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.
With a goal to identify, and ultimately removing from the oil fraction, the carcinogenic components, an oil fraction oil has been analyzed into a main three hydrocarbon groups, paraffins, aromatics, and polycyclic saturates. A multi-stage adsorption apparatus has been used. Four units of 300 g alumina each seems to be sufficient for removing the polynuclear aromatics from 75 g of an oil fraction boiling between 365-375 °C from Qurna crude oil. The usefulness of the ternary diagram for analyzing the oil fraction to the three hydrocarbons groups has been studied and verified. An experimentally based linear relationship of density and refractive index was established to enable of identifying the composition of an oil fraction using th
... Show MoreIn data transmission a change in single bit in the received data may lead to miss understanding or a disaster. Each bit in the sent information has high priority especially with information such as the address of the receiver. The importance of error detection with each single change is a key issue in data transmission field.
The ordinary single parity detection method can detect odd number of errors efficiently, but fails with even number of errors. Other detection methods such as two-dimensional and checksum showed better results and failed to cope with the increasing number of errors.
Two novel methods were suggested to detect the binary bit change errors when transmitting data in a noisy media.Those methods were: 2D-Checksum me
This research aims to provide insight into the Spatial Autoregressive Quantile Regression model (SARQR), which is more general than the Spatial Autoregressive model (SAR) and Quantile Regression model (QR) by integrating aspects of both. Since Bayesian approaches may produce reliable estimates of parameter and overcome the problems that standard estimating techniques, hence, in this model (SARQR), they were used to estimate the parameters. Bayesian inference was carried out using Markov Chain Monte Carlo (MCMC) techniques. Several criteria were used in comparison, such as root mean squared error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R^2). The application was devoted on dataset of poverty rates acro
... Show MoreThe Fauqi field is located about 50Km North-East Amara town in Missan providence in Iraq. Fauqi field has 1,640 MMbbl STOIIP, which lies partly in Iran. Oil is produced from both Mishrif and Asmari zones. Geologically, the Fauqi anticline straddles the Iraqi/Iranian border and is most probably segmented by several faults. There are several reasons leading to drilling horizontal wells rather than vertical wells. The most important parameter is increasing oil recovery, particularly from thin or tight reservoir permeability. The Fauqi oil field is regarded as a giant field with approximately more than 1 billion barrels of proven reserves, but it has recently experienced low production rate problems in many of its existing wells. This study
... Show MoreThis study investigates the possibility of removing ciprofloxacin (CIP) using three types of adsorbent based on green-prepared iron nanoparticles (Fe.NPs), copper nanoparticles (Cu. NPS), and silver nanoparticles (Ag. NPS) from synthesized aqueous solution. They were characterized using different analysis methods. According to the characterization findings, each prepared NPs has the shape of a sphere and with ranges in sizes from of 85, 47, and 32 nanometers and a surface area of 2.1913, 1.6562, and 1.2387 m2/g for Fe.NPs, Cu.NPs and Ag.NPs, respectively. The effects of various parameters such as pH, initial CIP concentration, temperature, NPs dosage, and time on CIP removal were investigated through batch experiments. The res
... Show MoreThe aim of the research is to identify learning difficulties and their role in children's perception of self-concept. The researcher adopted the descriptive and analytical approach method in this study. A questionnaire was designed by the researcher to collect some related information such as biodata, family, health, diagnostic and behavioral patterns of the case. In addition, the researcher adopted the scale of learning difficulties for elementary school students prepared by Zaidan Ahmed Al-Sartawi (1995), the scale of student appreciation for the survey of learning difficulties for primary school students by Michael Best, which was translated to the Arabic language by (Saeed Abdullah Debis). The researcher adopted also the Self-Concept
... Show MoreThe platforms of social networking sites, with their distinctive communication and technological features, create a social movement that led to the establishment of a new pattern of communication in a modern context. This allows the users on the internet to carry out many social interactions based on the interests and commonalities among them. Algerian women have a share of this digital presence by representing their views and discussing their issues on several sites like Facebook, for example.
In this research, we have analyzed the pages of Algerian women on Facebook site to find out the most important issues addressed by Algerian women so that we can organize their concerns in the digital channels and discover their different orie
Text Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as t
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