This study aims to analyze the spatial distribution of the epidemic spread and the role of the physical, social, and economic characteristics in this spreading. A geographically weighted regression (GWR) model was built within a GIS environment using infection data monitored by the Iraqi Ministry of Health records for 10 months from March to December 2020. The factors adopted in this model are the size of urban interaction areas and human gatherings, movement level and accessibility, and the volume of public services and facilities that attract people. The results show that it would be possible to deal with each administrative unit in proportion to its circumstances in light of the factors that appear in it. So, there will not be a single treatment for all areas with different urban characteristics, which sometimes helps not to stop social and economic life due to the imposition of a comprehensive ban on movement and activities. Therefore, there will be other supportive policies other than the ban, depending on the urban indicators for each region, such as reducing external movement from it or relying on preventing public activities only.
In this paper we proposes the philosophy of the Darwinian selection as synthesis method called Genetic algorithm ( GA ), and include new merit function with simple form then its uses in other works for designing one of the kinds of multilayer optical filters called high reflection mirror. Here we intend to investigate solutions for many practical problems. This work appears designed high reflection mirror that have good performance with reduction the number of layers, which can enable one to controlling the errors effect of the thickness layers on the final product, where in this work we can yield such a solution in a very shorter time by controlling the length of the chromosome and optimal genetic operators . Res
... Show Morethis paper presents a novel method for solving nonlinear optimal conrol problems of regular type via its equivalent two points boundary value problems using the non-classical
Cloud Computing is a mass platform to serve high volume data from multi-devices and numerous technologies. Cloud tenants have a high demand to access their data faster without any disruptions. Therefore, cloud providers are struggling to ensure every individual data is secured and always accessible. Hence, an appropriate replication strategy capable of selecting essential data is required in cloud replication environments as the solution. This paper proposed a Crucial File Selection Strategy (CFSS) to address poor response time in a cloud replication environment. A cloud simulator called CloudSim is used to conduct the necessary experiments, and results are presented to evidence the enhancement on replication performance. The obtained an
... Show MoreThis study represents an optical biosensor for early skin cancer detection using cysteine-cupped CdSe/CdS Quantum Dots (QDs). The study optimizes QD synthesis, surface, optical functionalization, and bioconjugation to enhance specificity and sensitivity for early skin cancer cell detection. The research provides insights into QD interactions with skin cancer biomarkers, demonstrating high-contrast, precise cellular imaging. Cysteine-capped CdSe/CdS absorption spectra reveal characteristic peaks for undamaged DNA, while spectral shifts indicate structural changes in skin-cancer-damaged DNA. Additionally, fluorescence spectra show sharp peaks for undamaged DNA and notable shifts and intensity variations when interacting with skin cancer. This
... Show MoreThis paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe
... Show MoreOptimizing the Access Point (AP) deployment is of great importance in wireless applications owing the requirement to provide efficient and cost-effective communication. Highly targeted by many researchers and academic industries, Quality of Service (QOS) is an important primary parameter and objective in mind along with AP placement and overall publishing cost. This study proposes and investigates a multi-level optimization algorithm based on Binary Particle Swarm Optimization (BPSO). It aims to an optimal multi-floor AP placement with effective coverage that makes it more capable of supporting QOS and cost effectiveness. Five pairs (coverage, AP placement) of weights, signal threshol