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2009 | Buch

Transactions on Computational Science VI

herausgegeben von: Marina L. Gavrilova, C. J. Kenneth Tan

Verlag: Springer Berlin Heidelberg

Buchreihe : Lecture Notes in Computer Science

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SUCHEN

Über dieses Buch

The LNCS journal Transactions on Computational Science reflects recent developments in the field of Computational Science, conceiving the field not as a mere ancillary science but rather as an innovative approach supporting many other scientific disciplines. The journal focuses on original high-quality research in the realm of computational science in parallel and distributed environments, encompassing the facilitating theoretical foundations and the applications of large-scale computations and massive data processing. It addresses researchers and practitioners in areas ranging from aerospace to biochemistry, from electronics to geosciences, from mathematics to software architecture, presenting verifiable computational methods, findings and solutions and enabling industrial users to apply techniques of leading-edge, large-scale, high performance computational methods.

The sixth volume of the Transactions on Computational Science journal contains the thoroughly refereed best papers selected from the International Conference on Computational Science and Its Applications, ICCSA 2008. All 21 papers included in the issue have been significantly revised and extended following the event. The journal has been divided into two parts. The 11 papers in Part 1 are devoted to the theme of information systems and communications and the 10 papers in Part 2 focus on geographical analysis and geometric modeling.

Inhaltsverzeichnis

Frontmatter

Part 1: Information Systems and Communications

Volterra – Lax-Wendroff Algorithm for Modelling Sea Surface Flow Pattern from Jason-1 Satellite Altimeter Data
Abstract
This paper introduces a modified formula for geostrophic current. The method is based on utilization of the Volterra series expansion in the geostrophic current equation. The purpose of this method is to transform the time series JASON-1 satellite altimeter data into a real ocean surface current. Then, the Volterra kernel inversion used to acquire the sea surface current velocity. In doing so, the finite element model of Lax-Wendorff scheme used to determine the spatial variation of current flow. The results show that the new formula of geostrophic current is able to avoid the impact of Coriolis and geoid parameters. The second-order Volterra kernel illustrates an error standard deviation of 0.03, thus performing a better estimation of flow pattern as compared to first-order Volterra kernel. We conclude that modeling of sea surface current by using JASON-1 satellite altimeter data can be operationalized by using the new formula for geostrophic current.
Maged Marghany
Guidelines for Web Usability and Accessibility on the Nintendo Wii
Abstract
The aim of the present study is to propose a set of guidelines for designing Internet web sites usable and accessible with the Nintendo Wii console. After an accurate analysis of usability issues and of the typical Wii Internet users, twelve usability guidelines will be proposed. These guidelines are focused on visibility, understandability, clickability and compatibility. We then restructured a sample web site according to the guidelines. To prove their effectiveness, we performed the usability tests on a sample of forty individuals, selected among the various categories of potential users of the Nintendo Wii console, after having visited the restructured and the original web sites. The analysis of the resulting information confirmed that the restructured web site is more usable than the original and the improvement is more pronounced for weak categories (elderly and individuals with no experience with web browsing). Furthermore the adoption of the guidelines reduces the difficulties experienced by users with different expertise, in visiting a web site with the Wii console.
Valentina Franzoni, Osvaldo Gervasi
Improving Urban Land Cover Classification Using Fuzzy Image Segmentation
Abstract
The increasing availability of high spatial resolution images provides detailed and up-to-date representations of cities. However, ana-lysis of such digital imagery data using traditional pixel-wise approaches remains a challenge due to the spectral complexity of urban areas. Object-Based Image Analysis (OBIA) is emerging as an alternative method to produce landcover information. Standard OBIA approaches rely on ima-ge segmentation which partitions the image into a set of ’crisp’ non-overlapping image-objects. This step regularly requires significant user-interaction to parameterise a functional segmentation model. This paper proposes fuzzy image segmentation which produces fully overlapping image-regions with indeterminate boundaries that serves as alternative framework for the subsequent image classification. The new method uses three stages: (i) fuzzy image segmentation, (ii) feature analysis, and (iii) defuzzification, that were implemented applying Support Vector Machine (SVM) techniques and using open source software. The new method was tested against a benchmark land-cover classification that applied standard crisp image segmentation. Results show that fuzzy image segmentation can produce good thematic accuracy with little user input. It therefore provides a new and automated technique for producing accurate urban land cover data from high spatial resolution imagery.
Ivan Lizarazo, Paul Elsner
Connecting the Dots: Constructing Spatiotemporal Episodes from Events Schemas
Abstract
This paper introduces a novel framework for deriving and mining high–level spatiotemporal process models in in-situ sensor measurements. The proposed framework is comprised of two complementary components, namely, hierarchical event schemas and spatiotemporal episodes. Event schemas are used in this work as the basic building model of spatiotemporal processes while episodes are used for organizing events in space and time in a consistent manner. The construction of event schemas is carried out using scale-space analysis from which the interval tree, a hierarchical decomposition of the data, is derived. Episodes are constructed from event schemas using by formulating the problem as a constraint network, in which spatial and temporal constraints are imposed. Consistency is achieved using a path–consistency algorithm. Once created, possible episodes can be derived from the network using a shortest–path search.
Arie Croitoru
Predictive Indexing for Position Data of Moving Objects in the Real World
Abstract
This paper describes a spatial-temporal indexing method for moving objects with a technique to predict future motion positions of moving objects. To build efficient index structure, we had an experiment to analyze practical moving objects, such as people walking in a hall. As the result, we found that any moving objects can be classified to just three types of motion characteristics; 1) staying, 2) straight moving, and 3) random walking. Indexing systems can predict accurate future positions of each object based on our found characteristics, moreover, the index structure can reduce the cost to update MBRs in spatial-temporal data structure. To show an advantage of our prediction method to previous works, we had an experiment to evaluate performance of each prediction method.
Yutaka Yanagisawa
SHWMP: A Secure Hybrid Wireless Mesh Protocol for IEEE 802.11s Wireless Mesh Networks
Abstract
In recent years, mesh networking has emerged as a key technology for the last mile Internet access and found to be an important area of research and deployment. The current draft standard of IEEE 802.11s has defined routing for Wireless Mesh Networks (WMNs) in layer-2 and is termed as Hybrid Wireless Mesh Protocol (HWMP). However, security in routing or forwarding functionality is not specified in the standard. As a consequence, HWMP in its current from is vulnerable to various types of routing attacks such as flooding, route disruption and diversion, spoofing etc. In this paper, we propose SHWMP, a secure HWMP protocol for WMN. The proposed protocol uses cryptographic extensions to provide authenticity and integrity of HWMP routing messages and prevents unauthorized manipulation of mutable fields in the routing information elements. We show via analysis that the proposed SHWMP successfully thwarts all the identified attacks. Through extensive ns-2 simulations, we show that SHWMP provides higher packet delivery ratio with little increase in end-to-end delay, path acquisition delay and control byte overhead.
Md. Shariful Islam, Md. Abdul Hamid, Choong Seon Hong
EDAS: Energy and Distance Aware Protocol Based on SPIN for Wireless Sensor Networks
Abstract
Energy-efficient is a challenge in designing effective dissemination protocols for Wireless Sensor Networks (WSNs). Several recent studies have been conducted in this area, and SPMS, which outperforms the well-known SPIN protocol, is a particularly representative protocol. One of the many characteristics of SPMS is its use of the shortest path to minimize energy consumption. However, since it repeatedly uses the same shortest path and, hence, reduces energy consumption, it is impossible to maximize the network lifetime. In this paper, a novel data dissemination protocol is proposed, called Energy and Distance Aware protocol based on SPIN (EDAS), which guarantees energy-efficient data transmission, as well as maximizing network lifetime. EDAS solves the network lifetime problem by taking account of both the residual energy and the most efficient distance between the nodes, to determine a path for data dissemination. Simulation results show that the EDAS guarantees energy-efficient transmission and moreover increases the network lifetime by approximately 69% than that of SPMS.
Jaewan Seo, Moonseong Kim, Hyunseung Choo, Matt W. Mutka
Scheme to Prevent Packet Loss during PMIPv6 Handover
Abstract
Mobile IPv6 (MIPv6) is a presentative protocol which supports global IP mobility. MIPv6 causes a long handover latency that a mobile node (MN) cannot send or receive packets. This latency can be reduced by using Proxy Mobile IPv6 (PMIPv6). PMIPv6 is a protocol which supports IP mobility without participation of the MN, and is studied in Network-based Localized Mobility Management (NETLMM) working group of IETF. There is much packet loss during handover in PMIPv6, although PMIPv6 reduces handover latency. In this paper, to reduce packet loss in PMIPv6 we propose Packet Lossless PMIPv6 (PL-PMIPv6) with authentication. In PL-PMIPv6 a previous mobile access gateway (pMAG) registers to a Local Mobility Anchor (LMA) on behalf of a new MAG (nMAG) during layer 2 handoff. Then, the nMAG buffers packets during handover after registration. Therefore, PL-PMIPv6 can reduce packet loss in MIPv6 and PMIPv6. Also, we use Authentication, Authorization and Accounting (AAA) infrastructure to authenticate the MN and to receive MN’s profiles securely. For the comparison with MIPv6 and PMIPv6, detailed performance evaluation is performed. From the evaluation results, we show that PL-PMIPv6 can achieve low handover latency and low total cost.
Seonggeun Ryu, Youngsong Mun
Wavelet Based Approach to Fractals and Fractal Signal Denoising
Abstract
In this paper localized fractals are studied by using harmonic wavelets. It will be shown that, harmonic wavelets are orthogonal to the Fourier basis. Starting from this, a method is defined for the decomposition of a suitable signal into the periodic and localized parts. For a given signal, the denoising will be done by simply performing a projection into the wavelet space of approximation. It is also shown that due to their self similarity property, a good approximation of fractals can be obtained by a very few instances of the wavelet series. Moreover, the reconstruction is independent on scale as it should be according to the scale invariance of fractals.
Carlo Cattani
Wavelet Analysis of Spike Train in the Fitzhugh Model
Abstract
This paper deals with the analysis of the wavelet coefficients for the nonlinear dynamical system which models the axons activity. A system with source made by a sequence of high pulses (spike train) is analyzed in dependence of the amplitude. The critical value of the amplitude, and a catastrophe are analyzed. The wavelet coefficients are computed and it is shown also that they are very sensitive to the local changes and can easily detect the spikes even on a nearly smooth function.
Carlo Cattani, Massimo Scalia
The Design and Implementation of Secure Socket SCTP
Abstract
This paper describes the design and implementation of secure socket SCTP (S2SCTP). S2SCTP is a new multi-layer, end-to-end security solution for SCTP. It uses the AUTH protocol extension of SCTP for integrity protection of both control and user messages; TLS is the proposed solution for authentication and key agreement; Data confidentiality is provided through encryption and decryption at the socket library layer. S2SCTP is designed to offer as much security differentiation support as possible using standardized solutions and mechanisms. In the paper, S2SCTP is also compared to SCTP over IPsec and TLS over SCTP in terms of packet protection, security differentiation, and message complexity. The following main conclusions can be draw from the comparison. S2SCTP compares favorably in terms of offered security differentiation and message overhead. Confidentiality protection of SCTP control information is, however, only offered by SCTP over IPsec.
Stefan Lindskog, Anna Brunstrom

Part 2: Geographical Analysis and Geometric Modeling

A General-Purpose Geosimulation Infrastructure for Spatial Decision Support
Abstract
In this paper we present the general-purpose simulation infrastructure MAGI, with features and computational strategies particularly relevant for strongly geo-spatially oriented simulations. Its main characteristics are (1) a comprehensive approach to geosimulation modelling, with a flexible underlying meta-model formally generalising a variety of types of models, both from the cellular automata and from the agent-based family of models, (2) tight interoperability between GIS and the modelling environment, (3) computationally efficiency and (4) user-friendliness. Both raster and vector representation of simulated entities are allowed and managed with efficiency, which is obtained through the integration of a geometry engine implementing a core set of operations on spatial data through robust geometric algorithms, and an efficient spatial indexing strategy for moving agents. We furthermore present three test-case applications to discuss its efficiency, to present a standard operational modelling workflow within the simulation environment and to briefly illustrate its look-and-feel.
Ivan Blecic, Arnaldo Cecchini, Giuseppe A. Trunfio
Exploratory Spatial Analysis of Illegal Oil Discharges Detected off Canada’s Pacific Coast
Abstract
In order to identify a model that best predicts spatial patterns it is necessary to first explore the spatial properties of the data that will be included in a predictive model. Exploratory analyses help determine whether or not important statistical assumptions are met, and potentially lead to the definition of spatial patterns that might exist in the data. Here, we present results from exploratory analyses based on data describing illegal oil spills detected by the National Aerial Surveillance Program (NASP) in Canada’s Pacific Region, and marine vessel traffic, the possible source of these oil discharges. We identify and describe spatial properties of the oil spills, surveillance flights and marine traffic, to ultimately identify the most suitable predictive model to map areas where these events are more likely to occur.
Norma Serra-Sogas, Patrick O’Hara, Rosaline Canessa, Stefania Bertazzon, Marina Gavrilova
Clustering and Hot Spot Detection in Socio-economic Spatio-temporal Data
Abstract
Distribution of socio-economic features in urban space is an important source of information for land and transportation planning. The metropolization phenomenon has changed the distribution of types of professions in space and has given birth to different spatial patterns that the urban planner must know in order to plan a sustainable city. Such distributions can be discovered by statistical and learning algorithms through different methods. In this paper, an unsupervised classification method and a cluster detection method are discussed and applied to analyze the socio-economic structure of Switzerland. The unsupervised classification method, based on Ward’s classification and self-organized maps, is used to classify the municipalities of the country and allows to reduce a highly-dimensional input information to interpret the socio-economic landscape. The cluster detection method, the spatial scan statistics, is used in a more specific manner in order to detect hot spots of certain types of service activities. The method is applied to the distribution services in the agglomeration of Lausanne. Results show the emergence of new centralities and can be analyzed in both transportation and social terms.
Devis Tuia, Christian Kaiser, Antonio Da Cunha, Mikhail Kanevski
Detecting Alluvial Fans Using Quantitative Roughness Characterization and Fuzzy Logic Analysis
Abstract
This research, based on a similarity geometric model, uses quantitative roughness characterization and fuzzy logic analysis to map alluvial fans. We choose to work in the Italian central Apennine intermountain basins because much human activities could mask this kind of landforms and because the timing of alluvial deposition is tied to land surface instabilities caused by regional climate changes. The main aim of the research is to understand where they form and where they extent in an effort to develop a new approach using the backscatter roughness parameters and primary attributes (elevation and curvature) derived from the SRTM DEM. Moreover, this study helps to provide a benchmark against which future alluvial fans detection using roughness and fuzzy logic analysis can be evaluated, meaning that sophisticated coupling of geomorphic and remote sensing processes can be attempted, in order to test for feedbacks between geomorphic processes and topography.
Andrea Taramelli, Laura Melelli
Evaluating the Use of Alternative Distance Metrics in Spatial Regression Analysis of Health Data: A Spatio-temporal Comparison
Abstract
A method is discussed to enhance the reliability of multivariate spatial regression analysis: alternative values of the Minkowski distance metric are used in the spatial weight matrix. The method is tested on an analysis of the association between heart disease incidence and a pool of socio-economic variables in Calgary over two consecutive census surveys. The method provides a reliable model, which can guide locational decisions to mitigate present and future disease incidence. The model is underpinned by a quantitative definition of neighbourhood connectivity throughout the city. Such connectivity, usually described by Euclidean distance, can be more effectively described by a specifically calibrated distance metric. The analytical results are meaningful, robust to neighbourhood size, and relatively constant over time. Owing to its effectiveness and simplicity, the procedure is generalizable to other health and socio-economic analysis. An automatic implementation is suggested, to assist in the definition of reliable spatial regression models.
Stefania Bertazzon, Scott Olson
Identifying Hazardous Road Locations: Hot Spots versus Hot Zones
Abstract
Traffic safety has become top priority for policy makers in most European countries. The first step is to identify hazardous locations. This can be carried out in many different ways, via (Bayesian) statistical models or by incorporating the spatial configuration by means of a local indicator of spatial association. In this paper, the structure of the underlying road network is taken into account by applying Moran’s I to identify hot spots. One step further than the pure identification of hazardous locations is a deeper investigation of these hot spots in a hot zone analysis. This extended analysis is important both theoretically in enriching the way of conceptualizing and identifying hazardous locations and practically in providing useful information for addressing traffic safety problems. The results are presented on highways in a province in Belgium and in an urban environment. They indicate that incorporating the hot zone methodology in a hot spot analysis reveals a clearer picture of the underlying hazardous road locations and, consequently, this may have an important impact on policy makers.
Elke Moons, Tom Brijs, Geert Wets
Geographical Analysis of Foreign Immigration and Spatial Patterns in Urban Areas: Density Estimation, Spatial Segregation and Diversity Analysis
Abstract
The paper is focused on the analysis of immigrant population and particularly on some of the characteristics of their spatial distribution in an urban environment. The attention is drawn on examining whenever there is a tendency to cluster in some parts of a city, with the risk of generating ethnic enclaves or ghettoes, therefore analysing also diversity other than the pure spatial distribution. Methods used in the past to measure segregation and other characteristics of immigrants have long been aspatial, therefore not considering relationships between people within a city. In this paper the attention is dedicated to methods to analyse the immigrant residential distribution spatially, with particular reference to density and diversity-based methods. The analysis is focused on the Municipality of Trieste (Italy) as a case study to test different methods for the analysis of immigration, and particularly to compare different indices, particularly traditional ones, as Location Quotients and the Index of Segregation, to different, spatial ones, based on Kernel Density Estimation functions, as the S index, and indices of diversity, as Shannon (SHDI) and Simpson (SIDI) ones as well as another diversity index proposed (IDiv). The different analysis and indices are performed and implemented in a GIS environment.
Giuseppe Borruso
Geostatistics in Historical Macroseismic Data Analysis
Abstract
This paper follows a geostatistical approach for the evaluation, modelling and visualization of the possible local interactions between natural components and built-up elements in seismic risk analysis. This method, applied to old town centre of Potenza hilltop town, offers a new point of view for civil protection planning using kernel density and autocorrelation indexes maps to analyse macroseismic damage scenarios and to evaluate the local geological, geomorphological and 1857 earthquake’s macroseismic data.
Maria Danese, Maurizio Lazzari, Beniamino Murgante
A Discrete Approach to Multiresolution Curves and Surfaces
Abstract
Subdivision surfaces have been widely adopted in modeling in part because they introduce a separation between the surface and the underlying basis functions. This separation allows for simple general-topology subdivision schemes. Multiresolution representations based on subdivision, however, incongruently return to continuous functional spaces in their construction and analysis. In this paper, we propose a discrete multiresolution framework applicable to many subdivision schemes and based only on the subdivision rules. Noting that a compact representation can only afford to store a subset of the detail information, our construction enforces a constraint between adjacent detail terms. In this way, all detail information is recoverable for reconstruction, and a decomposition approach is implied by the constraint. Our framework is demonstrated with case studies in Dyn-Levin-Gregory curves and Catmull-Clark surfaces, each of which our method produces results on par with earlier methods. It is further shown that our construction can be interpreted as biorthogonal wavelet systems.
Luke Olsen, Faramarz Samavati
On the Structure of Straight Skeletons
Abstract
For a planar straight line graph G, its straight skeleton S(G) can be partitioned into two subgraphs S c (G) and S r (G) traced out by the convex and by the reflex vertices of the linear wavefront, respectively. By further splitting S c (G) at the nodes, at which the reflex wavefront vertices vanish, we obtain a set of connected subgraphs M 1, ..., M k of S c (G). We show that each M i is a pruned medial axis for a certain convex polygon Q i closely related to G, and give an optimal algorithm for computation of all those polygons, for 1 ≤ i ≤ k. Here “pruned” means that M i can be obtained from the medial axis M(Q i ) for Q i by appropriately trimming some (if any) edges of M(Q i ) incident to the leaves of the latter.
Kira Vyatkina
Backmatter
Metadaten
Titel
Transactions on Computational Science VI
herausgegeben von
Marina L. Gavrilova
C. J. Kenneth Tan
Copyright-Jahr
2009
Verlag
Springer Berlin Heidelberg
Electronic ISBN
978-3-642-10649-1
Print ISBN
978-3-642-10648-4
DOI
https://doi.org/10.1007/978-3-642-10649-1