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 the similarity between hospitals of the study sample was measured according to the standards of quality of health services under fuzzy conditions (a case of uncertainty of the opinions of patients who were in the evaluation of health services provided to them, which was represented by a set of criteria and was measured in the form of a Likert five-point scale). Moreover, those criteria were organized into a questionnaire containing 31 items. The research found a number of conclusions, the most important is that both methods of hierarchical cluster analysis and fuzzy cluster analysis, classify the hospitals of the research sample into two clusters, each cluster comprises a group of hospitals that depend on applying health quality service standards. The second important conclusion is that the fuzzy cluster analysis is more suitable for the classification of the research sample compared to hierarchical cluster analysis.
The purpose of this paper is to define fuzzy subspaces for fuzzy space of orderings and we prove some results about this definition in which it leads to a lot of new results on fuzzy space of orderings. Also we define the sum and product over such spaces such that: If f = < a1,…,an > and g = < b1,…bm>, their sum and product are f + g = < a1…,an, b1, …, bm> and f × g =
This study aimed for isolation and identification of Candida glabrata and identifying some virulence factors. The distribution of patients with candidemia thrush showed that the age group 50-65 years old recorded the highest incidence of candidiasis in female and male with leukemia by 50% and 37.9 % respectively compared to the lowest incidence of candidiasis in the age group under 17 years old in female and male 8.8% and 13.5%, respectively. While the age group between 5-8 years was high, reaching 18 cases of oral candidiasis and 42% of children with leukemia compared with the age group, which was the least, that reached 9 cases, 21%. The highest incidence of C. glabrata was 59 isolates of females and males with leukemia, while C. kefyer w
... Show MoreThe research aims to verify the presence of correlation between the financial cycle and the economic cycle in the Iraqi economy. During the research period, the Iraqi economy witnessed a crisis cycle due to the permanent deviations in the state budget and the occurrence of sustainable deficits during the period of the economic blockade with the coincidence of an inflationary economic cycle due to the cheap money policy and the occurrence of Negative supply shocks due to the blockade and the madly high general level of prices, in addition to the weak financial planning of the state budget during the post-economic blockade and the entry of the economy into a stagnant economic cycle due to security and political instability, low levels of priv
... Show MoreIn this study, we investigate the behavior of the estimated spectral density function of stationary time series in the case of missing values, which are generated by the second order Autoregressive (AR (2)) model, when the error term for the AR(2) model has many of continuous distributions. The Classical and Lomb periodograms used to study the behavior of the estimated spectral density function by using the simulation.
We have presented the distribution of the exponentiated expanded power function (EEPF) with four parameters, where this distribution was created by the exponentiated expanded method created by the scientist Gupta to expand the exponential distribution by adding a new shape parameter to the cumulative function of the distribution, resulting in a new distribution, and this method is characterized by obtaining a distribution that belongs for the exponential family. We also obtained a function of survival rate and failure rate for this distribution, where some mathematical properties were derived, then we used the method of maximum likelihood (ML) and method least squares developed (LSD) to estimate the parameters an
... Show MoreThis research aims to study and analyze the reality of monetary policy and financial sustainability in Iraq through either a descriptive or analytical approach by trying to link and coordinate between monetary policy and fiscal policy to enhance economic sustainability. The research is based on the hypothesis that the monetary policy of Iraq contributes to achieving financial stability, which improves economic sustainability by providing aid and assistance to the state to reduce the budget deficit and exacerbate indebtedness. The author used the monetary policy indicators, the re-deduction of Treasury transfers by the central bank and the money supply, and financial sustainability indicators, including the public debt indicators and the
... Show MoreThis paper studies the combination fluid viscous dampers in the outrigger system to add supplementary damping into the structure, which purpose to remove the dependability of the structure to lower variable intrinsic damping. It works by connecting the central core, comprising either shear walls or braced frames, to the outer perimeter columns.
The modal considered is a 36 storey square high rise reinforced concrete building. By constructing a discrete lumped mass model, and using frequency-based response function, two systems of dampers, parallel and series systems are studied. The maximum lateral load at the top of the building is calculated, and this load w
... Show MoreBig data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an
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