Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

This study is attempt to improve thermal isolation through measuring thermal conductivity composite of on polyester resin with fillers of (TiO2, ZnO, Acrylonitril, wood flour Coconut (Wf). The grain size of the fillers is 200 µm. The number of samples is (16) in addition to the virgin sample; these samples are prepared by cast molding method for polyester with filler volume fractions (5%, 10%, 15% and 20%). Shore hardness tests were used to measure the hardness and Lee disk method for thermal conductivity. The experimental results showed that the (20% ZnO) sample has the maximum value of thermal conductivity where (20% w.f) has minimum thermal conductivity .on the other hand (15% ZnO) sample give the maximum value of hardness where (20% w

: Summary The establishment of the modern Iraqi state necessitated the establishment of diplomatic relations with neighboring countries. However, during the British Mandate period, these relations remained under the management of the British Embassy, which assumed responsibility for Iraq's foreign affairs. As the political situation evolved, the Iraqi Ministry of Foreign Affairs began making strenuous efforts to build a competent and effective diplomatic apparatus. Iraqi diplomatic representatives played an active role in strengthening and developing Iraq's foreign relations by implementing the Ministry of Foreign Affairs' directives, which focused on monitoring political, economic, and social developments in neighboring countries. This app

The purpose of this research was to evaluate rice husk functionalized with Mg-Fe-layered double hydroxide (RH-Mg/Fe-LDH) as an adsorbent for the removal of meropenem antibiotic (MA) from an aqueous solution. Several batch experiments were undertaken using various conditions. Based on the results, the optimal Mg/Fe-LDH adsorbent with a pH of 9 and an M2+/M3+ ratio of 0.5 was associated with the lowest particle size (specifically. 11.1 nm). The Langmuir and Freundlich models were consistent with the experimental isotherm data (R2 was 0.984 and 0.993, respectively), and MA’s highest equilibrium adsorption capacity was 43.3 mg/g. Additionally, the second-order model was consistent with the adsorption kinetic results.

In this paper, the using of Non-Homogenous Poisson Processes, with one of the scientific and practical means in the Operations Research had been carried out, which is the Queuing Theory, as those operations are affected by time in their conduct by one function which has a cyclic behavior, called the (Sinusoidal Function). (M_t / M / S) The model was chosen, and it is Single Queue Length with multiple service Channels, and using the estimating scales (QL_s, HOL, HOL_r) was carried out in considering the delay occurring to the customer before his entrance to the service, with the comparison of the best of them in the cases of the overload.

Through the experiments

According to grammarians In ( نإ) and Itha (اذإ) are conditionals and sometimes they may be used interchangeably. However, when they are mentioned in the Holy Qur’an, they have their own specific use. This paper attempts to investigate their meanings in the source language as well as investigate their translations and find out any differences or similarities. The translations that are adopted in this research are as follows: Pickthall, Al-Hilali & Khan, and Shakir.