Data mining is a data analysis process using software to find certain patterns or rules in a large amount of data, which is expected to provide knowledge to support decisions. However, missing value in data mining often leads to a loss of information. The purpose of this study is to improve the performance of data classification with missing values, precisely and accurately. The test method is carried out using the Car Evaluation dataset from the UCI Machine Learning Repository. RStudio and RapidMiner tools were used for testing the algorithm. This study will result in a data analysis of the tested parameters to measure the performance of the algorithm. Using test variations: performance at C5.0, C4.5, and k-NN at 0% missing rate, performance at C5.0, C4.5, and k-NN at 5–50% missing rate, performance at C5.0 + k-NNI, C4.5 + k-NNI, and k-NN + k-NNI classifier at 5–50% missing rate, and performance at C5.0 + CMI, C4.5 + CMI, and k-NN + CMI classifier at 5–50% missing rate, The results show that C5.0 with k-NNI produces better classification accuracy than other tested imputation and classification algorithms. For example, with 35% of the dataset missing, this method obtains 93.40% validation accuracy and 92% test accuracy. C5.0 with k-NNI also offers fast processing times compared with other methods.
The problem of research is that there are ways to protect and sustain environmentally important sites in Iraq. There are no documentary sources for these sites, such as the natural landscape of natural and important natural resources, which suffer from severe environmental neglect
Today, the science of artificial intelligence has become one of the most important sciences in creating intelligent computer programs that simulate the human mind. The goal of artificial intelligence in the medical field is to assist doctors and health care workers in diagnosing diseases and clinical treatment, reducing the rate of medical error, and saving lives of citizens. The main and widely used technologies are expert systems, machine learning and big data. In the article, a brief overview of the three mentioned techniques will be provided to make it easier for readers to understand these techniques and their importance.
Most frequently used models for modeling and forecasting periodic climatic time series do not have the capability of handling periodic variability that characterizes it. In this paper, the Fourier Autoregressive model with abilities to analyze periodic variability is implemented. From the results, FAR(1), FAR(2) and FAR(2) models were chosen based on Periodic Autocorrelation function (PeACF) and Periodic Partial Autocorrelation function (PePACF). The coefficients of the tentative model were estimated using a Discrete Fourier transform estimation method. FAR(1) models were chosen as the optimal model based on the smallest values of Periodic Akaike (PAIC) and Bayesian Information criteria (PBIC). The residual of the fitted models was diagn
... Show MoreThis paper addresses the nature of Spatial Data Infrastructure (SDI), considered as one of the most important concepts to ensure effective functioning in a modern society. It comprises a set of continually developing methods and procedures providing the geospatial base supporting a country’s governmental, environmental, economic, and social activities. In general, the SDI framework consists of the integration of various elements including standards, policies, networks, data, and end users and application areas. The transformation of previously paper-based map data into a digital format, the emergence of GIS, and the Internet and a host of online applications (e.g., environmental impact analysis, navigation, applications of VGI dat
... Show MoreFinding orthogonal matrices in different sizes is very complex and important because it can be used in different applications like image processing and communications (eg CDMA and OFDM). In this paper we introduce a new method to find orthogonal matrices by using tensor products between two or more orthogonal matrices of real and imaginary numbers with applying it in images and communication signals processing. The output matrices will be orthogonal matrices too and the processing by our new method is very easy compared to other classical methods those use basic proofs. The results are normal and acceptable in communication signals and images but it needs more research works.
This work bases on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The particular vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera
... Show MoreThe current study is considered a field study to measure the level of satisfaction of the academic programs of Media Masters students. That was accomplished through surveying the attitudes of the students who are enrolled in the faculties of media at the following universities: (Petra University, The Middle East University (MEU), and Al-Yarmouk University). Those students were enrolled in the master’s program within the formal educational system during the second semester of the academic year (2015 – 2016). This survey aims to identify the services, facilities and academic programs provided by the concerned faculties. It, also, aims to identify the public relations, administrative, educational and services aspects of those faculties.
... Show MoreIn this investigation, the mechanical properties and microstructure of Metal Matrix Composites (MMCs) of Al.6061 alloy reinforced by ceramic materials SiC and Al2O3 with different additive percentages 2.5, 5, 7.5, and 10 wt.% for the particle size of 53 µm are studied. Metal matrix composites were prepared by stir casting using vortex technique and then treated thermally by solution heat treatment at 530 0C for 1 hr. and followed by aging at 175 0C with different periods. Mechanical tests were done for the samples before and after heat treatment, such as impact test, hardness test, and tensile test. Also, the microstructure of the metal matrix composites was examine
... Show MoreSevere Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused enormous issues worldwide and is the most infectious pandemic. This study included 50 subjects (evenly distributed between sexes) and their range of ages starting from 2 to 67 years. According to the study's result, the ages and genders of subjects include susceptibility to COVID-19. Males were found to be more infected than females, and the ages of 36 to 67 were more common than other age ranges. Also, BMI calculations revealed that male patients with COVID-19 have the highest percentage of obesity. The clinical parameter results have been found serum C‐reactive protein (CRP) as an essential indicator that changes significantly in infection with COVID‐19 an
... Show MoreThe paper is concerned with the state and proof of the existence theorem of a unique solution (state vector) of couple nonlinear hyperbolic equations (CNLHEQS) via the Galerkin method (GM) with the Aubin theorem. When the continuous classical boundary control vector (CCBCV) is known, the theorem of existence a CCBOCV with equality and inequality state vector constraints (EIESVC) is stated and proved, the existence theorem of a unique solution of the adjoint couple equations (ADCEQS) associated with the state equations is studied. The Frcéhet derivative derivation of the "Hamiltonian" is obtained. Finally the necessary theorem (necessary conditions "NCs") and the sufficient theorem (sufficient conditions" SCs") for optimality of the stat
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