achieve via compilation. Unlike interpreters, our framework reorders the raster operations to maximize data reuse and minimize memory movements. The reordering occurs at two hierarchical levels and is controlled by a scheduler and a fusion technique. This strategy targets data locality, which, as we show, is key to the performance of raster spatial analysis. The experiments report speed-ups of one to two orders of magnitude compared to traditional interpreters. [ABSTRACT FROM AUTHOR]

We introduce a graphical method originating from the computer graphics domain that is used for the arbitrary placement of cells over a two-dimensional manifold. Using a bitmap image whose luminance provides cell density, this method guarantees a discrete distribution of the positions of the cells respecting the local density. This method scales to any number of cells, allows one to specify arbitrary enclosing shapes and provides a scalable and versatile alternative to the more classical assumption of a uniform spatial distribution. The method is illustrated on a discrete homogeneous neural field, on the distribution of cones and rods in the retina and on the neural density of a flattened piece of cortex. [ABSTRACT FROM AUTHOR]

Recognition of objects in pictures and movies requires the use of techniques, such as filtering, segmentation and classification. Image filtering is required to remove all artifacts that hinder the unequivocal identification and sharpen interesting objects. Segmentation refers to finding areas of images respected to individual objects. For the selected areas corresponding to objects in the selected picture, the classification of objects finally gives information about the type of object which orientation is made. This paper presents a method for the classification of objects from drawings as a bitmap using the method of fundamental solutions (MFS). The MFS was tested on the selected bitmap depicting simple geometric shapes. The correlations between errors occurring on the boundary for particular shapes are used for the selection of geometric shape figures. Due to this correlation, it is possible to recognize the shape of the image appearing on the drawing by an analysis consisting of the comparison of recognized points describing the shape of contour to a database containing solutions of boundary value problems for the selected shape. In one way, the comparison of the pattern can determine which shape from database it is most similar to in terms of contour. This article appear that this approach is very simple and clearly. In result, this method can be used to recognition of the objects in the systems of real-time processing. [ABSTRACT FROM AUTHOR]

We consider two NP-hard open dimension nesting problems for which a set of items has to be packed without overlapping into a two-dimensional bin in order to minimize one or both dimensions of this bin. These problems are faced by real-life applications, such as textile, footwear and automotive industries. Therefore, there is a need for specialized systems to help in a decision making process. Bearing this in mind, we derive new concepts as the no-fit raster, which can be used to check overlapping between any two-dimensional generic-shaped items. We also use a biased random key genetic algorithm to determine the sequence in which items are packed. Once the sequence of items is determined, we propose two heuristics based on bottom-left moves and the no-fit raster concept, which are in turn used to arrange these items into the given bin observing the objective criteria. As far as we know, the problem with two-open dimensions is being solved for the first time in the context of nesting problems and we present the first whole quadratic model for this problem. Computational experiments conducted on benchmark instances from the literature (some from the textile industry and others including circles, convex, and non-convex polygons) show the competitiveness of the approaches developed as they were able to calculate the best results for 74.14% of the instances. It can be observed that these results show new directions in terms of solving nesting problems whereby approaches can be coupled in existing intelligent systems to support decision makers in this field. [ABSTRACT FROM AUTHOR]

Due to the rapid development of the Internet of Things (IoT), many feasible deployments of sensor monitoring networks have been made to capture the events in physical world, such as human diseases, weather disasters and traffic accidents, which generate large-scale temporal data. Generally, the certain time interval that results in the highest incidence of a severe event has significance for society. For example, there exists an interval that covers the maximum number of people who have the same unusual symptoms, and knowing this interval can help doctors to locate the reason behind this phenomenon. As far as we know, there is no approach available for solving this problem efficiently. In this paper, we propose the Bitmap-based Maximum Range Counting (BMRC) approach for temporal data generated in sensor monitoring networks. Since sensor nodes can update their temporal data at high frequency, we present a scalable strategy to support the real-time insert and delete operations. The experimental results show that the BMRC outperforms the baseline algorithm in terms of efficiency. [ABSTRACT FROM AUTHOR]

Open access geospatial data represent a range of metrics relevant to global human population mapping at fine spatial scales. Detailed and contemporary spatial datasets that accurately describe population distributions are vital in order to measure impacts of population growth, monitor change, and plan interventions. To construct such datasets the harmonisation of geospatial data layers is a prerequisite because layer specifications differ widely. To this end the WorldPop Project is producing an open access archive of 3 and 30 arc-second (~100m and ~1km, respectively) resolution gridded data in a predominantly open source environment, using OSGEO4W utilities. Five tiled raster datasets form the basis of the archive: (i) Viewfinder Panoramas topography clipped to CIESIN national level administrative coastlines; (ii) a matching ISO 3166 country identification grid; (iii) country area; (iv) pixel area; (v) and slope layer. Further layers will include transport networks, landcover, urban extent, nightlights, climate, travel time to major cities, forest stand change, livestock densities, vegetation indices, and waterways. We here describe the base datasets and the production methodology in development. The alpha version of the archive can be downloaded both from the WorldPop Dataverse Repository and the WorldPop Project website. The improved and expanded beta version of the archive is in development for release next year, and will offer significantly improved standardisation of country boundaries, and inland water boundaries (forthcoming), to global census unit data. [ABSTRACT FROM AUTHOR]

Among cartographic works, three-dimensional panoramas should be marked out as a special kind of map, which are characterised by visual modes of representing objects in space. The main principles of the creation of both hand-painted and automated maps vector and raster graphics software (Corel Draw and Adobe Photoshop) are considered in the paper. The use of modern information technologies has several advantages over traditional mapping. [ABSTRACT FROM AUTHOR]

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]

Intuition from our everyday lives gives rise to the belief that information exchanged between remote parties is carried by physical particles. Surprisingly, in a recent theoretical study [Salih H, Li ZH, Al-Amri M, Zubairy MS (2013) Phys Rev Lett 110:170502], quantum mechanics was found to allow for communication, even without the actual transmission of physical particles. From the viewpoint of communication, this mystery stems from a (nonintuitive) fundamental concept in quantum mechanics—wave-particle duality. All particles can be described fully by wave functions. To determine whether light appears in a channel, one refers to the amplitude of its wave function. However, in counterfactual communication, information is carried by the phase part of the wave function. Using a single-photon source, we experimentally demonstrate the counterfactual communication and successfully transfer a monochrome bitmap from one location to another by using a nested version of the quantum Zeno effect. [ABSTRACT FROM AUTHOR]

Landscape researchers have described different options for landscape classifications and have suggested the approximate size of landscape units for various scale levels of study and the most suitable data layers (representing biophysical characteristics) for differentiating them. The literature already contains examples of evaluating data layers with regard to their information value, their correlation with one another, and so on, but less research has been done on the suitability of data layers from the perspective of the scale of landscape research. The objective of this paper is to propose a quantitative method to assess different data layers by landscape classification scale. The proposed method is based on systematic sequential multilevel division of the study area, calculating the average moderate coefficient of variation for each scale level, and comparing calculations between scale levels. It can be used to objectively determine which raster data layers are more suitable for defining large landscape units and which are more suitable for defining small ones. We tested the method for Slovenia, a small country at the junction of the Alps, Pannonian Basin, Mediterranean, and Dinaric Alps with a high landscape diversity. To test the method, we systematically divided the country into smaller units using ten differently structured grids (for the case of Slovenia, we used squares with a baseline of 1, 10, 20 km, and so on up to 100 km). For each data layer, we calculated the average moderate coefficient of variation for each division and compared it with the average coefficient of variation for the highest level, which represented the country as one whole unit. The ratios allowed us to classify the data layers into categories and assess which data layers are more important in landscape classification at a small scale, which ones are more important at a large scale, and which ones function as noise. As expected, variation diminishes with a smaller baseline in all cases, but the gradient of decreasing variation is different. We also studied the categorization of data layers using a hierarchical classification method. Following to the proposed method, it is possible to create various categories of data layers by the landscape classification scale for a certain area. The method can be used for any area and is an option for reducing subjectivity in selecting data layers for landscape analysis classification for the most general purposes (e.g., production of landscape classifications for education). [ABSTRACT FROM AUTHOR]

Geospatial transformations in the form of reprojection calculations for large datasets can be computationally intensive; as such, finding better, less expensive ways of achieving these computations is desired. In this paper, we report our efforts in developing a Compute Unified Device Architecture (CUDA)-based parallel algorithm to perform map reprojections for raster datasets on personal computers using Graphics Processing Units (GPUs). This algorithm has two unique features: a) an output-space-based parallel processing strategy to handle transformations more rigorously, and b) a chunk-based data decomposition method for projected space in conjunction with an on-the-fly data retrieval mechanism to avoid memory overflow. To demonstrate the performance of our CUDA-based map reprojection approaches, we have conducted tests between this method and the traditional serial version using the Central Processing Unit (CPU). The results show that speedup ratios range from 10 times to 100 times in all test scenarios. The lessons learned from the tests are summarized. [ABSTRACT FROM AUTHOR]

Summary The graphical fragment assembly (GFA) formats are emerging standard formats for the representation of sequence graphs. Although GFA 1 was primarily targeting assembly graphs, the newer GFA 2 format introduces several features, which makes it suitable for representing other kinds of information, such as scaffolding graphs, variation graphs, alignment graphs and colored metagenomic graphs. Here, we present GfaViz , an interactive graphical tool for the visualization of sequence graphs in GFA format. The software supports all new features of GFA 2 and introduces conventions for their visualization. The user can choose between two different layouts and multiple styles for representing single elements or groups. All customizations can be stored in custom tags of the GFA format itself, without requiring external configuration files. Stylesheets are supported for storing standard configuration options for groups of files. The visualizations can be exported to raster and vector graphics formats. A command line interface allows for batch generation of images. Availability and implementation GfaViz is available at https://github.com/ggonnella/gfaviz Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

The problem of caching shortest paths has been widely studied. All of existing methods that address this problem assume that the condition of road networks does not change with time. In this paper, we study how to refresh a cache when one edge of the underlying road network (graph) changes. A bitmap-based cache structure is proposed to store and give access to shortest paths. In the following, algorithms are developed to detect shortest paths that are affected by the change of edge. After detecting affected paths, several heuristic-based refreshment strategies are proposed to update the cache. We have conducted a series of experiments to compare the performance of proposed strategies. It shows that replacing affected shortest paths with new paths whose benefit values are the largest should be applied in the shortest path caching applications such as navigation and map services. [ABSTRACT FROM AUTHOR]

Background. Standard anthropometric methods applied to measurements of the skull differentials are laden with mistakes stemming from the way the measuring devices are built and from a lack of experience on the part of the researchers. To increase objectivity, digital imaging measurements via computer systems were introduced. Objectives. The aim of this research was to assess the asymmetry of the male and female orbit with the application of the new graphic methods: raster graphics and vector graphics. Material and methods. The examination was conducted on 184 well-preserved skulls. The photos were taken by a digital camera with high definition. Orbit asymmetry was examined by determining the distance between the centers of gravity of both orbits and the frontal median line d1 and d2. Then angles α and β were appointed. They are defined as angles between the line that runs through craniometrical points mf and ek on the right side (angle α) and on the left side (angle β), and the frontal median line at their crossing point. Distances r2 and r1, which are allocated points between the frontal median lines (LPP), were also set. Results. Angles α and β were also analyzed while comparing the skulls of both genders. Statistically significant differences were only observed in male skulls. However, differences for both genders were noted in parameters d1 and d2. No statistically significant differences were discovered between men and women for parameters r1 and r2. The groups of women and men were merged, being treated as a population; which resulted in the conclusion that there are no statistically significant differences between these parameters. Conclusions. The skull's asymmetry connected to gender and the asymmetry of the right and left sides of examined craniums can be used in criminal examinations as well as in facial reconstructive surgeries. [ABSTRACT FROM AUTHOR]

This paper presents a method for automatically constructing irregular floor plans. Given image patterns, the program produces a variety of layouts that satisfy users' geometric and topological requirements. The program extracts irregular regions from images via statistical region merging. It employs subgraph matching and simulated annealing to construct topologically feasible layouts. Methods for measuring similarities between the desired templates and irregular rooms are also reported. Applications using raster images and vector graphics are tested. Both applications generate feasible floor plans whose appearances resemble the input patterns. The results indicate that layout automation is valid without an orthogonal framework in the plane. Irregular layout synthesis allows architects to instantly implement visual preferences in early design stages. [ABSTRACT FROM AUTHOR]

Big data are visually cluttered by overlapping data points. Rather than removing, reducing or reformulating overlap, we propose a simple, effective and powerful technique for density cluster generation and visualization, where point marker (graphical symbol of a data point) overlap is exploited in an additive fashion in order to obtain bitmap data summaries in which clusters can be identified visually, aided by automatically generated contour lines. In the proposed method, the plotting area is a bitmap and the marker is a shape of more than one pixel. As the markers overlap, the red, green and blue (RGB) colour values of pixels in the shared region are added. Thus, a pixel of a 24-bit RGB bitmap can code up to 224 (over 1.6 million) overlaps. A higher number of overlaps at the same location makes the colour of this area identical, which can be identified by the naked eye. A bitmap is a matrix of colour values that can be represented as integers. The proposed method updates this matrix while adding new points. Thus, this matrix can be considered as an up-to-time knowledge unit of processed data. Results show cluster generation, cluster identification, missing and out-of-range data visualization, and outlier detection capability of the newly proposed method. [ABSTRACT FROM AUTHOR]

Bitmap indexes are commonly used in data warehousing applications such as on-line analytic processing (OLAP). Storing the bitmaps in compressed form has been shown to be effective not only for low cardinality attributes, as conventional wisdom would suggest, but also for high cardinality attributes. Compressed bitmap indexes, such as Byte - aligned Bitmap Compression (BBC), Word - Aligned Hybrid (WAH) and several of their variants have been shown to be efficient in terms of both time and space, compared to traditional database indexes. In this paper, we propose a new technique for compressed bitmap indexing, called Super Byte - aligned Hybrid (SBH) bitmap compression, which improves upon the current state-of-the-art compression schemes. In our empirical evaluation, the query processing time of SBH was about five times faster than that of WAH, while the size of its compressed bitmap indexes was retained nearly close to that of BBC. [ABSTRACT FROM AUTHOR]

This paper uses raster scan line as the basic describing unit of point, line and polygon. The definition of seven basic topological relations of raster scan line, formalized definition of topological relations for geometric objects like point, line and polygon are given in the paper. And the line-by-line calculation flow based on topological relations of raster scan line is designed. The test indicates that this method is suitable for collection objects of point, line and polygon and has higher computational efficiency. [ABSTRACT FROM AUTHOR]

The choice of the proper resolution in landslide susceptibility mapping is a worth considering issue. If, on the one hand, a coarse spatial resolution may describe the terrain morphologic properties with low accuracy, on the other hand, at very fine resolutions, some of the DEM-derived morphometric factors may hold an excess of details. Moreover, the landslide inventory maps are represented throughout geospatial vector data structure, therefore a conversion procedure vector-to-raster is required. This work investigates the effects of raster resolution on the susceptibility mapping in conjunction with the use of different algorithms of vector-raster conversion. The Artificial Neural Network technique is used to carry out such analyses on two Sicilian basins. Seven resolutions and three conversion algorithms are investigated. Results indicate that the finest resolutions do not lead to the highest model performances, whereas the algorithm of conversion data may significantly affect the ANN training procedure at coarse resolutions. [ABSTRACT FROM AUTHOR]

Virtualization provides the function of saving the entire status of the execution environment of a running virtual machine (VM), which makes checkpointing flexible and practical for HPC servers or data center servers. However, the system-level checkpointing needs to save a large number of data to the disk. Moreover, the overhead grows linearly with the increasing size of virtual machine memory, which leads to disk I/O consumption disaster along with poor system scalability. To target this, we propose a novel fast VM checkpointing approach, named Fast Incremental checkpoinTing with Delta memOry Compression (FITDOC). By studying the run-time memory characteristics of different workloads, FITDOC counts the dirty pages in a fine-granularity manner (i.e., the number of 8 bytes), instead of in the conventional method (i.e., the number of pages). FITDOC utilises a dirty page logging mechanism to record the dirty pages. Accordingly, a delta memory compression mechanism is implemented to eliminate redundant memory data in checkpointing files. To locate the dirty data in dirty pages, FITDOC utilizes two mechanisms: by analyzing the distribution characteristics of dirty pages in the dirty bitmap, we propose a fast dirty bitmap scanning method to locate the dirty pages, and take a multi-threading data comparison mechanism to locate the real dirty data in one page. The experimental results show that compared with Xen's default system-level checkpointing algorithm, FITDOC can on average reduce checkpointing time 70.54 % with a 1 GB memory size and achieve better improvement for VMs with larger memory configurations. FITDOC can reduce the size of checkpointing data 52.88 % on average compared with Remus's incremental solution, which is in page granularity. Compared with the default dirty bitmap scanning method in Xen, the scanning time of FITDOC is decreased by 91.13 % on average. [ABSTRACT FROM AUTHOR]

Developing and exploiting flexible techniques for optimizing the evaluation of queries over loosely structured data (e.g. tree or graph databases) is of crucial importance for modern database applications. In this context, we consider a new type of views which can be materialized as compressed bitmaps over tree data. We introduce the concept of view structural template to define classes of views. We then define and address a novel view selection problem (called view class selection (VCS) problem) where the goal is to select classes of bitmap views in order to optimize the overall evaluation cost of all tree pattern queries (TPQs) that can be issued against a database while satisfying a space constraint and ensuring that all the TPQs can be answered using exclusively the materialized views. We show that the VCS problem is NP-hard and we design two heuristic greedy algorithms which iteratively generate new batches of candidate view classes and make them available for selection. Each algorithm uses a different view class expansion technique to enable the systematic generation of candidate view classes from classes with smaller templates. We run extensive experiments to evaluate both the effectiveness of the algorithms and their efficiency on real, benchmark and synthetic datasets. Our algorithms are able to suggest high quality selections of view classes in a reasonable amount of time. [ABSTRACT FROM AUTHOR]

Cloud computing systems handle large volumes of data by using almost unlimited computational resources, while spatial data warehouses (SDWs) are multidimensional databases that store huge volumes of both spatial data and conventional data. Cloud computing environments have been considered adequate to host voluminous databases, process analytical workloads and deliver database as a service, while spatial online analytical processing (spatial OLAP) queries issued over SDWs are intrinsically analytical. However, hosting a SDW in the cloud and processing spatial OLAP queries over such database impose novel obstacles. In this article, we introduce novel concepts as cloud SDW and spatial OLAP as a service, and afterwards detail the design of novel schemas for cloud SDW and spatial OLAP query processing over cloud SDW. Furthermore, we evaluate the performance to process spatial OLAP queries in cloud SDWs using our own query processor aided by a cloud spatial index. Moreover, we describe the cloud spatial bitmap index to improve the performance to process spatial OLAP queries in cloud SDWs, and assess it through an experimental evaluation. Results derived from our experiments revealed that such index was capable to reduce the query response time from 58.20 up to 98.89 %. [ABSTRACT FROM AUTHOR]

For the compression of color images, a common bitmap usually is generated to replace the three individual bitmaps that originate from block truncation coding (BTC) of the R, G and B channels. However, common bitmaps generated by some traditional schemes are not the best possible because they do not consider the minimized distortion of the entire color image. In this paper, we propose a near-optimized common bitmap scheme for BTC using Binary Ant Colony Optimization (BACO), producing a BACO-BTC scheme. First, the color image is compressed by the BTC algorithm to get three individual bitmaps, and three pairs of quantization values for the R, G, and B channels. Second, a near-optimized common bitmap is generated with minimized distortion of the entire color image based on the idea of BACO. Finally, the color image is reconstructed easily by the corresponding quantization values according to the common bitmap. The experimental results confirmed that reconstructed image of the proposed scheme has better visual quality and less computational complexity than the referenced schemes. [ABSTRACT FROM AUTHOR]

We propose here an efficient algorithm for high-level vectorization of scanned images of mechanical engineering drawings. The algorithm is marked by several novel features, which merit its superiority over the existing techniques. After preprocessing and necessary refinement of junction points in the image skeleton, it first extracts the graphic primitives, such as lines, circles, and arcs, based on certain digital geometric properties of straightness and circularity in the discrete domain. The primitives are classified into different types with all associated details based on fast and efficient geometric analysis. The vector set is succinctly reduced by such classification in tandem with further consolidation to make out meaningful objects like rectangles and annuli, together with hatching information. Exhaustive testing shows the efficiency of the algorithm and also its robustness and stability toward any affine transformation and injected noise. Easy reconstruction to scalable vector graphics demonstrates its readiness and usability as a state-of-the-art solution. [ABSTRACT FROM AUTHOR]

This paper presents an important step towards the standardization of research works on Optical Character Recognition in Persian language. It describes the formations of a standard handwritten database, including isolated digits, isolated signs, multi-digit numbers, numerical strings, courtesy amounts, and postal codes. In this regard, binary images of 72,180 samples were extracted from the designed forms. These forms were filled by 180 writers selected from different ages, genders, and jobs. Then these forms were scanned at 300 dpi with a high-speed scanner. Finally, forms are segmented into samples and are stored in bitmap format. This database is named PHOND, Persian Handwritten Optical Numbers & Digits, and it is available to the research community. Comparisons with the previous related databases illustrate the advantages of PHOND against other databases. Different experiments are done using PHOND database and the results are compared with other research works in handwritten recognition. [ABSTRACT FROM AUTHOR]

Frame aggregation is one of the IEEE802.11n wireless networks features. In frame aggregation multiple frames are combined and then sent. However sending a large number of frames in one aggregation frame in an error-prone environment will result in massive frame loss and retransmission. Thus a prior knowledge about the state of the channel will help in selecting the proper aggregation size that would utilize the channel bandwidth and improve the system performance. In this paper, we introduce an algorithm that adjusts the aggregation size based on the ACK bitmap without adding any extra headers or messages for determining the network conditions. Simulation results show that the Acknowledgment Bitmap can be used as an indicator of the network conditions to create adaptive frame aggregation schemes. [ABSTRACT FROM AUTHOR]

Due to the advancement in cloud computing technology, the research on database outsourcing has been actively done. In database outsourcing, because a service provider might be untrusted or compromised, two issues of data security emerge: data confidentiality and data integrity. Many data transformation schemes were widely studied for preserving data confidentiality, but they are vulnerable to data leakage problem because they do not consider data distribution when encrypting original data. Meanwhile, several query authentication schemes were proposed to verity data integrity, but they suffer from transmission overhead of verification data. In this paper, we propose a privacy-aware data transformation and a query authentication scheme which guarantees the data confidentiality and the query result integrity of sensitive data. To solve the original data leakage problem, we propose a bitmap-based data transformation scheme with anchor selection based on data distribution. We also devise an algebraic coding-based hash index that transforms a query to a bitmap and retrieves the anchor information efficiently. To reduce the transmission overhead of verification data, we propose a query result authentication index that stores an encrypted signature for each anchor, which is an concatenated hash digest of cluster data. Through performance evaluation, we show that our scheme outperforms the existing method up to 15 times, in terms of query processing time and verification overhead. [ABSTRACT FROM AUTHOR]