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.
This study aims to simulate and assess the hydraulic characteristics and residual chlorine in the water supply network of a selected area in Al-Najaf City using WaterGEMS software. Field and laboratory work were conducted to measure the pressure heads and velocities, and water was sampled from different sites in the network and then tested to estimate chlorine residual. Records and field measurements were utilized to validate WaterGEMS software. Good agreement was obtained between the observed and predicted values of pressure with RMSE range between 0.09–0.17 and 0.08–0.09 for chlorine residual. The results of the analysis of water distribution systems (WDS) during maximum demand
The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when
... Show MoreThe purpose of this paper is to investigate Religious Human Rights Violations. Religious liberty is essential for everyone, everywhere. Because religion is significant to everyone, everywhere. Humans are religious by nature. Our nature drives us to seek answers to deep questions about ultimate things. We cannot live a fully human life unless we are free to seek those answers and live according to the truths we discover. In this study, the researcher used Marsh and White model for analysis A sample of an offensive image of an Islamic concept from the book "Mohammad believes it or else." this book is a comic book written by pseudonym Abdullah Aziz and published by Crescent Moon Publishing company. The book is marked with anti- Mohammad, preju
... Show MoreRecommender Systems are tools to understand the huge amount of data available in the internet world. Collaborative filtering (CF) is one of the most knowledge discovery methods used positively in recommendation system. Memory collaborative filtering emphasizes on using facts about present users to predict new things for the target user. Similarity measures are the core operations in collaborative filtering and the prediction accuracy is mostly dependent on similarity calculations. In this study, a combination of weighted parameters and traditional similarity measures are conducted to calculate relationship among users over Movie Lens data set rating matrix. The advantages and disadvantages of each measure are spotted. From the study, a n
... Show MoreAgInSe2 (AIS) thin films solar cell involving of n-type AgInSe2 and Si of p-type substrate by using thermal evaporation method. The influence of annealing of the preparation AgInSe2 were considered to find the best properties of solar device. Thin film AIS have been deposited under the vacuum of 1.5*10-6 Torr with (400) nm thickness at R.T and annealing temperatures (473,573) K. Polycrystalline tetragonal structure for AIS thin films from XRD and increasing of surface roughness from AFM, energy gap values decreasing with increasing annealing temperatures, all films were negative type, I-V characteristics show increasing of efficiency with increasing of annealing temperatures.
: The Aluminium (Al) material emerged as a plasmonic material in the wavelength ranges from the ultraviolet to the visible bands in different on-chip plasmonic applications. In this paper, we demonstrate the effect of using Al on the electromagnetic (EM) field distribution of a compact hybrid plasmonic waveguide (HPW) acting as a polarization rotator. We compare the performance of Al with other familiar metals that are widely used as plasmonic materials, which are Silver (Ag) and Gold (Au). Furthermore, we study the effect of reducing the geometrical dimensions of the used materials on the EM field distributions inside the HPW and, consequently, on the efficiency of the polarization rotation. We perform the study based o
... Show MoreThe art of theater penetrated various scientific and human fields, as well as touching the facts and events surrounding it, and scientific innovations had a wide field, so it adopted feedback in interactive theater performances, especially the theater of the oppressed. Then came the indicators that resulted from the theoretical framework for the formation of the tool by which the research sample is analyzed, and then the chapter concluded with previous studies. As for the third chapter, it involved the research procedures, and through the research tool and the research method, and by selecting the intentional sample, the sample represented by a play (the story of Shahrour) was analyzed. As for the fourth chapter, it included the results
... Show MoreThe field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet
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