In general, the importance of cluster analysis is that one can evaluate elements by clustering multiple homogeneous data; the main objective of this analysis is to collect the elements of a single, homogeneous group into different divisions, depending on many variables. This method of analysis is used to reduce data, generate hypotheses and test them, as well as predict and match models. The research aims to evaluate the fuzzy cluster analysis, which is a special case of cluster analysis, as well as to compare the two methods—classical and fuzzy cluster analysis. The research topic has been allocated to the government and private hospitals. The sampling for this research was comprised of 288 patients being treated in 10 hospitals. As t

A fixed firefighting system is a key component of fire safeguarding and reducing fire danger. It is installed as a permanent component in a structure to protect the entire or a portion of the building and its contents. The study aims to review the previous studies that deal with the evaluation of fire safety measures and their use in resolving problems associated with fire threats in buildings. For this reason, a number of previous studies in this field were reviewed compared with the NFPA code. The findings revealed that regulatory developments over the last several decades had created an atmosphere conducive to innovation. This has resulted in a growth in the number of fixed firefighting system types now obtainable. Th

Alpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images

Future generations of wireless networks are expected to heavily rely on unmanned aerial vehicles (UAVs). UAV networks have extraordinary features like high mobility, frequent topology change, tolerance to link failure, and extending the coverage area by adding external UAVs. UAV network provides several advantages for civilian, commercial, search and rescue applications. A realistic mobility model must be used to assess the dependability and effectiveness of UAV protocols and algorithms.  In this research paper, the performance of the Gauss Markov (GM) and Random Waypoint (RWP) mobility models in multi-UAV networks for a search and rescue scenario is analyzed and evaluated. Additionally, the two mobility models GM and RWP are descr

Groundwater quality investigation has been carried out in the western part of Iraq (west longitude '40°40). The physicochemical analyses of 64 groundwater samples collected from seven aquifers were used in the determination of groundwater characterization and assessment. The concept of spatial hydrochemical bi-model was prepared for quantitative and qualitative interpretation. Hydrogeochemical data referred that the groundwater is of meteoric origin and has processes responsible for observed brackishness. The geochemical facies of the groundwater reveal that none of the anions and cations pairs exceed 50% and there are practically mixtures of multi-water types (such as Ca–Mg–Cl–HCO₃ and Na+K–SO4–Cl water type) as do

This study aims to develop a thermosensitive mucoadhesive periodontal in situ gel of secnidazole for local release of drug for treatment of periodontitis, in order to increase the drug residence time and to increase patient compliance while lowering the side effects of the drug.

Cold method was used to prepare 30 formulas of secnidazole periodontal in situ gel, using different concentrations of thermosensitive polymers (poloxamer407 alone or in combination with poloxamer 188) and methyl cellulose (MC ) or hydroxypropyl methylcellulose (HPMC K4M )in different concentrations used as mucoadhesive polymer and the resultant formulations were subjected to several tests such as   gelation temperature GT, appearance and pH value. The fo

Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s