Research Title: Direct control of active and reactive power for a grid-connected single-phase photovoltaic inverter
Author: Emad A. Awada, Published Year: 2021
Faculty: Engineering and Technology

Abstract: This paper presents a single-phase grid-connected photovoltaic system with direct control of active and reactive power through a power management system of a Photovoltaic inverter. The proposed control algorithm is designed to allow maximum utilization of the inverter’s available KVA capacity while maintaining grid power factor and current total harmonic distortion (THD) requirements within the grid standards. To reduce the complexity and improve the efficiency of the system, two independent PI controllers are implemented to control single-phase unipolar PWM voltage source inverter. One controller is used to control the power angle, and hence the active power flow, while the other controller is used to control the reactive power, and consequently the power factor by adjusting the voltage modulation index of the inverter. The proposed system is modelled and simulated using MATLAB/Simulink. The PV inverter has been examined while being simultaneously connected to grid and local load. Results obtained showed the ability of the PV inverter to manage the active and reactive power flow at, and below rated levels of solar irradiances; resulting in an increased inverter utilization factor, and enhanced power quality. The proposed system, was capable of operating at power factors in the range of 0.9 lead or lag for reactive power compensation purposes and delivered its power at a wide range of solar irradiance variations.

Keywords: Distributed generation Grid-connected Maximum power tracking Photovoltaic array Reactive power Renewable energy Single-phase inverter

Research Title: Social RE-PBL: An Approach for Teaching Requirements Engineering Using PBL, SNSs, and Cloud Storages and File-Sharing Services
Author: Lamis Al-Qoran, Published Year: 2021
International Journal of Information and Education Technology, 11
Faculty: Information Technology

Abstract: Requirements engineering process showed that it has the potential to affect software development process and consequently cause unexpected problems in the produced software. Reducing the likelihood of such issues requires proper preparation for software engineering students during their undergraduate studies to reduce the gap between theory and practice. Students must develop the soft skills that are needed to practice software engineering activities, especially requirements engineering. Accordingly, encouraging students to learn and practice requirements engineering concepts and activities are required. Students undertake the requirements engineering course in one semester, where the lecturer focuses on delivering the theoretical concepts to students which creates teacher-centred learning. It is difficult for students to develop the required critical thinking and communication skills that enable them to solve real-world problems in such a teacher-centred environment. This study uses Project-Based Learning (PBL), Social Networking Sites (SNSs) and cloud enhanced communication to design a non-traditional teaching approach to improve students’ learning and to achieve a learner-centred learning environment in a requirements engineering course. The developed approach was applied to a requirements engineering course at our university to investigate its effectiveness and its impact on students’ learning ability. The students in the investigational group learned with the new method; however, the students in the control group learned with the traditional learning method. The results of our experiment show that the proposed approach significantly improved the achievement, motivation and attitude of our students as well as their ability to approach and solve real-world problems.

Keywords: Project-based learning, RE education, social networks sites (SNSs) for education, teaching requirements engineering.

Research Title: Education for Sustainable Development: A Qualitative Analytical Study on the Impact of the Jordanian Universities’ Role in Supporting Innovation among University Students
Author: Amani Ghazi Jarrar, Published Year: 2021
International Journal of Higher Education, 10
Faculty: Arts

Abstract: This study aimed at exploring and theorizing the role of Jordanian Universities in supporting innovation among university students within the context of education for sustainable development from the point of view of Jordanian University students. For that, the researcher adopted the grounded theory methodology by Strauss and Corbin. The study was conducted at two Jordanian Universities: the University of Jordan and Philadelphia University in the academic year (2019-2020), and the study population consisted of students from the two universities. The researcher chose (300) students from both genders from different faculties and academic years. By applying the grounded theory, the study concluded that the key category that emerged after analyzing the student’s responses describing the impact of the Jordanian Universities’ role in supporting innovation among university students for educational sustainable development is the emphasis on the need for developing proper University innovation ecosystems in their educational systems. Also, the respondents- through online interviews - have emphasized this concept of proper University innovation ecosystems. The key category of this study found that positive and negative impacts could result from applying or neglecting to apply this concept, which generated behaviors toward the concept, which could be considered as the phenomena in the current research.

Keywords: Education; Sustainable Development; Jordanian Universities; Innovation.

Research Title: A Genetic Framework model for Self-Adaptive software
Author: Enas Tawfiq Al-Naffar, Published Year: 2017
Faculty: Information Technology

Abstract: Self-adaptive software changes its behavior at runtime without affecting the ‎running system. It has recently been a rich research area. Lots of organizations have adopted it in ‎their environments to accommodate with changing requirements. Lots of bio-inspired research ‎works, which are better than the conventional ones, have been conducted in the area of self-‎adaptive software. All of them have focused on the external behavior of biological entities (like ‎birds, ants, immunity, etc.) without going in depth into their genetic material that causes this ‎behavior and constitutes the challenge the work presented in this paper dealt with. Materials and ‎Methods: This paper proposes a solution to the above current challenge by developing a ‎framework model for self-adaptive software; inspired by the adaptation (evolution) of biological ‎entities and taking into consideration the role of genetic material in the adaptation process. Its scope ‎is limited to changes that take place at runtime but that are known at design. Results: The obtained ‎framework model was evaluated through its reuse in software objects evolution. The practical and ‎theoretical obtained results were valuable in the object-oriented paradigm. The proposed framework ‎completes the others bio-inspired research current works by providing a natural implementing way. ‎The integration of the current bio-inspired approaches (which deal with natural entities behaviors ‎external modeling) with the proposed framework (which deals with genetics-inspired internal ‎modeling of these behaviors) will lead to homogenous and coherent bio-inspired approaches to ‎self-adaptive software. Conclusion: The proposed framework is limited to self-adaptations ‎predicted at the requirements and design steps in self-adaptive software engineering, which is ‎significant in practice. However, the unpredicted adaptation (to unpredicted errors, environment ‎requirements, etc.) will be a genetics-inspired approach real challenge. Separate evaluation of the ‎proposed framework performance is not determinant. However, the performance evaluation of the ‎actual bio-inspired hybrid approaches against the proposed integrated ones (which is impossible to ‎achieve actually) will be valuable. It might be expected that the integrated ones will be better (in the ‎whole self-adaptive software engineering processes) than the hybrid current ones. The homogeneity ‎of approaches has its important impact. ‎

Keywords: Self-adaptive software, Bio-inspired self-adaptive software, Genetics-inspired software modelling

Research Title: Classification and Prediction of Bee Honey Indirect Adulteration Using Physiochemical Properties Coupled with K-Means Clustering and Simulated Annealing-Artificial Neural Networks (SA-ANNs)
Author: Ahmad Jobran Al-Mahasneh, Published Year: 2021
Journal of Food Quality, 2021
Faculty: Engineering and Technology

Abstract: The higher demand and limited availability of honey led to different forms of honey adulteration. Honey adulteration is either direct by addition of various syrups to natural honey or indirect by feeding honey bees with sugar syrups. Therefore, a need has emerged for reliable and cost-effective quality control methods to detect honey adulteration in order to ensure both safety and quality of honey. In this study, honey is adulterated by feeding honey bees with various proportions of sucrose syrup (0 to 100%). Various physiochemical properties of the adulterated honey are studied including sugar profile, pH, acidity, moisture, and color. The results showed that increasing sucrose syrup in the feed resulted in a decrease in glucose and fructose contents significantly, from 33.4 to 29.1% and 45.2 to 35.9%, respectively. Sucrose content, however, increased significantly from 0.19 to 1.8%. The pH value increased significantly from 3.04 to 4.63 with increase in sucrose feed. Acidity decreased slightly but nonsignificantly with increase in sucrose feed and varied between 7.0 and 4.00 meq/kg for 0% and 100% sucrose, respectively. Honey’s lightness (L value) also increased significantly from 59.3 to 68.84 as sucrose feed increased. Other color parameters were not significantly changed by sucrose feed. K-means clustering is used to classify the level of honey adulteration by using the above physiological properties. The classification results showed that both glucose content and total sugar content provided 100?curate classification while pH values provided the worst results with 52% classification accuracy. To further predict the percent honey adulteration, simulated annealing coupled with artificial neural networks (SA-ANNs) was used with sugar profile as an input. RBF-ANN was found to provide the best prediction results with SSE = 0.073, RE = 0.021, and overall R2 = 0.992. It is concluded that honey sugar profile can provide an accurate and reliable tool for detecting indirect honey adulteration by sucrose solution.

Keywords: classification, prediction, k-means

Research Title: Effect of Aggression Management Training on Perceived Stress Levels of Nurses Working in Mental Health Care Settings in Jordan
Author: Fadwa Al-Halaiqa, Published Year: 2020
Journal of Psychosocial Nursing and Mental Health Services, 32845337
Faculty: Nursing

Abstract: The current study investigated the effect of an aggression management training course on reducing perceived stress levels of nurses working in mental health care settings in Jordan. This quasi-experimental pre/post study included 83 nurses (44 male, 39 female; mean age = 33 years) who completed a sociodemographic characteristics questionnaire and the Arabic Version of the Perceived Stress Scale 10-Items Questionnaire. Participants attended 32 hours of an aggression management training course and then answered the questionnaires for a second time. Female nurses reported significantly higher stress levels than male nurses before and after the training course. Paired-samples t test showed a significant decrease in the mean total score of perceived stress of all nurses after attending the training course. The results of this study highlight the need to design and implement aggression management courses, as such training can improve nurses' mental health and perceived stress levels. [Journal of Psychosocial Nursing and Mental Health Services, 58(10), 32-38.].

Keywords: Stress, mental health

Research Title: prevalence and prediction of depression, anxiety, and stress among youth at the time of COVID-19: an online cross-sectional multi-country study
Author: Fadwa Al-Halaiqa, Published Year: 2020
Depression research and Treatment, 10.1155/2020/888772
Faculty: Nursing

Abstract: Depression and anxiety are prevalent mental illnesses among young people. Crisis like the Coronavirus Disease 2019 (COVID-19) pandemic may increase the current prevalence of these illnesses. A cross-sectional, descriptive design was used to (1) explore the prevalence of depression, anxiety, and stress among youth and (2) identify to what extent certain variables related to COVID-19 could predict depression, anxiety, and stress (DAS) among young people in six different countries. Participants were requested to complete an online survey including demographics and the DAS scale. A total of 1,057 participants from Oman (n = 155), Saudi Arabia (n = 121), Jordan (n = 332), Iraq (n = 117), United Arab Emirates (n = 147), and Egypt (n = 182) completed the study. The total prevalence of depression, anxiety, and stress was 57%, 40.5%, and 38.1%, respectively, with no significant differences between countries. Significant predictors of stress, anxiety, and depression were being female, being in contact with a friend and/or a family member with mental illness, being quarantined for 14 days, and using the internet. In conclusion, COVID-19 is an epidemiological crisis that is casting a shadow on youths' DAS. The restrictions and prolonged lockdowns imposed by COVID-19 are negatively impacting their level of DAS. Healthcare organisations, in collaboration with various sectors, are recommended to apply psychological first aid and design appropriate educational programmes to improve the mental health of youth.


Research Title: IoT-Based Real-Time Monitoring System for Epidemic Diseases Patients; Design and Evaluation
Author: Fadwa Al-Halaiqa, Published Year: 2020
International Journal of Online and Biomedical Engineering, 17
Faculty: Nursing

Abstract: Epidemic diseases patients need constant monitoring of their health, whether in the hospital or at home, and this requires great costs. The employment of information and communication technologies and artificial intelligence concepts helps reduce these costs. This paper introduces a real-time monitoring system for monitoring pneumonia patients that will allow doctors to monitor the health of their patients remotely through smartphones or internet-connected devices. To verify the proper functioning of this system, a real-time monitoring device was developed. A secure mechanism is designed to establish a wireless connection to the monitoring unit.

Keywords: Healthcare; Epidemic diseases patients; Pneumonia patients; Real-time patient monitoring.

Research Title: Stemming Effects on Sentiment Analysis using Large Arabic Multi-Domain Resources
Author: Said Ahmad Ammar Ghoul, Published Year: 2019
2019 Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS),
Faculty: Information Technology

Abstract: Sentiment analysis is an area of great interest in research because of its importance and advantages in many different domains. Different approaches and techniques are used to classify the sentiment of texts, and there are different algorithms proposed to improve the performance through text preprocessing. Stemming is one of preprocessing step that is used in many research to enhance the performance of sentiment classification. In this research, we provide new comparative experiments on the impacts and effects of using two of the most commonly used stemmers in the Arabic language; light stemmer and Khoja stemmer in the preprocessing phase of sentiment analysis. We used large Arabic multi-domain datasets that include positive and negative reviews across multiple domains. Five classifiers are used; Naïve Bayes, support vector machines, k-nearest neighbors, decision trees, and logistic regression. The results indicate that Khoja stemmer outperformed that light stemmer Khoja stemmer in terms of precision, recall, f-measure, and accuracy, and it has an advantage in minimizing training time.

Keywords: Stemming, Sentiment Analysis, Arabic light stemmer, Khoja's stemmer

Research Title: Knowledge, Attitudes, and Practices of Oral Care in Mechanical Ventilated Patients.
Author: Fadwa Al-Halaiqa, Published Year: 2020
General Practitioner /Prakticky Lekar, 20
Faculty: Nursing

Abstract: Aim: To identify the intensive care unit nurses' (ICU) knowledge, attitudes, and practices of oral care in orally intubated patients. Method: A descriptive, cross--sectional, correlational design was used to describe the current knowledge, attitudes, and practice of oral care among ICU nurses' in two university-affiliated teaching hospitals, using a self-administered questionnaire that was developed by Lin et al., (2011) and Soh et al., (2011). Results: A total of 135 questionnaires were analyzed and showed that the mean percentages of critical care unit nurses' knowledge, attitudes, and practices of oral care were 53.6%, 67.5%, and 43.25% respectively. The main source of learning regarding oral care for intubated patients was the senior nurses in their units followed by nursing school, also, nurses who had more than one source for learning about oral care had greater knowledge regarding oral care, and performed oral care practices more frequently. The results also indicated that the nurses did not have adequate knowledge and clear perception about the characteristics of various oral cleaning solutions and the effective equipment that is used to remove dental plaque. Conclusion: The study results provide insight into oral care in ICU nurses' and the need for protocol development, implementation, and evaluation; moreover, enhancing nurses to get knowledge about oral care from different educational sources to improve their practices.

Keywords: Knowledge, attitudes, nursing practice, oral care, Jordan.