Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin

The results of studying the effects of M. anisopiliae spores on mosquito, C. quinquefasciatus showed a biological effects represented by immature mortality. The mortality increased proportionally with the concentrations of fungal spores, which reached (at high concentration 2×1011 spores / ml), to 86.6, 56.6% in first and late instar larvae, respectively. An important to mention that cumulative death rate was significantly associated with the time, which reached to 56% at 7 day after treatment. In addition, M. anisopiliae had a long period permanence in aquatic habitats; in which the residual effects stay 30 days in aquatic habitats after treatment at laboratory conditions. Interestingly, the long period exposure of fungal spores (30 minut

In recent years, the performance of Spatial Data Infrastructures for governments and companies is a task that has gained ample attention. Different categories of geospatial data such as digital maps, coordinates, web maps, aerial and satellite images, etc., are required to realize the geospatial data components of Spatial Data Infrastructures. In general, there are two distinct types of geospatial data sources exist over the Internet: formal and informal data sources. Despite the growth of informal geospatial data sources, the integration between different free sources is not being achieved effectively. The adoption of this task can be considered the main advantage of this research. This article addresses the research question of how the

Hierarchical temporal memory (HTM) is a biomimetic sequence memory algorithm that holds promise for invariant representations of spatial and spatio-temporal inputs. This article presents a comprehensive neuromemristive crossbar architecture for the spatial pooler (SP) and the sparse distributed representation classifier, which are fundamental to the algorithm. There are several unique features in the proposed architecture that tightly link with the HTM algorithm. A memristor that is suitable for emulating the HTM synapses is identified and a new Z-window function is proposed. The architecture exploits the concept of synthetic synapses to enable potential synapses in the HTM. The crossbar for the SP avoids dark spots caused by unutil

Recently, important efforts have been made in an attempt to search for the cheapest and ecofriendly alternatives adsorbents. In the present work, waste molasses from Iraqi date palm (Zahdi) had been used as a provenance to produce charcoal for the removal of methylene blue (MB) dye from water. The optimum prepared charcoal was obtained at 150 C, by increasing temperature to 175 C, the charcoal had almost converted to ash. The obtained charcoal have been inspected for properties using scanning electron microscope (SEM), atomic force microscope (AFM), porosity and surface area. Adsorption data were optimized to Langmuir and Freundlich and adsorption parameters have been evaluated. The thermodynamic parameters like a change

Orthogonal polynomials and their moments serve as pivotal elements across various fields. Discrete Krawtchouk polynomials (DKraPs) are considered a versatile family of orthogonal polynomials and are widely used in different fields such as probability theory, signal processing, digital communications, and image processing. Various recurrence algorithms have been proposed so far to address the challenge of numerical instability for large values of orders and signal sizes. The computation of DKraP coefficients was typically computed using sequential algorithms, which are computationally extensive for large order values and polynomial sizes. To this end, this paper introduces a computationally efficient solution that utilizes the parall