Search results for: Spatial Data Mining
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8009

Search results for: Spatial Data Mining

7469 Improved C-Fuzzy Decision Tree for Intrusion Detection

Authors: Krishnamoorthi Makkithaya, N. V. Subba Reddy, U. Dinesh Acharya

Abstract:

As the number of networked computers grows, intrusion detection is an essential component in keeping networks secure. Various approaches for intrusion detection are currently being in use with each one has its own merits and demerits. This paper presents our work to test and improve the performance of a new class of decision tree c-fuzzy decision tree to detect intrusion. The work also includes identifying best candidate feature sub set to build the efficient c-fuzzy decision tree based Intrusion Detection System (IDS). We investigated the usefulness of c-fuzzy decision tree for developing IDS with a data partition based on horizontal fragmentation. Empirical results indicate the usefulness of our approach in developing the efficient IDS.

Keywords: Data mining, Decision tree, Feature selection, Fuzzyc- means clustering, Intrusion detection.

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7468 Seasonal Variation of the Impact of Mining Activities on Ga-Selati River in Limpopo Province, South Africa

Authors: Joshua N. Edokpayi, John O. Odiyo, Patience P. Shikwambana

Abstract:

Water is a very rare natural resource in South Africa. Ga-Selati River is used for both domestic and industrial purposes. This study was carried out in order to assess the quality of Ga-Selati River in a mining area of Limpopo Province-Phalaborwa. The pH, Electrical Conductivity (EC) and Total Dissolved Solids (TDS) were determined using a Crinson multimeter while turbidity was measured using a Labcon Turbidimeter. The concentrations of Al, Ca, Cd, Cr, Fe, K, Mg, Mn, Na and Pb were analysed in triplicate using a Varian 520 flame atomic absorption spectrometer (AAS) supplied by PerkinElmer, after acid digestion with nitric acid in a fume cupboard. The average pH of the river from eight different sampling sites was 8.00 and 9.38 in wet and dry season respectively. Higher EC values were determined in the dry season (138.7 mS/m) than in the wet season (96.93 mS/m). Similarly, TDS values were higher in dry (929.29 mg/L) than in the wet season (640.72 mg/L) season. These values exceeded the recommended guideline of South Africa Department of Water Affairs and Forestry (DWAF) for domestic water use (70 mS/m) and that of the World Health Organization (WHO) (600 mS/m), respectively. Turbidity varied between 1.78-5.20 and 0.95-2.37 NTU in both wet and dry seasons. Total hardness of 312.50 mg/L and 297.75 mg/L as the concentration of CaCO3 was computed for the river in both the wet and the dry seasons and the river water was categorised as very hard. Mean concentration of the metals studied in both the wet and the dry seasons are: Na (94.06 mg/L and 196.3 mg/L), K (11.79 mg/L and 13.62 mg/L), Ca (45.60 mg/L and 41.30 mg/L), Mg (48.41 mg/L and 44.71 mg/L), Al (0.31 mg/L and 0.38 mg/L), Cd (0.01 mg/L and 0.01 mg/L), Cr (0.02 mg/L and 0.09 mg/L), Pb (0.05 mg/L and 0.06 mg/L), Mn (0.31 mg/L and 0.11 mg/L) and Fe (0.76 mg/L and 0.69 mg/L). Results from this study reveal that most of the metals were present in concentrations higher than the recommended guidelines of DWAF and WHO for domestic use and the protection of aquatic life.

Keywords: Contamination, mining activities, surface water, trace metals.

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7467 Multiscale Analysis and Change Detection Based on a Contrario Approach

Authors: F.Katlane, M.S.Naceur, M.A.Loghmari

Abstract:

Automatic methods of detecting changes through satellite imaging are the object of growing interest, especially beca²use of numerous applications linked to analysis of the Earth’s surface or the environment (monitoring vegetation, updating maps, risk management, etc...). This work implemented spatial analysis techniques by using images with different spatial and spectral resolutions on different dates. The work was based on the principle of control charts in order to set the upper and lower limits beyond which a change would be noted. Later, the a contrario approach was used. This was done by testing different thresholds for which the difference calculated between two pixels was significant. Finally, labeled images were considered, giving a particularly low difference which meant that the number of “false changes” could be estimated according to a given limit.

Keywords: multi-scale, a contrario approach, significantthresholds, change detection.

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7466 Analysis on Spatiotemporal Pattern of Land Surface Temperature in Kunming City, China

Authors: Jinrui Ren, Li Wu

Abstract:

Anthropogenic activities and changes of underlying surface affect the temporal and spatial distribution of surface temperature in Kunming. Taking Kunming city as the research area, the surface temperature in 2000, 2010 and 2020 as the research object, using ENVI 5.3 and ArcGIS 10.8 as auxiliary tools, and based on the spatial autocorrelation method, this paper devoted to exploring the interactions among the changes of surface temperature, urban heat island effect and land use type, so as to provide theoretical basis and scientific basis for mitigating climate change. The results showed that: (1) The heat island effect was obvious in Kunming City, the high temperature area increased from 604 km2 in 2000 to 1269 km2 in 2020, and the sub-high temperature area reached 1099 km2 in 2020; (2) In terms of space, the spatial distribution of LST was significantly different with the change of underlying surface. The high temperature zone extended in three directions: south, north and east. The overall spatial distribution pattern of LST was high in the east and low in the west. (3) The inter-annual fluctuation of land surface temperature (LST) was large, and the growth rate was faster, from 2000 to 2010. The lowest temperature in 2000 was 13.45 ℃, which raised to 19.71 ℃ in 2010, and the temperature difference in 10 years was 6.26 ℃. (4) The land use/land cover type has a strong effect on the change of LST: the man-made land made a great contribution to the increase of LST, followed by grassland and farmland, while forest and water have a significant cooling effect on LST. To sum up, the variation of surface temperature in Kunming is the result of the interactions of human activities and climate change.

Keywords: Surface temperature, urban heat island effect, land use cover type, spatiotemporal variation.

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7465 Socio-Spatial Transformations in Obsolete Port Regions: A Case for Istanbul-Karakoy District

Authors: Umut Tuğlu Karslı

Abstract:

Istanbul-Karakoy Port, field of this study, has lost its former significance in time due to the transformation of urban functions. Today, activities for regeneration of this region continue in two forms and scales. First of these activities is the "planned transformation projects," which also includes “Galataport project”, and the second one is "spontaneous transformation," which consists of individual interventions. Galataport project that based on the idea of arranging the area specifically for tourists was prepared in 2005 and became a topic of tremendous public debate. On the other hand, the "spontaneous transformation" that is observed in Karakoy District starts in 2004 with the foundation of “Istanbul Modern Museum” which allowed the cultural integration of old naval warehouses of the port to the daily life. Following this adaptive reuse intervention, the district started to accommodate numerous art galleries, studios, caféworkshops and design stores. In this context, this paper first examines regeneration studies in obsolete port regions, analyzes the planned and ongoing socio-spatial transformations in the specific case of Karakoy and performs a critical review of the sustainability of the proposals on how to reinstate the district in the active life of Istanbul.

Keywords: Port Cities, Socio-Spatial Transformation, Urban Regeneration, Urban Revitalization.

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7464 Data and Spatial Analysis for Economy and Education of 28 E.U. Member-States for 2014

Authors: Alexiou Dimitra, Fragkaki Maria

Abstract:

The objective of the paper is the study of geographic, economic and educational variables and their contribution to determine the position of each member-state among the EU-28 countries based on the values of seven variables as given by Eurostat. The Data Analysis methods of Multiple Factorial Correspondence Analysis (MFCA) Principal Component Analysis and Factor Analysis have been used. The cross tabulation tables of data consist of the values of seven variables for the 28 countries for 2014. The data are manipulated using the CHIC Analysis V 1.1 software package. The results of this program using MFCA and Ascending Hierarchical Classification are given in arithmetic and graphical form. For comparison reasons with the same data the Factor procedure of Statistical package IBM SPSS 20 has been used. The numerical and graphical results presented with tables and graphs, demonstrate the agreement between the two methods. The most important result is the study of the relation between the 28 countries and the position of each country in groups or clouds, which are formed according to the values of the corresponding variables.

Keywords: Multiple factorial correspondence analysis, principal component analysis, factor analysis, E.U.-28 countries, statistical package IBM SPSS 20, CHIC Analysis V 1.1 Software, Eurostat.eu statistics.

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7463 The Robust Clustering with Reduction Dimension

Authors: Dyah E. Herwindiati

Abstract:

A clustering is process to identify a homogeneous groups of object called as cluster. Clustering is one interesting topic on data mining. A group or class behaves similarly characteristics. This paper discusses a robust clustering process for data images with two reduction dimension approaches; i.e. the two dimensional principal component analysis (2DPCA) and principal component analysis (PCA). A standard approach to overcome this problem is dimension reduction, which transforms a high-dimensional data into a lower-dimensional space with limited loss of information. One of the most common forms of dimensionality reduction is the principal components analysis (PCA). The 2DPCA is often called a variant of principal component (PCA), the image matrices were directly treated as 2D matrices; they do not need to be transformed into a vector so that the covariance matrix of image can be constructed directly using the original image matrices. The decomposed classical covariance matrix is very sensitive to outlying observations. The objective of paper is to compare the performance of robust minimizing vector variance (MVV) in the two dimensional projection PCA (2DPCA) and the PCA for clustering on an arbitrary data image when outliers are hiden in the data set. The simulation aspects of robustness and the illustration of clustering images are discussed in the end of paper

Keywords: Breakdown point, Consistency, 2DPCA, PCA, Outlier, Vector Variance

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7462 Modeling of Heat and Mass Transfer in Soil Plant-Atmosphere. Influence of the Spatial Variability of Soil Hydrodynamic

Authors: Aouattou Nabila, Saighi Mohamed, Fekih Malika

Abstract:

The modeling of water transfer in the unsaturated zone uses techniques and methods of the soil physics to solve the Richards-s equation. However, there is a disaccord between the size of the measurements provided by the soil physics and the size of the fields of hydrological modeling problem, to which is added the strong spatial variability of soil hydraulic properties. The objective of this work was to develop a methodology to estimate the hydrodynamic parameters for modeling water transfers at different hydrological scales in the soil-plant atmosphere systems.

Keywords: Hydraulic properties, Modeling, Unsaturated zone, Transfer, Water

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7461 Sparsity-Based Unsupervised Unmixing of Hyperspectral Imaging Data Using Basis Pursuit

Authors: Ahmed Elrewainy

Abstract:

Mixing in the hyperspectral imaging occurs due to the low spatial resolutions of the used cameras. The existing pure materials “endmembers” in the scene share the spectra pixels with different amounts called “abundances”. Unmixing of the data cube is an important task to know the present endmembers in the cube for the analysis of these images. Unsupervised unmixing is done with no information about the given data cube. Sparsity is one of the recent approaches used in the source recovery or unmixing techniques. The l1-norm optimization problem “basis pursuit” could be used as a sparsity-based approach to solve this unmixing problem where the endmembers is assumed to be sparse in an appropriate domain known as dictionary. This optimization problem is solved using proximal method “iterative thresholding”. The l1-norm basis pursuit optimization problem as a sparsity-based unmixing technique was used to unmix real and synthetic hyperspectral data cubes.

Keywords: Basis pursuit, blind source separation, hyperspectral imaging, spectral unmixing, wavelets.

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7460 Coastal Resources Spatial Planning and Potential Oil Risk Analysis: Case Study of Misratah’s Coastal Resources, Libya

Authors: Abduladim Maitieg, Kevin Lynch, Mark Johnson

Abstract:

The goal of the Libyan Environmental General Authority (EGA) and National Oil Corporation (Department of Health, Safety & Environment) during the last 5 years has been to adopt a common approach to coastal and marine spatial planning. Protection and planning of the coastal zone is a significant for Libya, due to the length of coast and, the high rate of oil export, and spills’ potential negative impacts on coastal and marine habitats. Coastal resource scenarios constitute an important tool for exploring the long-term and short-term consequences of oil spill impact and available response options that would provide an integrated perspective on mitigation. To investigate that, this paper reviews the Misratah coastal parameters to present the physical and human controls and attributes of coastal habitats as the first step in understanding how they may be damaged by an oil spill. This paper also investigates costal resources, providing a better understanding of the resources and factors that impact the integrity of the ecosystem. Therefore, the study described the potential spatial distribution of oil spill risk and the coastal resources value, and also created spatial maps of coastal resources and their vulnerability to oil spills along the coast. This study proposes an analysis of coastal resources condition at a local level in the Misratah region of the Mediterranean Sea, considering the implementation of coastal and marine spatial planning over time as an indication of the will to manage urban development. Oil spill contamination analysis and their impact on the coastal resources depend on (1) oil spill sequence, (2) oil spill location, (3) oil spill movement near the coastal area. The resulting maps show natural, socio-economic activity, environmental resources along of the coast, and oil spill location. Moreover, the study provides significant geodatabase information which is required for coastal sensitivity index mapping and coastal management studies. The outcome of study provides the information necessary to set an Environmental Sensitivity Index (ESI) for the Misratah shoreline, which can be used for management of coastal resources and setting boundaries for each coastal sensitivity sectors, as well as to help planners measure the impact of oil spills on coastal resources. Geographic Information System (GIS) tools were used in order to store and illustrate the spatial convergence of existing socio-economic activities such as fishing, tourism, and the salt industry, and ecosystem components such as sea turtle nesting area, Sabkha habitats, and migratory birds feeding sites. These geodatabases help planners investigate the vulnerability of coastal resources to an oil spill.

Keywords: Coastal and marine spatial planning advancement training, GIS mapping, human uses, ecosystem components, Misratah coast, Libyan, oil spill.

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7459 Urban Land Cover Change of Olomouc City Using LANDSAT Images

Authors: Miloš Marjanović, Jaroslav Burian, Ja kub Miřijovský, Jan Harbula

Abstract:

This paper regards the phenomena of intensive suburbanization and urbanization in Olomouc city and in Olomouc region in general for the period of 1986–2009. A Remote Sensing approach that involves tracking of changes in Land Cover units is proposed to quantify the urbanization state and trends in temporal and spatial aspects. It actually consisted of two approaches, Experiment 1 and Experiment 2 which implied two different image classification solutions in order to provide Land Cover maps for each 1986–2009 time split available in the Landsat image set. Experiment 1 dealt with the unsupervised classification, while Experiment 2 involved semi- supervised classification, using a combination of object-based and pixel-based classifiers. The resulting Land Cover maps were subsequently quantified for the proportion of urban area unit and its trend through time, and also for the urban area unit stability, yielding the relation of spatial and temporal development of the urban area unit. Some outcomes seem promising but there is indisputably room for improvements of source data and also processing and filtering.

Keywords: Change detection, image classification, land cover, Landsat images, Olomouc city, urbanization.

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7458 Robust Variogram Fitting Using Non-Linear Rank-Based Estimators

Authors: Hazem M. Al-Mofleh, John E. Daniels, Joseph W. McKean

Abstract:

In this paper numerous robust fitting procedures are considered in estimating spatial variograms. In spatial statistics, the conventional variogram fitting procedure (non-linear weighted least squares) suffers from the same outlier problem that has plagued this method from its inception. Even a 3-parameter model, like the variogram, can be adversely affected by a single outlier. This paper uses the Hogg-Type adaptive procedures to select an optimal score function for a rank-based estimator for these non-linear models. Numeric examples and simulation studies will demonstrate the robustness, utility, efficiency, and validity of these estimates.

Keywords: Asymptotic relative efficiency, non-linear rank-based, robust, rank estimates, variogram.

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7457 Integration of Support Vector Machine and Bayesian Neural Network for Data Mining and Classification

Authors: Essam Al-Daoud

Abstract:

Several combinations of the preprocessing algorithms, feature selection techniques and classifiers can be applied to the data classification tasks. This study introduces a new accurate classifier, the proposed classifier consist from four components: Signal-to- Noise as a feature selection technique, support vector machine, Bayesian neural network and AdaBoost as an ensemble algorithm. To verify the effectiveness of the proposed classifier, seven well known classifiers are applied to four datasets. The experiments show that using the suggested classifier enhances the classification rates for all datasets.

Keywords: AdaBoost, Bayesian neural network, Signal-to-Noise, support vector machine, MCMC.

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7456 The Principle Probabilities of Space-Distance Resolution for a Monostatic Radar and Realization in Cylindrical Array

Authors: Anatoly D. Pluzhnikov, Elena N. Pribludova, Alexander G. Ryndyk

Abstract:

In conjunction with the problem of the target selection on a clutter background, the analysis of the scanning rate influence on the spatial-temporal signal structure, the generalized multivariate correlation function and the quality of the resolution with the increase pulse repetition frequency is made. The possibility of the object space-distance resolution, which is conditioned by the range-to-angle conversion with an increased scanning rate, is substantiated. The calculations for the real cylindrical array at high scanning rate are presented. The high scanning rate let to get the signal to noise improvement of the order of 10 dB for the space-time signal processing.

Keywords: Antenna pattern, array, signal processing, spatial resolution.

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7455 Scanning Device for Sampling the Spatial Distribution of the E-field

Authors: Juan Blas, Alfonso Bahillo, Santiago Mazuelas, David Bullido, Patricia Fernandez, Ruben M. Lorenzo, Evaristo J. Abril

Abstract:

This paper presents a low cost automatic system for sampling the electric field in a limited area. The scanning area is a flat surface parallel to the ground at a selected height. We discuss in detail the hardware, software and all the arrangements involved in the system operation. In order to show the system performance we include a campaign of narrow band measurements with 6017 sample points in the surroundings of a cellular base station. A commercial isotropic antenna with three orthogonal axes was used as sampling device. The results are analyzed in terms of its space average, standard deviation and statistical distribution.

Keywords: measurement device, propagation, spatial sampling.

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7454 Review of the Road Crash Data Availability in Iraq

Authors: Abeer K. Jameel, Harry Evdorides

Abstract:

Iraq is a middle income country where the road safety issue is considered one of the leading causes of deaths. To control the road risk issue, the Iraqi Ministry of Planning, General Statistical Organization started to organise a collection system of traffic accidents data with details related to their causes and severity. These data are published as an annual report. In this paper, a review of the available crash data in Iraq will be presented. The available data represent the rate of accidents in aggregated level and classified according to their types, road users’ details, and crash severity, type of vehicles, causes and number of causalities. The review is according to the types of models used in road safety studies and research, and according to the required road safety data in the road constructions tasks. The available data are also compared with the road safety dataset published in the United Kingdom as an example of developed country. It is concluded that the data in Iraq are suitable for descriptive and exploratory models, aggregated level comparison analysis, and evaluation and monitoring the progress of the overall traffic safety performance. However, important traffic safety studies require disaggregated level of data and details related to the factors of the likelihood of traffic crashes. Some studies require spatial geographic details such as the location of the accidents which is essential in ranking the roads according to their level of safety, and name the most dangerous roads in Iraq which requires tactic plan to control this issue. Global Road safety agencies interested in solve this problem in low and middle-income countries have designed road safety assessment methodologies which are basing on the road attributes data only. Therefore, in this research it is recommended to use one of these methodologies.

Keywords: Data availability, Iraq, road safety.

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7453 The Patterns of Unemployment and the Geography of Social Housing

Authors: Sónia Alves

Abstract:

During the last few decades in the academic field, the debate has increased on the effects of social geography on the opportunities of socioeconomic integration. On one hand, it has been discussed how the contents of the urban structure and social geography affect not only the way people interact, but also their chances of social and economic integration. On the other hand, it has also been discussed how the urban structure is also constrained and transformed by the action of social actors. Without questioning the powerful influence of structural factors, related to the logic of the production system, labor markets, education and training, the research has shown the role played by place of residence in shaping individual outcomes such as unemployment. In the context of this debate the importance of territory of residence with respect to the problem of unemployment has been highlighted. Although statistics of unemployment have already demonstrated the unequal incidence of the phenomenon in social groups, the issue of uneven territorial impact on the phenomenon at intra-urban level remains relatively unknown. The purpose of this article is to show and to interpret the spatial patterns of unemployment in the city of Porto using GIS (Geographic Information System - GIS) technology. Under this analysis the overlap of the spatial patterns of unemployment with the spatial distribution of social housing, allows the discussion of the relationship that occurs between these patterns and the reasons that might explain the relative immutability of socioeconomic problems in some neighborhoods.

Keywords: Unemployment, area effects, urban planning, Porto.

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7452 A Technical Perspective on Roadway Safety in Eastern Province: Data Evaluation and Spatial Analysis

Authors: Muhammad Farhan, Sayed Faruque, Amr Mohammed, Sami Osman, Omar Al-Jabari, Abdul Almojil

Abstract:

Saudi Arabia in recent years has seen drastic increase in traffic related crashes. With population of over 29 million, Saudi Arabia is considered as a fast growing and emerging economy. The rapid population increase and economic growth has resulted in rapid expansion of transportation infrastructure, which has led to increase in road crashes. Saudi Ministry of Interior reported more than 7,000 people killed and 68,000 injured in 2011 ranking Saudi Arabia to be one of the worst worldwide in traffic safety. The traffic safety issues in the country also result in distress to road users and cause and economic loss exceeding 3.7 billion Euros annually. Keeping this in view, the researchers in Saudi Arabia are investigating ways to improve traffic safety conditions in the country. This paper presents a multilevel approach to collect traffic safety related data required to do traffic safety studies in the region. Two highway corridors including King Fahd Highway 39 kilometre and Gulf Cooperation Council Highway 42 kilometre long connecting the cities of Dammam and Khobar were selected as a study area. Traffic data collected included traffic counts, crash data, travel time data, and speed data. The collected data was analysed using geographic information system to evaluate any correlation. Further research is needed to investigate the effectiveness of traffic safety related data when collected in a concerted effort.

Keywords: Crash Data, Data Collection, Traffic Safety.

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7451 Investigation of Maritime Accidents with Exploratory Data Analysis in the Strait of Çanakkale (Dardanelles)

Authors: Gizem Kodak

Abstract:

The Strait of Çanakkale (Dardanelles), together with the Strait of Istanbul and the Sea of Marmara, form the Turkish Straits System. In other words, the Strait of Çanakkale is the southern gate of the system that connects the Black Sea countries with the other countries of the world. Due to the heavy maritime traffic, it is important to scientifically examine the accident characteristics in the region. In particular, the results indicated by the descriptive statistics are of critical importance in order to strengthen the safety of navigation. At this point, exploratory data analysis offers strategic outputs in terms of defining the problem and knowing the strengths and weaknesses against possible accident risk. The study aims to determine the accident characteristics in the Strait of Çanakkale with temporal and spatial analysis of historical data, using Exploratory Data Analysis (EDA) as the research method. The study's results will reveal the general characteristics of maritime accidents in the region and form the infrastructure for future studies. Therefore, the text provides a clear description of the research goals and methodology, and the study's contributions are well-defined.

Keywords: Maritime Accidents, EDA, Strait of Çanakkale, navigational safety.

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7450 Remote Sensing, GIS, and AHP for Assessing Physical Vulnerability to Tsunami Hazard

Authors: Abu Bakar Sambah, Fusanori Miura

Abstract:

Remote sensing image processing, spatial data analysis through GIS approach, and analytical hierarchy process were introduced in this study for assessing the vulnerability area and inundation area due to tsunami hazard in the area of Rikuzentakata, Iwate Prefecture, Japan. Appropriate input parameters were derived from GSI DEM data, ALOS AVNIR-2, and field data. We used the parameters of elevation, slope, shoreline distance, and vegetation density. Five classes of vulnerability were defined and weighted via pairwise comparison matrix. The assessment results described that 14.35km2 of the study area was under tsunami vulnerability zone. Inundation areas are those of high and slightly high vulnerability. The farthest area reached by a tsunami was about 7.50km from the shoreline and shows that rivers act as flooding strips that transport tsunami waves into the hinterland. This study can be used for determining a priority for land-use planning in the scope of tsunami hazard risk management.

Keywords: AHP, GIS, remote sensing, tsunami vulnerability.

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7449 High Sensitivity Crack Detection and Locating with Optimized Spatial Wavelet Analysis

Authors: A. Ghanbari Mardasi, N. Wu, C. Wu

Abstract:

In this study, a spatial wavelet-based crack localization technique for a thick beam is presented. Wavelet scale in spatial wavelet transformation is optimized to enhance crack detection sensitivity. A windowing function is also employed to erase the edge effect of the wavelet transformation, which enables the method to detect and localize cracks near the beam/measurement boundaries. Theoretical model and vibration analysis considering the crack effect are first proposed and performed in MATLAB based on the Timoshenko beam model. Gabor wavelet family is applied to the beam vibration mode shapes derived from the theoretical beam model to magnify the crack effect so as to locate the crack. Relative wavelet coefficient is obtained for sensitivity analysis by comparing the coefficient values at different positions of the beam with the lowest value in the intact area of the beam. Afterward, the optimal wavelet scale corresponding to the highest relative wavelet coefficient at the crack position is obtained for each vibration mode, through numerical simulations. The same procedure is performed for cracks with different sizes and positions in order to find the optimal scale range for the Gabor wavelet family. Finally, Hanning window is applied to different vibration mode shapes in order to overcome the edge effect problem of wavelet transformation and its effect on the localization of crack close to the measurement boundaries. Comparison of the wavelet coefficients distribution of windowed and initial mode shapes demonstrates that window function eases the identification of the cracks close to the boundaries.

Keywords: Edge effect, scale optimization, small crack locating, spatial wavelet.

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7448 Extracting Terrain Points from Airborne Laser Scanning Data in Densely Forested Areas

Authors: Ziad Abdeldayem, Jakub Markiewicz, Kunal Kansara, Laura Edwards

Abstract:

Airborne Laser Scanning (ALS) is one of the main technologies for generating high-resolution digital terrain models (DTMs). DTMs are crucial to several applications, such as topographic mapping, flood zone delineation, geographic information systems (GIS), hydrological modelling, spatial analysis, etc. Laser scanning system generates irregularly spaced three-dimensional cloud of points. Raw ALS data are mainly ground points (that represent the bare earth) and non-ground points (that represent buildings, trees, cars, etc.). Removing all the non-ground points from the raw data is referred to as filtering. Filtering heavily forested areas is considered a difficult and challenging task as the canopy stops laser pulses from reaching the terrain surface. This research presents an approach for removing non-ground points from raw ALS data in densely forested areas. Smoothing splines are exploited to interpolate and fit the noisy ALS data. The presented filter utilizes a weight function to allocate weights for each point of the data. Furthermore, unlike most of the methods, the presented filtering algorithm is designed to be automatic. Three different forested areas in the United Kingdom are used to assess the performance of the algorithm. The results show that the generated DTMs from the filtered data are accurate (when compared against reference terrain data) and the performance of the method is stable for all the heavily forested data samples. The average root mean square error (RMSE) value is 0.35 m.

Keywords: Airborne laser scanning, digital terrain models, filtering, forested areas.

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7447 Socio-Spatial Resilience Strategic Planning Through Understanding Strategic Perspectives on Tehran and Bath

Authors: Aynaz Lotfata

Abstract:

Planning community has been long discussing emerging paradigms within the planning theory in the face of the changing conditions of the world order. The paradigm shift concept was introduced by Thomas Kuhn, in 1960, who claimed the necessity of shifting within scientific knowledge boundaries; and following him in 1970 Imre Loktas also gave priority to the emergence of multi-paradigm societies [24]. Multi-paradigm is changing our predetermined lifeworld through uncertainties. Those uncertainties are reflected in two sides, the first one is uncertainty as a concept of possibility and creativity in public sphere and the second one is uncertainty as a risk. Therefore, it is necessary to apply a resilience planning approach to be more dynamic in controlling uncertainties which have the potential to transfigure present time and space definitions. In this way, stability of system can be achieved. Uncertainty is not only an outcome of worldwide changes but also a place-specific issue, i.e. it changes from continent to continent, a country to country; a region to region. Therefore, applying strategic spatial planning with respect to resilience principle contributes to: control, grasp and internalize uncertainties through place-specific strategies. In today-s fast changing world, planning system should follow strategic spatial projects to control multi-paradigm societies with adaptability capacities. Here, we have selected two alternatives to demonstrate; these are; 1.Tehran (Iran) from the Middle East 2.Bath (United Kingdom) from Europe. The study elaborates uncertainties and particularities in their strategic spatial planning processes in a comparative manner. Through the comparison, the study aims at assessing place-specific priorities in strategic planning. The approach is to a two-way stream, where the case cities from the extreme end of the spectrum can learn from each other. The structure of this paper is to firstly compare semi-periphery (Tehran) and coreperiphery (Bath) cities, with the focus to reveal how they equip to face with uncertainties according to their geographical locations and local particularities. Secondly, the key message to address is “Each locality requires its own strategic planning approach to be resilient.--

Keywords: Adaptation, Relational Network, Socio-Spatial Strategic Resiliency, Uncertainty.

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7446 Context-aware Recommender Systems using Data Mining Techniques

Authors: Kyoung-jae Kim, Hyunchul Ahn, Sangwon Jeong

Abstract:

This study proposes a novel recommender system to provide the advertisements of context-aware services. Our proposed model is designed to apply a modified collaborative filtering (CF) algorithm with regard to the several dimensions for the personalization of mobile devices – location, time and the user-s needs type. In particular, we employ a classification rule to understand user-s needs type using a decision tree algorithm. In addition, we collect primary data from the mobile phone users and apply them to the proposed model to validate its effectiveness. Experimental results show that the proposed system makes more accurate and satisfactory advertisements than comparative systems.

Keywords: Location-based advertisement, Recommender system, Collaborative filtering, User needs type, Mobile user.

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7445 Semi-Automatic Method to Assist Expert for Association Rules Validation

Authors: Amdouni Hamida, Gammoudi Mohamed Mohsen

Abstract:

In order to help the expert to validate association rules extracted from data, some quality measures are proposed in the literature. We distinguish two categories: objective and subjective measures. The first one depends on a fixed threshold and on data quality from which the rules are extracted. The second one consists on providing to the expert some tools in the objective to explore and visualize rules during the evaluation step. However, the number of extracted rules to validate remains high. Thus, the manually mining rules task is very hard. To solve this problem, we propose, in this paper, a semi-automatic method to assist the expert during the association rule's validation. Our method uses rule-based classification as follow: (i) We transform association rules into classification rules (classifiers), (ii) We use the generated classifiers for data classification. (iii) We visualize association rules with their quality classification to give an idea to the expert and to assist him during validation process.

Keywords: Association rules, Rule-based classification, Classification quality, Validation.

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7444 Balancing of Quad Tree using Point Pattern Analysis

Authors: Amitava Chakraborty, Sudip Kumar De, Ranjan Dasgupta

Abstract:

Point quad tree is considered as one of the most common data organizations to deal with spatial data & can be used to increase the efficiency for searching the point features. As the efficiency of the searching technique depends on the height of the tree, arbitrary insertion of the point features may make the tree unbalanced and lead to higher time of searching. This paper attempts to design an algorithm to make a nearly balanced quad tree. Point pattern analysis technique has been applied for this purpose which shows a significant enhancement of the performance and the results are also included in the paper for the sake of completeness.

Keywords: Algorithm, Height balanced tree, Point patternanalysis, Point quad tree.

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7443 Texture Feature Extraction of Infrared River Ice Images using Second-Order Spatial Statistics

Authors: Bharathi P. T, P. Subashini

Abstract:

Ice cover County has a significant impact on rivers as it affects with the ice melting capacity which results in flooding, restrict navigation, modify the ecosystem and microclimate. River ices are made up of different ice types with varying ice thickness, so surveillance of river ice plays an important role. River ice types are captured using infrared imaging camera which captures the images even during the night times. In this paper the river ice infrared texture images are analysed using first-order statistical methods and secondorder statistical methods. The second order statistical methods considered are spatial gray level dependence method, gray level run length method and gray level difference method. The performance of the feature extraction methods are evaluated by using Probabilistic Neural Network classifier and it is found that the first-order statistical method and second-order statistical method yields low accuracy. So the features extracted from the first-order statistical method and second-order statistical method are combined and it is observed that the result of these combined features (First order statistical method + gray level run length method) provides higher accuracy when compared with the features from the first-order statistical method and second-order statistical method alone.

Keywords: Gray Level Difference Method, Gray Level Run Length Method, Kurtosis, Probabilistic Neural Network, Skewness, Spatial Gray Level Dependence Method.

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7442 Machine Learning Methods for Network Intrusion Detection

Authors: Mouhammad Alkasassbeh, Mohammad Almseidin

Abstract:

Network security engineers work to keep services available all the time by handling intruder attacks. Intrusion Detection System (IDS) is one of the obtainable mechanisms that is used to sense and classify any abnormal actions. Therefore, the IDS must be always up to date with the latest intruder attacks signatures to preserve confidentiality, integrity, and availability of the services. The speed of the IDS is a very important issue as well learning the new attacks. This research work illustrates how the Knowledge Discovery and Data Mining (or Knowledge Discovery in Databases) KDD dataset is very handy for testing and evaluating different Machine Learning Techniques. It mainly focuses on the KDD preprocess part in order to prepare a decent and fair experimental data set. The J48, MLP, and Bayes Network classifiers have been chosen for this study. It has been proven that the J48 classifier has achieved the highest accuracy rate for detecting and classifying all KDD dataset attacks, which are of type DOS, R2L, U2R, and PROBE.

Keywords: IDS, DDoS, MLP, KDD.

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7441 Optimal One Bit Time Reversal For UWB Impulse Radio In Multi-User Wireless Communications

Authors: Hung Tuan Nguyen

Abstract:

In this paper, with the purpose of further reducing the complexity of the system, while keeping its temporal and spatial focusing performance, we investigate the possibility of using optimal one bit time reversal (TR) system for impulse radio ultra wideband multi-user wireless communications. The results show that, by optimally selecting the number of used taps in the pre-filter the optimal one bit TR system can outperform the full one bit TR system. In some cases, the temporal and spatial focusing performance of the optimal one bit TR system appears to be compatible with that of the original TR system. This is a significant result as the overhead cost is much lower than it is required in the original TR system.

Keywords: Time reversal, optimal one bit, UWB, multi-user interference, inter symbol interference

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7440 Spatial Distribution of Cd, Zn and Hg in Groundwater at Rayong Province, Thailand

Authors: T. Makkasap, T. Satapanajaru

Abstract:

The objective of this study was to evaluate the distribution patterns of Cd, Zn and Hg in groundwater by geospatial interpolation. The study was performed at Rayong province in the eastern part of Thailand, with high agricultural and industrial activities. Groundwater samples were collected twice a year from 31 tubewells around this area. Inductively Coupled Plasma-Atomic Emission Spectrometer (ICP-AES) was used to measure the concentrations of Cd, Zn, and Hg in groundwater samples. The results demonstrated that concentrations of Cd, Zn and Hg range from 0.000-0.297 mg/L (x = 0.021±0.033 mg/L), 0.022-33.236 mg/L (x = 4.214±4.766 mg/L) and 0.000-0.289 mg/L (x = 0.023±0.034 mg/L), respectively. Most of the heavy metals concentrations were exceeded groundwater quality standards as specified in the Ministry of Natural Resources and Environment, Thailand. The trend distribution of heavy metals were high concentrations at the southeastern part of the area that especially vulnerable to heavy metals and other contaminants.

Keywords: Groundwater, Heavy metals, Kriging, Rayong, Spatial distribution.

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