Cognitive radios have the potential to greatly improve spectral efficiency in wireless networks. Cognitive radios are considered lower priority or secondary users of spectrum allocated to a primary user. Their fundamental requirement is to avoid interference to potential primary users in their vicinity. Spectrum sensing has been identified as a key enabling functionality to ensure that cognitive radios would not interfere with primary users, by reliably detecting primary user signals. In addition, reliable sensing creates spectrum opportunities for capacity increase of cognitive networks. One of the key challenges in spectrum sensing is the robust detection of primary signals in highly negative signal-to-noise regimes (SNR).In this paper ,

The purposes of this study are to measure masculine's identification among secondary school students, and to examine the significant differences among secondary school students in respect of students age (16-18) year. The researcher has prepared a questionnaire comprised (25) item to measure masculine identification among students: this scale was applied on (100) student who were selected as a sample from four different school at al-rusafa side in Baghdad. The scale then modified to (23) item to be more consistent. The results revealed that there were no significant differences among students based on the variable of age, and the mean of masculine identification showed a high level than the hypothesized mean.

Different bremsstrahlung spectra from tungsten anode x-ray tube generated at 30, 40 and 50 kV have been examined theoretically and experimentally for an attempt to find a most suitable spectrum to radiograph a test object of 0.01 cm thickness of Cu and Ag. The high contrast using this suitable spectrum is demonstrated and the possible effects of fluorescent radiation are discussed.

Objective(s): To assess the behavior that impedes the eating of children with autism spectrum disorders in Baghdad city, and find out the relationships between the behaviors that impede eating of autistic children and their demographic characteristics.
Methodology: The study started from the period of 16th September 2019 to the 16th of March 2020. A non-probability (purposive) sample of 80 children with autism spectrum disorders was selected. The questionnaire was designed and composed of two parts: the first part includes the autistic children demographic data, the second part includes scales of behavior that impede eating followed by parents towards autistic child. The reliability of the questionnaire was determined through a pilot

n this study, data or X-ray images Fixable Image Transport System (FITS) of objects were analyzed, where energy was collected from the body by several sensors; each sensor receives energy within a specific range, and when energy was collected from all sensors, the image was formed carrying information about that body. The images can be transferred and stored easily. The images were analyzed using the DS9 program to obtain a spectrum for each object,an energy corresponding to the photons collected per second. This study analyzed images for two types of objects (globular and open clusters). The results showed that the five open star clusters contain roughly t

واحدة من أكثر مواد السيراميك الهيكلية الواعدة هي كربيد السيليكون(SiC) ، حيث له خصائص حرارية وكهروميكانيكية ممتازة. هذه الخصائص مفيدة ل CMC لتعزيز أداء المركب خاصة عند إضافات النانو المتكاملة. في هذا البحث, تم تصنيع مركب SiC من SiC بثلاثة تركيزات مع  ZnO و Si. تم اختبار الخواص المغناطيسية لجميع المخاليط باستخدام مراقبة العينة الاهتزازية (VSM). تم تلبيد العينات الخضراء في فرن التلبيد عند 1600 درجة مئوية في بيئة النيتروجي

In this study, the nanocrystal-ZnS-loaded graphene was synthesized by a facile coprecipitation route. The effect of graphene on the characterization of Zinc Sulphide (ZnS) was investigated. The X-ray Diffraction (XRD) results reveal that ZnS has cubic system while hexagonal structure which is observed by loading graphene during the preparation of ZnS. Energy Dispersive X-ray Spectroscopy (EDS) analysis proved the presence of all expected elements in the prepared materials. Nanosize of fabricated materials has been measured using Scanning Electron Microscopy (SEM) technique. This study also found that the graphene plays a critical role in lowering the optical energy gap of ZnS nanoparticles from 4 eV to 3.2 eV. The characterization of detec

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

Research targeted availability of moral anxiety among secondary school students. The research sample consisted of 500 students from the (fifth grade secondary school) scientific and literary branches.
The researcher prepared a measure of moral anxiety which is in its final form of (36) items. The researcher analyzed the data statistically, significant results showed that the sample of the research they have a moral anxiety .
From these results the researcher came up with a number of recommendations and proposals.