Summary: This study aims to examine the names of four-legged animals found in Turkish translations of the Qur’an written between the 11th and 15th centuries from linguistic, etymological, and semantic perspectives. These translations, belonging to the Old Anatolian Turkish period, serve not only as religious texts but also as valuable documents reflecting the social structure, cultural values, and linguistic features of the time. Within the scope of this research, six major tafsir (exegesis) texts were systematically analyzed, and the data obtained were evaluated within historical and cultural contexts. The theoretical framework of the study is based on Lakoff and Johnson’s Conceptual Metaphor Theory and Wierzbicka’s approach to lingu

The physical substance at high energy level with specific circumstances; tend to behave harsh and complicated, meanwhile, sustaining equilibrium or non-equilibrium thermodynamic of the system. Measurement of the temperature by ordinary techniques in these cases is not applicable at all. Likewise, there is a need to apply mathematical models in numerous critical applications to measure the temperature accurately at an atomic level of the matter. Those mathematical models follow statistical rules with different distribution approaches of quantities energy of the system. However, these approaches have functional effects at microscopic and macroscopic levels of that system. Therefore, this research study represents an innovative of a wi

The most important environmental constraints at the present time
is the accumulation of glass waste (transparent glass bottles). A lot of
experiments and research have been made on waste and recycling
glass to get use it as much as possible. This research using recycling
of locally waste colorless glass to turn them into raw materials as
alternative of certain percentages of cement to save the environment
from glass waste and reduce some of the disadvantages of cement
with conserving the mechanical and physical properties of concrete
made. A set of required samples were prepared for mechanical test
with different weight percentage of waste glass (2%, 4%, 5%, 6%,
8%, 10%, 15%, 20% and 25%). American standard

The ground level ozone concentration at different locations in Baghdad city was identified. Five
different sites have been chosen to identify the ground level ozone concentration. Al- Dora and Al-
Za'afarania were chosen as areas contained point source ( power plant station ) in addition to high traffic
load , while Al –Uma park, Aden square and Al-Mawal square were chosen as area contained heavy
traffic only (line source). The measurement focuses on spring and fall because these periods display
favorable meteorology to ozone formation. During the research period the maximum values (peaks) for
ground level ozone concentration were observed at fall: at Al-Za'afarania area 101ppb as an average, at
Al-Dora 87 ppb as a

The aim of this paper is to measure the characteristics properties of 3 m radio telescope that installed inside Baghdad University campus. The measurements of this study cover some of the fundamental parameters at 1.42 GHz. These parameters concentrated principally on, the system noise temperature, signal to noise ratio and sensitivity, half power beam width, aperture efficiency, and effective area. These parameters are estimated via different radio sources observation like Cas-A, full moon, sky background, and solar drift scan observations. From the results of these observations, these parameters are found to be approximately 64 K, 1.2, 0.9 Jansky, 3.7°, 0.54, and 3.8 m2 respectively. The parameters values have vital affect to quantitativ

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct