The density-based spatial clustering for applications with noise (DBSCAN) is one of the most popular applications of clustering in data mining, and it is used to identify useful patterns and interesting distributions in the underlying data. Aggregation methods for classifying nonlinear aggregated data. In particular, DNA methylations, gene expression. That show the differentially skewed by distance sites and grouped nonlinearly by cancer daisies and the change Situations for gene excretion on it. Under these conditions, DBSCAN is expected to have a desirable clustering feature i that can be used to show the results of the changes. This research reviews the DBSCAN and compares its performance with other algorithms, such as the tradit

  The indicators were important core for any work, and may be occurring this indicators way of communicating among planers and decision makers, even also for public participating, do make any decision. The urban and regional planning is one of those science highly depending on using indictors, for two  reasons, first, way to communicating ideas between specialist and non-specialist, (politician and decision makers), the second one, this field are multidisciplinary science, so the need indictors to clearing thoughts among different backgrounds in one team, as common language.

This research tries to clear importance of GIS in forming and building Spatial Planning Indicators, to cross communication problem among planning g

Urban land uses of all kinds are the constituent elements of the urban spatial structure. Because of the influence of economic and social factors, cities in general are characterized by the dynamic state of their elements over time. Urban functions occur in a certain way with different spatial patterns. Hence, urban planners and the relevant urban management teams should understand the future spatial pattern of these changes by resorting to quantitative models in spatial planning. This is to ensure that future predictions are made with a high level of accuracy so that appropriate strategies can be used to address the problems arising from such changes. The Markov chain method is one of the quantitative models used in spatial planning to ana

OpenStreetMap (OSM), recognised for its current and readily accessible spatial database, frequently serves regions lacking precise data at the necessary granularity. Global collaboration among OSM contributors presents challenges to data quality and uniformity, exacerbated by the sheer volume of input and indistinct data annotation protocols. This study presents a methodological improvement in the spatial accuracy of OSM datasets centred over Baghdad, Iraq, utilising data derived from OSM services and satellite imagery. An analytical focus was placed on two geometric correction methods: a two-dimensional polynomial affine transformation and a two-dimensional polynomial conformal transformation. The former involves twelve coefficients for ad

Find all boils down to is marked with (recruitment aesthetic of digital technology for (color) in the film novelist) And the relationship between the aesthetic employment of digital technology for (color) and its impacts on the level of artistic creativity through digital technology and its impacts on the technical and completed the final film in the film.Search and distributed at five chapters The first chapter discusses the methodological framework of the research, which included the research problem and is as follows:What is the digital technology to enrich color in the context in the film narrative to reflect the dramatic effect?And the importance of research and its objectives, including:1 - Employment aesthetic of digital technolog

A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.

Aim. We investigate, in the mid-infrared, the spatial properties of the polycyclic aromatic hydrocarbons (PAHs) emission in the disk of HD 179218, an intermediate-mass Herbig star at ~300 pc.

Methods. We obtained mid-infrared images in the PAH-1, PAH-2 and Si-6 filters centered at 8.6, 11.3, and 12.5 μm, and N-band low-resolution spectra using CanariCam on the 10-m Gran Telescopio Canarias (GTC). We compared the point spread function (PSF) profiles measured in the PAH filters to the profile derived in the Si-6 filter, where the thermal continuum emission dominates. We performed radiative transfer modeling of

The study population growth of the most important demographic phenomena upon which planners to meet changes in the size of the population increase is through knowledge of the requirements of population growth can be planned for the future. On this basis, Tuz District was chosen for the study of population growth, which set her period (1977-2012), and compared with the growth of the population of the province and the extent of the variation in population growth, according to the administrative units, has touched search numerical and proportional distribution of the population according to the administrative aspects of the judiciary, as well as environmental distribution.

The elimination of the study population growth dramatically

This research aims to provide insight into the Spatial Autoregressive Quantile Regression model (SARQR), which is more general than the Spatial Autoregressive model (SAR) and Quantile Regression model (QR) by integrating aspects of both. Since Bayesian approaches may produce reliable estimates of parameter and overcome the problems that standard estimating techniques, hence, in this model (SARQR), they were used to estimate the parameters. Bayesian inference was carried out using Markov Chain Monte Carlo (MCMC) techniques. Several criteria were used in comparison, such as root mean squared error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R^2). The application was devoted on dataset of poverty rates acro