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Prof. Dr. Ghassan Beydoun
School of Information, Systems and Modelling, University of Technology Sydney, NSW 2007, Australia

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0 Artificial Intelligence
0 Disaster Management
0 Requirements Engineering
0 agent-based modelling
0 Information systems methodologies

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Article
Published: 28 January 2021 in Information Systems Frontiers
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This research paper assesses complexity in cloud computing adoption, using the context of the local government sector in Australia. The research utilized both cloud computing adoption literature and an Information Systems Complexity Framework to propose a complexity assessment model for cloud computing adoption. A mixed method approach was used in this research. Firstly, we conducted 21 indepth interviews with IT managers in the local governments in Australia to obtain their insights into the complexity of cloud computing adoption. Secondly, a quantitative method is used in which 480 IT staff from 47 local governments responded to an online survey to validate the proposed assessment model. The findings indicate that structural complexity of an organization (i.e., knowledge management), structural complexity of technology (i.e., technology interoperability, and data processing capability), dynamic complexity of an organization (i.e., business operations), and dynamic complexity of technology (i.e., systems integration, IT infrastructure update, and customization resources) are critical complexity aspects to be considered during cloud computing adoption. These findings provide important implications for both researchers and managers that are trying to understand the complexities involved in cloud computing adoption.

ACS Style

Omar Ali; Anup Shrestha; Maryam Ghasemaghaei; Ghassan Beydoun. Assessment of Complexity in Cloud Computing Adoption: a Case Study of Local Governments in Australia. Information Systems Frontiers 2021, 1 -23.

AMA Style

Omar Ali, Anup Shrestha, Maryam Ghasemaghaei, Ghassan Beydoun. Assessment of Complexity in Cloud Computing Adoption: a Case Study of Local Governments in Australia. Information Systems Frontiers. 2021; ():1-23.

Chicago/Turabian Style

Omar Ali; Anup Shrestha; Maryam Ghasemaghaei; Ghassan Beydoun. 2021. "Assessment of Complexity in Cloud Computing Adoption: a Case Study of Local Governments in Australia." Information Systems Frontiers , no. : 1-23.

Journal article
Published: 13 January 2021 in Sustainability
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Absorptive capacity is a common barrier to knowledge transfer at the individual level. However, technology absorptive capacity can enhance an individual’s learning behaviour. This study investigates that technology readiness, the tools for knowledge sources, social influences, and social networks influence an individual’s absorptive capacity on an adaptation of the individual learning behaviour. A quantitative approach is used to assess the presence of a causal relationship from the constructs mentioned above. Data were collected from university students in Australia to examine the hypotheses. With 199 responses, a partial least squares structural equation modelling (PLS-SEM) approach was used for the analysis. The results generated mixed findings. Individual’s technological belief in optimism and innovation and social influences had a significantly weaker effect on individual absorptive capacity, which in turn had a significantly weaker impact on their learning behaviour.

ACS Style

Thomas Dolmark; Osama Sohaib; Ghassan Beydoun; Kai Wu. The Effect of Individual’s Technological Belief and Usage on Their Absorptive Capacity towards Their Learning Behaviour in Learning Environment. Sustainability 2021, 13, 718 .

AMA Style

Thomas Dolmark, Osama Sohaib, Ghassan Beydoun, Kai Wu. The Effect of Individual’s Technological Belief and Usage on Their Absorptive Capacity towards Their Learning Behaviour in Learning Environment. Sustainability. 2021; 13 (2):718.

Chicago/Turabian Style

Thomas Dolmark; Osama Sohaib; Ghassan Beydoun; Kai Wu. 2021. "The Effect of Individual’s Technological Belief and Usage on Their Absorptive Capacity towards Their Learning Behaviour in Learning Environment." Sustainability 13, no. 2: 718.

Article
Published: 07 January 2021 in Information Systems Frontiers
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This paper explains how social media drives organization-public collaborative outcomes such as social media-enabled service co-creation in non-profit organizations (nonprofits). We assume a technology affordances perspective to identify social media structures enacted through discovering functional affordances, managing constraints through privacy preferences, and constructing meaning and values, We explain how these structures relate to service co-creation. We surveyed 73 nonprofits on social media and collected 289 usable responses. We apply structural equation modeling to analyze the data. Our findings suggest that symbolic constructed meaning and values together with the organization’s privacy preferences on social media are positively related to socialization, visibility, and information sharing affordances. Unlike information sharing, socialization and visibility affordances are, in turn, positively related to service co-creation. This study advances our theoretical understanding of how social technology structures produce collaborative outcomes and offers practical insights into the cumulative value of social media.

ACS Style

Fatuma Namisango; Kyeong Kang; Ghassan Beydoun. How the Structures Provided by Social Media Enable Collaborative Outcomes: A Study of Service Co-creation in Nonprofits. Information Systems Frontiers 2021, 1 -19.

AMA Style

Fatuma Namisango, Kyeong Kang, Ghassan Beydoun. How the Structures Provided by Social Media Enable Collaborative Outcomes: A Study of Service Co-creation in Nonprofits. Information Systems Frontiers. 2021; ():1-19.

Chicago/Turabian Style

Fatuma Namisango; Kyeong Kang; Ghassan Beydoun. 2021. "How the Structures Provided by Social Media Enable Collaborative Outcomes: A Study of Service Co-creation in Nonprofits." Information Systems Frontiers , no. : 1-19.

Conference paper
Published: 18 October 2020 in Lecture Notes in Computer Science
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Providing personalized online learning services has become a hot research topic. Online knowledge-sharing services represents a popular approach to enable learners to use fragmented spare time. User asks and answers questions in the platform, and the platform also recommends relevant questions to users based on their learning interested and context. However, in the big data era, information overload is a challenge, as both online learners and learning resources are embedded in data rich environment. Offering such web services requires an intelligent recommender system to automatically filter out irrelevant information, mine underling user preference, and distil latent information. Such a recommender system needs to be able to mine complex latent information, distinguish differences between users efficiently. In this study, we refine a recommender system of a prior work for web-based knowledge sharing. The system utilizes attention-based mechanisms and involves high-order feature interactions. Our experimental results show that the system outperforms known benchmarks and has great potential to be used for the web-based learning service.

ACS Style

Jiayin Lin; Geng Sun; Jun Shen; Tingru Cui; David Pritchard; Dongming Xu; Li Li; Wei Wei; Ghassan Beydoun; Shiping Chen. Attention-Based High-Order Feature Interactions to Enhance the Recommender System for Web-Based Knowledge-Sharing Service. Lecture Notes in Computer Science 2020, 461 -473.

AMA Style

Jiayin Lin, Geng Sun, Jun Shen, Tingru Cui, David Pritchard, Dongming Xu, Li Li, Wei Wei, Ghassan Beydoun, Shiping Chen. Attention-Based High-Order Feature Interactions to Enhance the Recommender System for Web-Based Knowledge-Sharing Service. Lecture Notes in Computer Science. 2020; ():461-473.

Chicago/Turabian Style

Jiayin Lin; Geng Sun; Jun Shen; Tingru Cui; David Pritchard; Dongming Xu; Li Li; Wei Wei; Ghassan Beydoun; Shiping Chen. 2020. "Attention-Based High-Order Feature Interactions to Enhance the Recommender System for Web-Based Knowledge-Sharing Service." Lecture Notes in Computer Science , no. : 461-473.

Journal article
Published: 14 September 2020 in IEEE Access
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Big data management and analytics, in the context of IoT (Internet of Things)-enabled smart buildings, is a challenging task. It is a diffused and complex area of knowledge due to the diversity of IoT devices and the nature of data generated by the IoT devices. Many international bodies have developed metamodels for IoT-enabled ecosystems to allow knowledge sharing. However, these are often narrow in focus and deal with only the IoT aspects without taking into account the management and analytics of big data generated by the IoT devices. Hence, in this paper we propose a metamodel for the Integrated Big Data Management and Analytics (IBDMA) framework for IoT-enabled smart buildings. The IBDMA Metamodel can be used to facilitate interoperability between existing big data management and analytics ecosystems deployed in smart buildings or other smart environments. We import the metamodel into a knowledge graph management tool and by considering a case study we validate the metamodel using this tool. The evaluation results demonstrate that IBDMA Metamodel is indeed suitable for its intended purpose.

ACS Style

Muhammad Rizwan Bashir; Asif Qumer Gill; Ghassan Beydoun; Brad Mccusker. Big Data Management and Analytics Metamodel for IoT-Enabled Smart Buildings. IEEE Access 2020, 8, 169740 -169758.

AMA Style

Muhammad Rizwan Bashir, Asif Qumer Gill, Ghassan Beydoun, Brad Mccusker. Big Data Management and Analytics Metamodel for IoT-Enabled Smart Buildings. IEEE Access. 2020; 8 (99):169740-169758.

Chicago/Turabian Style

Muhammad Rizwan Bashir; Asif Qumer Gill; Ghassan Beydoun; Brad Mccusker. 2020. "Big Data Management and Analytics Metamodel for IoT-Enabled Smart Buildings." IEEE Access 8, no. 99: 169740-169758.

Journal article
Published: 11 August 2020 in Science of The Total Environment
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On 28th September 2018, a very high magnitude of earthquake Mw 7.5 struck the Palu city in the Island of Sulawesi, Indonesia. The main objective of this research is to estimate the earthquake risk based on probability and hazard in Palu region using cross-correlation among the derived parameters, Silhouette clustering (SC), pure locational clustering (PLC) based on hierarchical clustering analysis (HCA), convolutional neural network (CNN) and analytical hierarchy process (AHP) techniques. There is no specific or simple way of identifying risks as the definition of risk varies with time and space. The main aim of this study is: i) to conduct the clustering analysis to identify the earthquake-prone areas, ii) to develop a CNN model for probability estimation, and iii) to estimate and compare the risk using two calculation equations (Risk A and B). Owing to its high prediction ability, the CNN model assessed the probability while SC and PLC were implemented to understand the spatial clustering, Euclidean distance among clusters, spatial relationship and cross-correlation among the estimated Mw, PGA and intensity including events depth. Finally, AHP was implemented for the vulnerability assessment. To this end, earthquake probability assessment (EPA), susceptibility to seismic amplification (SSA) and earthquake vulnerability assessment (EVA) results were employed to generate risk A, while earthquake hazard assessment (EHA), SSA and EVA were used to generate risk B. The risk maps were compared and the differences in results were obtained. This research concludes that in the case of earthquake risk assessment (ERA), results obtained in Risk B are better than the risk A. This study achieved 89.47% accuracy for EPA while for EVA a consistency ratio of 0.07. These results have important implications for future large-scale risk assessment, land use planning and hazard mitigation.

ACS Style

Ratiranjan Jena; Biswajeet Pradhan; Ghassan Beydoun; Abdullah M. Alamri; Ardiansyah; Nizamuddin; Hizir Sofyan. Earthquake hazard and risk assessment using machine learning approaches at Palu, Indonesia. Science of The Total Environment 2020, 749, 141582 .

AMA Style

Ratiranjan Jena, Biswajeet Pradhan, Ghassan Beydoun, Abdullah M. Alamri, Ardiansyah, Nizamuddin, Hizir Sofyan. Earthquake hazard and risk assessment using machine learning approaches at Palu, Indonesia. Science of The Total Environment. 2020; 749 ():141582.

Chicago/Turabian Style

Ratiranjan Jena; Biswajeet Pradhan; Ghassan Beydoun; Abdullah M. Alamri; Ardiansyah; Nizamuddin; Hizir Sofyan. 2020. "Earthquake hazard and risk assessment using machine learning approaches at Palu, Indonesia." Science of The Total Environment 749, no. : 141582.

Conference paper
Published: 30 June 2020 in Transactions on Petri Nets and Other Models of Concurrency XV
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Aims to provide flexible, effective and personalized online learning service, micro learning has gained wide attention in recent years as more people turn to use fragment time to grasp fragmented knowledge. Widely available online knowledge sharing is one of the most representative approaches to micro learning, and it is well accepted by online learners. However, information overload challenges such personalized online learning services. In this paper, we propose a deep cross attention recommendation model to provide online users with personalized resources based on users’ profile and historical online behaviours. This model benefits from the deep neural network, feature crossing, and attention mechanism mutually. The experiment result showed that the proposed model outperformed the state-of-the-art baselines.

ACS Style

Jiayin Lin; Geng Sun; Jun Shen; David Pritchard; Tingru Cui; Dongming Xu; Li Li; Ghassan Beydoun; Shiping Chen. Deep-Cross-Attention Recommendation Model for Knowledge Sharing Micro Learning Service. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 168 -173.

AMA Style

Jiayin Lin, Geng Sun, Jun Shen, David Pritchard, Tingru Cui, Dongming Xu, Li Li, Ghassan Beydoun, Shiping Chen. Deep-Cross-Attention Recommendation Model for Knowledge Sharing Micro Learning Service. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; ():168-173.

Chicago/Turabian Style

Jiayin Lin; Geng Sun; Jun Shen; David Pritchard; Tingru Cui; Dongming Xu; Li Li; Ghassan Beydoun; Shiping Chen. 2020. "Deep-Cross-Attention Recommendation Model for Knowledge Sharing Micro Learning Service." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 168-173.

Conference paper
Published: 10 June 2020 in Advances in Intelligent Systems and Computing
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There is an increasing interest in IoT-enabled smart digital systems. However, it is important to address their security concerns. This paper aims to address this need and proposes an adaptive architecture driven approach to securing IoT systems. The paper proposes IoT security principles and a foundational adaptive architecture framework. These two combined provide a guide to design and embed the security across various layers of an IoT system. This will ensure that the important aspects of the IoT security are not accidentally missed, and thus provides a holistic end to end adaptive architecture driven approach for IoT security. This paper covers the interaction, human, digital technology, physical facility and environment architecture layers and principles related to IoT security as opposed to focusing only on the IoT devices. Thus, it demonstrates and concludes that the IoT security is much more than IoT device, network and perimeter security.

ACS Style

Asif Qumer Gill; Ghassan Beydoun; Mahmood Niazi; Habib Ullah Khan. Adaptive Architecture and Principles for Securing the IoT Systems. Advances in Intelligent Systems and Computing 2020, 173 -182.

AMA Style

Asif Qumer Gill, Ghassan Beydoun, Mahmood Niazi, Habib Ullah Khan. Adaptive Architecture and Principles for Securing the IoT Systems. Advances in Intelligent Systems and Computing. 2020; ():173-182.

Chicago/Turabian Style

Asif Qumer Gill; Ghassan Beydoun; Mahmood Niazi; Habib Ullah Khan. 2020. "Adaptive Architecture and Principles for Securing the IoT Systems." Advances in Intelligent Systems and Computing , no. : 173-182.

Journal article
Published: 10 June 2020
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ACS Style

Jiayin Lin; Geng Sun; Jun Shen; David Pritchard; Tingru Cui; Dongming Xu; Li Li; Ghassan Beydoun; Shiping Chen. Deep-Cross-Attention Recommendation Model for Knowledge Sharing Micro Learning Service. 2020, 12164, 168 -173.

AMA Style

Jiayin Lin, Geng Sun, Jun Shen, David Pritchard, Tingru Cui, Dongming Xu, Li Li, Ghassan Beydoun, Shiping Chen. Deep-Cross-Attention Recommendation Model for Knowledge Sharing Micro Learning Service. . 2020; 12164 ():168-173.

Chicago/Turabian Style

Jiayin Lin; Geng Sun; Jun Shen; David Pritchard; Tingru Cui; Dongming Xu; Li Li; Ghassan Beydoun; Shiping Chen. 2020. "Deep-Cross-Attention Recommendation Model for Knowledge Sharing Micro Learning Service." 12164, no. : 168-173.

Original article
Published: 03 June 2020 in Complex & Intelligent Systems
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Nowadays, Android applications play a major role in software industry. Therefore, having a system that can help companies predict the success probability of such applications would be useful. Thus far, numerous research works have been conducted to predict the success probability of desktop applications using a variety of machine learning techniques. However, since features of desktop programs are different from those of mobile applications, they are not applicable to mobile applications. To our knowledge, there has not been a repository or even a method to predict the success probability of Android applications so far. In this research, we introduce a repository composed of 100 successful and 100 unsuccessful apps of Android operating system in Google PlayStoreTM including 34 features per application. Then, we use the repository to a neural network and other classification algorithms to predict the success probability. Finally, we compare the proposed method with the previous approaches based on the accuracy criterion. Experimental results show that the best accuracy which we achieved is 99.99%, which obtained when we used MLP and PCA, while the best accuracy achieved by the previous work in desktop platforms was 96%. However, the time complexity of the proposed approach is higher than previous methods, since the time complexities of NPR and MLP are O\(( n^3\)) and O\(( nph^koi\)), respectively.

ACS Style

Mehrdad Razavi Dehkordi; Habib Seifzadeh; Ghassan Beydoun; Mohammad H. Nadimi-Shahraki. Success prediction of android applications in a novel repository using neural networks. Complex & Intelligent Systems 2020, 6, 573 -590.

AMA Style

Mehrdad Razavi Dehkordi, Habib Seifzadeh, Ghassan Beydoun, Mohammad H. Nadimi-Shahraki. Success prediction of android applications in a novel repository using neural networks. Complex & Intelligent Systems. 2020; 6 (3):573-590.

Chicago/Turabian Style

Mehrdad Razavi Dehkordi; Habib Seifzadeh; Ghassan Beydoun; Mohammad H. Nadimi-Shahraki. 2020. "Success prediction of android applications in a novel repository using neural networks." Complex & Intelligent Systems 6, no. 3: 573-590.

Journal article
Published: 06 February 2020 in International Journal of Disaster Risk Reduction
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The prerequisite for earthquake risk estimation is vulnerability assessment. Therefore, estimating vulnerability is necessary to reduce future fatalities. This study aims to evaluate the earthquake vulnerability assessment (EVA) in Banda Aceh by using the multi-criteria decision-making approach through an analytical hierarchy process and VIseKriterijumska Optimizacija I Kompromisno Resenje method using a geographical information system. Banda Aceh City is located close to the Great Sumatran Fault in North Sumatra. Several factors were used to produce social vulnerability, structural vulnerability, and geotechnical vulnerability indices. Subsequently, the adopted approaches were integrated and applied to estimate the criteria weight, priority ranking, and alternatives of criterion by applying the pair-wise comparison at all levels. Finally, vulnerability layers were superimposed to estimate the earthquake vulnerability index and produce the vulnerability map. Results showed that the central part of the city exhibits high to very high vulnerability. A tiny part of the northern–central part is under severe vulnerability conditions. The consistency ratios for all three vulnerability layers were 1.9%, 4.6% and 5.5%. The consistency ratios for the final EVA was 1.9%. The developed map revealed that 3.39% of Banda Aceh City falls under very high, 11.86% high, 23.73% medium, 28.82% low, and 32.20% of very low vulnerability areas. The proposed method for the EVA provides useful information that could assist in earthquake disaster mitigation.

ACS Style

Ratiranjan Jena; Biswajeet Pradhan; Ghassan Beydoun. Earthquake vulnerability assessment in Northern Sumatra province by using a multi-criteria decision-making model. International Journal of Disaster Risk Reduction 2020, 46, 101518 .

AMA Style

Ratiranjan Jena, Biswajeet Pradhan, Ghassan Beydoun. Earthquake vulnerability assessment in Northern Sumatra province by using a multi-criteria decision-making model. International Journal of Disaster Risk Reduction. 2020; 46 ():101518.

Chicago/Turabian Style

Ratiranjan Jena; Biswajeet Pradhan; Ghassan Beydoun. 2020. "Earthquake vulnerability assessment in Northern Sumatra province by using a multi-criteria decision-making model." International Journal of Disaster Risk Reduction 46, no. : 101518.

Correction
Published: 15 January 2020 in Information Systems Frontiers
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ACS Style

Farid Shirvani; Ghassan Beydoun; Pascal Perez; William Scott; Peter Campbell. Correction to: An Architecture Framework Approach for Complex Transport Projects. Information Systems Frontiers 2020, 1 -1.

AMA Style

Farid Shirvani, Ghassan Beydoun, Pascal Perez, William Scott, Peter Campbell. Correction to: An Architecture Framework Approach for Complex Transport Projects. Information Systems Frontiers. 2020; ():1-1.

Chicago/Turabian Style

Farid Shirvani; Ghassan Beydoun; Pascal Perez; William Scott; Peter Campbell. 2020. "Correction to: An Architecture Framework Approach for Complex Transport Projects." Information Systems Frontiers , no. : 1-1.

Review
Published: 09 January 2020 in Arabian Journal of Geosciences
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The historical records of earthquakes play a vital role in seismic hazard and risk assessment. During the last decade, geophysical, geotechnical, geochemical, topographical, geomorphological, geological data, and various satellite images have been collected, processed, and well-integrated into qualitative and quantitative spatial databases using geographical information systems (GIS). Various types of modeling approaches, such as traditional and GIS-based models, are used. Progressively, seismic studies can improve and modify systematic models and standardize the inventory map of earthquake-susceptible regions. Therefore, this paper reviews different approaches, which are organized and discussed on various models primarily used to create an earthquake scenario focusing on hazard and risk assessment. The reviews are divided into two major parts. The first part is the basic principles, data, and the methodology of various models used for seismic hazard and risk assessment. In the second part, a comparative analysis in terms of the limitations and strengths of the models, as well as application variability is presented. Furthermore, the paper includes the descriptions of software, data resources, and major conclusions. The main findings of this review explain that the capability of machine learning techniques regularly enhances the state of earthquake research, which will provide research opportunities in the future. The model suitability depends on the improvement of parameters, data, and methods that could help to prevent future risk. This paper will help researchers further understand the models based on their strengths, limitations, and applicability.

ACS Style

Ratiranjan Jena; Biswajeet Pradhan; Ghassan Beydoun; Abdullah Al-Amri; Hizir Sofyan. Seismic hazard and risk assessment: a review of state-of-the-art traditional and GIS models. Arabian Journal of Geosciences 2020, 13, 50 .

AMA Style

Ratiranjan Jena, Biswajeet Pradhan, Ghassan Beydoun, Abdullah Al-Amri, Hizir Sofyan. Seismic hazard and risk assessment: a review of state-of-the-art traditional and GIS models. Arabian Journal of Geosciences. 2020; 13 (2):50.

Chicago/Turabian Style

Ratiranjan Jena; Biswajeet Pradhan; Ghassan Beydoun; Abdullah Al-Amri; Hizir Sofyan. 2020. "Seismic hazard and risk assessment: a review of state-of-the-art traditional and GIS models." Arabian Journal of Geosciences 13, no. 2: 50.

Article
Published: 02 January 2020 in Information Systems Frontiers
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Transport infrastructure systems are very complex and expensive. Projects to procure such systems are costly, long and complex to manage. The procurement context usually includes many collaborating organizations but often with different concerns and priorities, and many interactions to other parties. This makes the procurement very complex and entangled. DoDAF, MoDAF and TRAK are three architecture frameworks (AF) that model the whole enterprise/system life cycle that includes system procurement. They are expressed as metamodels. In this paper, we analyse various procurements strategies and identify the concerns that AFs should address. The TRAK AF is then applied to a Rail procurement case study in collaboration with Transport for New South Wales (NSW) in Australia to assess its effectiveness in meeting the procurement needs. In all stages of the study, TRAK is mapped and compared to DoDAF and MoDAF to examine whether DoDAF or MoDAF can cover the inadequacies of TRAK. This paper shows that there is a considerable number of procurement needs which are overlooked by these architecture frameworks. It proposes a metamodel driven expansion to these frameworks to improve their completeness and expressiveness.

ACS Style

Farid Shirvani; Ghassan Beydoun; Pascal Perez; William Scott; Peter Campbell. An Architecture Framework Approach for Complex Transport Projects. Information Systems Frontiers 2020, 23, 575 -595.

AMA Style

Farid Shirvani, Ghassan Beydoun, Pascal Perez, William Scott, Peter Campbell. An Architecture Framework Approach for Complex Transport Projects. Information Systems Frontiers. 2020; 23 (3):575-595.

Chicago/Turabian Style

Farid Shirvani; Ghassan Beydoun; Pascal Perez; William Scott; Peter Campbell. 2020. "An Architecture Framework Approach for Complex Transport Projects." Information Systems Frontiers 23, no. 3: 575-595.

Article
Published: 23 October 2019 in World Wide Web
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The soaring development of Web technologies and mobile devices has blurred time-space boundaries of people’s daily activities. Such development together with the life-long learning requirement give birth to a new learning style, micro learning. Micro learning aims to effectively utilize learners’ fragmented time to carry out personalized learning activities through online education resources. The whole workflow of a micro learning system can be separated into three processing stages: micro learning material generation, learning materials annotation and personalized learning materials delivery. Our micro learning framework is firstly introduced in this paper from a higher perspective. Then we will review representative segmentation and annotation strategies in the e-learning domain. As the core part of the micro learning service, we further investigate several the state-of-the-art recommendation strategies, such as soft computing, transfer learning, reinforcement learning, and context-aware techniques. From a research contribution perspective, this paper serves as a basis to depict and understand the challenges in the data sources and data mining for the research of micro learning.

ACS Style

Jiayin Lin; Geng Sun; Tingru Cui; Jun Shen; Dongming Xu; Ghassan Beydoun; Ping Yu; David Pritchard; Li Li; Shiping Chen. From ideal to reality: segmentation, annotation, and recommendation, the vital trajectory of intelligent micro learning. World Wide Web 2019, 23, 1747 -1767.

AMA Style

Jiayin Lin, Geng Sun, Tingru Cui, Jun Shen, Dongming Xu, Ghassan Beydoun, Ping Yu, David Pritchard, Li Li, Shiping Chen. From ideal to reality: segmentation, annotation, and recommendation, the vital trajectory of intelligent micro learning. World Wide Web. 2019; 23 (3):1747-1767.

Chicago/Turabian Style

Jiayin Lin; Geng Sun; Tingru Cui; Jun Shen; Dongming Xu; Ghassan Beydoun; Ping Yu; David Pritchard; Li Li; Shiping Chen. 2019. "From ideal to reality: segmentation, annotation, and recommendation, the vital trajectory of intelligent micro learning." World Wide Web 23, no. 3: 1747-1767.

Journal article
Published: 23 July 2019 in Geoscience Frontiers
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Catastrophic natural hazards, such as earthquake, pose serious threats to properties and human lives in urban areas. Therefore, earthquake risk assessment (ERA) is indispensable in disaster management. ERA is an integration of the extent of probability and vulnerability of assets. This study develops an integrated model by using the artificial neural network–analytic hierarchy process (ANN–AHP) model for constructing the ERA map. The aim of the study is to quantify urban population risk that may be caused by impending earthquakes. The model is applied to the city of Banda Aceh in Indonesia, a seismically active zone of Aceh province frequently affected by devastating earthquakes. ANN is used for probability mapping, whereas AHP is used to assess urban vulnerability after the hazard map is created with the aid of earthquake intensity variation thematic layering. The risk map is subsequently created by combining the probability, hazard, and vulnerability maps. Then, the risk levels of various zones are obtained. The validation process reveals that the proposed model can map the earthquake probability based on historical events with an accuracy of 84%. Furthermore, results show that the central and southeastern regions of the city have moderate to very high risk classifications, whereas the other parts of the city fall under low to very low earthquake risk classifications. The findings of this research are useful for government agencies and decision makers, particularly in estimating risk dimensions in urban areas and for the future studies to project the preparedness strategies for Banda Aceh.

ACS Style

Ratiranjan Jena; Biswajeet Pradhan; Ghassan Beydoun; Nizamuddin Nizamuddin; Ardiansyah; Hizir Sofyan; Muzailin Affan. Integrated model for earthquake risk assessment using neural network and analytic hierarchy process: Aceh province, Indonesia. Geoscience Frontiers 2019, 11, 613 -634.

AMA Style

Ratiranjan Jena, Biswajeet Pradhan, Ghassan Beydoun, Nizamuddin Nizamuddin, Ardiansyah, Hizir Sofyan, Muzailin Affan. Integrated model for earthquake risk assessment using neural network and analytic hierarchy process: Aceh province, Indonesia. Geoscience Frontiers. 2019; 11 (2):613-634.

Chicago/Turabian Style

Ratiranjan Jena; Biswajeet Pradhan; Ghassan Beydoun; Nizamuddin Nizamuddin; Ardiansyah; Hizir Sofyan; Muzailin Affan. 2019. "Integrated model for earthquake risk assessment using neural network and analytic hierarchy process: Aceh province, Indonesia." Geoscience Frontiers 11, no. 2: 613-634.

Original article
Published: 11 July 2019 in Complex & Intelligent Systems
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The process of assessing the suitability of reuse of a software component is complex. Indeed, software systems are typically developed as an assembly of existing components. The complexity of the assessment process is due to lack of clarity on how to compare the cost of adaptation of an existing component versus the cost of developing it from scratch. Indeed, often pursuit of reuse can lead to excessive rework and adaptation, or developing suites of components that often get neglected. This paper is an important step towards modelling the complex reuse assessment process. To assess the success factors that can underpin reuse, we analyze the cognitive factors that belie developers’ behavior during their decision-making when attempting to reuse. This analysis is the first building block of a broader aim to synthesize a framework to institute activities during the software development lifecycle to support reuse.

ACS Style

Ghassan Beydoun; Achim Hoffmann; Rafael Valencia Garcia; Jun Shen; Asif Gill. Towards an assessment framework of reuse: a knowledge-level analysis approach. Complex & Intelligent Systems 2019, 6, 87 -95.

AMA Style

Ghassan Beydoun, Achim Hoffmann, Rafael Valencia Garcia, Jun Shen, Asif Gill. Towards an assessment framework of reuse: a knowledge-level analysis approach. Complex & Intelligent Systems. 2019; 6 (1):87-95.

Chicago/Turabian Style

Ghassan Beydoun; Achim Hoffmann; Rafael Valencia Garcia; Jun Shen; Asif Gill. 2019. "Towards an assessment framework of reuse: a knowledge-level analysis approach." Complex & Intelligent Systems 6, no. 1: 87-95.

Journal article
Published: 23 June 2019 in Information Sciences
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Substantial difficulties in adopting cloud services are often encountered during upgrades of existing software systems. A reliable early stage analysis can facilitate an informed decision process of moving systems to cloud platforms. It can also mitigate risks against system quality goals. Towards this, we propose an interactive goal reasoning approach which is supported by a probabilistic layer for the precise analysis of cloud migration risks to improve the reliability of risk control. The approach is illustrated using a commercial scenario of integrating a digital document processing system to Microsoft Azure cloud platform.

ACS Style

Mahdi Fahmideh; Ghassan Beydoun; Graham Low. Experiential probabilistic assessment of cloud services. Information Sciences 2019, 502, 510 -524.

AMA Style

Mahdi Fahmideh, Ghassan Beydoun, Graham Low. Experiential probabilistic assessment of cloud services. Information Sciences. 2019; 502 ():510-524.

Chicago/Turabian Style

Mahdi Fahmideh; Ghassan Beydoun; Graham Low. 2019. "Experiential probabilistic assessment of cloud services." Information Sciences 502, no. : 510-524.

Conference paper
Published: 19 June 2019 in Transactions on Petri Nets and Other Models of Concurrency XV
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With the development of data mining and machine learning techniques, data-driven based technology-enhanced learning (TEL) has drawn wider attention. Researchers aim to use established or novel computational methods to solve educational problems in the ‘big data’ era. However, the readiness of data appears to be the bottleneck of the TEL development and very little research focuses on investigating the data scarcity and inappropriateness in the TEL research. This paper is investigating an emerging research topic in the TEL domain, namely micro learning. Micro learning consists of various technical themes that have been widely studied in the TEL research field. In this paper, we firstly propose a micro learning system, which includes recommendation, segmentation, annotation, and several learning-related prediction and analysis modules. For each module of the system, this paper reviews representative literature and discusses the data sources used in these studies to pinpoint their current problems and shortcomings, which might be debacles for more effective research outcomes. Accordingly, the data requirements and challenges for learning analytics in micro learning are also investigated. From a research contribution perspective, this paper serves as a basis to depict and understand the current status of the readiness of data sources for the research of micro learning.

ACS Style

Jiayin Lin; Geng Sun; Jun Shen; Tingru Cui; Ping Yu; Dongming Xu; Li Li; Ghassan Beydoun. Towards the Readiness of Learning Analytics Data for Micro Learning. Transactions on Petri Nets and Other Models of Concurrency XV 2019, 66 -76.

AMA Style

Jiayin Lin, Geng Sun, Jun Shen, Tingru Cui, Ping Yu, Dongming Xu, Li Li, Ghassan Beydoun. Towards the Readiness of Learning Analytics Data for Micro Learning. Transactions on Petri Nets and Other Models of Concurrency XV. 2019; ():66-76.

Chicago/Turabian Style

Jiayin Lin; Geng Sun; Jun Shen; Tingru Cui; Ping Yu; Dongming Xu; Li Li; Ghassan Beydoun. 2019. "Towards the Readiness of Learning Analytics Data for Micro Learning." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 66-76.

Conference paper
Published: 08 June 2019 in Transactions on Petri Nets and Other Models of Concurrency XV
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As the result of the intense research activity of the past decade, Semantic Web technology has achieved a notable popularity and maturity. This technology is leading the evolution of the Web via interoperability by providing structured metadata. Because of the adoption of rich data models on a large scale to support the representation of complex relationships among concepts and automatic reasoning, the computational performance of ontology-based systems can significantly vary. In the evaluation of such a performance, a number of critical factors should be considered. Within this paper, we provide an empirical framework that yields an extensive analysis of the computational performance of ontology-based systems. The analysis can be seen as a decision tool in managing the constraints of representational requirements versus reasoning performance. Our approach adopts synthetic ontologies characterised by an increasing level of complexity up to OWL 2 DL. The benefits and the limitations of this approach are discussed in the paper.

ACS Style

Salvatore F. Pileggi; Fabian C. Peña; Maria Del Pilar Villamil; Ghassan Beydoun. Analysing the Trade-Off Between Computational Performance and Representation Richness in Ontology-Based Systems. Transactions on Petri Nets and Other Models of Concurrency XV 2019, 237 -250.

AMA Style

Salvatore F. Pileggi, Fabian C. Peña, Maria Del Pilar Villamil, Ghassan Beydoun. Analysing the Trade-Off Between Computational Performance and Representation Richness in Ontology-Based Systems. Transactions on Petri Nets and Other Models of Concurrency XV. 2019; ():237-250.

Chicago/Turabian Style

Salvatore F. Pileggi; Fabian C. Peña; Maria Del Pilar Villamil; Ghassan Beydoun. 2019. "Analysing the Trade-Off Between Computational Performance and Representation Richness in Ontology-Based Systems." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 237-250.