Abstract:

The models of time series often suffer from the problem of the existence of outliers ​​that accompany the data collection process for many reasons, their existence may have a significant impact on the estimation of the parameters of the studied model. Access to highly efficient estimators  is one of the most important stages of statistical analysis, And it is therefore important to choose the appropriate methods to obtain good  estimators. The aim of this research is to compare the ordinary estimators and the robust estimators of the estimation of the parameters of

Digital change detection is the process that helps in determining the changes associated with land use and land cover properties with reference to geo-registered multi temporal remote sensing data. In this research change detection techniques have been employed to detect the changes in marshes in south of Iraq for two period the first one from 1973 to 1984 and the other from 1973 to 2014 three satellite images had been captured by land sat in different period. Preprocessing such as geo-registered, rectification and mosaic process have been done to prepare the satellite images for monitoring process. supervised classification techniques such maximum likelihood classification has been used to classify the studied area, change detection aft

Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c

The effect of different doping ratio (0.3, 0.5, and 0.7) with thickness in the range 300nmand annealed at different temp.(Ta=RT, 473, 573, 673) K on the electrical conductivity and hall effect measurements of AgInTe2thin film have and been investigated AgAlxIn(1-x) Te2 (AAIT) at RT, using thermal evaporation technique all the films were prepared on glass substrates from the alloy of the compound. Electrical conductivity (σ), the activation energies (Ea1, Ea2), Hall mobility and the carrier concentration are investigated as a function of doping. All films consist of two types of transport mechanisms for free carriers. The activation energy (Ea) decreased whereas electrical conductivity increases with increased doping. Results of Hall Effect

    Multivariate Non-Parametric control charts were used to monitoring the data that generated by using the simulation, whether they are within control limits or not. Since that non-parametric methods do not require any assumptions about the distribution of the data.  This research aims to apply the multivariate non-parametric quality control methods, which are Multivariate Wilcoxon Signed-Rank ( ) , kernel principal component analysis (KPCA) and k-nearest neighbor ( −

The game of volleyball requires the formation of new motor responses, which in turn requires special physical characteristics in the performance of that skill, and the correct and accurate performance during the performance of the skills of passing from the top and smash serve in volleyball cannot be developed or improved without a good level of accuracy and what is required to perform the movements in terms of responses to the defense and attack movements. Therefore, the researchers decided to identify the type of relationship between the motor response speed with the performance accuracy of the skills of passing from the top and the smash serve in volleyball. The research aims to: 1. Identifying the motor response speed of fourth-stage s

Background: The value of lateral cephalometric radiographs to evaluate the pharyngeal airway is limited because it provided 2-dimensional (2D) images of complex 3-dimensional (3D) anatomic structures. Three dimensional analyses of the airway volumes are required to understand oral and pharyngeal adaptations in mouth breathing and nasal breathing subjects. The aim of this study was to measure the pharyngeal airway volume and the size of the face, then compare between pharyngeal airway volume in mouth breathing and nasal breathing subjects and find the gender difference in each group, also to study the relation between pharyngeal airway volume and the size of the face. Material and Methods: Fifty patients including 28 males and 22 females wit

When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat