In this paper, the process of comparison between the tree regression model and the negative binomial regression. As these models included two types of statistical methods represented by the first type "non parameter statistic" which is the tree regression that aims to divide the data set into subgroups, and the second type is the "parameter statistic" of negative binomial regression, which is usually used when dealing with medical data, especially when dealing with large sample sizes. Comparison of these methods according to the average mean squares error (MSE) and using the simulation of the experiment and taking different sample

In The Name of Allah Most Gracious Most Merciful

The reason for choosing this topic was:

First: It is my great love for the Prophet Muhammad, may God’s prayers and peace be upon him, his family, his companions, his followers, the followers of their followers, and the scholars after them until the Day of Judgment.

Secondly: Showing a great jurisprudential figure who has contributed by speaking about important jurisprudential issues in the life of this nation, and bringing out this immortal book to put it in the hands of scholars, so I chose a figure from the followers (may God be pleased with them all).

Third: The study of the jurisprudence of the companions

The present study aims at scrutinizing the impoliteness types, causes, and purposes utilized by Iraqi English language learners when refusing marriage proposals. Thus, it attempts to answer the questions: (1) what are the impoliteness formulas used by the Iraqi learners of English in refusing marriage proposals?, and (2) What are their impoliteness triggers/causes and the purposes? The study is significant in bridging the gap that few linguistic types of research concentrate on studying intentionality and emotions allied with impoliteness. Data were collected from 35 Iraqi learners of English responding to 6 situations of marriage. The data were analyzed using Culpeper’s (2011) formulas of impoliteness and Bousfield’s (2007) impolite

Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

 

This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

The present study aims at scrutinizing the impoliteness types, causes, and purposes utilized by Iraqi English language learners when refusing marriage proposals. Thus, it attempts to answer the questions: (1) what are the impoliteness formulas used by the Iraqi learners of English in refusing marriage proposals?, and (2) What are their impoliteness triggers/causes and the purposes? The study is significant in bridging the gap that few linguistic types of research concentrate on studying intentionality and emotions allied with impoliteness. Data were collected from 35 Iraqi learners of English responding to 6 situations of marriage. The data were analyzed using Culpeper’s (2011) formulas of impoliteness and Bousfield’s (2007) imp

The automatic estimation of speaker characteristics, such as height, age, and gender, has various applications in forensics, surveillance, customer service, and many human-robot interaction applications. These applications are often required to produce a response promptly. This work proposes a novel approach to speaker profiling by combining filter bank initializations, such as continuous wavelets and gammatone filter banks, with one-dimensional (1D) convolutional neural networks (CNN) and residual blocks. The proposed end-to-end model goes from the raw waveform to an estimated height, age, and gender of the speaker by learning speaker representation directly from the audio signal without relying on handcrafted and pre-computed acou