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
... Show MoreA new two-way nesting technique is presented for a multiple nested-grid ocean modelling system. The new technique uses explicit center finite difference and leapfrog schemes to exchange information between the different subcomponents of the nested-grid system. The performance of the different nesting techniques is compared, using two independent nested-grid modelling systems. In this paper, a new nesting algorithm is described and some preliminary results are demonstrated. The validity of the nesting method is shown in some problems for the depth averaged of 2D linear shallow water equation.
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The phenomena of Dust storm take place in barren and dry regions all over the world. It may cause by intense ground winds which excite the dust and sand from soft, arid land surfaces resulting it to rise up in the air. These phenomena may cause harmful influences upon health, climate, infrastructure, and transportation. GIS and remote sensing have played a key role in studying dust detection. This study was conducted in Iraq with the objective of validating dust detection. These techniques have been used to derive dust indices using Normalized Difference Dust Index (NDDI) and Middle East Dust Index (MEDI), which are based on images from MODIS and in-situ observation based on hourly wi
High-performance liquid chromatographic methods are used for the determination of water-soluble vitamins with UV-Vis. Detector. A reversed-phase high-performance liquid chromatographic has been developed for determination of water-soluble vitamins. Identification of compounds was achieved by comparing their retention times and UV spectra with those of standards solution. Separation was performed on a C18 column, using an isocratic 30% (v/v) acetonitril in dionozed water as mobile phase at pH 3.5 and flow rate 1.0m/min. The method provides low detection and quantification limits, good linearity in a large concentration interval and good precision. The detection limits ranged from 0.01 to 0.025µg/ml. The accuracy of the method was
... Show MoreBackground: Poly (methyl methacrylate) has been widely utilized for fabrication of dentures for many years as it has good advantages but not achieved all demands of the mechanical properties such as low transverse strength, low impact strength, low surface hardness, high water solubility and high water sorption. Material and method: To provide bonding between ZrO2 nanoparticles and PMMA matrix, the ZrO2 Nano-fillers were surface-treated with a saline coupling agent. Plasma surface treatment of polyethylene (PE) fiber was done to change surface fiber by using DC- glow discharge system. For characterization of interring any functional groups, the (FTIR) spectrum were done .then the mechanical properties studied to choose the appropriate perc
... Show MoreAdministrative procedures in various organizations produce numerous crucial records and data. These
records and data are also used in other processes like customer relationship management and accounting
operations.It is incredibly challenging to use and extract valuable and meaningful information from these data
and records because they are frequently enormous and continuously growing in size and complexity.Data
mining is the act of sorting through large data sets to find patterns and relationships that might aid in the data
analysis process of resolving business issues. Using data mining techniques, enterprises can forecast future
trends and make better business decisions.The Apriori algorithm has bee
Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.