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.
Context: The ability of implant dentistry to be a successful alternative for edentulous patients has increased in the last decade. Clinical features such as osseointegration and stability, in addition to the endurance of the integration urged the researchers towards a better understanding of the design parameters that control long term success of the implants. It is therefore necessary to quantify the effect of changing implant design parameters on interface stress distribution within the maxilla bone. Methods and Materials: A 3D-finite element study was conducted to investigate the effect of changing implant shape parameters (implant body design and implant thread depth) on stress distribution while insertion of the implant in two diff
... Show MoreThe study aims to enrich the information of planners, policymakers, and water resources managers for planning and operating dams. This research aims to address the following question: What are the environmental, economic, and social impacts of the construction and operation of dams on the environment and society? The study assumes that good management is the ideal solution to solve the problems of negative effects resulting from the construction and operation of dams. The research relied on the descriptive analytical approach in studying the positive and negative impacts of Haditha Dam and the government's role. A questionnaire was conducted for 30 specialists in urban and regional planning to find out the most important strategies for sust
... Show MorePre-breakdown phenomenon was investigated within the two, non-mixed dielectric liquids; transformation oil and cresol. Finite element technique was used to follow the initiation and growth of plasma channels (streamer discharge) within pin-plane configuration. That was done for different spacing between the pin-electrode and the liquid-liquid interface. Streamer growth model assumed that, the streamer initiation occurs at the region of the highest value of electric field. Our study shows that the streamer initiates at the tip of the pin and growths toward the other electrode. The study shows, too, that the streamer path controlled by the difference of permittivity of the two liquids and spacing distance of the liquid-liquid interface fro
... Show MoreA new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification
... Show MoreThis article aims to provide a bibliometric analysis of intellectual capital research published in the Scopus database from 1956 to 2020 to trace the development of scientific activities that can pave the way for future studies by shedding light on the gaps in the field. The analysis focuses on 638 intellectual capital-related papers published in the Scopus database over 60 years, drawing upon a bibliometric analysis using VOSviewer. This paper highlights the mainstream of the current research in the intellectual capital field, based on the Scopus database, by presenting a detailed bibliometric analysis of the trend and development of intellectual capital research in the past six decades, including journals, authors, countries, inst
... Show MorePVC membrane sensor for the selective determination of Mefenamic acid (MFA) was constructed. The sensor is based on ion association of MFA with Dodecaphospho molybdic acid (PMA) and Dodeca–Tungstophosphoric acid(PTA) as ion pairs. Nitro benzene (NB) and di-butyl phthalate (DBPH) were used as plasticizing agents in PVC matrix membranes. The specification of sensor based on PMA showed a linear response of a concentration range 1.0 × 10–2 –1.0 × 10–5 M, Nernstian slopes of 17.1-18.86 mV/ decade, detection limit of 7 × 10-5 -9.5 × 10 -7M, pH range 3 – 8 , with correlation coefficients lying between 0.9992 and 0.9976, respectively. By using the ionphore based on PTA gives a concentration range of 1.0 × 10–4 –1.0 × 10–5 M,
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