Registration techniques are still considered challenging tasks to remote sensing users, especially after enormous increase in the volume of remotely sensed data being acquired by an ever-growing number of earth observation sensors. This surge in use mandates the development of accurate and robust registration procedures that can handle these data with varying geometric and radiometric properties. This paper aims to develop the traditional registration scenarios to reduce discrepancies between registered datasets in two dimensions (2D) space for remote sensing images. This is achieved by designing a computer program written in Visual Basic language following two main stages: The first stage is a traditional registration p

    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

The appearance of Mixed Mode Oscillations (MMOs) and chaotic spiking in a Light Emitting Diode (LED) with optoelectronic feedback theoretically and experimentally have been reported. The transition between periodic and chaotic mixed-mode states has been investigated by varying feedback strength. In incoherent semiconductor chaotically spiking attractors with optoelectronic feedback have been observed to be the result of canard phenomena in three-dimensional phase space (incomplete homoclinic scenarios).

Historical concepts are among the concepts that are difficult to present to the pre-school child except by using modern techniques, as well as the difficulty of making visits to all historical monuments and going back to antiquity and the lack of studies in this area, therefore, we need an attractive medium that children love which is able to convey some abstract concepts that are difficult to teach to children using traditional methods, and among these activities that the kindergarten provides to children are the stories through which they develop their linguistic wealth, consolidate their religious and spiritual inclinations, refine their correct morals, and form their proper attitudes, knowledge and life concepts.

The

The aimes of this study is to investigate Optimism and Pessimism among university undergraduates including the first and fourth stage students ,the sample of this stoudy contained (326) students ,(166) male and (160) female, The researcher adopted a scale of Dember et al (1889) translated and adjusted  to arabic version by Al-Dosoke (2001). The results have shown that   students have  optimism including the first and fourth stage and no significant difference between the students  as far as ncluding the first and fourth  study stage and gender, Implications of the results and recommendations for further research are discussed.

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

The purpose of this paper to discriminate between the poetic poems of each poet depending on the characteristics and attribute of the Arabic letters. Four categories used for the Arabic letters, letters frequency have been included in a multidimensional contingency table and each dimension has two or more levels, then contingency coefficient calculated.

The paper sample consists of six poets from different historical ages, and each poet has five poems. The method was programmed using the MATLAB program, the efficiency of the proposed method is 53% for the whole sample, and between 90% and 95% for each poet's poems.

Use of electrodes that provide a high surface area for reaction, such as Nickel foam and Carbon Fiber Felt, has proven highly efficient in treating wastewater. In this study, a mixture of dyes (Eosin Y, Methylene Blue, and Methylene Violet) was treated using Ni foam as a cathode and carbon fiber felt as an anode in the Electro-Fenton process, relying on iron waste, such as iron filings, as the catalyst source. The analysis characterization of electrodes and iron filings was determined by Energy dispersive X-Ray (EDX) and Scanning electron microscopy (SEM) tests. The results showed high efficiency in decomposing the dye mixture. The highest Re % 96.4591 which attained after accomplishing the experiments based on Response Surface Method (RSM)