People with blindness or low vision utilize mobile assistive tools for various applications such as object recognition, text recognition, etc. Most of the available applications are focused on recognizing generic objects. And they have not addressed the recognition of food dishes and fruit varieties. In this paper, we propose a smartphone-based system for recognizing the food dishes as well as fruits for children with visual impairments. The Smartphone application utilizes a trained deep CNN model for recognizing the food item from the real-time images. Furthermore, we develop a new deep convolutional neural network (CNN) model for food recognition using the fusion of two CNN architectures. The new deep CNN model is developed using the ensemble learning approach. The deep CNN food recognition model is trained on a customized food recognition dataset.The customized food recognition dataset consists of 29 varieties of food dishes and fruits. Moreover, we analyze the performance of multiple state of art deep CNN models for food recognition using the transfer learning approach. The ensemble model performed better than state of art CNN models and achieved a food recognition accuracy of 95.55 % in the customized food dataset. In addition to that, the proposed deep CNN model is evaluated in two publicly available food datasets to display its efficacy for food recognition tasks.

Mental disorders can significantly impact children's lives and affect their emotional, cognitive, and behavioral development. Family support and care is critical to the well-being of children, particularly children with mental disorders. However, given the “gap” between research and practice“,” there have been very few studies in the Arab region that focus on the role of the family in supporting children with mental disorders. The study also examines how families cope with caring for a person with mental disorders and what behaviors may influence the patient's distress. In addition, the study will examine the importance of family rehabilitation and integration of people with mental disorders into society. The study adopts the descriptive-analytical method and uses a questionnaire to gather data from the participants. The 350-parents sample (with 113 boys, 237 girls) was selected from the Shafallah Center for Integrating People with Disability. Morgan's law is used to determine the sample size. The results show that there are statistically significant differences in the role of family members in supporting people with mental disorders due to two variables: Gender and Work. Age has no statistically significant effect on the role of family members in supporting people with mental disorders. This study is the first study conducted to investigate the role of family in supporting children with mental disorders in the Gulf Cooperation Council (GCC) in general and Qatar in particular. The results show that families should cope with the needs of a person with a mental disorder. Family rehabilitation is important in the care of people with mental disorders. There are certain behaviors of family members that can increase or decrease stress for the person. The results suggest that the family plays an essential role in supporting and promoting the lives of people with mental disorders and recommending effective ways to cope with them.

This study aimed to examine the psychometric properties of the Arabic version of a short version of the Reinforcement Sensitivity Theory of Personality Questionnaire (RST-PQ-S) among a sample of 700 patients with anxiety disorders (53.1% were female). Participants completed the RST-PQ-S, NEO-FFI, Positive Mental Health (PMH), and Kessler Psychological Distress scale. Both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were employed to test the construct validity of the scale. This study also utilized a network perspective, incorporating Exploratory Graph Analysis (EGA) and centrality measures. As a result of the EFA and CFA, it was determined that the scale consists of 22 items and six subdimensions. These subdimensions were named as follows: “Flight Fight-Freeze System”, “Behavioral Inhibition System”, “Reward Interest”, “Reward Reactivity”, “Goal-Drive Persistence”, and “Impulsivity”. Additionally, the network analysis’s findings confirmed the six-factor structure derived from the construct validity assessment. The results of this study demonstrated that the Arabic version of the personality scale is a valid and reliable tool for assessing personality in Arabic-speaking individuals with anxiety disorders. It has the potential to serve as an important diagnostic instrument in clinical and research settings. These findings may assist psychologists and clinicians in Arabic-speaking countries to better understand how the personality traits and anxiety disorders are related.