Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based on the percentage of an accuracy measure of the previous work, are surveyed and introduced, with the aim of producing a concise review of using these algorithms in crime prediction. It is expected that this review study will be helpful for presenting such techniques to crime researchers in addition to supporting future research to develop these techniques for crime analysis by presenting some crime definition, prediction systems challenges and classifications with a comparative study. It was proved though literature, that supervised learning approaches were used in more studies for crime prediction than other approaches, and Logistic Regression is the most powerful method in predicting crime.
Abstract
The Classical Normal Linear Regression Model Based on Several hypotheses, one of them is Heteroscedasticity as it is known that the wing of least squares method (OLS), under the existence of these two problems make the estimators, lose their desirable properties, in addition the statistical inference becomes unaccepted table. According that we put tow alternative, the first one is (Generalized Least Square) Which is denoted by (GLS), and the second alternative is to (Robust covariance matrix estimation) the estimated parameters method(OLS), and that the way (GLS) method neat and certified, if the capabilities (Efficient) and the statistical inference Thread on the basis of an acceptable
... Show MoreUnconfined Compressive Strength is considered the most important parameter of rock strength properties affecting the rock failure criteria. Various research have developed rock strength for specific lithology to estimate high-accuracy value without a core. Previous analyses did not account for the formation's numerous lithologies and interbedded layers. The main aim of the present study is to select the suitable correlation to predict the UCS for hole depth of formation without separating the lithology. Furthermore, the second aim is to detect an adequate input parameter among set wireline to determine the UCS by using data of three wells along ten formations (Tanuma, Khasib, Mishrif, Rumaila, Ahmady, Maudud, Nahr Um
... Show MoreThe physical and elastic characteristics of rocks determine rock strengths in general. Rock strength is frequently assessed using porosity well logs such as neutron and sonic logs. The essential criteria for estimating rock mechanic parameters in petroleum engineering research are uniaxial compressive strength and elastic modulus. Indirect estimation using well-log data is necessary to measure these variables. This study attempts to create a single regression model that can accurately forecast rock mechanic characteristics for the Harth Carbonate Formation in the Fauqi oil field. According to the findings of this study, petrophysical parameters are reliable indexes for determining rock mechanical properties having good performance p
... Show MoreModeling data acquisition systems (DASs) can support the vehicle industry in the development and design of sophisticated driver assistance systems. Modeling DASs on the basis of multiple criteria is considered as a multicriteria decision-making (MCDM) problem. Although literature reviews have provided models for DASs, the issue of imprecise, unclear, and ambiguous information remains unresolved. Compared with existing MCDM methods, the robustness of the fuzzy decision by opinion score method II (FDOSM II) and fuzzy weighted with zero inconsistency II (FWZIC II) is demonstrated for modeling the DASs. However, these methods are implemented in an intuitionistic fuzzy set environment that restricts the ability of experts to provide mem
... Show MoreAbstract
The current research aims to identify the effect of using a model of generative learning in the achievement of first-middle students of chemical concepts in science. The researcher adopted the null hypothesis, which is there is no statistically significant difference at the level (0.05) between the mean scores of the experimental group who study using the generative learning model and the average scores of the control group who study using the traditional method in the chemical concepts achievement test. The research consisted of (200) students of the first intermediate at Al-Farqadin Intermediate School for Boys affiliated with the Directorate of General Education in Baghdad Governorate / Al-Karkh 3 wit
... Show MoreWith the advent of the globalization, the rapid development in technology and the intensity of competition companies attemptto maintain competition advantages and retain customers. The traditional methods in managerial accounting become irrelevance to achieve the objectives of these companies especially with the rapid changes in modern manufacturing environment .Thus there is a need to new tools in accounting such as lean accounting, which is considered as a costing method that support creating value for the customer by costing the entire value stream, eliminating waste in the accounting process, reduced lead time, improved quality, lowered time delivery and increased available capacity. Using value stream focuses not only on the waste&n
... Show MoreThe development that solar energy will have in the next years needs a reliable estimation of available solar energy resources. Several empirical models have been developed to calculate global solar radiation using various parameters such as extraterrestrial radiation, sunshine hours, albedo, maximum temperature, mean temperature, soil temperature, relative humidity, cloudiness, evaporation, total perceptible water, number of rainy days, and altitude and latitude. In present work i) First part has been calculated solar radiation from the daily values of the hours of sun duration using Angstrom model over the Iraq for at July 2017. The second part has been mapping the distribution of so
Purpose – The Cloud computing (CC) and its services have enabled the information centers of organizations to adapt their informatic and technological infrastructure and making it more appropriate to develop flexible information systems in the light of responding to the informational and knowledge needs of their users. In this context, cloud-data governance has become more complex and dynamic, requiring an in-depth understanding of the data management strategy at these centers in terms of: organizational structure and regulations, people, technology, process, roles and responsibilities. Therefore, our paper discusses these dimensions as challenges that facing information centers in according to their data governance and the impa
... Show MoreIn this paper, image compression technique is presented based on the Zonal transform method. The DCT, Walsh, and Hadamard transform techniques are also implements. These different transforms are applied on SAR images using Different block size. The effects of implementing these different transforms are investigated. The main shortcoming associated with this radar imagery system is the presence of the speckle noise, which affected the compression results.