The paper discusses the structural and optical properties of In2O3 and In2O3-SnO2 gas sensor thin films were deposited on glass and silicon substrates and grown by irradiation of assistant microwave on seeded layer nucleated using spin coating technique. The X-ray diffraction revealed a polycrystalline nature of the cubic structure. Atomic Force Microscopy (AFM) used for morphology analysis that shown the grain size of the prepared thin film is less than 100 nm, surface roughness and root mean square for In2O3 where increased after loading SnO2, this addition is a challenge in gas sensing application. Sensitivity of In2O3 thin film against NO2 toxic gas is 35% at 300oC. Sensing properties were improved after adding Tin Oxide (SnO2) to be mo

The present paper is an experimental study to improve the productivity of the conventional solar still. This done by modifying conventional still in a way that the distilled basin is larger than distillation basin, thus providing an increase in the condensation surface and speeding up the condensation process. Moreover, increase in the dimensions of the distilled base helps coupling reflective panels to the distilled base to reflect incident solar radiation to the distillation basin. For this purpose , two solar stills were made, one conventional designand another made according to the proposed design. The two solar stills were tested during the period from February to July 2009 under varying weather conditions of Basra, Iraq (latitude o

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

The current research aims to determine the necessary linguistic competencies for Arabic language teachers of the preparatory stage (fourth grade preparatory), which were five main competencies: Arabic grammar competencies, literary competencies, cultural competencies, rhetorical competencies, and expression competencies. To achieve the objective of the research, the researcher developed a questionnaire as the main tool for collecting data based on literature, it consists of (28) items including the five main competencies. The questionnaire was administered to (60) male and female teachers at Al-Karkh's first Education Directorate in the city of Baghdad. The findings of the research indicated that Arabic language proficiency got the highe

The study aimed to find out the degree of practicing Arabic language teachers in the preparatory stage of higher-order thinking skills from their point of view in the first, second and third Baghdad Rusafa directorates of education. The descriptive survey method was used. The study population consisted of teachers of the Arabic language in the directorates of Baghdad, Rusafa, First, Second and Third, and the sample number was (284) teachers. A questionnaire was built on higher-order thinking skills. The validity and reliability of the tool were verified, after which the scale was applied to the research sample of (116) schools and (168) teachers who were randomly selected from the schools affiliated to the Baghdad Education Directorates Rus