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Bayesian Computational Methods of the Logistic Regression Model
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Abstract<p>In this paper, we will discuss the performance of Bayesian computational approaches for estimating the parameters of a Logistic Regression model. Markov Chain Monte Carlo (MCMC) algorithms was the base estimation procedure. We present two algorithms: Random Walk Metropolis (RWM) and Hamiltonian Monte Carlo (HMC). We also applied these approaches to a real data set.</p>
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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Engineering
A Novel Analytical Model to Design Piezoelectric Patches Used to Repair Cracked Beams
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In this paper, an analytical solution describing the deflection of a cracked beam repaired with piezoelectric patch is introduced. The solution is derived using perturbation method. A novel analytical model to calculate the proper dimensions of piezoelectric patches used to repair cracked beams is also introduced. This model shows that the thickness of the piezoelectric patch depends mainly on the thickness of the cracked beam, the electro-mechanical properties of the patch material, the applied load and the crack location. Furthermore, the model shows that the length of the piezoelectric patches depends on the thickness of the patch as well as it depends on the length of the cracked beam and the crack depth. The additio

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Semi parametric Estimators for Quantile Model via LASSO and SCAD with Missing Data
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In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

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Publication Date
Mon Dec 03 2018
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Condition assessment and rehabilitation for trunk sewer deterioration based on Semi-Markov model
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An accurate assessment of the pipes’ conditions is required for effective management of the trunk sewers. In this paper the semi-Markov model was developed and tested using the sewer dataset from the Zublin trunk sewer in Baghdad, Iraq, in order to evaluate the future performance of the sewer. For the development of this model the cumulative waiting time distribution of sewers was used in each condition that was derived directly from the sewer condition class and age data. Results showed that the semi-Markov model was inconsistent with the data by adopting ( 2 test) and also, showed that the error in prediction is due to lack of data on the sewer waiting times at each condition state which can be solved by using successive conditi

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Publication Date
Sat Jun 04 2022
Journal Name
Al–bahith Al–a'alami
paratexte in specialized literary journals : AL ADEEB AL IRAQI magazine is a model
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Post-structural critical studies highlighted the importance of studying the texts surrounding the text as an important part in the process of receiving and understanding texts, and although this topic was dealt with by the ancient Arabs and Europeans, interest in it appeared clearly after the appearance of Gerard Genet's book (SEUILS), which separated it Text Thresholds. Or what he called paratexte, and dealt with them with interest as he reads them on books. With the development of semiotic studies, interest in paratexte studies began in a broader way and in various literary and non-literary texts, including journalistic texts. And since specialized magazines are one of the press releases that enjoy their privacy in terms of topics and

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Publication Date
Mon Oct 28 2019
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
Heuristic Initialization And Similarity Integration Based Model for Improving Extractive Multi-Document Summarization
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Publication Date
Mon Aug 21 2023
Journal Name
Communications In Mathematical Biology And Neuroscience
Delay in eco-epidemiological prey-predator model with predation fear and hunting cooperation
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It is recognized that organisms live and interact in groups, exposing them to various elements like disease, fear, hunting cooperation, and others. As a result, in this paper, we adopted the construction of a mathematical model that describes the interaction of the prey with the predator when there is an infectious disease, as well as the predator community's characteristic of cooperation in hunting, which generates great fear in the prey community. Furthermore, the presence of an incubation period for the disease provides a delay in disease transmission from diseased predators to healthy predators. This research aims to examine the proposed mathematical model's solution behavior to better understand these elements' impact on an eco-epidemi

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Publication Date
Wed Aug 28 2024
Journal Name
Mesopotamian Journal Of Cybersecurity
A Novel Anomaly Intrusion Detection Method based on RNA Encoding and ResNet50 Model
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Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

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Publication Date
Wed Aug 28 2024
Journal Name
Mesopotamian Journal Of Cybersecurity
A Novel Anomaly Intrusion Detection Method based on RNA Encoding and ResNet50 Model
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Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

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Publication Date
Wed Jun 15 2022
Journal Name
Journal Of Sensors
A Modern Approach towards an Industry 4.0 Model: From Driving Technologies to Management
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Every so often, a confluence of novel technologies emerges that radically transforms every aspect of the industry, the global economy, and finally, the way we live. These sharp leaps of human ingenuity are known as industrial revolutions, and we are currently in the midst of the fourth such revolution, coined Industry 4.0 by the World Economic Forum. Building on their guideline set of technologies that encompass Industry 4.0, we present a full set of pillar technologies on which Industry 4.0 project portfolio management rests as well as the foundation technologies that support these pillars. A complete model of an Industry 4.0 factory which relies on these pillar technologies is presented. The full set of pillars encompasses cyberph

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Publication Date
Sat Aug 02 2025
Journal Name
Engineering, Technology &amp; Applied Science Research
A New Method for Face-Based Recognition Using a Fuzzy Face Deep Model
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Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

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