The very fast developments of web and data collection technologies have enabled non-experts to collect and disseminate geospatial datasets through web applications. This new type of spatial data is usually known as collaborative mapping or volunteered geographic information VGI. There are various countries around the world could benefit from collaborative mapping data because it is cost free data, easy to access and it provides more customised data. However, there is a concern about its quality because the data collectors may lack the sufficient experience and training about geospatial data production. Most previous studies which have outlined and analysed VGI quality focused on positional and linear features. The current research has been conducted to investigate the quality of another feature type such as polygons (buildings) of collaborative mapping data. Two different VGI data sources have been tested: Google Maps and WikiMapia services. The VGI data was compared with reference data extracted from high resolution aerial image which was provided from General Directorate of Surveying. The suggested methodology based on applying several metrics and methods such as surface distance method, compactness, elongation, and ratio of areas computation. The polygon shape accuracy was analysed by comparing conventional statistical values such as mean, median, standard deviation, minimum, and maximum. The results indicated that there is no big difference between the shape similarities of collaborative mapping polygons. Hence, it can be used for several applications such as spatial data infrastructures (SDI) and urban planning.
The purpose of this study is to examine the dimensions of strategic intent (SI; see Appendix 1) according to the Hamel and Prahalad model as a building for the future, relying on today’s knowledge-based and proactive strategic directions of management as long-term and deep-perspective creative directions, objective vision and rational analysis, integrative in work, survival structure and comprehensiveness in perception.
The quantitative approach was used based on research, detection and proof, as data were collected from leader
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Aromaticity, antiaromaticity and chemical bonding in the ground (S0), first singlet excited (S1) and lowest triplet (T1) electronic states of disulfur dinitride, S2N2, were investigated by analysing the isotropic magnetic shielding, σiso(r), in the space surrounding the molecule for each electronic state. The σiso(r) values were calculated by state-optimized CASSCF/cc-pVTZ wave functions with 22 electrons in 16 orbitals constructed from gauge-including atomic orbitals (GIAOs). The S1 and T1 electronic states were confirmed as 11Au and 13B3u, respectively, through linear response CC3/aug-cc-pVTZ calculations of the vertical excitation energies for eight singlet (S1–S8) and eight triplet (T1–T8) electronic states. The aromaticities of S
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This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi
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This study aims to determine the reasons for the increase in the frequency of sand and dust storms in the Middle East and to identify their sources and mitigate them. A set of climatic data from 60 years (1960–2022) was analyzed. Sand storms in Iraq are a silty sand mature arkose composed of 72.7% sand, 25.1% silt, and 2.19% clay; the clay fraction in dust storms constitutes 70%, with a small amount of silt (20.6%) and sand (9.4%). Dust and sand storms (%) are composed of quartz (49.2, 67.1), feldspar (4.9, 20.9), calcite (38, 5), gypsum (4.8, 0.4), dolomite (0.8, 1.0), and heavy minerals (3.2, 6.6). Increasing temperatures in Iraq, by an average of 2 °C for sixty years, have contributed to an increase in the number of dust storm
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