Abstract The purpose of the study is to develop self-attendance fear measures for table tennis players and tennis players with disabilities, as well as to gauge how severe these fears are in both groups. The authors propose that there are no statistically significant differences in the level of fear of self-attendance for players of ground tennis and table tennis for the disabled between the arithmetic mean and the hypothetical mean. In keeping with the nature of the current study, we adopted a descriptive methodology, and the sample comprised 62 players of table tennis and tennis for the disabled. The authors make use of the Al-Taei prepared scale (fears of selfattendance). The statistical package for educational sciences (spss v 26)

Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,

This study aims to identify the forgiveness level among gifted students and its relation to the self-awareness. The study sample consisted of (207) students were randomly chosen, they are integrated in secondary schools in Abha / Saudi Arabia. The correlative, analytical descriptive method was adopted. Two scales were adopted by the researcher: The forgiveness scale prepared by Rye et al (2001) which translated to Arabic by Al-Mahasneh (2017) and the self-awareness scale which prepared by Al-Ghezwani (2017). The study results indicated the following: the forgiveness level among the talented students was high, the self-awareness level among talented students was high, and there is a positive statistically significant relationship

The psychological scientific studies suggest that basic human situations stem from human emotional abilities and those with a lack of emotional intelligence are unable to cope with life, which might lead to anxiety and psychological depression. The current study aimed to investigate this problem by identifying the level of emotional intelligence and psychological depression among the students of the University of Anbar. To achieve the objectives of the study, the researchers created two questionnaires: 1) to measure emotional intelligence. 2) to measure psychological depression and applied these questionnaires on (300) students. The results revealed that the participants showed a high level of emotional intelligence with a low level of p

This study assesses the short-term and long-term interactions between firm performance, financial education and political instability in the case of Malaysia Small to Medium Enterprises (SMEs). The simultaneous insertion of financial education and political instability within the study is done intentionally to inspect the effect of these two elements in one equation for the Malaysian economy. Using the bound testing methodology for cointegration and error correction models, advanced within an autoregressive distributed lag (ARDL) framework, we examine whether a long-run equilibrium connection survives between firm performance and the above mentioned independent variables. Using this method, we uncover evidence of a positive long-term link b

The study deals with China's soft power and diplomacy in the Middle East, and it focuses specifically on the tools and foundations of China's soft diplomacy and how it achieves its goals in the region in addition to its challenges in the region. In this regard, the study also focuses on the Chinese Belt and Road Initiative and its soft foundations and how they serve China’s diplomacy and soft power in the region. The study ends with a set of conclusions, perhaps the most prominent of which is that diplomacy and soft power have become a fundamental pillar of China's foreign policy to achieve its foreign goals and to establish an international system compatible with China's principles. As for the Middle East, China has established a poli

          Melanoidins can be diagnosed using the Fourier transform infrared (FTIR) technique. UV/Vis is an effective tool for both qualitative and quantitative analysis of chemical components in melanoidin polymers. The structural and vibrational features of melanoidin synthesized from D-glucose and D-fructose are identical, according to FTIR spectra, with the only difference being the intensity of bands.  Using FTIR spectra, the skeleton of melanoidin is divided into seven major regions. The existence of the C=C, C=N, and C=O groups in all melanoidins formed from fructose and glucose with ammonia is confirmed by the areas ranging from 1600 to 1690 cm^-1, and the band is largely evident as a broad shoulder. Both melan

Do’a and Zikr al-Mā’thur (authentic supplications and remembrance of ALLAH ‘Azza wa Jalla) can be suggested to Muslims to help them deal with challenges or issues in life. Counselling cases affect a person’s feelings. Do’a and Zikr al-Mā’thur are often applied as a counselling intervention. Unfortunately, the authentic Do’a and Zikr al-Mā’thur are dispersed in many resources not visible to users, and the fact that not all online resources offer access to accurate Do’a and Zikr al-Mā’thur to users and the dubious Do’a and Zikr al-Mā’thur frequently credited to the Prophet (pbuh). The goal of this research is to develop an ontology

Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med