Assessment of Nutrition Knowledge and Dietary Behaviors of Post Bariatric Surgery Patients Attending the Outpatient Clinic of Rashid Hospital, Dubai

Obesity is regarded as an increasingly prevalent public health problem, with enormous adverse health consequences. It also increases the risk for co-morbidities. There are several means to treat obesity, and bariatric surgery has emerged as one of the most prevalent ways to treat obesity. Despite the vast research assessing nutrition knowledge of patients regarding several health conditions, existing research assessing the nutrition knowledge of post-bariatric surgery patients is limited, although this category of patients is very susceptible to malnutrition post-surgery. The aim of this study was to assess the patients’ general nutrition knowledge and the knowledge specific to the dietary protocol post-surgery. This study also assessed the medical and nutritional complications associated with bariatric surgery, including patients’ awareness and understanding of dumping syndrome, patients’ perception of the clarity of information conveyed by the dietitians and its effect on their levels of compliance with post-surgery dietary protocol and the follow- up appointments with the dietitians. Results of this study showed that patients had good general nutrition knowledge. The questions assessing nutrition knowledge of the dietary protocol showed that the majority of the participants (66.2%) had average knowledge. In addition, most patients did not know what dumping syndrome is, and of those who knew what it is, only had knowledge about the food that promotes its occurrence. On the other hand, most patients followed up with a dietitian, although only 29% showed strong compliance to the dietitian’s instructions. This was strongly related to majority of patients (71.2%) finding the information conveyed as vague and unclear. The most experienced symptom post-bariatric surgery was nausea, followed by dizziness, dehydration, and vomiting. As for the overall quality of life, most of the patients never felt agitated, fatigued and/or regretted their decision of undergoing the surgery, and almost all participants found their daily activities to be more enjoyable. Future research on the relation of compliance to dietary protocol and improved quality of patients’ life post bariatric surgeries to extend our findings is needed

Anti-spoofing using challenge-response user interaction

2D facial identification has attracted a great amount of attention over the past years, due to its several advantages including practicality and simple requirements. However, without its capability to recognize a real user from an impersonator, face identification system becomes ineffective and vulnerable to spoof attacks. With the great evolution of smart portable devices, more advanced sorts of attacks have been developed, especially the replayed videos spoofing attempts that are becoming more difficult to recognize. Consequently, several studies have investigated the types of vulnerabilities a face biometric system might encounter and proposed various successful anti-spoofing algorithms. Unlike spoofing detection for passive or motionless authentication methods that were profoundly studied, anti-spoofing systems applied on interactive user verification methods were broadly examined as a potential robust spoofing prevention approach. This study aims first at comparing the performance of the existing spoofing detection techniques on passive and interactive authentication methods using a more balanced collected dataset and second proposes a fusion scheme that combines both texture analysis with interaction in order to enhance the accuracy of spoofing detection

Incorporated model of deep features fusion

Abdelaziz, A., & Mahmoud, A. N. (2022). Skin Cancer Detection Using Deep Learning and Artificial Intelligence: Incorporated model of deep features fusion. Fusion: Practice and Applications, 8(2), 8-15. https://doi.org/10.54216/FPA.080201 © 2022, American Scientific Publishing Group (ASPG). All rights reserved.Among the most frequent forms of cancer, skin cancer accounts for hundreds of thousands of fatalities annually throughout the globe. It shows up as excessive cell proliferation on the skin. The likelihood of a successful recovery is greatly enhanced by an early diagnosis. More than that, it might reduce the need for or the frequency of chemical, radiological, or surgical treatments. As a result, savings on healthcare expenses will be possible. Dermoscopy, which examines the size, form, and color features of skin lesions, is the first step in the process of detecting skin cancer and is followed by sample and lab testing to confirm any suspicious lesions. Deep learning AI has allowed for significant progress in image-based diagnostics in recent years. Deep neural networks known as convolutional neural networks (CNNs or ConvNets) are essentially an extended form of multi-layer perceptrons. In visual imaging challenges, CNNs have shown the best accuracy. The purpose of this research is to create a CNN model for the early identification of skin cancer. The backend of the CNN classification model will be built using Keras and Tensorflow in Python. Different network topologies, such as Convolutional layers, Dropout layers, Pooling layers, and Dense layers, are explored and tried out throughout the model's development and validation phases. Transfer Learning methods will also be included in the model to facilitate early convergence. The dataset gathered from the ISIC challenge archives will be used to both tests and train the model.publishersversionpublishe

Statistical Analysis for Revealing Defects in Software Projects: Systematic Literature Review

Mahmoud, A. N., & Santos, V. (2021). Statistical Analysis for Revealing Defects in Software Projects: Systematic Literature Review. International Journal of Advanced Computer Science and Applications, 12(11), 237-249. https://doi.org/10.14569/IJACSA.2021.0121128Defect detection in software is the procedure to identify parts of software that may comprise defects. Software companies always seek to improve the performance of software projects in terms of quality and efficiency. They also seek to deliver the soft-ware projects without any defects to the communities and just in time. The early revelation of defects in software projects is also tried to avoid failure of those projects, save costs, team effort, and time. Therefore, these companies need to build an intelligent model capable of detecting software defects accurately and efficiently. The paper is organized as follows. Section 2 presents the materials and methods, PRISMA, search questions, and search strategy. Section 3 presents the results with an analysis, and discussion, visualizing analysis and analysis per topic. Section 4 presents the methodology. Finally, in Section 5, the conclusion is discussed. The search string was applied to all electronic repositories looking for papers published between 2015 and 2021, which resulted in 627 publications. The results focused on finding three important points by linking the results of manuscript analysis and linking them to the results of the bibliometric analysis. First, the results showed that the number of defects and the number of lines of code are among the most important factors used in revealing software defects. Second, neural networks and regression analysis are among the most important smart and statistical methods used for this purpose. Finally, the accuracy metric and the error rate are among the most important metrics used in comparisons between the efficiency of statistical and intelligent models.publishersversionpublishe

Statistical Analysis for Revealing Defects in Software Projects

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementDefect detection in software is the procedure to identify parts of software that may comprise defects. Software companies always seek to improve the performance of software projects in terms of quality and efficiency. They also seek to deliver the soft-ware projects without any defects to the communities and just in time. The early revelation of defects in software projects is also tried to avoid failure of those projects, save costs, team effort, and time. Therefore, these companies need to build an intelligent model capable of detecting software defects accurately and efficiently. This study seeks to achieve two main objectives. The first goal is to build a statistical model to identify the critical defect factors that influence software projects. The second objective is to build a statistical model to reveal defects early in software pro-jects as reasonable accurately. A bibliometric map (VOSviewer) was used to find the relationships between the common terms in those domains. The results of this study are divided into three parts: In the first part The term "software engineering" is connected to "cluster," "regression," and "neural network." Moreover, the terms "random forest" and "feature selection" are connected to "neural network," "recall," and "software engineering," "cluster," "regression," and "fault prediction model" and "software defect prediction" and "defect density." In the second part We have checked and analyzed 29 manuscripts in detail, summarized their major contributions, and identified a few research gaps. In the third part Finally, software companies try to find the critical factors that affect the detection of software defects and find any of the intelligent or statistical methods that help to build a model capable of detecting those defects with high accuracy. Two statistical models (Multiple linear regression (MLR) and logistic regression (LR)) were used to find the critical factors and through them to detect software defects accurately. MLR is executed by using two methods which are critical defect factors (CDF) and premier list of software defect factors (PLSDF). The accuracy of MLR-CDF and MLR-PLSDF is 82.3 and 79.9 respectively. The standard error of MLR-CDF and MLR-PLSDF is 26% and 28% respectively. In addition, LR is executed by using two methods which are CDF and PLSDF. The accuracy of LR-CDF and LR-PLSDF is 86.4 and 83.8 respectively. The standard error of LR-CDF and LR-PLSDF is 22% and 25% respectively. Therefore, LRCDF outperforms on all the proposed models and state-of-the-art methods in terms of accuracy and standard error

The Role of Najran University in Spreading the Culture of Entrepreneurship and Innovation in Achieving the Goals of Sustainable Development Among Students

Purpose: Therefore, the study aimed to identify the role of Najran University in spreading the culture of entrepreneurship and innovation in achieving sustainable development goals among students, and the statistical differences therein according to the variables of gender, type of college, and academic year.   Theoretical Framework: The culture of entrepreneurship and innovation is an important and valuable resource in achieving sustainable development goals in society. It is one of the main pillars and its driving force and one of the outlets for creating economic and social efficiency, innovation, and creativity among members of society. It is also one of the most important incubators to provide job opportunities for students and youth in the future, eradicate poverty and unemployment, and move towards free entrepreneurial work.   Design/Methodology/Approach: The study used the descriptive approach by a survey method through a questionnaire, which consisted, of (27) items distributed in three main dimensions: the university's vision, mission, and goals, university leadership and support, and education and partnership for entrepreneurship and innovation, after verifying validity and reliability indications. The study sample consisted of (378) male and female students, of whom (186) male and (192) female students were selected from Najran University in the Kingdom of Saudi Arabia. To conclude, descriptive statistical methods were used, "means and standard deviations" and parametric statistical analysis methods, such as the t-test for independent samples, one-way analysis of variance, and post-comparison by Scheffe's method.   Findings:   The results showed an average level in the role of the University of Najran in spreading the culture of entrepreneurship and innovation in achieving sustainable development goals among students at the total score and all areas of the study tool. The results also revealed statistically significant differences in the responses of the study sample about the level of the role of Najran University in spreading the culture of entrepreneurship and innovation in achieving the goals of sustainable development among students due to the variable of the academic year; the differences were in favor of students in the third and fourth years or more. In addition, there were no statistically significant differences in the variables of gender and type of college.   Practical Implications: The study implicates for need of spreading rhe culture of entrepreneurship and innovation in achieving sustainable development goals among university students.   Originality/Value:  The study identifies the role of Najran University in spreading the culture of entrepreneurship and innovation in achieving sustainable development goals among students

تداعيات العقوبات الاقتصادية أحادية الجانب على الاقتصاد السوريّ "العقوبات الأميركية أنموذجاً"

إن العقوبات الاقتصادية تعتبر من أبرز الوسائل غير العسكرية التي تستخدمها الدول الكبرى كأداة لتنفيذ مخططاتها السياسية والاقتصادية، ولقد اتبعت الولايات المتحدة الأميركية هذه الوسيلة في أغلب الأحيان ضد الدول التي تخالف سياستها والنهج الذي تسير عليه، وتعتبر سورية أنموذجاً واضحاً حيث حاولت الولايات المتحدة الأميركية تطويعها بما يتفق مع أهدافها السياسية والاقتصادية إلا أن رفض سورية لذلك جعل منها هدفاً أساسيً من قبلها تفرض عليها تلك العقوبات الانفرادية غير الشرعية منذ عام 1979 وحتى الآن متذرعة بذلك بعدة حجج حيث اتجهت في بعض الأحيان إلى اتهام سورية بأنها داعمة للإرهاب وتارة أخرى بحجة حماية المواطنين السوريين وغيرها من الحجج غير المقبولة، وكان من أبرز تلك العقوبات قانون قيصر الأميركي الذي شمل ببنوده جميع القطاعات الاقتصادية وكافة الشركاء الذي كان من الممكن أن يقدموا دعماً لسورية وخاصة في ظل الحرب الكونية عليها. كل ذلك كان له تأثير سلبي على أبرز مؤشرات الاقتصاد السوري كالناتج المحلي الإجمالي وبدوره هذا سلب من المواطن السوري أبسط حقوقه كحقه في الحصول على غذاء ومأوى وحقه في العيش الكريم، ولذلك كان ثمة حاجة ملحة لدراسة أثر تلك العقوبات الانفرادية على سورية بصفة عامة، وعلى المواطن السوري بصفة خاصة

تداعيات العقوبات الاقتصادية أحادية الجانب على الاقتصاد السوريّ "العقوبات الأميركية أنموذجاً"

إن العقوبات الاقتصادية تعتبر من أبرز الوسائل غير العسكرية التي تستخدمها الدول الكبرى كأداة لتنفيذ مخططاتها السياسية والاقتصادية، ولقد اتبعت الولايات المتحدة الأميركية هذه الوسيلة في أغلب الأحيان ضد الدول التي تخالف سياستها والنهج الذي تسير عليه، وتعتبر سورية أنموذجاً واضحاً حيث حاولت الولايات المتحدة الأميركية تطويعها بما يتفق مع أهدافها السياسية والاقتصادية إلا أن رفض سورية لذلك جعل منها هدفاً أساسيً من قبلها تفرض عليها تلك العقوبات الانفرادية غير الشرعية منذ عام 1979 وحتى الآن متذرعة بذلك بعدة حجج حيث اتجهت في بعض الأحيان إلى اتهام سورية بأنها داعمة للإرهاب وتارة أخرى بحجة حماية المواطنين السوريين وغيرها من الحجج غير المقبولة، وكان من أبرز تلك العقوبات قانون قيصر الأميركي الذي شمل ببنوده جميع القطاعات الاقتصادية وكافة الشركاء الذي كان من الممكن أن يقدموا دعماً لسورية وخاصة في ظل الحرب الكونية عليها. كل ذلك كان له تأثير سلبي على أبرز مؤشرات الاقتصاد السوري كالناتج المحلي الإجمالي وبدوره هذا سلب من المواطن السوري أبسط حقوقه كحقه في الحصول على غذاء ومأوى وحقه في العيش الكريم، ولذلك كان ثمة حاجة ملحة لدراسة أثر تلك العقوبات الانفرادية على سورية بصفة عامة، وعلى المواطن السوري بصفة خاصة

The Effect of Television and Electronic Advertisements on The Mental Image of Women Among A Group of Female Media Professionals

The study aimed to know the effect of television and electronic advertisements broadcast on Arab television screens and on websites on the mental image formed by a group of female media professionals affiliated with the Arab Media Center about women, by answering the sub-questions of the study, the study adopted the descriptive approach through the study tool, which is the questionnaire designed to answer the questions of the study through the respondents, that consisted of 200 female individuals who watch TV advertisements and follow them on the website, and after filling out the questionnaires, analyzing and interpreting them, the following conclusions were reached, the reasons for the respondent’s viewing of advertisements varied, but the largest percentage 94%, was that they watch advertisements involuntarily while watching TV or electronically presented material. This is what is classified as accidental exposure. The percentage of those who believe that the use of women in advertising greatly distorts the image of women is 66.5%. 91% of respondents agreed that women's rights associations and organizations must exert pressure to preserve the image of women and to educate society about their true role through various media, with a rate of 89.5%, the respondents expressed that they were shy when watching an advertisement that aroused in front of family members. 89% of the respondents believe that the ads that appear on social media and YouTube contain in their content greater freedom, and therefore the size of their distance from Arab values is greater, and in the same percentage came the emphasis on the need for some competent authorities to implement training courses for Arab ad directors to comply with our customs and traditions. The percentage of supporters decreased to 30% for the idea that advertising can only be successful by showing the charms of women, the woman's mind by presenting her as a consumer who does not care and only thinks about her elegance and beauty 30%. The study recommended that if a woman must appear in the advertisement, then this appearance should be appropriate to her reality and reflect the real role of women in society. Women's rights associations and organizations must exert pressure to preserve the image of women and educate society about their true role through the various media

Formulation, evaluation and optimization of miconazole nitrate tablet prepared by foam granulation technique

The aim of our study was to utilize novel foam granulation technique in formulation of miconazole nitrate; a model hydrophobic drug as oral disintegrating tablets "ODT" particularly to enhance its bioavailability. Foam granulation technique has additional advantages over the other traditional granulation technique since; it enhances the granulation process and produce acceptable tablets. Fractional factorial design was used to investigate the effect of formulation and processing variables on the prepared miconazole ODT. The prepared granules were evaluated by measuring their density, flowability, granules size and shape, and granules wetting time. The quality attributes of the prepared tablets; drug content, tablet thickness, uniformity of weight, tablet tensile strength, friability, disintegration, and dissolution were also evaluated. The results indicated that, the prepared granules showed acceptable characteristics and is significantly affected by the disintegrant type, urea concentration, and the lubricant type. The quality attributes of the tablets were not affected by the processing parameters. From the prepared formulas; F20, F19, F12, and F20 displayed 18, 35, 35, and 40 seconds disintegration time respectively and the percent of dissolution after 15 minutes ranged from 94.4-100%. These results ascertained that foam granulation technique fulfill the requirement in preparation of miconazole ODT. Key words: miconazole nitrate, foam granulation, oral disintegrating tablet