In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.
Purpose:To evaluate knowledge, practice and attitude of community pharmacists in Basra regarding modified release dosage forms which are widely used for many therapeutic purposes in pharmacy practice.
Methods:The current study was conducted among certified pharmacists in Basra governorate- south of Iraq. Data collection was carried out by a questionnaire.
Results:A total number of 175 community pharmacists responded to the questionnaire. The majority worked in OTC based dispensing pharmacies located in the center of the city. Most respondents missed K1 and were unable to state the difference between different types of modified products. There was a major positive agreemen
... Show MoreBackground: obesity is nowadays a pandemic condition. Obese subjects are commonly characterized by musculoskeletal disorders and particularly by non-specific low back pain (LBP). However, the relationship between obesity and LBP remain to date unsupported by an objective measurement of the mechanical behavior of spine and it is morphology in obese subjects. . Objectives: To identify the relationship between obesity and LBP regarding (height, weight, sleeping, chronic diseases, smoking, and steroid). Method: A cross-sectional study was conducted from the first of January 2016 to January 2018 in obe
... Show MoreSome of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems. Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic. Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance. In this study, two different sets of select
... Show MoreThe primary objective of this research is to determine the best EDI
software application that meets the users' requirements, and to show
the functionality potentially presented in any software of electronic
data interchange (EDI) system. Also, in this paper, will be addressed
issues relating to integration EDI system into business process, and
the issues regarding the performance of EDI application will also be
discussed
Introduction:
Many business owners suffer major financial problems during periods of financial stagnation, the decline of markets and businesses, or under the impact of financial shocks for certain reasons that result in large debts and the consequent financial and legal obligations. This is the beginning of a long and endless path of suffering and the search for a safe exit. It is even worse for financial institutions to facilitate financial solutions that rely on lending as a solution to their financial problem. Debt and its consequences increase, and the problem deepens and becomes complicated until things become entangled and the escape or declaration of bank
... Show MoreObjective(s): To evaluate women's perceptions toward wellness. Methodology: A descriptive-evaluation design is employed through the present study to evaluate women's perceptions toward wellness in Baghdad City. A non-probability (purposive) sample of (140) woman is selected from three primary health centers in Baghdad City. A questionnaire, of (57) items, is designed and constructed for the purpose of the study. Split-half internal consistency reliability of the study instrument is determined through computation of Cronbach alpha correlation coefficient and the content validity of the instrument determined thr
This paper aims to evaluate large-scale water treatment plants’ performance and demonstrate that it can produce high-level effluent water. Raw water and treated water parameters of a large monitoring databank from 2016 to 2019, from eight water treatment plants located at different parts in Baghdad city, were analyzed using nonparametric and multivariate statistical tools such as principal component analysis (PCA) and hierarchical cluster analysis (HCA). The plants are Al-Karkh, Sharq-Dijlah, Al-Wathba, Al-Qadisiya Al-Karama, Al-Dora, Al-Rasheed, Al-Wehda. PCA extracted six factors as the most significant water quality parameters that can be used to evaluate the variation in drinkin
Background: Complete removal of filling material from the root canal is an essential requirement for endodontic retreatment. The purpose of the present study is to evaluate and compare the dissolving capabilities of various solvents (Xylene, Eugenate Desobturator, Eucalyptol, EDTA and Distilled water (as a control)) on four different types of sealer (Endofill, Apexit Plus, AH Plus and EndoSequence bioceramic sealer). Materials and method: Eighty samples of each sealer were prepared according to the manufacturers' instructions and then divided into ten groups (of 8 samples) for immersion in the respective solvents for 2 and 5 min immersion periods. Each sealer specimen was weighed to obtain its initial mass. The specimens were immersed in
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