@zuj.edu.jo
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Mustafa AlRifaee, Sally Almanasra, Adnan Hnaif, Ahmad Althunibat, Mohammad Abdallah, and Thamer Alrawashdeh
Tech Science Press
Ahmad Alkhatib, Khalid Jaber, Hassan Alzo’by, Mohammad Abdallah, and Mousa Salah
Deanship of Scientific Research
An International, Mousa Salah, Ayman Abdalla, Mohammad Abdallah, Ahmad A. Mazhar, Basem Alokush and I. Jebril
Natural Sciences Publishing
: Most university campuses, such as the campus of Al-Zaytoonah University of Jordan (ZUJ), are usually large and comprise many buildings. Finding the location of an office, a lecture hall, a service center, etc. is not an easy task for most visitors and even for many students and employees. Therefore, a virtual tour of the campus and its buildings will provide a valuable tool that eases this task, especially when it is available on a public website and accessible without the need for special virtual reality devices. Previous studies on virtual tours focused on their important marketing aspect. On the other hand, this study is focused on using virtual tours as a guide for finding the specific locations that different users seek to visit. Consequently, a virtual tour of ZUJ has been designed and provided via the university website. The building names and numbers are provided on the website in Arabic and English with links to their tours. The tours that lead to the important locations include many significant details inside the buildings such as room numbers, bathroom signs, and door signs. The study showed user satisfaction with the tours and the efficacy of using the website without special virtual reality devices.
Daniel Staegemann, Matthias Pohl, Christian Haertel, Christian Daase, Mohammad Abdallah, and Klaus Turowski
IEEE
With society’s increasing data production and the corresponding demand for systems that are capable of utilizing them, the big data domain has gained significant importance. However, besides the systems’ actual implementation, their testing also needs to be considered. For this, oftentimes, proper test data sets are necessary. This publication discusses several different approaches how these can be provisioned and, further, highlights the respective advantages, disadvantages, and suitable application scenarios. In doing so, researchers and practitioners that are implementing big data applications and need to test them, or who are generally interested in the domain, are supported in their own considerations on how to obtain test data.
Daniel Staegemann, Matthias Volk, Mohammad Abdallah, and Klaus Turowski
SCITEPRESS - Science and Technology Publications
Mohammad Abdallah, Alaa Hammad, and Daniel Staegemann
IEEE
Big data applications have gained widespread usage across various fields, including healthcare, business, and education. The effectiveness and accuracy of these applications heavily rely on the availability of a large volume of data. However, the collected and generated data for these applications often suffer from incompleteness, inaccuracy, and lack of structure. Consequently, significant efforts are required to clean and process the vast amount of data collected. In this research, we conduct a comprehensive review of existing data quality models that address data and big data quality in general. Building upon this review, we propose a data collection quality model that incorporates a wide range of quality factors. Our model aims to produce clear and accurate data that can be readily utilized, thereby enhancing the value of data and supporting the performance of big data systems. Additionally, the proposed model contributes to reducing storage space requirements and processing time for data. To validate the effectiveness of the model, a case study is conducted using a predefined dataset. The results indicate that the model significantly streamlines the process of obtaining clean and accurate data. Nonetheless, further investigation is necessary to address additional aspects such as legal and privacy considerations pertaining to the collected data. Overall, this research presents a robust data collection quality model that addresses existing challenges and provides a foundation for improved utilization of big data in various domains.
Daniel Staegemann, Matthias Volk, Mohammad Abdallah, and Klaus Turowski
IEEE
Big data analytics have claimed an important role in today's society. Consequently, ways of improving the design and development of the corresponding applications are highly sought after. One rather current proposition is the application of test driven development (TDD) in the big data domain. The idea behind it is to increase the quality and the flexibility of the developed solutions. However, the application of TDD is often seen as a rather challenging task. Therefore, to increase the accessibility and facilitate its use, it is necessary to provide information that give orientation for interested developers. Hence, the publication at hand focuses on the question which considerations, information, and resources need to be provided to facilitate the widespread utilization of TDD in the big data domain. In doing so, it can be used as the foundation for an inventory of the current state of the related literature but also as a call for action to fill remaining gaps by conducting corresponding research endeavours.
Hussain Aletabi and Mohammad Abdallah
IEEE
Infrastructure as a Service (IaaS) is a service provided by cloud computing systems vendors. IaaS provides virtual computing resources to the users such as hardware, servers, data center space and storage, and network components all over the internet. Just like any other growing technology, cloud computing and specifically IaaS faces some challenges that affect the quality of service and must be conquered to achieve users' satisfaction and the most reliable service. Therefore, the service must be dependable to satisfy the business. In this study, a quality model will be proposed from the users' perspective to help the IaaS vendor to understand the IaaS users' nonfunctional requirements.
Gana Sawalhi and Mohammad Abdallah
IEEE
This research paper proposes a new quality model for social media websites based on an extensive literature review and analysis of previous studies. The study identifies seven key quality factors that are essential for evaluating social networking websites: user friendliness, community-drivenness, website appearance, entertainment, security and privacy, efficiency, and navigability. These factors were selected based on their prominence in previous research and their relevance to user satisfaction in the context of social media platforms. The paper explores each quality factor, providing definitions and highlighting their significance in shaping users' perceptions of website quality and satisfaction. The research aims to contribute to a deeper understanding of the factors that influence user experiences and satisfaction with social media websites, providing valuable insight to website designers and developers to enhance user engagement and overall website quality.
Mousa Salah, Ayman Abdalla, and Mohammad Abdallah
IEEE
Several studies were conducted in the past for evaluating the benefits and shortcomings of virtual tours in various sites including university campuses. The previous studies addressed numerous issues such as providing initial perceptions, guiding visitors, etc. Most of these issues can be related, up to some extent, to Jordanian universities in general. However, there are issues specific to Jordan that need to be addressed such as the availability of fast internet connection and suitable data caps. Furthermore, new demands rose recently such as the need for social distancing under COVID-19 restrictions, thus limiting the sizes of physical tour groups. This paper reviews previous studies on virtual tours and evaluates their applicability to Jordanian university and their present practicality. Then, the paper outlines the motivations and limitations of virtual campus tours in Jordan.
Mohammad Abdallah and Mustafa Alrifaee
Zarqa University
Background: Quality is a critical aspect of any software system. Indeed, it is a key factor for the competitiveness, longevity, and effectiveness of software products. Code review facilitates the discovery of programming errors and defects, and using programming language standards is such a technique. Aim: In this study, we developed a code review technique for achieving maximum software quality by using programming language standards. Method: A Java Code Quality Reviewer tool (JCQR) was proposed as a practical technique. It is an automated Java code reviewer that uses SUN and other customized Java standards. Results: The JCQR tool produces new quality-measurement information that indicates applied, satisfied, and violated rules in a piece of code. It also suggests whether code quality should be improved. Accordingly, it can aid junior developers and students in establishing a successful programming attitude. Limitation: JCQR uses customized SUN-based Java programming language standards. Therefore, it fails to cover certain features of Java.
Mustafa M. Al Rifaee, Mohammad M. Abdallah, Mosa I. Salah, and Ayman M. Abdalla
Computers, Materials and Continua (Tech Science Press)
Hand veins can be used effectively in biometric recognition since they are internal organs that, in contrast to fingerprints, are robust under external environment effects such as dirt and paper cuts. Moreover, they form a complex rich shape that is unique, even in identical twins, and allows a high degree of freedom. However, most currently employed hand-based biometric systems rely on hand-touch devices to capture images with the desired quality. Since the start of the COVID-19 pandemic, most hand-based biometric systems have become undesirable due to their possible impact on the spread of the pandemic. Consequently, new contactless hand-based biometric recognition systems and databases are desired to keep up with the rising hygiene awareness. One contribution of this research is the creation of a database for hand dorsal veins images obtained contact-free with a variation in capturing distance and rotation angle. This database consists of 1548 images collected from 86 participants whose ages ranged from 19 to 84 years. For the other research contribution, a novel geometrical feature extraction method has been developed based on the Curvelet Transform. This method is useful for extracting robust rotation invariance features from vein images. The database attributes and the veins recognition results are analyzed to demonstrate their efficacy.
Mohammad Abdallah, Alaa Hammad, and Wael AlZyadat
Springer International Publishing
Ahmad Althunibat, Mohammad Abdallah, Mohammed Amin Almaiah, Nour Alabwaini, and Thamer Ahmad Alrawashdeh
Computers, Materials and Continua (Tech Science Press)
Mohammad Abdallah, Khalid Mohammad Jaber, Mousa Salah, Mohammad Abdul Jawad, Naji AlQbailat, and Ayman Abdalla
IEEE
The standard of e-learning is a compound of different quality factors quality dimensions. The researchers looked at the efficiency of e-learning from various angles and viewpoints. However, few works of literature study, specifically, the quality of e-learning portals or software. Besides, the students' or learners' opinions about this issue. In this research, we only focused on the quality of e-learning portals and technology and what factors and impact they have on e-learning in general from the students’ perspectives. The results show that the students are more concerned about the usability and related factors because their learning process become depends fully on the e-learning portal as a result of the COVID-19 pandemic.
Wael Alzyadat, Aysh AlHroob, Ikhlas Hassan Almukahel, Mohammad Muhairat, Mohammad Abdallah, and Ahmad Althunibat
IEEE
Big Data filed is an unsettled standard comparing with a traditional database, data mining, or data warehouse. Stability measure aims to acquire the quality dataset which encourages to use of preprocessing data method to handle instability that miniaturization missing data. Therefore, to increase the data quality in order to achieve an accurate prediction, significant rules are used to provide value and meaningful data. Through, three measures by support, confidence, and the lift to acquire frequently rules. These rules are used to conduct the objective extracting pattern, to estimate each browsing customer's likelihood of making a purchase, and to choose meaningful patterns from the discovered association rules.
Daniel Staegemann, Matthias Volk, Erik Lautenschlager, Matthias Pohl, Mohammad Abdallah, and Klaus Turowski
IEEE
Big data has evolved to a ubiquitous part of today’s society. However, despite its popularity, the development and testing of the corresponding applications are still very challenging tasks that are being actively researched in pursuit of ways for improvement. One newly introduced proposition is the application of test driven development (TDD) in the big data domain. To facilitate this concept, existing literature reviews on TDD have been analyzed to extract insights from those sources of aggregated knowledge, which can be applied to this new setting. After introducing the different studies, lessons for the application of TDD in the big data domain are deducted and discussed. Finally, avenues for future works are proposed.
Tamara Jaber, Mohammad Abdallah, and Ahmad Al-thunibat
IEEE
Code inspection is the way to ensure the quality and the control of products and software by detecting, correcting or reducing defects. Nowadays, several methods of code inspection emerged, most of which consisted of processing, preparation, analysis, meetings, and reform. However, each code inspection method may face problems in terms of number of developers, whether large or small, ease of attendance at meetings, and defects coverage. Moreover, some uses of the programs do not tolerate errors during implementation. In this paper, we will propose a new code inspection model that integrates the program slicing technique with code inspection process. We create reports that facilitate the implementation of the code review process and reduce its time, costs, and team size. The proposed model supposed to be more accurate detection and resolution of existing defects.
Rana Bader, Basem Alukosh, Mohammad Abdallah, Khalil Awad, and Amir Ngah
Universitas Ahmad Dahlan
Many organization, programmers, and researchers need to debug, test and make maintenance for a segment of their source code to improve their system. Program slicing is one of the best techniques to do so. There are many slicing techniques available to solve such problems such as static slicing, dynamic slicing, and amorphous slicing. In our paper, we decided to develop a tool that supports many slicing techniques. Our proposed tool provides new flexible ways to process simple segments of Java code, and it generates needed slicing according to the user needs, our tool will provide the user with direct and indirect dependencies for each variable in the code segments. This tool can work under various operating systems and does not need particular environments. Thus, our tool is helpful in many aspects such as debugging, testing, education, and many other elements.
Daniel Staegemann, Matthias Volk, Abdulrahman Nahhas, Mohammad Abdallah, and Klaus Turowski
IEEE
Today, the amount and complexity of data that is globally produced increases continuously, surpassing the abilities of traditional approaches. Therefore, to capture and analyze those data, new concepts and techniques are utilized to engineer powerful big data systems. However, despite the existence of sophisticated approaches for the engineering of those systems, the testing is not sufficiently researched. Hence, in this contribution, a comparison of traditional software testing, as a common procedure, and the requirements of big data testing is drawn. The determined specificities in the big data domain are mapped to their implications on the implementation and the consequent challenges. Furthermore, those findings are transferred into six guidelines for the testing of big data systems. In the end, limitations and future prospects are highlighted.