The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator has superior performance compared with other estimators.
This research takes up address the practical side by taking case studies for construction projects that include the various Iraqi governorates, as it includes conducting a field survey to identify the impact of parametric costs on construction projects and compare them with what was reached during the analysis and the extent of their validity and accuracy, as well as adopting the approach of personal interviews to know the reality of the state of construction projects. The results showed, after comparing field data and its measurement in construction projects for the sectors (public and private), the correlation between the expected and actual cost change was (97.8%), and this means that the data can be adopted in the re
... Show MorePermeability data has major importance work that should be handled in all reservoir simulation studies. The importance of permeability data increases in mature oil and gas fields due to its sensitivity for the requirements of some specific improved recoveries. However, the industry has a huge source of data of air permeability measurements against little number of liquid permeability values. This is due to the relatively high cost of special core analysis.
The current study suggests a correlation to convert air permeability data that are conventionally measured during laboratory core analysis into liquid permeability. This correlation introduces a feasible estimation in cases of data loose and poorly consolidated formations, or in cas
Information systems and data exchange between government institutions are growing rapidly around the world, and with it, the threats to information within government departments are growing. In recent years, research into the development and construction of secure information systems in government institutions seems to be very effective. Based on information system principles, this study proposes a model for providing and evaluating security for all of the departments of government institutions. The requirements of any information system begin with the organization's surroundings and objectives. Most prior techniques did not take into account the organizational component on which the information system runs, despite the relevance of
... Show MoreThe research presents the reliability. It is defined as the probability of accomplishing any part of the system within a specified time and under the same circumstances. On the theoretical side, the reliability, the reliability function, and the cumulative function of failure are studied within the one-parameter Raleigh distribution. This research aims to discover many factors that are missed the reliability evaluation which causes constant interruptions of the machines in addition to the problems of data. The problem of the research is that there are many methods for estimating the reliability function but no one has suitable qualifications for most of these methods in the data such
Credential compromise is one of the most widespread security threats, allowing adversaries to bypass traditional authentication measures and impersonate legitimate users. Traditional intrusion detection systems are often based on network-level or macro-behavioral indicators, which can be easily spoofed by an attacker, thus compromising the effectiveness of those mechanisms. This study presents an improved adaptive intrusion detection system to authenticate user behavior based on micro-digital behavioral profiling. It involves the use of timing of keystrokes, micro-mouse, navigation in the application, and interaction rhythm signatures. The proposed system uses a hybrid model consisting of Long Short-Term Memory (LSTM) sequence predi
... Show MoreHuman Interactive Proofs (HIPs) are automatic inverse Turing tests, which are intended to differentiate between people and malicious computer programs. The mission of making good HIP system is a challenging issue, since the resultant HIP must be secure against attacks and in the same time it must be practical for humans. Text-based HIPs is one of the most popular HIPs types. It exploits the capability of humans to recite text images more than Optical Character Recognition (OCR), but the current text-based HIPs are not well-matched with rapid development of computer vision techniques, since they are either vey simply passed or very hard to resolve, thus this motivate that
... Show MoreCongenital anomalies commonly occur in humans, possibly visible. If these anomalies appear in visible parts in human body such as face, hands and feet. They may only appear after utilizing a number of special tests in order to show by means of the anomalies that occur in the internal organs of the body such as heart, stomach and kidneys.
Research data have comprised accessible information in the anomalies birth statistics form situated of Health and Life Statistics section at the Ministry of Health and environment, where the number of anomalies births involved in the study (2603 anomalies birth) in Iraq, except Kurdistan region, at 2015. A two way-response logistic regression analysis h
... Show MoreThis research dealt with the analysis of murder crime data in Iraq in its temporal and spatial dimensions, then it focused on building a new model with an algorithm that combines the characteristics associated with time and spatial series so that this model can predict more accurately than other models by comparing them with this model, which we called the Combined Regression model (CR), which consists of merging two models, the time series regression model with the spatial regression model, and making them one model that can analyze data in its temporal and spatial dimensions. Several models were used for comparison with the integrated model, namely Multiple Linear Regression (MLR), Decision Tree Regression (DTR), Random Forest Reg
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