Research Title: A Genetic Framework model for Self-Adaptive software

Author: Enas Tawfiq Al-Naffar, Published Year: 2017

JSE,

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: 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: ‎A Holystic Self-adaptive systems model‎

Author: Said Ahmad Ammar Ghoul, Published Year: 2021

International Journal of Software Engineering & Applications ‎, ‎12, 2/3, May 2021‎

Faculty: Information Technology

Abstract: The recent self-adaptive software systematic literature reviews stated clearly the following ‎insufficiencies: (1) the need for a holistic self-adaptive software model to integrate its different ‎aspects (2) The limitation of adaptations to context changes (3) The absence of a general and ‎complete adaptations’ picture allowing its understandability, maintainability, evaluation, reuse, and ‎variability. (4) The need for an explicit and a detailed link with resources, and (5) a usual limitation ‎to known events. ‎ In order to metigate these insufficiencies, this paper is proposing a holistic model that integrates the ‎operating, adaptations, and adaptations’ manager aspects. The proposed model covers all possible ‎adaptations: operating (dealing with software functions failures), lifecycle (handling adaptations ‎required by some software lifecycle steps), and context (facing context changes events). The ‎presented work introduces the concept of software adaptations process integrating the ‎specifications of all the above kind of adaptations. In fact, this work shows an explicit trace to its ‎pure bio-inspired origin. ‎ An application of the proposed approach on a “car industry case study” demonstrated its feasibility ‎in comparison with similar works that proved its meaningful added value and its promising research ‎perspectives.‎

Keywords: Self-adaptive software, bio-inspired approach, adaptation events, immune system.‎

Research Title: ‎A Feature Model Based Configuration Reuse for Context-aware Systems‎

Author: Said Ahmad Ammar Ghoul, Published Year: 2021

Computers, Materials & Continua ‎, Under press

Faculty: Information Technology

Abstract: Most of Self-Adaptive Systems (SAS) use Feature Models (FMs) to represent their complex ‎architecture and benefit from reusing commonalities and variability information. However ‎triggering SAS reconfiguration process, each time a system needs to be adapted, continues to ‎cost time and effort. Current FM techniques have modelled SAS concepts, focusing on ‎representing and reusing elementary features without taking into consideration modelling and ‎reusing configurations. This work presents an extension to the FM in order to remedy this ‎important problem by introducing and managing the configuration feature. Evaluation shows that ‎the reuse of configuration feature reduces reconfiguration process effort and time during the run ‎time in order to meet the required scenario according to the context. ‎

Keywords: Self-Adaptive system, Feature Model, System reuse, Configuration management, Variability ‎modelling‎

Research Title: تطبيقات محاسبية وإحصائية باستخدام برنامج إكسل

Author: Yousef Ali Hroot, Published Year: 2016

Faculty: Business

Abstract: https://www.noor-book.com/book/review/505917

Keywords: تطبيقات محاسبية وإحصائية باستخدام برنامج إكسل

Research Title: The impact of organizational storytelling on organizational performance within Jordanian telecommunication sector

Author: Atef Al-Raoush, Published Year: 2020

Journal of Workplace Learning, Vol. 32 No. 5, pp.

Faculty: Business

Abstract: Purpose This study aims to assess the impact of organizational storytelling on organizational performance by undertaking telecommunication companies located in the Middle Eastern nation of Jordan. Design/methodology/approach A quantitative design has been adopted to identify the impact of organizational storytelling on organizational performance, recruiting 460 employees at managerial levels from three telecom companies (Umniah, Zain and Orange). A step-wise regression analysis has been applied to analyze the data collected using a close-ended structured questionnaire. Findings A total of 284 male and 176 female employees took part in the study. The study has found a positive and significant impact of organizational learning, change management, corporate culture, training and development and leadership and indicated that these determinants positively related to organizational performance. Findings …

Keywords: Change management, Organizational Performance, Corporate Culture, Leadership, Training and development

Research Title: Impact of Financial Management on Improving Quality at Jordanian Public University Hospitals

Author: Atef Al-Raoush, Published Year: 2020

Journal of Information & Knowledge Management, Vol. 19, No. 03, 205

Faculty: Business

Abstract: The main purpose of this study was to investigate the impact of financial management on improving quality at the public university hospitals in Jordan. We used a quantitative method with a sample of 220 public university hospital staff. Using simple linear regression analysis, we showed via our findings a significant impact of the financial management dimension on the quality management dimension. These findings emphasise that using a proficient financial management system would improve the quality of services and overall organisational performance in the Jordanian public healthcare sector.

Keywords: Public administration financial management quality management public university hospitals Jordan

Research Title: The lived experience of family members who care for children with cancer: An interpretative phenomenological approach

Author: Maha Mohammed Wahbi Atout, Published Year: 2021

European Journal of Nursing Oncology , NA

Faculty: Nursing

Abstract: Purpose This study aimed to explore the lived experiences of family carers in the care of children with cancer. Method A phenomenological hermeneutic approach was conducted, informed by the philosophy of Martin Heidegger. Fourteen interviews were conducted with family members: mothers (n = 9), grandmothers and fathers (n = 5). Fourteen family carers were voluntarily enrolled from a public children's oncology department in Bethlehem in the Occupied Palestinian Territories. Interpretative Phenomenological Analysis (IPA) was used to analyze the data. Results Three major themes emerged from the data analysis. The first theme was the caring experience, which included three subthemes: changing priorities over time, information given about children's illness, and parents suffering due to treating irritable children. The second theme was the challenges to effective care, which illustrates the most significant challenges faced during caring, including the effects of family relations and emotional support. The final theme was around the support system; family carers found several resources to support them in their children's care, including other parents' experiences with similar diseases, the hospital environment, and their religious beliefs. Conclusions This study informs parents and healthcare providers about the daily lived experiences of family carers. Healthcare providers can fulfil a significant role in giving emotional support and relief to family carers. However, they will need continuous practise to equip them with the communication skills they require to deal with the family carers in these difficult situations.

Keywords: Family carers children cancer experience phenomenology

Research Title: The Nature of the Relationship between Money Supply and Inflation in the Jordanian Economy (1980–2019)

Author: Atif Issa Batarseh, Published Year: 2021

banks and bank systems, 16 issue 1

Faculty: Arts

Abstract: The current study aims at investigating and analyzing the relation between money supply (M1) and inflation in the Jordanian economy during the period of 1980–2019. In order to achieve the goal of the study, the methodology of econometric analysis of time series was utilized through the following tests: Augmented Dickey-Fuller (ADF) to test the stability of the study variables, Johansen’s Cointegration Approach to determine the long-term equilibrium relationship between the study variables, and Granger Causality Test to determine the direction of the causal relationship if it exists in the short term. The results of the study demonstrate that inflation has stabilized at the level, while the money supply M1 was unstable at a level and stabilized after taking the first difference. The results of the Cointegration test indicated that there was no causal link between the money supply M1 and inflation in the long term. Finally, the results of Granger Causality presented a unidirectional causality running from the money supply M1 to inflation in the short term, meaning that money supply causes inflation, not vice versa; this means that the money supply M1 can explain the changes that occur in the consumer price index (CPI) in the Jordanian economy. The study recommends that monetary authority in Jordan should have greater control over the money supply because of its impact on the stability of the general level of prices, in order to avoid a repeat of the 1989 crisis represented by the hard decline of the dinar exchange rate against other currencies and the increase in the inflation rate that year to 25.6 %.

Keywords: Money Supply M1, Inflation, ADF Test, Causality Test, Co-Integration Test, Jordanian Economy.