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Progressing digitalization of business, economy, and the society places higher education institutions (HEIs) in the center of the debate on how to effectively respond to challenges and opportunities that are thus triggered. Several facets of this process and corresponding challenges exist, including the complex question of how to match students’ skills and competencies with the demands and expectations of the industry. From a different angle, considering the changing nature of work, HEIs are responsible for equipping future employees with skills necessary to work in virtual, distributed, culturally diverse, and frequently global, teams. In the domain of software development, i.e., the backbone of the digital world, the challenge HEIs need to face is paramount. For this reason, the way software development is taught at HEIs is crucial for the industry, for the economy, for the students, and for the HEIs. As there is a tendency in the industry to embrace the scrum method and seek employees equipped with skills necessary for the scrum methodology use, it is necessary to ensure that HEIs offer the students the opportunity to get exposed to scrum. By querying the challenges of switching to agile software development methodologies in senior capstone projects, this paper makes a case that software development and software development methodology form the thrust of a multi-stakeholder ecosystem that defines today’s digital economy and society. In this context, the added value of this paper rests in the elaboration of a method enabling HEIs to move toward scrum in senior projects.
Kawther Saeedi; Anna Visvizi. Software Development Methodologies, HEIs, and the Digital Economy. Education Sciences 2021, 11, 73 .
AMA StyleKawther Saeedi, Anna Visvizi. Software Development Methodologies, HEIs, and the Digital Economy. Education Sciences. 2021; 11 (2):73.
Chicago/Turabian StyleKawther Saeedi; Anna Visvizi. 2021. "Software Development Methodologies, HEIs, and the Digital Economy." Education Sciences 11, no. 2: 73.
Social media, and especially Twitter, in specific domains such as healthcare, education and politics, turned into the key venue of social interaction today. Many higher education institutions (HEIs) seek therefore to utilize the value-added of Twitter to disseminate and to collect information from students in view of improving the quality of education at their institutions. In this view, the ability to mine, classify and interpret the content of Tweets is crucial. By examining the case of the King AbdulAziz University in Saudi Arabia, this paper offers a preliminary insight into what kind of information can be collected and in which ways it can be useful for a given HEI as regards teaching, administration and overall management. To this end, this paper examines the usability of three machine learning models, including Support Vector Machine (SVM), K Nearest Neighbor and, finally, Random Forests (RF). The outcomes of this study that this paper elaborates on suggest that in terms of accuracy, SVM is the best performing classifier. Meanwhile, even if the RF proved to be a strong classifier too, it did not perform as well as the SVM.
Walaa Alhabashi; Kawther Saeedi; Naif Aljohani; Sachi Arafat; Rabeeh Abbasi. Mining and Classifying Social Network Data: The Case on King Abdul-Aziz University Twitter Accounts. Designing Networks for Innovation and Improvisation 2021, 317 -326.
AMA StyleWalaa Alhabashi, Kawther Saeedi, Naif Aljohani, Sachi Arafat, Rabeeh Abbasi. Mining and Classifying Social Network Data: The Case on King Abdul-Aziz University Twitter Accounts. Designing Networks for Innovation and Improvisation. 2021; ():317-326.
Chicago/Turabian StyleWalaa Alhabashi; Kawther Saeedi; Naif Aljohani; Sachi Arafat; Rabeeh Abbasi. 2021. "Mining and Classifying Social Network Data: The Case on King Abdul-Aziz University Twitter Accounts." Designing Networks for Innovation and Improvisation , no. : 317-326.
Chest X-ray (CXR) imaging is a standard and crucial examination method used for suspected cases of coronavirus disease (COVID-19). In profoundly affected or limited resource areas, CXR imaging is preferable owing to its availability, low cost, and rapid results. However, given the rapidly spreading nature of COVID-19, such tests could limit the efficiency of pandemic control and prevention. In response to this issue, artificial intelligence methods such as deep learning are promising options for automatic diagnosis because they have achieved state-of-the-art performance in the analysis of visual information and a wide range of medical images. This paper reviews and critically assesses the preprint and published reports between March and May 2020 for the diagnosis of COVID-19 via CXR images using convolutional neural networks and other deep learning architectures. Despite the encouraging results, there is an urgent need for public, comprehensive, and diverse datasets. Further investigations in terms of explainable and justifiable decisions are also required for more robust, transparent, and accurate predictions.
Hanan S. Alghamdi; Ghada Amoudi; Salma Elhag; Kawther Saeedi; Jomanah Nasser. Deep Learning Approaches for Detecting COVID-19 From Chest X-Ray Images: A Survey. IEEE Access 2021, 9, 20235 -20254.
AMA StyleHanan S. Alghamdi, Ghada Amoudi, Salma Elhag, Kawther Saeedi, Jomanah Nasser. Deep Learning Approaches for Detecting COVID-19 From Chest X-Ray Images: A Survey. IEEE Access. 2021; 9 ():20235-20254.
Chicago/Turabian StyleHanan S. Alghamdi; Ghada Amoudi; Salma Elhag; Kawther Saeedi; Jomanah Nasser. 2021. "Deep Learning Approaches for Detecting COVID-19 From Chest X-Ray Images: A Survey." IEEE Access 9, no. : 20235-20254.
Due to the wide-ranging development of data-oriented sustainable systems in the government and the public sectors, the development of such sustainable systems is replete with potential. The ultimate focus of developing these sustainable systems is to provide citizens with transparency, accountability, awareness as well as a single point of query for asking integrated and smart queries. In view of these benefits, the Saudi government has taken the initiative to publish and develop sustainable open data-oriented information systems. However some major challenges in the Saudi Government Open Data are that the (1) data are published and available in different formats such as Excel sheets, CSV files (Comma Separated Values), images, scanned documents and social media sources such as Twitter, (2) datasets from different government departments are not linked with each other or to existing datasets in Linked Open Data Cloud (even though they have strong links with each other), and (3) there is no SPARQL Endpoint that can be used to pose smart semantic-based queries to Saudi Government Data. This paper is part of an ongoing research project to present a framework that can be used to transfer the government data from different sources to RDF format. The framework can also be used to clean and classify/map the data according to the Saudi Government Ontology. We also describe our approach for semiautomatically linking Saudi Government Datasets with one another as well as with other existing open datasets, thus resulting in the Saudi Linked Open Government Data Cloud (SLOGDC). Finally, taking the topic “Public’s Response to Women’s Driving in Saudi Arabia” as a case study, we demonstrate the SLOGD SPARQL Endpoint as a data-oriented system by executing different queries and analyzing results of these queries. This work also contributes new insights into women’s driving in Saudi Arabia using the SLOGDC, thus suggesting the way forward in shaping policies for decision-making.
Afnan AlSukhayri; Muhammad Aslam; Kawther Saeedi; Muhamad Malik. A Linked Open Data-Oriented Sustainable System for Transparency and Open Access to Government Data: A Case Study of the Public’s Response to Women’s Driving in Saudi Arabia. Sustainability 2020, 12, 8608 .
AMA StyleAfnan AlSukhayri, Muhammad Aslam, Kawther Saeedi, Muhamad Malik. A Linked Open Data-Oriented Sustainable System for Transparency and Open Access to Government Data: A Case Study of the Public’s Response to Women’s Driving in Saudi Arabia. Sustainability. 2020; 12 (20):8608.
Chicago/Turabian StyleAfnan AlSukhayri; Muhammad Aslam; Kawther Saeedi; Muhamad Malik. 2020. "A Linked Open Data-Oriented Sustainable System for Transparency and Open Access to Government Data: A Case Study of the Public’s Response to Women’s Driving in Saudi Arabia." Sustainability 12, no. 20: 8608.
An emerging technology with a secure and a decentralized nature, blockchain has the potential to transform conventional practices in an efficient and dynamic manner. However, migrating to blockchain can be challenging due to the complexity of its infrastructure and processes. The complexity of building applications on blockchain has been highlighted by many studies, thus stressing the need to investigate practical solutions further. A commonly known software engineering concept, software design pattern contributes to the acceleration of software development. It offers a holistic reusable solution for commonly occurring problems in a given context. It helps to identify problems that occur repetitively and describes best practices to address them. The present study is one of the first investigations to inquire into design patterns for blockchain application. Seeking to reduce the complexity in understanding and building applications on blockchain, this paper identifies a design pattern elicitation framework from similar blockchain applications. Next, it provides a demonstration of the Proof of Integrity (PoI) pattern elicited from two different applications on the blockchain. The applicability of the pattern is evaluated by building a blockchain application to verify the integrity of the academic certificates and by explaining how this integrity has been achieved empirically.
Kawther Saeedi; Monirah Almalki; Dania Aljeaid; Anna Visvizi; Muhammad Aslam. Design Pattern Elicitation Framework for Proof of Integrity in Blockchain Applications. Sustainability 2020, 12, 8404 .
AMA StyleKawther Saeedi, Monirah Almalki, Dania Aljeaid, Anna Visvizi, Muhammad Aslam. Design Pattern Elicitation Framework for Proof of Integrity in Blockchain Applications. Sustainability. 2020; 12 (20):8404.
Chicago/Turabian StyleKawther Saeedi; Monirah Almalki; Dania Aljeaid; Anna Visvizi; Muhammad Aslam. 2020. "Design Pattern Elicitation Framework for Proof of Integrity in Blockchain Applications." Sustainability 12, no. 20: 8404.
In the context of the debate on the need to place citizens at the center of the technological revolution, this paper makes a case for a natural language processing (NLP) crowdsourcing platform that ensures inclusion and diversity, thus making the research outcome relevant and applicable across issues and domains. This paper also makes the case that by enabling participation for a wide variety of stakeholders, this NLP crowdsourcing platform might ultimately prove useful in the decision- and policy-making processes at city, community, and country levels. Against the backdrop of the debates on artificial intelligence (AI) and NLP research, and considering substantial differentiation specific to the Arab language, this paper introduces and evaluates an Arab language-sensitive NLP crowdsourcing platform. The value of the platform and its accuracy are measured via the System Usability Scale (SUS), where it scores 72.5, i.e., above the accepted usability average. These findings are crucial for NLP research and the research community in general. They are equally promising in view of the practical application of the research findings.
Dimah Alahmadi; Amal Babour; Kawther Saeedi; Anna Visvizi. Ensuring Inclusion and Diversity in Research and Research Output: A Case for a Language-Sensitive NLP Crowdsourcing Platform. Applied Sciences 2020, 10, 6216 .
AMA StyleDimah Alahmadi, Amal Babour, Kawther Saeedi, Anna Visvizi. Ensuring Inclusion and Diversity in Research and Research Output: A Case for a Language-Sensitive NLP Crowdsourcing Platform. Applied Sciences. 2020; 10 (18):6216.
Chicago/Turabian StyleDimah Alahmadi; Amal Babour; Kawther Saeedi; Anna Visvizi. 2020. "Ensuring Inclusion and Diversity in Research and Research Output: A Case for a Language-Sensitive NLP Crowdsourcing Platform." Applied Sciences 10, no. 18: 6216.
Bashayer Alotaibi; Rabeeh Ayaz Abbasi; Muhammad Ahtisham Aslam; Kawther Saeedi; Dimah Alahmadi. Startup Initiative Response Analysis (SIRA) Framework for Analyzing Startup Initiatives on Twitter. IEEE Access 2020, 8, 10718 -10730.
AMA StyleBashayer Alotaibi, Rabeeh Ayaz Abbasi, Muhammad Ahtisham Aslam, Kawther Saeedi, Dimah Alahmadi. Startup Initiative Response Analysis (SIRA) Framework for Analyzing Startup Initiatives on Twitter. IEEE Access. 2020; 8 ():10718-10730.
Chicago/Turabian StyleBashayer Alotaibi; Rabeeh Ayaz Abbasi; Muhammad Ahtisham Aslam; Kawther Saeedi; Dimah Alahmadi. 2020. "Startup Initiative Response Analysis (SIRA) Framework for Analyzing Startup Initiatives on Twitter." IEEE Access 8, no. : 10718-10730.
Social media analytics has experienced significant growth over the past few years due to the crucial importance of analyzing and measuring public social behavior on different social networking sites. Twitter is one of the most popular social networks and means of online news that allows users to express their views and participate in a wide range of different issues in the world. Expressed opinions on Twitter are based on diverse experiences that represent a broad set of valuable data that can be analyzed and used for many purposes. This study aims to understand the public discussions that are conducted on Twitter about essential topics and developing an analytics framework to analyze these discussions. The focus of this research is the analytical framework of Arabic public discussions using the hashtag #SaudiWomenCanDrive, as one of the hot trends of Twitter discussions. The proposed framework analyzed more than two million tweets using methods from social network analysis. The framework uses the metrics of graph centrality to reveal essential people in the discussion and community detection methods to identify the communities and topics used in the discussion. Results show that @SaudiNews50, @Algassabinasser, and @Abdulrahman were top users in two networks, while @KingSalman and @LoujainHathloul were the top two users in another network. Consequently, “King Salman” and “Loujain Hathloul” Twitter accounts were identified as influencers, whereas “Saudi News” and “Algassabi Nasser” were the leading distributors of the news. Therefore, similar phenomena could be analyzed using the proposed framework to analyze similar behavior on other public discussions.
Zubaida Jastania; Mohammad Ahtisham; Rabeeh Ayaz; Kawther Saeedi. Using Social Network Analysis to Understand Public Discussions: The Case Study of #SaudiWomenCanDrive on Twitter. International Journal of Advanced Computer Science and Applications 2020, 11, 1 .
AMA StyleZubaida Jastania, Mohammad Ahtisham, Rabeeh Ayaz, Kawther Saeedi. Using Social Network Analysis to Understand Public Discussions: The Case Study of #SaudiWomenCanDrive on Twitter. International Journal of Advanced Computer Science and Applications. 2020; 11 (2):1.
Chicago/Turabian StyleZubaida Jastania; Mohammad Ahtisham; Rabeeh Ayaz; Kawther Saeedi. 2020. "Using Social Network Analysis to Understand Public Discussions: The Case Study of #SaudiWomenCanDrive on Twitter." International Journal of Advanced Computer Science and Applications 11, no. 2: 1.
Blockchain is an evolving technology that provides trusted decentralized records of information through encrypted blocks of linked data. This technology promised to provide immutable and integral records shared among authorized parties. This infrastructure creates a vast range of opportunities and reforms wide range of business practices. However, this emerging technology is lacking application development experience in real life project. In this paper, building blockchain-based application is represented for two purposes. The first one is a show case of how blockchain application can reform current business practice. The case represents a blockchain application replacing common business practice of having a middleman (Third-party) delivering original bills between healthcare providers and insurance companies. A ClaimChain application is built to demonstrate the potential benefits of the blockchain application in comparison to conventional practice. The second purpose is a demonstration of design decisions made to build blockchain application with reference to blockchain application design approaches introduced by software architecture community. The paper ends with a summary of lessons learned and recommendations for development process of blockchain application.
Kawther Saeedi; Arwa Wali; Dema Alahmadi; Amal Babour; Faten AlQahtani; Rawan AlQahtani; Raghad Khawaja; Zaina Rabah. Building a Blockchain Application: A Show Case for Healthcare Providers and Insurance Companies. Robotics in Education 2019, 785 -801.
AMA StyleKawther Saeedi, Arwa Wali, Dema Alahmadi, Amal Babour, Faten AlQahtani, Rawan AlQahtani, Raghad Khawaja, Zaina Rabah. Building a Blockchain Application: A Show Case for Healthcare Providers and Insurance Companies. Robotics in Education. 2019; ():785-801.
Chicago/Turabian StyleKawther Saeedi; Arwa Wali; Dema Alahmadi; Amal Babour; Faten AlQahtani; Rawan AlQahtani; Raghad Khawaja; Zaina Rabah. 2019. "Building a Blockchain Application: A Show Case for Healthcare Providers and Insurance Companies." Robotics in Education , no. : 785-801.
With the advancement of technology, academics and curriculum developers are always under pressure to provide students with skills that match the market’s requirements. A systematic and continuous examination of the market is needed, to stay up to date with the required skills, and then to update the curriculum to train the students with required market skills. In this article, we present a framework referred to as Align My Curriculum (AMC). The AMC framework aims to facilitate alignment between acquired university curriculum outcomes and required market skills. It can be used to classify, compare and visualize the data of a university curriculum and job vacancies in the market. The presented framework benefits academics and curriculum developers by improving the courses and therefore bridging the skills gap. Stakeholders from both academia and industry can gain insights into the predominant required and acquired skills. In addition, it may be useful for analysts, students, and job applicants. This article describes the architecture, implementation and experimental results, with visual analysis to help decision and policy-makers.
Ahood Almaleh; Muhammad Ahtisham Aslam; Kawther Saeedi; Naif Radi Aljohani. Align My Curriculum: A Framework to Bridge the Gap between Acquired University Curriculum and Required Market Skills. Sustainability 2019, 11, 2607 .
AMA StyleAhood Almaleh, Muhammad Ahtisham Aslam, Kawther Saeedi, Naif Radi Aljohani. Align My Curriculum: A Framework to Bridge the Gap between Acquired University Curriculum and Required Market Skills. Sustainability. 2019; 11 (9):2607.
Chicago/Turabian StyleAhood Almaleh; Muhammad Ahtisham Aslam; Kawther Saeedi; Naif Radi Aljohani. 2019. "Align My Curriculum: A Framework to Bridge the Gap between Acquired University Curriculum and Required Market Skills." Sustainability 11, no. 9: 2607.